Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA304433 | ENA |
REPOSITORIES: ENA
Similar Datasets
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 (CRC) is the third most common cancer worldwide and is a heterogeneous disease, with differences between cancer in the right colon, left colon, and rectum. In this study, plasma samples from CRC patients with varying stage (II or III), primary tumor location (right colon, left colon, or rectum) and survival (survived or died due to CRC) were studied with quantitative label-free proteomics using ultra-definition MSE. Patients were also divided into subgroups based on preoperative radiotherapy status and gender. Further analysis subsequently identified multiple plasma proteins whose expression differed depending on tumor stage, location, patient survival, preoperative radiotherapy status, or gender.
2019-08-22 | PXD013150 | Pride
Project description:Samples were taken from surgically resected tumor specimens from patients with proximal colon cancer. The expression profiles were determined using the Affymetrix GeneChip Human Exon 1.0 ST Array version 2. APC gene mutation status was determined using Sanger sequencing. A classifier for APC mutation status was trained using these expression data. 52 microsatellite stable (MSS) proximal colon cancers samples were analyzed. 17 samples were APC wild-type and 35 had APC protein-truncating mutations.
2016-03-02 | E-GEOD-63624 | biostudies-arrayexpress
Project description:Adenomatous polyposis coli (APC) is an important tumor suppressor and most directly related to the regulation of WNT/β-catenin signaling pathway. APC mutation has been identified as an early event in more than 80% of sporadic colorectal cancers (CRCs). However, obvious prognostic differences are observed in CRC patients with APC mutations. Although previous genomics has investigated the roles of concomitant gene mutations in determining the phenotypic heterogeneity of APC-mutant tumors, valuable prognostic determinants for APC-mutant CRC patients are still lacking. By using combined proteome and phosphoproteome, we classified the APC-mutant colon cancer patients and revealed the genomic, proteomic and phosphoproteomic heterogeneity in APC-mutant tumors. Of importance, we identified RAI14 as a key prognostic determinant for APC-mutant colon cancer patients, but not for APC-wildtype colon cancer patients. The heterogeneity and prognostic biomarkers in APC-mutant tumors were further confirmed in Clinical Proteomic Tumor Analysis Consortium (CPTAC) colon cancer cohort. In addition, we found that knockdown of RAI14 in cell lines led to reduced cell migration and changes in some epithelial-mesenchymal transition (EMT)-related markers. Mechanistically, knockdown of RAI14 was able to remodel the phosphoproteome associated with cell adhesion, which might promote F-action degradation and alter the expression of certain EMT markers. Collectively, this work describes the phenotypic heterogeneity of APC-mutant tumors and identifies the prognostic determinants for APC-mutant colon cancer patients. The prognostic utility of RAI14 in APC-mutant colon cancer will provide early warning and increase the chance of successful treatment.
2022-11-10 | PXD038081 |
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: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:The Adenomatous Polyposis Coli (APC) tumor suppressor is mutated in the vast majority of human colorectal cancers (CRC) and leads to deregulated Wnt signaling. To determine whether Apc disruption is required for tumor maintenance, we developed a mouse model of CRC whereby Apc can be conditionally suppressed using a doxycycline-regulated shRNA. Apc suppression produces adenomas in both the small intestine and colon that, in the presence of Kras and p53 mutations, can progress to invasive carcinoma. In established tumors, Apc restoration drives rapid and widespread tumor-cell differentiation and sustained regression without relapse. Tumor regression is accompanied by the re-establishment of normal crypt-villus homeostasis, such that once aberrantly proliferating cells reacquire self-renewal and multi-lineage differentiation capability. Our study reveals that CRC cells can revert to functioning normal cells given appropriate signals, and provide compelling in vivo validation of the Wnt pathway as a therapeutic target for treatment of CRC Analysis of RNA isolated from colon polyps that presented in shAPC or shAPC/Kras mice as compared to shRenilla (neutral) mouse colon mucosa
2015-06-18 | E-GEOD-67186 | biostudies-arrayexpress