Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA145569 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Purpose: A 128-gene signature has been proposed to predict poor outcomes in patients with stage II and III colorectal cancer. In the present study we aimed to validate this previously published 128-gene signature on external and independent data from patients with stage II and III colon cancer.
2011-09-01 | GSE31595 | GEO
Project description:Purpose: The present study aimed to develop a classification model to predict recurrence in stage II and III colon cancer, using a previously published 128-gene signature on external and independent material. Experimental Design: Microarray gene expression data from 148 patients (37 Danish patients and 111 patients retrieved from the Gene Expression Omnibus, GSE17536) with stage II and III colon cancer were analyzed using Affymetrix Arrays (Affymetrix, Santa Clara, USA). Based on a known 128-gene signature, a classification model was created with the random forest method, using a training set consisting of stage I colon cancers (with localized disease and a good prognosis) and stage IV colon cancers (with metastasis and a poor prognosis). The classifier were built to predict stage II and III colon cancers as either stage I-like (good prognosis) or stage IV-like (poor prognosis). Results: The 3-year relapse-free survival probability (RFS) of stage III patients predicted to have a good prognosis was 79% compared to 55% of patients with a poor prognosis (P = 0.177, log-rank test). The classification model could not stratify stage II colon cancer. The complete dataset representing: (1) the 37 Danish patients (2) the 111 patients retrieved from Series GSE17536 (re-used data), is linked below as a supplementary file. Tumor samples were obtained from 37 patients with stage II and III colon cancer, who underwent colon resection at the Department of Surgery, Roskilde Hospital, Denmark and the Department of Surgery, Bispebjerg Hospital, Denmark between 2001 and 2008. Purified tumor RNA was reverse-transcribed, labelled and hybridized to Affymetrix Human Genome U133 Plus 2.0 GeneChip Array (Affymetrix, Santa Clara, USA) according to the manufacturers instructions and scanned at the RH Microarray Center, Rigshospitalet, University of Copenhagen.
2011-08-31 | E-GEOD-31595 | biostudies-arrayexpress
Project description:Colorectal cancer is one of the most common cancers in the world. Histological staging is efficient but combination with molecular markers may improve tumors classification. Gene expression profiles have been defined as prognosis predictors among stage II and III tumors but their implementation in medical practice remains controversial. Stage-II tumors have been recognized as a heterogeneous group and high-risk morphologic features have been retained as justifying adjuvant chemotherapy. We propose here the investigation of clinical features and expression profiles from stage II and stage III colon carcinomas without DNA mismatch repair defect. A series of 130 colon cancer samples was retained. Expression profiles were established on oligonucleotide microarrays and processed in the R/Bioconductor environment. Hierarchical then supervised analyses were successively performed applying the data-sampling approach. A molecular signature of seven genes was found to cluster stage III tumors with an adjusted p-values lower than 10^-10. A subgroup of stage-II tumors aggregated this cluster in both series. No correlation was found between with the disease severity but the function of the discriminating genes suggests that tumors have been classified according to their putative response to adjuvant targeted or classic therapies. Further pharmacogenetic studies might document this observation. Expression profile of stage-II colon carcinomas distinguishes two patterns of tumors based on a 7-gene signature. One pattern is very similar to that of stage-III tumors and the corresponding tumors aggregate into a single cluster. Genes function suggests possible tumor determinism in drug response more than in prognosis evolution.
2012-05-10 | E-GEOD-37892 | biostudies-arrayexpress
Project description:Colorectal cancer is one of the most common cancers in the world. Histological staging is efficient but combination with molecular markers may improve tumors classification. Gene expression profiles have been defined as prognosis predictors among stage II and III tumors but their implementation in medical practice remains controversial. Stage-II tumors have been recognized as a heterogeneous group and high-risk morphologic features have been retained as justifying adjuvant chemotherapy. We propose here the investigation of clinical features and expression profiles from stage II and stage III colon carcinomas without DNA mismatch repair defect. A series of 130 colon cancer samples was retained. Expression profiles were established on oligonucleotide microarrays and processed in the R/Bioconductor environment. Hierarchical then supervised analyses were successively performed applying the data-sampling approach. A molecular signature of seven genes was found to cluster stage III tumors with an adjusted p-values lower than 10^-10. A subgroup of stage-II tumors aggregated this cluster in both series. No correlation was found between with the disease severity but the function of the discriminating genes suggests that tumors have been classified according to their putative response to adjuvant targeted or classic therapies. Further pharmacogenetic studies might document this observation.
