Molecular subtypes in gastric cancer. [II]
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE84433 | GEO | 2018/03/20
REPOSITORIES: GEO
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Project description:We identified the molecular subtypes and conserved modules in gastric cancer by unsupervised clustering algorithm. We defined five molecular subtypes and six molecular signatrues of gastric cancer associated with the biological heterogeneity of gastric cancer and clinical outcome of patients.
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Project description:We identified the molecular subtypes and conserved modules in gastric cancer by unsupervised clustering algorithm. We defined six molecular signatrues of gastric cancer associated with the biological heterogeneity of gastric cancer and clinical outcome of patients.
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Project description:Molecular subtypes in gastric cancer.
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Project description:Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this retrospective analysis, we use our machine learning algorithm NTriPath [Park, Sunho et al. “An integrative somatic mutation analysis to identify pathways linked with survival outcomes across 19 cancer types.” Bioinformatics (2016): 1643-51. doi:10.1093/bioinformatics/btv692] to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identify four molecular subtypes that are prognostic for survival. We then built a support vector machine with linear kernel to generate a risk score that is prognostic for five-year overall survival and validate the risk score using three independent datasets. We also find that the molecular subtypes predict response to adjuvant 5-fluorouracil and platinum therapy after gastrectomy and to immune checkpoint inhibitors in patients with metastatic or recurrent disease. In sum, we show that the 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated in a prospective manner.
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Project description:Gastric cancer is a leading cause of death from cancer globally. Gastric cancer is classified into intestinal, diffuse and indeterminate subtypes based on histology according to the Laurén classification. The intestinal and diffuse subtypes, although different in histology, demographics and outcomes, are still treated in the same fashion. This study was designed to discover proteomic signatures of diffuse and intestinal subtypes. Mass spectrometry-based proteomics using tandem mass tags (TMT)-based multiplexed analysis was used to identify proteins in tumor tissues from patients with diffuse or intestinal gastric cancer with adjacent normal tissue control. A total of 7,804 or 5,166 proteins were identified from intestinal or diffuse subtype, respectively. This quantitative mass spectrometric analysis defined a proteomic signature of differential expression across the two subtypes, which included gremlin1 (GREM1), bcl-2-associated athanogene 2 (BAG2), olfactomedin 4 (OLFM4), thyroid hormone receptor interacting protein 6 (TRIP6) and melanoma-associated antigen 9 (MAGE-A9) proteins. Although GREM1, BAG2, OLFM4, TRIP6 and MAGE-A9 have all been previously implicated in tumor progression and metastasis, they have not been linked to intestinal or diffuse subtypes of gastric cancer. Using immunohistochemical labelling of a tissue microarray comprising of 132 cases of gastric cancer, we validated the proteomic signature obtained by mass spectrometry in the discovery cohort. Our findings should help investigate the pathogenesis of these gastric cancer subtypes and potentially lead to strategies for early diagnosis and treatment.
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Project description:Next-generation sequencing analysis of molecular subtypes of gastric cancer
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Project description:Genome-wide mRNA expression profiles of 70 primary gastric tumors from the Australian patient cohort. Like many cancers, gastric adenocarcinomas (gastric cancers) show considerable heterogeneity between patients. Thus, there is intense interest in using gene expression profiles to discover subtypes of gastric cancers with particular biological properties or therapeutic vulnerabilities. Identification of such subtypes could generate insights into the mechanisms of cancer progression or lay the foundation for personalized treatments. Here we report a robust gene-xpression-based clustering of a large collection of gastric adenocarcinomas from Singaporean patients [GSE34942 and GSE15459]. We developed and validated a classifier for the three subtypes in Australian patient cohort. Profiling of 70 primary gastric tumors on Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. All tumors were collected with approvals from Peter MacCallum Cancer Center, Australia; the Research Ethics Review Committee; and signed patient informed consent.
