Original ResearchClinical—Alimentary TractIntrinsic Subtypes of Gastric Cancer, Based on Gene Expression Pattern, Predict Survival and Respond Differently to Chemotherapy
Section snippets
GC Cell Lines
GC cell lines were obtained from commercial sources or collaborators and cultured as recommended (Supplementary Materials and Methods). Cell proliferation assays were performed using a tetrazolium compound–based colorimetric method (Supplementary Materials and Methods).
Patient Cohorts and Clinical Characteristics
Four independent patient cohorts were analyzed (N = 521); cohort 1 (SG) included 200 patients from the National Cancer Centre Singapore in Singapore, cohort 2 (AU) included 70 patients from Peter MacCallum Cancer Centre in
Genomic Analysis of GC Cell Lines Reveals 2 Major Intrinsic Subclasses
We performed gene expression profiling for a panel of 37 GC cell lines. To identify pervasive and thereby “intrinsic” gene expression differences across the cell lines, we analyzed the expression data using 4 different unsupervised and unbiased clustering techniques (hierarchical clustering, silhouette plot analysis,22 nonnegative matrix factorization,23 and principal components analysis). Two major intrinsic subtypes were identified by hierarchical clustering (Figure 1A). The robustness of the
Discussion
In this study, we report the discovery of 2 genomic subtypes of GC using profiles initially derived from GC cell lines. Because cancer cell lines are devoid of stroma, vasculature, and immune cells, we reasoned that comparing signatures between cell lines would be more likely to reflect intrinsic differences between tumor cells, minimizing potentially confounding effects from neighboring noncancer tissues. The validity of the cell line–based approach is supported by similar studies in other
References (41)
- et al.
Gastric cancer
Lancet
(2009) Silhouettes: A graphical aid to the interpretation and validation of cluster analysis
J Comput Appl Math
(1987)- et al.
A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes
Cancer Cell
(2006) - et al.
Fluorouracil versus combination of irinotecan plus cisplatin versus S-1 in metastatic gastric cancer: a randomised phase 3 study
Lancet Oncol
(2009) - et al.
Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world
J Clin Oncol
(2006) Clinical guidelines in oncology: gastric cancer
(2009)- et al.
Expression of the E2F family in human gastrointestinal carcinomas
Int J Cancer
(1999) - et al.
Frequent loss of membranous E-cadherin in gastric cancers: a cross-talk with Wnt in determining the fate of beta-catenin
Clin Exp Metastasis
(2005) - et al.
Validation of the Royal Marsden hospital prognostic index in advanced esophagogastric cancer using individual patient data from the REAL 2 study
J Clin Oncol
(2009) The two histological main types of gastric carcinoma: diffuse and so-called intestinal-type carcinomaAn attempt at a histo-clinical classification
Acta Pathol Microbiol Scand
(1965)
Chemotherapy in advanced gastric cancer: a systematic review and meta-analysis based on aggregate data
J Clin Oncol
The World Health Organization's histologic classification of gastrointestinal tumorsA commentary on the second edition
Cancer
Gastric carcinomaA pathobiological classification
Cancer
Differences in the mode of the extension of gastric cancer classified by histological type: new histological classification of gastric carcinoma
Gut
A combined comparative genomic hybridization and expression microarray analysis of gastric cancer reveals novel molecular subtypes
Cancer Res
Expression profiling and subtype-specific expression of stomach cancer
Cancer Res
Variation in gene expression patterns in human gastric cancers
Mol Biol Cell
Distinctive patterns of gene expression in premalignant gastric mucosa and gastric cancer
Cancer Res
Protein expression profiling and molecular classification of gastric cancer by the tissue array method
Clin Cancer Res
Reporting recommendations for tumor marker prognostic studies (REMARK)
J Natl Cancer Inst
Cited by (287)
GCclassifier: An R package for the prediction of molecular subtypes of gastric cancer
2024, Computational and Structural Biotechnology JournalTargeting HER2 in metastatic gastroesophageal adenocarcinomas: What is new?
2023, Bulletin du CancerFurther prognostic stratification of intestinal type of gastric adenocarcinoma by CDX2 expression pattern
2023, Human PathologyCitation Excerpt :Several environmental factors, including age, sex, dietary habits, smoking, family history, Helicobacter pylori infections, and ionizing radiation, as well as genetic alterations were reported to predispose to the development of gastric cancer [2]. Patients with gastric cancer are frequently diagnosed at advanced stages with a 5-year survival of about 20% [3]. Individual gastric cancers exhibit differences in disease aggressiveness, histologic morphology, and response rates to current therapeutic regimens, indicating the highly heterogeneous nature of this disease [3].
A convolutional neural network model for survival prediction based on prognosis-related cascaded Wx feature selection
2022, Laboratory InvestigationMolecular Classifications in Gastric Cancer: A Call for Interdisciplinary Collaboration
2024, International Journal of Molecular Sciences
View this article's video abstract at www.gastrojournal.org
Conflicts of interest The authors disclose the following: As mandated for research projects funded by the Singapore government, a patent application covering this work has been filed by Exploit Technologies Pte Ltd, the intellectual property arm of the Agency for Science Technology and Research, Singapore.
Funding Supported by grants from BMRC 05/1/31/19/423 (to P.T.), NMRC grant TCR/001/2007 (to P.T.), and a Duke-National University of Singapore core grant (to P.T.). Also supported by grants from the National Research Foundation of Singapore and American Society of Clinical Oncology Conquer Cancer Foundation (to I.B.T.). Cohort 3 was funded by NIH R01 (to J.-S.L.). J.A.A. is supported by a program grant from the University of Texas MD Anderson Cancer Center; the Park, Dallas, Cantu, and Smith families; Kevin and Sultan funds; and Rivercreek and Schecter Private Foundations. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.