capr-23-0449-html.html

Stool protein mass spectrometry identifies biomarkers for the early

detection of diffuse-type gastric cancer

Running Title: Stool protein biomarkers for early detection of diffuse GC

Chi-Lee C. Ho

1,2

, Michael B. Gilbert

, Guillaume Urtecho

, Hyoungjoo Lee

, David A. Drew

6,7

, Samuel J.

Klempner

, Jin S. Cho

, Thomas J. Ryan

, Naryan Rustgi

Hyuk Lee

, Jeeyun Lee

, Alexander

Caraballo

, Marina V. Magicheva-Gupta

, Carmen Rios

, Alice E. Shin

, Yuen-Yi Tseng

Jeremy L.

Davis

, Daniel C. Chung

, Andrew T. Chan

, Harris H. Wang

, Sandra Ryeom

Department of Surgery, Herbert Irving Comprehensive Cancer Center, Columbia University Irving

Medical Center, New York, NY;

Cell and Molecular Biology Program, University of Pennsylvania

Perelman School of Medicine,

Philadelphia, PA;

Department of Biochemistry and Biophysics,

University of Pennsylvania Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA;

Department of Systems Biology, Columbia University, New York, NY;

Quantitative Proteomics

Resource Core, University of Pennsylvania, Philadelphia, PA;

Clinical Translational Epidemiology

Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA;

Division of

Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA;

Department of Medicine, Division of Hematology-Oncology

Massachusetts General Hospital, Boston,

MA;

Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center,

Sungkyunkwan University School of Medicine, Seoul, Korea;

Broad Institute of MIT and Harvard,

Dana-Farber Cancer Institute, Boston, MA

;

Herbert Irving Comprehensive Cancer Center, Division of

Digestive and Liver Diseases, Department of Medicine, New York, New York, USA;

Surgical Oncology

Program, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD

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ABSTRACT

There is a high unmet need for early detection approaches for diffuse gastric cancer (DGC). We

examined whether the stool proteome of mouse models of GC or individuals with hereditary diffuse GC

(HDGC) have utility as biomarkers for early detection. Proteomic mass spectrometry of stool from a

genetically engineered mouse model driven by oncogenic

Kras

G12D

and loss of

p53

and

Cdh1

in gastric

parietal cells (known as TCON mice) identified differentially abundant proteins compared to littermate

controls. Immunoblot assays validated a panel of proteins including actinin alpha 4 (ACTN4), N-

acylsphingosine amidohydrolase 2 (ASAH2), dipeptidyl peptidase 4 (DPP4), and valosin-containing

protein (VCP) as enriched in TCON stool compared to littermate control stool. Immunofluorescence

analysis of these proteins in TCON stomach sections revealed increased protein expression as compared to

littermate controls. Proteomic mass spectrometry of stool obtained from HDGC patients with

CDH1

mutations identified increased expression of ASAH2, DPP4, VCP, lactotransferrin (LTF), and

tropomyosin-2 (TPM2) relative to stool from healthy sex and age-matched donors. Chemical inhibition of

ASAH2 using C6-urea ceramide was toxic to GC cell lines and patient derived-GC organoids. This

toxicity was reversed by adding downstream products of the S1P synthesis pathway, suggesting a

dependency on ASAH2 activity in GC. An exploratory analysis of the HDGC stool microbiome identified

features which correlated with patient tumors. Here we provide evidence supporting the potential of

analyzing stool biomarkers for the early detection of DGC.

Prevention Relevance:

This study highlights a novel panel of stool protein biomarkers which correlate with the presence of

diffuse-type gastric cancer and has potential use as early detection to improve clinical outcomes.

INTRODUCTION

Gastric cancer (GC) is ranked 4

in prevalence and 4

in mortality among cancers worldwide(1).

Cancer stage at diagnosis is a critical factor in patient prognosis as 5-year survival rates for localized

disease is 70% compared to 6% for patients who present with disseminated disease(2). Regular screening

programs have proven effective in increasing GC patient survival by promoting early-stage disease

detection. In one such case, biennial screening in South Korea for adults over 40 years-old has led to a

significant increase in the diagnosis of GC patients with early-stage disease from 39% in 2001 to 73% in

2016. This is in contrast to the United States where routine screening is not practiced and only 25% of GC

patients present with early-stage disease(3). GC is primarily diagnosed by endoscopy, which is arduous,

resource intensive, and has inherent limitations, particularly in the detection of early-stage gastric cancers

which can be morphologically subtle. Therefore, alternative, non-invasive approaches to detect early-

stage GC are needed.

GC can be histologically classified as diffuse, intestinal, or mixed subtypes(4). Whereas intestinal-

type GC (IGC) has a better prognosis and decreasing incidence, diffuse-type GC (DGC) has a worse

prognosis and rising incidence(5,6). DGC does not classically undergo stepwise development of

metaplasia or pre-neoplastic lesions as seen in IGC, further limiting the ability for early detection through

endoscopic screening(7). The spontaneous nature of DGC development makes studying the disease

difficult; however in cases of hereditary DGC (HDGC), patients possess pathogenic germline mutations,

predominantly in CDH1, which predispose them to developing DGC(8). HDGC is associated with a

cumulative lifetime risk of developing GC between 33-83%(9), thereby necessitating routine surveillance

and providing an opportunity to study DGC. As early-stage DGC frequently appears macroscopically

normal, regular endoscopic screening and extensive biopsies are required for disease surveillance. Thus,

non-invasive approaches to early detection through profiling of tumor-associated biomarkers in bodily

fluids are particularly attractive. Indeed, GC patient saliva, serum, and excreta have been shown to be

variably enriched for tumor-associated DNA(10,11), RNA(12–14), and proteins(15–18). Unfortunately,

these studies have not yet resulted in clinically available biomarker assays for GC detection.

