Nur-Afidah Mohamed Suhaimia, Wai Min Phyoa,b, Hao Yun Yapa · Nur-Afidah Mohamed Suhaimia, Wai Min Phyoa,b, Hao Yun Yapa, Sharon Heng Yee Choy c , Xiaona Wei a , Yukti Choudhury a,b

Metformin Inhibits Cellular Proliferation and Bioenergetics in

Colorectal Cancer Patient-Derived Xenografts

Nur-Afidah Mohamed Suhaimia, Wai Min Phyoa,b, Hao Yun Yapa,

Sharon Heng Yee Choyc, Xiaona Weia, Yukti Choudhurya,b, Wai Jin

Tana, Luke Anthony Peng Yee Tana, Roger Sik Yin Food,e, Suzanne

Hui San Tand, Zenia Tiangd, Chin Fong Wongf, Poh Koon Kohg and

Min-Han Tana,b,g,h*

aInstitute of Bioengineering and Nanotechnology Singapore. 31

Biopolis Way, The Nanos #09-01, Singapore 138669

bLucence Diagnostics Pte Ltd. 217 Henderson Road #03-08,

Henderson Industrial Park, Singapore 159555

cBiological Resource Centre Singapore. 20 Biopolis Way, Centros #07-

01, Singapore 138668

dGenome Institute of Singapore, 60 Biopolis Street, Singapore 138672

eCardiovascular Research Institute, National University Health

Systems. 14 Medical Way, Singapore 117599

fTan Tock Seng Hospital Singapore. 11 Jalan Tan Tock Seng,

Singapore 308433

gConcord Cancer Hospital Singapore. 19 Adam Road, Singapore

289891

hNational Cancer Centre Singapore. 11 Hospital Drive, Singapore

169610

on October 1, 2020. © 2017 American Association for Cancer Research. mct.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on May 22, 2017; DOI: 10.1158/1535-7163.MCT-16-0793

http://mct.aacrjournals.org/

Running title: Metformin inhibits growth of colorectal cancer PDX

Keywords: Patient-Derived Xenografts, Metformin, Colorectal Cancer,

Next-Generation Sequencing

*Corresponding Author: Min-Han Tan, Institute of Bioengineering and

Nanotechnology, 31 Biopolis Way, The Nanos #09-01, Singapore

138669; Telephone: +65-68247110, Fax: +65-64789010; Email:

[email protected]

Financial Disclosure: This work is supported by the Institute of

Bioengineering and Nanotechnology and Agency for Science,

Technology and Research, Singapore. M.H. Tan received grant from

Biomedical Research Council (Diagnostics Grant & Strategic

Positioning Fund SPF 2012/003 and SPF2015/002)

Word Count: 3842

Total no. of tables and figures: 6




3

Abstract

There is increasing pre-clinical evidence suggesting that metformin, an

anti-diabetic drug, has anti-cancer properties against various

malignancies including colorectal cancer (CRC). However, majority of

evidence which were derived from cancer cell lines and xenografts are

likely to overestimate the benefit of metformin since these models are

inadequate and require supraphysiological levels of metformin. Here,

we generated patient-derived xenografts (PDX) lines from 2 CRC

patients to assess the properties of metformin and 5-fluorouracil (5-

FU), the first-line drug treatment for CRC. Metformin (150 mg/kg) as a

single agent inhibits the growth of both PDX tumours by at least 50% (p

< 0.05) when administered orally for 24 days. In one of the PDX

models, metformin given concurrently with 5-FU (25 mg/kg) leads to an

85% (p = 0.054) growth inhibition. Ex vivo culture of organoids

generated from PDX demonstrate that metformin inhibits growth by

executing metabolic changes to decrease oxygen consumption and

activating AMPK-mediated pathways. In addition, we also performed

genetic characterizations of serial PDX samples with corresponding

parental tissues from patients using next generation sequencing

(NGS). Our pilot NGS study demonstrates that PDX represent a useful

platform for analysis in cancer research since it demonstrates high

fidelity with parental tumour. Furthermore, NGS analysis of PDX may

be useful to determine genetic identifiers of drug response. This is the

first pre-clinical study using PDX and PDX-derived organoids to

investigate the efficacy of metformin in colorectal cancer.




