Single-cell RNA-seq reveals immunosuppressive gastric stem-like cancer cells as a poor prognostic factor
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ABSTRACT:
PROVIDER: PRJNA643852 | ENA |
REPOSITORIES: ENA
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Project description:BEX2 is poor prognostic factor and required for cancer stemness in gastric cancer
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Project description:BEX2 is poor prognostic factor and required for cancer stemness in gastric cancer [GCIY_siBEX2]
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Project description:BEX2 is poor prognostic factor and required for cancer stemness in gastric cancer [MKN1_siBEX2]
| PRJNA882745 | ENA
Project description:Array CGH analysis was done with 56 primary gastric cancers to elucidate prognostic biomarkers on the BAC basis. Using the extracted genomic DNA from 56 primary gastric cancers, array CGH was done to elucidate the prognostic biomarkers.
2010-08-10 | E-GEOD-15436 | biostudies-arrayexpress
Project description:Despite continual efforts to establish pre-operative prognostic model of gastric cancer by using clinical and pathological parameters, a staging system that reliably separates patients with early and advanced gastric cancer into homogeneous groups with respect to prognosis does not exist. With use of microarray and quantitative RT-PCR technologies, we exploited series of experiments in combination with complementary data analyses on tumor specimens from 161 gastric cancer patients. Various statistical analyses were applied to gene expression data to uncover subgroups of gastric cancer, to identify potential biomarkers associated with prognosis, and to construct molecular predictor of risk from identified prognostic biomarkers.Two subgroups of gastric cancer with strong association with prognosis were uncovered. The robustness of prognostic gene expression signature was validated in independent patient cohort with use of support vector machines prediction model. For easy translation of our finding to clinics, we develop scoring system based on expression of six genes that can predict the likelihood of recurrence after curative resection of tumors. In multivariate analysis, our novel risk score was an independent predictor of recurrence (P=0.004) in cohort of 96 patients, and its robustness was validated in two other independent cohorts. We identified novel prognostic subgroups of gastric cancer that are distinctive in gene expression patterns. Six-gene signature and risk score derived from them has been validated for predicting the likelihood of survival at diagnosis.
2011-07-19 | GSE13861 | GEO
Project description:Despite continual efforts to establish pre-operative prognostic model of gastric cancer by using clinical and pathological parameters, a staging system that reliably separates patients with early and advanced gastric cancer into homogeneous groups with respect to prognosis does not exist. With use of microarray and quantitative RT-PCR technologies, we exploited series of experiments in combination with complementary data analyses on tumor specimens from 161 gastric cancer patients. Various statistical analyses were applied to gene expression data to uncover subgroups of gastric cancer, to identify potential biomarkers associated with prognosis, and to construct molecular predictor of risk from identified prognostic biomarkers.Two subgroups of gastric cancer with strong association with prognosis were uncovered. The robustness of prognostic gene expression signature was validated in independent patient cohort with use of support vector machines prediction model. For easy translation of our finding to clinics, we develop scoring system based on expression of six genes that can predict the likelihood of recurrence after curative resection of tumors. In multivariate analysis, our novel risk score was an independent predictor of recurrence (P=0.004) in cohort of 96 patients, and its robustness was validated in two other independent cohorts. We identified novel prognostic subgroups of gastric cancer that are distinctive in gene expression patterns. Six-gene signature and risk score derived from them has been validated for predicting the likelihood of survival at diagnosis. 65 primary gastric adenocarcinoma, 6 GIST and 19 surrounding normal fresh frozen tissues were used for microarray. All the tissues were obtained after curative resection after pathologic confirm at Yonsei cancer center(Seoul, Korea). Microarray experiment and data analysis were done at Dept. of systems biology, MDACC DNA microarray (Illumina human V3)
2011-07-18 | E-GEOD-13861 | biostudies-arrayexpress
Project description:Array CGH analysis was done with 56 primary gastric cancers to elucidate prognostic biomarkers on the BAC basis.