Stool is a promising source of GC biomarkers as it is an easily obtainable direct byproduct of the

gastrointestinal system. We performed an unbiased protein mass spectrometry screen on stool obtained

from genetically engineered mice with mixed-type GC and from HDGC patients to identify potential

biomarkers for DGC detection. Since mass spectrometry of stool is not routinely performed, we validated

our approach using a genetically engineered mouse model of GC previously described by our group

(referred to as TCON mice) with tumorigenesis driven by oncogenic

Kras

G12D

and loss of

p53

and

Cdh1

in gastric parietal cells together with a yellow fluorescent protein (YFP) reporter(19). Proteomic analysis

of TCON mouse stool revealed differential abundance of a panel of proteins which correlated with tumor

development: actinin alpha 4 (ACTN4), neutral ceramidase (ASAH2), dipeptidyl peptidase 4 (DPP4), and

valosin-containing protein (VCP). Immunofluorescence analysis of TCON mouse stomachs with early to

late-stage GC revealed corresponding protein enrichment in the tissue. Proteomic analysis of stool

obtained from HDGC patients identified proteins that overlapped with the mouse panel, namely ASAH2,

DPP4, and VCP, as well as HDGC specific proteins lactotransferrin (LTF) and tropomyosin-2 (TPM2)

that were enriched compared to gender and age-matched healthy individuals. ASAH2, which has not been

previously associated with GC tumorigenesis, is a neutral ceramidase that catalyzes ceramide to

sphingosine which becomes phosphorylated to sphingosine-1-phosphate (S1P), a potent regulator of cell

growth and survival(20). Pharmacologic targeting of ASAH2 reduced viability of GC cell lines and GC

patient-derived organoids that was rescued with the addition of S1P. We also characterize the HDGC

stool microbiome and identified microbial features which correlate with patient disease status. Using an

unbiased approach, we identified proteins enriched in the stool of GC mouse models and HDGC patients

that correlate with disease and may serve as biomarkers for the early detection of DGC.

MATERIALS AND METHODS

Animals

Animal studies were approved by Columbia University Animal Research Compliance. Our

laboratory’s TCON mouse model of mixed type GC was previously described(19). TCON and littermate

control mice were co-housed when necessary. Fresh stool samples obtained from mice were directly

collected into microtubes. For flank tumor studies, TCON cells grown in Dulbecco’s Modified Eagle

Medium (DMEM) supplemented with penicillin, streptomycin, L-glutamine, and fetal bovine serum

(FBS)(Gibco) were subcutaneously injected into the flank of mice at 1x10

cells. The orthotopic mouse

model was generated by injecting C57BL/6 mice with 1x10

TCON cells transduced with luciferase

lentivirus (Cellomics). For the generation of TCON tumor derived cell-lines,

TCON mice stomachs were

minced, digested in 2.5mg/mL collagenase II and 0.5mg/mL DNAse, passed through 40µm strainer, and

cells were grown in complete DMEM media at 37°C with 5% CO

The esophageal adenocarcinoma

mouse model was previously established by another group(21). Briefly, it was generated by adding

deoxycholic acid (Sigma) at 0.3% in water of L2-IL-1β mice for ad libitum consumption beginning at 6-

weeks of age. N-Methyl-N-nitrosourea (MNU)(Spectrum) was added to this water at alternating weeks for

5 treatment cycles. The azoxymethane (AOM)-induced colorectal cancer model was generated using

C57BL/6J mice (Jackson Laboratory) using a method previously described by another group(22). Briefly,

8-week old mice were administered AOM (Sigma Aldrich, A5486) via intraperitoneal injection at a

dosage of 10 mg/kg body weight. This treatment was repeated weekly for a total duration of 6 weeks,

amounting to six injections per mouse. Mice weights were monitored regularly and developed tumors

around 20 weeks post initial AOM treatment. Stool was collected as mice weights declined, indicative of

growing tumors. Tumor growth was validated post-mortem by examining histology slides of the intestinal

tract.

Gastric lavage of mice

Mice were fed a liquid diet (Bio-Serv) 48 hours prior to euthanasia with isoflurane. To collect

gastric fluid, PBS (Corning) was flushed through the stomach and collected. To remove debris, the lavage

was centrifuged at 5000xg for 5 min and the supernatant was retained. This was performed three times.

The supernatant was processed using a DNA/protein isolation kit (Qiagen). Protein was quantified using

DC Protein Assay (Biorad) measured on a SpectraMax iD3. DNA was quantified using a DeNovix DS-11

Spectrophotometer.

Stool Immunoblotting

Stool was dissociated in RIPA lysis buffer (25mM Tris pH=7.4, 2.5mM EDTA, 1% Triton X100,

0.1% SDS, 150mM NaCl) supplemented with 5% SDS and protease inhibitors (ThermoFisher) for 30 min

at room temperature with intermittent vortexing. The solution was centrifuged for 10 min at 15,000xg,

supernatant was collected, quantified by DC Protein Assay (Bio-Rad) on a SpectraMax iD3, mixed with

6x Laemmli buffer, and boiled at 95°C for 5 min. 40



g of lysate per sample was loaded onto pre-cast

SDS-PAGE gels (GeneScript) and electrophoresis was conducted for 70 min at 110V. Gels were

transferred to methanol activated PVDF membranes for 70 min at 110V. Membranes were blocked in 5%

BSA in PBST for 1 hour at room temperature. Antibodies for ACTN4 (Proteintech Group, PTG #19096-

1-AP), ASAH2 (PTG

27742-1-AP), DPP4 (PTG #29403-1-AP), LTF (PTG #10933-1-AP), TPM2 (PTG

#11038-1-AP), VCP (PTG #10736-1-AP), YFP (Abcam #ab13970), and α-tubulin (PTG #66031-1-Ig)

were diluted 1:2000 in 5% BSA in PBST and added to membranes for 1 hour at room temperature.

Membranes were washed three times with PBST for 10 min and incubated with HRP conjugated

secondary antibody (PTG) diluted 1:4000 in 5% BSA in PBST for 1 hour at room temperature.

Membranes were washed 3 times with PBST before incubation with ECL reagent (ThermoFisher) and

imaged using the iBright 1500CL (ThermoFisher).

For dot blot assays, 10µg of protein in 3µL of lysate was spotted onto a nitrocellulose membrane

and incubated at room temperature for 60 min. Membranes were blocked in 5% BSA in PBST for 1 hour

at room temperature. Primary and secondary antibody protocols and imaging are the same as for Western

blots.