4

1. Introduction

Anti-cancer drug development is often impeded by a lack of suitable

pre-clinical models that are highly predictive of therapeutic efficacy in

humans. Most studies utilizing cell lines and xenografts are useful in

the laboratory setting, but may not translate well to the clinical setting

(1). The failure of many cell line xenografts to accurately predict the

clinical efficacy of anti-cancer agents, is due to their inability to reflect

the complexity and heterogeneity of human tumours (2). Substantial

genetic divergence exists between primary tumour and the

corresponding cell line derived from that tumour, as compared to a

direct transplant of tumour into mice (3–5). Patient-derived xenografts

(PDXs), in which patient-derived tumour fragments are directly

implanted into immunocompromised mice through serial passaging, is

an increasingly recognised tool for drug candidate evaluation. These

PDXs are unlikely to have undergone extensive selection pressure

typically associated with cell line establishment as manifested through

genetic and molecular changes (3), and are thus valuable for drug

studies.

We evaluated the performance of 5-fluorouracil (5-FU), the first-line

treatment for CRC (6), along with the anti-diabetic drug metformin.

Epidemiological studies have suggested the beneficial effects of

metformin in cancer treatment among diabetic patients (7,8). This was

supported by pre-clinical studies, which demonstrate that metformin

has anti-neoplastic activity in breast, colon, lung, and prostate cancer




5

(9–14), spurring significant interest to repurpose metformin as an anti-

cancer agent. Nonetheless, pre-clinical studies often involve

supraphysiological concentrations of metformin that are in excess of

the therapeutic levels achieved in patients. In humans, the initial dose

of metformin is 500 – 1000 mg/daily, and subsequently, a maintenance

dose of 2000 mg/daily is required. Studies performed on cell lines

require elevated doses of metformin (2 – 50 mM) to elicit cellular

response, while in vivo studies require up to 4 times the maximum

clinical dose in humans of 2550 mg/day (15). Thus, it is anticipated that

good, relevant models are necessary for physiological modelling of

metformin.

To the best of our knowledge, this is the first study evaluating the use

of metformin on CRC PDX, a highly relevant system for drug candidate

testing. Using next-generation sequencing (NGS), we interrogated the

molecular profiles of these PDX to evaluate selection pressures

initiated during the course of drug treatment. In addition, we aimed to

identify molecular signatures that influence response to metformin. In

parallel, we utilized CRC organoids to elucidate the mechanistic effect

of metformin.

2. Materials and Methods

2.1 Cell culture maintenance, proliferation and clonogenic assays

Cell lines were obtained in 2012 from ATCC directly while isogenic

lines HCT116 p53+/+ (wildtype, WT) and p53-/- (knockout, KO) were

kindly provided by Dr. Bert Vogelstein (John Hopkins University, MD,




6

USA). Independent authentication of cells was not performed. Cells

were cultured in DMEM with 10% fetal bovine serum, and maintained

in 37°C incubator supplemented with 5% CO2. The MycoAlert™

Mycoplasma Detection Kit (Lonza) was used to test for Mycoplasma

contaimination at defined intervals and the tests indicate that cell lines

were free of Mycoplasma throughout the study.

The CellTiter96® AQueous One Solution Assay (Promega) was used

to assess proliferation of cells incubated with metformin (0 – 20 mM)

and/or 5-FU (10 μM) in the presence of high (4500 mg/L) or low (1000

mg/L) glucose. For clonogenic assay, cells harvested from exponential

phase cultures were plated in six-well plates. Seeding densities varied

from 100 – 300 cells per well. After 7 days, cells were washed with

PBS, fixed with methanol and stained with Coomassie blue. Assays

were done in triplicate. Colonies were counted by two independent

investigators.

2.2 Microsatellite Instability (MSI) Analysis.

MSI was determined using the MSI Analysis Kit version 1.2 (Promega).

Briefly, DNA from matched normal and tumor specimens were

amplified using a panel of markers designed to amplify targeted

microsatellite regions (BAT-25, BAT-26, NR-21, NR-24 and MONO-

27). Fragment analysis was performed to assess the size of

microsatellite repeats and determine MSI status.




