Transcriptional heterogeneity in primary and metastatic gastric cancer revealed using single-cell RNA sequencing
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE163558 | GEO | 2022/02/22
REPOSITORIES: GEO
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Project description:Molecular knowledge of normal gastric tissues and gastric cancers remains incomplete. Here, we used single-cell RNA-seq to study the cell diversity of gastric tissues and gastric cancers. The expression landscape of normal gastric cell types and several candidate stem cell markers were obtained. Surprisingly, nearly all cell types in the antrum could transdifferentiate to intestinal metaplasia (IM). We also explored intra-tumoral heterogeneity and identified four common features of gastric cancer. In addition, we classified tumor cells into three major subtypes, which are associated with their prognosis. Finally, the proportions of mesenchymal and endothelial cells in the tumor microenvironment (TME) were negatively correlated with the prognosis of gastric cancer. Therefore, our work provides comprehensive molecular characterizations of both gastric development and gastric cancer at single-cell resolution and has significant potential to inspire better treatment strategies for gastric cancer. Keywords: Expression profiling by high throughput sequencing
2022-09-27 | GSE112302 | GEO
Project description:Gastric cancer (GC) is a leading cause of cancer-induced mortality with poor prognosis with metastasis. However, the mechanism of gastric carcinoma lymph node metastasis remains unknown due to traditional bulk-leveled approaches mask roles of subpopulations. To answer questions from the gastric carcinoma intratumoral perspective in the metastasis, we performed single-cell level analysis on three gastric cancer patients with primary cancer and paired metastatic lymph node cancer tissues using scRNA-seq. Results showed distinct carcinoma profiles from each patient, and diverse microenvironmental subsets were shared by a different patient. Clustering data showed significant intratumoral heterogeneity. Results also revealed a subgroup of cells bridging the metastatic group and primary group, implying the transition state of cancer during the metastatic process. In the present study we obtained a more comprehensive picture over gastric cancer lymph node metastasis, and we discovered some GC lymph node metastasis marker genes (ERBB2, CLDN11 and CDK12), as well as potential gastric cancer evolutionary driving genes (FOS and JUN), which provide a basis for the treatment of heterogeneity.
2020-12-06 | GSE158631 | GEO
Project description:Genome-wide mRNA expression profiles of 200 primary gastric tumors from the Singapore patient cohort. Gastric cancer (GC) is the second leading cause of global cancer mortality, with individual gastric tumors displaying significant heterogeneity in their deregulation of various oncogenic pathways. We aim to identify major oncogenic pathways in GC that robustly impact patient survival and treatment response. We used an in silico strategy based on gene expression signatures and connectivity analytics to map patterns of oncogenic pathway activation in 25 unique GC cell lines, and in 301 primary gastric cancers from three independent patient cohorts. Of 11 oncogenic pathways previously implicated in GC, we identified three predominant pathways (proliferation/stem cell, NF-kB, and Wnt/b-catenin) deregulated in the majority (>70%) of gastric tumors. Using a variety of proliferative, Wnt, and NF-kB-related assays, we experimentally validated the pathway predictions in multiple GC cell lines showing similar pathway activation patterns in vitro. Patients stratified at the level of individual pathways did not exhibit consistent differences in clinical outcome. However, patients grouped by oncogenic pathway combinations demonstrated robust and significant survival differences (e.g., high proliferation/high NF-kB vs. low proliferation/low NF-kB), suggesting that tumor behavior in GC is likely influenced by the combined effects of multiple oncogenic pathways. Our results demonstrate that GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Experiment Overall Design: Profiling of 200 primary gastric tumors on Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. All tumors were collected with approvals from the National Cancer Centre, Singapore; the Research Ethics Review Committee; and signed patient informed consent.
2009-04-10 | E-GEOD-15459 | 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:Generation of preclinical models which recapitulate at best the extreme intra-tumoral heterogeneity (using two cell culture conditions) and inter-tumor heterogeneity between children diagnosed with high-grade gliomas.
