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NMI (near-infrared dye conjugate MAO A inhibitor) outperformed FDA-approved prostate cancer drugs with a unique mechanism based on bioinformatic analysis of NCI60 screening data

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NMI (near-infrared dye conjugate MAO A inhibitor) outperformed FDA-approved prostate cancer drugs with a unique mechanism based on bioinformatic analysis of NCI60 screening data

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NMI (Near-infrared dye conjugate MAO A Inhibitor) Outperformed
FDA-Approved Prostate Cancer Drugs with a Unique Mechanism Based
on Bioinformatic Analysis of NCI60 Screening Data

by

Yihan Qian

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
MOLECULAR PHARMACOLOGY AND TOXICOLOGY

May 2021

Copyright 2021 Yihan Qian

Acknowledgements

I would like to express my special thanks of gratitude to my advisor Dr. Jean C. Shih who gave
me the opportunity to complete this wonderful research, as well as all the faculty members and
students in our lab. Dr. Shih not only provided me with great guidance and support in my topic,
but also taught me how to do the research by myself and how to express my thoughts clearly to
others, which are all very important in the scientific field.
Besides my lab, I would like to thank the rest of my thesis committee members, Dr. Roger
Duncan and Dr. Ian Haworth, for their insightful comments and guidance.
I would also like to thank my parents and friends who helped me a lot in writing and finalizing
the project within the limited time. Their encouragement and company helped me smoothly
complete this project. They also gave me unique ideas to make this project better.

ii
Table of Contents

Acknowledgements..........................................................................................................................ii
List of Tables..................................................................................................................................iv
List of Figures..................................................................................................................................v
Abstract...........................................................................................................................................vi
Introduction......................................................................................................................................1
1. Prostate Cancer................................................................................................................1
2. Monoamine Oxidase A (MAO A)...................................................................................3
3. NMI ( N ear-infrared dye conjugate M AO A I nhibitor)....................................................4
4. NCI60...............................................................................................................................5
5. COMPARE Algorithm....................................................................................................6
Method.............................................................................................................................................7
1. Screening Methodology...................................................................................................7
2. CellMiner.........................................................................................................................8
3. COMPARE Algorithm....................................................................................................8
4. Statistical Analysis...........................................................................................................8
Results..............................................................................................................................................9
1. MAO A Expression in Different Cancer Types...............................................................9
2. MAO A Expression in Prostate Normal Tissues vs. Prostate Tumor Tissues...............11
3. NCI60 Screening Results of NMI..................................................................................15
4. Potencies of NMI in Cancer Cell Lines.........................................................................17
5. Comparison Between NMI and Other FDA-Approved Drugs for Prostate Cancer......23
6. COMPARE Analysis of NMI and FDA-Approved Prostate Cancer Drugs..................28
7. Safety Analysis of NMI and Comparison Between Other Prostate Cancer Drugs........30
8. COMPARE Analysis of NMI and Other Drugs or Compounds....................................32
9. Genes or Pathways Correlated to MAO A.....................................................................35
Discussion......................................................................................................................................40
1. Cancer Types with Increased MAO A Expression other than Prostate Cancer.............40
2. MAO A Expression in Different Prostate Cancer Grades and Types............................41
3. Relationship between MAO A Inhibition and Other Possible Mechanisms..................43
4. MAO A-Mediated Pathway Underlying Prostate Cancer Metastasis............................43
5. Selecting Genes Related to Prostate Cancer in Interacting Genes with MAO A..........45
Conclusion.....................................................................................................................................48
References......................................................................................................................................49
Appendix: Correlation Between MAO A and Top 10 Interacting Genes with MAO A...............53

iii
List of Tables

1. The stages of prostate cancer.......................................................................................................1
2. Comparison of MAO A expression in prostate tumor tissues vs. normal tissues......................12
3. GI50, TGI and LC50 of NMI and FDA-approved prostate cancer drugs..................................24
4. Min-max normalization value and cumulative score of GI50, TGI and LC50..........................26
5. COMPARE results between NMI and FDA-approved prostate cancer drugs...........................29
6. Therapeutic index values for NMI and FDA-approved prostate cancer drugs..........................31
7. COMPARE results between NMI and marketed cancer drugs..................................................33
8. Compounds with correlation over 0.75 between NMI in drug activity.....................................34
iv
List of Figures

1. Different types of treatment for prostate cancer..........................................................................3
2. Chemical structure of NMI..........................................................................................................4
3. Waterfall plot of MAO A expression in NCI60 cell lines.........................................................10
4. Boxplot of MAO A expression in 17 cancer types....................................................................11
5. MAO A expression raw data from different datasets................................................................12
6. Mean graph of growth percent for NMI in NCI60 cell lines.....................................................15
7. Inhibition of growth curves of NMI in NCI60 cell lines...........................................................16
8. Waterfall plot of GI50, TGI, and LC50 for NMI.......................................................................18
9. 3D plot of GI50, TGI and LC50................................................................................................20
10. Boxplots of GI50, TGI and LC50 for NMI..............................................................................21
11. Heatmap of GI50, TGI, and LC50 for NMI and FDA-approved prostate cancer drugs..........24
12. Bar graphs of GI50, TGI, LC50, and cumulative score for NMI and FDA-approved prostate
cancer drugs...................................................................................................................................27
13. COMPARE plots of NMI and FDA-approved prostate cancer drugs.....................................28
14. Therapeutic index values of NMI in NCI60 cell lines grouped by 9 cancer types..................30
15. COMPARE plot of NMI and marketed cancer drugs with top 10 PCC values.......................33
16. COMPARE plots of compounds with highest PCC to NMI in DTP.......................................34
17. Schematic figure outlining MAO A inducing of EMT............................................................36
18. Model showing MAO A-mediated HIF1α/VEGF-A/FOXO1/TWIST1 pathway...................37
19. Model showing MAO A-TWIST1-SEMA3C/Plexin A2/NRP1-cMET pathway...................38
20. Top 10 interacting genes with MAO A....................................................................................39
21. Boxplot of MAO A expression in different prostate cancer grades.........................................41
22. MAO A expression in different kinds of prostate cancers.......................................................42
23. Model showing MAO A-mediated Shh-IL6-RANKL paracrine pathway..............................44
24. Heatmap representing expression levels of top 10 genes interacting with MAO A in prostate
adenocarcinoma vs. prostate glands...............................................................................................46
25. Plots from GEO databases showing gene expression in different cells...................................46

v
Abstract

As a novel target for prostate cancer treatment, MAO A overexpressed in prostate tumor tissues
compared to normal tissues according to database and literature research. This study investigated
NMI (Near-infrared dye conjugate MAO A Inhibitor) efficacy and safety in prostate cancer cell
lines (PC-3 and DU-145) based on NCI60 screening data of 5-dose tests. The results showed that
32 cell lines had 90% growth inhibition at 10 μM treatment and 8 cell lines had 50% growth
inhibition at only 1 μM treatment of NMI. Compared with FDA-approved prostate cancer drugs
which had NCI60 data, NMI outperformed most of these existing drugs in inhibition efficacy
with a relatively safe therapeutic index. With the Pairwise Pearson Correlation Coefficient (PCC)
lower than 0.80 between all marketed anti-cancer drugs, NMI was demonstrated to have a unique
mechanism in cancer inhibition from existing drugs. The research in non-marketed compounds
indicated that NMI may also have a role in protein synthesis. The MAO
A-HIF1α/VEGF-A/FOXO1/TWIST1 pathway and the MAO A–TWIST1–SEMA3C/Plexin
A2/NRP1–cMET pathway provided possible working models of MAO A in prostate cancer
progression. Some genes interacting with MOA A may also influence NMI efficacy. This study
showed that NMI is a potent candidate with unique and complex mechanisms for the treatment
of prostate cancer.