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2.3 Development of PDX

Fresh colorectal tumours were obtained from consenting patients at

Concord Cancer Hospital in accordance with protocols approved by the

Institutional Review Board. Tumours were transplanted into severe

combined immunodeficient (SCID) female mice aged 4 – 8 weeks

(InVivos Singapore) under the approved protocol by the Institutional

Animal Care and Use Committee. Tumour specimens were cut into 2 –

4 mm3 pieces and implanted subcutaneously in the left flank of the

mice. PDX was maintained by passaging into subsequent generations

when tumour volumes reached ~1000–1500 mm3. For treatment

studies, tumours were expanded in the left flanks of 5 – 12 mice (at

least 5 evaluable tumours per arm). Mice were grouped into three

arms; (i) control, (ii) metformin or (iii) metformin and 5-FU when tumour

volumes reached 100 – 200 mm3. Mice were treated daily with

metformin dissolved in drinking water (150 mg/kg, orally) and/or weekly

with 5-FU (25 mg/kg, intra-peritoneally) for 24 days. Mice were

monitored daily for signs of toxicity and tumour size was evaluated

twice weekly by caliper measurements using the following formula:

tumour volume in mm3 = [length x width2]/2. Tumour growth inhibition

(TGI) was calculated as shown: TGI = [(tumour volume of control on

day 24 – tumour volume of treated on day 24)/(tumour volume of

control on day 24 – tumour volume of control on day 0)] x 100.

At endpoint, tumours were harvested. A portion of each tumour was

fixed for histological sections and haematoxylin and eosin (H & E)




8

staining, while the remaining portions were snap-frozen or used for

organoids derivation.

2.4 Organoids derivation and cellular respiration assay

Tumours from control mice were used for ex vivo measurement of

cellular respiration. After removal of necrotic tissue, tumours were

washed in HBSS, minced and digested in digestion media (RPMI

media with 5X Penicillin-Streptomycin-Amphotericin B, 10 mM HEPES,

300 U/mL Collagenase, 100 U/mL Hyaluronidase and 10 µM Y-27632)

for 2 hours at 37°C. Digestion media were removed and digested

tissues were resuspended in culture media (Advanced DMEM/F12 with

5X Penicillin-Streptomycin-Amphotericin B, 1X Glutamax, 1X B27, 1X

N-2, 1 mM N-Acetylcysteine, 50 ng/mL rhEGF and 10µM Y-27632),

and filtered through 100 and 40 microns filter. Organoids were

collected from the 40 – 100 microns fraction, and the numbers were

estimated.

Oxygen consumption rate (OCR) of organoids were measured using

Seahorse Bioscience XF96 analyzer as described previously (16). 500

organoids were seeded overnight in a 96-well cartridge and pre-treated

with 0.1 mM or 1.0 mM metformin for 24 hours. Before measurement,

the cells were washed and medium was replaced. Reagents from the

Cell Mito Stress Kit (Seahorse Bioscience) were injected into each well

sequentially and serve as control.




9

2.5 Next-generation sequencing

A customized Ion AmpliSeq™ Colon Panel was designed to amplify

513 regions covering 40 genes implicated in CRC (Supplementary

Table 1). Briefly, the customized panel was designed based on the

multidimensional analysis of genomic profiles in CRC published by The

Cancer Genome Atlas Network (17) and molecular subtypes signatures

(18–20). Hotspot mutations in genes of interest and other genes

related to probable actionable drug targets were identified and ranked.

10 ng of DNA was used to generate libraries using the Ion Ampliseq

library preparation kit v2.0. The barcoded libraries were diluted to 7 pM

for template preparation using the OneTouch 2 instrument and Ion

PGM™ Template OT2 200 Kit. The resulting pooled libraries were

quality control checked using the Ion Sphere quality control kit, and

were then sequenced on the Ion Torrent PGM using a PGM 200

sequencing kit v2 and 318 Chip v2 (Life Technologies).