Patient stool collection

Stool was collected from patients enrolled in the GI Disease and Endoscopy Registry (GIDER) at

Massachusetts General Hospital. Patients were provided an at-home stool collection kit for use two days

prior to scheduled endoscopy. Stool was self-collected using a tube containing 200 proof ethanol with

enclosed scoop. Once returned, stool samples were centrifuged at 15,000xg for 10 minutes, decanted, and

the pellet was rinsed in ethanol twice and stored at -80°C. Study participants provided written informed

consent. The study protocol was approved by the Mass General Brigham Institutional Review Board

(Protocol #2015P000275).

Studies were conducted in accordance with the Good Clinical Practice and

Declaration of Helsinki

NanoLC-MS/MS of Urea lysed stool

Samples were lysed in a buffer of 8 M urea, 100 mM NaCl, 50 mL Tris-HCl (pH=8) and protease

inhibitors. Samples were sonicated with a Biorupter (Diagenode), incubated on ice, and centrifuged at

21,000xg at 4°C. Protein was quantified using BCA protein assay (ThermoFisher). Proteins were reduced

with 5 mM dithiothreitol for 30 min at 55°C and alkylated with 10 mM iodoacetamide in the dark for 30

min. Proteins were diluted to 2 M urea with Tris-HCl and digested with trypsin (Promega) at an

enzyme:protein ratio of 1:25 for 12 hr at 37°C. The digestion was quenched with 1% trifluoroacetic acid.

Samples were desalted using Pierce C18 Tips, 10 µL bed (ThermoFisher). Peptides were brought to 0.33

μg/μL in 0.1% formic acid.

Samples were analyzed with nanoLC-MS/MS. Peptides were separated using an UltiMate3000

(Dionex) HPLC system (ThermoFisher) using 75 μm ID fused capillary and packed with 2.4 μm

ReproSil-Pur C18 beads to 20 cm. The HPLC gradient was 0%–35% solvent B (A = 0.1% formic acid, B

= 95% acetonitrile, 0.1% formic acid) over 20 min and from 45% to 95% solvent B in 40 min at a flow

rate of 300nL/min. The QExactive HF (ThermoFisher) mass spectrometer was configured following a

data-dependent acquisition method. All solvents used in analysis of MS samples were LC-MS grade. Full

MS scans from 300-1500 m/z were analyzed in the Orbitrap at 120,000 FWHM resolution and 5E5 AGC

target value, for 50 ms maximum injection time. Ions were selected for MS2 analysis with an isolation

window of 2 m/z, for a maximum injection time of 50 ms and a target AGC of 5E4. MS raw files were

processed with Proteome Discoverer version 2.3 and MS spectra were searched against a target + reverse

database with the SEQUEST search engine using H. sapiens FASTA databases (reviewed, canonical

entries, downloaded 9/27/21). For global proteome samples, iBAQ quantification was performed on

unique + razor peptides. Trypsin cleavage was specific with up to 2 missed cleavages allowed. Match

between runs parameters included a retention time alignment window of 20 min and a match time window

of 0.7 min. False discovery rate was set to 0.01.

LC-MS/MS of 5% SDS lysed stool

Stool supernatant was harvested after centrifugation at 15,000xg for 10 min and reduced using 5

mM dithiothreitol/25 mM NH4HCO3 pH=8.0 for 60 min at 52°C. The solution was stored at room

temperature in 25 mM iodoacetamide in the dark for 60 min. Protein digestion was performed with S-

TrapTM Column (Protifi). Nano high-performance liquid chromatography analyses were performed using

an Easy n-LC 1000 system (ThermoFisher). A Q-Exactive HF-X (ThermoFisher) was used for MS

analyses and operated with Xcalibur. Full MS scans were acquired on the Orbitrap from m/z 350–1200 at

a resolution of 60,000 using an automatic gain control (AGC) value of 5x10

. The minimum threshold

was 50,000 ion counts. MS/MS data were collected in centroid mode in the ion trap using an isolation

width of 1.6 m/z units, a maximum injection time of 50 ms, and an AGC value of 1x10

. Raw data files

were analyzed using the Proteome Discoverer software (ThermoFisher) against Mus musculus database.

Immunofluorescence

Stomachs were dissected, rinsed in PBS, and incubated in 10% formalin overnight at room

temperature before rinsing with PBS, embedded in paraffin, and sectioned by the Columbia University

Molecular Pathology Shared Resource. Antigens were unmasked by sequential 5 min incubations in the

following solutions: Xylene, 100% EtOH, 95% EtOH, 80% EtOH, 70% EtOH, 50% EtOH, and water.

Slides were pressure and heat treated for 1 min in unmasking solution (Vector Labs H-3300). Slides were

rinsed in PBST then blocked in 5% BSA PBST for 1 hr at room temp. Primary antibodies listed above

were incubated per manufacturer recommendations in 5% BSA PBST for 1 hr at room temp. Slides were

rinsed 5 times with PBST then incubated with fluorescent antibodies for 1 hr at room temp in the dark.

Slide covers were mounted using DAPI mounting gel (Electron Microscopy Sciences) incubated

overnight at 4°C. Images were obtained using a Nikon TI2E AXR confocal microscope.

Patient derived cancer organoid model generation

Human

gastric

adenocarcinoma

specimens,

namely

CCLF_UPGI_0008_T

and

CCLF_UPGI_0061_T, were obtained from consenting patients at the Dana-Farber Cancer Institute

(DFCI) under IRB protocol DF-HCC 03-189. The organoid model generation process was done by the

Cancer Cell Line Factory team at the Broad Institute. All procedures were carried out in accordance with

an Institutional Review Board (IRB)-approved protocol. Patient tumor resections were immediately

placed in a sterile conical tube containing DMEM media (ThermoFisher) supplemented with 10% FBS

(Sigma Aldrich), 1% penicillin-streptomycin (ThermoFisher), 10 μg/mL of gentamicin, and 250 ng/mL

fungizone. This media was maintained at a cold temperature during transport from the operating room to

the research laboratory. Upon arrival, resections were transferred to a 15 ml conical tube containing 5 mL

of DMEM media with 10% FBS, 1% penicillin-streptomycin, and digestion enzymes including regular

collagenase (StemCell #07912) and dispase (StemCell #07913). The tube was subjected to rotation and

incubated at 37°C for 1 hour. Subsequently, the cells were centrifuged at 1,000 rpm for 5 minutes. The

resulting cell pellets were resuspended and subsequently embedded into Matrigel (Corning #356231)

following an established protocol(23). Gastric cancer organoids were maintained and passaged using cold

PBS and TrypLE Express (ThermoFisher #12604039) upon reaching 80-90% confluence. Tumor purity

was verified by Whole Exon Sequencing.

