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Investigating the effect of FLT3 tyrosine kinase inhibitors and anti-FLT3 antibody-based therapy in acute myeloid leukemia
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Investigating the effect of FLT3 tyrosine kinase inhibitors and anti-FLT3 antibody-based therapy in acute myeloid leukemia
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Content
Investigating the effect of FLT3 tyrosine kinase inhibitors and
anti-FLT3 antibody-based therapy
in acute myeloid leukemia
By
Sandra Erere-Nwa Onyemaechi
A Thesis Presented to the
FACULTY OF THE USC SCHOOL OF PHARMACY
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(PHARMACEUTICAL SCIENCES)
August 2022
Copyright 2022 Sandra Erere-Nwa Onyemaechi
ii
Acknowledgments
I thank God almighty for giving me the grace and wisdom to pull through this program. I am
extremely grateful to everyone involved in my life who played an incredible path in my journey. I
would first like to express my deepest gratitude and appreciation to my advisor, Dr. Houda
Alachkar for her guidance, inspiration, and insight which made this work possible. You played an
immersed role in propelling me as an individual and your passion for science is what motivates
me to strive to be a better scientist. I appreciate my committee members Dr. Okamoto, Dr. Zhang,
and Dr. Mackay for their insightful contributions to my thesis.
I would like to thank my mentor Atham, who made my graduate school experience fun and
memorable. Each day you continue to make me a better scientist and I am grateful. Thanks for
encouraging me to pursue my Ph.D. and motivating me with your enthusiasm. Thanks for teaching,
supporting, believing in me, and wishing the best for me. To the rest of my wonderful lab members,
Ritu, Jeremy, Yang, Ophelia, Amani, and Tina. I would like to thank you all for your support
throughout this process. I am fortunate to be a part of this amazing group as you all made my
experience in the lab worth the journey. To my dearest friends Josephine, Kimia, Gagan, Kaday,
and peace, I am blessed to have you guys in my life.
Finally, to my amazing and extremely supportive family: My mom, dad, Uncle (Ediom Ogah),
Aunty (Maureen Ogah), and siblings: Kester, Clara, Elyse, Merete, Precious, and Emery, words
are not enough to express my deepest appreciation. Thank you all for setting the bar so high,
providing me the resources needed to succeed, for the sacrifices you make, and for being my
number one support system. I was able to pull through and still aiming high because of your
continuous love and support. I love you all.
iii
Table of Contents
Acknowledgments ii
List of Tables v
List of Figures vi
Abbreviations viii
Abstract ix
Chapter 1: Introduction 1
1.1 Acute Myeloid Leukemia 1
1.1.1 Epidemiology of AML ................................................................................................... 1
1.1.2 Disease etiology and pathophysiology ........................................................................... 4
1.1.3 Diagnosis ........................................................................................................................ 5
1.1.4 AML Classification Schemes ......................................................................................... 8
1.1.5 The Genomic landscape of AML ................................................................................. 11
1.1.6 Prognostic factors ......................................................................................................... 13
1.1.7 Standard Treatment for AML ....................................................................................... 19
1.1.8 Targeted therapy in AML ............................................................................................. 22
1.1.9 Supportive care ............................................................................................................. 24
1.2 FMS-like tyrosine kinase 3 (FLT3) 24
1.2.1 Overview of FLT3 gene ................................................................................................ 24
1.2.2 FLT3 activation and signaling pathways ...................................................................... 26
1.2.3 Mutations in FLT3 gene ............................................................................................... 28
1.2.4 Glycosylation status in FLT3 receptor mutations ........................................................ 30
1.2.5 FLT3 Tyrosine kinase inhibitors .................................................................................. 34
1.2.6 Resistance in FLT3 target therapies ............................................................................. 37
1.3 Research Hypothesis/Experimental Design 42
Chapter 2: Materials and Method 44
2.1 Cell line and cell culture 44
2.2 Treatment with Tyrosine kinase inhibitors 44
2.3 FLT3-single-chain variable fragment (scFv) 45
2.4 Measurement of FLT3 surface expression level 46
iv
2.5 Measurement of FLT3-scFv binding in AML cell line 46
2.6 Cell proliferation and viability assays 47
2.6.1 CCK-8 cell viability assay ............................................................................................ 47
2.6.2 Trypan blue cell viability assay .................................................................................... 48
2.7 Apoptosis assay 48
2.8 Statistical analysis 48
Chapter 3: Results 50
3.1 FLT3 tyrosine kinase inhibitors upregulate FLT3 surface expression 50
3.2 The effect of FLT3-TKIs treatment on anti-FLT3-scFv binding to FLT3 positive cells 54
3.3 FLT3 inhibitors enhance the anti-leukemic activity of α-FLT3-scFv in FLT3-ITD positive
AML 58
3.4 FLT3 inhibitors and anti-FLT3-scFv induce apoptosis of FLT3-ITD cells 62
Chapter 4: Discussion 69
References 78
v
List of Tables
Table 1: WHO AML Classification Scheme ................................................................................ 10
Table 2: Commonly mutated genes in AML ................................................................................ 12
Table 3: AML is categorized into three prognostic groups .......................................................... 16
Table 4: The 2017 ELN prognosis classification .......................................................................... 18
vi
List of Figures
Figure 1: Impact of age at diagnosis .............................................................................................. 2
Figure 2: AML incidence by age and gender .................................................................................. 3
Figure 3: Representation of common AML genetic mutations ................................................... 12
Figure 4: The estimated overall survival rate after 2 and 5 years of initial diagnosis ................. 15
Figure 5: Structure of FLT3 receptor ............................................................................................ 27
Figure 6: Binding conformation state of FLT3 receptor. .............................................................. 36
Figure 7: Illustration of thesis rationale ........................................................................................ 43
Figure 8: AML cell lines response after treatment with FLT3 Tyrosine kinase inhibitors .......... 52
Figure 9: Quantified response after treatment with FLT3 inhibitors . .......................................... 53
Figure 10: FLT3-WT response after treatment with FLT3 inhibitors .......................................... 54
Figure 11: Binding signals of anti-His tag secondary antibody to FLT3-scFv at different
concentrations in the presence or absence of TKIs ....................................................................... 56
Figure 12: Quantified binding signals of anti-His tag secondary antibody to FLT3-scFv in the
presence or absence of TKIs ......................................................................................................... 57
Figure 13: Effect of dual treatment with α-FLT3-scFv and FLT3-inhibitors on FLT3-ITD
positive cell proliferation .............................................................................................................. 60
Figure 14: Antileukemic activity of α-FLT3-scFV and FLT3-inhibitors dual treatment in AML
cells ............................................................................................................................................... 61
Figure 15: Apoptosis of FLT3-ITD positive cell after dual treatment with α-FLT3-scFv and
midostaurin at 48 hours ................................................................................................................. 64
Figure 16: Apoptosis of FLT3-ITD positive cell after dual treatment with α-FLT3-scFv and
midostaurin at 72 hours ................................................................................................................ 65
vii
Figure 17: Dual treatment with α-FLT3-scFv and quizartinib induces apoptosis in FLT3-ITD
positive cells at 48 hours ............................................................................................................... 66
Figure 18: Dual treatment with α-FLT3-scFv and quizartinib induces apoptosis in FLT3-ITD
positive cells at 72 hours ............................................................................................................... 67
Figure 19: Quantified antileukemic activity of α-FLT3-scFv and FLT3-inhibitors dual treatment
in AML cells ................................................................................................................................. 68
viii
Abbreviations
AML, Acute Myeloid Leukemia; ANOVA, Analysis of Variance; ATP, Adenosine
Triphosphate; DMEM, Dulbecco Modified Eagle Medium; ELN, European Leukemia Net; FAB,
French-American-British Classification; FBS, Fetal Bovine Serum; FDA, Food and Drug
Administration; FLT3, FMS like Tyrosine Kinase-3; FL, FLT3 Ligand; HSC, Haematopoietic
stem cell; ITD, Internal Tandem Duplications; JMD, Juxtamembrane domain; MCL-1, Myeloid
cell leukemia; MEK, MAPK/ERK Kinase; STAT5, signal transducer and activator of
transcription 5; TKI, Tyrosine Kinase Inhibitor; WHO, World Health Organization; FLT3-WT,
Wild type FLT3.
ix
Abstract
Acute Myeloid leukemia (AML) is a hematological disorder characterized by clonal expansion
and proliferation of undifferentiated myeloid cells. Mutations in the FMS-like tyrosine kinase
(FLT3) gene are present in 25-30% of AML cases. FLT3-(ITD internal tandem duplicate) is
characterized as a 15-150 base pair insertion resulting in conformational changes in the
juxtamembrane domain of the FLT3 receptor. FLT3-ITD is the most frequent mutation in AML
mutation and is associated with poor prognosis and leukocytosis. FLT3 mutations result in
constitutive activation of the FLT3 kinases activity and activation of downstream signaling
pathways leading to increased proliferation and resistance to apoptosis. Several FLT3 small
molecule inhibitors have been developed and some have been FDA approved (midostaurin and
gilteritinib) for the treatment of patients with AML. Yet, even with these targeted therapies, the
majority of patients with FLT3 mutations die of their disease as the 5-year overall survival rate is
still relatively low. Since FLT3-ITD is mainly expressed in the intracellular compartment of the
cells with little expression detected on the cell surface, it has been demonstrated that treating these
FLT3-ITD positive cells with small molecules, inactivating point mutations, or co-expression with
other protein tyrosine phosphatases (PTPs) promotes complex glycosylation and surface
localization of these receptors (Schmidt-Arras et al., 2005). By leveraging this mechanism, my
research aims to promote cell surface localization of FLT3-ITD using FLT3-Tyrosine kinase
inhibitors (TKIs) and the subsequent introduction of our in-house anti-FLT3-scFv to enhance
efficacy and reduce cell viability in FLT3-ITD positive AML cell lines. Collectively, our result
confirms that FLT3 inhibitors promote cell surface expression of FLT3 in FLT3 mutated cells but
not in FLT3-WT cells. In addition, we show that dual treatments of FLT3 inhibitors with anti-
FLT3-scFv significantly reduced cell viability in these cells when compared with either treatment
x
alone. Taken together, our current findings suggest combining FLT3 inhibitors with antibody-
based therapy has the potential to enhance the efficacy of FLT3-TKIs in the treatment of FLT3-
ITD positive leukemic cells. To further validate this in-vitro study, in-vivo studies will be needed
to show the therapeutic potential of the combination of FLT3-inhibitors with FLT3-directed
antibody treatment against FLT3-ITD driven AML in preclinical models.
1
Chapter 1: Introduction
1.1 Acute Myeloid Leukemia
Acute myeloid leukemia (AML) is a blood cancer that initiates in the bone marrow
characterized by differentiation arrest and clonal proliferation of the myeloid progenitor cells
which consequently accumulate in the blood and infiltrate the bone marrow and other organs
(Abuhelwa et al., 2017). Over proliferation reduces the ability of the cells to differentiate into their
mature form, thereby leading to the accumulation of immature cells or leukemic blasts in the bone
marrow and/or peripheral blood. Increased production of blast cells with reduced mature cells
leads to varieties of symptoms such as anemia (due to the decreased production of RBCs),
increased risk of infection (due to the decreased production of mature WBCs), and bleeding due
to reduced platelets. Over the years, AML has also been referred to as acute myelogenous leukemia
and acute nonlymphocytic leukemia.
1.1.1 Epidemiology of AML
Although AML is a rare disease accounting for only 1.1% of all cancer cases, it is still one
of the most common types of leukemia in adults (Key Statistics for Acute Myeloid Leukemia
(AML), n.d. and Acute Myeloid Leukemia - Cancer Stat Facts, n.d.). AML is the second most
frequent type of blood cancer in adults and children, accounting for approximately 33% of all
leukemias in the United States (Chen et al., 2017). It is responsible for around 80% of cases in the
adult population, with an annual incidence of over 20,000 cases in the United States (De
Kouchkovsky & Abdul-Hay, 2016). The American Society of Cancer estimates that 11,540 people
will die from AML by 2022, the majority of whom will be adults. The incidence of AML increases
with age as adults are more likely to be diagnosed than children, hence it is predominantly a disease
2
in older adults. AML is also diagnosed in children and younger patients; however, they have a
considerably lower incidence. According to the Surveillance, Epidemiology, and End Results
(SEER) database, the incidence of AML in adults 65 and older compared to younger patients is
20.1 and 2.0 cases per 100,000, respectively. AML is more typically diagnosed in adults aged 65
to 74, with the median age of diagnosis being 68 years (Acute Myeloid Leukemia - Cancer Stat
Facts, n.d.). Nonetheless, the average age for diagnosing AML differs across various countries.
For example, in countries like the United Kingdom and Canada, the average age of diagnosis
ranges from 63-71 years and around age 40-45 years in countries like Brazil, India, and Algeria
(Shallis et al., 2019).
Figure 1: Impact of age at diagnosis - Incidence of patients diagnosed with AML in the USA at various ages over a 5-year
period (2011-2016) (Shallis et al., 2019).
3
The prevalence of AML differs among ethnicities with Caucasians and African Americans
having a lower incidence of AML with either the t(8;21) or inv(16) chromosomal translocation
(Shallis et al., 2019). Higher incidence of acute promyelocytic leukemia (APL) occurs more
frequently in the Hispanic population (Douer et al., 1996 as cited in Shallis et al., 2019). A
population-based study performed in some countries including the United States shows that males
are 1.2 - 1.6 times more likely to develop AML than females (Shallis et al., 2019). Therefore,
gender can be considered when grouping the incidence of AML as males tend to have a higher risk
compared to females.
Figure 2: AML incidence by age and gender - Incidence of patients diagnosed with AML in the USA by age and gender over a
5-year period (2011-2016) (Shallis et al., 2019).
4
1.1.2 Disease etiology and pathophysiology
AML is a heterogeneous malignancy characterized by highly diverse genetic and
epigenetic abnormalities (Yu et al., 2017). Depending on the onset of the disease, AML is
categorized into two subtypes namely de novo and secondary disorder. It is referred to as de novo
when the diagnosed patient has no prior clinical history of myelodysplastic syndrome (MDS),
myeloproliferative disorder (MPD), or exposure to leukemogenic therapies or agents (Cheson et
al., 2003). Secondary AML develops from DNA damage caused by prior exposure to
chemotherapy or radiotherapy (therapy-related AML), toxic exposure, or other hematological
malignancy such as MDS or MPD (Villela & Bolaños-Meade, 2011). Polycythemia Vera (PV) is
one medical condition with a higher risk factor of progressing into AML after treatment. Study
shows that within a 10-year period about 2-14% of cases of patients with PV develop AML
(Cerquozzi & Tefferi, 2015). The majority of AML cases in previously healthy people develop as
de novo malignancies. There are approximately 10-30% of secondary AML cases, and about 7-
15% of these cases are classed as therapy-related AML (Leone et al., 1999). Undiagnosed MDS
accounts for most patients with this disease, making it difficult to assess the proportion of
secondary AML cases.
Irrespective of the etiology of AML, the pathogenesis of this disease requires abnormal
proliferation and differentiation of myeloid cells (De Kouchkovsky & Abdul-Hay, 2016).
Chimeric proteins such as RUNX1- RUNX1T1 and PML-RARA, which disrupt the normal
maturation process of myeloid precursor cells, are formed due to chromosomal translocation such
as t(8:21) in core-binding factor AML (CBF-AML) or t (15:17) in acute promyelocytic leukemia
(APL) respectively (De Kouchkovsky & Abdul-Hay, 2016). Genetic mutations were identified in
greater than 97% of AML cases and often happen in the absence of any large chromosomal
5
abnormality (De Kouchkovsky & Abdul-Hay, 2016). Early preclinical studies using mice models
led to the development of two-hit models of leukemogenesis, namely class I and class II mutations,
that are used to classify the various mutations related to AML (De Kouchkovsky & Abdul-Hay,
2016). Based on these early preclinical studies, class I mutations such as FLT3 internal tandem
duplications (ITD) and tyrosine kinase domain mutations (FLT3-TKD), K/NRAS, and c-KIT result
in the activation of pro-proliferative pathways and this must occur in conjunction with class II
mutations which alter the normal hematopoietic differentiation process. Approximately 28% of
the cases that arise from class I mutations are FLT3-ITD/TKD, with 12% being from K/NRAS.