Keywords: prostate cancer, MAO A, NMI, NCI60 screening, COMPARE algorithm

vi
Introduction
1. Prostate Cancer
Among men worldwide, prostate cancer is the second most common cancer and the fifth
most common cause of cancer death. Approximately 99% of cases occur after the age of 50 1 . The
main risk factors for the development of prostate cancer are age, family history, and race.
Prostate cancer is mainly adenocarcinoma, which is inert in most cases but can also be fatal.
Gleason score, serum prostate-specific antigen (PSA) level, and stage are significant prognostic
indicators. Recurrent prostate cancers with mutations of protein-altering are rare. The most
common ones appear in the androgen receptor, PTEN, AKT1 and TP53 genes and are usually in
high-grade prostate cancers 1 .
Nowadays, the staging of prostate cancers is based on the results of digital rectal exam
(DRE), PSA testing, and Gleason score 2 . The Gleason score is calculated according to how much
the cancer cell looks like a healthy cell when being viewed under a microscope. Gleason scores
of 5 or lower are not used, so the lowest Gleason score is 6, which means that the cells look
similar to healthy cells. This kind of cell is called well differentiated. A Gleason score of 7
means that the cells look somewhat similar to healthy cells, which is called moderately
differentiated. With a Gleason score of 8, 9, or 10, the cells look very different from healthy
cells and are called poorly differentiated or undifferentiated 2 . A lower Gleason score also means
that the cancer grows more slowly and is less likely to spread. The staging of prostate cancers
and their characteristics are shown in Table 1 .
1
Prostate Cancer Stage PSA Levels Characteristics
Stage I Low
slow growing; cannot be felt; involves one-half
of 1 side of the prostate or even less; look like
healthy cells

Table 1: The stages of prostate cancer.
DRE: digital rectal exam; PSA: serum prostate-specific antigen.
So far there have been several different types of therapies to treat prostate cancer, which
can be concluded in Figure 1 . Patients in stages I and II are recommended to receive radical
prostatectomy or radiation therapy with hormonal therapy as standard treatment options. Patients
with locally advanced prostate cancer (stage III) should be treated with external-beam radiation
therapy as well as hormonal therapy or just treated with surgery alone. When cancer becomes
metastatic cancer (stage IV), supportive treatment should be used to relieve symptoms and side
effects caused by other treatments. Since there is no cure for metastatic prostate cancer. Mainly
used supportive care include transurethral resection of the prostate (TURP) for bleeding or
urinary obstruction; bone-modifying drugs for osteopenia and osteoporosis or patients with
prostate cancer that has spread to the bone; and intravenous radiation therapy with radium-223,
strontium, and samarium for bone pain 3 . So it can be concluded that current treatments have
2
Stage II
Stage IIA
Medium
cannot be felt; involves half of 1 side of the
prostate or even less; cancer cells are well
differentiated
Stage IIB
found only inside the prostate; large enough to be
felt during DRE; cancer cells are moderately
differentiated
Stage IIC
found only inside the prostate; large enough to be
felt during DRE; cancer cells are moderately or
poorly differentiated
Stage III
Stage IIIA
High
spread beyond the outer layer of the prostate into
nearby tissues or spread to the seminal vesicles
Stage IIIB
grown outside of the prostate gland or have
invaded nearby structures (bladder or rectum)
Stage IIIC
cancer cells are poorly differentiated, look very
different from healthy cells
Stage IV
Stage IVA
High
spread to the regional lymph nodes
Stage IVB
spread to distant lymph nodes, other parts of the
body, or to the bones
limited effectiveness for patients with advanced stages of castration-resistant and metastatic
prostate cancers. Novel and effective therapies based on new targets or mechanisms are urgently
needed.
Figure 1: Different types of treatment for prostate cancer.
LHRH: luteinizing hormone-releasing hormone; AR: androgen receptor; PARP: poly
(ADP-ribose) polymerase
a. Focal therapy is a less invasive treatment that can eliminate small prostate tumors without
having an impact on other parts of the prostate gland. Heat, cold, and other methods are used
mainly for low- or intermediate-risk prostate cancer 3 .
b. Bone-modifying drugs can treat osteopenia and osteoporosis that may be caused or worsened
by hormonal therapy or skeletal-related events but have not been shown to prevent the spread of
prostate cancer to the bone 3 .

2. Monoamine Oxidase A (MAO A)
Monoamine oxidase A (MAO A) is a mitochondria-bound enzyme that degrades
monoamine neurotransmitters (including serotonin and norepinephrine) via oxidative
deamination and produces H 2 O 2 . It was initially found that MAO A has a role in psychoses and
3
neurodegenerative and stress-related disorders 4 . Later studies 5,6 showed that increased MAO A
levels are associated with prostate cancer progression and MAO A may be a key factor in the
aggressive behavior of high grade cancer. MAO A is identified to be one of the most highly
overexpressed genes in Gleason score 8/9-10 prostate cancers compared to Gleason score 7
cancers 6 . Also MAO A expression is proved to be correlated with other prognostic markers such
as preoperative serum PSA 6 , indicating that it may promote the growth of high grade prostate
cancer.
What’s more, Flamand et al. 7 found that an irreversible inhibitor of MAO A, clorgyline
inhibits several oncogenic pathways in prostate cancer cells and can reduce the growth of
prostate cancer cells in vitro and tumor xenografts in vivo , indicating that MAO A may be a
novel target for prostate cancer treatment.

3. NMI ( N ear-infrared dye conjugate M AO A I nhibitor)
The structure of NMI (Near-infrared dye conjugate MAO A Inhibitor, Figure 2 ) is
composed of clorgyline and a near-infrared (NIR) dye (MHI-148) and it is synthesized starting
with commercially available 3-bromopropylamine hydrobromide 8 .
Figure 2: Chemical structure of NMI. MAO A inhibitor (MAOI), clorgyline was conjugated
with MHI-148 via a thioester bond.
4
NMI targets specifically to tumors and has a dual function for diagnosis and therapy for
prostate cancer. Our previous studies showed that NMI can reduce the growth of prostate tumors
by regulating tumor hypoxia and angiogenesis. Tumor hypoxia can mediate the uptake of
MHI-148 by tumor cells, and increase the uptake and retention of NMI by activating the
HIF1α/OATPs signaling axis, thus enhancing the tumor-targeting effect of NMI. The OATP
pathway primarily regulates the uptake of MHI-148, then the hypoxia further promotes the
absorption of the dye. By co-staining with the mitochondrial specific dye MitoTracker Green, it
can be proved that NMI rapidly accumulates in prostate cancer cells and is located in the
mitochondria. Since NIR dyes can be visualized by non-invasive imaging, NMI has a dual
function for diagnosis and therapy for prostate cancer 8 .
Furthermore, our in vitro studies showed that NMI can reduce the colony formation,
migration, and invasion of prostate cancer cells. Our in vivo studies showed that NMI reduces the
growth rate of the tumor, PSA, and tumor MAO A activity of C4-2B (prostate cancer)
tumor-implanted animal models, indicating that NMI can reduce the rate of growth of prostate
xenografts in nude mice 8 .

4. NCI60
Since the early 1990s, the Developmental Therapeutics Program (DTP) of the National
Cancer Institute (NCI) has utilized a panel of 60 human tumor cell lines (NCI60) to screen for
potential new anti-cancer agents and it has had a significant role in the development of many
agents that are now part of standard cancer care 9 . NCI60 screens 60 human tumor cell lines
representing 9 cancer types including leukemia, non-small cell lung cancer (NSCLC), colon
cancer, CNS cancer, melanoma, ovarian cancer, renal cancer, prostate cancer, and breast cancer.
5
The NCI60 screening data identifies and characterizes novel agents by three endpoints: GI50, the
concentration at which growth is 50% of the no-drug control; TGI, total growth inhibition, the
concentration where the number of cells is equal to those at time zero, when the drug is added;
and LC50, the concentration at which the number of viable cells is 50% of those present at time
zero 9 . The data of most agents (including FDA-approved anti-cancer drugs and newly discovered
or synthesized compounds) are available on the DTP website ( https://dtp.cancer.gov ).
In NCI60 data, prostate cancer cell lines are PC-3 and DU-145. PC-3 is a human prostate
cancer cell line from a 62-year old male and was derived from bone metastasis of prostate
adenocarcinoma. PC-3 cells have high metastatic potential. They do not express androgen
receptors and PSA and their proliferation are independent of androgen. PC-3 cells are positive
for neuroendocrine markers and stem cell-associated marker CD44 10 .
DU-145 is a human prostate cancer cell line from a 69-year old male. The patient was
androgen-independent and unresponsive to hormone therapy. It was derived from a central
nervous system metastasis of primary prostate adenocarcinoma origin 11 . DU-145 cells have
moderate metastatic potential and do not express PSA. And it is an AR-positive prostate cancer
cell line 12 .

5. COMPARE Algorithm
Although an early design hypothesis of the NCI60 screen was to identify compounds
with disease specificity, it soon became clear that by studying the patterns of which cells
responded to the compound and which were more resistant, the mechanism of novel compounds
could be obtained. Paull et al. 13 formalized this observation with the COMPARE algorithm.
Dose-response curves for each cell line are converted into end point patterns of GI50, TGI, and
6
LC50. These end point patterns are utilized by the COMPARE algorithm to calculate the
Pairwise Pearson Correlation Coefficient (PCC), measuring how similar the patterns are. A PCC
of 1.0 identifies a perfect match, a PCC of -1.0 means a mirror image, whereas a PCC of 0
indicates that there is no correlation between the two patterns. The COMPARE algorithm is
provided on the DTP website and can be used to perform interactive analysis of screening data
for different compounds. The development of the COMPARE algorithm enables investigators to
search for compounds or molecular targets with similar patterns of sensitivity or expression in
the cell line screen.

