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.
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.
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.
Project description:Increasing evidence has clarified that the tumor microenvironment (TME) is closely related to the prognosis and therapeutic efficacy of gastric cancer (GC). However, there is no reliable TME evaluation system used to accurately predict the prognosis and therapeutic efficacy of gastric cancer. In this study, immune cell enrichment analysis was used to construct an immune microenvironment score (IMS).We further demonstrated that IMS may be used as an indicator to predict the efficacy of immunotherapy in patients with GC.
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.
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.
Project description:We obtained transcriptome profiling (RNA-seq) of H+/K+ ATPase negative epithelial cells purified from gastric corpus of mice fed with HFD or control diet by using next generation sequencing.