Award Title: The TARGET Study (TArgeted biopsies to Risk Stratify Gastric cancer precursors for tailored Endoscopic surveillance and Treatment)
Funder: Guts UK

Abstract: Background: Despite a precipitous decline in previous decades, gastric adenocarcinoma (GA)
incidence and mortality have now plateaued in the UK. Roughly 6700 new cases are diagnosed per
year in the UK, on a par with melanoma and oesophageal adenocarcinoma incidence. Only 19% of
adults survive their diagnosis at 5 years, with UK survival among the lowest in Europe (average 24-
28% 5-year survival). The main risk factor for developing GA is Helicobacter pylori infection and over
35% of adults in the UK are chronically infected. Patients with extensive metaplastic atrophic
gastritis are at greatest GA risk, however our current approach to risk stratification involving
random biopsies and histopathology assessment is subjective, imprecise, and unreliable. This
situation is unacceptable. Recent evidence (Esposito et al. 2019; Pimentel-Nunes et al. 2016) and
2019 British (Banks et al. 2019) and European guidelines (Pimentel-Nunes et al. 2019) now advocate
the use of enhanced imaging endoscopy with a move towards targeted biopsies to more robustly
assess disease extent and cancer risk. There is now an urgent clinical need to develop a
quantitative understanding of the evolution to gastric cancer in chronic gastritis patients to
accurately identify the minority of high-risk individuals. Our group has pioneered a unique
targeted spatial analysis of early cancer evolution in chronic gastritis (details in this application).
Here we request Guts UK Development Funding to investigate precancerous clonal diversity from
targeted endoscopic gastric biopsies within the context of an ongoing prospective clinical study
(ESTIMATE study).
Aim and deliverables: We aim to develop an objective molecular test that allows accurate
stratification of patients with chronic atrophic metaplastic gastritis for future gastric cancer risk.
1. We hypothesise that biopsies targeted to patches of gastric intestinal metaplasia (GIM) enable
sensitive detection of clonal genetic abnormalities and represent a superior method for
interrogating clonal diversity within the at-risk stomach compared to random biopsies.
2. We hypothesise that copy number alteration (CNA) burden and clonal diversity correlate with
markers of cancer progression risk (dysplasia detection, endoscopic and histopathologic
staging of atrophy and IM) and could therefore act as an accurate predictor of neoplastic
progression risk.
Design & Methods: We are currently running an international multicentre study (ESTIMATE study)
comparing the current gold standard approach of random biopsies (timepoint 1) to endoscopically
targeted biopsies (timepoint 2), in patients with chronic atrophic metaplastic gastritis. Each patient (target recruitment 240 patients, on schedule December 2019) will undergo two endoscopies on
separate occasions at least six months apart. At each endoscopy 5 biopsies will be taken and thus
10 biopsies per patient are available from two timepoints, one reference set of random biopsies
and a second patient-matched set of targeted biopsies. The ESTIMATE trial will reveal the accuracy
and reproducibility of endoscopic risk stratification for chronic gastritis patients.
Here we propose to leverage this unique resource to assess the benefit of targeted biopsies to
interrogate within-patient clonal diversity as a marker of GC progression risk. We will carry out
shallow depth whole genome sequencing (sdWGS) (median depth 0.15x) to reveal clonal diversity
and total CNA burden, comparing random gastric biopsies (Timepoint 1, 5 biopsies) to biopsies
targeted at clonal metaplastic precursors (Timepoint 2, 5 biopsies) for each of 60 patients (total 600
sdWGS analyses, Work package 1). Our pilot data demonstrate that we can reliably perform sdWGS
to map genetic clonal diversity within these patients from routine ESTIMATE formalin-fixed paraffinembedded
(FFPE) biopsies (see pilot data below). We will profile the within-patient clonal diversity
and CNA burden from multiple individual patches of GIM and correlate these molecular data to
clinical markers of progression risk (dysplasia detection, serum atrophy, endoscopic stage of
disease, histopathologic OLGIM staging, Work package 2). This will allow us to compare the breadth
of GIM clonal diversity in these patients undergoing gastric surveillance (endoscopy cohort) to those
that have progressed to gastric cancer (our established surgical cohort) and develop a clinicalmolecular
risk prediction model of cancer progression in chronic gastritis. Our proposal benefits
from the robust within-patient control design of targeted to random biopsies and the wealth of
clinically annotated ESTIMATE study data: histopathology including subtype of GIM (complete vs
incomplete) demographics, endoscopy, serology for further risk prediction modeling studies.
Clinical & Scientific Summary: By taking a targeted approach to sampling cancer precursor lesions
our proposal presents a fundamentally new approach to risk stratification in chronic gastritis
patients. This award will allow us to establish proof of principle data that can be tested in future
larger prospective clinical trials with dysplasia detection primary endpoints. The ESTIMATE study is
part of an international study between the UK and the Netherlands for which collateral funding has
been obtained (endoscopy study running costs, €147,807) from the Dutch Gastroenterology Society
MLDS.

Lay Abstract: Project Summary: 

Stomach cancer has a poor survival rate, particularly in the UK. Accurate identification of changes to the stomach lining in people with chronic gastritis that might be precursors to cancer is essential for earlier detection. This project aims to identify the molecular nature of these changes, to develop an early, easy, and accurate test for early detection of stomach cancer.

Research Activity Codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health Categories: CANCER AND NEOPLASMS