Gene expression signature in advanced colorectal cancer patients select drugs and response for the use of leucovorin, fluorouracil, and irinotecan
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Pierre Martineau
PROVIDER: E-GEOD-62322 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:To identify genes implicated in metastatic colonization of the liver in colorectal cancer, we collected pairs of primary tumors and hepatic metastases before chemotherapy in 13 patients. We compared mRNA expression in the pairs of patients to identify genes deregulated during metastatic evolution. We then validated the identified genes using data obtained by different groups. The 33-gene signature was able to classify 87% of hepatic metastases, 98% of primary tumors, 97% of normal colon mucosa, and 95% of normal liver tissues in six datasets obtained using five different microarray platforms. The identified genes are specific to colon cancer and hepatic metastases since other metastatic locations and hepatic metastases originating from breast cancer were not classified by the signature. Gene Ontology term analysis showed that 50% of the genes are implicated in extracellular matrix remodeling, and more precisely in cell adhesion, extracellular matrix organization and angiogenesis. Because of the high efficiency of the signature to classify colon hepatic metastases, the identified genes represent promising targets to develop new therapies that will specifically affect hepatic metastasis microenvironment. 57 samples of patients with stage IV colorectal cancer. We compared using Affymetrix chips gene expression profiles between primary tumors and hepatic metastases
2014-10-15 | E-GEOD-62321 | biostudies-arrayexpress
Project description:To identify genes implicated in metastatic colonization of the liver in colorectal cancer, we collected pairs of primary tumors and hepatic metastases before chemotherapy in 13 patients. We compared mRNA expression in the pairs of patients to identify genes deregulated during metastatic evolution. We then validated the identified genes using data obtained by different groups. The 33-gene signature was able to classify 87% of hepatic metastases, 98% of primary tumors, 97% of normal colon mucosa, and 95% of normal liver tissues in six datasets obtained using five different microarray platforms. The identified genes are specific to colon cancer and hepatic metastases since other metastatic locations and hepatic metastases originating from breast cancer were not classified by the signature. Gene Ontology term analysis showed that 50% of the genes are implicated in extracellular matrix remodeling, and more precisely in cell adhesion, extracellular matrix organization and angiogenesis. Because of the high efficiency of the signature to classify colon hepatic metastases, the identified genes represent promising targets to develop new therapies that will specifically affect hepatic metastasis microenvironment. 57 samples of patients with stage IV colorectal cancer. We compared using Affymetrix chips gene expression profiles between primary tumors and hepatic metastases
2013-09-01 | E-GEOD-49355 | biostudies-arrayexpress
Project description:Type I interferon (IFN) is a family of 15 cytokines (in human 13α, 1β,1ω) which exert several cellular functions through the binding to a common receptor. Despite the initial activation of the same Jak/Stat signalling pathway, the cellular response may be different depending on the type I IFN subtype. We investigated the activity of different type I IFN subtypes - IFNα1, α2, α8, α21, ω and β- on the differentiation of DC. Transcriptome analyses identified two distinct groups, the IFNα/ω-DC and the IFNβ-DC. 78 genes, 7 chemokines and expression levels of cell surface markers characteristic of DC distinguished IFNα-DC and IFNβ-DC. These differences are unlikely to impact the efficacy of T cell functional response since IFNα2-DC and IFNβ-DC were equipotent in inducing the proliferation and the polarization of allogenic naïve CD4 T cells into Th1 cells and in stimulating autologous memory CD4 or CD8 T cells. In contrast, IFNα2-DC were found to be more efficient than IFNβ-DC in the phagocytic uptake of dead cells. Human blood monocytes were differentiated in DC by using 5 differents IFN type I (IFNα2, α1, α8, α21 and β). After 3 days of differentiation RNA were extracted and analyzed by affymetrix microarray.
2012-09-20 | E-GEOD-40268 | biostudies-arrayexpress
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. All tissue samples were maintained at −180°C (liquid nitrogen) until RNA extraction and were weighed before homogenization. Tissue samples were then disrupted directly into a lysis buffer using Mixer Mill MM 300 (Qiagen, Valencia, CA). Total RNA was isolated from tissue lysates using the RNeasy Mini Kit (Qiagen), and additional DNAse digestion was performed on all samples during the extraction process (RNase-Free DNase Set Protocol for DNase treatment on RNeasy Mini Spin Columns; Qiagen). After each extraction, a small fraction of the total RNA preparation was taken to determine the quality of the sample and the yield of total RNA. Controls analyses were performed by UV spectroscopy and analysis of total RNA profile using the Agilent RNA 6000 Nano LabChip Kit with the Agilent 2100 Bioanalyser (Agilent Technologies, Palo Alto, CA) to determine RNA purity, quantity, and integrity.
2014-10-06 | E-GEOD-62080 | biostudies-arrayexpress
Project description:Regulatory T (Treg) cells actively control pathological immune responses and immunotherapeutic strategies triggering an increase in the number and/or the function of endogenous Treg cells emerge as a promising therapeutic strategy in autoimmune diseases to restore tolerance. A remarkable heterogeneity in peripheral Treg cells has been evidenced and underscored the need to better characterize them and compare their suppressive function to determine which Treg subset will be optimally suitable for a given clinical situation. We demonstrated that repetitive injections of immature dendritic cells (DC) expand FoxP3-negative CD49b+ Treg cells that display an effector memory phenotype. Transcriptome analysis of ex-vivo isolated Treg-expanded by DC injections contains multiple transcripts of the canonical Treg signature shared mainly by CD25+ but also by other Treg subphenotypes. We provided an in-depth characterization of the CD49b+ Treg cells phenotype underscoring their similarities with CD25+ Treg cells and highlighting some specific expression pattern for several markers including LAG3, KLRG1, CD103, ICOS, CTLA-4 and GZB. Comparison of their suppressive mechanism in vitro and in vivo with that of FoxP3-positive Treg cells provide evidence of their potent suppressive activity in vivo, partly dependent on IL-10 secretion. Altogether our results underscore the therapeutic potential of IL-10 secreting CD49b+ Treg cells in arthritis and strongly suggest that expression of several canonical markers and suppressive function could be FoxP3-independent All gene expression profiles were obtained from highly purified T cell populations sorted by flow cytometry. To reduce variability, cells from multiple mice were pooled for sorting, and two to three replicates were generated for all groups. RNA from 2.5-10 x 105 cells was amplified, labeled, and hybridized to Affymetrix M430v2 microarrays.
2015-12-10 | E-GEOD-68621 | biostudies-arrayexpress
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.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.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%.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.
| S-EPMC2257989 | biostudies-literature
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.
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