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Investigating the effects of targeting CD99 on T cells to enhance their antileukemia activity
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Investigating the effects of targeting CD99 on T cells to enhance their antileukemia activity
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Investigating the effects of targeting CD99 on T cells to enhance their antileukemia activity.
By
Shephali Milind Kadam
A Thesis Presented to the
FACULTY OF THE USC MANN SCHOOL OF PHARMACY
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(PHARMACEUTICAL SCIENCES)
August 2024
Copyright 2024 Shephali Milind Kadam
ii
Dedication
With immense gratitude, I dedicate my thesis
To my father, Milind Kadam, for inspiring me to pursue a path in science. You are my role model
and mentor. Thank you for teaching me to trust my instincts and to always dream bigger. You
have always believed in me and continue being my biggest supporter. Thank you for supporting
my decisions and inspiring me to pursue a career in science.
To my mother, Rupali Kadam, for showing me by example that it is possible to have a successful
career while raising a family. Thank you for your encouragement and for all the sacrifices you
had to make for the family.
iii
Acknowledgements
First and foremost, I’d like to express my utmost gratitude to my advisor, Dr. Houda
Alachkar for supporting and encouraging me for the past two years. Thank you for teaching me
and being patient as I experienced successes and challenges throughout my learning process. I
would like to thank my committee members, Dr. J. Andrew MacKay and Dr. Yong ‘Tiger’ Zhang
for their time and inputs regarding my thesis.
I would also to express my heartfelt gratitude to all my lab members, with a special
mention to Mateusz Pospiech and Atham Ali, for training and assisting me. Thank you for being
so patient with me, for helping me master my techniques, for being so encouraging, for teaching
me how to deal with negative outcomes and most importantly for being a friend. I would like to
thank my lab mates and fellow batchmates, Kanaka Dhuri and Xiaochen Zhang, for supporting
me, motivating me and being someone I could always count on. Thank you for making my days
memorable and filled with laughter. I would also like to thank Sandra Onyemaechi for being
available to provide her time, help and input for the project along with all the volunteers who
graciously donated their blood enabling me to successfully complete my project.
I would like to thank my friends, with a special mention to Ruchira Joshi and Palak
Agarwal, for providing me with the sense of family away from home and for being constant
pillars of support in the face of all the challenges I faced. It was because of you guys that I found
the courage to live independently and experience some of the most memorable years of my life.
Most importantly, I am grateful to my parents, Milind and Rupali Kadam, for supporting
my ambition and providing me with all the means possible to realizing all my hopes and dreams.
It is with your encouragement that I found the courage to move away from home and achieve
iv
this milestone. I would also like to thank my brother, Priyal Kadam, for being a confidant. I hope
I can continue to make you all proud. I love you all.
Thank you.
v
TABLE OF CONTENTS
Dedication…………………………………………………………………………………………ii
Acknowledgements………………………………………………………………………….…....iii
Abbreviations…………………………………………………………………………………….vii
List of Tables……………………………………………………………………………………...ix
List of Figures……………………………………………………………………………………..x
Abstract………………………………………………………………………………...…….….xiii
Chapter 1: Background……………………………………………………………………………1
T cells……………………………………………………………………………………...1
CD99………………………………………………………………………………………9
CD99 gene and protein….…………………………………………………………………9
CD99 expression…………………………………………………………………………14
Role of CD99 in T cells…………………………………………………………………..21
Role of CD99 in cancer...………………………………………………………………...23
Role of CD99 in Acute myeloid Leukemia………………………………………………25
Anti-CD99 antibodies…………………………………………………………………….28
Anti-CD99 ScFv ELP…………………………………………………………………….29
Chapter 2: Materials and Methods……………………………………………………………….32
Sample Collection from Healthy Donors…………………………………………………32
Peripheral Blood Mononuclear Cell (PBMC) Isolation…………………………………..32
Stimulation and Expansion of T cells…………………………………………………….33
Treatment with A192 and -CD99-A192 ELPs…………………………………………..33
vi
Binding assay…………………………………………………………………………….33
Cell counting and proliferation assays……………………………………………………34
T cell phenotyping………………………………………………………………………..35
RNA Sample Preparation and RNA-seq Data Analysis………………………………….36
Cytokine Release Profile Analysis……………………………………………………….37
Co-culture Apoptosis Assay……………………………………………………………...38
Luciferase Assay…………………………………………………………………………39
Statistical Analysis……………………………………………………………………….40
Chapter 3: Results………………………………………………………………………………..41
-CD99-A192 induces cell aggregation in T cells.……………………………………....41
-CD99-A192 increases cell proliferation in T cells…………………………………….43
-CD99-A192 increases the expression of activation markers but does not affect
the T cell phenotypes………………………………………………………………..……46
-CD99-A192 alters gene expression in T cells………………………………………….49
-CD99-A192 shows altered cytokine release profile in T cells………………………….52
-CD99-A192 treated T cells exhibit enhanced cytotoxicity against leukemic cells……..54
Chapter 4: Discussion…………………………………………………………………………….57
Bibliography………………………………………………………………….…………………..63
vii
Abbreviations
CD99 – Cluster of Differentiation 99
AML – Acute Myeloid Leukemia
-CD99-A192 - Anti-CD99-A192
scFv - Single Chain Variable Fragment
ELP - Elastin-like Polypeptides
IL-2 - Interleukin 2
TCR - T-cell Receptor
MHC - Major Histocompatibility Complex
HSC - Hematopoietic Stem Cell
MPP - Multipotent Progenitor Cell
NK- Natural Killer
CD – Cluster of Differentiation
DN – Double Negative
IL4 – Interleukin 4
IL7 – Interleukin 7
IL15 – Interleukin 15
APC- Antigen-Presenting Cell
Th – T helper cells
Treg – Regulatory T cells
CAR - Chimeric Antigen Receptor (CAR)
Wt – Wild type
viii
IL6 – Interleukin 6
TNF - Tumor Necrosis Factor Alpha
IFN - Interferon Gamma
OS- Osteosarcoma
HSP70- Heat Shock Protein 70
LSC – Leukemic Stem Cell
FOXP3 – Forkhead Box P3
IL17A – Interleukin 17A
mAb – Monoclonal Antibody
T-ALL – T-cell Acute Lymphoblastic Leukemia
PBMC – Peripheral Blood Mononuclear Cell
DPBS - Dulbecco’s Phosphate-buffered Saline
RPMI - Roswell Park Memorial Institute
FBS - Fetal Bovine Serum
PHA - Phytohemagglutinin-L
CFSE - Carboxyfluorescein succinimidyl ester
DMSO – Dimethylsulfoxide
GSEA-MSigDB - Gene Set Enrichment Analysis-Molecular Signatures Database
E:T – Effector: Target
GFP – Green Fluorescent Protein
ix
List of Tables
Table 1. Cell surface markers of the T cell clusters of Bone Marrow. …………………………..17
Table 2. Cell surface markers of the T cell clusters of Thymus. ………………………………...20
x
List of Figures
Figure 1. Overall scheme of Normal Hematopoiesis (Created on BioRender) …………………...3
Figure 2. Overall scheme of T cell development (Created on BioRender) ……………………….4
Figure 3. T cells responses to antigen attacks (Waldman et al., 2020) …………………………...5
Figure 4. Activation of T cells into effector cells (Created on BioRender) ………………………6
Figure 5. Types of Adoptive T Cell Therapies (Waldman et al., 2020) …………………………..8
Figure 6. CD99 gene structure and their isoforms (Pasello et al., 2018) ………………………..10
Figure 7. Structural Representation of CD99 Isoforms (Ali et al., 2022) ……………………….11
Figure 8. Structural Representation of the Long Isoform of the CD99 Protein
(Created on PyMol) ……………………………………………………………………………...12
Figure 9. Schematic Diagram of Functions of CD99 (Created on BioRender) ……….…………13
Figure 10. CD99 expression in human tissues (From GTEx portal) ………………….…………14
Figure 11. Single Cell CD99 Expression in Bone Marrow (From The Human Protein
Atlas; available at https://www.proteinatlas.org/ENSG00000002586-
CD99/single+cell+type/bone+marrow) (Uhlen et al., 2019)…………………………………….15
Figure 12. Heat Map exhibiting Fraction of Highest CD99 expression on blood cells in
Bone Marrow; with 0 (yellow) being the lowest and 1 (black) being the highest
expression (From The Human Protein Atlas; available at
https://www.proteinatlas.org/ENSG00000002586-CD99/single+cell+type/bone+marrow)
(Uhlen et al., 2019)……………………………………………………………………………...16
Figure 13. Single Cell CD99 Expression in Thymus (From The Human Protein
xi
Atlas; available at https://www.proteinatlas.org/ENSG00000002586-
CD99/single+cell+type/thymus) (Uhlen et al., 2019)……………………………………………18
Figure 14. Heat Map exhibiting Fraction of Highest CD99 expression on blood cells in
Thymus; with 0 (yellow) being the lowest and 1 (black) being the highest expression
(From The Human Protein Atlas; available at
https://www.proteinatlas.org/ENSG00000002586-CD99/single+cell+type/thymus)
(Uhlen et al., 2019)………………………………………………………………………………19
Figure 15. CD99 Protein Concentration in Various Cancers (From The Human Protein
Atlas; available at https://www.proteinatlas.org/ENSG00000002586-CD99/disease)
(Uhlén et al., 2005)………………………………………………………………………………24
Figure 16. Hematopoiesis is AML (Created on BioRender) …………………………………….26
Figure 17. Overexpression of CD99 in AML cells (Vaikari et al., 2020) ……………………….27
Figure 18. Graphic representation of CD99 protein with the mAbs binding to different
epitopes of the protein (Pasello et al., 2018)…………………………………………………......28
Figure 19. Overview of the Anti-CD99 scFv ELP (Vaikari et al., 2020) ………………………..31
Figure 20. -CD99-A192 binds T cells and induces homotypic adhesion. ……………………..42
Figure 21. Treatment with -CD99-A192 increases cell proliferation in T cells. ………………44
Figure 22. -CD99-A192 increases expression of activation marker CD38 but does
not affect T cell phenotypes.…………………………………………………………..…………47
Figure 23. -CD99-A192 treated T cells show an altered gene expression with
upregulation of inflammatory pathways compared to control. ………………………………….50
Figure 24. -CD99-A192 treated T cells show altered expression of inflammatory
cytokines.………………………………………………………………………………...………53
xii
Figure 25. -CD99-A192 treated T cells show increased cytotoxicity against leukemic
cells.……………………………………………………………………………………………...55
xiii
Abstract
T cells are a part of the adaptive immune system who have been explored for their cytotoxic
potential as a form of immunotherapy. Cluster of Differentiation 99 (CD99) is a transmembrane
protein encoded by the MIC2 gene. It is expressed on many human tissues and almost all types of
human cells. In normal physiological conditions, CD99 plays role in lymphocyte development,
cell adhesion, cell differentiation, apoptosis, leukocyte diapedesis and protein trafficking. The
expression of CD99 is found to be higher on T cells with varying levels of expression on various
T cell subsets.