2.6 NGS variant analysis

Point mutations were identified with the Torrent Suite Software v3.0

and the Ion Torrent Variant Caller v4.0 Plugin using the somatic high

stringency parameters and the targeted and hotspot pipelines. A 5%

allele frequency threshold and 500X minimum coverage was set to

report de novo mutations. All the variants identified were established by

visualizing the data through IGV 2.3 (Broad Institute). Concurrently,

orthogonal verification of variant calls made was performed using the

iCMDB™ (Vishuo Biomedical, Singapore) platform which provides




10

variant annotation, as well as Sanger sequencing for variant validation.

2.7 Western Blot

100 mg of snap-frozen tissues were lysed in RIPA buffer containing

protease and phosphatase inhibitors. Protein extracts (50 μg) were

electrophoresed on 4-12% Bis-Tris gels and transferred to PVDF

membranes. Membranes were blocked with 5% bovine serum albumin

in Tris-buffered saline and incubated overnight at 4˚C with 1:1000

dilutions of anti-phospho-mTOR (Ser2448), anti-mTOR, anti-phospho-

p70S6K (Thr389), anti-p70S6K, anti-phospho-AMPKα (Thr172), and

anti-AMPK antibodies (Thermofisher). Membranes were then washed

and incubated with a 1:2000 dilution of horseradish peroxidase-

conjugated goat anti-rabbit secondary antibody. Immunoreactive bands

were detected by chemiluminescence using the ECL Prime Western

Blotting Kit (GE Healthcare). Intensity of each immunoreactive band

was quantified by densitometry using Image J software, and expressed

relative to the control mice after normalization to ß-actin.

2.8 Statistical analysis

Sample size determination for in vivo studies was performed using

preliminary data generated from cell line xenografts a priori. Briefly,

number of samples required per treatment group is 4, at 95%

confidence level and 80% power, for a desired effect size of at least

1000 mm3. For all experiments, Mann-Whitney and Kruskal-Wallis tests

were used to determine the differences between two groups, or three




11

and more groups respectively. P-values <0.05 were recognized as

statistically significant.

3. Results

3.1 Growth inhibition of 5-FU and metformin on cancer cell lines

Metformin has been reported to preferentially inhibit the growth of p53-

mutant cells by forcing a metabolic burden that result in selective

toxicity (9,21,22). However, recent evidence suggests that metformin

requires p53 activity for metformin-induced growth inhibition (23,24). To

investigate whether metformin affects tumour proliferation in a p53-

dependent manner, we screened a panel of CRC cell lines with known

p53 statuses (Table 1), including a pair of isogenic cell lines HCT-116

(p53-WT and p53-KO). Increasing concentration of 5-FU at micromolar

levels results in a growth inhibition of all CRC cells (Figure 1A) while

supraphysiological concentrations of metformin were required to

achieve 50% cell growth inhibition (relative to untreated cells) at 48

hours (Figure 1B).

Under glucose-deprived conditions, the degree of growth inhibition by

metformin is higher in CRC lines (Figure 1C). There was no differential

growth inhibition in response to 5-FU (Figure 1D) and metformin

between the paired isogenic p53 lines (p = 0.206) as was previously

reported, although cells with p53-WT were inhibited to a greater extent

under low glucose conditions (p = 0.06) (Figure 1E). The clonogenic

ability of p53-WT and p53-KO cells were similar upon metformin

treatment (p = 0.743); nonetheless, cell growth for both lines were




12

severely impaired under glucose-deprived conditions (Figure 1C and

1D).

Approximately 15% of CRC display miscrosatellite instability and are

classified as microsatellite instable (MSI) or microsatellite stable

(MSS). Characterization of CRC cells for MSI/MSS status indicates that

there was no difference in response to metformin between MSI and

MSS cell lines. Essentially, our results indicate that there is non-

differential growth inhibition to metformin, regardless of microsatellite or

p53 status.

3.2 PDX Generation

2 primary CRC tumours, FIT-CRC-086 and FIT-CRC-104, with different

clinicopathological characteristics (Table 2), were engrafted into 4 – 6

weeks old female SCID mice. Growth rates ranged from 8 to 15 weeks

for the initial transplantation to reach a tumour volume of 1000 – 1500

mm3, and 3 to 8 weeks for subsequent passages. Histopathology of

patient’s primary tumours and various xenograft passages showed that

the PDX models retained the original morphology of the human primary

tumour (Figure 2A).