About 8% and 4% of the case arises from mutations in TP53 and c-KIT, respectively (De
Kouchkovsky & Abdul-Hay, 2016). Mutations involving NPM1 and CEBPA are categorized under
class II mutations. However, recent advances in the genomic landscape led to a better
understanding of AML mutations involving different classes of genes. Approximately, 40% of
AML cases develop from a mutation in DNA methylated genes such as DNMT3A, TET2, and IDH-
½ (Isocitrate dehydrogenase) (De Kouchkovsky & Abdul-Hay, 2016). The genomic landscape of
AML will be discussed in a later section.
1.1.3 Diagnosis
Diagnosing AML is traditionally done based on the cell morphology, immunophenotyping,
histology, Fluorescence In Situ Hybridization (FISH), and cytogenetic. Recent advancement in
technology is slowly expanding the field of molecular testing as a common diagnostic approach.
However, due to a potential gene-gene interaction and cellular heterogeneity, researchers are
exploring more genetic approaches to successfully diagnose AML (Yu et al., 2017). As discussed
previously, WHO requires >20% of blasts observed in the bone marrow or peripheral blood to be
6
classified as acute leukemia when looking at the cell morphology. Auer rods are present in most
AML; however, some lack Auer rods, therefore, their presence is not essential for diagnosis.
Regardless of the blast percentage, it has been observed that the presence of extramedullary tissue
infiltrates, or a documented t(8;21), inv(16), or t(15;17) in clinical settings is diagnostic for AML
(De Kouchkovsky & Abdul-Hay, 2016). The treatment for Acute promyelocytic Leukemia (APL);
(AML with t(15;17) (q22;q12); PML-RARA) is different from all other types of AML and so it is
important to accurately diagnose patients. In APL, cell differentiation is blocked at the
promyelocytic stage. Microscopic examination presents abnormal hypergranular promyeloid,
some Auer rods butterfly or coin-on-coin nucleus appearance. DIC following death can occur
within hours due to the release of primary granules. In AML with t(9:11), cells may show
pseudopods as they can be motile. Blast cells are observed in the peripheral blood with large
abundant cytoplasm and fine nuclear chromatin, and they may present with granules and or
vacuoles. Stains such as myeloperoxidase (MPO) or Sudan black B (SBB) and alpha-naphthyl
esterase (also known as nonspecific esterase; NSE) can demonstrate the myeloid origin of these
cells and are hence further used to diagnose AML (Döhner et al., 2010).
Immunophenotyping is
another commonly used approach in diagnosing AML. It identifies the types of markers or antigens
that are present on a cell surface. Newly diagnosed acute leukemia is usually indicated using flow
cytometry to identify these specific markers such as CD33 or cytoplasmic myeloperoxidase
(cMPO) present on granulocytes (Döhner et al., 2010). To diagnose AML with minimal
differentiation, acute megakaryoblastic leukemia, and leukemia of ambiguous lineages,
immunophenotyping is essential as AML with minimal differentiation shows no morphologic or
cytochemical changes (Döhner et al., 2010).
7
Conventional and molecular cytogenetics are other approaches used to detect AML. When
a patient is suspected of having acute leukemia, conventional cytogenetics analysis is a major
component required for diagnosis. This assessment detects chromosomal abnormalities in about
55% of adults with AML (Döhner et al., 2010). Another advantage is that the conventional
cytogenetic analysis alone is a sufficient approach used to establish the WHO diagnosis of AML
with myelodysplasia-related features when 20% of blasts are observed in blood smears. In
addition, this can also detect the chromosomal changes that are observed in the different categories
of AML with recurrent genetic abnormalities (Döhner et al., 2010). FISH is a form of molecular
cytogenetic approach used to detect gene rearrangements such as RUNX1-RUNX1T1, CBFB-
MYH11, MLL, and EVI1 gene fusions, as well as 5q and 7q chromosomal deletions (Döhner et al.,
2010). FISH combines molecular approaches with karyotyping to detect more subtle anomalies
such as inv(16) and t(11q23) in newly diagnosed individuals with t(8;21) translocation (Fröhling
et al., 2002). Patients who present poor chromosomal morphology with little or no metaphase cells
benefit from molecular diagnostic methods (Fröhling et al., 2002). Molecular diagnostic
approaches are beneficial to patients who have poor chromosomal morphology and few or no
metaphase cells (Fröhling et al., 2002).
An additional diagnostic approach for AML is molecular genetics. Reverse transcriptase-
polymerase chain reaction (RT-PCR) is a type of molecular diagnostic technique used to identify
recurring gene fusions such as RUNX1-RUNX1T1, CBFB-MYH11, MLLT3-MLL, and DEK-
NUP21 (Döhner et al., 2010). In genes such as the NPM1, FLT3, KIT, and CEBPA, molecular
diagnostic techniques are valuable in identifying the acquired somatic mutation they possess
(Döhner et al., 2010).
More recently the use of genome-wide sequencing is gradually evolving as
a diagnostic method for leukemia. In addition to the AML diagnostic tests, other tests routinely
8
performed in the laboratory includes serum pregnancy test, complete cell count and peripheral
blood smear, biobanking, coagulation test, urinalysis, viral testing such as HIV, HBV, HCV, HAV,
performance status, analysis of comorbidity, patient demographic and medical history (Döhner et
al., 2010).
1.1.4 AML Classification Schemes
In 1976, a group of French-American, and British physicians devised a classification
scheme for AML based on cell morphologic characteristics and special staining. Using the French
American-British (FAB) classification system, >30% of blast in the peripheral blood (PB)
indicates Acute Leukemia, while <30% of blast cells in the PB signifies MDS or MPD. AML is
grouped into eight subtypes categorized from M0 (the undifferentiated acute myeloblastic
leukemia) through M7(Acute megakaryoblastic leukemia) based on the type of cell lineage the
leukemia differentiation from or the microscopic morphology of the cell (Abuhelwa et al., 2017).
Subtypes categorized as M0 through M5 start from the early stage (immature forms) of WBCs,
while M6 is the immature form of RBCs, and M7 is the immature form of cells responsible for
platelet production. The FAB classification system can be helpful; however, it fails to consider
many other factors that may affect the prognosis and management of AML.
To advance the diagnosis and management of AML, the World Health Organization
(WHO) introduced a new classification scheme in 2001, and this has been revised over the years
as research in this field continues to evolve. This classification scheme is based on cell lineage,
cell morphology, immunophenotyping, genetic features, and clinical syndrome. Under the WHO
classification scheme 20% of blast cells are required to be diagnosed as acute leukemia. The WHO
classification scheme is the most recent and it is currently used to categorize AML. The 2008
9
WHO revision introduced two new provisional entities of AML with mutated NPM1 and CEBPA
genes known as “AML with mutated NPM1 [nucleophosmin (nucleolar phosphoprotein B23,
numatrin)],” and “AML with mutated CEBPA [CCAAT/enhancer-binding protein (C/EBP),
alpha].” Current research shows rising evidence that these two provisional entities represent
primary genetic lesions also known as class II gene mutations which therefore impair
hematopoietic differentiation (Döhner et al., 2010). Mutation in BCR-ABL1 and RUNXI were later
introduced in the 2016 revision (De Kouchkovsky & Abdul-Hay, 2016). The 2016 revision of
WHO classification scheme specified AML into six disease entities: AML with recurrent genetic
abnormalities; AML with myelodysplasia-related features; therapy-related AML; AML not
otherwise specified; myeloid sarcoma; and myeloid proliferation related to Down Syndrome (De
Kouchkovsky & Abdul-Hay, 2016). Subtypes of AML are further categorized under AML with
recurrent genetic abnormalities as shown in Table 1.1. AML with t(8;21)(q22;122);
RUNX1/RUNX1T1 are mostly seen in children and adults. Occurrence of myelodysplasia-related
cytogenetic abnormalities such as monosomy 5 or 7, and deletion 5q or 7q, along with the history
of MDS is important to identify cases of AML with myelodysplasia-related features (De
Kouchkovsky & Abdul-Hay, 2016). Multilineage dysplasia is frequent in AML patients presenting
with myelodysplastic-related changes (AML-MRC). Following WHO classification, AML-MRC
presents with ≥ 50% dysplastic cells in at least two hematopoietic lineages.
10
Table 1: WHO AML Classification Scheme (Döhner et al., 2010, and De Kouchkovsky & Abdul-Hay, 2016).
11
1.1.5 The Genomic landscape of AML
Recent studies investigating the cases of AML in patients found that it is common to have
more than one mutation concurrently occurring in the same patient (Hou & Tien, 2020). This
observation along with the use of whole-genome sequencing led to the finding that most leukemic
genes are infrequently mutated, with AML patients presenting with more than one driver mutation
(Papaemmanuil et al., 2016). Therefore, it is safe to say that the etiology of AML is influenced by
a complex interaction of genetic events which contributes to the pathogenesis of the disease in
different patients (
Papaemmanuil et al., 2016 and Ley et al., 2013). Accumulating reports from
several studies identified that over 95% of patients with AML have driving mutations and co-
concurring mutations irrespective of the presence of cytogenetic abnormalities (Papaemmanuil et
al., 2016; Bullinger et al., 2017; and Hou & Tien, 2020). These mutations are further categorized
into eight categories based on their biological function, which include the genes responsible for
myeloid transcription factor, signaling genes such as FLT3, NPM1, tumor suppressing genes,
genes involved in DNA methylation, splicing genes, chromatin modifier, and cohesin complex
(Hou & Tien, 2020).
The 2017 European Leukemia Net (ELN) is a risk classification scheme that encompasses
genomic changes as well as gene mutations and FLT3-ITD allelic ratio, hence it is the most widely
used AML prognostic scheme in the clinical setting as shown in Table 1.2 (Hou & Tien, 2020).
The bar chart shown in Figure 3 represents the common molecular gene mutation observed in a
subset of AML patients in Taiwan. It is important to note that the ELN classification schemes
suggest a more aggressive approach for patients in the adverse risk category (Hou & Tien, 2020).
12
Table 2: Commonly mutated genes in AML (Hou & Tien, 2020).
Figure 3: Representation of common AML genetic mutations - Bar chart showing the common genetic mutations observed in the
population of Taiwanese patients with AML (Hou & Tien, 2020).
13
In a study done to understand the genetic diversity that distinguishes the pathophysiology
of AML, they found in their population of AML patients that mutations in these genes tend to
occur concurrently with multiple clones coexisting at the same time (Papaemmanuil et al., 2016).
This means that the gene mutations observed were not exclusively isolated but rather the patients
had multiple mutations in genes which eventually developed into AML. Depending on the location
of the mutation, the frequency of mutation, and the genes mutated, the prognosis impact on the
patient can range from mild to adverse risk type. During their study, they observed that mutations
that occur in the tyrosine kinase receptor and RAS pathway genes usually occur late in the process,
and in some occasions may likely occur more than once in the same patient (Papaemmanuil et al.,
2016). They also found that mutation on the NPM1 gene typically occurs after mutation on
DNMT3A, IDH1, or NRAS genes, and hence the NPM1 mutation is categorized as a secondary
event in AML development (Papaemmanuil et al., 2016). Therefore, the data from their study
suggests that specific and ordered evolutionary trajectories are required for the development of
AML (Papaemmanuil et al., 2016).
1.1.6 Prognostic factors
AML prognosis is influenced by a number of factors, which vary substantially depending
on age and the type of AML identified. To appropriately manage AML, a comprehensive risk
evaluation is required, as physicians need some prognostic guidance when establishing treatment
plans for patients. The National Comprehensive Cancer Network (NCCN) guidelines have
grouped AML into various categories in terms of increased risk of resistance to treatment or
treatment-related mortality (TRM) (De Kouchkovsky & Abdul-Hay, 2016). Among many other
substantial risk factors, increased age and poor performance status are associated with lower rates
14
of complete remission (CR) and reduced overall survival (OS) (Kantarjian et al., 2006 and Shah
et al., 2013). While age and performance status are significant factors when determining the
prognosis of AML, other factors such as blood protein, bilirubin, creatinine, neutrophil count,
fibrinogen, hemoglobin levels, and the comorbidity of stem cell transplant can impact the increased
risk of TRM in older patients (Walter et al., 2011).
The prognosis of AML worsens with increased age (Walter et al., 2011). Upon diagnosis,
age significantly impacts the likelihood of long-term survival as shown in Figures 1.4 and 1.5
(Shallis et al., 2019).
Younger patients diagnosed with AML generally tend to have a good
prognosis and older patients commonly get a poorer prognosis which implies that there is an
unknown age-related factor affecting these outcomes (Döhner et al., 2010).
Studies show that
patients diagnosed with AML on or before 40 years of age generally have a higher overall 2-year
and 5-year survival rate of 66.9% and 58.2% respectively compared to patients diagnosed after 65
years of age (Shallis et al., 2019). As AML treatment remains challenging in older patients, data
from SEER (2000-2018) demonstrated a 5-year survival rate of 55.8 % for patients younger than
50 years old, 30.9% in patients between 50-64 years, and 7.1% in patients 65 and above (Acute
Myeloid Leukemia - Cancer Stat Facts, n.d.). The fact that older individuals are more likely to
have various comorbidities such as organ failure and a compromised immune system contributes
to the decrease in survival rate in this population (Kantarjian et al., 2021). In addition, older
individuals are more likely to have complicated AML karyotypes and genetic anomalies, as well
as a higher risk of treatment AML (Kantarjian et al., 2021), making treatment more challenging in
this population.
15
Figure 4: The estimated overall survival rate after 2 and 5 years of initial diagnosis within a 5-year period (2011- 2016)
(Shallis et al., 2019).
Although age is an important factor, this alone should not be used to determine the therapy
most beneficial to patients. Poor prognosis are common in AML patients with prior malignancy
and those with therapy-related AML (De Kouchkovsky & Abdul-Hay, 2016). While clinical
symptoms are used to properly manage therapy, cytogenetic changes make up a single prognostic
factor for CR and OS rate (De Kouchkovsky & Abdul-Hay, 2016). Genetic profiling has made it
possible for AML to be grouped into different prognosis categories such as favorable, intermediate,
and adverse risk-based groups (Estey, 2014), as shown in table 1.3. AML with recurrent genetic
abnormalities such as t(8;21), t(15;17) also known as CBF AML, and inv(16) usually have a
favorable prognosis with a 3-year overall survival of 66% in younger patients compared to 33% in
patients other than 60 years of age (De Kouchkovsky & Abdul-Hay, 2016). There is a significant
decrease in the OS rate and a high risk of relapse in patients who have c-KIT mutation along with
t(8;21) or inv(16) translocation compared to patients with intermediate-risk AML (De
Kouchkovsky & Abdul-Hay, 2016 and Döhner et al., 2010). Other chromosomal translocations
classified under AML with recurrent genetic abnormalities such as monosomy 5 or 7, t(6;9), inv(3),
16
or 11q changes are associated with a higher risk of treatment failure and death (De Kouchkovsky
& Abdul-Hay, 2016). In addition, AML with t(9;11) confers poor prognosis.
Table 3: AML is categorized into three prognostic groups (De Kouchkovsky & Abdul-Hay, 2016).
Patients diagnosed with AML associated with normal cytogenetic (CN-AML) usually
present with intermediate-risk prognosis while those with class II single mutations on NPM1 and
CEBPA gene indicate a better prognosis. About 40% of CN-AML patients diagnosed with NPM1
mutations will also have FMS like tyrosine kinase3- Internal tandem duplications (FLT3-ITD) and
this presents a poorer prognosis and lower CR and OS rate when compared to patients lacking
FLT3-ITD (Döhner et al., 2010).
In general, CN-AML patients with FLT3-ITD gene mutation
have a poorer prognosis compared to patients that lack this gene (Döhner et al., 2010).