CD99 is overexpressed in many diseases including, Acute Myeloid Leukemia (AML),
presenting a potential novel therapeutic target. Our group has previously developed anti-CD99-
A192 (-CD99-A192), comprising of single chain variable fragment (scFv) and elastin-like
polypeptides (ELPs), and reported promising anti-leukemic activity in AML preclinical models.
Treatment with -CD99-A192 induced apoptosis in AML cell lines and prolonged survival in
AML xenograft models. Considering CD99's expression and role in T cell activation, in the current
study, we propose that -CD99-A192 could have a dual function, i.e., targeting leukemic cells and
activating T cells. This manuscript reports the effects of -CD99-A192 on T cells in the context
of AML.
To explore the effects of -CD99-A192 on T cells, we obtained blood samples from
healthy donors, to isolate Peripheral Blood Mononuclear Cells (PBMCs) using the Ficollcentrifugation method. We expanded T cells using cytokine expansion and treated the T cells with
xiv
our control ELP and -CD99-A192 ELP. We explored the effects of -CD99-A192 on T cells by
conducting proliferation assays using cell count method and cell trace, T cell phenotyping by flow
cytometry to understand the expression of T cell markers, activation marker expression analysis
by flow cytometry, cytokine release profile analysis and gene expression analysis. We also
explored the cytotoxic effects of the -CD99-A192-activated T cells by designing a co-culture
assay of the -CD99-A192 treated T cells and leukemic cell lines. The apoptosis was measured
by flow cytometry and luciferase assay.
We found that -CD99-A192 is effective binding to T cells and induces increased
aggregation of T cells, also known as homotypic adhesion. -CD99-A192 treatment enhances T
cell proliferation and doesn’t affect the T cell phenotype expression. -CD99-A192 treatment also
showed an increase in the expression of activation markers activation and increase in the release
of pro-inflammatory cytokines in T cells. -CD99-A192 treated T cells exhibited heightened
cytotoxicity against leukemic cells. Altogether, these findings suggest -CD99-A192 enhances T
cell activation and cytotoxic potential consistent with dual mechanisms of action for -CD99-
A192.
1
Chapter 1: Background
T cells
The human immune system is a complex network of cells and organs that protect the
body from pathogens like bacteria, viruses and fungi. The two parts of the immune system:
innate immune system and adaptive immune system work in harmony to provide our body’s
defense. The innate immune system forms barriers for the entry of pathogens and harmful
substances into the body. The adaptive immune system comprises of B cells and T cells. B cells
are responsible for producing antibodies against antigens when the immune system identifies an
antigen in the body. T cells are responsible for the formation and maintenance of immune
responses, memory and homeostasis along with playing a significant role in the development of
inflammatory and autoimmune disorders. T cells comprise of different subsets, namely naïve T
cells, which respond to new antigens, memory T cells, which are formed from previous antigen
responses and are responsible for long term immunity, and regulatory T cells which regulate the
immune responses. Immune responses initiate when naïve T cells encounter an antigen, which
results in interleukin 2 (IL2) production, T cell proliferation and differentiation into effector
cells. T cells express T-cell receptors (TCRs) which recognize foreign pathogens and antigens in
the form of a short peptide called Major Histocompatibility Complex (MHC) (Kumar et al.,
2018).
The birth of T cells begins from the hematopoietic stem cells (HSCs) in the bone marrow
by a process called hematopoiesis. HSCs give rise to multipotent progenitor cells (MPPs) which
further differentiate into two kinds of cells, namely, myeloid progenitor cells and lymphoid
2
progenitor cells which are a part of the body’s innate and adaptive immune systems providing
defense against pathogenic attacks (Olson et al., 2020). Myeloid progenitor cells differentiate
into granulocyte-macrophage progenitors and megakaryocyte-erythroid progenitors which give
rise to mature myeloid cells megakaryocytes (which further differentiate to form platelets),
erythrocytes, neutrophils, eosinophils, monocytes (which further differentiate to form dendritic
cells and macrophages) and basophils (Weiskopf et al., 2016). The lymphoid progenitor cells
give rise to natural killer (NK) cells, B lymphocytes in the bone marrow, but some migrate to the
thymus to form T cells or Thymus-dependent lymphocytes.
3
Figure 1. Overall scheme of Normal Hematopoiesis (Created on BioRender)
The T-cell precursors formed in the thymus enter a differentiation phase which includes
expression of T cell specific surface molecules followed by proliferation. After this
differentiation phase, the thymocytes express unique surface markers of the T-cell lineage but not
the mature T cell surface markers like CD3, CD4 or CD8. These cells are known as double
negative (DN) thymocytes due to the absence of cell surface markers like CD4 and CD8. Based
on the cell surface expression, the DN thymocytes can be further divided into CD44 (which is an
adhesion molecule), CD25 (IL2 receptor) and c-Kit (stem cell factor receptor).
4
Initially, the DN thymocytes exhibit the surface expression of c-Kit and CD44 but as they
develop, the surface expression of CD25 increases and the chain locus rearrangement of the
TCR occurs. The cells that successfully make the chain locus rearrangements and can express
the chain, lose their CD25 surface expression. The chains expressed on the thymocytes
conjugate with a surrogate chain called pT (also known as pre T-cell ) to form a pre-T-cell
receptor. The cell surface expression of the pre-T-cell receptor is in the form of a complex with
CD3 molecules which form the TCR signaling component. This CD3: pre T-cell receptor
complex is responsible for cell proliferation, expression of CD4 and CD8 (double positive
thymocytes) and the seizing of further chain locus rearrangements. These double positive
thymocytes undergo positive selection, i.e., cells that can recognize self MHC mature and exhibit
high expression of TCR (Germain, 2002; Klein et al., 2014; Kumar et al., 2018). They also stop
expression one of the two co-receptor molecules and become either CD4 or CD8 single positive
thymocyte.
Figure 2. Overall scheme of T cell development (Created on BioRender)
5
T cells are activated via co-stimulatory signals in the presence of an antigen. These T
cells after activation, produce and utilize cytokines like IL2, IL4 and IL7, to proliferate.
Depending on the environment, they can undergo restimulation-induced cell death if they
encounter a strong antigenic stimulation repeatedly or they can enter a stage called T cell
exhaustion which is characterized by an unresponsive state. As the immune response diminishes
and the pathogen clears, cytokine withdrawal takes place which allows the expansion of the
antigen-specific T cells. Some cells differentiate to form memory T cells facilitated by IL7 and
IL15, which then circulate in the immune system (Waldman et al., 2020).
Figure 3. T cells responses to antigen attacks (Waldman et al., 2020)
6
Activation of a cytotoxic (CD8) or helper (CD4) T cell into an effector cell can occur via
three kinds of signals presented by an antigen-presenting cell (APC). Signal 1 is mediated by
engagement of the T-cell receptor (TCR) of the foreign peptide presented by a MHC protein on
the surface of the APC. Signal 2 is presented by costimulatory proteins like CD80 and CD86
whose expression is induced by the presence of pathogens. These costimulatory proteins can be
recognized by CD28 present on the T cell surface. Signal 3 refers to the cytokine production of
the differentiated helper T cells consisting of Th1, Th2, Th17, Treg and Tfh cells. T cell
activation causes the T cells to secrete IL2 which in turn increases cell proliferation and
differentiation (Crotty, 2011; Lee et al., 2020; Zhu et al., 2010).
Figure 4. Activation of T cells into effector cells (Created on BioRender)
7
T cells have been utilized for their cytotoxic functions for cancer immunotherapy. The
first attempt to use T cells was made in the late 1980s (Rosenberg et al., 1988) for the treatment
of metastatic melanoma, where lymphocytes were extracted from a cancer biopsy and after
expansion with IL2 ex vivo, they were injected back into the same patient with IL2. The first
attempt was only partially successful (Rosenberg et al., 1994). The researchers experienced more
success when the patients were depleted of lymphocytes before reinfusing the extracted
lymphocytes (Rosenberg et al., 2011). These studies faced the limitation of presence of T cells
possessing antitumor activity in the patients (Perica et al., 2015). To overcome the limitation, a
new form of TCR engineered lymphocyte therapy emerged. The TCR engineered cells faced the
challenge of responding only to the MHC-presented tumor antigens and not the antigens
expressed on the tumor cell surface (Perica et al., 2015). Developing adoptive T cell therapy, led
to the evolution of generating chimeric antigen receptors (CAR) which can overcome the
limitation of MHC and exhibit targeted cytotoxicity to a target/receptor molecule expressed on
the tumor cell (Garrido et al., 2016). The CAR-T cell therapy is carried out in such a way that T
cells are isolated from a patient, or an allogeneic donor and these T cells are modified to express
the CAR. These modified cells are then expanded and reinfused into the patient.
The first generation of CART cells was developed only using the CD3 -chain to mimic
TCR signaling (Kuwana et al., 1987) but this design failed in the clinical trial due to cytokine
storms and restricted T cell proliferation (Brocker, 2000; Jensen et al., 2010). The CART cell
design has evolved over the years to include domains from ligands like CD28, CD40 and other
ligands that regulate T cell activation and cytotoxicity in vivo (Finney et al., 2004; Imai et al.,
2004; Kuhn et al., 2019; Maher et al., 2002). Development of a second-generation CART cell
8
included CD19 domain and exhibited effective responses in the treatment of chronic lymphocytic
leukemia (Porter et al., 2011). Though CD19 is a good target due to its high expression in
malignancies, in some cases the treatment has failed due to loss of CD19 antigen. Owing to the
success and limitations presented by CART cells, new generations of CART cells are being
investigated, for example, a CART cell design is being investigated in which the CART cells can
produce 1L12 which helps overcome immune suppression by regulatory T cells and promotes T
cell cytotoxicity (Zhao et al., 2012).