3.3 Non-differential inhibition of metformin on PDX

To evaluate tumour response in vivo, we utilized two PDX models with

differing p53 and MSI/MSS status (Table 1). Mice treated with

metformin had a lower tumour burden as compared to control group,

regardless of p53 nor microsatellite status (Figure 2B – 2D). Metformin




13

was able to slow tumour growth initially, but at 12 days post-treatment

initiation, PDX tumours eventually progressed. After 24 days of drug

treatment, the average tumour volume of the metformin-treated group

was reduced by 50% (p = 0.056) and 65% (p < 0.05) for p53-wildtype

and p53-mutant PDX respectively. A systemic effect of metformin on

cell growth was observed in the PDXs independent of tumour p53

status, with more pronounced growth inhibition being observed in the

PDXs with mutant-p53.

When metformin was administered concurrently with a clinically

acceptable dose of 5-FU, only an additional 4% (p = 0.767) tumour

inhibition was observed in in PDX-FIT-CRC-104; in contrast, a

pronounced tumour growth inhibition of 85% (p = 0.054) was observed

in PDX-FIT-CRC-086.

3.3 Metformin activates AMPK pathway

To determine whether metformin influenced the AMPK and mTOR-

signalling pathway in the PDX materials, we evaluated the

phosphorylation of AMPK, mTOR and p70S6K (Figure 2E). Metformin

treatment activated AMPK as determined by phosphorylation at

Thr172, with a corresponding inhibition of mTOR signalling and

downstream target phosphorylation of p70S6K. In tumours treated with

metformin and 5-FU, AMPK was activated; interestingly, mTOR

signalling appears to be activated and not suppressed although

phosphorylation of p70S6K was inhibited (Figure 2F).

3.4 Metformin inhibits oxygen consumption rate (OCR)




14

For ex vivo measurement of oxygen consumption, organoids derived

from PDX were treated with metformin (Figure 3A). Drugs affecting

mitochondrial functions were used in parallel to demonstrate normal

mitochondrial function. Metformin inhibited OCR of both FIT-CRC-086

and FIT-CRC-104 (Figure 3B and 3C respectively) in a concentration-

dependent manner. Consequent injection of oligomycin did not

suppress the OCR further in these metformin-treated organoids, while

injection of FCCP, the mitochondrial uncoupler, rescues the respiration

inhibition, albeit to a lesser extent in the metformin-treated organoids

as compared to control.

Correspondingly, metformin inhibition on cellular respiration resulted in

an increase in glycolysis, as measured by the extracellular acidification

rate (ECAR) (Figure 3D and 3E). It was evident that metformin inhibits

mitochondrial function as early as 4 hours (Figure 3F and 3G).

3.5 Molecular profiling of circulating biomarkers in mice

To determine if tumour burden in vivo can be assessed using

alternative approaches that are viable in the clinical setting, we

investigate the use of cfDNA in our models (25). CfDNA is a

heterogeneous mixture of normal and tumour-associated cell

populations (26,27) which makes cfDNA analysis technically

challenging. In xenografts, both human and mouse-derived cell

populations are present, and the ability to distinguish these two cell

populations is critical in order to assess the PDX response to treatment

using cfDNA. Here, using a limited amount of cfDNA, our assay can




15

distinguish human and mice-derived DNA efficiently (Supplementary

Figure 1), with limit of detection of 10% human DNA in a background of

mice DNA. No cfDNA was detected at week 0, at the point of tumour

implantation. Subsequent evaluation of the cfDNA at different

timepoints in the course of treatment indicate that human-derived DNA

could be detected in the mice blood, suggesting that cfDNA could be a

viable non-invasive biomarker for tumour burden.

3.6 Mutation profile of primary tumour and corresponding

xenografts

Human samples and PDX were analysed for variants/mutations by

NGS using a panel of 40 genes commonly implicated in CRC. The

mean sequencing depth across all experiments was 1,385X for FIT-

CRC-086 and 2,534X for FIT-CRC-104. A summary of annotated

variants are shown in Figure 4A.