Method
1. Screening Methodology
A detailed description of the screening methodology is on the website
https://dtp.cancer.gov/discovery_development/nci-60/methodology.htm . All compounds
submitted to the NCI60 are tested initially at a single high dose (10 -5 M) in the full NCI60 cell
panel. Only compounds that satisfy pre-determined threshold inhibition criteria in a minimum
number of cell lines will progress to the full five-dose assay. Cells lines are grown under the
appropriate conditions and seeded in 96 well microtiter plates and then incubated for one day
under the appropriate environment. After one-day incubation, two plates of each cell line were
measured as initial cell density at time zero (before adding drug). The drug was added into the
rest plates of each cell line in the appropriate concentration range and then was incubated for
additional two days under a certain environment 9 . The number reported for the one-dose assay is
growth relative to the no-drug control, and relative to the time zero number of cells. This allows
detection of both growth inhibition (values between 0 and 100) and lethality (values less than 0).
7
For the five-dose screen, the percentage of growth is calculated at different drug concentrations,
allowing the determination of GI50, TGI, and LC50.

2. CellMiner
Several important forms of bioinformatics analyses of NCI60 are available at the
Genomics and Bioinformatics Group's CellMiner ( https://discover.nci.nih.gov/cellminer/ ) site. It
is a database and query tool designed for the cancer research community to facilitate the
integration and study of molecular and pharmacological data for the NCI60 analysis. It allows
the user to rapidly obtain information for the NCI60 that would otherwise require lengthy data
retrieval, compilation, and assessment. Included are data for relative transcript and microRNA
levels, as well as drug activity. CellMiner also includes pattern comparison functionality that
enables the identification of relationships between these and other parameters 14 .

3. COMPARE Algorithm
Analyses and the PCCs were calculated by using a commercial statistical package
procedure (SAS Institute Inc, Cary, NC).

4. Statistical Analysis
The 3D scatter plot of NMI combining GI50, TGI, and LC50 and boxplots of different
cancer types are made using R (version 4.0.3). R is a programming language and free software
environment for statistical computing and graphics supported by the R Foundation for Statistical
Computing. The comparisons among 9 cancer types were analyzed by the Kruskal-Wallis test.
The comparisons between prostate cancer and the other 8 cancer types were analyzed by the
8
Wilcoxon Signed Rank test. A p-value less than 0.05 was considered to be statistically
significant.

Results
1. MAO A Expression in Different Cancer Types
In order to investigate the role of MAO A in cancer inhibition, I used CellMiner
(RNA-seq gene expression values) to get the expression of MAO A in NCI60 cell lines and made
a waterfall plot ( Figure 3 ). The waterfall plot could help us to get an easier look at which type of
cancer has a higher expression of MAO A. Also, Figure 4 was obtained from the TCGA (The
Cancer Genome Atlas) dataset showing the expression of MAO A in total 17 cancer types. As
shown in Figure 3 , cell lines with higher expression of MAO A are in the higher place of the
waterfall plot. Prostate cell lines PC-3 and DU-145 (in black) are in the top 10 and top 20 of all
59 cell lines. And to take cancer types into consideration, prostate cancer can be the top 3 types,
only after colon cancers and melanoma.
From Figure 4 , it is clear that prostate cancer has the second highest MAO A expression
in these 17 cancer types. And among the 9 cancer types which NCI60 includes, prostate cancer
tissues have the highest expression of MAO A than the other 8 cancer types. With the highest
median and average FPKM of MAO A among these 9 cancers, prostate cancer may have more
relationships with MAO A compared to the other 8 ones. The research in MAO A inhibitors on
prostate cancer is meaningful with the gene expression keeping a relatively high level in prostate
tumors.
9
Figure 3: The graph of MAO A expression in NCI60 cell lines in waterfall plot format. X-axis
represents log2 expression of MAO A in the unit of FPKM a . Cancer types are color-coded: black
= Prostate Cancer; yellow = CNS Cancer; brown = NSCLC; light blue = Colon Cancer; green =
Melanoma; light green = Ovarian Cancer; red = Renal Cancer; purple = Breast Cancer; blue =
Leukumia.
a. FPKM: fragments per kilobase of exon per million reads, normalized fragments of DNA
divided by the total length of all exons in the gene (or transcript).
10
Figure 4: Boxplot of MAO A expression in 17 cancer types from TCGA dataset. Prostate cancer
is pointed in the red arrow.

From both Figure 3 and Figure 4 , it could be concluded that prostate cancer cell lines
have higher expression of MAO A expression than most other types of cancers. Then the
comparison between prostate tumor tissues and prostate normal tissues was searched in order to
see whether NMI could have a role in prostate cancer treatment due to its MAO A inhibition
ability.

2. MAO A Expression in Prostate Normal Tissues vs. Prostate Tumor Tissues
Based on several different datasets, the MAO A expression data of prostate gland and
tumors were calculated and integrated into Table 2 . Figures and raw data from these datasets
were shown in Figure 5 .
11

Table 2: The comparison of MAO A expression in prostate tumor tissues and prostate gland
tissues (normal tissues) from different datasets. Then the fold changes of tumor tissues/normal
tissues were calculated and displayed in the last column.
a. TPM: transcripts per 1,000,000 mapped reads, a unit of the proportion of transcripts in mRNA.
b. Data from GENT2 are in the form of Log2 expression, without the unit. The exact number of
Log2 expressions was calculated from the downloaded expression data, with raw data of
thousands of samples. And Log2FC (fold changes) are displayed on the website. Thus the fold
changes were calculated based on Log2FC.

12
Dataset Prostate Tumor Prostate Gland Fold Change
CRN (Cancer RNA-Seq Nexus) 114.28 TPM a
75.90 TPM 1.51
EMBL-EBI (The European
Bioinformatics Institute)
192.00 TPM 108.00 TPM 1.78
51.00 FPKM 35.00 FPKM 1.46
GENT2 (Gene Expression database of
Normal and Tumor tissues 2)
Log2 = 9.53 b
Log2 = 10.58 2.07
Log2 = 9.28 Log2 = 9.64 1.28
TCGA (The Cancer Genome Atlas) 54.6 FPKM / /
GTEx (The Genotype-Tissue Expression) / 65.50 TPM /
Figure 5: Figures and raw data of MAO A expression obtained from different datasets.
A. MAO A expression in prostate tumor vs. prostate adjacent normal tissues from CRN;
B. MAO A expression in prostate adenocarcinoma vs. prostate gland from EMBL-EBI (in TPM);
C. MAO A expression in prostate adenocarcinoma vs. prostate gland from EMBL-EBI (in
FPKM);
D. Boxplot for MAO A expression in different cancers (GPL570 platform), with p-value and
Log2FC between prostate cancer and prostate normal;
E. Boxplot for MAO A expression in different cancers (GPL96 platform), with p-value and
Log2FC between prostate cancer and prostate normal;
F. MAO A expression data in prostate cancer samples from TCGA;
G. MAO A expression data in prostate normal tissues from GTEx.

From the first three datasets ( Figure 5A-5E ) which have complete data for both normal
tissues and tumor tissues, MAO A expression in prostate cancer is higher than that in normal
tissues. These three datasets measure the MAOA expression in different tissues by using the
RNA-Seq technology. The CRN database uses one of the most common units of RNA-Seq,
TPM, to show the MAOA expression; the EMBL-EBI database uses two different RNA-Seq
units, TPM and FPKM, for MAOA expression in different tissues. TPM is a measurement unit of
13
the proportion of transcripts in mRNA, it represents transcripts per million mapped reads. FPKM
means fragments per kilobase of exon per million reads, it is a normalization of fragments of
DNA dividing by the total length of all exons in the gene (or transcript). For GENT2, it only
shows the Log2FC of tumor/normal without the unit of gene expression. With an average fold
change of 1.62 for tumor/normal, inhibiting MAO A may help treat prostate cancers. Figure 5F
and Figure 5G were supplements to previous data, showing the exact median and average MAO
A expression in tumors and glands. But these two databases only contained one type of tissue
due to the information they focused on. Since the data were in different units. It was not possible
to compare them together. However, the data somehow matched the numbers from other
datasets, showing that the results were reliable. Additionally, Xu et al. 15 found that MAOA
exhibited significantly higher levels in prostate cancer compared to normal prostate gland tissue.
With fold change of 1.63 and 1.60 in Arredouani Prostate and Luo Prostate, respectively. By
comparing the results from datasets and literature, it could be concluded that MAO A expressed
higher in prostate tumors and the fold change of MAO A expression in prostate tumors vs.
prostate gland normal tissues matched (about 1.62).
By combining both database data and experimental results in the literature, prostate
cancer could be proved to have a higher expression of MAO A than prostate gland, indicating
that MAO A inhibitors may have a role in the treatment of prostate cancer. As an MAO A
inhibitor conjugator, NMI could also be expected to be a novel treatment for prostate cancer. So
it was sent for NCI60 analysis to see whether it could be a candidate for the treatment of prostate
cancer as well as other cancer types which may also have higher MAO A expression in tumors
than in normal tissues.