Figure 5. Evolution of Adoptive T Cell Therapies (Waldman et al., 2020)
9
CD99
CD99 gene and protein
CD99 is a highly O-glycosylated transmembrane protein encoded by MIC2 gene. The
MIC2 gene, composed of 10 exons, is in the pseudo autosomal region of X (Xp22.33-Xpter) and
Y (Yp11-Ypter) (Banting et al., 1989; Goodfellow et al., 1986) chromosomes in humans, is 50 kb
long (Pasello et al., 2018) and is present proximally to PAR1. Due to sequential duplication of
PAR during human evolution, researchers have identified CD99-related genes. The three genes
are: PBDX, CD99L1 and CD99L2. PBDX encodes the Xga blood antigen (Ellis, Tippett, et al.,
1994) and has a 48% similar homology with CD99 (Ellis, Ye, et al., 1994). CD99L1 (also known
as MIC2R) shows relation to exons 1, 4, and 5 of MIC2 (Suh et al., 2003).
The gene encodes two isoforms due to alternative splicing process of the cytoplasmic
region, namely, a long isoform or a wild type (wt) full length CD99 (Type 1 or CD99wt)
composed of 185 amino acids (molecular weight: 32 kDa) and short isoform (Type 2 or CD99sh)
composed of 161 amino acids (molecular weight: 28 kDa) (J. H. Hahn et al., 1997a). The
transcript for the short isoform is composed of an 18-bp insertion at the exon 8 and 9 boundary,
which leads to an introduction of a stop codon thereby causing generation of a short polypeptide.
10
Figure 6. CD99 gene structure and their isoforms (Pasello et al., 2018)
CD99 is reported to be highly O-glycosylated, with 14kDa of its estimated molecular size
being accounted to chains of carbohydrates (Aubrit et al., 1989). CD99 as a protein exhibits
abundant proline residues and comprises an extracellular domain of 100 amino acids, a
transmembrane domain and a short intracellular C-terminal domain of 38 amino acids like a
typical integral transmembrane protein (Mahiddine et al., 2016a). The isoforms share a zone
which contains positively charged amino acids and a cysteine residue. The long isoform of CD99
contains a SHR motif for PKC and a leucine repeat which is unique to the isoform (Mahiddine et
al., 2016b). It has also been reported that long isoform comprises of two phosphorylation sites,
one at a serine at amino acid residue 168 and the other at a threonine at amino acid residue 181,
which might be required for extracellular molecular interactions or intracellular signaling events.
11
The serine at amino acid residue 168 has been reported as a site for PKC phosphorylation and is
essential for the onco-suppressive role of CD99 (Scotlandi et al., 2007).
Figure 7. Structural Representation of CD99 Isoforms (Ali et al., 2022)
12
Structurally, Kim et al. reported that the cytoplasmic domain of the long isoform of the
human CD99 protein presents as a hairpin structure that is unfolded, is held together by two
flexible loops and does not present any regular secondary structures (H.-Y. Kim et al., 2004).
Figure 8. Structural Representation of the Long Isoform of the CD99 Protein (Created on
PyMol)
N-terminus
C-terminus
13
CD99 is reported to have a role in various cellular functions like protein trafficking
(Brémond et al., 2009a), cell adhesion (G. Bernard et al., 1995), cell apoptosis (G. Bernard et al.,
1997), leukocyte diapedesis (Watson et al., 2015), lymphocyte development and cell
differentiation (Huang et al., 2012).
Figure 9. Schematic Diagram of Functions of CD99 (Created on BioRender)
14
CD99 expression
CD99 is widely expressed in human tissues at varying levels with highest expression in
fibroblasts, arterial tissues, adipose tissues and lowest expression in brain and kidneys
(Fagerberg et al., 2014).
Figure 10. CD99 expression in human tissues (Fagerberg et al., 2014) (From GTEx portal)
CD99 is widely expressed in almost all human cell types including pancreatic islet cells,
cortical thymocytes, testis, ovarian cells, ependymal cells, endothelial cells, CD34+
cells and a
broad range of hematopoietic cells. Among the cells originating from the hematopoietic system,
15
CD99 expression has been observed on nearly all cell types except granulocytes . The CD99
expression pattern has been hypothesized to be linked to cell maturation with high expression
levels observed on cortical thymocytes but relatively lower expression levels observed on
differentiated medullary thymocytes (Waclavicek et al., 1998a). CD99 has shown high
expression on T cells in the bone marrow and thymus compared to other blood cells (Uhlen et al.,
2019).
Figure 11. Single Cell CD99 Expression in Bone Marrow (From The Human Protein Atlas;
available at https://www.proteinatlas.org/ENSG00000002586-
CD99/single+cell+type/bone+marrow) (Uhlen et al., 2019)
16
Figure 12. Heat Map exhibiting Fraction of Highest CD99 expression on blood cells in Bone
Marrow; with 0 (yellow) being the lowest and 1 (black) being the highest expression (From
17
The Human Protein Atlas; available at https://www.proteinatlas.org/ENSG00000002586-
CD99/single+cell+type/bone+marrow) (Uhlen et al., 2019)
Table 1. Cell surface markers of the T cell clusters of bone marrow.
T cell cluster Cell Surface
Markers
nTPM Z-score Inference
T cells c-0 CD3E 1366.5 0.90 CD8+
CD4 5.0 -0.36
CD8A 1052.5 1.25
T cells c-1 CD3E 1130.9 0.80 FOXP3+
CD4 93.4 1.08
CD8A 144.5 0.21
FOXP3 8.2 2.27
T cells c-2 CD3E 921.8 0.69 CD3+
CD4 0.8 0
CD8A 280 0.56
T cells c-4 CD3E 1086.1 0.78 FOXP3+
CD4 64.9 0.90
CD8A 265.6 0.53
FOXP3 4.4 1.46
T cells c-6 CD3E 1243.1 0.85 CD4+
CD4 102.3 1.13
CD8A 306.9 0.61
18
Analyzing the expression of CD99 in the bone marrow tissue, T cells have the highest
expression of CD99 compared to other blood cells. Within the T cell clusters, helper T cells
(CD4+
) show the highest CD99 expression followed by cytotoxic T cells (CD8+
) and regulatory
T cells (FOXP3+
).
Figure 13. Single Cell CD99 Expression in Thymus (From The Human Protein Atlas; available
at https://www.proteinatlas.org/ENSG00000002586-CD99/single+cell+type/thymus) (Uhlen et
al., 2019)
19
Figure 14. Heat Map exhibiting Fraction of Highest CD99 expression on blood cells in
Thymus; with 0 (yellow) being the lowest and 1 (black) being the highest expression (From
The Human Protein Atlas; available at https://www.proteinatlas.org/ENSG00000002586-
CD99/single+cell+type/thymus) (Uhlen et al., 2019)
20
Table 2. Cell surface markers of the T cell clusters of thymus.
T cell cluster Cell Surface
Markers
nTPM Z-score Inference
T cells c-0 CD3E 976.1 1.85 CD4+
CD4 87.5 1.44
CD8A 23.1 1.52
FOXP3 20.9 1.39
IL17A 0.2 0
T cells c-1 CD3E 596.3 1.67 CD4+
CD4 69.8 1.34
CD8A 11 1.09
FOXP3 16.9 1.29
T cells c-4 CD3E 843.8 1.8 CD8+ IL17+
CD4 57.6 1.25
CD8A 331.5 3.04
FOXP3 7.8 0.92
IL17A 2.4 1.56
T cells c-18 CD3E 1261.6 1.94 FOXP3+
CD4 139.9 1.65
CD8A 3.4 0.42
FOXP3 423.1 2.85
21
Analyzing the expression of CD99 in the thymus tissue, T cells have moderate expression
of CD99 compared to other blood cells. Within the T cell clusters, cytotoxic T cells (CD8+
) show
the highest CD99 expression followed by regulatory T cells (FOXP3+
) and helper T cells (CD4+
).
Thus, compared to other blood cells, T cells show the highest expression of CD99, with varying
expression among the T cell subsets.
Role of CD99 in T cells
CD99 plays a role in cell apoptosis (G. Bernard et al., 1997; Pasello et al., 2018; Pettersen
et al., 2001), cell adhesion (G. Bernard et al., 1995; J. H. Hahn et al., 1997a; Kasinrerk et al., 2000),
lymphocyte development (Pasello et al., 2018), leukocyte diapedesis (Watson et al., 2015), cell
differentiation, and protein trafficking (Brémond et al., 2009b; Cerisano et al., 2004; Choi et al.,
1998a; Yoon et al., 2003). Initially, CD99 was discovered as a protein having a role in the T cell
rosette formation, which brought focus on it as a protein causing cell adhesion (A. Bernard et al.,
1988). CD99 is expressed via two isoforms, namely the long 32 kDa and short 28 kDa isoform (J.
H. Hahn et al., 1997b). T cells, single-positive thymocytes and some T cell lines express the long
isoform, while double-positive thymocytes express both isoforms (Alberti et al., 2002), whereas
peripheral T cell and single positive thymocytes only express the long form (Alberti et al., 2002).
CD99 is considered an integral part of lymphocyte development as it was found that CD99-
deficient fetuses exhibited an impaired thymus, thus highlighting CD99’s role in thymus and
lymphocyte development (Shin et al., 1999). In T cells, CD99 contributes to cell proliferation,
expression of activation markers (Wingett et al., 1999), and differentiation (M. Manara et al., 2018;
22
Pasello et al., 2018). CD99 has also been reported to induce homotypic cell adhesion causing
formation of T cell aggregates. Both isoforms are reported to have a role in the CD99-induced T
cell functions. In an experiment performed with CD99 transfected Jurkat T cells, it was found that
the presence of both isoforms was necessary to induce cell apoptosis, but the presence of either
isoforms was enough to regulate cell adhesion. It was also reported that the presence of long
isoform is impertinent for the actin cytoskeleton activation (Alberti et al., 2002). Previous studies
have reported an increase of CD99 expression in memory and activated T cells; however, the exact
signal transduction pathway and CD99’s role in T cell regulation remains poorly understood
(Takheaw et al., 2020).