2010-08-10 | GSE15436 | GEO
Project description:Purpose: Our study aimed to disclose the specific gene expression profile representing peritoneal relapses inherent in primary gastric cancers and to identify patients at high risk of peritoneal relapse in a prospective study on the basis of the molecular prediction. Experimental Design: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly we constructed molecular prediction system and validated the robustness and prognostic validity of the analysis by 500 times multiple random sampling in 56 retrospective set consisting of 38 relapse free and 18 peritoneal relapse patients. Secondly we applied this prediction to 85 prospective set to assess the predictive accuracy and prognostic validity. Results: In retrospective phase, 500 times multiple random sampling analysis yielded 68% predictive accuracy in average and 22 gene expression profile associated with peritoneal relapse was identified. This prediction could identify significantly poor prognostic patients. In prospective phase, the molecular prediction yielded 76.9% overall accuracy. KaplanâMeier analysis with peritoneal relapse free survival showed a significant difference between âgood signature groupâ and âpoor signature groupâ (Log-rank p=0.0017). Multivariate analysis by Cox regression hazards model revealed that the molecular prediction was the only independent peritoneal relapse prognostic factor. Conclusions: Gene expression profile inherent in primary gastric cancer tissues can be useful to predict peritoneal relapse prospectively after curative surgery and individualize postoperative management to improve the prognosis of advanced gastric cancers. Of 141 samples, 56 represented the retrospective phase and 85 represented the prospective phase.
2010-05-23 | E-GEOD-15081 | biostudies-arrayexpress
Project description:The aim of this study is to identify and verify a prognosis set that is able to distinguish patient overall survival status based on whole genome expression profiling. Using Illumina HumanWG-6 beadarray, we analyzed the expression of 47,296 transcripts in two groups of gastric cancer patients who all underwent surgical resection. Thirty-nine of 46 samples in group one were used as a training set to discover candidates for overall survival prediction by using semi-supervised method, resulting in a panel of 10 genes as prognosis markers. This 10-marker set classified each case into a low or a high risk group with significantly different survival times (P = 0.000047) and maintained independent prognostic value in multivariate analysis. These 10 candidates were then verified in a fully independent validation set comprising 33 samples (P = 0.0009). Furthermore, the prognosis was consistent with the classical TNM staging system, and showed even better prediction. Interestingly, six of ten survival markers are ribosomal proteins, suggesting a possible association between deregulation of ribosome-related expression and poor prognosis. In conclusion, by whole genome expression profiling, 10 markers, including 6 ribosomal proteins, for overall survival prognosis of gastric cancer were found and validated, and which may be parallelly used with the TNM system. We investigated the transcriptome profiles of gastric cancer patients with different prognosis. Thirty-nine patients from first batch samples were used to discover prognostic markers and another 33 samples from batch two were used for validation.
2011-07-12 | E-GEOD-21983 | biostudies-arrayexpress
Project description:Gastric cancer is a dominating cause of cancer-associated mortality with limited therapeutic options. Here, we show that syndecan-4 (SDC4), a plasma membrane proteoglycan, is highly expressed in intestinal subtype gastric tumours and that this signature associates with patients’ poor survival. Further, we mechanistically demonstrate that SDC4 is a master regulator of gastric cancer motility and invasion. We also find that SDC4 conjugated with heparan sulfate chains is efficiently sorted in extracellular vesicles (EVs). Interestingly, SDC4 in EVs regulates gastric cancer cell-derived EV organ distribution, uptake and functional effects in recipient cells. Specifically, we show that SDC4 knockout disrupts the tropism of EVs for the common gastric cancer metastatic sites. Our findings set the basis of the molecular implications of SDC4 expression in gastric cancer cells and open new perspectives on the development of therapeutic strategies targeting the glycan-EV axis to limit tumour progression.
2023-05-05 | PXD035679 | Pride