Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA236612 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Sadanandam et al. (2013) recently published a study based on the use of microarray data to classify colorectal cancer (CRC) samples. The classification claimed to have strong clinical implications, as reflected in the paper title: “A colorectal cancer classification system that associates cellular phenotype and responses to therapy”. They defined five subtypes: (i) inflammatory; (ii) goblet-like; (iii) enterocyte; (iv) transit-amplifying; and (v) stem-like. Based on drug sensitivity data from 21 patients, they also reported that the so-called stem-like subtype show differential sensitivity to FOLFIRI. This is the key result in their publication, since it implies a direct relation between the subtype and the choice of CRC therapy (i.e. FOLFIRI response). However, our analyses using the same drug sensitivity data and results from additional patients showed that the CRC classification reported by Sadanandam et al. is not predictive of FOLFIRI response.
2014-09-10 | GSE54483 | GEO
Project description:Sadanandam et al. (2013) recently published a study based on the use of microarray data to classify colorectal cancer (CRC) samples. The classification claimed to have strong clinical implications, as reflected in the paper title: “A colorectal cancer classification system that associates cellular phenotype and responses to therapy”. They defined five subtypes: (i) inflammatory; (ii) goblet-like; (iii) enterocyte; (iv) transit-amplifying; and (v) stem-like. Based on drug sensitivity data from 21 patients, they also reported that the so-called stem-like subtype show differential sensitivity to FOLFIRI. This is the key result in their publication, since it implies a direct relation between the subtype and the choice of CRC therapy (i.e. FOLFIRI response). However, our analyses using the same drug sensitivity data and results from additional patients showed that the CRC classification reported by Sadanandam et al. is not predictive of FOLFIRI response. We used the classification algorithm to obtain CRC subtypes from our samples. Then we tested the subtype-drug response association performing a retrospective study.
2014-09-10 | E-GEOD-54483 | biostudies-arrayexpress
Project description:We report that previously described molecular subtypes of colorectal cancer are associated with the response to therapy in patients with metastatic disease. We also identified a patient population with high FOLFIRI sensitivity, as indicated by their 2.7-fold longer overall survival when treated with FOLFIRI, as first-line regimen, instead of FOLFOX. Our results demonstrate the interest of molecular classifications to develop tailored therapies for patients with metastatic colorectal cancer.
2017-08-17 | GSE72968 | GEO
Project description:We report that previously described molecular subtypes of colorectal cancer are associated with the response to therapy in patients with metastatic disease. We also identified a patient population with high FOLFIRI sensitivity, as indicated by their 2.7-fold longer overall survival when treated with FOLFIRI, as first-line regimen, instead of FOLFOX. Our results demonstrate the interest of molecular classifications to develop tailored therapies for patients with metastatic colorectal cancer.
2017-08-17 | GSE72969 | GEO
Project description:Response rates of 118 colorectal cancer patients to regiments were evaluated by histoculture drug response assay. Affymetrix SNP 6.0 chips were used to determine genotypes of the same colorectal cancer patients. SNPs associated with chemosensitivity to treatment regiments were identified by genome-wide association study. AV: avastin (Bevacizumab), ER: Erbitux (Cetuximab), FXA: bevacizumab + FOLFOX, FXE: Cetuximab + FOLFOX , FRA: Bevacizumab + FOLFIRI, FRE: Cetuximab + FOLFIRI; Numbers (0-100) represent responsiveness to the given drug regimens; the larger, the better responsive to given regimens
2011-03-25 | GSE21228 | GEO
Project description:Relapse and metastatic progression is a frequent event in colorectal cancer patients detected at early stages. The risk of recurrence requires the development of new biomarkers to correctly predict biological behavior of early stage II and stage III patients and their response to adjuvant chemotherapy. Here, we combined the proteomic quantification of secreted proteins involved in metastasis with a transcriptional analysis to develop a risk score algorithm based on the expression of six genes (SEC6). The SEC6 signature was predictive of survival and recurrence for stage II and III patients in four different datasets including a total of 1534 patients and was also associated with deficient mismatch repair, CpG-island methylator positive status and BRAF mutation. SEC6 was also predictive of beneficial or detrimental effects from 5-Fluorouracil-containing regimes and the improved response to more aggressive chemotherapies based on FOLFOX and FOLFIRI. In summary, the SEC6 risk-score algorithm may constitute a new tool for decision-making in colorectal cancer management.
2022-12-27 | PXD032899 | Pride
Project description:In patients with advanced colorectal cancer, leucovorin, fluorouracil, and irinotecan (FOLFIRI) is considered as one of the reference first-line treatments. However, only about half of treated patients respond to this regimen, and there is no clinically useful marker that predicts response. A major clinical challenge is to identify the subset of patients who could benefit from this chemotherapy. We aimed to identify a gene expression profile in primary colon cancer tissue that could predict chemotherapy response. Patients and Methods:- Tumor colon samples from 21 patients with advanced colorectal cancer were analyzed for gene expression profiling using Human Genome GeneChip arrays U133. At the end of the first-line treatment, the best observed response, according to WHO criteria, was used to define the responders and nonresponders. Discriminatory genes were first selected by the significance analysis of microarrays algorithm and the area under the receiver operating characteristic curve. A predictor classifier was then constructed using support vector machines. Finally, leave-one-out cross validation was used to estimate the performance and the accuracy of the output class prediction rule. Results:- We determined a set of 14 predictor genes of response to FOLFIRI. Nine of nine responders (100% specificity) and 11 of 12 nonresponders (92% sensitivity) were classified correctly, for an overall accuracy of 95%. Conclusion:- After validation in an independent cohort of patients, our gene signature could be used as a decision tool to assist oncologists in selecting colorectal cancer patients who could benefit from FOLFIRI chemotherapy, both in the adjuvant and the first-line metastatic setting.
2014-10-06 | GSE62080 | GEO
Project description:Gene expression profiling of immortalized human mesenchymal stem cells with hTERT/E6/E7 transfected MSCs. hTERT may change gene expression in MSCs. Goal was to determine the gene expressions of immortalized MSCs.
2010-09-25 | GSE24338 | GEO
Project description:Gene based influence of PDGF/VEGF in colorectal cancer
| PRJNA282668 | ENA