14
3. NCI60 Screening Results of NMI
NMI was first tested at 10 μM in the full NCI60 cell panel. The result of the one-dose test
was presented in Growth Percent. They were the response values in the NCI60 screening assay,
which were the count of remaining cells as a percentage of the count of starting cells. Then the
values were calculated and converted into the mean graph showing the different responses of 59
cell lines to the treatment of NMI ( Figure 6 ).
15
Figure 6: The mean graph of growth percent for NMI in 59 screened cell lines. The zero-point in
the x-axis represents the mean Growth Percent of NMI in these 59 cell lines (= 12.87%). Bars in
the left part mean the growth inhibition of NMI to these cell lines is less potent than the ones in
the right part. Cancer types are color-coded: purple = Breast Cancer; black = Prostate Cancer;
red = Renal Cancer; light green = Ovarian Cancer; green = Melanoma; yellow = CNS Cancer;
light blue = Colon Cancer; brown = NSCLC; blue = Leukemia.

The average Growth Percent was 12.87%, meaning that NMI had an excellent overall
inhibition ability in NCI60 cell lines. From the raw data of Growth Percent, it can be concluded
that 32 cell lines had 90% growth inhibition at 10 μM treatment of NMI. For prostate cancer cell
lines (in black), PC-3 and DU-145 were both in the left part of the mean graph, indicating that
they did not reach the average Growth Percent. But when we focus on the exact number in the
left column, NMI inhibited 79.12% (100% - 20.88%) of cancer cells in PC-3 and 52.98% (100%
- 47.02%) in DU-145 at 10 μM, both were more than 50%. So NMI could still be potent in
prostate cancer treatment and even more potent in many other cancer types.
With a significant growth inhibition in the One-Dose Screen, NMI was then evaluated
against the NCI60 cell panel at five concentration levels (10 -4 M to 10 -8 M) and the results were
shown in Figure 7 .
16
Figure 7: The inhibition of growth curves of NMI in 59 cell lines performed by NCI60 analysis.
The x-axis represents the five concentration levels of NMI, 10 -4 M to 10 -8 M. The y-axis
represents the percentage growth. The 100% growth indicates the observed growth of cells
without treatment. The 0% growth represents no observed growth of cells, corresponding to the
number of cells at the start point. The -100% growth means all cells are killed by the treatment.

As shown in Figure 7 , there are 59 cell lines out of 9 types of cancers used for NCI60
analysis. The inhibition of cell growth of NMI in all cell lines was determined by five-dose
screening, from 10 -4 M to 10 -8 M. At 10 μM treatment, 48 cell lines had 100% growth inhibition
and 9 cell lines had 50% growth inhibition. And 8 cell lines had 50% growth inhibition at only 1
μM treatment of NMI, indicating that NMI has an excellent potency in NCI60 cancer cell lines.
To further investigate the potency of NMI in prostate cancer, the NCI60 screening data were
arranged and analyzed into different following plots.

4. Potencies of NMI in Cancer Cell Lines
Firstly, NCI60 screening data of GI50, TGI, and LC50 values for NMI were arranged
and made into waterfall plots ( Figure 8 ). The most potent cell lines were at the top of the graphs.
The cell line potency for NMI was determined by the GI50, TGI, and LC50 values. A more
potent cell line had a lower concentration in GI50, TGI, and LC50. Therefore, the cell line at the
top of the figure showed the most potency, and the following cell lines decreased progressively.
Although Leukemia cell lines showed great potency in GI50 (at the top of the waterfall plot),
they performed worse in TGI and even the worst in LC50. Overall they were not potent to NMI
treatment. By combining all these 3 waterfall plots, prostate cancer cell line PC-3 showed higher
potency than DU-145 (Shown in the higher place of all 3 waterfall plots). But neither of them
showed higher sensitivity than other of these 59 cell lines. Taking MAO A expression in tumor
and normal tissue shown in Figure 5D and 5E from GENT2 into consideration, only prostate
17
cancer showed higher MAO A expression in tumors (among 9 cancer types in NCI60). The
reason why NMI showed even higher potency in cell lines that had lower MAO A expression in
tumors may be that NMI does not treat cancers only through MAO A inhibition. Also, there were
many other prostate cancer cell lines that were not in the NCI60 panel, among which may
respond better to NMI.

18
Figure 8: The graph of GI50, TGI, and LC50 of NMI in waterfall plot format. The most potent
cell lines of each endpoint are at the top of the plot, with the lowest molar concentration. The
x-axis represents log concentration in GI50, TGI, and LC50 (-3.8 M to -6.8 M). Cancer types are
color-coded: black = Prostate Cancer; yellow = CNS Cancer; brown = NSCLC; light blue =
Colon Cancer; green = Melanoma; light green = Ovarian Cancer; red = Renal Cancer; purple =
Breast Cancer; blue = Leukemia.
A. Waterfall plot of GI50 for NMI; B. Waterfall plot of TGI for NMI; C. Waterfall plot of LC50
for NMI.

For better visualization, R was used to correlate GI50, TGI, LC50 of NMI in a 3D plot
( Figure 9 ). The cell line at the top right of the figure is the most potent, and the one at the
bottom left of the figure is the least potent. In Figure 9 , it can also be proved that PC-3, plotting
at the top right corner of the 3D scatter plot, exhibited higher potency than DU-154 and there
remained many other cell lines at a better place than PC-3.
19
Figure 9: The GI50, TGI, and LC50 of NMI in a 3D scatter plot. The graph is generated by R.
The x-axis is the negative log value of GI50, the y-axis is the negative log value of TGI, and the
z-axis is the negative log value of LC50. The location of each point in the plot indicates the
potency of the cell line to NMI. Cancer types are color-coded: red = Prostate cancer; grey = other
cancers.

To further investigate the difference between prostate cancer cell lines and other cancer
types, 3 boxplots of GI50, TGI, and LC50 were made and shown in Figure 10 . The p-value
among 9 cancer types was calculated by the Kruskal-Wallis test. It is a non-parametric method
for testing whether samples originate from the same distribution. And it is used for comparing
two or more independent samples of equal or different sample sizes. Since the p-values of
20
Kruskal-Wallis tests for GI50, TGI and LC50 were all lower than 0.05 (0.0064, 0.0058, 0.0032),
there was a significant difference between cancer types. However, it was not clear which types
were different. So the Wilcoxon Signed Rank test was used to analyze the difference between
prostate cancer and other 8 cancer types. The Wilcoxon Signed Rank is a non-parametric
statistical hypothesis test used to compare two related samples, matched samples, or repeated
measurements on a single sample to assess whether their population means ranks differ as a
paired difference test.

21

22
Figure 10: Boxplots of GI50, TGI, and LC50 for NMI. The comparisons among 9 cancer types
were analyzed by the Kruskal-Wallis test. The comparisons between prostate cancer and the
other 8 cancer types were analyzed by the Wilcoxon Signed Rank test. The p-values of these
tests were labeled in the plots.
A. Boxplot of GI50 for NMI; B. Boxplot of TGI for NMI; C. Boxplot of LC50 for NMI.

Results showed that the medians of LC50 for leukemia and LC50 for prostate cancer had
significant differences. Some other pairs, like GI50 of breast cancer-prostate cancer, GI50 of
leukemia-prostate cancer, GI50 of melanoma-prostate cancer, TGI of melanoma-prostate cancer,
and LC50 of melanoma-prostate cancer also had p-values close to 0.05. Among them, melanoma
showed somehow different from prostate cancer in all 3 parameters and all of them had a higher
median than prostate cancer as shown in Figure 10 . And from the waterfall plots in Figure 8 ,
melanoma cell lines (in green) were also in a higher place of 3 plots, indicating that the results of
waterfall plots and boxplots matched. However, Figures 5D and 5E from GENT2 showed that
skin cancer had lower MAO A expression. The mechanism of NMI for cancer treatment must
have other genes or pathways involved.

5. Comparison Between NMI and Other FDA-Approved Drugs for Prostate Cancer
In order to have a closer look at how potent NMI is for prostate cancer treatment, the
NCI60 results of FDA-approved anti-cancer drugs for prostate cancer were collected and
compared with the result of NMI. To date, there are 18 cancer drugs approved by the FDA for
prostate cancer, with NCI60 screening data available for 8 of these drugs (Rucaparib, Olaparib,
Enzalutamide, Abiraterone Acetate, Cabazitaxel, Docetaxel, Leuprolide Acetate, and
Mitoxantrone Hydrochloride). The NCI60 data of NMI and these 8 drugs in prostate cancer cell
lines were shown in Table 3 .

23

Table 3: Table of GI50, TGI, and LC50 for NMI and 8 FDA-approved prostate cancer drugs in
NCI60 cell lines PC-3 and DU-145.
Figure 11: Heatmap representing GI50, TGI, and LC50 of NMI and 8 FDA-approved prostate
cancer drugs in NCI60 cell lines PC-3 and DU-145. A warm-to-cool color spectrum (red >
yellow > green) is used to represent the parameter value (0.01 μM > 5 μM > 100 μM).