On the
other hand, CN-AML patients with a mutation in CEBPA or a mutated NPM1 gene, but without
17
the FLT3 gene have been shown to have a favorable prognosis (Döhner et al., 2005). Regardless
of the original mutation observed, the presence of the FLT3 gene indicates a poor prognosis in
terms of managing AML. Study shows that NPM1 mutations in CN-AML patients are associated
with better CR rates, improved recurrence-free survival (RFS), and events-free survival (EFS)
(Döhner et al., 2010 and Döhner et al., 2005).
FLT3 mutations are seen in about 25-30% of newly
diagnosed AML patients with 25% presenting with the ITD and the other roughly 5% having TKD
mutations (Hou & Tien, 2020). Patients who have the FLT3-ITD mutation have a higher relapse
rate, a lower overall survival rate, and shorter disease-free survival (DFS) (Kottaridis et al., 2001).
Therefore, in the first CR, an early allogeneic hematopoietic stem cell transplant is recommended
for patients with FLT3-ITD mutations (Hou & Tien, 2020). So far, the prognostic impact of FLT3-
TKD is not clear, hence more research needs to be done in understanding this field. Table 1.4
Shows the ELN prognostic classification scheme. The heterogeneity among cases associated with
CEBPA mutation indicates that patients who have a double mutation, typically biallelic, have a
better prognosis (Döhner et al., 2010). There are questions as to whether the presence of the FLT3-
ITD gene impacts the prognostic factor in patients with mutated CEBPA gene. Studies show that
the prognostic impact of FLT3-ITD may depend on the presence of the biallelic mutations as poor
prognosis has been linked to patients with higher mutant to wild-type allelic ratios (Gale et al.,
2008). In addition, AML with mutated TP53 gene correlates with an unfavorable prognosis and
this can signify a single unfavorable genetic prognosis factor (Grossmann et al., 2012).
Furthermore, in roughly 50% of AML cases, increased STAT3 phosphorylation has been observed
and this confers adverse prognosis (Stevens et al., 2015).
18
Mutations in DNA-related genes are also essential in stratifying the prognostic factors for
AML. Studies show that a mutation in the DNA methyltransferases gene (DNMT3A) indicates an
adverse prognosis for OS and RFS. This is valid irrespective of the patient's age, whether the
patient presents a normal cytogenetics profile or has a high-risk genotype (Shivarov et al., 2013).
Furthermore, histone methyltransferase is encoded in KMT2A, and partial tandem duplication of
this gene signifies a worse prognosis in CN-AML patients (Grossmann et al., 2012).
Table 4: The 2017 ELN prognosis classification (Tyner et al., 2018)
19
1.1.7 Standard Treatment for AML
There is currently no standard treatment to cure AML. The primary therapeutic goal is to
sufficiently kill the leukemic cells to provide an effective response to therapy, thereby allowing
the patient to achieve complete remission (Villela & Bolaos-Meade, 2011). Various treatment
methods, such as chemotherapy, radiation, bone marrow transplant (BMT), or stem cell transplant
(SCT), are available as therapeutic options depending on the nature of the disease and the patient's
background. As part of the current standard care practice, it is required to measure the residual
disease in AML patients in complete remission (CR). The presence of measurable residual disease
(MRD) in CR patients implies a poor prognosis, with a greater relapse rate and a lower overall
survival rate (Jongen-Lavrencic et al., 2018 and Short et al., 2020). To achieve CR, eligible patients
first undergo induction therapy. It is recommended that patients under 60 years of age receive
intensive induction therapy, while older patients or those in the advanced risk group, those with
comorbidities, those with poor performance, and those with multi-drug resistant diseases should
receive less intensive treatment, such as hypomethylating agents (O'Donnell et al., 2017).
Induction therapy is a good approach, but the consequence of minimal residual disease continues
to be a threat in CR. Also, when treatment is discontinued, the patients are prone to relapse (De
Kouchkovsky & Abdul-Hay, 2016). To facilitate a satisfactory response to induction therapy, the
treatment should be followed by consolidation therapy as this can help eliminate any residual
disease and avoid relapse (De Kouchkovsky & Abdul-Hay, 2016).
20
Treatment options for consolidation therapy include chemotherapy and allogeneic
hematopoietic stem cell transplant (allo-HSCT). Studies suggest chemotherapy as the top choice
first-line consolidation treatment for patients with favorable prognosis. However, it is advisable to
weigh the risk of TRM against the risk of treatment failure or relapse when deciding on which
consolidation therapy is best for individual patients (De Kouchkovsky & Abdul-Hay, 2016).
Two
weeks after the initial treatment using induction therapy, the response rate should be evaluated
with a bone marrow aspirate and core biopsy (De Kouchkovsky & Abdul-Hay, 2016). Some
patients show cytological evidence of disease after the first round of standard therapy and hence
require reinduction with anthracycline combined with a second round of standard-dose cytarabine.
Cytarabine can be used alone in high doses or in combination with FLAG-1DA (De Kouchkovsky
& Abdul-Hay, 2016).
A standard induction therapy also referred to as the 7+3 therapy consists of 7 days of
cytarabine and 3 days of anthracycline in the appropriate doses. In patients younger than 60 years
of age, this regime achieves a CR rate of about 56-76% and a lower CR of 38-45% in patients
older than 60 (Villela & Bolaños-Meade, 2011). This 7+3 regime is commonly given to patients
with a low risk of TRM and those with intermediate to a favorable prognosis. Induction therapy
using daunorubicin or idarubicin can also show similar results (De Kouchkovsky & Abdul-Hay,
2016). Standard induction therapy is a reasonable choice for patients with <2 performance status
and those with no comorbidities, as it results in about 50% CR rate and it also significantly reduces
the rate of death in aplasia or from indeterminate cause to < 15% (Döhner et al., 2010).
21
AML in the older population typically present with poor prognosis and high-risk factors.
Conventional chemotherapy may be extremely toxic for older patients, hence the NCCN created a
guideline that separates treatment recommendations based on performance status, cytogenetic or
molecular characteristics, and comorbid conditions (Medeiros et al., 2015). Older patients, who
can receive the 7+3 regimen are recommended to do so, otherwise, they should be given less
intensive chemotherapy with DNA hypomethylating agents and low dose cytarabine (Medeiros et
al., 2015). HMAs, such as 5-azacitidine (AZA) or decitabine (DEC), are DNA methyltransferase
(DNMT) inhibitors commonly used as a standard treatment in elderly patients with AML
(Fleischmann et al., 2021). In R/R AML patients as well as in elderly patients not eligible for
intensive treatment, HMA is used as standard treatment due to its effectiveness in improving
patients' OS when compared to standard chemotherapy (Kantarjian et al., 2012).
Older patients with AML who have not been treated previously are now eligible to receive
venetoclax, a BCL-2 inhibitor together with HMA or low-dose cytarabine (LDAC) (Wei et al.,
2019). In some cases, older patients simply get supportive treatment and no antileukemic therapy,
as patients older than 65 are less likely to respond to chemotherapy and more likely to have an
adverse cytogenetic-risk profile and treatment-related toxicity (DiNardo et al., 2019; De
Kouchkovsky & Abdul-Hay, 2016 and Klepin et al., 2019). Despite this unfavorable response from
the older population, it has been shown that the use of induction therapy improves survival rate in
comparison to taking only supportive care measures and palliative chemotherapy (De
Kouchkovsky & Abdul-Hay, 2016).
22
Enasidenib and ivosidenib are the two IDH-inhibitors currently FDA approved for use as
standard treatment in patients with R/R AML. In addition, Ivosidenib is also approved for the
treatment of newly diagnosed AML patients who do not qualify for intensive treatment (DiNardo
et al., 2018 and Roboz et al., 2020). Also, several studies have shown promising results that
combining HMA with venetoclax yields promising results in R/R AML patients (Aldoss et al,
2018 and Piccini et al., 2021). Combination therapy of HMA and venetoclax are also used as
standard treatment in patients who present with FLT3 mutations but are ineligible for intensive
therapy (DiNardo et al., 2020). In addition, patients midostaurin (PKC412) and gilteritinib are
FLT3 inhibitors commonly used as first-line treatment in newly diagnosed FLT3-ITD mutated
patients (Hou & Tien, 2020). Combining midostaurin with traditional chemotherapy has been
shown to improve the OS in these patients and gilteritinib is currently approved as a single
treatment for patients presenting with R/R FLT3-mutated AML (Hou & Tien, 2020).
1.1.8 Targeted therapy in AML
Due to the complex mutational patterns detected across patients with AML, it has been a
challenge to implement targeted therapies over the years. The discovery and understanding of the
mutational landscape in AML have significantly expanded the field of developing targeted
therapies for AML patients (Tyner et al., 2018). The introduction of all-trans retinoic acid and
arsenic trioxide for the treatment of APL, as well as a tyrosine kinase inhibitor for the treatment
of chronic myeloid leukemia (CML), has prompted scientists to focus their efforts on developing
targeted therapeutics for AML (Burnett et al., 2015). Several FLT3 antibodies with high binding
affinities have been developed and were either FDA approved or still undergoing clinical trials
(Almatani et al., 2021). Midostaurin and gilteritinib which are targeted drugs commonly used as
23
standard treatment in FLT3 mutated patients will be later discussed. More recently the combination
of hypomethylating agents (HMA) such as azacitidine or decitabine with venetoclax has been
utilized as an intensive treatment for older patients while younger patients get combined
chemotherapy with venetoclax treatment (Kantarjian et al., 2021). The introduction of monoclonal
antibodies as a stand-alone or in conjunction with chemotherapy agents in AML treatment has
evolved as it was determined in an open-label study that combining gemtuzumab ozogamicin
(GO), an antibody that binds to CD33 present on the myeloid lineage with standard treatment
yields low toxicity and better treatment outcome (Castaigne et al., 2012). GO was initially FDA
approved in 2000; however, consequent studies demonstrated an increased risk of treatment-
related toxicity and mortality which led to withdrawal of the drug 10 years after the conditional
approval (Petersdorf et al., 2013). Subsequently, in 2017 this drug was FDA approved for use in
R/R CD33 positive AML cases in both pediatric and adult populations as later studies indicated
treatment with a lower dose solved the toxicity-related issues (Hills et al., 2014). Introducing the
concept of bispecific antibodies targeting two different antigens is another approach widely
explored. Several studies have incorporated immunotherapy in this construct such that one arm of
the antibody targets the protein of interest and the other enhances T-cell activation. Examples of
some bispecific antibodies reported in preclinical studies include 7370 Anti-FLT3 CD3 and
CD123-cross-over dual variable T-cell engager (CD123-CODV-TCE) (Bonnevaux et al., 2021 and
Yeung et al., 2020). Subsequently, chimeric antigen receptor (CAR)-T-cells have been extensively
explored with several ongoing clinical studies utilizing CAR-T- cells as targeted therapy for AML.
The development of FLT3 inhibitors has expanded over the years and some of these are currently
undergoing clinical trials. Eight drugs that target certain gene mutations such as those involved in
the biological pathways and or surface antigens are currently approved by the FDA for the
24
treatment of AML (Hou & Tien, 2020). Targeted therapy used in the treatment of AML involves
those that inhibit FLT3, KIT, TP53, RAS, and IDH. Of these inhibitors listed, the discovery and
use of FLT3 inhibitors have gained a major spotlight in the research of targeted therapy.
1.1.9 Supportive care
Most AML patients develop anemia, and low platelet count and are more susceptible to
infections due to lower WBCs. Undergoing transfusion therapy is one of the supportive measures
taken to return their cell count to the normal range. Since the introduction of platelet transfusion,
the mortality rate of AML patients dying from hemorrhage has significantly decreased (Döhner et
al., 2010). Platelet transfusion is recommended when a count of < 20 x 10
9
/L is detected. In
addition to low platelet count as a criterion for transfusion, the presence of mucosal bleeding,
infection, fever, and severe mucositis is considered to have an increased risk of hemorrhage and
hence transfusion may be required (Döhner et al., 2010). To improve supportive care, it is
important to understand and differentiate between treatment-related mortality (TRM) from
disease-related death.
1.2 FMS-like tyrosine kinase 3 (FLT3)
1.2.1 Overview of FLT3 gene
The cluster of differentiation antigen 135 (CD135), commonly known as FMS-like tyrosine
kinase 3 (FLT3), is a type III receptor tyrosine kinase (RTK) and a growth factor gene that plays
an important role in regulating early hematopoiesis. In normal hematopoiesis, this gene is
expressed in CD34+ cells as it is present in the early stages of cell development. However, as cells
begin to mature, their surface expression is lost during cellular differentiation (Matthews et al.,
25
1991), subsequently resulting in cell proliferation and differentiation into dendritic cell
progenitors, B-cell progenitors, and natural killer cells (Stirewalt & Radich 2003 and Chen et al.,
2017). In 1991, the human FLT3 gene was first cloned independently by two research groups and
was referred to as the FLK-2 (fetal live kinase-2), FLT3 (Fms-like tyrosine kinase 3), and STK-1
(human stem cell kinase-11) gene (Gilliland & Griffin, 2002 and Levis & Small, 2003). This
human FLT3 gene was first cloned from a stem-cell enriched cDNA library produced from CD34
positive cells, and it was discovered to have 92% amino acid similarity with a murine gene, hence
it was also named the STK-1 (human stem cell kinase-11) gene (Levis & Small, 2003). More
recently both the human and murine versions of this gene are commonly referred to as the FLT3
or FLK-2 gene (Levis & Small, 2003). FLT3 is expressed in both B-lymphoid and myeloid lineage
in several human and murine cell line models (Gilliland & Griffin, 2002) encoding a
transmembrane receptor of 993 and 1000 amino acid protein in the human and mouse model
respectively (Gilliland & Griffin, 2002). The FLT3 gene consists of 24 exons that extend over
more than 100 kilobases (kb) and it is located on chromosome 13 (13q12) closely linked to the
FKT1 gene which encoded a receptor for vascular endothelial growth in humans (Levis & Small,
2003 and deLapeyrière, O et.al 1995).
FLT3 is shown to be expressed in hematopoietic cells and cells in the nervous system.
However, unlike the CSF1R/FMS and SLFR/KIT gene, FLT3 is restricted to early progenitor cells,
stem cells, and immature lymphoblasts (deLapeyrière, O et.al 1995). In addition to being expressed
in immature hematopoietic cells, the FLT3 gene is expressed in several organs in the body which
primarily include the brain, specifically the cerebellum, the placenta, and gonads (deLapeyrière,
O et al., 1995 and Gilliland & Griffin, 2002). FLT3 expression is limited to early progenitors’ cells
in the normal bone marrow. However, in about 70%-100% of acute myelogenous malignancies
26
and other hematological malignancies such as pre-B ALL9 acute lymphoid leukemia), T-cell ALL,
and CLL (chronic lymphoid leukemia), FLT3 is overexpressed (Gilliland & Griffin, 2002; Chen
et al., 2017; and Carow et al., 1996). FLT3 has also been shown to be present in CD34 positive
cells exhibiting a high level of CD117 (c-KIT) expression and a small fraction of CD34-negative
cells which eventually differentiates to become dendritic cells (Gilliland & Griffin, 2002 and Levis
& Small, 2003). Since normal expression of FLT3 is limited to early progenitor cells, this gene is
known to be a driving factor in the growth and differentiation of hematopoietic cells (Small et al.,
1994).