Various CD99 targeting ligands have been developed in the form of recombinant proteins
and monoclonal antibodies, which upregulate IL6, TNF (Takheaw et al., 2019), IFN
(Waclavicek et al., 1998b) and Th1 (Takheaw et al., 2019; Waclavicek et al., 1998a). It is also
reported that CD99 is necessary for the HLA expression caused by IFN (Brémond et al., 2009c).
CD99 has been reported to cause an upregulation of MHC and TCR expression on T cell surfaces
(Choi et al., 1998b; Sohn et al., 2001). Increasing the MHC-TCR interactions (M.-J. Hahn et al.,
2000; Waclavicek et al., 1998a; Wingett et al., 1999), increases the possibility of CD99 being
involved in the positive selection of lymphocytes. The interaction between CD99 and MHC
signaling during the process of lymphocyte development and maturation is believed to be complex
as MHC engagement has been reported to have a decreasing effect on CD99 engagement (M. K.
Kim et al., 2003). Several studies have reported CD99 to have a role in T cell activation, with
studies reporting increased expression of T cell activation markers and an increase in the
intracellular levels of Ca2+ and higher phosphorylation of cellular proteins (Waclavicek et al.,
23
1998a; Wingett et al., 1999). CD99 engagement also causes an increase in the TCR-mediated
signaling by translocation of TCR complexes to lipid rafts (Oh et al., 2007). Some studies have
also reported a decrease in the T cell proliferation with the use of anti-CD99 mAbs (Pata et al.,
2011).
The role of CD99 has been investigated before in terms of studying the activation effects
and the cytotoxic effects. In terms of the function of CD99 in CD4+ cells, it has been reported
that CD99 ligation enhances activation markers like CD25, CD69 and CD40L which has pointed
towards the existence of a CD99-induced signal transduction pathway (Wingett et al., 1999).
Role of CD99 in cancer
Pathologically, CD99 has been investigated for its role as a transmembrane cell receptor
in various diseases. CD99 expression has been reported to be increased in disorders like myeloid
malignancies (Chung et al., 2017a), Ewing’s sarcoma (Ambros et al., 1991; Llombart-Bosch et
al., 2009), malignant gliomas (Seol et al., 2012; Urias et al., 2014) and lymphoblastic
lymphoma/leukemia (Dworzak et al., 2004). Some other diseases that have been reported to
exhibit sporadic overexpression of CD99 are mesenchymal chondrosarcoma (Brown & Boyle,
2003), thymic tumors, synovial sarcoma (Fisher, 1998), gastrointestinal neuroendocrine tumors
(Goto et al., 2004), rhabdomyosarcoma (RAMANI et al., 1993), hemangiopericytoma (Rajaram
et al., 2004), pulmonary neuroendocrine tumors (Goto et al., 2004), thymic tumors, sex-cord
stromal tumors (Baker et al., 1999) and some cases of breast cancers (Milanezi et al., 2001). In
some cases of neoplasms, like osteosarcoma (M. C. Manara et al., 2006), pancreatic endocrine
24
neoplasms and gastric adenocarcinoma (Jung et al., 2002; Maitra et al., 2003), CD99 has been
reported to be overexpressed in benign conditions but not in malignant conditions.
Figure 15. CD99 Protein Concentration in Various Cancers (From The Human Protein Atlas;
available at https://www.proteinatlas.org/ENSG00000002586-CD99/disease) (Uhlén et al., 2005)
In tumors, CD99 influences the invasion, metastasis, and migration of the malignant cells
through various mechanisms. CD99 has shown effectiveness in preclinical xenograft models,
which has made it a promising therapeutic target, opening the possibilities for development of
antibodies against the receptor and their clinical applications. It has also been reported that
engaging CD99 also enhances toxicity towards the tumor cells through Natural Killer (NK) cells
by the induction of heat shock protein 70 (HSP70) (Husak & Dworzak, 2012). Cell apoptosis
25
occurs through mechanisms like methuosis (M. C. Manara et al., 2016) or the induction of
oncogenic stress (Chung et al., 2017a; Husak & Dworzak, 2017; Pasello et al., 2018).
Role of CD99 in Acute myeloid Leukemia
Acute Myeloid Leukemia (AML) is a disease originating from hematopoietic cells
(Bonnet & Dick, 1997). Due to a series of mutations that occur in the DNA, immature
hematopoietic cells give rise to Leukemic Stem Cells (LSCs). LSCs have the ability of selfrenewal and can differentiate into leukemia progenitor cells, which give rise to majority of the
leukemic blasts (Lapidot et al., 1994). The regulatory axis of the hematopoietic system is
disrupted in the case of AML, but with enhanced self-renewal and regenerative signaling
pathways working together to progress the leukemic development (Olson et al., 2020).
26
Figure 16. Hematopoiesis is AML (Created on BioRender)
To investigate new therapies for the treatment of AML and overcome resistance due to
existing therapies, many cell surface proteins have been identified which have been reported to
have a unique expression or overexpression on LSCs compared to healthy HSCs. Some of the
identified proteins include cell surface markers like CD44 (Jin et al., 2006), CD47 (Majeti et al.,
2009), CD123 (Jin et al., 2009), CD96 (Hosen et al., 2007) and many more.
CD99 has also been investigated as a cell surface marker overexpressed on LSCs. The
expression of CD99 is increased in CD34+CD38- cell populations of AML blasts when
27
compared to healthy bone marrow cells. Overexpression of CD99 on these blasts causes
enrichment for functional LSCs (Chung et al., 2017a; Vaikari, Du, et al., 2020). Overexpression
of CD99 on AML initiating cells has identified CD99 as a potential disease marker and
therapeutic target.
Figure 17. Overexpression of CD99 in AML cells (Vaikari et al., 2016)
In a study conducted by Chung et al., using primary patients’ samples and xenograft
models they were able to establish CD99 as a novel AML LSC marker. They examined a large
pool of primary AML samples and compared the cell surface expression in the primary AML
samples with the CD99 cell surface expression in healthy HSCs. They found an increased
expression of CD99 cell surface expression in primary AML samples compared to healthy
samples in such a manner that the CD99 expression enabled distinctive identification of
leukemic blasts from healthy or pre-leukemic cells. They also studied the therapeutic potential of
targeting CD99 by using anti-CD99 monoclonal antibodies (mAbs) and showing apoptosis in
leukemic cell lines (Chung et al., 2017b).
28
Anti-CD99 antibodies
The effects of targeting CD99 have been studied using anti-CD99 monoclonal antibodies
(mAbs) like O13, DN16, MSGB1, 0662, 12E7, YG32 and F21in murine models. These mAbs
target different epitopes of the target. In a study conducted by Jung et al., they reported that
YG32 showed greater affinity to CD99 than DN16 (Gil et al., 2002). Both recognized different
CD99 epitopes (Gil et al., 2002; J. H. Hahn et al., 1997a). They also reported that binding of
DN16 induced cell apoptosis is Jurkat cells but YG32 binding did not induce cell apoptosis.
YG32 induced homotypic adhesion, Fas-mediated cell apoptosis and caused MAP kinase
activation (Jung et al., 2003). Bernard et al., also reported that O662 antibody induced cell death
of immature thymocytes (G. Bernard et al., 1997).
Figure 18. Graphic representation of CD99 protein with the mAbs binding to different
epitopes of the protein (Pasello et al., 2018)
Owing to CD99’s overexpression in leukemic cells, many antibodies have been
developed targeting CD99 in leukemia which have shown effect in vitro and in vivo. Anti-CD99
mAbs have been identified as a promising targeted therapeutic strategy. Anti-CD99 mAb (clone
29
H036-1.1) has been reported to cause cytotoxic effects to leukemic stem cells (LSCs) in vivo, and
cause apoptosis of AML blasts in vitro and ex vivo by a function of SFK activation (Chung et al.,
2017a). Another mAb Ad20 was found to induce CD99-mediated programmed cell death in
transformed T cell lines which was independent of CD3, CD4, CD45, p56 and CD47- mediated
T cell death responses. But since they did not observe the same death response with normal
peripheral T cells, they suggested that CD99 might have biological relevance in early T cells
(Pettersen et al., 2001).
Romero et al. reported an engineered antibody 10A1 targeting CD99 showing effective
binding to T-ALL cells. Their human IgG-based 10A1 antibody showed cytotoxicity to T- cell
Acute Lymphoblastic Leukemia (T-ALL) cells with no reported cytotoxicity towards healthy
peripheral blood cells (Romero et al., 2022). Moreover, Shi et al. have reported CAR T cell
therapy targeting CD99 showing effective cytotoxicity against CD99 positive T-ALL cell lined
and primary tumor cells in vitro and prolonged survival in cell-line derived xenograft or patientsderived xenograft models in vivo (Shi et al., 2021a).
Anti-CD99 ScFv ELP
Antibodies developed targeting CD99, specifically monoclonal antibodies, face the
challenge of successfully translating into clinical trials due to the intricate development process.
One of the solutions to overcome this limitation would be using single-chain antibody fragments
(scFvs) (Vaikari, Park, et al., 2020). They consist of heavy and light variable regions, linked by a
flexible peptide linker and can be more easily modified by recombinant protein engineering
30
(Skerra & Plückthun, 1988). But they face the limitation of a short half-life, owing to their rapid
clearance and low stability (Hayhurst & Harris, 1999; Hutt et al., 2012). To address these
limitations, our team recently developed anti-CD99-A192 (-CD99-A192) nanoparticles that are
composed of -CD99 single chain variable fragment (scFv) linked to A192, which is an elastinlike polypeptide (ELP) (Jenkins et al., 2021).
ELPs are repetitive pentameric peptides derived from human tropoelastin that stabilize
the assembly of scFvs into multi-valent nanoparticles (MacKay et al., 2010; Phan & MacKay,
2024; Urry, 1997). They are genetically engineered protein polymers comprising of the amino
acid sequence (VPGXG)n , where ‘X’ stands for a guest amino acid and ‘n’ stands of the number
of pentameric repeats (Despanie et al., 2016). Since they are like human tropoelastin, ELPs have
the advantage of being biodegradable and biocompatible. One of the vital features of ELPs is that
they can be purified without chromatography owing to their reversible phase separation above a
transition temperature (Christensen et al., 2009).