2012-05-11 | GSE37892 | GEO
Project description:High-throughput proteomics profiling-derived signature associated with chemotherapy response and survival for stage II/III colorectal cancer
2023-06-19 | PXD043116 |
Project description:A seven-gene signature aggregates a subgroup of stage II colon cancers with stage III.
| PRJNA165699 | ENA
Project description:The purpose of this study was to establish a new prognostic model for stage II/III colon cancer. Using public DNA microarray data of colon cancer patients, we created an integrated prognostic model for classifying the patients into high- and low-risk groups based on the expression levels of 55 genes and the KRAS mutation status. For validation, we examined specimens from patients with stage II/III colon cancer who had undergone radical resection at our department, and successfully confirmed prognostic value of our model. We believe that our prognostic model may be clinically helpful to select patients for adjuvant chemotherapy.
2018-03-30 | GSE92921 | GEO
Project description:Background and Aims: Staging inadequately predicts metastatic risk in colon cancer patients. We used a gene expression profile derived from invasive murine colon cancer cells that were highly metastatic in an immunocompetent mouse model to identify colon cancer patients at risk for recurrence in a phase I, exploratory biomarker study. Methods: 55 colorectal cancer patients from Vanderbilt Medical Center (VMC) were used as the training dataset and 177 patients from the Moffitt Cancer Center were used as the independent dataset. The metastasis-associated gene expression profile developed from the mouse model was refined using comparative functional genomics in the VMC gene expression profiles to identify a 34-gene classifier associated with high risk of metastasis and death from colon cancer. A recurrence score derived from the biologically based classifier was tested in the Moffitt dataset. Results: A high score was significantly associated with increased risk of metastasis and death from colon cancer across all pathological stages and specifically in stage II and stage III patients. The recurrence score was shown to independently predict risk of cancer recurrence and death in both univariate and multivariate models. For example, among stage III patients, a high score translated to increased relative risk for cancer recurrence (hazard ratio = 4.7 (95% CI=1.566-14.05)). Furthermore, the recurrence score identified stage III patients whose five-year recurrence-free survival was >88% and for whom adjuvant chemotherapy did not provide improved survival. Conclusion: Our biologically based gene expression profile yielded a potentially useful classifier to predict cancer recurrence and death independently of conventional measures in colon cancer patients. Keywords: Functional genomics, metastatic colon cancer, mouse model, human colon cancer
2009-11-14 | GSE17537 | GEO
Project description:Background and Aims: Staging inadequately predicts metastatic risk in colon cancer patients. We used a gene expression profile derived from invasive murine colon cancer cells that were highly metastatic in an immunocompetent mouse model to identify colon cancer patients at risk for recurrence in a phase I, exploratory biomarker study. Methods: 55 colorectal cancer patients from Vanderbilt Medical Center (VMC) were used as the training dataset and 177 patients from the Moffitt Cancer Center were used as the independent dataset. The metastasis-associated gene expression profile developed from the mouse model was refined using comparative functional genomics in the VMC gene expression profiles to identify a 34-gene classifier associated with high risk of metastasis and death from colon cancer. A recurrence score derived from the biologically based classifier was tested in the Moffitt dataset. Results: A high score was significantly associated with increased risk of metastasis and death from colon cancer across all pathological stages and specifically in stage II and stage III patients. The recurrence score was shown to independently predict risk of cancer recurrence and death in both univariate and multivariate models. For example, among stage III patients, a high score translated to increased relative risk for cancer recurrence (hazard ratio = 4.7 (95% CI=1.566-14.05)). Furthermore, the recurrence score identified stage III patients whose five-year recurrence-free survival was >88% and for whom adjuvant chemotherapy did not provide improved survival. Conclusion: Our biologically based gene expression profile yielded a potentially useful classifier to predict cancer recurrence and death independently of conventional measures in colon cancer patients. Keywords: Functional genomics, metastatic colon cancer, mouse model, human colon cancer
2009-11-14 | GSE17536 | GEO
Project description:Analysis of expression profiles in stage II colon cancer according to the APC gene status
2011-01-28 | GSE26906 | GEO