For FIT-CRC-086, mutations in APC (K1350*), KRAS (G12V), TP53

(R248Q) and SMAD4 (L495R) were observed for parental tumour and

xenografts, but were not present in germline or normal colon. Likewise,

in FIT-CRC-104, mutations were observed in KRAS (A146T) and

MLH1 (R100*) in parental tumour. Essentially, mutations remain

conserved across PDX passages. An example of a variant conserved

in tumour and PDX as depicted by NGS are corroborated by Sanger

sequencing in Figure 4B. Interestingly, we also observed the presence

of variants that are not reported in COSMIC database. Using Sanger

sequencing, we verified the non-COSMIC variants that were detected




16

(Figure 4C). Nonetheless, non-COSMIC variants were not present in

every PDX. Within the same treatment subset, individuals exhibit

heterogeneity. Whether these new variants were a function of clonal

selection of a subset of tumour cells warrants further investigation.

One of the key objectives of performing NGS is to identify biomarkers

that may reflect response to metformin. Our analysis indicates that

there are no key CRC genes that are associated with metformin’s

activity.

4. Discussion

Metformin has been extensively reported as a promising anti-cancer

agent in cancer prevention and therapy (9–12,21,22,28,29). In the

present study, we evaluated the effects of metformin using pre-clinical

models. Similar to reported studies, we observed that the anti-

proliferative properties of metformin manifest at supraphysiological

conditions in cell lines (30). A recurrent feature is that these cells are

typically maintained in non-physiological conditions that are optimised

only for in vitro growth and proliferation. The excessive concentration of

growth factors, insulin and glucose may account for the elevated doses

of metformin required to elicit cellular responses and trigger metabolic

stress. As such, it is virtually impossible to translate these

supraphysiological conditions in the clinical setting, especially when the

pharmacokinetics of the drug is different in culture settings and in the

human body.




17

Consequently, we observed that low glucose conditions accentuated

the growth inhibition by metformin. This is not surprising – glucose

deprivation is a distinctive feature of the tumour microenvironment

caused by the imbalance between nutrient supply and oxygen

consumption rate (31). In a study exploring the role of tumour

microenvironment in potentiating the effect of metformin, metformin is

synthetically lethal with glucose withdrawal in cancer cells (32).

Essentially, this suggests that the clinically irrelevant,

supraphysiological levels needed to observe metformin’s anti-cancer

effects as reported by many in vitro studies merely underlie the

artifactual experimental conditions that poorly reflect actual glucose-

starved in vivo conditions.

Most pre-clinical in vivo models have generally proven to be sub-

optimal for directing clinical application of new anti-cancer therapies,

largely due to their inability to reflect the complexity and heterogeneity

of human tumours. PDX, where surgically resected tumour samples

are engrafted directly into immunocompromised mice, offer several

advantages (33,34). In our study, we have shown that PDX tumours

maintained the molecular, genetic and histological heterogeneity typical

of tumours of origin (35–39). PDX provides an excellent platform to

study cancer biology, analyse cancer therapeutics and novel drug

combinations. In our study, we demonstrated metformin efficacy in our

PDX models. To the best of our knowledge, ours represents the first

study reported for CRC PDX using metformin. Administering

metformin at physiological levels of 150 mg/kg per day in our mice,




18

which is equivalent to initial clinical dose of 500 – 1000 mg/daily in

human, is sufficient to inhibit tumour growth in PDX. Furthermore, we

obserbed that the response to metformin may be independent of p53

status and are inconsistent with the observations reported earlier

(9,24). Conversely, studies conducted in breast cancer indicate that

metformin’s effects are independent of p53 status (40,41). This

contraindication suggests that p53 may not be a reliable companion

biomarker to predict response to metformin.