24
GI50 (μM) TGI (μM) LC50 (μM)
PC-3 DU-145 PC-3 DU-145 PC-3 DU-145
NMI 1.70 3.02 3.98 11.00 9.55 34.70
Rucaparib 23.40 18.20 100.00 36.30 100.00 72.40
Enzalutamide 20.00 31.60 100.00 100.00 100.00 100.00
Abiraterone Acetate 3.98 20.00 100.00 100.00 100.00 100.00
Cabazitaxel 0.01 0.01 79.40 0.01 100.00 100.00
Docetaxel 0.01 0.01 100.00 77.63 100.00 100.00
Leuprolide Acetate 100.00 100.00 100.00 100.00 100.00 100.00
Mitoxantrone 0.14 0.02 1.45 0.47 10.47 11.48
Olaparib 51.29 100.00 100.00 100.00 100.00 100.00
For better visualization, NCI60 screening data of these 9 compounds were presented in
heat correlation maps ( Figure 11 ). Three parameters were coded on a warm-to-cool color
spectrum in which the warmer color (red) represents the lowest values, while the colder color
(green) represents the highest values. Since lower GI50, TGI and LC50 indicate higher potency,
it is clear in Figure 11 that GI50 and TGI of NMI were in the warm range of the color scale.
Compared to prostate cancer drugs, only Mitoxantrone Hydrochloride showed better response in
GI50 and TGI. For LC50, NMI and Mitoxantrone Hydrochloride showed far higher potency to
PC-3 and DU-145 than other drugs.
GI50, TGI, and LC50 are 3 separated but correlated parameters, in order to consider these
3 parameters together, min-max normalization was used to calculate normalized GI50, TGI, and
LC50 for each drug into a range [0, 1] by an equation which is identified as:
, x′ =
x−min(x)
max(x)−min(x)

where x is the original value of endpoints, min and max are the minimum and maximum values
in the set of observed endpoint values; score 0 means the lowest concentration required for each
parameter, and score 1 means the highest. Take GI50 as an example, x is GI50 of each drug,
max(x) is the maximum GI50 among these 9 compounds, and min(x) is the minimum GI50
among them. TGI and LC50 were calculated and normalized in the same way. Then 3 parameters
were added up to calculate the cumulative score (score 0 means the highest efficacy, score 3
means the lowest efficacy). The min-max normalization of GI50, TGI, and LC50 and their
cumulative scores for NMI and FDA-approved drugs in NCI60 prostate cancer cell lines were
shown in Table 4 .

25
Table 4: The min-max normalization value and the cumulative score of GI50, TGI, and LC50 in
different cell lines for NMI and FDA-approved prostate cancer drugs in PC-3 and DU-145. The
lowest cumulative score of each cell line was in red. NMI shows lower GI50, TGI, and LC50
than most FDA-approved prostate cancer drugs and the second lowest cumulative score in PC-3
and DU-145 cell lines.

Additionally, bar graphs of NMI and 8 prostate cancer drugs were made for GI50, TGI,
LC50, and the cumulative score ( Figure 12 ), which can help us easier to see the rank of these 9
compounds in different parameters. The comparison of original GI50 values of NMI with 8
FDA-approved prostate cancer drugs on 2 prostate cancer cell lines indicated that the GI50 of
NMI is more potent than many FDA-approved prostate cancer drugs in both cell lines ( Figure
12A ). Figure 12B showed original TGI values and Figure 12C showed original LC50 values.
The TGI of NMI exhibited higher potency among all the FDA-approved prostate cancer drugs
except Mitoxantrone Hydrochloride in PC-3 cell line and Cabazitaxel and Mitoxantrone
Hydrochloride in DU-145 cell line ( Figure 12B ). The LC50 of NMI showed the second highest
potency compared to other FDA-approved prostate cancer drugs in both cell lines ( Figure 12C ).
Based on the original GI50, TGI, and LC50 values, when compared respectively, NMI displays
26
better GI50, TGI, and LC50 than most of the existing prostate cancer drugs as a prostate cancer
drug candidate.
Figure 12: Bar graphs of GI50, TGI, LC50, and cumulative score calculated after min-max
normalization for NMI and FDA-approved cancer drugs treated prostate cancer cell lines.
A. Bar graph of GI50 of NMI and 8 FDA-approved prostate cancer drugs.
B. Bar graph of TGI of NMI and 8 FDA-approved prostate cancer drugs.
C. Bar graph of LC50 of NMI and 8 FDA-approved prostate cancer drugs.
D. Bar graph of the cumulative score of NMI and 8 FDA-approved prostate cancer drugs.
Y-axis represents concentration in GI50, TGI, LC50 (0 μM to 100 μM), and cumulative score
(0.0 to 3.0). Drugs are color-coded: red = NMI; purple = Rucaparib, green = Enzalutamide;
yellow = Abiraterone Acetate; blue = Cabazitaxel; pink = Docetaxel; light blue = Leuprolide
Acetate; grey = Mitoxantrone Hydrochloride; orange = Olaparib.

As shown in Figure 12D , NMI has the second lowest cumulative score, showing that
NMI has better inhibition results in prostate cancer cell lines (PC-3 and DU-145) than these
FDA-approved drugs except Mitoxantrone Hydrochloride. So NMI has great potency for treating
prostate cancer.
27
6. COMPARE Analysis of NMI and FDA-Approved Prostate Cancer Drugs
According to the MAO A expression and cell lines’ potencies to NMI, it could be
concluded that the mechanism of NMI for cancer treatment was not just because of MAO A
inhibition. In order to compare the mechanism of NMI with FDA-approved prostate cancer
drugs, GI50, TGI and LC50 were used as data inputs to the COMPARE algorithm to calculate
the Pairwise Pearson Correlation Coefficient (PCC). High PCC (> 0.8, shown in yellow, orange,
or red in the matrix COMPARE figure) means two drugs have similar patterns, indicating that
they have similar mechanisms in inhibiting these cancer cell growth. PCC between NMI and
existing prostate cancer drugs were all in green (< 0.8) or black (< 0.0) (shown in the last row of
these 3 graphs in Figure 13 ). Also, the exact numbers of PCC between them ( Table 5 ) were all
lower than 0.8. What’s more, the mechanism of action and the indication of 8 prostate cancer
drugs were also shown in Table 5 . With 6 different kinds of mechanisms shown in Table 5 ,
NMI did not present similar GI50, TGI, or LC50 graphs with these 8 drugs. Since these
mechanisms cover most of the drug treatments to date, it could be indicated that NMI has a
unique mechanism of cancer inhibition, at least for the treatment of prostate cancers.

28

Figure 13: COMPARE plots of NMI and FDA-approved prostate cancer drugs. High PCC (>
0.8, shown in yellow, orange, or red in the matrix COMPARE figure) means two drugs have
similar patterns, indicating that they have similar mechanisms in inhibiting these cancer cell
growth.
A. COMPARE plot of GI50; B. COMPARE plot of TGI; C. COMPARE plot of LC50.

29
Prostate Cancer
Drug (NSC No.) PCC Indication Mechanism of Action
Rucaparib
(756644)
GI50: No data (StdDev = 0)
mCRPC PARP Inhibitor TGI: No data (StdDev = 0)
LC50: No data (StdDev = 0)
Enzalutamide
(755605)
GI50: -0.15
mCRPC and mCSPC Androgen Receptor Inhibitor TGI: 0.38
LC50: 0.29
Abiraterone
Acetate (749227)
GI50: 0.07
mCRPC and mCSPC CYP17 Inhibitor TGI: 0.14
LC50: 0.17
Cabazitaxel
(761432)
GI50: 0.13
mCRPC Antimicrotubular Antineoplastic Agent TGI: 0.11
LC50: 0.24
Docetaxel
(628503)
GI50: 0.26
mCRPC Antimicrotubular Antineoplastic Agent TGI: 0.19
LC50: 0.15

Table 5: Table of the COMPARE results between NMI and FDA-approved prostate cancer
drugs as well as their indications and mechanisms.
mCRPC: metastatic Castration-Resistant Prostate Cancer; mCSPC: metastatic
Castration-Sensitive Prostate Cancer; GnRH: Gonadotropin-Releasing Hormone

7. Safety Analysis of NMI and Comparison Between Other Prostate Cancer Drugs
Figure 14: Therapeutic index (TI) values of NMI for the 59 cancer cell lines screened in NCI60
and grouped by 9 cancer types. Y-axis represents TI which was calculated by LC50/GI50 in
Molar. Cancer types are color-coded: blue = Leukemia; brown = NSCLC; light blue = Colon
30
Leuprolide
Acetate (746847)
GI50: 0.41
palliative treatment of
advanced prostate cancer
GnRH Agonist TGI: No data (StdDev = 0)
LC50: No data (StdDev = 0)
Mitoxantrone
(758450)
GI50: 0.25
advanced prostate cancer
not responding to
hormone treatment
Topoisomerase Inhibitor TGI: 0.24
LC50: 0.42
Olaparib
(753686)
GI50: 0.09
mCRPC PARP Inhibitor TGI: 0.07
LC50: No data (StdDev = 0)
Cancer; yellow = CNS Cancer; green = Melanoma; light green = Ovarian Cancer; red = Renal
Cancer; black = Prostate Cancer; purple = Breast Cancer.

