nur-afidah mohamed suhaimia, wai min phyoa,b, hao yun yapa · nur-afidah mohamed suhaimia, wai min...
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![Page 1: 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](https://reader036.vdocuments.us/reader036/viewer/2022063003/5f768eb7e4002a2fd56e9b5f/html5/thumbnails/1.jpg)
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
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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:
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
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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.
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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
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(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,
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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)
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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.
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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
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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
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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
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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
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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)
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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
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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
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(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.
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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,
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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
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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,
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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
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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.
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49. Mohamed Suhaimi N-A, Foong YM, Lee DYS, Phyo WM, Cima I, Lee EXW, et al. Non-invasive sensitive detection of KRAS and BRAF mutation in circulating tumor cells of colorectal cancer patients. Mol Oncol. 2015;9:850–60.
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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).
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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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Published OnlineFirst May 22, 2017.Mol Cancer Ther Nur-Afidah Mohamed Suhaimi, Wai Min Phyo, Hao Yun Yap, et al. Colorectal Cancer Patient-Derived XenograftsMetformin Inhibits Cellular Proliferation and Bioenergetics in
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