1.2.2 FLT3 activation and signaling pathways
The homologous structure and sequence of the FLT3 gene are closely related to the stem
cell growth factor receptor c-KIT (CD117), colony-stimulating factor-1 receptor (CSF1R;
CD115), and two platelet-derived growth factor receptors (PDGFR) (Levis & Small, 2003; Small
et al., 1994; Iwai et al., 1999; Gilliland & Griffin, 2002; Sexauer & Tasian, 2017; and Kiyoi et al.,
2020). It is composed of four domains characterized by a single extracellular (EC) ligand-binding
region consisting of five immunoglobulin-like (IgL) structures, a transmembrane domain (TMD),
and located in the intracellular region is the juxtamembrane domain (JMD), and tyrosine kinase
domain (TKD) separated by a stretch of hydrophobic amino acids known as the kinase insert (KI)
followed by a C-terminal domain (Levis & Small, 2003; Small et al., 1994; Iwai et al., 1999;
Rosnet & Birnbaum, 1993; Gilliland & Griffin, 2002; Sexauer & Tasian, 2017; and Kiyoi et al.,
2020). FLT3 signaling cascade is activated through phosphorylation of cytoplasmic proteins
present in the biochemical pathways which subsequently promote cell growth and inhibit cell death
(Levis & Small, 2003). In the normal activation process, the FLT3 receptor is stimulated by the
27
binding of the FLT3 ligand (FL), a cytokine that regulates early progenitor cells, to the
extracellular domain (Iwai et al., 1999). The binding of the FL ligand dimerizes the FLT3 receptor
leading to trans-phosphorylation of the tyrosine residues in the activation loop (A-Loop) and
subsequent activation of different intracellular downstream signaling cascade which includes
STAT5, SHIP, and SHP-2 (Kiyoi et al., 2020; Iwai et al., 1999; Levis & Small, 2003; and Sexauer
& Tasian, 2017). In addition, signals through critical oncogenic pathways such as Ras/Raf/MAPK
and PI3K/ Akt/mTOR are also active during the process (Kiyoi et al., 2020; Iwai et al., 1999; Levis
& Small, 2003; and Sexauer & Tasian, 2017). Simulation of these signaling cascades ultimately
promotes hematopoietic cell survival, cell proliferation and inhibits cell apoptosis.
Figure 5: Structure of FLT3 receptor -The FLT3 receptor is composed of a single extracellular (EC) ligand-binding region
consisting of five immunoglobulin-like (IgL) structures, a transmembrane (TM) domain, and located in the intracellular region is
the juxtamembrane domain (JMD), and tyrosine kinase domain (TKD) separated by a stretch of hydrophobic amino acids known
as the kinase insert (KI) followed by a C-terminal domain.
28
1.2.3 Mutations in FLT3 gene
Mutations in FLT3 present with the most frequent genetic abnormalities in AML and it is
associated with a high relapse rate and poor prognosis in AML patients. Therefore, FLT3 serves
as an excellent therapeutic target. FLT3 mutations are classified into two types namely: internal
tandem duplications (ITD), also referred to as the gain-of-function mutation, and point mutations
located in the tyrosine kinase domain (TKD). Internal tandem duplication in the juxtamembrane
domain coding sequence of the FLT3 gene (FLT3-ITD) was first identified in 1996 as an active
mutation of FLT3 in AML patients (Nakao et al., 1996). Subsequently, in 2001 a missense point
mutation on aspartic acid D835 residue and point mutations, deletions, and insertions in the codons
surrounding D835 or 836 within a TK domain of FLT3 (FLT3-TKD) was identified (Abu-Duhier
et al.,2001 and Yamamoto et al., 2001). Both the FLT3-ITD and TKD mutations lead to
constitutive activation of the FLT3 signaling pathway. However, a mutation in FLT3-ITD which
involves 3-400 bp in-frame duplication in the JMD is found in about 20-30% of AML patients,
while the FLT3-TKD mutation accounts for about 7% of de novo AML cases (Chen et al., 2017
and Sexauer & Tasian 2017).
29
Cytogenetic abnormalities or other genetic alterations are frequently associated with FLT3
mutations in AML. Therefore, FLT3 mutation is common in cytogenetically normal AML (CN-
AML) but typically uncommon in AML with altered karyotypes (Kiyoi et al., 2020 and Kiyoi &
Naoe 2006). However, Mixed lineage leukemia (MLL) rearrangement which involves the fusion
of 11q23 with different genes has recently been identified as a common fusion gene observed in
patients with FLT3-ITD and TKD mutations (Guan et al., 2021). MLL gene alterations are known
to play a key role in leukemogenesis and are recognized as potent AML initiators (Guan et al.,
2021). Although FLT3-ITD/TKD mutations are frequent in AML cases, they are also present in
approximately 3% of patients with myelodysplastic syndromes (MDS) which is a type of myeloid
neoplasm. However, this percentage increases as patients progress into advanced MDS. Hence,
FLT3 ITD/TKD mutation is present in about 15% of patients who develop AML secondary to
MDS (Kiyoi et al., 2020). As AML has been proven to be associated with age, studies have shown
that FLT3 mutations may also be associated with AML patients' age as the frequency of this
mutation increases with age. However, the reason why incidences with age correlate with the
mutations still remains unclear (Xu et al., 2000). About 25% of adult patients and over 30% of
patients 55 years and older present with FLT3-ITD mutation, making it one of the most common
single mutations in adults (Kiyoi et al., 1999; Stirewalt et al., 2001; and Kiyoi & Naoe, 2002). On
the other hand, FLT3 mutation is only found in about 10% of pediatric patients and in fewer than
5% of infant AML patients under the age of one (Xu et al., 2000 and Kiyoi et al., 2020).
Under normal circumstances in its inactive state, the wild-type FLT3 gene remains in the
monomeric form on the cell membrane. FLT3 ligand, FL is required for activation of wild-type
FLT3 gene, and the JMD regulates dimerization of this receptor (Chen et al., 2017). However, the
mutation in FLT3 constitutively activates this receptor even in the absence of its ligand (Kiyoi et
30
al., 1998) leading to phosphorylation of tyrosine residues in the cytoplasmic domain and activation
of downstream signaling pathways which promotes cell growth and inhibits cell death (Kiyoi et
al., 2020). The presence of FLT3-ITD mutations has been reported to promote FLT3 ligand-
independent dimerization of this receptor, autophosphorylation, and activation of STAT5,
RAS/MAPK, and PI3K pathways due to the mutation in the JMD which disrupts its structure and
function (Chen et al., 2017; Hayakawa et al., 2000; and Kiyoi & Naoe, 2002). FLT3-ITD mutation
possesses huge significant clinical consequences as they are frequently associated with disease
progression, shorter overall survival, unfavorable prognosis, and increased risk of relapse
(Kottaridis et al., 2001; Levis & Small, 2003; Kiyoi et al., 1999, Whitman et al., 2001; and Thiede
et al., 2002).
While FLT3-ITD mutation is mainly confined in the JMD, several studies have shown that
the ITD mutation can also be found in some parts of the kinase domain (Kayser et al., 2009 and
Breitenbuecher 2009). A clinical study done in AML patients with FLT3-ITD mutation revealed
localization of FLT3-ITDs outside the JMD in approximately 30% of patients with FLT3-ITD
mutation (Kayser et al., 2009). Results from this study indicate that FLT3-ITD mutation located in
the tyrosine kinase domain (FLT3-TKD) presents with a significantly worst prognosis when
compared with patients with FLT3-ITD mutation in the JMD (Kayser et al., 2009). These findings
propose that the location of the FLT3-ITD mutation possesses yet another substantial factor related
to clinical outcomes in these patients.
1.2.4 Glycosylation status in FLT3 receptor mutations
Glycosylation which involves the covalent binding of various glycans (also known as
sugars, carbohydrates, or saccharides) to specific amino acid residues in proteins is the most
31
prevalent form of post-translational modification (PTM) on extracellular membrane-associated
proteins (Spiro, 2002 and Hu & Chen, 2019). Based on their unique characteristics, glycoproteins
play an important role in a variety of biological and chemical processes, including cell
proliferation, differentiation, immunological regulation, localization, protein structure, and
stability of new peptide chains (Hu & Chen, 2019). In several hematological, inflammatory,
autoimmune diseases, and cancer malignancies, altered cell glycosylation has been identified
(Mori et al., 1998; Dube and Bertozzi, 2005; Chui et al., 2001; Pang et al., 2018; and Ząbczyńska
et al., 2021). Several studies have shown that the FLT3 receptor is initially synthesized as a 110-
kDa protein and partially glycosylated in the endoplasmic reticulum (ER) with a mannose-rich
branched oligosaccharide. It is then transported to the Golgi apparatus to be further modified by
complex glycosylation and then released to the cell surface (Helenius and Aebi, 2004; Helenius
and Aebi, 2001; Schmidt-Arras et al., 2005; Hu & Chen, 2019; and Stowell et al., 2015). Different
types of protein glycosylation, such as N-glycosylation, O-mannosylation, and
glycosylphosphatidylinositol (GPI) anchor addition, are initiated in the ER before the protein is
transported to the Golgi apparatus. Improper glycosylation in the Golgi complex leads to impaired
trafficking of receptors to the cell surface and subsequent accumulation of FLT3 protein in the ER
(Hu & Chen, 2019; Stowell et al., 2015; and Helenius and Aebi, 2004). This thereby causes cells
to respond to unfolded proteins and consequently promotes cell growth while triggering signaling
pathways other than that mediated by the glycosylation species (Hu & Chen, 2019 and Stowell et
al., 2015).
Western blot studies confirmed that FLT3 can be detected in two forms: namely the under-
glycosylated 130-kDa and the fully glycosylated 150-kDa molecules. Wild-type FLT3 cells
predominately express the fully glycosylated 150-kDa mature form on the cell surface (Schmidt-
32
Arras et al., 2005). On the other hand, the 130-kDa molecule that represents the under-glycosylated
immature form with a mannose-rich structure is predominately observed in FLT3-ITD mutated
cells (Schmidt-Arras et al., 2005). Since mannose-rich glycoproteins are a hallmark of ER proteins
(Takahashi, 2019), it was determined that the FLT3-ITD resides primarily in the intracellular
compartment of the cells such as the ER, perinuclear region, or Golgi apparatus (Schmidt-Arras et
al., 2005). It has also been demonstrated that FLT3-WT undergoes the normal process where
extracellular ligand stimulation is required for activation of this cell surface-bound receptor. In
contrast to the WT, FLT3-ITD is constitutively active and does not require ligand stimulation for
activation (Kiyoi et al., 2002; Schmidt-Arras et al., 2005; and Mizuki et al., 2000). The ligand-
activated FLT3-WT and oncogenic FLT3-ITD mutant receptors are both activated at the plasma
membrane. However, only the mutant FLT3-ITD is activated intracellularly before reaching the
cell surface (Choudhary et al., 2009). FLT3 ITD mutant receptor has been reported to have a higher
transforming potential and activates aberrant signaling when compared to the FLT3-WT receptor
(Kiyoi et al., 2002; Stirewalt and Radich, 2003; Rocnik et al., 2006; and Choudhary et al., 2009).
In addition to the different activation processes identified, several studies show that the
differences in localization of FLT3-WT/ITD alter the phosphorylation pattern of the receptor hence
leading to the activation of different downstream signaling cascades (Choudhary et al., 2009). For
example, it has been demonstrated that FLT3-ITD induces tyrosine phosphorylation on several
signaling intermediates such as the STAT signaling pathways leading to the upregulation of
targets, such as serine-threonine kinase (Pim-1/2 kinases) (Kiyoi et al., 2002; Mizuki et al., 2000;
and Hayakawa et al., 2000). STAT5 is a transcription factor mainly involved in the regulation of
self-renewal and differentiation of hematopoietic progenitor cells. In FLT3-WT leukemic cells,
this protein is only partially activated. Conversely, in cells expressing FLT3-ITD, such as leukemic
33
cell lines and blast cells from AML patients, STAT5 is constitutively phosphorylated and activated
(Zhang et al., 2000). While plasma membrane localization of WT-FLT3 receptor is needed for full
activation of the MAPK and PI3K signaling pathways (Choudhary et al., 2009), FLT3-ITD which
represents the under-glycosylated form mainly present in the intracellular compartment tends to
activate different signaling pathways such as STAT3 and STAT5a/b (Rocnik et al., 2006; Schmidt-
Arras et al., 2009; and Choudhary et al., 2009). Consequently, mutant FLT3 receptors (FLT3-ITD)
tend to abolish the phosphorylating activity of Erk1/2 and Akt, which are the two key downstream
components of the Ras/MAPK and PI3K signaling pathways known to be activated with the
ligand-binding WT-FLT3 receptor (Choudhary et al., 2009; Schmidt-Arras et al., 2009; and Hu &
Chen, 2019). Since improper glycosylation of this receptor impairs trafficking to the cell surface
hence promoting accumulation in the intracellular compartment (Helenius and Aebi, 2004), several
studies have demonstrated that treatment of FLT3-ITD with tyrosine kinase inhibitors such as
AC220, redirect the localization of this mutant receptor from intracellular to the surface level
(Schmidt-Arras et al., 2005), thereby inducing full activation of the MAPK and PI3K pathway
which is different from the signaling pathways activated when emitted from the ER (Choudhary
et al., 2009). When the FLT3-ITD receptor goes from the ER to the plasma membrane, the nature
of the signaling changes, indicating that retention of FLT3-ITD in the intracellular compartment
could help boost leukemic transformation (Choudhary et al., 2009). Therefore, these results
strongly suggest that changes in localization, as well as proper glycosylation of this FLT3 receptor,
play an integral role in the downstream signaling cascades activated.
34
1.2.5 FLT3 Tyrosine kinase inhibitors
With the adverse prognostic impact of FLT3-ITD mutations in AML and the increased
frequency of FLT3 mutations, mutant FLT3 are considered appropriate therapeutic targets for
leukemia-directed therapies (Hou & Tien, 2020 and Ley et al., 2013). FLT3 inhibitors are
competitive inhibitors that structurally mimic the purine ring of adenosine hence they bind to the
ATP-binding sites of the FLT3 receptor (Levis & Small, 2005 and Ley et al., 2013). The binding
of FLT3 inhibitors to the FLT3 receptor leads to the arrest of the cell cycle process and halts cell
differentiation (Ley et al., 2013). FLT3 inhibitors are divided into two categories based on their
efficacy and target specificity namely: first-generation and second-generation inhibitors (Hou &
Tien, 2020).
Midostaurin, sorafenib, lestaurtinib, and sunitinib are tyrosine kinase inhibitors also known
as first-generation FLT3 inhibitors (Hou & Tien, 2020). It is implied that the first-generation FLT3
inhibitors came into existence coincidentally as researchers were originally looking to inhibit other
kinases. They discovered the FLT3 kinase as their tested compounds inhibited the activity of this
protein along with other kinases (Zhou and Chen, 2019). These first-generation inhibitors are
known to be relatively nonspecific for FLT3 as they target other kinase pathways. They tend to
have a higher toxicity level, and typically present with a broad range of off-target effects (Hou &
Tien, 2020 and Ley et al., 2013). Furthermore, due to an increased incidence of relapse, drug
resistance to first-generation TKIs, and acquired secondary mutations after treatment with the first-
generation TKIs, research to develop second-generation FLT3 inhibitors was prompted.
Quizartinib, crenolanib, and gilteritinib are second-generation FLT3 inhibitors known to be more
selective and effective for mutant FLT3 (Hou & Tien, 2020 and Ley et al., 2013).
35
FLT3 inhibitors are classified into two types based on the mechanism through which they
interact with their target receptors. Type I inhibitors engage with their target receptors through a
different mechanism than type II inhibitors (Hou & Tien, 2020). Type I inhibitors such as
lestaurtinib, midostaurin, gilteritinib, and crenolanib bind to the FLT3 gatekeeper domain at the
activation loop or the ATP binding pocket, hence receptor conformation has no effect on their
binding mechanism (Ley et al., 2013). As a result, type I FLT3 inhibitors are considered potent
against FLT3-ITD and FLT3-TKD (Hou & Tien, 2020). Conversely, sorafenib and quizartinib
which are type II inhibitors bind next to the ATP binding domain in the hydrophobic area, hence
this binding only occurs when the protein is in an inactive conformational state (Ley et al., 2013).
Since FLT3-TKD mutation favors protein binding in an active conformational state, type II
inhibitors are primarily effective against FLT3-ITD mutations and possess no substantial activity
against FLT3-TKD mutations (Hou & Tien, 2020 and
Ley et al., 2013).