In vitro

cell viability assays

Gastric epithelial adenocarcinoma cell lines AGS (female patient)(RRID:CVCL_0139)(CRL-

1739) and NCI-N87 (male patient)(RRID:CVCL_1603)(CRL-5822) were obtained from ATCC which

performs STR profiling on its cell lines. Cells were not authenticated again after purchase from ATCC.

MKN45 gastric adenocarcinoma cell line (female patient)(RRID:CVCL_0434)(ACC409) was obtained

from the DSMZ Leibniz Institute which performs STR profiling of its cell lines. Cells were not

authenticated again after purchase from ATCC. AGS, NCI-N87 and MKN45 cell lines were expanded and

tested for mycoplasma using MycoAlert Plus Mycoplasma Detection Kit (Lonza LT07-318) upon receipt

from ATCC and DSMZ before aliquoting in freezing media CELLBANKER 1 (Amsbio LLC 11910) and

stored in liquid nitrogen. Each cell line aliquot was thawed and used for experiments described here after

one week in culture and cells were used only for 8-10 passages. 2D cell culture assays were maintained in

RPMI media supplemented with 10% FBS and 1% penicillin, streptomycin, glutamine (ThermoFisher)

and grown in an incubator at 5% CO

at 37°C. Small molecules C6 urea ceramide, D-erythro-MAPP,

ARN14988, ceramide, sphingosine, and S1P were solubilized as recommended by manufacturer (Cayman

Chemicals). For viability assays, 96-well plates were seeded at 2000 cells per well, allowed to recover

overnight, and compounds were added and incubated at 5% CO

at 37°C for 72 hours. Viability was

measured using Cell titer glo viability reagent (Promega) and luminescence was measured using the

SpectraMax iD3.

Patient derived organoids were obtained from the Broad Institute and maintained in 50uL Matrigel

(Corning, #354234) in 24-well plates and cultured in 5% CO2 and at 37°C. After Matrigel solidification,

organoids were overlaid with DMEM/F-12 (Gibco, #11320-033) supplemented with 1X B-27 (Gibco,

#0080085SA), and 1X N2 (Gibco, #A13707-01); Wnt3A conditioned media, m-Noggin conditioned

media, and R-spondin conditioned media (10% total for all three); 3% L-WRN conditioned media (Sigma

RESULTS

YFP detection validates stool protein biomarkers for GC in TCON mice

Few studies have investigated the use of stool proteins as biomarkers for GC in an unbiased

manner, thus we utilized our previously described transformed gastric parietal cell specific KPC mouse

model of GC, referred to as TCON, as a discovery platform(19). We hypothesized that stool biomarkers

would originate from biomolecules shed into the stomach lumen either by tumor cells or non-tumor cells

affected by the presence of the tumor. To assess this, gastric lavage was collected from 5 to 9-week-old

TCON and littermate control mice and measured for total DNA and protein concentration (

Figure 1A

Significantly higher DNA and protein concentrations were observed in the gastric lavage obtained from

TCON mice as compared to littermate controls. The yellow fluorescent protein (YFP) reporter expressed

in ATP4b-Cre expressing transformed gastric parietal cells represents a surrogate for GC cell-derived

proteins in the TCON mouse model. We probed for YFP in gastric lavage fluid from TCON mice by

Western blot, revealing robust expression (

Figure 1B)

which suggests that tumor cell-derived proteins are

being released into the GI tract and possibly in the stool. To assess this, stool lysates from TCON and

littermate control mice were probed for YFP, revealing enrichment in TCON mouse stool but not

littermate controls (

Figure 1C

). The ability to detect tumor cell YFP in the stool of TCON mice suggests

that other protein biomarkers may be present in stool.

Proteomic mass spectrometry analysis of TCON stool nominates early detection biomarkers

Previous stool mass spectrometry studies demonstrate that protein identification is variable based

upon the lysis buffer composition(24); thus, we utilized two buffers types that maximize protein

discovery: 8M Urea and 5% SDS. We selected 6-week-old TCON mice as our window for early detection

since mice display YFP-positive tumors in the stomach without signs of metastasis(19) and co-housed

them with littermate control mice to normalize their microbiome(25). Stool from 6-week-old TCON and

littermate control mice were lysed and analyzed by mass spectrometry. A Venn diagram of identified

stool proteins based on lysis buffer used (

Supplemental Figure 1

) suggests certain proteins are enriched

in stool depending on the lysis buffer and the presence of GC tumors. Previously published mass

spectrometry analysis of WT mouse stool proteins(26) was additionally considered with our control stool

proteins to validate our approach. A total of 765 proteins were identified by stool protein mass

spectrometry from n=2 littermate controls and n=4 TCON mice. The 10 most enriched and depleted

proteins (

Figure 2A)

from the stool of TCON mice are listed as candidate biomarkers for GC detection.

We focused on proteins enriched in TCON stool and validated them by probing stool from 7 to 9-week-

old mice with commercially available antibodies. Multiple proteins were found to be consistently enriched

in stool from TCON mice as compared to littermate controls: ACTN4, VCP, ASAH2, and DPP4 (

Figure

). This data identifies a panel of proteins that specifically correlate with stool from the TCON mouse

model of GC which may serve as biomarkers for gastric cancer detection.

Candidate TCON stool biomarkers are detected in early gastric tumors

Next, we sought to understand the kinetics of stool biomarker protein expression in our TCON

mouse model to evaluate its effectiveness in early detection. We conducted a weekly collection of stool

from TCON and littermate control mice from 4 to 8 weeks of age. As previously published(19), by 3

weeks of age, TCON mice have dysplastic lesions throughout the stomach. By 6 weeks, there is

significant increase in lesion size with some localized invasion, while by 9 weeks of age, 100% of mice

have invasive carcinomas with a median overall survival of 11 weeks.