Studies from a recent phase 2 clinical trial evaluating metformin and 5-

FU in patients with refractory CRC showed only a mild median

progression-free survival (PFS) of 1.8 months and median overall

survival (OS) of 7.9 months, with majority of patients (78%) having

disease progression before 8 weeks (42). For 11 out of 50 patients

(22%) having stable disease at the end of 8 weeks, their median PFS

and OS were 5.6 months and 16.2 months respectively. Likely, the

modest benefits of metformin and 5-FU observed in this trial may be

due to the nature of the refractory CRC cases and that the benefits

may be significant in non-refractory CRC cases.

Interestingly, in our study, we observed that combination of 5-FU with

metformin leads to a pronounced growth inhibition in the p53-mutant

PDX but not in p53-wildtype PDX. It may be possible that p53 status

plays a role in differential response to metformin and 5-FU; however, it

is also likely that 5-FU is non-beneficial in the p53-wildtype PDX since

this PDX have MSI. Indeed, clinical observations have suggested that




19

patients having a deficient mismatch repair system or MSI do not

benefit from 5-FU-based adjuvant therapy in CRC (43,44). Thus, our

observations using PDX are in line with observations obtained in the

clinic, thus emphasizing the crucial role PDXs play as a clinically

relevant model.

To demonstrate the integrity of PDX as suitable models, we performed

high-throughput NGS to characterize the genetic profiles of parental

tumour and PDX. We demonstrate that genes such as TP53, APC,

KRAS and SMAD4, were mutated in the parental tumour and

conserved throughout serial passaging of the xenografts. More

importantly, in an effort to characterize biomarkers that can serve as

companion marker to predict metformin response, we compared the

genetic differences between the two PDX lines. Our NGS analysis

suggests that there is lack of novel actionable genes that may reflect

metformin’s activity based on genotype. Nonetheless, the key limitation

in this particular analysis is likely due to limited variation in genotype

between the two PDX lines.

To gain insight into possible mechanisms of metformin action, we

evaluated the frequently implicated AMPK-signalling pathway (45).

Indeed, our data showed that metformin triggered phosphorylation of

Thr172 on AMPKα, which consequently led to downregulation of

mTOR and its target p70S6K, whose phosphorylation at Thr389 is

necessary for protein synthesis (46). Moreover, we observed that

metformin inhibits oxygen consumption in organoids derived from PDX,




20

as early as 4 hours, with a concomitant increase in glycolysis. Taken

together, it is likely that treatment with metformin activates the AMPK

pathway, which alters the mTOR signalling, and executes a metabolic

change in the cells, which ultimately affects cell growth in the PDX.

We acknowledged that there are several limitations to our current

study. Firstly, we restricted the use of PDX to subcutaneous tumour

models. Subcutaneous models are inferior to orthotopic models since

the former do not represent appropriate sites for human tumours, and

may not be accurately predictive for drug evaluation (47). However,

orthotopic tumour models are time-consuming and technically

challenging. Furthermore, it is difficult to monitor tumour growth, and

sophisticated micro-imaging techniques are required to visualize the

tumour. In anticipation of this limitation (should the need arise to

monitor tumour burden in orthotopic models), we assessed non-

invasive circulating biomarkers (cfDNA) in our subcutaneous PDX

models. Using established techniques that we have utilized previously

for clinical cancer patients (48,49), we demonstrated that it is feasible

to prove the presence of human-derived DNA circulating in plasma.

Utilizing NGS approach could aid in predictive biomarker(s)

identification as a result of drug selection. Since this is a pilot study

involving metformin and PDX, banking on molecular profiles derived

from 2 CRC patients may be inadequate for biomarker discovery

process. Expanding the repertoire of PDX lines with different genetic

make-up are likely to shed more information in future. While the




21

creation of PDX is of clear interest as a means to better define optimal

therapy for CRC, it is undeniable that the high-throughput data are

challenging to manage and visualize. Thoughtful interpretation is

necessary to convert the knowledge derived from existing data in order

to understand treatment outcomes.

In essence, our study demonstrated the utility of PDX in assessing

drug efficacy via molecular analysis, metabolic profiling and

bioinformatics approaches. This is the first study that describes the use

of metformin in CRC PDX and organoids, providing direct evidence of

metformin as an anti-cancer agent in CRC.