In 2017 midostaurin (PKC412), a type I first-generation inhibitor became the first FLT3
inhibitor approved in the United States for the treatment of newly diagnosed FLT3-mutated AML
patients (Hou & Tien, 2020). When used together with traditional induction therapy, studies show
a significant increase in AML patients' overall survival rate. Subsequently, the following year,
gilteritinib, a second-generation type I inhibitor became the second FLT3 inhibitor approved for
use in the USA. Gilteritinib is approved as a monotherapy for patients with relapsed or refractory
(R/R) FLT3-mutated AML (Hou & Tien, 2020). In a trial done to compare the overall survival rate
(OS) and event-free survival (EFS) in patients administered with gilteritinib to those undergoing
chemotherapy, it was observed that patients on gilteritinib maintained a longer OS and EFS than
those on chemotherapy (Hou & Tien, 2020). Nonetheless, even with these advances, the duration
of remission when used as monotherapy is relatively short as issues with resistance remain a
36
challenge. Quizartinib is another second-generation but a type II inhibitor that has been approved
for usage in Japan for the treatment of patients with R/R FLT3-ITD mutations due to its efficacy
in improving OS in these patients (Hou & Tien, 2020). Quizartinib is currently not approved for
usage in the United States or the European Union due to various safety concerns and the treatment's
low survival benefit (Hou & Tien, 2020). FLT3 inhibitors such as tandutinib, crenolanib, and
cabozantinib are currently in clinical trials or are still being developed (Hou & Tien, 2020).
Figure 6: Binding conformation state of FLT3 receptor - Binding conformation state of FLT3 receptor. Type I FLT3 inhibitors
bind to the FLT3 receptor in both the active and inactive state as depicted above. Type II inhibitor is highly selective and binds to
the FLT3 receptor only in the inactive conformation state as shown on the left. Blue color indicates second generation FLT3
inhibitors.
37
1.2.6 Resistance in FLT3 target therapies
Although the current FLT3 inhibitors approved remain promising, resistance to these
inhibitors possess a major threat in treatment. While the inherent nature of leukemic blast may
induce a resistance risk, several clinical studies have shown that patients developed resistance after
treatment with chemotherapy or with FLT3 inhibitors. Based on the underlying drug resistance
mechanism, resistance to treatment is classified into two potential groups; namely primary and
secondary (Chen et al., 2017, Scholl et al., 2020, and Kiyoi et al., 2020). Primary resistance occurs
due to the nature of leukemic blasts and the drugs used while secondary resistance is caused by
the acquired feature of the cancer cells during the drug treatment (Chen et al., 2017). Primary
resistance collectively includes inhibitory activity arising from the various cellular mechanisms
such as allele-specific FLT3-ITD or TKD mutations, FGF2-mediating resistance, CYP3A-
mediated resistance in the liver, the activation of other signaling pathways in both leukemic cells
and bone marrow niche, and FL-dependent resistance which present as an increase in plasma level
of FLT3 ligand after treatment (Kurokawa et al., 2008, Traer et al., 2016, Scholl et al., 2020, and
Kiyoi et al., 2020). Study shows that constitutive activation of kinases such as a mutation in the
FLT3 gene, BCR-ABL and TEL-PDGFRb can inhibit the apoptosome function by interacting with
Hsp90b, a molecular chaperone abundant in cancer cells after chemotherapy treatment (Kurokawa
et al., 2008). Also, the presence of FLT3 mutation increases the expression levels of a
phosphoprotein, the FOXO3A transcription factor. An increased level of FOXO3A transcription
factor along with the co-expression of mutant FLT3 lead to poor prognosis, and reduced remission
time, with an increased risk of developing primary drug resistance (Kornblau et al., 2010).
FLT3 inhibitors are effective against leukemic blast cells in the peripheral blood. However
stromal protection of leukemic blast in the bone marrow allows for resistance against FLT3
38
inhibitors such as nilotinib, PKC412, and Lestaurtinib (CEP-701) suggesting that the bone marrow
niche contributes to resistance against FLT3 inhibitors (Weisberg et al., 2008, 2009, Smith et al.,
2004, and Stone et.al, 2005). Another study confirms the cytotoxic effect of quizartinib on
peripheral blast while only inducing terminal myeloid differentiation of bone marrow blasts
(Sexauer et al., 2012). In a study aimed to determine the microenvironmental factors which protect
AML cells from FLT3 inhibitors, it was established that fibroblast growth factor 2 (FGF2) which
is highly expressed in the bone marrow as well as FL induces FLT3 resistance to FLT3 inhibitors
such as quizartinib (Traer et al., 2016). When treated with quizartinib, an increased level of FGF2
expression in bone marrow stromal cells was observed in FLT3-ITD positive patients (Traer et al.,
2016). Various mechanisms in which FLT3 mutated cells (MOLM-14) attained protection were
assessed and ultimately it was discovered that FGF2 activates the receptor FGFR1, which in turn
protects the FLT3-ITD positive cells (Traer et al., 2016). This observation was also true when
tested with primary AML samples positive for FLT3-ITD mutations (Traer et al., 2016). Next, they
determined that FGF2 was able to mediate resistance via the reactivation of the MAPK pathway
as phosphorylation of ERK was observed in resistance cells with little phosphorylation of FLT3
(Traer et al., 2016). This observation was also true for cells in which resistance was induced via
FL (Traer et al., 2016). Since treatment of FLT3-ITD positive cells halts phosphorylation of the
FLT3 gene, it is possible that by protecting these cells in tumor microenvironments such as the
bone marrow, they can secure time to turn on signaling pathways other than those involving FLT3
to escape apoptosis and hence develop resistance via these pathways.
Furthermore, the length of FLT3-ITD mutation in the JMD confers yet another resistance
mechanism since longer ITDs can invade the TKD. A study investigating the impact of ITD length
on prognosis confirms the integration of longer ITD mutation into the beta-sheet of the first kinase
39
domain (FLT3-ITD627E) (Breitenbuecher et al., 2009). This integration promotes resistance to
FLT3 inhibitors like midostaurin by inducing the upregulation of myeloid cell leukemia 1 protein
(MCL-1), an anti-apoptotic protein (Breitenbuecher et al., 2009). This observation was similar to
findings in other clinical studies revealing that the size of FLT3-ITD mutation in patients did in
fact lead to poor prognosis, decreased OS, and increased risk of resistance (Stirewalt et al., 2006
and Kayser et al., 2009). Cytochrome P450 enzymes (CYPs) in the liver are another contributor to
resistance against antileukemic therapy in general as well as FLT3 inhibitors. CYP3A4 enzymes
along with other CYPs are highly expressed in bone marrow stromal where they can potentially
metabolize FLT3 inhibitors. Hepatic CYP3A4 was shown to inhibit the anti-leukemic activity of
sorafenib, quizartinib, and gilteritinib in the bone marrow microenvironment thus inducing
resistance to these FLT3 inhibitors (Chang et al., 2019). As a result, metabolic enzymes in the liver
reduce drug concentration in the plasma, providing another pathway for drug resistance. Autocrine
stimulation of FLT3 ligand is another mechanism by which cells are resistant to FLT3-inhibitors.
Treatment with chemotherapy or FLT3 inhibitors such as lestaurtinib and ABT-869 resulted in
increased plasma levels of FLT3 ligand which in turn decreased the efficacy of treatment in both
preclinical and clinical studies (Sato et al., 2011, Zhou et al., 2009, Levis et al., 2011, and Chen et
al., 2017). FL ligand is thought to activate WT-FLT3 and not FLT3-ITD mutated cells in co-
expression cells (Chen et al., 2016). Co-expression of FLT3 mutation and WT-FLT3 contributes
to increased FL stimulation which impairs the anti-leukemic activity of FLT3-inhibitors on these
cells (Chen et al., 2016). The mechanism at which this resistance occurred was assessed and FL-
dependent activation of WT-FLT3 was shown to be attained via activation of MAPK pathways
which possess yet another major mechanism in FL-induced FLT3 inhibitor resistance (Chen et al.,
2016). In addition, FLT3-ITD-positive patients presenting with a pre-existing mutation in the
40
CCND3 gene (encoding cyclin D3) failed to respond to treatment with pexidartinib (PLX3397),
an FLT3-inhibitor (Smith et al., 2021). This finding suggests that resistance to FLT3 inhibitors can
be initiated by mutations in other genes rather than mutations directly in FLT3.
Secondary resistance is distinguished into two types based on the molecular changes within
FLT3-ITD allele (also known as the on-target resistance) and the activation of signaling pathways
other than FLT3 (known as the off-target resistance) (Scholl et al., 2020 and Kiyoi et al., 2020).
On-target resistance was first identified in patients with FLT3-ITD who relapsed after quizartinib
treatment (Smith et al., 2012). It was observed that although the leukemic blast remained
dependent on FLT3 signals, they developed resistance to FLT3 inhibitors by acquiring point
mutations at these three residues: D835, Y842, and F691(known as the gatekeeper in the kinase
domain within the FLT3 gene) (Smith et al., 2012). Co-existing mutations such as FLT3-ITD +
D835Y, +D835V, +Y842C, +Y842H, or +F691L-expressing Ba/F3 cells decrease the inhibitory
effect of quizartinib and sorafenib in these patients (Smith et al., 2012 and Baker et al., 2013).
Consequently, since quizartinib is specific to only ITD mutation, it is possible that conferring an
additional mutation in the TKD domain induces yet another resistance mechanism (Smith et al.,
2015). In addition, A-loop resistance mutations were also found in patients who were on sorafenib,
another type II inhibitor (Scholl et al., 2011 and Kiyoi et al., 2020). Following midostaurin
treatment, patients with R/R AML developed a single amino acid alteration at (N676K) within the
FLT3 kinase domain that conferred treatment resistance. (Heidel et al., 2006). This observation
was also true in preclinical studies where tyrosine kinase phosphorylation of FLT3 was sustained
primary blast at relapse despite sufficient concentration of midostaurin in serum (Heidel et al.,
2006). Furthermore, in roughly 4% of patients with FLT3-ITD mutations, preliminary reports
41
revealed that co-existing or acquired Janus kinase (JAK1, JAK2, or JAK3) mutations confers
resistance to sorafenib, midostaurin, and quizartinib (Rummelt et al., 2021).
Off-target resistance occurs due to persistent activation of alternative downstream
signaling pathways such as PI3K/Akt and/or Ras/MEK/MAPK after treatment with FLT3
inhibitors (Piloto et al., 2007). Furthermore, mutations or abnormal expressions of genes such as
BCL2, NF-kB, MCL-1, PTPN11, CBL, and BRAF mutations are thought to inhibit the anti-
leukemic activity of FLT3-inhibitors (Chen et al., 2017). Previous studies revealed that whereas
on–target resistance is common in individuals treated with type II inhibitors, off-target resistance
is common in those treated with type I inhibitors (Chen et al., 2017). A clinical study revealed that
although FLT3 mutations were not observed after treatment with gilteritinib, mutations in the
RAS/MAPK pathway signaling, frequently in NRAS or KRAS were acquired (McMahon et al.,
2019). This finding indicates that FLT3 mutation-negative clones can acquire new mutations and
further expand as resistant clones. Treatment with lestaurtinib on FLT3-ITD positive cell lines also
showed acquisition of the NRAS mutation leading to the aberrant activation of AKT and MAPK
pathways (Chen et al., 2017). After treatment with crenolanib, another type I inhibitor, mutations
associated with epigenetic regulators, transcription factors, and cohesion factors such as NRAS,
STAG2, CEBPA, ASXL1, and IDH2 were observed in FLT3-dependent clones suggesting that
during crenolanib therapy, these clones escaped treatment (Zhang et al., 2019).
Together, these findings suggest that the mechanisms of acquired resistance to FLT3
inhibitors may not be mutually exclusive. As a result, the evolution of relevant subclones should
be investigated at the time a patient relapse (Scholl et al., 2020). Taken together, the introduction
of combination therapy with FLT3 inhibitors may evolve as a promising therapeutic option for
future research against resistant mechanisms.
42
1.3 Research Hypothesis/Experimental Design
Although there have been a lot of advancements in AML treatment, FLT3 mutation which
is present in approximately 25% of newly diagnosed AML cases is still associated with poor
prognosis hence more research and drug development are needed in this field. Midostaurin, an
FDA-approved first-generation FLT3 inhibitor is currently used for treatment. However, problems
with new resistance mechanisms continue to be a challenge. Quizartinib on the other hand is a
second-generation and more potent FLT3 inhibitor approved for use in Japan. Safety concerns
such as increased QTC prolongation led to the FDA's disapproval of the drug in 2019. Several
preclinical studies have demonstrated the potency of this drug. In addition, several studies
demonstrated that dual therapy with FLT3 inhibitors and other chemotherapeutic agents
significantly enhances the antileukemic activity of FLT3-ITD positive cells when compared to a
single treatment. Herein I propose that combining these FLT3-inhibitors with our in-house
antibody-based therapy (anti-FLT3 scFv) will enhance treatment efficacy, address the current
issues related to treatment resistance mechanisms, and tackle issues with safety concerns.
I hypothesize that treatment with FLT3 inhibitors (quizartinib and midostaurin) will
upregulate the re-localization of FLT3 to the cell surface in FLT3-ITD positive cells which will
enhance the anti-leukemic effect of our antibody-based therapy (anti-FLT3 scFv) on these cells.
Therefore, this study aims to utilize FLT3 inhibitors (midostaurin and quizartinib) to upregulate
FLT3 surface expression in FLT3-ITD positive cells with subsequent introduction of our recently
developed anti-FLT3 scFv to induce synergy in-vitro. More specifically this study will investigate
the following:
43
- The effect of FLT3 inhibitors (quizartinib and midostaurin) in promoting cell surface
localization in FLT3-ITD positive cell
- The effect of dual therapy (FLT3-inhibitors and anti-FLT3 scFv) treatment in inhibiting
the proliferative activity and inducing cell death of FLT3-ITD positive cells in pre-clinical
models.
Figure 7: Illustration of thesis rationale - Pre-treatment with FLT3-inhibitors induced FLT3 surface level expression on FLT3-
ITD positive cells and enhance the anti-leukemic activity of anti-FLT3-scFv.
44
Chapter 2: Materials and Method
2.1 Cell line and cell culture
The human AML-derived cell lines expressing FLT3 (MOLM-13) were obtained from
collaborators at City of Hope. The human Histiocytic Lymphoma-derived cell line not expressing
FLT3 (U937 cells), and FLT3-WT AML derived cell line THP-1 were purchased from the
American Type Culture Collection (ATCC). Authentication of cell lines was done at the University
of Arizona Cell Authentication Core facility. All cell lines were cultured in Roswell Park Memorial
Institute1640 (RPMI 1640) medium (Thermo Fisher, MA, USA) supplemented with 10% (v/v)
fetal bovine serum (FBS), 1% (v/v) Antibiotic-Antimycotic, and 1% (v/v) L-Glutamine (Thermo
Fisher, MA, USA). All cells were maintained in a 37 °C humidified atmosphere containing 5%
CO2.
2.2 Treatment with Tyrosine kinase inhibitors
Midostaurin (Cat # M1323-1MG, Sigma-Aldrich, St. Louis MO, USA), an FDA approved tyrosine
kinase inhibitor (TKI) and Quizartinib (AC220) (Cat# S1526, Selleck Chemicals, Houston TX,
USA) another TKI approved for use in Japan were both used to treat MOLM-13 and U937 cell
lines. The TKIs were stored at a stock concentration of 10mM in -20
o
C. Cells were treated with
different concentrations of TKIs ranging from 5nM to 50nM for six hours in 5% CO2, 37
o
C
incubator setting.
45
2.3 FLT3-single-chain variable fragment (scFv)
The production and design of the FLT3-scFv were done in collaboration with Dr. Zhang’s lab at
the University of Southern California. The molecular weight of the antibody is approximately 27.8
kDa. Using primers, the DNA encoding the -FLT3 scFv was cloned into the pFUSE backbone
(InvivoGen, CA):
ATL225-
TGTCACGAATTCGTATCCATACGACGTACCGGATTATGCAGAAGTCCAACTGGTCCA
GTCAGGC and ATL256
TGGCCAGCTAGCTTATTAATGGTGGTGGTGATGGTGCTTGATTTCCAAGCGAGTCCC
CTG.