2019-01-01 | GSE101799 | GEO
Project description:The inter-patient variability of tumor proteomes has been investigated on a large scale but many tumors display also intra-tumoral heterogeneity (ITH) regarding morphological and genetic features. To what extent the local proteome of tumors intrinsically differs remains largely unknown. Here, we used hepatocellular carcinoma (HCC) as a model system, to quantify both inter- and intra-tumor heterogeneity across human patient specimens with spatial resolution. We first defined proteomic features that robustly distinguish neoplastic from the directly adjacent non-neoplastic tissue by integrating proteomic data from human patient samples and genetically defined mouse models with available gene expression data. We then demonstrated the existence of intra-tumoral variations in protein abundance that re-occur across different patient samples, and affect clinically relevant proteins, even in the absence of obvious morphological differences or genetic alterations. Our work demonstrates the suitability and the benefits of using mass spectrometry based proteomics to analyze diagnostic tumor specimens with spatial resolution
2018-01-24 | PXD007052 | Pride
Project description:Analysis of genomic and transcriptomic profiling has proposed new insights for diagnosis and prognosis in gastric cancer (GC). Human GCs are a unified model composed of diverse cells, including premalignant, immune and cancer. In this study, we present a human cell population of GC and premalignant states at single cell resolution using the 10X Chromium platform. We profiled 112,041 gastric cell landscape across 24 individuals with adjacent normal and GC lesions.
2022-01-30 | GSE150290 | GEO
Project description:Transcriptional heterogeneity in primary and metastatic gastric cancer revealed using single-cell RNA sequencing
| PRJNA689571 | ENA
Project description:Genome-wide mRNA expression profiles of 200 primary gastric tumors from the Singapore patient cohort. Gastric cancer (GC) is the second leading cause of global cancer mortality, with individual gastric tumors displaying significant heterogeneity in their deregulation of various oncogenic pathways. We aim to identify major oncogenic pathways in GC that robustly impact patient survival and treatment response. We used an in silico strategy based on gene expression signatures and connectivity analytics to map patterns of oncogenic pathway activation in 25 unique GC cell lines, and in 301 primary gastric cancers from three independent patient cohorts. Of 11 oncogenic pathways previously implicated in GC, we identified three predominant pathways (proliferation/stem cell, NF-kB, and Wnt/b-catenin) deregulated in the majority (>70%) of gastric tumors. Using a variety of proliferative, Wnt, and NF-kB-related assays, we experimentally validated the pathway predictions in multiple GC cell lines showing similar pathway activation patterns in vitro. Patients stratified at the level of individual pathways did not exhibit consistent differences in clinical outcome. However, patients grouped by oncogenic pathway combinations demonstrated robust and significant survival differences (e.g., high proliferation/high NF-kB vs. low proliferation/low NF-kB), suggesting that tumor behavior in GC is likely influenced by the combined effects of multiple oncogenic pathways. Our results demonstrate that GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Keywords: gastric cancer, primary tumor
2009-10-06 | GSE15459 | GEO
Project description:Genome-wide mRNA expression profiles of 25 unique gastric cancer cell lines (GCCLs). Gastric cancer (GC) is the second leading cause of global cancer mortality, with individual gastric tumors displaying significant heterogeneity in their deregulation of various oncogenic pathways. We aim to identify major oncogenic pathways in GC that robustly impact patient survival and treatment response. We used an in silico strategy based on gene expression signatures and connectivity analytics to map patterns of oncogenic pathway activation in 25 unique GCCLs, and in 301 primary gastric cancers from three independent patient cohorts. Of 11 oncogenic pathways previously implicated in GC, we identified three predominant pathways (proliferation/stem cell, NF-kB, and Wnt/b-catenin) deregulated in the majority (>70%) of gastric tumors. Using a variety of proliferative, Wnt, and NF-kB-related assays, we experimentally validated the pathway predictions in multiple GC cell lines showing similar pathway activation patterns in vitro. Patients stratified at the level of individual pathways did not exhibit consistent differences in clinical outcome. However, patients grouped by oncogenic pathway combinations demonstrated robust and significant survival differences (e.g., high proliferation/high NF-kB vs. low proliferation/low NF-kB), suggesting that tumor behavior in GC is likely influenced by the combined effects of multiple oncogenic pathways. Our results demonstrate that GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Keywords: gastric cancer, cell culture Profiling of 25 unique Gastric Cancer Cell Lines on Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. Replicates are included for a total of 33 arrays.
2009-10-06 | E-GEOD-15455 | biostudies-arrayexpress