-CD99-A192 was developed as a nanoworm targeting CD99. -CD99-A192 exhibits
specific binding to AML cell lines expressing CD99. Moreover, these fusion proteins also
exhibited increased apoptosis and decreased cell viability in both primary AML cells and AML
cell lines in vitro, along with prolonged survival and decreased leukemic burden in AML
xenograft models (Vaikari, Park, et al., 2020). Considering that CD99 is also expressed on T cells
and given its role in T cell activation, we proposed that -CD99-A192 plays a dual function:
targeting leukemic cells while activating T cells. Thus, having established its anti-leukemic
31
activity in pre-clinical models, this manuscript now characterizes the effects of antibody-based
CD99 nanoparticle on T cells and how that impacts their antileukemic activity.
Figure 19. Overview of the Anti-CD99 scFv ELP (Vaikari, Park, et al., 2020)
32
Chapter 2: Materials and Methods
Sample Collection from Healthy Donors
Healthy donors were consented in a written format authorizing the use of the collected samples
before collection. Each subject was presented with a California Bill of Rights and provided with a
copy of their signed consent form. The use of human materials was approved by the Institution
Review Boards of the University of Southern California in accordance with the Declaration of
Helsinki (Ref#: HS-16-00274; Date of approval: 2 March 2019).
Peripheral Blood Mononuclear Cell (PBMC) Isolation
The collected whole human peripheral blood was diluted with Dulbecco’s Phosphate-buffered
Saline (DPBS) (Thermo Fisher Scientific, Ref#14190-144) and methodically layered over a FicollPaque PLUS density gradient (Cytiva, Ref#17144003). Blood layered over Ficoll was centrifuged
for 30 minutes at zero deceleration and acceleration of 1. With the help of density gradient
centrifugation, the desired PBMCs were present at the interface of the separated layers. The
PBMCs were collected, subsequently washed thrice with DPBS, and resuspended in Roswell Park
Memorial Institute (RPMI) 1640 (1X) (Thermo Fisher Scientific, Ref#11875-093) culture medium
supplemented with 20% fetal bovine serum (FBS).
33
Stimulation and Expansion of T cells
The desired amount of PBMCs were stimulated with cytokines, recombinant human
interleukin-2 (rhIL-2) (R&D systems, Cat# BT-002) and Phytohemagglutinin-L (PHA) Solution
(500x) (Invitrogen, Ref# 00-4977-93), at a concentration of 1:1000 for PHA-L and 2.5ng/ml for
rhIL-2, for 72-96 hours in RPMI media with 20% FBS. At the end of the incubation period, the
expanded T cells, also labeled as stimulated cells, were washed with DPBS, and collected for
further treatment.
Treatment with A192 and -CD99-A192 ELPs
The PBMCs and PHA and IL2 expanded T cells were washed and resuspended in 200ml
PBS. They were further divided into control and treated groups. The control A192 scFv ELP was
added to the control group and -CD99-A192 scFv ELP was added to the treated group at a
concentration of 10mM of the final volume. The treated cells were then incubated on ice for 30
minutes and later washed with DPBS. The cells were resuspended in RPMI supplemented with
20% FBS and cultured in 12-well suspension plates for further analyses.
Binding assay
The PHA and IL2 expanded T cells were treated with NHS-Rhodamine labeled A192 and
NHS-Rhodamine labeled -CD99-A192 scFv ELPs and incubated on ice for 30 minutes. After the
incubation period, the ELP-bound T cells were washed and resuspended in 300ml PBS in flow
34
tubes. The fluorescence intensity of phycoerythrin (PE) was used to identify the ELP binding. Flow
cytometry was performed on the BD Fortessa X20 flow cytometer and data analysis was performed
using FlowJo v10 10.7.1.
Cell counting and proliferation assays
The A192 and -CD99-A192 treated PBMCs, and T cells were seeded into a 12-well plate
according to their treatment conditions, namely, untreated, A192 and -CD99-A192. Cells were
counted on day 1, day 3, day 5, day 7, day 9, and day 10 using Trypan blue solution and an
Improved Neubauer Hemocytometer with a chamber depth of 100mm. Cell concentration was
obtained by taking the average of the quadrants, multiplying by the dilution factor, and further
multiplying by 10,000 to obtain the cell concentration per ml of the solution. The experiment was
performed in triplicates and terminated on day 10 after the treatment.
The PBMCs and the expanded T cells were initially stained using the Cell Trace
Carboxyfluorescein succinimidyl ester (CFSE) Cell Proliferation Kit (Invitrogen, Ref#C34554).
CFSE dye was reconstituted using 18ml Dimethyl sulfoxide (DMSO) to make the 5mM stock
concentration, and the required amount was diluted using DPBS to obtain the final diluted
concentration of 2mM CFSE. The cells were resuspended using the diluted stain and incubated
away from light for 20 minutes. After incubation, 4x volume of DPBS was added and the cells
were incubated for 5 minutes. The cells were then centrifuged at 1300rpm for 3 minutes, washed
once with DPBS and resuspended in cell culture medium. The stained cells were washed and
treated with control A192 ScFv ELP and -CD99-A192 scFv ELP at a concentration of 10mM of
35
the final volume. The cells were then seeded in a 12 well plate according to the treatment groups.
An aliquot of the cells was taken every alternate day with day 0 being the day of treatment. The
aliquot was washed and resuspended in 300ml DPBS. The cells were then analyzed on the LSRII
BD Fortessa X20 flow cytometer by measuring the fluorescence intensity of Alexa Fluor 488 and
data analysis was performed using FlowJo v10 10.7.1. The experiment ended on day 9.
T cell phenotyping
The A192 and -CD99-A192 treated PBMCs, and T cells were collected in flow tubes on
day 5 after the treatment. The cells were then washed and resuspended with the prepared stain
master mix. The master mix was prepared using FITC anti-human CD3 (Clone: UCHT1;
Biolegend, Cat#300406), Anti-Human CD4 PE (Clone: OKT4; eBioscience Cat#4337556), AntiHu CD8a PE-Cyanine 7 (Clone: SK1; eBioscience Cat#2066348) and Anti-Hu CD25 APC (Clone:
BC96; eBioscience Cat#1946588) antibodies. The cells were incubated with the master mix on ice
away from light for 25-30 minutes. After incubation, the cells were centrifuged at 1300rpm for 3
minutes, washed twice with 500ml DPBS and resuspended in 300ml DPBS for analysis on the
flow cytometer. Flow cytometry was performed on the LSRII BD Fortessa X20 flow cytometer
and data analysis was performed using FlowJo v10 10.7.1.
For expression analysis of the activation markers, CD38 and CD69, the control and -
CD99-A192 treated T cells were collected in flow tubes on day 5 after the treatment. The cells
were washed twice with DPBS and resuspended in 100ml of DPBS. Anti-Human CD3 PerCPCyanine 5.5 (Clone: OKT3; eBioscience, Ref#45-0037-42), Anti-Human CD38 FITC (Clone:
36
HB7; eBioscience, Ref#11-0388-42) and Anti-Human CD69 PE (Clone: FN50; eBioscience,
Ref#12-0699-42) was added to the cells. The cells were incubated on ice for 25-30 minutes on ice
and away from light. After incubation, the cells were centrifuged at 1300rpm for 3 minutes, washed
twice with 500ml DPBS and resuspended in 300 ml DPBS for analysis on the flow cytometer.
Flow cytometry was performed on the LSRII BD Fortessa X20 flow cytometer and data analysis
was performed using FlowJo v10 10.7.1.
RNA Sample Preparation and RNA-seq Data Analysis
The PBMCs obtained from healthy donor were expanded with PHA and IL2 for 72 hours.
The expanded T cells were then treated with A192 and -CD99-A192 ELPs at a concentration of
10mM. The A192 and -CD99-A192 treated T cells were cultured in RPMI media with 20% FBS
and collected on day 5 after treatment. The cells were washed once with DPBS and then
resuspended in 300ml of RLT buffer (composed of 0.01% of -mercaptoethanol). Cells were then
centrifuged at 1300rpm for 3 minutes and washed twice with 1ml of DPBS. Total RNA was
isolated from cell pellet using the RNeasy mini kit with on-column DNAse digestion (Qiagen, Cat.
#74104) according to the manufacturer's protocol. RNA concentration and integrity were assessed
by Thermo Scientific NanoDrop OneC and Agilent high sensitivity RNA ScreenTape (Agielnt
Technologies, Cat. #5067-5579). RNA samples were stored at −80°C until they were shipped to
Azenta for library preparation and sequencing.
The RNA sequencing data obtained from Azenta was analyzed using Gene Set Enrichment
Analysis-Molecular Signatures Database (GSEA-MSigDB) computational tool version 4.3.2
37
(Broad Institute, UC San Diego). After successfully uploading the expression dataset and
phenotype label files, the parameters set for analyzing the dataset were
h.all.v2023.3.Hs.symbols.gmt (Hallmark gene set) for gene sets database and
Human_Ensembl_Gene_ID_MSigDB.v2023.2.Hs.chip for Chip platform. Using the uploaded
files and set parameters, the analysis was run to obtain the gene enrichment plots.
Cytokine Release Profile Analysis
The PBMCs obtained from healthy donor were expanded with PHA and IL2 for 72 hours.
The expanded T cells were then treated with A192 and -CD99-A192 ELPs at a concentration of
10mM. The A192 and -CD99-A192 ELP treated T cells were cultured in RPMI media with 20%
FBS and collected on day 5 after treatment. The supernatant of the A192 and -CD99-A192 treated
T cells was collected on day 5 and analyzed for their cytokine and chemokine release profile using
the Proteome Profiler Array kit by R&D systems (Cat# ARY005B), according to the
manufacturer's protocol. The samples were prepared by incubating the supernatants with the
Human Cytokine Array Detection Antibody Cocktail at room temperature for one hour and later
the solution was added to the membrane provided (which was incubated with array buffer earlier).
The membranes were then incubated overnight at 2-8°c on a rocking platform. The membranes
were then collected the next day, washed, and incubated with diluted Streptavidin-HRP. After
incubation, the membranes were washed and visualized using Chemi Reagent Mix for 10-15
minutes on Image ChemiDoc. The visualized membranes were then analyzed using BioRad
software. The plots were created using the mean pixel intensity after subtracting the mean
38
background intensity. The adjusted mean pixel intensity was then normalized to the adjusted mean
pixel intensity of the reference spots present on the membranes.