After analyzing the efficacy of NMI to prostate cancer, the indicator of the relative safety
of NMI - the therapeutic index (TI) was calculated and compared with existing drugs. TI values
of NMI in different cancer types were calculated as an LC50 to GI50 ratio and made into a
scatter plot of Figure 14 . High TI values indicate a more favorable safety profile. It was clear in
Figure 14 that NMI has a very good TI (>10) in many of the NCI60 cell lines and leukemia
showed pretty high TI due to its high LC50. However, pretty high GI50, TGI, or LC50
represented no significant cell growth inhibition efficacy. It is important to combine efficacy and
safety to decide whether the new compound was a candidate for cancer treatment.
Then TI of NMI and 8 FDA-approved prostate cancer drugs in prostate cancer cell lines
were calculated and listed in Table 6 . TI of NMI in PC-3 and DU-145 were higher than that of
Rucaparib, Enzalutamide, Leuprolide Acetate, and Olaparib, indicating that NMI was safe
enough to be a candidate for prostate cancer treatment.

Table 6: Table of therapeutic index (TI) values for NMI and 8 FDA-approved prostate cancer
drugs. TI was calculated by LC50/GI50 in Molar.
31
Cell Lines PC-3 DU-145
NMI 5.618 11.480
Rucaparib 4.274 3.978
Enzalutamide 5.000 3.165
Abiraterone Acetate 25.126 5.000
Cabazitaxel 10000 10000
Docetaxel 10000 10000
Leuprolide Acetate 1.000 1.000
Mitoxantrone 74.262 637.889
Olaparib 1.950 1.000
8. COMPARE Analysis of NMI and Other Drugs or Compounds
In addition to the COMPARE with FDA-approved prostate cancer drugs, the COMPARE
analysis was also done between NMI and other marketed drugs in order to investigate other
possible mechanisms of NMI in cancer inhibition. The data were collected from PRIVATE
COMPARE Web Site Navigation with the target set of MAEKETED_DRUGS_GI50. The drugs
with top 10 PCC values compared with NMI were chosen and the COMPARE plot was shown in
Figure 15 . The exact PCC value and the mechanism of these 20 drugs were listed from high
PCC to low PCC in Table 7 , with their drug names and NSC numbers. It could be obviously
seen in Figure 15 that Romidepsin had pretty high PCC with Actinomycin D (0.94, shown in
orange-red).
When we focus on their mechanisms, Romidepsin is a histone deacetylase inhibitor
(HDAC inhibitor) and Actinomycin D is a transcription inhibitor. HDAC inhibitors exert their
anti-tumor effects via the induction of expression changes of oncogenes or tumor suppressors,
through modulating the acetylation/deacetylation of histones and/or non-histone proteins such as
transcription factors and can act as transcription repressors. So it can be proved that drugs with
similar cancer inhibition mechanisms show similar patterns in GI50 mean graphs. Although
PCCs between NMI and these 10 drugs were higher than that of prostate cancer drugs, none of
them reached 0.8 and were all in green (shown in the penultimate line of Figure 15 ). So the
mechanism of NMI should be different from all marketed drugs approved for cancer treatment.

32
Figure 15: COMPARE plot of NMI and marketed cancer drugs with top 10 PCC values.

Table 7: Table of the COMPARE results between NMI and marketed cancer drugs with top 10
PCC values from high to low, as well as their drug names and mechanisms.

To further investigate whether there remain some compounds still in lab work that have
similar patterns to NMI, CellMiner was used for “Pattern Comparison” in drug activity by NSC
number. The ones with a correlation over 0.75 were selected and listed in Table 8 .
33
NSC No. Drug Name PCC-GI50 Mechanism of Action
758252 Carfilzomib (Kyprolis) 0.63 Selective Proteasome Inhibitor
754143 Romidepsin 0.6 Histone Deacetylase Inhibitor
608210 Vinorelbine Tartrate 0.59 Antimicrotubular Antineoplastic Agent
123127 Doxorubicin 0.58 Topoisomerase Inhibitor
758253 Homoharringtonine 0.58 Protein Synthesis Inhibitor
3053 Actinomycin D 0.57 Transcription Inhibitor
82151 Daunorubicin 0.57 Topoisomerase Inhibitor
630176 Romidepsin 0.57 Histone Deacetylase Inhibitor
24559 Mitramycin 0.51 RNA Synthesis Inhibitor
813783 Trabectedin (Yondelis) 0.51 Alkylating Drug

Table 8: Table of compounds with a correlation over 0.75 between NMI in drug activity from
CellMiner Pattern Comparison.

As shown in Table 8 , most of these compounds have not got drug names yet and only
one of them has been in the process of the clinical trial. So all of them are still in lab work or
have some reason for not continuing being studied for cancer treatment. Then these compounds
were searched on PRIVATE COMPARE Web Site Navigation and the COMPARE plots of
GI50, TGI, and LC50 were shown in Figure 16 .

34
Correlations NSC No. Name Mechanism FDA status
0.797 720622 - - -
0.765 762152 ONX-0914 Immunoproteasome -specific Inhibitor Clinical trial
0.761 342443 S-3'-deacetyl-phyllan-thoside - -
0.759 786148 - - -
0.759 76411 olivomycin - -
0.756 795014 - - -
0.755 800374 - - -
0.751 746032 - - -
0.751 634791 - - -
Figure 16: COMPARE plots of compounds with highest PCC to NMI in DTP.
A. COMPARE plot of GI50; B. COMPARE plot of TGI; C. COMPARE plot of LC50.

By combining the PCC of GI50, TGI, and LC50 together, two compounds had relatively
high PCC of all these 3 parameters, with the NSC number of 342443 (PCC-GI50: 0.75,
PCC-TGI: 0.73, PCC-LC50: 0.59) and 800374 (PCC-GI50: 0.76, PCC-TGI: 0.70, PCC-LC50:
0.63). For compound NSC342443 (S-3'-deacetyl-phyllan-thoside), it has been shown to inhibit
transcription or translation in eukaryotic cells and further inhibit the protein synthesis by Garreau
de Loubresse et al. 16 But NSC800374 is a new compound that is still under lab work, no extra
information about it could be found, and the mechanism is undetermined. Therefore, NMI may
also play a role in protein synthesis inhibition other than MAO A inhibition.

9. Genes or Pathways Correlated to MAO A
Since MAO A should be the major target of NMI due to its synthesis, genes or pathways
correlated to MAO A may also be influenced by NMI.
Although MAO A has been proved to have an association with high-grade prostate
cancer, it is still unclear how MAO A promotes prostate cancer progression. According to Wu,
35
J.B. et al. 17 , the overexpression of MAO A in human prostate cancer cell lines will produce
reactive oxygen species (ROS). ROS has been proved to inhibit Prolyl hydroxylase 3 (PHD3),
then the stabilization of hypoxia-inducible factor 1 α (HIF1α) will be increased. Thus it will
induce the epithelial-mesenchymal transition (EMT) which can enhance growth, invasiveness,
and metastasis of prostate cancer cells. The general process from MAO A to EMT can be shown
in Figure 17 .
Figure 17: A schematic figure outlining MAO A stabilization of HIF1α by repression of PHD
activity through ROS production and thus inducing EMT.
ROS: reactive oxygen species; PHD3: Prolyl hydroxylase 3; HIF1α: hypoxia-inducible factor 1
α; EMT: epithelial-mesenchymal transition.

For the detailed pathway from an increasing level of MAO A to EMT and tumor hypoxia,
the MAOA-dependent HIF1α/VEGF-A/FOXO1/TWIST1 pathway is involved 17, 18 . HIF1α causes
the up-regulation of its target genes, including vascular endothelial growth factor A (VEGF-A),
glucose transporter 1 (GLUT1), and Twist family BHLH transcription factor 1 (TWIST1).
Furthermore, the interaction between VEGF and neuropilin-1 (NRP1) activates the
phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signal transduction pathway, leading
to the nuclear output of phosphorylation of forkhead box protein O 1 (FOXO1) transcription
repressor. The nuclear output of phosphorylation then enhances the expression of TWIST1,
thereby promoting EMT. Also, MAO A can repress E-cadherin transcription and promote EMT
in prostate cancer cells by activating the transcription of TWIST1 via AKT/ FOXO1 signaling.
Additionally, the ROS produced by MAO A enhances tumor hypoxia, thereby increasing cancer
progression through the tumor microenvironment. And stimuli like hypoxia can exacerbate MAO
36
A mediated production of ROS. With these factors, the increased MAO A expression level will
promote ROS production, EMT and tumor hypoxia, which will lead to prostate tumorigenesis,
progression, and metastasis. The related pathways and genes of this model were all shown in
Figure 18 , which can essentially describe the role of MAO A in prostate cancer progression.
Figure 18: The model showing how MAO A regulates prostate cancer progression by the
promotion of ROS production, EMT, and tumor hypoxia via HIF1α/VEGF-A/FOXO1/TWIST1
pathway. Also involved in VEGF-A/NRP1 signaling and the AKT/FOXO1 pathway.
NRP1: neuropilin-1; AKT: protein kinase B; GLUT1: glucose transporter 1; VEGF-A: vascular
endothelial growth factor A; FOXO1: forkhead box protein O 1; TWIST1: Twist family BHLH
transcription factor 1; E-cadherin: epithelial cadherin.