This primer was introduced to the N-terminal HA-tag and a C-terminal His6 tag. Next, restriction
enzymes EcoRI and NheI were used to induce double digestion of the pFUSE vectors and purified
PCR product before ligation with T4 ligase (New England Biolabs, MA, USA). To purify α-FLT3
scFv, the plasmids were transfected into Expi293F cells (Thermo Fisher, MA, USA). Cells were
cultured for 5 days, and the supernatant was collected for dialysis purposes. Using elution buffer
(20 mM Tris pH 7.5, 500 mM NaCl, 400 mM imidazole), bound scFv were washed and
concentrated using Amicon Ultra-15 Centrifugal Filter Units (MilliporeSigma, MA, USA). To
collect the desired protein, samples were loaded onto an ÄKTA pure chromatography system (GE
Healthcare Life Sciences, MA, USA) with a Superdex 75 10/300 GL column (GE Healthcare Life
Sciences, MA, USA) equilibrated with PBS for gel filtration and buffer exchange into PBS (Park
et al., 2020). The encoded DNA and amino acid sequence of α-FLT3 scFv was previously
demonstrated by (Park et al., 2020).
46
2.4 Measurement of FLT3 surface expression level
The surface level expression of FLT3 was analyzed by flow cytometry measurement of anti-FLT3
antibody on AML cells. Briefly, 5×10
5
MOLM-13 cells were treated with midostaurin or
quizartinib at 5, 10, 20, and 50nM respectively for 6 hours. As a negative control, THP-1 cells
were treated with midostaurin and quizartinib as described above. After treatment cells were spun
down at 1300 rpm for 3 minutes and then washed 2X with phosphate-buffered saline (PBS, pH
7.4, Cat# 14190-144 Gibco by Thermo Fisher Scientific) to remove the media and further stained
with APC (Adenomatous polyposis coli)-conjugated Anti-Hu CD135 (FLT3) (Cat # 17-1357-42,
Invitrogen, Carlsbad CA, USA) for 20 min at room temperature. Following incubation, cells were
washed with PBS 2X, and the shift in mean fluorescence intensity (MFI) in comparison to the
corresponding control was evaluated. Mean fluorescence intensity was normalized to the unstained
condition and data were analyzed using the LSRII BD Fortessa X20 flow cytometer. Results were
further analyzed using FlowJo software (version 10.6.2; TreeStar, USA).
2.5 Measurement of FLT3-scFv binding in AML cell line
The binding of anti-FLT3-scFv to the cell surface was assessed by incubating 1×10
6
FLT3-ITD
positive (MOLM-13) cells with anti-FLT3-scFv at either 1μM or 10μM for 30 minutes at room
temperature. The FLT3-scFv treated cells were incubated either alone (i.e., untreated) or pre-
treated with 10nM midostaurin or 5nM quizartinib. Cells were then washed 2X with PBS to
remove media and incubated with PE-conjugated anti-His tag mouse IgG1 (Cat # IC050P, R&D
Systems, Minneapolis MN, USA) for 30 mins on ice. To get rid of unbound antibodies after
incubation, cells were washed twice with PBS. Bound anti-His tags labeled FLT3-scFv were
measured by assessing the shift representing the mean fluorescence intensity (MFI). Mean
47
fluorescence intensity was normalized to the unstained condition and data were analyzed using the
LSRII BD Fortessa X20 flow cytometer. Results were further investigated using FlowJo software
(version 10.6.2; TreeStar, USA).
2.6 Cell proliferation and viability assays
MOLM-13 cells were seeded at a density of 2 ×10
6
cells/mL in the presence or absence of TKIs
(10nM midostaurin or 5nM quizartinib) respectively and incubated in a 5% CO2, 37
o
C incubator
for 6 hours. After incubation, samples were spun down via centrifugation for 3 minutes at 1300rpm
and washed once with PBS. Sample pellets were further resuspended in PBS and anti-FLT3-scFv
added in their respective concentrations (1μM and 10μM) to labeled tubes and then incubated on
ice for 30 mins. After 20 mins incubation RPMI1640 media was added to each condition to bring
the total volume up to 1000uL. Subsequently, samples were seeded and incubated at a
concentration of 5 × 10
4
/mL/100 µL cells per well in 96-well plates.
2.6.1 CCK-8 cell viability assay
Cell proliferation viability assay was measured by using the Cell Counting Kit-8 (Cat # ab228554,
Abcam, Boston MA, USA) according to the manufacturer’s instructions. MOLM-13 cells in their
respective conditions were plated at 5 ×10
4
cells/100 µL per well in 96-well plates and allowed to
incubate for 48 and 72 hours respectively. Thereafter, the CCK-8 reagent was added and incubated
for another 4 hours at 37°C and absorbance was measured at 450 nm using the BioTek Synergy
H1 microplate reader. Experiment was performed in triplicates and analyzed using GraphPad
Prism 8.0c (GraphPad Software, La Jolla CA, USA), and P < 0.05 was considered statistically
significant.
48
2.6.2 Trypan blue cell viability assay
Cell viability assay was also investigated using Trypan blue staining and the viable cell count was
performed using the hemocytometer. Again, MOLM-13 cells in their respective conditions were
plated at 5 ×10
4
cells/100 µL per well in 96-well plates and allowed to incubate. Using trypan blue
stain (Cat # 15250–061, Life Technologies, Grand Island NY, USA), the live cells then were
counted at 48 and 72 hours, and cell viability was determined by taking the ratio of the number of
live cells in treated conditions and normalizing that to that in untreated conditions. Each
experiment was performed in triplicates and analyzed using GraphPad Prism 8.0c (GraphPad
Software, La Jolla CA, USA), and P < 0.05 was considered statistically significant.
2.7 Apoptosis assay
MOLM-13 cells in their respective conditions were plated at 5 ×10
4
cells/100 µL per well in 96-
well plates and allowed to incubate for 48 and 72 hours respectively. 200uL of cells were harvested
from each condition at 48 and 72 hours. Harvested cells were washed, and an in-vitro apoptosis
assay was performed using the Annexin V and PI APC kit according to the manufacturer's protocol
(Cat # 88–8007-74, Invitrogen, Carlsbad CA, USA). Percent apoptotic cell death (APC + and PI
+) events in cells were compared among groups. Data were analyzed using the LSRII BD Fortessa
X20 flow cytometer and processed on the FlowJo software (version 10.6.2; TreeStar, USA).
2.8 Statistical analysis
All data are presented as mean ± standard deviation (SD). Ordinary one-way ANOVA with
Dunnett's Multiple Comparison Test was performed for multiple comparisons among groups and
also for comparison between two groups. All data were analyzed using GraphPad Prism 8.0c
49
(GraphPad Software, La Jolla CA, USA), and P < 0.05 was considered statistically significant. All
experiments were either performed in quadruplets, triplicates, or duplicates as stated in figure
legends and the data shown is the average and SD from replicates.
50
Chapter 3: Results
3.1 FLT3 tyrosine kinase inhibitors upregulate FLT3 surface expression
Several studies investigating the localization of FLT3 mutants after treatment with FLT3
tyrosine kinase inhibitors showed an increase of FLT3 proteins on the cell surface in FLT3-ITD
positive cells. Since FLT3-ITD is mainly expressed in the intracellular compartment of the cells
with little expression detected on the cell surface, it has been demonstrated that treating these
FLT3-ITD positive cells with small molecules, inactivating point mutations, or co-expression with
other protein tyrosine phosphatases (PTPs) promotes complex glycosylation and surface
localization of these receptors (Schmidt-Arras et al., 2005). To confirm the increase in expression
of the FLT3 surface marker on FLT3-ITD positive cells, MOLM-13 cells (FLT3ITD-/+) were
treated with different concentrations (5nM, 10nM, 20nM, and 50nM) of either midostaurin or
quizartinib respectively for 6 hours. FLT3-WT expressing AML cell line, and THP-1 were treated
with quizartinib as described above.
51
Flow cytometry data showed that increasing concentrations of FLT3-TKIs in the
heterozygous FLT3-ITD positive cell lines MOLM-13 induced an increase in FLT3 surface-level
expression on these cells. In contrast, no shift was observed in FLT3-WT negative cell line U937
after treatment with midostaurin and quizartinib at equal concentrations when compared to the
untreated condition Figure 3.1.1. Quantitative analysis was evaluated by combining the mean
fluorescence intensity (MFI) from three independent experiments and taking the ratio from
unstained (n=3) for all conditions to get the fold change in MFI as shown in Figure 3.1.2. In
addition, quizartinib failed to increase FLT3 surface expression on FLT3-WT THP-1 cells as
expected in Figure 3.1.3. Our results indicate that treatment with FLT3 inhibitors significantly
promotes the FLT3 surface expression in MOLM-13 cells in a dose-dependent manner when
compared to the untreated condition, and no increase was observed in U937 cells. In addition,
when comparing the means across groups in the different concentrations, one-way ANOVA shows
statistical significance in MOLM-13 cells treated with midostaurin and quizartinib (p <0.0001 and
p = 0.0056) respectively. As expected, the p-value was not significant in U937 treated with either
midostaurin or quizartinib (p= 0.1436 and p= 0.3426) respectively.
52
Figure 8: AML cell lines response after treatment with FLT3 Tyrosine kinase inhibitors - Heterozygous FLT3-ITD AML cell
line MOLM-13 and AML cell line not expressing FLT3, U937 cells were treated with increasing concentrations (5nM, 10nM,
20nM, and 50nM) of either midostaurin or quizartinib and incubated for 6 hours in a 37 °C humidified atmosphere containing 5%
CO2. The binding was measured via (A-D) flow cytometry by measuring the peak shift in APC-conjugated anti-Hu CD135 (FLT3)
to bound cells. (a) Increase in FLT3 expression in MOLM-13 cells with increasing midostaurin concentrations, and (b) no increase
in FLT3 expression was observed in U937 cells with the same treatment. (c) Increase FLT3 expression in MOLM-13 cells with
increasing quizartinib concentrations, and (d) no increase in FLT3 expression observed in U937 cells with the same treatment.
53
Figure 9: Quantified response after treatment with FLT3 inhibitors- Heterozygous FLT3-ITD AML cell line MOLM-13 and AML
cell line not expressing FLT3 U937 cells were treated with increasing concentrations (5nM, 10nM, 20nM, and 50nM) of either
midostaurin or quizartinib and incubated for 6 hours in a 37 °C humidified atmosphere containing 5% CO2. The binding was
measured via flow cytometry by analyzing the mean fluorescence intensity (MFI) of APC. Bar graphs showing peak shift quantified
based on MFI normalized to the unstained condition (A-D). (a) Increase FLT3 expression in MOLM-13 cells with increasing
midostaurin concentrations (p <0.0001), and (b) no increase in FLT3 expression observed in U937 cells with the same treatment
(p=0.1436). (c) Increase FLT3 expression in MOLM-13 cells with increasing quizartinib concentrations (p=0.0056), and (d) no
increase in FLT3 expression was observed in U937 cells with the same treatment (p=0.3426). Data represented as mean ± SD and
in triplicates (n=3).
54
Figure 10: FLT3-WT response after treatment with FLT3 inhibitors - WT-FLT3 AML cell line THP-1 cells were treated with
increasing concentrations (5nM, 10nM, 20nM, and 50nM) of Midostaurin and quizartinib respectively and incubated for 6 hours
in a 37 °C humidified atmosphere containing 5% CO2. The binding was measured via flow cytometry by analyzing the mean
fluorescence intensity (MFI) of APC. No response in surface-level FLT3 expression was observed in THP-1 cells with increasing
midostaurin (a) and quizartinib (c) concentrations. (b and d) Bar graphs showing peak shift quantified based on MFI normalized
to the unstained. Data represented as a single experiment (n=1).
3.2 The effect of FLT3-TKIs treatment on anti-FLT3-scFv binding to FLT3 positive cells
To test whether the treatment with FLT3 inhibitors enhances anti-FLT3-scFv to the FLT3
surface receptor on the FLT3-ITD positive cell line, binding was analyzed via flow cytometry
using an antibody against FLT3 (CD135). Data from the binding assay suggests our FLT3-scFv
binds to MOLM-13 cells (Figure 3.2.1a and 3.2.1c) with no shift observed in FLT3 negative
(U937) cells (Figure 3.2.1b and 3.2.1d). Next, we investigated the effect of combination therapy
55
on MOLM-13 cells by first testing the binding activity of anti-FLT3 scFv administered alone or in
combination with either midostaurin or quizartinib. Cells were treated with 10nM midostaurin or
5nM quizartinib alone or in combination with either 16μM scFv or 33μM scFv. Data from flow
cytometry indicates more binding with the combination therapy (FLT3-TKIs and FLT3-scFv)
compared to MOLM-13 cells treated with FLT3-scFv alone at either 16μM or 33μM, and no shift
was observed in the untreated condition. As expected, in the FLT3 negative cell line, U937 there
was no shift observed with FLT3-scFv treatment alone or in combination with either midostaurin
or quizartinib when compared to the untreated condition. Quantitative analysis was evaluated by
analyzing mean fluorescence intensity from four (n=4) or three independent experiments (n=3) in
all conditions as stated in the figure legend. Quantitative analysis shows binding of FLT3-scFv to
MOLM-13 cells with more shift observed in the presence of midostaurin (p = 0.0253). Following
one-way ANOVA, Dunnette’s Multiple Comparison test was done to compare 10nM midostaurin
alone or in combination (10nM midostaurin + 16μM FLT3-scFv) and p = 0.0169 Figure 3.2.2a.
On the other hand, because U937 cells do not express FLT3, competition with both antibodies
(anti-FLT3 scFv and anti-his tag) which are non-specific for these cells possibly caused the
decrease in the signals in the treated group (p <0.0001) Figure 3.2.2b. As with quizartinib, one-
way ANOVA indicated a significant p-value (p=0.0258) in MOLM-13 cells and the p-value was
not significant (p= 2.584) in U937 cells as expected (Figure 3.2.2c -3.2.2d).
56
Figure 11: Binding signals of anti-His tag secondary antibody to FLT3-scFv at different concentrations in the presence or
absence of TKIs - Heterozygous FLT3-ITD AML cell line MOLM-13 and AML cell line not expressing FLT3 U937 cells were
treated with different concentrations (16μM or 33μM) of FLT3-scFV in the absence of TKIs or after treatment with either 10nM
midostaurin or 5nM quizartinib. The binding was measured via (A-D) flow cytometry by measuring the peak shift in PE-conjugated
Anti-His tag secondary antibody to FLT3-scFv to bound cells. (a) FLT3-scFv binds to MOLM-13 cells with increased binding in
the presence of midostaurin, and (b) no binding was observed in U937 cells both in the presence or absence of TKIs. (c) FLT3-
scFV binds to MOLM-13 cells with an increase in binding in the presence of quizartinib, and (d) no binding was observed in U937
cells both in the presence or absence of TKIs.
57
Figure 12: Quantified binding signals of anti-His tag secondary antibody to FLT3-scFv in the presence or absence of TKIs -
Heterozygous FLT3-ITD AML cell line MOLM-13 and AML cell line not expressing FLT3 U937 cells were treated with different
concentrations (16μM or 33μM) of FLT3-scFV in the absence of TKIs or after treatment with either 10nM midostaurin or 5nM
quizartinib. The binding was measured via flow cytometry by analyzing the mean fluorescence intensity (MFI) of PE-conjugated
Anti-His tag secondary antibody and normalizing data to untreated cells. Bar graphs showing peak shift quantified based on MFI
(A-D). (a) FLT3-scFv binds to MOLM-13 cells with binding intensify in the presence of midostaurin (p=0.0253), and (b) no binding
was observed in U937 cells both in the presence or absence of midostaurin although (p=<0.0001). (c) FLT3-scFv binds to MOLM-
13 cells with binding intensify in the presence of quizartinib (p=0.0258), and (d) no binding was observed in U937 cells both in
the presence or absence of quizartinib (p= 0.0826). Data represented as mean ± SD and in quadruplets (n=4) figures A-C or figure
D in triplicate (n=3).