Co-culture Apoptosis Assay
The Carboxyfluorescein succinimidyl ester (CFSE) from the Cell Trace CFSE Cell
Proliferation Kit (Invitrogen, Cat# 2420667) was resuspended with 18ml DMSO to obtain a 5mM
stock concentration. The required amount of CFSE solution was diluted in DPBS to obtain the
final diluted concentration of 2mM CFSE. The leukemic MV4-11 cells were cultured in RPMI
1640 (1X) culture medium supplemented with 20% FBS. The required number of MV4-11 cells
were collected and centrifuged at 1300rpm for 3 minutes and washed twice with DPBS. The cells
were resuspended in the diluted CFSE solution at a concentration of 2mM and incubated away
from light for 20 minutes. After incubation, 4x volume of DPBS was added and the cells were
incubated for 5 minutes. After incubation, the cells were centrifuged at 1500rpm for 5 minutes.
The supernatant was removed, and RPMI 1640 (1X) culture medium supplemented with 20% FBS
was added.
The PBMCs obtained from healthy donor were expanded with PHA and IL2 for 72 hours.
The expanded T cells were then treated with A192 and -CD99-A192 ELPs at a concentration of
10mM. For the treatment of T cells, the control A192 ScFv ELP was added to the control group
and -CD99-A192 ScFv ELP was added to the treated group at a concentration of 10mM of the
final volume. The cells were then incubated on ice for 30 minutes and later washed with DPBS to
remove the ELPs. The A192 and -CD99-A192 treated T cells were incubated with the CFSE-
39
labeled leukemic MV4-11 cells at an Effector to Target (E:T) ratio of 5:1 in a 12-well suspension
plate.
The cells were collected at 18 and 48 hours, centrifuged at 1300rpm for 3 minutes and
washed twice with DPBS. The cells were resuspended in 100ml DPBS. Annexin V stain was
prepared by diluting Annexin V APC (Invitrogen, Ref#17-8007-74) with Annexin V Binding
Buffer (10x) (Invitrogen, Ref#00-0055-56) in a ratio of 1:9. The diluted stain was added to the
cells and the cells were incubated on ice for 25-30 minutes away from light. After incubation, the
cells were centrifuged at 1300rpm for 3 minutes, washed twice with DPBS and resuspended in
300ml DPBS. Flow cytometry was performed on the LSRII BD Fortessa X20 flow cytometer and
data analysis was performed using FlowJo v10 10.7.1. For analyzing the data, the live cell
population was identified first followed by identifying the Green Fluorescent Protein+
(GFP+
)
MV4-11 cells using the FITC channel. The MV4-11 cells undergoing apoptosis were then
identified using the annexin V stain under the APC channel.
Luciferase Assay
The A192 and -CD99-A192 treated T cells were incubated with leukemic MV4-11, THP1 and MOLM-13 cells transfected with lentivirus plasmids carrying GFP and luciferase genes, at
an Effector: Target (E:T) ratio of 5:1 in a 96-well U-bottom suspension culture plate. The cells
were collected within 24 hours, washed, and incubated with the lysis reagent in a 96-well F-bottom
white microplate (Greiner bio-one, Ref#655075). Luciferase substrate (final concentration :1
mg/ml) Reagent (20ml) was added to each well and the produced color was measured using Biotek
40
Synergy 2 Plate Reader (Model: Synergy 2 SL). The fluorescence intensity recorded was analyzed
using Microsoft Excel.
Statistical Analysis
Experiments were conducted in triplicates unless mentioned otherwise in the figure legend;
results were presented as the mean ± standard deviation. The normality of the data was determined
using Shapiro-Wilk test and parametric and non-parametric tests were used accordingly. Statistical
comparisons utilized unpaired T test for binding assay, apoptosis assay and activation marker
analysis, One-Way ANOVA with Tukey correction for proliferation assay, Two-Way ANOVA with
Tukey correction for expression of T cell phenotypes and unpaired T-tests with Holm-Sidak
correction for multiple comparisons for comparing cell aggregate counts and cytokine expression
analysis. Statistical significance was calculated in GraphPad Prism Version 8.2.1 (GraphPad
Software, Inc.). P value <0.05 was considered significant.
41
Chapter 3: Results
-CD99-A192 induces cell aggregation in T cells.
The binding of -CD99-A192 to T cells was analyzed by observing the median
fluorescence shift of NHS-Rhodamine labeled -CD99-A192 bound PE positive cells compared
with the NHS-Rhodamine labeled A192 treated cells assessed by flow cytometry (Figure 20A).
The IL2 and PHA expanded T cells show effective binding to the NHS-Rhodamine labeled -
CD99-A192 compared to the A192 control. Compared to the control A192, the median
fluorescence of -CD99-A192 bound T cells is significantly shifted and increased. (Figure 20B,
A192 vs. -CD99-A192, 1.00 vs. 1.16, p = 0.029).
T cells that were expanded in the presence of IL2 and PHA for 3 days were treated with -
CD99-A192. The treated and control group were observed under the microscope for 7 days and
images were captured on day 1, day 2 and day 3. We observed that the -CD99-A192 treated T
cells exhibit increased cell aggregation compared with the control A192 group (Figure 20C-D, day
1: A192 vs. -CD99-A192, 19 vs. 32, p=0.05; day 2: A192 vs. -CD99-A192, 12.50 vs. 29,
p=0.005; day 3: A192 vs. -CD99-A192, 16 vs. 52.5, p=0.005).
42
Figure 20. -CD99-A192 binds T cells and induces homotypic adhesion.
A, Flow cytometry panel exhibiting shift in the fluorescence peak of -CD99-A192 bound T cells
compared to control A192 bound T cells of three healthy donor samples. B, Comparison of the
median fluorescence of PE positive cells with respect to control between A192 and -CD99-A192
bound T cells exhibiting specific ELP binding. C, Microscope images of A192 treated T cells and
-CD99-A192 treated T cells on days 1, 2 and 3 after treatment, exhibiting cell aggregation, which
is known as homotypic adhesion. D, Observed cell aggregates per field for A192 and -CD99-
A192 treated T cells. The differences between the groups were analyzed using One-Way ANOVA
followed by Tukey correction. (**,P<0.01; *,P<0.05). The experiments were performed utilizing
samples obtained from three donors for the binding study and two donors for the cell aggregate
observation.
43
-CD99-A192 increases cell proliferation in T cells.
To assess the effect of -CD99-A192 on T cell viability and proliferation, the viability
assay was performed using trypan blue cell counts on both treated PBMCs and expanded T cells
that were stimulated with IL2 and PHA for three days. A decrease in unstimulated PBMC counts
was observed throughout all treatment groups. The control groups showed a slow decrease across
the days as observed normally with hematopoietic cells. In contrast, the -CD99-A192 treated
PBMCs exhibit a rapid decline in cell number over 10 days in vitro (Figure 21A, Day 9: untreated
vs. -CD99-A192, 64.92% vs. 24.66%, p= 0.01; Day 10: untreated vs. A192 vs. -CD99-A192,
71.46% vs. 58.71% vs. 14.57%, untreated vs. -CD99-A192, p=0.002 and A192 vs. -CD99-
A192, p=0.005). On the other hand, expanded T cells treated with -CD99-A192 exhibit increased
cell proliferation compared with the untreated control and A192 treated T cell groups. The trypan
blue cell counts of the -CD99-A192 treated T cells are significantly higher than the controls,
untreated and A192 treated T cell groups, on day 5 after the treatment (Figure 21B, Day 5:
untreated vs. A192 vs. -CD99-A192, 97% vs. 92.4% vs. 163.3%, p=0.042 and p=0.03). The cell
proliferation was also tracked using the cell trace assay which exhibited a shift in the peak as the
days progressed. Compared with the control naïve T cells and A192 treated T cells, -CD99-A192
treated T cells exhibit a significant decrease in the intensity of the CFSE dye (Figure 21C-F, T
cells: Day 6: untreated vs. A192 vs. -CD99-A192, 58.86% vs. 57.25% vs. 35.23%, untreated vs.
-CD99-A192, p=0.009 and A192 vs. -CD99-A192, p=0.02). The cell proliferation across
unstimulated PBMCs was not significant across all groups implying no significant increase or
decrease in proliferation.
44
Figure 21. Treatment with -CD99-A192 increases cell proliferation in T cells.
A, Cell viability of PBMCs treated with -CD99-A192 and control groups from Day 1- Day 10
by trypan blue cell counts was assessed and quantified. B, Cell viability assay of expanded T cells
treated with -CD99-A192 and control groups from Day 1- Day 10 by trypan blue cell counts was
assessed and quantified showing a significant increase in -CD99-A192 treated group observed
on Day 5 compared with control groups. Flow cytometry panels showing CFSE+ cells as C,
PBMCs and D, T cells by Cell Trace Assay. Bar graph comparing the percentage of CFSE positive
45
cells of the control and -CD99-A192 treated E, PBMCs and F, T cells. The differences between
the groups were analyzed with ANOVA with Tukey correction. (**,P<0.01; *,P<0.05). The
experiments were performed utilizing samples obtained from three donors.
46
-CD99-A192 increases the expression of activation markers but does not affect the T cell
phenotypes.
To explore T cell phenotypes after treating the T cells with -CD99-A192, the following T
cell populations were observed by flow cytometry: CD4+
, CD8+
and CD25+ T cells (Figure 22AH). When comparing the percentage of CD4+
, CD8+
and CD25+ T cells between the control
untreated, A192 treated PBMCs, and -CD99-A192 -treated PBMCs, there is a significant increase
between the percentage of CD3+ T cells of -CD99-A192 treated PBMCs compared with the A192
treated PBMCs (Figure 22I, A192 vs. -CD99-A192, 67.73% vs. 84.93%, p=0.04); however, no
significant differences were observed in other phenotypes. There were no significant differences
in the percentage levels of CD4+
, CD8+
and CD25+ across treatment groups. (Figure 22J).
Analysis of the T cells activation markers, CD38 and CD69 showed a significant increase
in CD38 levels in the -CD99-A192 group compared with the control A192 (Figure 22K-N, CD38:
A192 vs. -CD99-A192, 1 vs. 1.182, p=0.003). While CD69 expression was higher in the -
CD99-A192 group compared with the control A192, the difference was not statistically significant.
47
48
Figure 22. -CD99-A192 increases expression of activation marker CD38 but does not affect
T cell phenotypes.