2012-07-04 | E-GEOD-35809 | biostudies-arrayexpress
Project description:Background: Intestinal metaplasia (IM) is a gastric precancerous lesion that precedes the development of gastric cancer in up to 3.77 cases/1000 person-years. It consists in a trans-differentiation process of gastric to intestinal tissue. Two histological subtypes exist, complete (CIM) and incomplete (IIM), the latter having higher progression rates to gastric cancer . Our objective was to identify molecular processes responsible for the tumoral transition from intestinal metaplasia to GC and the initial steps of this lesion Methods: We used expression microarray to compare the transcriptome of intestinal metaplasia subtypes that progress to gastric cancer (IIM-GC and CIM-GC) after a follow-up period with respect to those that do not progress (IIM control and CIM control). Also, IM-NoGC (IM control, comprising both IIM and CIM Control) was compared with healthy gastric mucosa. Differentially expressed genes were obtained and functional analyses (GSEA and IPA softwares) were performed. Some deregulated genes were validated by qPCR. Results: Histological subtypes of intestinal metaplasia that progress or not to GC differ less among them than to healthy mucosa. Incomplete intestinal metaplasia has a higher number of over-expressed carcinogenic genes and molecular processes than the complete subtype. Most relevant molecular processes and genes in this group include antigenic processing, inflammation, activation of cell cycle and cell proliferation, oncogenes and tumor suppressors. When IM-NoGC is compared with healthy gastric mucosa new identified transcripts include TRIM, TMEM, homeobox, transporters and nucleolar RNAs SNORDs116. We confirm previously reported processes such us intestinal differentiation, metabolism of lipids and of xenobiotics and identify new ones such as non tumoral Warburg effect and melatonin degradation. Conclusions: Differentially expressed genes and molecular processes have been identified for the first time in intestinal metaplasia that progress to gastric cancer. New genes and molecular processes have also been identified in intestinal metaplasia in comparison with healthy gastric mucosa.
2017-06-12 | GSE78523 | GEO
Project description:Gastric cancer, a leading cause of cancer related deaths, is a heterogeneous disease, with little consensus on molecular subclasses and their clinical relevance. We describe four molecular subtypes linked with distinct patterns of molecular alterations, disease progression and prognosis viz. a) Microsatellite Instable: hypermutated intestinal subtype tumors occurring in antrum, best overall prognosis, lower frequency of recurrence (22%), with liver metastasis in 23% of recurred cases b) Mesenchymal-like: diffuse tumors with worst prognosis, a tendency to occur at an earlier age and highest recurrence (63%) with peritoneal seeding in 64% of recurred cases, low frequency of molecular alterations c) TP53-inactive with TP53 loss, presence of focal amplifications and chromosomal instability d) TP53-active marked by EBV infection and PIK3CA mutations. The key molecular mechanisms and associated survival patterns are validated in multiple independent cohorts, to provide a consistent and unified framework for further preclinical and clinical research. ACRG Gastric cohort: microarray profiles from 300 gastric tumors from gastric cancer patients.
2015-04-17 | E-GEOD-62254 | biostudies-arrayexpress
Project description:To gain molecular understanding of carcinogenesis, progression, and diversity of gastric cancer, 22 primary human advanced gastric cancer tissues and 8 noncancerous gastric tissues were analyzed by high-density oligonucleotide microarray in this study. Based on expression analysis of approximately 6800 genes, a two-way clustering algorithm successfully distinguished cancer tissues from noncancerous tissues. Subsequently, genes that were differentially expressed in cancer and noncancerous tissues were identified; 162 and 129 genes were highly expressed (P < 0.05) >2.5-fold in cancer tissues and noncancerous tissues, respectively. In cancer tissues, genes related to cell cycle, growth factor, cell motility, cell adhesion, and matrix remodeling were highly expressed. In noncancerous tissues, genes related to gastrointestinal-specific function and immune response were highly expressed. Furthermore, we identified several genes associated with lymph node metastasis including Oct-2 or histological types including Liver-Intestine Cadherin. These results provide not only a new molecular basis for understanding biological properties of gastric cancer, but also useful resources for future development of therapeutic targets and diagnostic markers for gastric cancer. Keywords: other
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