In addition to this model, Yin et al. 19 found that MAO A would promote prostate cancer
cell perineural invasion through SEMA3C/PlexinA2/NRP1-cMET signaling. Perineural invasion
(PNI) is a complex process of neoplastic invasion of nerves which has been recognized as a
significant route for the metastatic spread of prostate cancer and it is highly prevalent in PC,
observed in up to 75% of surgical resection specimens 20 . The increased MAO A expression is
associated with the promotion of PNI through a mechanism started with TWIST1-dependent
37
transcriptional upregulation of Semaphorin 3C (SEMA3C). According to Figure 18 , increasing
expression of MAO A will lead to the upregulation of TWIST1. And TWIST1 directly interacts
with the SEMA3C via E-box sites. So MAO A also activates SEMA3C, which subsequently
interacts with Plexin A2 and NRP1 to activate cMET in an autocrine or paracrine manner. cMET
binds to Hepatocyte Growth Factor (HGF) as a receptor tyrosine kinase (RTK) and has been
proved to drive the proliferation, survival, movement, and invasion of cancer cells after
dimerization and autophosphorylation 21 . And the physical interaction of cMET with Plexin A2
and NRP1 leads to its activation, thus promoting PNI in prostate cancer cells. This MAO
A-TWIST1-SEMA3C/Plexin A2/NRP1-cMET signaling in PNI of prostate cancer cells can be
demonstrated in Figure 19 .

Figure 19: The model showing how MAO A promotes PNI of prostate cancer cells via the MAO
A-TWIST1-SEMA3C/Plexin A2/NRP1-cMET signaling, with TWST1-dependent transcriptional
manner and the autocrine or paracrine interaction between SEMA3C/Plexin A2/NRP1 and
cMET.
TWIST1: Twist family BHLH transcription factor 1; SEMA3C: Semaphorin 3C; NRP1:
neuropilin-1; PNI: perineural invasion.
38
Besides these two models of signaling pathways, MAO A has been proved to have a
correlation with different genes. From the UCSC Genome Browser, the top 10 interacting genes
with MAO A (excluding MAO A itself) were shown in Figure 20 . The solid grey lines mean that
the interaction was only supported by literature, while the dashed blue lines mean that the
interaction was only supported by database research. Based on the data provided on Broad
Institute Cancer Cell Line Encyclopedia (CCLE), CPM, NR3C1, GBA, HSPA5, and ARL8B
were negatively correlated with MAO A, while MAO B, MPO, ATP6V1A, GAPDH, and
CKMT1B were positively correlated with MAO A in prostate cancer cells (shown in
Supplementary Figure S1 .)
Figure 20: Top 10 interacting genes with MAO A from the UCSC Genome Browser. Only
MAOA-interacting genes and only the most-mentioned/most-curated interactions are shown in
the graph. The type of lines between two genes was differentially expressed due to their data
sources.
Solid grey lines mean only text-mining support can be found for this interaction, and the
thickness of the line indicates the number of articles supporting it.
Dashed blue lines mean at least one database supports this interaction: the dark blue indicates
that the information is obtained from a paper describing fewer than 10 interactions; while the
light blue indicates that the information is obtained from a high-throughput paper, describing
more than 10 interactions.

What’s more, results from Wu et al. 8 showed the gene expression profiling of prostate
tumor samples in control samples and NMI-treated ones. Genes involved in MAO
39
A-downstream signaling which could promote EMT (VIM, SNAI1, SNAI2, and TWIST1),
tumor hypoxia (VEGFA and GLUT1), and cancer cell migration, invasion, and metastasis (IL6,
IL8, MMP2, MMP9, and MET) all showed reduced expression after NMI treatment; while
Cadherin-1 (CDH1) increased after NMI treatment as it encodes E-cadherin which would be
repressed with increased MAO A. These changes could further confirm the possibility of the two
models mentioned above and the MAO A inhibition ability of NMI.

Discussion
1. Cancer Types with Increased MAO A Expression other than Prostate Cancer
With different data sources from different databases, the comparison between tumor
tissues vs. normal tissues of MAO A expression differed from each other in some cancer types of
NCI60 screening. In literature research, Kushal et al. 22 reported highly expressed MAO A
activity in human and mouse glioma cell lines (1.29 nmol/mg/hr, 126.93 nmol/mg/hr) compared
with no detectable MAO A activity in normal human astrocytes. Liu et al. 23 found that MAO A
expression in non-small cell lung cancer (NSCLC) tissue was higher than that in normal lung
tissue, with a fold change of 2.5. According to Bdaiwi et al. 24 , MAO A expression was found to
be significantly increased (p < 0.05) in cerebrospinal fluid of patients with acute lymphoblastic
leukemia (ALL) compared with control groups. While Ye et al. 25 found that MAO A was
reduced in acute myeloid leukemia (AML), with the fold change of 0.5. So the comparison of
expression for MAO A in leukemia was not the same in different kinds of leukemia. Based on
these text-mining results, it could be indicated that data sources of datasets (mainly from patients
or unpublished laboratory results) were somehow different from the cell or mice experiments
results published in the literature. And these cancer types may also be potent to NMI treatment.
40
2. MAO A Expression in Different Prostate Cancer Grades and Types
According to the results shown before, NMI has been proved to be a potential candidate
for prostate cancer treatment. However, prostate cancer was different from other diseases due to
its progression and metastasis (shown in Table 1 of different stages). So the performance of NMI
in slowing down the cancer progression was also very important to be a novel and effective drug.
Then the expression of MAO A in different cancer stages was obtained from GENT2 (shown in
Figure 21 ).
Figure 21: Boxplot of MAO A expression in different prostate cancer grades. The x-axis
represents the Gleason score of prostate cancer from 4 to 9. The y-axis represents the Log2
expression of MAO A in these tumor cells.

Since a higher Gleason score means a higher stage of prostate cancer, the results showed
that MAO A expression increased with a more serious stage in general. With the major
mechanism of MAO A inhibition, NMI was likely to slow the progression of prostate cancer and
prevent cancer metastasis. For PC-3 and DU-145 cell lines, they were all derived from the
41
metastasis of prostate adenocarcinoma. In order to investigate the cancer progression prevention
efficacy of NMI, cell lines or mice models from previous stages were needed for analysis.
Based on the different conclusions from MAO A expression in overall prostate cancer
and in PC-3 and DU-145 from NCI60, it was greatly possible that MAO A activity differed from
each other in different prostate cancer cells. So Figure 22 was obtained from EMBL-EBI to
show MAO A expression in specific cell types.
Figure 22: MAO A expression in different kinds of prostate cancers from EMBL-EBI. The
x-axis represents MAO A expression in the unit of TPM.

It was clearly shown in the plot that PC-3 and DU-145 had the lowest expression of
MAO A compared to other prostate cancer types such as LNCaP and VCaP. Unlike PC-3 and
DU-145, LNCaP cells express PSA and are androgen-sensitive so that they share remarkable
similarities with human prostate cancer and can closely mimic human disease progression 26 .
Similarly, VCaP cells express large quantities of PSA and are also androgen-sensitive in vivo and
in vitro 27 . Compared to the classical cell lines used in NCI60 screening, LNCaP and VCaP may
be more suitable for studying the effects of drugs in humans. With the highly expressed MAO A,
NMI may be even more potent in other prostate cancer cell lines, which needs further
experiments to prove.
42
3. Relationship between MAO A Inhibition and Other Possible Mechanisms
According to the results of COMPARE between NMI and all compounds provided in
CellMiner, protein synthesis and transcription or translation inhibition may be another
mechanism of NMI in cancer treatment. It seems that these two mechanisms were quite different
in inhibiting tumor progression or tumorigenesis. But Du et al. 28 reported that Cancer-associated
fibroblasts (CAFs) could induce the invasion of EMT and prostate cancer cells through the MAO
A/mTOR/HIF1α pathway, which uses ROS to drive the migration and aggressive phenotype of
prostate cancer cells. As we all know, the mammalian target of rapamycin (mTOR) could
regulate many components involved in protein synthesis, including initiation and elongation
factors, as well as the biogenesis of the ribosome itself 29 . So the upregulation of MAO A may
also activate the protein synthesis via the MAO A/mTOR/HIF1α pathway. In addition, it was
found by Samulitis et al. 30 that one small molecule anti-cancer drug, as a protein synthesis
inhibitor, blocked the translation of new proteins including HIF1α, indicating that NMI may also
inhibit some kind of proteins in the downstream of MAO A signaling pathway besides its major
target to further strengthen its anti-cancer efficacy.