Immunoblot analysis of stool

lysates identified biomarker protein expression as early as 4 weeks with increasing abundance during

disease progression (

Figure 3A

). Next, we assessed the expression of stool biomarker proteins in stomach

tumors. Stomachs isolated from 6-week-old TCON and littermate control mice were sectioned and

analyzed by immunofluorescence for biomarker protein expression along with YFP to indicate tumor cells

(

Figure 3B

) (

Supplemental Figure 2

). ACTN4 and DPP4 were identified as significantly upregulated

whereas ASAH2 and VCP were noticeably enriched. The expression of ACTN4 and DPP4 was examined

in the stomach tissue of TCON mice at 4 and 8 weeks of age which mirrored previous observations that

biomarker protein expression concentrated at areas of YFP-positive tumor growth, in contrast to control

tissue with general diffuse expression (

Supplemental Figure 3

). Taken together, the data suggest that our

stool biomarkers are upregulated in stomach tumors.

TCON stool biomarkers in other models of GC

To further characterize our stool biomarkers, we examined their presence in the stool of multiple

mouse models of gastrointestinal cancer. A commonly used experimental model of tumorigenesis is

subcutaneous injection of tumor cells into the flanks of mice. This model allows for convenient

monitoring of tumor growth but has limited physiological relevance since tumors lack the appropriate

microenvironment. Subcutaneous implantation of TCON-derived GC cells into the flank of syngeneic

C57BL/6 mice did not result in biomarker expression of ACTN4 in the stool at early or late stages of

tumor growth

(Figure 4A

). In contrast, orthotopic injection of luciferase expressing TCON GC cells into

the stomachs of syngeneic C57BL/6 mice resulted in significant enrichment of ACTN4 and DPP4 in the

stool after tumor presence was confirmed by luminescence imaging (

Figure 4B

). The difference in stool

biomarker presence between subcutaneous and orthotopic GC cell implantation suggests a dependence on

location for stool biomarker detection, namely along the GI tract. Published studies have compared GC

with Barrett’s esophagus/esophageal adenocarcinoma (EAC) and indicated a similar cell of origin(21) and

molecular fingerprint(27). To explore whether our GC-correlated biomarkers also identify the presence of

EAC, we probed for biomarker expression in stool from a previously established model of EAC generated

by treating mice overexpressing IL-1β in the esophageal epithelium with N-methyl-N-nitrosourea (MNU)

and deoxycholate (DCA) administered in the drinking water(21). Immunoblot analysis of stool from EAC

mice after MNU and DCA treatment revealed enrichment of ACTN4 and DPP4 in the stool as compared

to stool from control mice without treatment (

Figure 4C

). Colorectal cancer (CRC) is the only GI cancer

with an FDA approved stool test, potentially owing to reduced biomarker degradation at the posterior GI

tract. Studies have suggested a role of ACTN4 and DPP4 in the tumorigenesis of CRC(28,29); therefore,

we wanted to examine the efficacy of these proteins as biomarkers for CRC. We analyzed the stool of

mice treated with Azoxymethane (AOM), a model frequently used to study spontaneous CRC(30). Mice

developed tumors approximately 20 weeks after initial AOM treatments, indicated by weight loss and

posthumously confirmed by histology. Compared to untreated controls, we identified a significant

correlation of ACTN4 and DPP4 in the stool of AOM-driven CRC mouse models compared to age and

sex matched untreated healthy controls (

Figure 4D

). Collectively, these observations suggest that our

stool biomarkers correlate with tumorigenesis along the GI tract and are potentially biomarkers in

multiple types of GI cancers.

Proteomic mass spectrometry analysis of HDGC patient stool nominates detection biomarkers

Currently, the only FDA approved use of stool in cancer diagnostics is for colorectal cancer

screening. Previous studies of stool biomarkers for GC detection were targeted and limited in

outcome(17,18). We performed an unbiased stool mass spectrometry approach based upon the conditions

utilized in our mouse studies for biomarker discovery in HDGC patient stool. Stool was collected from

healthy donors (H) and HDGC patients with

CDH1

germline mutations stratified into an at-risk group

(HDGC-AR) if GC was not detected by endoscopy or as GC-confirmed (HDGC-GC) if endoscopy

confirmed the presence of GC at the time of stool collection. Donor information is summarized in

Supplemental Table 1

. Stool from our cohorts were analyzed by mass spectrometry which identified 834

proteins in total. The 20 most upregulated and downregulated proteins in HDGC patient stool compared

to healthy donor stool are listed (

Table 1

). Select proteins were used to generate heat maps of stool

proteins enriched in HDGC-GC and -AR groups (

Supplemental Figure 4A

) and diminished stool

proteins in the HDGC-GC group compared to healthy donors (

Supplemental Figure 4B

). These data

reveal distinct stool proteomes which correlate with the donor tumor status. Additionally, a panel of

proteins was identified that distinguishes the HDGC-GC group from the HDGC-AR group

(

Supplemental Figure 4C

) and may represent proteins specific to the presence of more established

lesions. Validation of biomarkers enriched in HDGC patient stool compared to healthy donors by

immunoblot assay identified a panel of proteins associated with the presence of disease: ASAH2, DPP4,

VCP, lactotransferrin (LTF), and tropomyosin-2 (TPM2) (

Figure 5A

). Similar to our findings in TCON

mice, we sought to determine if the stool biomarkers enriched in HDGC patients are upregulated in the

stomach. The primary tumor proteome of 84 DGC patients compared to healthy adjacent tissue (HAT) has

been previously characterized(31) and searching for our biomarkers in their data confirmed DPP4, LTF,

and VCP as significantly upregulated (

Figure 5B

). We next validated the HDGC stool biomarkers in a

simplified version of an immunoblot analysis, commonly referred to as a dot blot assay, to assess the

feasibility of rapid screening. Dot blot analysis revealed robust detection of ASAH2 and DPP4 in the stool

of donors with endoscopy confirmed GC tumors compared to healthy donors or HDGC donors without

tumors (

Figure 5C

). These data support the feasibility of stool protein diagnostics for HDGC and suggest

potential candidate proteins for further study and translation to the clinic.