Flow cytometry panels of control, untreated and A192, and -CD99-A192 treated PBMCs for A,
CD3, B, CD4, C, CD8 and D, CD25. Flow cytometry panels of control, untreated and A192, and
-CD99-A192 treated T cells for E, CD3, F, CD4, G, CD8 and H, CD25. I, Quantified percentage
levels of CD3, CD4, CD8 and CD25 untreated, A192 treated and -CD99-A192 treated PBMCs.
J, Quantified percentage levels of CD3, CD4, CD8 and CD25 untreated, A192 treated and -
CD99-A192 treated T cells. K, Flow cytometry panel exhibiting CD3+CD69+ cells (Q2) for
control A192 T cells and T cells treated with -CD99-A192. L, Flow cytometry panel exhibiting
CD3+CD38+ cells (Q2) for control A192 T cells and T cells treated with -CD99-A192. M,
Percentage of CD69+ for A192 and -CD99-A192 treated t cells where no significant change is
observed in the -CD99-A192 treated T cells compared to the control. N, Percentage of CD38+
for A192 and a-CD99-A192 treated T cells where a significant increase is observed in the -CD99-
A192 treated T cells compared to the control. The differences between the groups were analyzed
using unpaired t tests (**,P<0.01; *,P<0.05). The experiments were performed utilizing samples
obtained from three donors for T cell phenotyping and five donors for CD69 and CD38 activation
marker analysis. The T cells utilized in these experiments were expanded using PHA and IL2 from
the PBMCs obtained from healthy donors.
49
-CD99-A192 alters gene expression in T cells.
We analyzed the RNA-sequencing results for -CD99-A192 treated T cells and control T
cells for understanding gene enrichment and the involved pathways. We identified 274
differentially expressed genes with 164 (59%) upregulated genes and 110 (40%) downregulated
genes in -CD99-A192 treated T cells compared to control A192 treated T cells. Among the
upregulated genes, we found many genes that encoded inflammatory and immune responses
(Figure 23C, IL1B: A192 vs. -CD99-A192, 6.882 log fold change, IER3: A192 vs. -CD99-
A192, 2.555 log fold change, CXCL3: A192 vs. -CD99-A192, 5.455 log fold change, CXCL5:
A192 vs. -CD99-A192, 8.286 log fold change). Among genes that are associated with T cell
exhaustion such as PD-1, CTLA-4, TIM-3, and LAG-3 (Thommen & Schumacher, 2018), we
found a significant downregulation of the exhaustion marker HAVCR2 (TIM3) (A192 vs. -CD99-
A192, -0.72 log fold change, q=0.03) and CD84 (A192 vs. -CD99-A192, -0.61 log fold change,
q=0.01). We found significant enrichment in -CD99-A192 phenotype of pathways involved in
inflammatory response, immune response, T cell activation and differentiation such as TNFa
signaling via NFKB (NES: 2.94, p<0.001, q<0.001), inflammatory response (NES: 2.63, p<0.001,
q<0.001), IL6 JAK STAT3 signaling (NES: 2.31, p<0.001, q<0.001), hypoxia (NES: 1.88,
p<0.001, q=0.003), KRAS signaling (NES: 1.70, p<0.001, q=0.008), IL2 STAT5 signaling (NES:
1.63, p<0.001, q=0.012), and TGF beta signaling (NES: 1.44, p=0.042, q=0.044) (Figure 23A4D).
50
51
Figure 23. -CD99-A192 treated T cells show an altered gene expression with upregulation
of inflammatory pathways compared to control.
A, Gene enrichment plots of the significantly enriched pathways involved in immune and
inflammatory responses. B, Heat map of differentially expressed genes in 3 -CD99-A192 treated
T cell samples compared to control A192 treated T cells. C, Volcano plot showing the differentially
expressed genes according to the log fold change in -CD99-A192 treated T cell samples
compared to control A192 treated T cells. D, Plot showing NES and False Discovery Rate (FDR)
q-values derived from GSEA using relevant gene signatures in 3 -CD99-A192 treated T cell
samples compared to control A192 treated T cells. The experiments were performed utilizing
samples obtained from three donors.
52
-CD99-A192 shows altered cytokine release profile in T cells.
We analyzed the cytokine release profile of the -CD99-A192 treated T cells and the
control A192 treated T cells. We observed changes in the presence and expression of cytokines
involved mainly in the inflammatory and activation pathways on the membranes (Figure 24A-B).
We observed significant increases in IL-1β/IL-1F2 and TNF-α, along with a marked decrease in
IL-8. GM-CSF and IL-16 levels are also increased, though not significantly after adjustment
(Figure 24C, IL-1β/IL-1F2, A192 vs. -CD99-A192, 11-fold change, p<0.001, adjusted p=0.006;
TNF-α, A192 vs. -CD99-A192, 12-fold change, p=0.002, adjusted p=0.03; IL-8, A192 vs. -
CD99-A192, 70% reduction, p<0.001, adjusted p=0.001; GM-CSF, A192 vs. -CD99-A192, 20-
fold change, p=0.005, adjusted p=0.07; IL-16, A192 vs. -CD99-A192, 2-fold change, p=0.003,
adjusted p=0.05).
53
Figure 24. -CD99-A192 treated T cells show altered expression of inflammatory cytokines.
Cytokine Panel Profile membrane visualized for A, control A192 T cells and B, -CD99-A192. C,
Cytokine Panel analysis of control and -CD99-A192 treated T cells. The differences between the
groups were analyzed using multiple unpaired t tests with Holm-Sidak correction for multiple
comparisons (**,P<0.01; *,P<0.05). The experiments were performed utilizing samples obtained
from two donors.
54
-CD99-A192 treated T cells exhibit enhanced cytotoxicity against leukemic cells
We co-cultured the control A192 treated T cells and -CD99-A192 treated T cells with
FITC (CFSE) stained MV4-11 (leukemic cells) at an E:T ratio of 5:1 and measured the apoptosis
by flow cytometry and luciferase assay. The co-culture assays show increased cell apoptosis in the
FITC labeled MV4-11 cells at 18 hours (Figure 25A and 25E , A192 vs. -CD99-A192, 33.6% vs.
41.13%, p=0.015) and a reduction in the viable leukemic cells at 18 hours (Figure 25B and 25F,
A192 vs. -CD99-A192, 10.89% vs. 8.05%, p=0.034) and 48 hours (Figure 25D and 24F, A192
vs. -CD99-A192, 9.69% vs. 6.54%, p=0.065) in the -CD99-A192 compared with the control
A192 treated group. Though no significant increase in cell apoptosis in the -CD99-A192 group
is observed at 48 hours (Figure 25C and 25E). These results indicate that -CD99-A192 induces
enhanced T cell cytotoxicity. We also analyzed the apoptosis in T cells at both timepoints and we
did not observe any significant toxicity in T cells due to -CD99-A192 treatment (Figure 25G-I).
The apoptosis results from flow cytometry were also validated by the luciferase assay. We found
a significant decrease in the percentage of live leukemic MV4-11 and THP-1 cells (luciferase
signal) in the -CD99-A192 group compared with the control (Figure 25J-L, MV4-11: A192 vs.
-CD99-A192, 100% vs. 52.84%, ~47% reduction, p=0.032; THP-1: A192 vs. -CD99-A192,
100% vs. 58.77%, ~41% reduction, p=0.0008). We also observed a decrease, though not
significant, in the percentage of live leukemic MOLM-13 cells (luciferase signal) in the -CD99-
A192 group compared to the control (Figure 25I, A192 vs. -CD99-A192, 100% vs. 74.97%,
~25% reduction, p=0.193).
55
56
Figure 25. -CD99-A192 treated T cells show increased cytotoxicity against leukemic cells.
Flow cytometry panels showing. A, Annexin V positive cells at 18 hours B, FITC+ live MV4-11
cells at 18 hours C, Annexin V positive cells at 48 hours D, FITC+ MV4-11 cells at 48 hours for
A192 and -CD99-A192 treated T cells cocultured with leukemic MV4-11 cells at an E:T ratio of
5:1. Co-culture assays showed E, greater apoptosis in MV4-11 cells at 18 hours, but no significant
apoptosis in MV4-11 cells at 48 hours and F, a reduction in viable leukemic cells at 18 and 48
hours in -CD99-A192 treated T cells cocultured with leukemic MV4-11 cells at an E:T ratio of
5:1 compared to control. Flow cytometry panels showing Annexin V positive FITC- T cells G, 18
hours and H, 48 hours. I, Co-culture assays showed no significant toxicity to T cells at 18 hours
and 48 hours. Luciferase assay also exhibited a reduction in viable leukemic cells in -CD99-
A192 treated T cells cocultured with leukemic J, MV4-11 cells, K, THP-1 and L, MOLM-13 cells
at an E:T ratio of 5:1 compared to control. The differences between the groups were analyzed using
unpaired t tests (***,P<0.001; **,P<0.01; *,P<0.05). The experiments were performed utilizing
samples obtained from three donors.
57
Chapter 4: Discussion
T cells form an integral part of the immune system allowing the body to defend itself
against pathogenic attacks. Owing to the innate cytotoxicity of the T cells, many successful efforts
have been made to harness their cytotoxicity and target it towards cancer immunotherapy. Many
cell surface receptors and targets have been identified which increase the potency of the T cells.
One such cell surface receptor molecule identified in CD99. CD99 plays several functions in T
cells, including cell proliferation, differentiation, and inflammation (Pasello et al., 2018). Various
CD99 targeting antibodies have been developed and their effects on T cells have been studied in
different contexts. Previous studies have established T cell expansion (Wingett et al., 1999),
apoptosis (G. Bernard et al., 1997), activation (Waclavicek et al., 1998a; Wingett et al., 1999),
upregulation of phenotypes and cytokines (Takheaw et al., 2019; Waclavicek et al., 1998a) when
T cells were treated with various CD99 targeting antibodies. CD99 has also been identified as a
potential target in multiple diseases like Ewing sarcoma and AML owing to its overexpression on
malignant cells. Many monoclonal antibodies have been developed against CD99 and tested in a
preclinical testing. These monoclonal antibodies have exhibited cytotoxicity against cancer cells,
which validated CD99 as a role. Our group has previously developed an antibody-based AntiCD99 scFv ELP (-CD99-A192) which has exhibited cytotoxicity against AML cell lines and
prolonged survival in AML xenograft models. Harnessing the functions of CD99 on T cells, we
characterized the effects of -CD99-A192 on T cells and the CD99-induced cytotoxic potential of
T cells.