58
3.3 FLT3 inhibitors enhance the anti-leukemic activity of α-FLT3-scFv in FLT3-ITD
positive AML
To assess the effects of combination therapy, the anti-proliferative activity of anti-FLT3
scFv alone or in combination with FLT3 inhibitors (midostaurin or quizartinib) on MOLM-13,
FLT3-ITD positive cell line was performed at 48 and 72 hours. Proliferation assay using trypan
blue staining demonstrated that FLT3 mutant (MOLM-13) cells were sensitive to treatment with
FLT3-scFv alone and in combination with either midostaurin or quizartinib in a dose-dependent
manner. Moreover, p values from one-way ANOVA showed a difference among groups at 48 and
72 hours, however, it did not reach statistical significance (p = 0.1131; p=0.0748 respectively) as
shown in Figures 3.3.1a and 3.3.1b. This result could be attributed to the fact that 10nM
midostaurin treatment is too low to attain the effective concentration required to observe synergy
with the dual treatment. On the other hand, a statistically significant difference was observed in
the quizartinib treated group at both 48 and 72 hours (p = 0.0009; p=0.0001 respectively).
Following one-way ANOVA, Dunnette’s Multiple Comparison test was done to compare 10μM
FLT3-scFv alone or in combination (5nM quizartinib + 10μM FLT3-scFv) at 72 hours.
Interestingly, our result indicates a significant difference (0.66 vs 0.38; p=0.0042) between these
groups, suggesting a synergistic effect at this drug concentration (Figures 3.3.1c and 3.3.1d). In
addition, 72-hour post-treatment with 5nM quizartinib vs dual treatment with 10μM scFv yielded
a 0.74 vs 0.36-fold changes (p= 0.0017). Collectively, data from our cell count demonstrated that
FLT3 mutant cells (MOLM-13) were more sensitive to dual treatment with 5nM quizartinib and
10μM FLT3-scFv when compared to quizartinib or anti-FLT3-scFv treatment alone.
59
The anti-leukemic activity of TKIs and anti-FLT3-scFv was also evaluated using the cell
counting kit-8 (CCK-8), a sensitive colorimetric cell viability assay that produces a water-soluble
formazan dye upon reduction in the presence of an electron carrier. Results from the CCK-8 assay
showed a similar trend as observed with the trypan blue assay (Figure 3.3.2). However, a slight
increase in cell viability was observed in the 10nM midostaurin treated group when compared to
the untreated condition or cells treated with anti-FLT3-scFv alone at 48- and 72 hours post-
treatment. Since CCK-8 depends on the metabolic activity of living cells via measuring the
dehydrogenase activity, our result could be attributed to the fact that at this very low dose (10nM)
of midostaurin, the cells might be undergoing some unknown metabolic changes which in turn
increases the dehydrogenase activity hence the high absorbance recorded in this treatment group.
On the other hand, MOLM-13 cells treated with 5nM quizartinib indicate the strongest effect with
the dual treatment (quizartinib and FLT3-scFv) at 48 and 72 hours when compared to the untreated
condition or either treatment given alone at the tested concentrations (p = 0.0069 and p = 0.0011)
respectively. Following one-way ANOVA, Dunnette’s Multiple comparison test was done to
compare 10μM FLT3-scFv alone or in combination (5nM quizartinib + 10μM FLT3-scFv) at 72
hours. Interestingly, our result indicates a significant difference (0.72 vs 0.46; p=0.0274) between
these groups, suggesting a synergistic effect at this drug concentration (Figures 3.3.2c and 3.3.2d).
In addition, 72-hour post-treatment with 5nM quizartinib vs dual treatment with 10μM scFv
yielded a 0.84 vs 0.46-fold changes (p= 0.0051). Overall, a significant decrease in proliferation in
response to the dual therapy was observed in MOLM-13 cells treated with quizartinib compared
to midostaurin at the concentrations investigated.
60
Figure 13: Effect of dual treatment with α-FLT3-scFv and FLT3-inhibitors on FLT3-ITD positive cell proliferation. (A-D)
Trypan blue viability assay was performed in MOLM-13 (FLT3-ITD) cells treated with different concentrations (1μM or 10μM)
of α-FLT3-scFv in the in the absence of TKIs or after treatment with either 10nM midostaurin or 5nM quizartinib for 48 hours
(left) and 72 hours (right). The number of live cells was normalized to untreated cells and represented as % cell viability. Data
represented as mean ± SD. (A) Bar graphs represent experiments done in triplicates n=3. (B-D) Bar graphs represent
experiments done twice n=2.
61
Figure 14: Antileukemic activity of α-FLT3-scFV and FLT3-inhibitors dual treatment in AML cells. (A-D) CCK-8 assay cell
viability assay was performed in MOLM-13 (FLT3-ITD) treated with different concentrations (1μM or 10μM) of α-FLT3-scFV in
the absence of TKIs or after treatment with either 10nM midostaurin or 5nM quizartinib for 48 hours (left) and 72 hours (right).
The number of live cells was normalized to untreated cells and represented as % cell viability. Data represented as mean ± SD.
(A-B) Bar graphs represent experiments done in triplicates n=3. (C-D) Bar graphs represent experiments done twice n=2.
62
3.4 FLT3 inhibitors and anti-FLT3-scFv induce apoptosis of FLT3-ITD cells
To assess the effect of the dual treatment on apoptosis/cell death, we carried out Annexin
V-based flow cytometry analysis at 48- and 72 hours post-treatment. Based on data from binding
and proliferation assays, a fixed concentration of midostaurin (10nM) and quizartinib (5nM) was
administered alone or in combination with either 1μM or 10μM anti-FLT3 scFv was used in the
apoptosis analysis. Analysis from apoptosis assay was consistent with that observed with
proliferation assay. FLT3-ITD positive cells, MOLM-13 cells, were sensitive to treatment with
FLT3-scFv alone and in combination with either midostaurin or quizartinib. Moreover, no
significant difference was observed with the combined treatment (10nM midostaurin + 10μM
scFv) when compared with cells treated with the 10μM anti-FLT3-scFv alone at both 48 and 72
hours (Figures 3.4.1 and 3.4.2). As previously mentioned, increasing this dosing concentration of
midostaurin may lead to a more effective therapy outcome. On the other hand, combined treatment
of 5nM quizartinib and anti-FLT3 scFv resulted in increased apoptosis/cell death of MOLM-13
cells (Figures 3.4.3 and 3.4.4) in a dose-dependent manner when compared to either treatment
administered alone at both 48 and 72 hours.
Quantitative analysis was evaluated by combining the flow cytometry events recorded in
Q1 and Q2 (representing necrosis and late apoptosis cells respectively) and collectively presented
as percent apoptotic cell death. This calculation was performed by combining three independent
experiments (n=3) in the midostaurin treated group and two independent experiments (n=2) in the
quizartinib treatment group. Although MOLM-13 cells treated with either TKIs or anti-FLT3-scFv
were sensitive to treatment, bar graphs from the midostaurin treatment group fail to show a
significant difference when comparing dual treatment vs cells treated with a single treatment as
shown in Figure 3.4.5a and 3.4.5b. Moreover, combined treatment of 5nM quizartinib and anti-
63
FLT3 scFv resulted in increased apoptosis/cell death of MOLM-13 cells in a dose-dependent
manner (p = 0.0005 and p= 0.0001 respectively) at 48 hours and 72 hours as shown in Figure
3.4.5c and 3.4.5d. Interestingly at 48 hours, treatment with 1μM scFv alone and in combination
with 5nM quizartinib yielded a 1.50 vs 3.5-fold change in cell death (p = 0.0093); 10μM scFv
alone and in combination with 5nM quizartinib yielded a 2.22 vs 4.11 fold change (p = 0.0044);
and 5nM quizartinib vs dual treatment with both 1μM and 10μM scFv yielded a 2.78 vs 3.50 vs
4.42 fold changes (p= 0.4117 and p = 0.0234) respectively. 72 hours apoptotic analysis following
treatment with 1μM scFv alone and in combination with 5nM quizartinib yielded a 0.87 vs 2.27-
fold change (p = 0.0149); 10μM scFv alone and in combination with 5nM quizartinib yielded a
1.55 vs 4.40-fold change (p = 0.0003); and 5nM quizartinib vs dual treatment with both 1μM and
10μM scFv yielded a 1.67 vs 2.27 vs 4.40-fold change (p= 0.3431 and p = 0.0004) respectively.
64
Figure 15: Apoptosis of FLT3-ITD positive cell after dual treatment with α-FLT3-scFv and midostaurin at 48 hours. Apoptosis
of FLT3-ITD + cells (MOLM-13) was measured by flow cytometry analysis using APC conjugated annexin V and propidium iodide
(PI) staining. Cells were treated with different concentrations (1μM or 10μM) of α-FLT3-scFv in the presence or absence of 10nM
midostaurin at 48 hours. In all experiments to determine MOLM-13 apoptosis, the following controls were set to establish the
appropriate quadrant allocation. Flow cytometry density plots of MOLM-13 stained with annexin V (X-axis) and PI (Y-axis). Shown
in the lower right quadrant (Q3) is Annexin V positive/PI negative staining which indicates early apoptosis. High annexin V and
PI staining in the right upper quadrant (Q2) implies late apoptosis, while low annexin V and high PI staining in the left upper
quadrant (Q1) indicate necrosis. Q4 in the lower left quadrant represents the viable cells. In all experiments to determine MOLM-
13 apoptosis, the following controls were set to establish the appropriate quadrant allocation.
65
Figure 16: Apoptosis of FLT3-ITD positive cell after dual treatment with α-FLT3-scFv and midostaurin at 72 hours. Apoptosis
of FLT3-ITD + cells (MOLM-13) was measured by flow cytometry analysis using APC conjugated annexin V and PI staining. Cells
were treated with different concentrations (1μM or 10μM) of α-FLT3-scFv in the presence or absence of 10nM midostaurin at 72
hours. In all experiments to determine MOLM-13 apoptosis, the following controls were set to establish the appropriate quadrant
allocation. Flow cytometry density plots of MOLM-13 stained with annexin V (X-axis) and PI (Y-axis). Shown in the lower right
quadrant (Q3) is Annexin V positive/PI negative staining which indicates early apoptosis. High annexin V and PI staining in the
right upper quadrant (Q2) implies late apoptosis, while low annexin V and high PI staining in the left upper quadrant (Q1) indicate
necrosis. Q4 in the lower left quadrant represents the viable cells. In all experiments to determine MOLM-13 apoptosis, the
following controls were set to establish the appropriate quadrant allocation.
66
Figure 17: Dual treatment with α-FLT3-scFv and quizartinib induces apoptosis in FLT3-ITD positive cells at 48 hours.
Apoptosis of FLT3-ITD + cells (MOLM-13) was measured by flow cytometry analysis using APC conjugated annexin V and PI
staining. Cells were treated with different concentrations (1μM or 10μM) of α-FLT3-scFv in the presence or absence of 5nM
quizartinib at 48 hours. In all experiments to determine MOLM-13 apoptosis, the following controls were set to establish the
appropriate quadrant allocation. Flow cytometry density plots of MOLM-13 stained with annexin V (X-axis) and PI (Y-axis). Shown
in the lower right quadrant (Q3) is Annexin V positive/PI negative staining which indicates early apoptosis. High annexin V and
PI staining in the right upper quadrant (Q2) implies late apoptosis, while low annexin V and high PI staining in the left upper
quadrant (Q1) indicate necrosis. Q4 in the lower left quadrant represents the viable cells. In all experiments to determine MOLM-
13 apoptosis, the following controls were set to establish the appropriate quadrant allocation.
67
Figure 18: Dual treatment with α-FLT3-scFv and quizartinib induces apoptosis in FLT3-ITD positive cells at 72 hours.
Apoptosis of FLT3-ITD + cells (MOLM-13) was measured by flow cytometry analysis using APC conjugated annexin V and PI
staining. Cells were treated with different concentrations (1μM or 10μM) of α-FLT3-scFv in the presence or absence of 5nM
quizartinib at 72 hours. In all experiments to determine MOLM-13 apoptosis, the following controls were set to establish the
appropriate quadrant allocation. Flow cytometry density plots of MOLM-13 stained with annexin V (X-axis) and PI (Y-axis). Shown
in the lower right quadrant (Q3) is Annexin V positive/PI negative staining which indicates early apoptosis. High annexin V and
PI staining in the right upper quadrant (Q2) implies late apoptosis, while low annexin V and high PI staining in the left upper
quadrant (Q1) indicate necrosis. Q4 in the lower left quadrant represents the viable cells. In all experiments to determine MOLM-
13 apoptosis, the following controls were set to establish the appropriate quadrant allocation.
68
Figure 19: Quantified antileukemic activity of α-FLT3-scFv and FLT3-inhibitors dual treatment in AML cells. Apoptosis of
FLT3-ITD + (MOLM-13) cells were treated with different concentrations (1μM or 10μM) of α-FLT3-scFv in the absence of FLT3
inhibitors or after treatment with either 10nM midostaurin or 5nM quizartinib for 48 hours (left) and 72 hours (right). Apoptosis
was measured via flow cytometry assessment of annexin V and PI staining. (A-D) Bar graphs represent percent apoptotic cells
calculated using late apoptotic and necrosis cells (Q1+Q2) with data presented as % apoptotic cell death. All experiments were
performed twice (n=2), and data represented as mean ± SD.
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Chapter 4: Discussion
AML is a hematological disease accounting for about 33% and 80% of leukemia cases in
children and adults respectively, hence making it the second most common leading cause of newly
diagnosed leukemia in the USA (Chen et al., 2017 and De Kouchkovsky & Abdul-Hay, 2016).
The utilization of genomic sequencing has made it easier to understand the diversity of this disease
which in turn helps with treatment decisions. Over the year progress has been made in developing
several therapies targeting AML pathways such as the implementation of immunotherapies
(gemtuzumab), drugs targeting apoptotic pathways in AML (venetoclax), the FLT3 kinase receptor
(midostaurin and gilteritinib), and mitochondria pathway (ivosidenib and enasidenib). In addition
to these FDA-approved drugs, several clinical trials utilizing other targeted therapy are currently
ongoing. AML is a difficult disease to treat due to the high degree of heterogeneity it acquires.
Hence, if not totally eradicated at the outset, the blast cells become resistant to subsequent
therapies.
Mutation in the FMS like tyrosine kinase accounts for approximately 30% of AML cases
with FLT3-ITD accounting for 25% of the recorded cases (Chen et al., 2017 and Sexauer & Tasian
2017). Therefore, targeting FLT3 is a beneficial therapeutic approach. Although the discovery of
targeted therapeutic pathways like monoclonal antibodies and FLT3 inhibitors has made progress
in terms of treatment and improving the overall survival in AML patients, the 5-year OS in adult
patients newly diagnosed with this disease is still relatively poor (Kantarjian et al., 2021; Castaigne
et al., 2012; Bonnevaux et al., 2021 and Yeung et al., 2020). As with many other diseases and
cancer cases, resistance and relapse continue to be of great challenge.
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Midostaurin and gilteritinib are FLT3 inhibitors approved for use in FLT3-ITD mutated
patients. Midostaurin can be used in combination with traditional chemotherapy in patients with
relapsed/refractory AML. However, only gilteritinib is approved as a monotherapy in R/R AML
patients (Hou & Tien, 2020). Although the therapeutic benefit of these FLT3 inhibitors seems
promising, issues with both treatment-related and acquire resistance continues to be a major
challenge in eradicating this disease. Studies have confirmed several mechanisms through which
AML patients confer resistance to FLT3 inhibitors. This resistance mechanism ranges from
molecular alterations of the FLT3-ITD allele and the inhibitory activity resulting from a variety of
cellular mechanisms, such as the allele-specific FLT3-ITD or TKD mutations, FGF2-mediated
resistance. Cytochrome P450 (CYP3A) in the liver and the bone marrow stromal protection (such
as CYP3A and cytokines secreted in this environment) is another known contributor to resistance.
Increased plasma production of FLT3 ligand and activation of other signaling pathways following
treatment with FLT3 inhibitors possess yet another mechanism of resistance (Kurokawa et al.,
2008, Traer et al., 2016, Scholl et al., 2020, Kiyoi et al., 2020, and Lam & Leung 2020).