Stool biomarker ASAH2 as a potential therapeutic target for GC treatment

ASAH2 is a stool biomarker identified in our screen that has not been previously associated with

GC tumorigenesis. ASAH2 is a neutral ceramidase which converts ceramide into sphingosine, after which

it is phosphorylated by kinases into sphingosine-1-phosphate (S1P). S1P is a pro-tumorigenic lipid that is

secreted by many cancer cells and recognized by S1P receptors which are G-protein coupled receptors

that promote signaling through canonical growth pathways such as RAS, P13K, and STAT3(20). Multiple

tumor types have been demonstrated to exploit S1P signaling to promote tumorigenesis and metastasis,

including liver(32), breast(33), colon(34), pancreatic(35), and gastric cancer(36). To test the role of

ASAH2 in GC, we treated multiple GC cell lines with C6 urea ceramide (C6-U-Cer), a small molecule

inhibitor of ASAH2 (

Figure 6A

). GC cell lines were sensitive to ASAH2 inhibition with apparent

complete toxicity at 5µM C6-U-Cer. There are five human ceramidases: one acid ceramidase (ASAH1),

three alkaline ceramidases (ACER1-3), and one neutral ceramidase (ASAH2). To determine which

ceramidases were critical for GC cell viability, we challenged the IGC cell line NCI-N87 and the DGC

cell line MKN45 with inhibitors specific for neutral (C6-U-Cer), acidic (ARN14988), and alkaline (D-

erythro-MAPP) ceramidases (

Figure 6B

). Only inhibition of neutral ceramidase ASAH2 induced cell

death, suggesting that among the ceramidases, ASAH2 is critical for GC viability.

ASAH2 activity is downstream of ceramide and upstream of sphingosine in the S1P synthesis

pathway; therefore, we hypothesized that addition of downstream products of ASAH2 may rescue the

anti-proliferative effects of C6-U-Cer. GC cell lines MKN and NCI-N87 were treated with C6-U-Cer

immediately followed by the addition of either ceramide, sphingosine, or S1P (

Figure 6C

)(

Supplemental

Figure 5

). Indeed, the addition of ceramide did not affect C6-U-Cer toxicity however the addition of

downstream products sphingosine and S1P significantly restored GC cell viability. These data suggest

that ASAH2 has a functional role in the survival of GC cell lines, possibly through S1P signaling. GC

patient-derived organoids (PDOs) more closely model an

in vivo

tumor as compared to 2D cell lines thus

we treated GC PDOs with C6-U-Cer and determined that GC PDOs are similarly sensitive to the ASAH2

inhibitor (

Figure 6D

). PDO Patient biopsy information (

Supplemental Table 2

) suggests that ASAH2

inhibition is effective against primary and peritoneal cavity metastasis tumors. These data support further

investigation of ASAH2 inhibition as targeted therapy for GC.

Stool microbial features distinguish HDGC patient stool from healthy donor stool

The microbiome plays a significant role in human metabolism and are diverse symbionts which

may influence the composition of proteins in the stool(37). In an exploratory analysis, we characterized

the HDGC patient microbiome by 16S rRNA sequencing of HDGC patient and healthy donor stool.

Generalized examination of the bacterial composition was done by hierarchical clustering (

Figure 7A

)

and Shannon entropy measurements of species richness and evenness (

Figure 7B

) which did not identify

significant differences between the patient stool cohorts. However, comparisons of the relative abundance

of bacterial families in the stool (

Figure 7C

) identified a significant increase in members of the

Streptococcaceae

family among HDGC-GC patient stool (

Figure 7D

) which aligns with observations in

GC patients(38). Furthermore, analysis of bacterial species abundance between patient stool cohorts

identified multiple significantly differentially enriched species (

Figure 7E

Phascolarctobacterium

faecium

Ruminococcus bromii

, and

Escherichia marmotae

were significantly upregulated in HDGC-AR

and HDGC-GC stool samples; meanwhile,

Bacteroides xylanisolvens

and

Metalysinibacillus jejuensis

are

enriched in the stool of healthy donors. These data highlight several microbiome trends in HDGC and

healthy donor stool and suggests that the stool microbiome may be a potential indicator as HDGC

biomarkers.

DISCUSSION

Our study reports the identification of stool protein biomarkers in mouse models of GC and

HDGC patients through an unbiased proteomic mass spectrometry approach. The difficulty of studying

biomarkers for DGC is the spontaneous nature of the disease and the advanced stage at which GC patients

are diagnosed. Our GC mouse model serves as a valuable platform for discovery. The TCON mouse

model of mixed-type GC reliably develops GC at established kinetics which allowed us to optimize and

validate stool mass spectrometry for the discovery of proteins in the stool which correlate with disease.

We leveraged our mass spectrometry conditions to analyze the stool of HDGC patients who reliably

develop DGC and are routinely monitored for GC tumorigenesis. Immunoblot analysis validated protein

candidates enriched in stool from TCON mice and HDGC patients, confirming a correlation between

disease and protein upregulation. Additionally, many biomarkers overlapped between TCON mice and

HDGC patients, suggesting a conserved feature of GC tumorigenesis in which proteins are enriched in the

GI tract and ultimately end up in the stool. Our mouse and human data offer proof of principle for

coupling preclinical systems and annotated patient cohorts to optimize detection strategies. We examine

for the first time, the stool proteome in HDGC patients and nominate several candidate proteins as

biomarkers for disease detection.

The identification of proteins known to promote GC tumorigenesis such as ACTN4(39),

DPP4(40), and VCP(41) validates our unbiased approach; however, a subset of proteins have not been

previously associated with GC. These potentially represent proteins with undiscovered roles in GC

tumorigenesis. Due to the prevalence of S1P in tumor biology, identification of ASAH2 as a stool

biomarker motivated further characterization of its role in GC. Studies characterizing the pro-tumorigenic

functions of ASAH2 include protecting myeloid derived suppressor cells from ferroptosis(42) and its

importance in colorectal cancer tumorigenesis(43). Here we demonstrate that ASAH2 activity is

important in the proliferation of GC cell lines and PDOs derived from a primary tumor and a peritoneal

cavity metastasis. Further studies will determine if ASAH2 may be a therapeutic target for GC;

nonetheless, its importance in GC cell lines

in vitro

is promising as validation for the proteins identified

from our unbiased stool biomarker study.

