Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Genomic landscape of metastatic colorectal cancer

ABSTRACT: Response to drug therapy in individual colorectal cancer (CRC) patients is associated with tumor biology. Here we describe the genomic landscape of tumor samples of a homogeneous well-annotated series of patients with metastatic CRC of two phase III clinical trials, CAIRO and CAIRO2. DNA copy number aberrations of 349 patients are determined. Within three treatment arms, 194 chromosomal sub-regions are associated with progression free survival PFS (uncorrected single-test p-values < 0.005). These sub-regions are filtered for effect on mRNA expression, using an independent data set from The Cancer Genome Atlas (TCGA) which returned 171 genes. Three chromosomal regions are associated with a significant difference in PFS between treatment arms with or without irinotecan. One of these regions, 6q16.1-q21, correlates in vitro with sensitivity to SN-38, the active metabolite of irinotecan. This genomic landscape of metastatic CRC reveals a number of DNA copy number aberrations associated with response to drug therapy. aCGH data of colorectal cancers of patients from 2 clinical trials (CAIRO, CAIRO2). 105 patients were treated with capecitabine first line (CAIRO arm A), 111 patients were treated with capecitabine and irinotecan first line (CAIRO arm B), and 133 patients were treated with capecitabine, oxaliplatin and bevacizumab (CAIRO2 arm A).

ORGANISM(S): Homo sapiens

SUBMITTER: Daoud Sie

PROVIDER: E-GEOD-36864 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Background & Aims: The metastatic process is complex and remains a major obstacle in the management of colorectal cancer (CRC). To gain a better insight into the biologic events driving the metastatic process we investigated genomic aberrations in a large cohort of matched CRC primaries and distant metastases from various sites. Methods: In total, 62 primary colorectal cancers, 62 matched normal specimens, and 68 matched metastases (from liver, lung, ovary, omentum, and distant lymph nodes) were analyzed by high resolution array comparative genomic hybridization (array CGH) for DNA copy number changes. Findings were validated using a publicly available dataset consisting of 21 primary tumors and matched liver metastases. Fluorescence in situ hybridization (FISH) was used to confirm some of the DNA copy number changes observed. Results: Overall patterns of DNA copy number aberrations were highly similar between primary tumors and their metastases, confirming clonality. Additional copy number aberrations in metastasis are rare and rather than recurrent they were sporadic for individual patients. The only recurrent differences between primary tumors and their metastases were two chromosomal regions, 6q21 and 8q24.21 encompassing the MYC oncogene, that coamplified in three metastases of two patients (3.2%). FISH analysis confirmed the high level co-amplification in the metastasis, which were not detected in their primary tumors. Conclusions: Primary CRC and their metastases show highly similar patterns of DNA copy number changes, additional copy number aberrations in metastasis are rare and recurrences exceptional. These observations are consistent with the hypothesis that the metastatic potential is predestined early in the development of the primary tumor. In total, 62 primary colorectal cancers, 62 matched normal specimens, and 68 matched metastases (liver, lung, ovarian, omentum and distant lymph nodes) were analyzed by high resolution array comparative genomic hybridization (array CGH).

Project description:Claret2009 - Predicting phase III overall survival in colorectal cancer This model is described in the article: Model-based prediction of phase III overall survival in colorectal cancer on the basis of phase II tumor dynamics. Claret L, Girard P, Hoff PM, Van Cutsem E, Zuideveld KP, Jorga K, Fagerberg J, Bruno R. J. Clin. Oncol. 2009 Sep; 27(25): 4103-4108 Abstract: PURPOSE: We developed a drug-disease simulation model to predict antitumor response and overall survival in phase III studies from longitudinal tumor size data in phase II trials. METHODS: We developed a longitudinal exposure-response tumor-growth inhibition (TGI) model of drug effect (and resistance) using phase II data of capecitabine (n = 34) and historical phase III data of fluorouracil (FU; n = 252) in colorectal cancer (CRC); and we developed a parametric survival model that related change in tumor size and patient characteristics to survival time using historical phase III data (n = 245). The models were validated in simulation of antitumor response and survival in an independent phase III study (n = 1,000 replicates) of capecitabine versus FU in CRC. RESULTS: The TGI model provided a good fit of longitudinal tumor size data. A lognormal distribution best described the survival time, and baseline tumor size and change in tumor size from baseline at week 7 were predictors (P < .00001). Predicted change of tumor size and survival time distributions in the phase III study for both capecitabine and FU were consistent with observed values, for example, 431 days (90% prediction interval, 362 to 514 days) versus 401 days observed for survival in the capecitabine arm. A modest survival improvement of 39 days (90% prediction interval, -21 to 110 days) versus 35 days observed was predicted for capecitabine. CONCLUSION: The modeling framework successfully predicted survival in a phase III trial on the basis of capecitabine phase II data in CRC. It is a useful tool to support end-of-phase II decisions and design of phase III studies. This model is hosted on BioModels Database and identified by: MODEL1708310001. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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Genomic landscape of metastatic colorectal cancer

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