58
Using the previously developed antibody-based CD99 nanoparticle, -CD99-A192
(Vaikari, Park, et al., 2020), we examined the effects of CD99 ligation on T cells. CD99
engagement with -CD99-A192 significantly increased the T cell proliferation and aggregation.
Increased cell aggregation with -CD99-A192 activation agrees with the previously reported
function of CD99 being involved in cell aggregation. This phenomenon also known as homotypic
adhesion has been reported before with anti-CD99 antibodies in Jurkat cells (Kasinrerk et al.,
2000) and thymocytes (G. Bernard et al., 1995). Cell aggregation also indicates the initiation of T
cell activation and acts as a marker of T cell activity (RUDNICKA et al., 2008). Activation of
CD99 by -CD99-A192 showed an increase in the proliferation of T cells but a decrease in the
number of PBMCs. The decrease in cell numbers following -CD99-A192 treatment was only
observed after the PBMCs cells had been in culture for more than 7 days in the absence of any
cytokines, which could naturally affect their health and survivability. Moreover, -CD99-A192
has been reported to have toxic effects towards leukemic cells which are of myeloid origin (Vaikari,
Park, et al., 2020), which could provide a possible reason towards the enrichment of CD3+
cells
and depletion of other peripheral blood cells evolving from myeloid origin. Nonetheless,
comprehensive toxicity studies are essential to fully establish the safety profile of CD99 antibodybased therapeutics in AML. Though, CD99 induced cell apoptosis in thymocytes has been reported
in double positive thymocytes before undergoing cell differentiation (G. Bernard et al., 1997).
Our study shows that there were no significant differences observed in the percentages of
the CD4+
, CD8+
and CD25+ T cell phenotypes in both the expanded T cells and PBMCs except for
an increase in CD3+
cells in a-CD99-A192 treated PBMCs compared with A192 control. This is
consistent with a-CD99-A192's opposite effects of targeting the myeloid cells while expanding the
59
T cells. In PBMCs, we also observed a slight increase, though not significant, in the expression of
CD25+
cells which could imply enrichment of activated T cells upon treatment with -CD99-
A192. This is consistent with the increased expression of CD38 in expanded T cells, which is
another T cell activation marker that is highly expressed in response to infections (Glaría &
Valledor, 2020).
We also analyzed the expression of CD69, which is an early marker of lymphocyte
activation (Cibrián & Sánchez‐Madrid, 2017; Sancho et al., 2005). However, the CD69 expression
was highly variable among samples, despite RNA-seq analysis showing an upregulation of the
CD69 gene which points towards lymphocyte activation. To capture changes in the expression of
CD69 by flow cytometry, evaluation of different treatment timepoints might be needed.
Treatment of T cells with -CD99-A192 resulted in changes in several cytokines which
can be classified as pro-inflammatory, inflammatory, and immune modulatory cytokines, all
involved in inflammatory and immune responses (Bhattacharya et al., 2015; Bickel, 1993; Idriss
& Naismith, 2000; Mathy et al., 2000; Vijayaraj et al., 2021). It should be noted that, despite all
efforts of removing the bacterial endotoxins from the ELPs during the purification process, even
low levels that persist may cause activation of inflammatory cytokines in the treated cells.
Excluding LPS-induced inflammatory responses, several pathways were associated with -CD99-
A192 treatment in T cells such as IL-2 STAT5 signaling pathway, IL-17 signaling pathway and the
KRAS signaling pathway. Among the T cells activation markers, a-CD99-A192 induced CD38
expression, which has also been linked to increase in production of inflammatory cytokines (Ghosh
et al., 2023). The expression of inflammatory cytokines and enrichment of inflammatory pathways
60
is consistent with the induced inflammatory T cell response observed in the RNA-seq and cytokine
analyses.
With the in vitro co-culture study, within the span of 24 hours, we observed increased cell
apoptosis within the leukemic cells with the early apoptosis marker Annexin and in terms of viable
leukemic cells. These results were also validated by luciferase assay. We did not see the same
magnitude of effects at a later timepoint of 48 hours which is consistent with T cell mediated killing
(Chanda et al., 2022) that occurs shortly after the co-culture. These results highlight the cytotoxic
effects of the activated T cells and indicate the -CD99-A192 treated T cells mediated cell
apoptosis in the absence of direct treatment of the leukemic cells with -CD99-A192, thus
validating the proposed dual cytotoxic mechanism of -CD99-A192 as targeting leukemic cells
while activating T cells. While one of the possible reasons for enhanced cytotoxicity could be
mechanisms contributing to the increased cell activation and proliferation, another possible
mechanism that may explain the early antileukemia effect could be that coating the T cells with
the ELPs on their surface may enable engaging the T cells with leukemic cells overexpressing
CD99. Therefore, -CD99-A192 scFv ELP acts as a linker that brings T cells into contact with the
leukemic cells for an enhanced cytotoxicity.
Future directions for the study could be designed to further explore the activation and
cytotoxic effects of -CD99-A192 treated T cells. The activation effects can be further expanded
to include multiple doses of -CD99-A192 to treat the T cells. It would help determine if the T
cell activation is dose dependent. Mechanistic studies can be conducted to investigate the
activation pathways or signaling pathways playing a role in the CD99-mediated activation of the
61
T cells. Another aspect of the study could include studying the effects of the CD99 isoforms on T
cells. This study can be designed in a way to transfect CD99-deficient Jurkat T cells with one
isoform of CD99 and studying the effects of the treatment of -CD99-A192 on T cells.
To study cytotoxicity, in vivo studies with animal xenograft models can be designed. The
study design could include periodic injections of the -CD99-A192 scFv-ELP treated T cells in
NSG mice engrafted with leukemic cells. The study could be conducted over the span of 21 days
with periodic injections within the span of 5-7 days. At the end of the treatment cycle, the mice
would be tested for leukemic burden in organs like bone marrow, spleen and blood. Another study
that would help explore the cytotoxic effects of the activated T cells would be an apoptosis assay
with a co-culture of the treated T cells and primary AML blasts isolated from AML patient samples,
at different E:T ratios.
Owing to the role of CD99 and its expression profile both on healthy and malignant cells,
anti-CD99 CART cells have been developed which have shown efficacy in pre-clinical settings
(Shi et al., 2021b). After establishing the toxicity profile of the target, CD99 can be studied with
the interest of it being a T cell engager. BiTE (Bispecific T-cell engager) molecules are gaining
interest for their target specificity and for their ability to harness the cytotoxic potential of the
body’s immune cells. CD99, owing to its overexpression in many forms of cancer, can be a receptor
of great interest for the development of a BiTE molecule. The molecule can be designed in such a
way that one part of the molecule binds to CD3 of the T cells and the other part of the molecule
binds to the overexpressed CD99 on the tumors. Another design that can be explored is when one
62
end of the BiTE molecule is designed to bind to the CD99 present on the T cells and the other end
of the molecule would target a unique receptor or mutation on the malignant cells.
In conclusion, -CD99-A192 scFv-ELP nanoparticle activates T cells in terms of
stimulation of T cell proliferation, elevation of activation markers, gene enrichment of pathways
involved in inflammatory and immune responses and increase in the release of pro-inflammatory
cytokines. -CD99-A192 also culminates in heightened cytotoxicity of T cells against leukemic
cells.
63
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Abstract (if available)
Abstract
T cells are a part of the adaptive immune system who have been explored for their cytotoxic potential as a form of immunotherapy. Cluster of Differentiation 99 (CD99) is a transmembrane protein encoded by the MIC2 gene. It is expressed on many human tissues and almost all types of human cells. In normal physiological conditions, CD99 plays role in lymphocyte development, cell adhesion, cell differentiation, apoptosis, leukocyte diapedesis and protein trafficking. The expression of CD99 is found to be higher on T cells with varying levels of expression on various T cell subsets.
CD99 is overexpressed in many diseases including, Acute Myeloid Leukemia (AML), presenting a potential novel therapeutic target. Our group has previously developed anti-CD99- A192 (a-CD99-A192), comprising of single chain variable fragment (scFv) and elastin-like polypeptides (ELPs), and reported promising anti-leukemic activity in AML preclinical models. Treatment with a-CD99-A192 induced apoptosis in AML cell lines and prolonged survival in AML xenograft models. Considering CD99's expression and role in T cell activation, in the current study, we propose that a-CD99-A192 could have a dual function, i.e., targeting leukemic cells and activating T cells. This manuscript reports the effects of a-CD99-A192 on T cells in the context of AML.
To explore the effects of a-CD99-A192 on T cells, we obtained blood samples from healthy donors, to isolate Peripheral Blood Mononuclear Cells (PBMCs) using the Ficoll- centrifugation method. We expanded T cells using cytokine expansion and treated the T cells with our control ELP and a-CD99-A192 ELP. We explored the effects of a-CD99-A192 on T cells by conducting proliferation assays using cell count method and cell trace, T cell phenotyping by flow cytometry to understand the expression of T cell markers, activation marker expression analysis by flow cytometry, cytokine release profile analysis and gene expression analysis. We also explored the cytotoxic effects of the a-CD99-A192-activated T cells by designing a co-culture assay of the a-CD99-A192 treated T cells and leukemic cell lines. The apoptosis was measured by flow cytometry and luciferase assay.
We found that a-CD99-A192 is effective binding to T cells and induces increased aggregation of T cells, also known as homotypic adhesion. a-CD99-A192 treatment enhances T cell proliferation and doesn’t affect the T cell phenotype expression. a-CD99-A192 treatment also showed an increase in the expression of activation markers activation and increase in the release of pro-inflammatory cytokines in T cells. a-CD99-A192 treated T cells exhibited heightened cytotoxicity against leukemic cells. Altogether, these findings suggest a-CD99-A192 enhances T cell activation and cytotoxic potential consistent with dual mechanisms of action for a-CD99- A192.
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Kadam, Shephali Milind
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Investigating the effects of targeting CD99 on T cells to enhance their antileukemia activity
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Pharmaceutical Sciences
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2024-08
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Tags
acute myeloid leukemia (AML)
antibodies
CD99
immunotherapy
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