We observed a subset of our stool protein biomarkers, originally discovered in GC, to correlate

with tumorigenesis in multiple mouse models of GI cancer. ACTN4 and DPP4 have been implicated in

the tumorigenesis of multiple tumor types including GC, EAC, and CRC(44,45); therefore, it is possible

that these proteins may act as stool biomarkers for multiple GI cancers. Another explanation is that the

presence of the GI tumor induces non-tumor cells along the GI tract to behave differently, resulting in the

changes in stool protein levels and thus the diverse correlations with our GC biomarker panel with

multiple GI tumor types. More studies need to be done to determine the organ(s) and cell type(s)

responsible for mediating the stool biomarkers.

Mass spectrometry studies of the GC tumor proteome from patient biopsies have identified

differentially expressed proteins and potential biomarkers(31,46–48); however, our stool biomarkers are

not among their most upregulated proteins. One explanation is that proteins enriched in GC tumors are

abundantly expressed by healthy tissue throughout the GI tract, limiting its usefulness as a stool

biomarker. Additionally, GC specific proteins may be metabolized by the host or microbiome, preventing

their accumulation in the GI tract and stool. Our approach avoids these and other unknown variables by

quantifying protein species directly from stool. This is highlighted by our immunofluorescence images of

mouse stomachs (

Figure 3B

) which did not detect statistical difference between control and TCON

stomach expression levels of ASAH2 and VCP; however, stool protein levels show robust correlation.

The mechanisms regulating the accumulation and stability of our stool biomarker proteins through the

digestive process have not yet been elucidated. We hypothesize the possibility that some biomarker

proteins are protected in membrane bound extracellular vesicles which escort the proteins through the

digestive system. Our future studies will aim to identify how the biomarker proteins survive degradative

pressures in the GI tract.

Our exploratory analysis of the HDGC stool microbiome characterized microbial features which

distinguish donors based on disease state. We hypothesize that these bacteria may influence the presence

and stability of proteins in the GI tract, therefore altering the stool protein composition. Interestingly,

several bacterial species which correlated in the stool from non-GC donors have been shown to be

enriched in cancer patients who respond to anti-PD1 therapy:

P.faecium

(49),

B.xylanisolvens

(50), and

R.bromii

(51). Additionally, we found

E.marmotae

, a potential enteric human pathogen(52), to be enriched

in the stool of GC-confirmed HDGC patients. The functional significance of these microbial features and

whether the microbiome influences the availability of protein biomarkers remain as topics for future

studies; however, our data suggest that the microbial features themselves may be further studied as

potential biomarkers of GC.

Our study focuses on characterizing stool proteins upregulated in the context of GC; however,

downregulated stool proteins may also serve as potential indicators of disease. Interestingly, many of the

downregulated stool proteins we identified are digestive enzymes. It has been shown that loss of normal

digestive function is associated with GC(53), which reflects the reduced abundance of digestive enzymes

in our stool proteome findings. The stool proteins we identified to be downregulated in the context of GC

may indicate a healthy state and remains a prospective area of study.

The stool protein biomarkers identified in this study which correlate with disease in HDGC

patients have potential clinical implications for the early detection of GC. However, we could not validate

many of our top hits due to the lack of commercially available antibodies. The use of diagnostic mass

spectrometry may avoid the problem of antibody availability and is a promising area of study.

Nonetheless, assaying our validated panel of candidate biomarker proteins in stool samples suggests the

possibility for high throughput routine testing of individuals at high risk for GC to inform them when an

endoscopy is warranted. These populations include those infected with

H.pylori

, ethnicities which are

prone to developing GC, and families with history of or individuals with known genetic predispositions to

developing GC. Additionally, these stool biomarkers may have the potential to serve as indicators of

patient response to tumor therapies, which are currently assessed by arduous tumor biopsies.

Limitations of the study

This study had a limited number of stool donors from the Boston area. Further studies are needed to

expand our observations to more populations.

Concluding remarks

Through an unbiased mass spectrometry screen of stool, we demonstrate the potential of stool biomarkers

as indicators of disease in HDGC patients and GC mouse models. The overlap of biomarkers between

mouse and human stool suggests conserved features of stool biomarker enrichment and supports the

possibility of characterizing this phenomenon in the TCON mouse model.

Acknowledgements

We thank Joy Hang Che for data analysis advice. We thank Yasmin Kadry and Nancy Shek for engaging

topic-related

discussion.

Heat

map

analysis

performed

Morpheus

(https://software.broadinstitute.org/morpheus). Histology and immunofluorescence analysis of mouse

stomachs was performed by the Molecular Pathology Shared Resource at the Herbert Irving

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Table 1: List of Proteins Altered in HDGC Patient Stool

The 20 most upregulated (blue, top) and downregulated (orange, bottom) stool proteins in HDGC donors
(n=6) compared to healthy donors (n=6).