4. MAO A-Mediated Pathway Underlying Prostate Cancer Metastasis
Since prostate cancers often have no obvious symptoms in the early stage and usually
become more fatal with distant metastasis. Another important issue for prostate cancer treatment
is to prevent its metastasis. With most cases of metastasis occurring in the lymph nodes and the
bones shown in Table 1 , curing treatments or prevention for bone metastasis of prostate cancer
are urgently needed. Wu et al. 31 demonstrated that MAO A could also promote prostate cancer
metastasis to the bone by activating the paracrine Shh-IL6-RANKL signaling underlying
43
tumor-stromal interactions. As mentioned earlier, MAO A has been proved to activate TWIST1
and then promote prostate cancer promotion in different pathways. Direct interaction between
TWIST1 and Sonic Hedgehog signaling molecule (Shh) promoter provides the connection
between MAO A and Shh. Then Shh is bound to the transmembrane protein Patched 1 (Ptch1),
activates Gli transcription factors, promoting their translocation to the nucleus and inducing
downstream gene expression including receptor activator of nuclear factor κB ligand (RANKL)
and interleukin-6 (IL6). And the osteoblast production of RANKL and IL6 finally promotes
prostate cancer bone metastasis. What’s more, the transcriptional activation of IL6 by direct
binding of Gli1/Gli2 to IL6 promoter can induce tumor cell proliferation as a feedforward loop,
thus enhancing the prostate cancer progression and metastasis. The overall working model of
MAO A-mediated Shh-IL6-RANKL pathway was shown in Figure 23 .
Figure 23: The model showing how MAO A promotes prostate cancer bone metastasis via the
Shh-IL6-RANKL paracrine signaling pathway.
TWIST1: Twist family BHLH transcription factor 1; Shh: Sonic Hedgehog signaling molecule;
Ptch1: Patched 1; IL6: interleukin-6; RANKL: receptor activator of nuclear factor κB ligand.

It was also reported that the treatment of clorgyline, an MAO A inhibitor could reduce
the expression of both Shh target genes (Ptch1, Gli1, and Hhip) and Shh-interacting partner
44
genes (TGFb1, BMP2, and BMP4) compared with the control group. And the mRNA expression
of RANKL and IL6 in mice bone stromal cells also reduced after clorgyline treatment 31 . So NMI,
with its major target of MAO A, could also be expected to have a role in the prevention of
prostate cancer bone metastasis.

5. Selecting Genes Related to Prostate Cancer in Interacting Genes with MAO A
To further investigate the role of these top 10 interacting genes with MAO A in prostate
cancer, the expression levels of these genes in FPKM in prostate tumor tissues vs. normal tissues
were obtained from EMBL-EBI shown in the heatmap ( Figure 24 ). By comparing the heatmap
results to the scatter plot results shown in Supplementary Figure S1 , ATP6V1A and GAPDH
were upregulated in prostate tumors as well as positively correlated with MAO A expression in
prostate cancer. Others showed minor differences or were not matched with the correlation
results. In addition, the results from GEO databases in Figure 25 showed that CPM was
downregulated in most kinds of prostate cancer ( Figure 25A ), which was also negatively
correlated with MAO A expression in prostate cancer according to Supplementary Figure S1 .
ATP6V1A increased with the prostate cancer progression from prostate intraepithelial neoplasia
to the invasive prostate tumor ( Figure 25B ). For MAO B, the data showed that it decreased with
the prostate cancer progression but could not be detected in metastatic prostate cancer ( Figure
25C ). Overall, CPM, ATP6V1A, and GAPDH may influence prostate cancer with their
interactions to MAO A since their results of expression and correlation with MAO A matched.
Other genes were likely to interact with MAO A via pathways not related to prostate cancer. So
CPM, ATP6V1A, and GAPDH could be further studied to see whether they were related to the
NMI cancer treatment mechanism.
45
Figure 24: Heatmap representing expression levels of top 10 genes interacting with MAO A in
prostate adenocarcinoma vs. prostate glands in the unit of FPKM from EMBL-EBI. A light
blue-to-dark blue color spectrum is used to represent the expression levels from low to high.
46
Figure 25: Plots from GEO databases showing gene expression in different cells.
A. The comparison of CPM expression in prostate cancer cells and normal cells from GDS4824
in the count.
B. The comparison of ATP6V1A expression in prostate intraepithelial neoplasia and invasive
prostate tumor from GDS2443 in Log2 ratio.
C. The comparison of MAO B expression in benign prostate cancer, primary prostate cancer, and
metastatic prostate cancer from GDS1439 in the count.

47
Conclusion
Based on the results of databases and literature, prostate cancer tissues have an increased
level of MAO A expression than normal tissues. Compared with FDA-approved prostate cancer
drugs, NMI, an MAO A inhibitor conjugator, outperformed most of these existing drugs in
prostate cancer cell lines inhibition efficacy with a relatively safe therapeutic index according to
the NCI60 screening data of both one-dose and five-dose tests. The screening data of NMI also
showed that prostate cancer cell lines (PC-3, DU-145) had a median response to NMI treatment
among 59 cell lines showing that the mechanism of NMI in prostate cancer treatment was not
limited to MAO A inhibition. With PCCs lower than 0.80 between all marketed anti-cancer
drugs, NMI was proved to have a unique mechanism in cancer inhibition from existing drugs.
Further investigation in non-marketed compounds indicated that NMI may also have a role in
protein synthesis besides MAO A inhibition. The MAO A-HIF1α/VEGF-A/FOXO1/TWIST1
pathway and the MAO A–TWIST1–SEMA3C/Plexin A2/NRP1–cMET pathway provided
possible working models of MAO A in prostate cancer progression as well as other genes that
may be related to the mechanism of NMI, with a supplement of interacting genes with MAO A.
In conclusion, NMI was proved to be a potential candidate for prostate cancer treatment but the
mechanism underlying its cancer inhibition ability is not simply due to MAO A inhibition (the
original intention of NMI synthesis) and needs further research.

48
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52
Appendix: Correlation Between MAO A and Top 10 Interacting Genes with MAO A
53
Figure S1: Scatter plots of the correlation between the mRNA expression of top 10 interacting
genes with MAO A and the mRNA expression of MAO A in 8 different prostate cancer cells,
including MDA PCa 2b, LNCaP clone FGC, 22Rv1, NCI-H660, PC-3, DU-145, VCaP,
PRECLH. The x-axis represents the mRNA expression of these 10 genes in different prostate
cancer cells. The y-axis represents the mRNA expression of MAO A in these 8 prostate cancer
cells. Results showed that CPM, NR3C1, GBA, HSPA5, and ARL8B were negatively correlated
with MAO A, while MAO B, MPO, ATP6V1A, GAPDH, and CKMT1B were positively
correlated with MAO A in prostate cancer cells.
A. Correlation of ARL8B-MAO A;
B. Correlation of ATP6V1A-MAO A;
C. Correlation of CKMT1B-MAO A;
D. Correlation of CPM-MAO A;
E. Correlation of GAPDH-MAO A;
F. Correlation of GBA-MAO A;
G. Correlation of HSPA5-MAO A;
H. Correlation of MAO B-MAO A;
I. Correlation of MPO-MAO A;
J. Correlation of NR3C1-MAO A.

54

Abstract (if available)

Abstract As a novel target for prostate cancer treatment, MAO A overexpressed in prostate tumor tissues compared to normal tissues according to database and literature research. This study investigated NMI (Near-infrared dye conjugate MAO A Inhibitor) efficacy and safety in prostate cancer cell lines (PC-3 and DU-145) based on NCI60 screening data of 5-dose tests. The results showed that 32 cell lines had 90% growth inhibition at 10 μM treatment and 8 cell lines had 50% growth inhibition at only 1 μM treatment of NMI. Compared with FDA-approved prostate cancer drugs which had NCI60 data, NMI outperformed most of these existing drugs in inhibition efficacy with a relatively safe therapeutic index. With the Pairwise Pearson Correlation Coefficient (PCC) lower than 0.80 between all marketed anti-cancer drugs, NMI was demonstrated to have a unique mechanism in cancer inhibition from existing drugs. The research in non-marketed compounds indicated that NMI may also have a role in protein synthesis. The MAO A-HIF1α/VEGF-A/FOXO1/TWIST1 pathway and the MAO A‐TWIST1‐SEMA3C/Plexin A2/NRP1‐cMET pathway provided possible working models of MAO A in prostate cancer progression. Some genes interacting with MOA A may also influence NMI efficacy. This study showed that NMI is a potent candidate with unique and complex mechanisms for the treatment of prostate cancer.

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Creator Qian, Yihan (author)

Core Title NMI (near-infrared dye conjugate MAO A inhibitor) outperformed FDA-approved prostate cancer drugs with a unique mechanism based on bioinformatic analysis of NCI60 screening data

School School of Pharmacy

Degree Master of Science

Degree Program Molecular Pharmacology and Toxicology

Publication Date 04/24/2021

Defense Date 03/26/2021

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag COMPARE algorithm,MAO A,NCI60 screening,NMI,OAI-PMH Harvest,prostate cancer

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Shih, Jean C. (committee chair), Duncan, Roger F. (committee member), Haworth, Ian (committee member)

Creator Email 939585424@qq.com,yihanqia@usc.edu

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