To overcome this challenge with resistance, current preclinical and clinical studies are
introducing the concept of combination treatment with two or more drugs. Combination of
standard chemotherapy agents with FLT3 inhibitors such as midostaurin has been shown to
increase the OS in AML patients. Therefore, based on FDA approval midostaurin can now be
incorporated as a standard care treatment in FLT3 mutated patients. Sorafenib has also been shown
to be beneficial when combined with traditional chemotherapy (Röllig et al., 2015). Crenolanib,
quizartinib (NCT02668653), and gilteritinib (NCT02236013, NCT02310321) are other FLT3
inhibitors currently being tested in combination with standard chemotherapy in clinical trials (Lam
& Leung 2020). Since patients with FLT3 mutation also present with other co-morbidities,
71
combining two drugs with different targets can be advantageous in overcoming the current
challenges with resistance. Preclinical and clinical studies utilizing FLT3 inhibitors such sorafenib,
quizartinib, and gilteritinib in combination with low-intensity drugs such as HMA (azacytidine or
decitabine) demonstrated synergy and better efficacy in inhibiting AML (Lam & Leung 2020, Gill
et al., 2015, and Swaminathan et al., 2021).
Introducing the concept of bispecific antibodies targeting two different antigens is another
approach widely explored to overcome challenges with resistance. Immunotherapy has been
incorporated into this construct in several studies, with one arm of the antibody targeting the
protein of interest and the other enhancing T-cell activation. 7370 Anti-FLT3 CD3 and CD123-
cross-over dual variable T-cell engager (CD123-CODV-TCE) are two bispecific antibodies that
have been described in preclinical studies (Bonnevaux et al., 2021 and Yeung et al., 2020).
Following that, chimeric antigen receptor (CAR)-T-cells have been thoroughly investigated, with
numerous clinical trials utilizing CAR-T-cells as a targeted therapy for AML currently underway.
The introduction of CAR-T Cell therapy in Acute lymphoid leukemia (ALL) malignancies has
promoted research in utilizing CAR-T cells in AML patients. FLT3-CAR T cells are currently in
the preclinical stage of development and have shown encouraging outcomes. The main challenges
to treating refractory AML using CAR-T cells are AML target antigen via secretory molecules, a
lack of specific antigen such as CD19 used in ALL, and CAR-T cell therapy-related toxicity such
as cytokine storm following CAR-T cell therapy (Gu et al., 2020). To overcome these challenges,
targeting multiple antigens (dual targeting) on cancer cells at the same time is a proposed
mechanism to overcome this challenge (Gu et al., 2020).
Recently a group developed a bispecific FLT3scFv/NKG2D-CAR T cells to efficiently kill
leukemic blast in FLT3-ITD positive cells (Li et al., 2022). Utilizing gilteritinib, an FLT3 inhibitor
72
that upregulates FLT3 and NKG2DL expression in AML cells, and the subsequent introduction of
this bispecific FLT3scFv/NKG2D-CAR T cell construct, they show synergistic effect in
eliminating AML blast cells (Li et al., 2022). Collectively, this current study supports the use of
gilteritinib in combination with FLT3scFv/NKG2D-CAR T cells as a treatment for R/R FLT3
mutated AML (Li et al., 2022). Additionally, our group has developed two antibody-based targeted
therapy namely: anti-FLT3 scFvs and anti-FLT3 A192. This FLT3-A192 was designed by fusing
anti-FLT3 scFv with an elastin-like protein peptide (ELP), A192 (Park et al., 2020). These scFv
and ELPs can be constructed into a bispecific and co-assemble antibody-directed therapy
respectively to efficiently target leukemic cells. Preliminary studies using both anti-FLT3 scFv
and ELPs demonstrated potency in eliminating FLT3 positive leukemic blasts. Herein, this
research aims to target FLT3-ITD cells with a combination of our in-house antibody-based therapy
and FLT3 inhibitors.
It has been reported that treating FLT3 mutated cells with FLT3 inhibitors such as
midostaurin, quizartinib, and sorafenib promotes cell surface localization which is achieved via
inducing glycosylation of the mutant FLT3 (Reiter et al., 2018). Additionally, by introducing the
concept of chimeric antigen receptor (CAR) T-cell therapy, another group demonstrated that the
treatment of FLT3-ITD cells with crenolanib induces FLT3 cell surface localization and the
addition of FLT3-CAR T-cells enhanced the antileukemic activity against crenolanib treated
FLT3-ITD positive cells (Jetani et al., 2018). To confirm this, we pre-treated MOLM-13, FLT3-
ITD positive cells known to be heterozygous for this mutation with two selected FLT3 inhibitors:
midostaurin and quizartinib. Heterozygosity, in this case, means these MOLM-13 cells present
with one WT and one mutant (ITD positive) gene, unlike MV4-11 cells which are known to be
homozygous for this mutation. THP-1 are FLT3-WT expressing cells and were introduced as a
73
negative control. FLT3-WT cells are fully glycosylated hence they have a substantial amount of
FLT3 on their cell surface and require binding of the FLT3 ligand to be activated. Conversely,
FLT3 mutant cells tend to be under-glycosylated and located mainly in the intracellular
compartment of the cells (Schmidt-Arras et al., 2005). Consistent with other studies, midostaurin
and quizartinib failed to improve cell surface localization when tested with FLT3-WT THP-1 cells
and FLT3 negative expressing (U937) cells in our study. Interestingly and contrary to a study
where it was demonstrated that the FLT3 surface expression was barely increased after treatment
with FLT3 inhibitors in MOLM-13 cells (Reiter et al., 2018), our result indicates that treatment
with FLT3 inhibitors (midostaurin and quizartinib) promotes cell surface expression in FLT3-ITD
positive (MOLM-13) cells. In this study, TKI-treated MV4-11 cells also demonstrated an increase
in total FLT3 protein levels, which was likely due to the upregulation of FLT3 mRNA expression
(Reiter et al., 2018). While the overall FLT3 mRNA level in MOLM-13 cells was unaffected by
quizartinib treatment. This finding was attributed to the allelic expression favoring the WT allele
as observed with the increased difference in the ratio of FLT3-WT to FLT3-ITD expressing cells
(Reiter et al., 2018). The changes in FLT3 surface expression after treatment with FLT3 inhibitors
may differ in MV4-11 and MOLM-13 cells hence this cannot be disputed until we carry out an
experiment using MV4-11 cells. As with our results, another study reported a decrease in the
proliferation of MOLM-13 cells after treatment with quizartinib (Li et al., 2020).
In the later part of this project, anti-FLT3 scFv were introduced to test how dual treatment
which involves first pre-treatment with FLT3-inhibitor and addition of antibody-based therapy
enhances binding of the scFv to FLT3 expressed on the cell surface. Combination therapy is one
proposed mechanism to overcome the current issues of FLT3 resistance to treatment (Chen et al.,
2017; Kiyoi et al., 2019; Reiter et al., 2018; Nagai et al., 2018; Li et al., 2020; Zhu et al, 2021 and
74
Eisfelder et al., 2021). Based on results from the initial study, we picked an optimal concentration
where the binding intensity was considered the highest. Therefore, 10nM was selected for
midostaurin and 5nM for the quizartinib treated group. Our result confirms the binding of FLT3-
scFv to only MOLM-13 cells and further indicates that pre-treatment with FLT3 inhibitors
(midostaurin and quizartinib) enhances binding to these cells. Although qualitative analysis of
midostaurin and FLT3 negative (U937) cells indicated no binding, one-way ANOVA from this
group showed significance. Raw data from all four experiments consistently indicate a slightly
higher signal in the untreated and midostaurin treated group compared to the groups treated with
FLT3 scFv. The discrepancy is attributed to the fact that U937 does not express FLT3 and hence
anti-FLT3 scFv which is masked on the cell surface is competing with the anti-his tag now
introduced for visualization. Competition with both antibodies which are non-specific for the U937
cells reduces the signals in the treated group due to the non-specific binding observed.
Next, we assessed the anti-proliferative activity of our FLT3-scFv alone and in
combination with FLT3 inhibitors as several studies demonstrate that dual treatment with FLT3
inhibitors and drugs targeting other pathways in AML result in better anti-leukemic activity (Reiter
et al., 2018; Nagai et al., 2018; Li et al., 2020; Zhu et al, 2021 and Eisfelder et al., 2021). Trypan
blue count, CCK8, and apoptosis assays were used to assess cell proliferation and death at 48 and
72 hours. Data from all three assays were consistent across the board and our results demonstrated
that combination treatment of quizartinib and anti-FLT3 scFv showed a more significant anti-
proliferative effect on MOLM-13 cells in a dose-dependent manner when compared with each
agent alone. Unfortunately, there was no significant effect on cell proliferation in cells treated with
midostaurin and our FLT3 scFv. Midostaurin as a first-generation, type-I FLT3 inhibitor is known
to be less specific than quizartinib which is more potent and more toxic to cells (Hou & Tien, 2020
75
and Ley et al., 2013). Based on these known characteristics, a higher dose of midostaurin may be
needed to achieve the desired concentration required to exert potency. Therefore, to optimize these
results, I aim to test multiple concentrations of midostaurin at an increased dose. To further
improve this study other assays which include measuring the synergistic effect on cell cycle
progression, protein quantification, and in-vivo studies will be needed. Although our result
indicates no binding of our single or combined agent to FLT3 negative (U937) cells, anti-
proliferative assays using a negative cell line need to be performed to rule out off-target effects.
Several studies confirm by western blot the presence of the two forms of FLT3 protein
namely, the partially glycosylated 130kDa and the fully glycosylated 150kDa (Schmidt-Arras et
al., 2005). FLT3-WT predominately expresses the fully glycosylated 150kDa protein while cells
with FLT3-ITD mainly express the 130kDa protein. A study reported that 24-hour treatment with
FLT3 inhibitors increased FLT3 fully glycosylated form while reducing the immature form in
FLT3 mutant cells (Reiter et al., 2018). To confirm this, I aim to perform western blot assays with
FLT3 mutated and WT cells in the presence and absence of FLT3 inhibitors (midostaurin and
quizartinib). I expect to see increased phosphorylation in the fully glycosylated FLT3 protein in
FLT3 mutant cells treated with FLT3 inhibitors when compared to the untreated conditions. FLT3
inhibitors are known to not possess any substantial effect on the FLT3-WT cells, hence I do not
expect to see any changes in the FLT3 glycosylation pattern in these cells. As with the difference
in the glycosylation pattern observed, studies have also revealed that FLT3-WT and mutated cell
lines activate different signaling pathways. FLT3-ITD mutation leads to the constitutive activation
of downstream proliferative signaling pathways such as the Ras/MAPK, PI3, and ERK pathways
(Kiyoi et al., 2002; Mizuki et al., 2000; and Hayakawa et al., 2000). Unlike the FLT3-WT, FLT3-
ITD mutated cells also lead to aberrant activation of STAT5, hence phosphorylation of STAT5 is
76
another downstream protein of particular interest. Western blot studies utilizing FLT3-ITD
mutated cells (MOLM13 and MV4-11) cells demonstrated that the α-FLT3-A192 fusion protein
developed by our group effectively downregulates STAT5 and ERK pathways after 6- and 24-
hours treatment when compared to the untreated condition (Park et al., 2020). To investigate if our
combination therapy exerts synergistic anti-leukemic effects through upregulation of fully
glycosylated FLT3 expression leading to a pronounced decrease in phosphorylation of STAT5, I
plan to perform immunoblot assays. In addition, imaging studies could also be performed to show
FLT3 protein localization and surface binding before and after treatment with FLT3 inhibitors as
several studies have reported the influence of glycosylation and difference in protein localization
(Reiter et al., 2018). While our results suggest anti-FLT3 scFv synergizes with FLT3 inhibitor
(quizartinib) when used in a combinatory therapy in-vitro, a combination index would be a better
approach to confirm this synergistic effect. Hence to properly demonstrate this synergy, I plan to
test multiple doses of FLT3 inhibitors and anti-FLT3 scFv to get the optimal dose for each
individual treatment needed to achieve an effective therapeutic goal.
Although scFvs are considered favorable therapeutic options for in-vivo and in-vitro
studies in cancer among other diseases, there has been some concern questioning the efficacy of
scFv with issues referencing the stability and proposed short half-life of these antibodies. Our
group has developed a fusion protein called FLT3-A192 to target AML (Park et al., 2020). In-vivo
studies utilizing FLT3-A192 showed better retention of the FLT3-A192 in the bone marrow when
compared to the mAbs. In addition, an increase in OS and a reduction in tumor burden were
observed in mice treated with FLT3-A192 (Park et al., 2020). These findings aligned with the
rationale that ELPs can remain in circulation longer than the scFv since they can avoid glomerular
filtration. To address this concern, I plan to carry out in-vivo studies utilizing ELP as they exert a
77
more potent pharmacokinetic profile and are easier to administer. Also, the ELP possesses a longer
half-life when compared to the scFv and hence has a higher therapeutic advantage for in-vivo
studies.
In conclusion, by exploring the use of flow cytometry using CD135 antibody conjugated
to APC, we confirm that FLT3 inhibitors are only able to promote cell surface expression of FLT3
in FLT3 mutated cells and not in FLT3-WT cells. Next, utilizing flow cytometry with anti-his tag
conjugated to PE, we showed increased binding of our FLT3-scFv in the presence of FLT3
inhibitors. As with the increased binding, we observed a decrease in proliferation and increased
cell death in the quizartinib treated group. Taken together, our current findings suggest combining
FLT3 inhibitors with our in-house developed antibody-based therapy has the potential to enhance
the efficacy of FLT3 TKIs in the treatment of FLT3-ITD positive leukemic cells.
78
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Abstract (if available)
Abstract
Acute Myeloid leukemia (AML) is a hematological disorder characterized by clonal expansion and proliferation of undifferentiated myeloid cells. Mutations in the FMS-like tyrosine kinase (FLT3) gene are present in 25-30% of AML cases. FLT3-(ITD internal tandem duplicate) is characterized as a 15-150 base pair insertion resulting in conformational changes in the juxtamembrane domain of the FLT3 receptor. FLT3-ITD is the most frequent mutation in AML mutation and is associated with poor prognosis and leukocytosis. FLT3 mutations result in constitutive activation of the FLT3 kinases activity and activation of downstream signaling pathways leading to increased proliferation and resistance to apoptosis. Several FLT3 small molecule inhibitors have been developed and some have been FDA approved (midostaurin and gilteritinib) for the treatment of patients with AML. Yet, even with these targeted therapies, the majority of patients with FLT3 mutations die of their disease as the 5-year overall survival rate is still relatively low. Since FLT3-ITD is mainly expressed in the intracellular compartment of the cells with little expression detected on the cell surface, it has been demonstrated that treating these FLT3-ITD positive cells with small molecules, inactivating point mutations, or co-expression with other protein tyrosine phosphatases (PTPs) promotes complex glycosylation and surface localization of these receptors (Schmidt-Arras et al., 2005). By leveraging this mechanism, my research aims to promote cell surface localization of FLT3-ITD using FLT3-Tyrosine kinase inhibitors (TKIs) and the subsequent introduction of our in-house anti-FLT3-scFv to enhance efficacy and reduce cell viability in FLT3-ITD positive AML cell lines. Collectively, our result confirms that FLT3 inhibitors promote cell surface expression of FLT3 in FLT3 mutated cells but not in FLT3-WT cells. In addition, we show that dual treatments of FLT3 inhibitors with anti-FLT3-scFv significantly reduced cell viability in these cells when compared with either treatment alone. Taken together, our current findings suggest combining FLT3 inhibitors with antibody-based therapy has the potential to enhance the efficacy of FLT3-TKIs in the treatment of FLT3-ITD positive leukemic cells. To further validate this in-vitro study, in-vivo studies will be needed to show the therapeutic potential of the combination of FLT3-inhibitors with FLT3-directed antibody treatment against FLT3-ITD driven AML in preclinical models.
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Creator
Onyemaechi, Sandra Erere-Nwa (author)
Core Title
Investigating the effect of FLT3 tyrosine kinase inhibitors and anti-FLT3 antibody-based therapy in acute myeloid leukemia
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School of Pharmacy
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Master of Science
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Pharmaceutical Sciences
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2022-08
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07/29/2023
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Tags
acute myeloid leukemia
FLT3
FLT3-ITD
FLT3-TKIs
midostaurin
quizartinib