Accession

Coverage

[%]

Peptides

Gene

Symbol

Ratio ALL

HDGC/Healthy

p-value

P12273

PIP

10.19

0.004

P07951

TPM2

6.64

0.006

P02788

LTF

5.92

0.005

P06732

CKM

5.74

0.005

P01036

CST4

5.69

0.158

Q14315

FLNC

5.62

0.038

P14410

5.41

0.005

P05976

MYL1

5.33

0.007

P12883

MYH7

5.02

0.027

O14983

ATP2A1

4.02

0.017

Q13642

FHL1

3.95

0.021

P03973

SLPI

3.79

0.013

P12955

PEPD

3.63

0.039

P07339

CTSD

3.57

0.033

Q9UKX3

MYH13

3.25

0.000

P09622

DLD

3.18

0.126

P02766

TTR

3.09

0.091

A7E2Y1

MYH7B

2.98

0.025

P61626

LYZ

2.86

0.050

P68032

ACTC1

2.82

0.043

Accession

Coverage

[%]

Peptides

Gene Symbol

Ratio ALL

HDGC/Healthy

p-value

P33778

HIST1H2BB

0.37

0.054

P07148

FABP1

0.39

0.109

Q6W4X9

MUC6

0.44

0.036

P35030

PRSS3

0.51

0.117

P17538

CTRB1

0.51

0.057

P05451

REG1A

0.53

0.315

P80188

LCN2

0.54

0.205

P19835

CEL

0.55

0.120

Q14CN2

CLCA4

0.58

0.245

P13646

KRT13

0.60

0.248

Q03403

TFF2

0.62

0.335

Q12864

CDH17

0.63

0.207

Q86UP6

CUZD1

0.64

0.136

P11277

SPTB

0.68

0.281

P04054

PLA2G1B

0.70

0.236

P07355

ANXA2

0.71

0.175

Q8N6Q3

CD177

0.72

0.331

A6NMY6

ANXA2P2

0.73

0.195

P08217

CELA2A

0.76

0.394

P13533

MYH6

0.77

0.352

FIGURE LEGENDS

Figure 1.

Validation of YFP reporter protein in gastric fluid and stool of TCON mice. (A) Measurement

of DNA and protein concentration in the gastric lavage fluid of littermate control (n=5) and TCON (n=5)

mice. Values are normalized to the average concentration of littermate control mice. Immunoblot analysis

of littermate control (n=3) and TCON (n=3) mice (B) gastric lavage fluid and (C) stool. Band intensities

are quantified and normalized to average intensity of littermate control mice. Parametric unpaired t-test

analysis; *p≤0.05, **p≤0.01.

Figure 2.

Mass spectrometry identification and immunoblot validation of stool protein biomarkers in

TCON mice. Stool from TCON (n=4) and littermate control (n=2) mice were collected and analyzed by

protein mass spectrometry. (A) The top 10 proteins upregulated (blue) and downregulated (orange) in the

stool of TCON mice are listed. (B) Immunoblot analysis of stool from TCON (n=6) and littermate

controls (n=6) with quantified band intensities normalized to α-tubulin. Parametric unpaired t-test

analysis; *p≤0.05, **p≤0.01.

Figure 3.

Characterization of TCON stool biomarkers. (A) Immunoblot assay of TCON mice (n=3) and

littermate control (n=2) stool from 4-8 weeks of age. Quantified band intensities displayed normalized to

α-tubulin. (B) Representative H&E images and immunofluorescence microscopy images of biomarkers

ACTN4 and DPP4 in 6-week-old TCON and littermate control mice. Triplicate images for all biomarkers

can be found in

Supplemental Figure 2

. Fluorescence intensity of biomarker staining normalized to

DAPI staining for control (blue) and TCON (red) mice quantified. Parametric unpaired t-test analysis;

ns=not significant, *p≤0.05, **p≤0.01, *** p≤0.001.

Figure 4.

GC stool biomarkers in mouse models of GI cancer. (A) Immunoblot analysis of stool from

C57BL/6 mice with sub-cutaneous flank implantation of TCON-derived stomach tumor cells cultured

vitro

2 and 4 weeks post implantation (post inj)(n=6). ‘TCON’ and ‘Control’ lanes indicate stool lysates

from 8-week old mice previously analyzed for stool biomarkers. (B) Immunoblot analysis of stool from

C57BL/6 mice untreated (n=3, Control, blue) or with orthotopic injection of TCON-derived stomach

tumor cells cultured

in vitro

(n=6, red). Representative luciferase activity of 3 GC-bearing mice at the

time of stool collection 2 weeks after implantation. (C) Immunoblot analysis of stool from a mouse model

of EAC untreated (n=3, Control, blue) or treated with MNU and DCA (n=6, EAC, red). (D) Immunoblot

analysis of stool from mice treated with AOM (n=5, red) and healthy control mice (n=5, blue). Parametric

unpaired t-test analysis; *p≤0.05.

Figure 5.

Validation of stool biomarkers that correlate with HDGC. (A) Immunoblot assay validation of

proteins identified by mass spectrometry. (B) Analysis of HDGC biomarker proteins in DGC patients’

tumor (red, n=84) and healthy adjacent tissue (HAT, blue, n=84) from published study

. Parametric

unpaired t-test analysis; ns=not significant, *p≤0.05, **p≤0.01, **** p≤0.001. (C) Dot blot assay of

HDGC biomarker proteins in stool.

Figure 6.

The role of ASAH2 in GC progression. (A) Various GC cell lines (MKN45, NCI-N87, and

AGS) were incubated with neutral ceramidase inhibitor C6 urea ceramide (C6-U-Cer) at various

concentrations as indicated for 3 days. (B) GC cell lines (MKN45 and NCI-N87) were incubated with

ceramidase inhibitors (C6-U-Cer for neutral ceramidase, D-erythro-MAPP for alkaline ceramidases, and

ARN14988 for acid ceramidase) at various concentrations as indicated for 3 days. (C) A diagram of the

ceramide to S1P synthesis pathway is shown. GC cell lines (MKN45 and NCI-N87) were incubated with

3µM C6-U-Cer immediately followed by vehicle or 9µM of one of the following: C6 ceramide

(d18:1/6:0), sphingosine (d18:1), or S1P (d18:1). Drugs were incubated for 3 days. Parametric unpaired t-

test analysis; ns=not significant, **p≤0.01, *** p≤0.001. (D) Brightfield microscopy images of

CCLF_UPGI_0008_T (PDO 008) and CCLF_UPGI_0061_T (PDO 061) GC PDOs after DMSO or C6-U-

Cer (20µM) treatment. Graph indicates GC PDO viability after incubation with indicated concentrations

of C6-U-Cer for 3 days.

Figure 7

. Bacterial microbiota analysis of HDGC patient stool. (A) Hierarchical clustering of 16S rRNA

composition of patient stool: Healthy (H), HDGC-AR (AR), HDGC-GC (GC). (B) Normalized Shannon

Entropy analysis of bacterial populations in stool. (C) Relative abundance of bacterial families found in