Acknowledgements: We would like to thank Concord Cancer Hospital

for the provision of the tissue samples, and Vishuo Biomedical for the

support in the bioinformatics analysis. We would like to thank Chua

Teck Chiew Timothy, Ma Janise Ann Kabiling Lalic, Mukta Pathak and

Hannes Martin Hentze from A*STAR Biological Resource Centre for

their help and support in PDX work. We would also like to thank Chit

Fang Cheok for the helpful discussion on the in vitro work and

Shengyong Ng for the assistance in organoids derivation and culture.




22

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Table 1. p53 and microsatellite status of cell lines and PDX

Sample p53 status Microsatellite instability (MSI)/ Microsatellite stable (MSS)

DLD-1 Mutant MSI

HCT116 Wild-type MSS

SK-CO-1 Wild-type MSS

SW-480 Mutant MSS

PDX FIT-CRC-086 Mutant MSS

PDX FIT-CRC-104 Wild-type MSI

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Table 2. Clinicopathological information of patients with xenografts generated

Patient Histology Tumor Site Tumor Grade

Tumor Type

Tumor Size (Largest Dimension in cm)

AJCC Stage

pT pN pM Lmph Node Invasion

FIT-CRC-086 Adenocarcinoma Rectum 1 Ulcerated 4 IVA 3 0 1a 0/7

FIT-CRC-104 Mucinous Adenocarcinoma

Ascending Colon 2 Localised 5 IIA 3 0 0 0/39

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Figure Captions

Figure 1: In vitro effects of 5-Fluorouracil (5-FU) and metformin on

colorectal cancer (CRC) cells. 5-FU, the first-line treatment for CRC,

inhibits cell proliferation at micromolar levels (A). Millimolar levels of

metformin are required to inhibit cell proliferation at 48 hours, with

pronounced inhibition observed in combination with 10 µM 5-

Fluorouracil (5-FU) (B). Glucose deprivation accentuates growth

inhibition by metformin (C). Inhibition of CRC cell proliferation to 5-FU

(D) and metformin is independent of p53 status, in both HCT116 p53

knock-out (p53 KO) and HCT116 p53 wildtype (p53 WT) cell lines, but

with stronger degree of growth inhibition observed under glucose-

deprived conditions in the presence of metformin (E). Absolute number

of colonies is presented as an average of triplicates (F).

Figure 2: Histomorphological features of parental tumour are retained

in patient-derived xenografts after serial passaging. Representative

tumour cells are indicated by solid arrows; mucins are indicated by

diamond arrowheads (A). Gross morphology of PDX-FIT-CRC-086

tumours treated with metformin and 5-FU (B). Tumour growth profile of

PDX-FIT-CRC-086 (C) and PDX-FIT-CRC-104 (D). Metformin triggers

AMPK activation and inhibits mTOR signaling in PDX (E). Protein

levels were normalized to ß-actin and fold changes are quantified

relative to vehicle control (F).




30

Figure 3: Organoids derived from PDX under 10X (left image) and 40X

(right image) (A). Pre-treatment with 0.1 mM metformin or 1.0 mM

metformin for 24 hours inhibits oxygen consumption rate (OCR) relative

to vehicle control for both FIT-CRC-086 (B) and FIT-CRC-104 (C). with

corresponding increase in glycolysis for FIT-CRC-086 (D) and FIT-

CRC-104 (E). Pre-treatment with 0.1 mM metformin and 1.0 mM

metformin inhibits OCR as early as 4 hours in both FIT-CRC-086 (F)

and FIT-CRC-104 (G). 1.0 μM oligomycin, 1.0 μM carbonyl cyanide-p-

trifluoromethoxyphenylhydrazone (FCCP) and 0.5 μM

rotenone/antimycin A were used as mitochondrial stress controls.

Figure 4: Molecular characterization of germline DNA, parental

tumour, serial passages of xenografts and xenografts treated with

drugs. Variant allelic frequency is reflected on the scale of 0 to 1 (A).

An example of a COSMIC variant detected by next-generation

sequencing (NGS) and independently verified by Sanger sequencing

(B) 2 variants that have not been reported in COSMIC are detected by

NGS and Sanger sequencing (C).
















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