Dataset Information

Integrated multidimensional analysis is required for accurate prognostic biomarkers in colorectal cancer.

ABSTRACT: CRC cancer is one of the deadliest diseases in Western countries. In order to develop prognostic biomarkers for CRC (colorectal cancer) aggressiveness, we analyzed retrospectively 267 CRC patients via a novel, multidimensional biomarker platform. Using nanofluidic technology for qPCR analysis and quantitative fluorescent immunohistochemistry for protein analysis, we assessed 33 microRNAs, 124 mRNAs and 9 protein antigens. Analysis was conducted in each single dimension (microRNA, gene or protein) using both the multivariate Cox model and Kaplan-Meier method. Thereafter, we simplified the censored survival data into binary response data (aggressive vs. non aggressive cancer). Subsequently, we integrated the data into a diagnostic score using sliced inverse regression for sufficient dimension reduction. Accuracy was assessed using area under the receiver operating characteristic curve (AUC). Single dimension analysis led to the discovery of individual factors that were significant predictors of outcome. These included seven specific microRNAs, four genes, and one protein. When these factors were quantified individually as predictors of aggressive disease, the highest demonstrable area under the curve (AUC) was 0.68. By contrast, when all results from single dimensions were combined into integrated biomarkers, AUCs were dramatically increased with values approaching and even exceeding 0.9. Single dimension analysis generates statistically significant predictors, but their predictive strengths are suboptimal for clinical utility. A novel, multidimensional integrated approach overcomes these deficiencies. Newly derived integrated biomarkers have the potential to meaningfully guide the selection of therapeutic strategies for individual patients while elucidating molecular mechanisms driving disease progression.

SUBMITTER: Mariani M

PROVIDER: S-EPMC4079703 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrated multidimensional analysis is required for accurate prognostic biomarkers in colorectal cancer.

Mariani Marisa M He Shiquan S McHugh Mark M Andreoli Mirko M Pandya Deep D Sieber Steven S Wu Zheyang Z Fiedler Paul P Shahabi Shohreh S Ferlini Cristiano C

PloS one 20140702 7

CRC cancer is one of the deadliest diseases in Western countries. In order to develop prognostic biomarkers for CRC (colorectal cancer) aggressiveness, we analyzed retrospectively 267 CRC patients via a novel, multidimensional biomarker platform. Using nanofluidic technology for qPCR analysis and quantitative fluorescent immunohistochemistry for protein analysis, we assessed 33 microRNAs, 124 mRNAs and 9 protein antigens. Analysis was conducted in each single dimension (microRNA, gene or protein ...[more]

PMID: 24988459

Similar Datasets

Project description:BackgroundBreast cancer is a malignancy and lethal tumor in women. Metastasis of breast cancer is one of the causes of poor prognosis. Increasing evidences have suggested that the competing endogenous RNAs (ceRNAs) were associated with the metastasis of breast cancer. Nonetheless, potential roles of ceRNAs in regulating the metastasis of breast cancer remain unclear.MethodsThe RNA expression (3 levels) and follow-up data of breast cancer and noncancerous tissue samples were downloaded from the Cancer Genome Atlas (TCGA). Differentially expressed and metastasis associated RNAs were identified for functional analysis and constructing the metastasis associated ceRNA network by comprehensively bioinformatic analysis. The Kaplan-Meier (K-M) survival curve was utilized to screen the prognostic RNAs in metastasis associated ceRNA network. Moreover, we further identified the metastasis associated biomarkers with operating characteristic (ROC) curve. Ultimately, the data of Cancer Cell Line Encyclopedia (CCLE, https://portals.broadinstitute.org/ccle) website were selected to obtained the reliable metastasis associated biomarkers.Results1005 mRNAs, 22 miRNAs and 164 lncRNAs were screened as differentially expressed and metastasis associated RNAs. The results of GO function and KEGG pathway enrichment analysis showed that these RNAs are mainly associated with the metabolic processes and stress responses. Next, a metastasis associated ceRNA (including 104 mRNAs, 19 miRNAs, and 16 lncRNAs) network was established, and 12 RNAs were found to be related to the overall survival (OS) of patients. In addition, 3 RNAs (hsa-miR-105-5p, BCAR1, and PANX2) were identified to serve as reliable metastasis associated biomarkers. Eventually, the results of mechanism analysis suggested that BCAR1 might promote the metastasis of breast cancer by facilitating Rap 1 signaling pathway.ConclusionIn the present research, we identified 3 RNAs (hsa-miR-105-5p, BCAR1 and PANX2) might associated with prognosis and metastasis of breast cancer, which might be provide a new perspective for metastasis of breast cancer and contributed to the treatment of breast cancer.

Dataset Information

Integrated multidimensional analysis is required for accurate prognostic biomarkers in colorectal cancer.

Publications

Integrated multidimensional analysis is required for accurate prognostic biomarkers in colorectal cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure