Abstract Background: CRC cancer is one of the deadliest diseases in Western countries. In order to develop predictive biomarkers for CRC (colorectal cancer) aggressiveness, we analyzed retrospectively 267 CRC patients via a novel, multidimensional biomarker platform. Methods: 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 combined the data into multidimensional scores using inverse sliced regression for sufficient dimension reduction. Accuracy was assessed using the Area under the Curve (AUC) and the receiver operating characteristic (ROC) method. Results: 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 multidimensional biomarkers, AUCs were dramatically increased with values approaching and even exceeding 0.9. Conclusions: Single dimension analysis generates statistically significant predictors, but their predictive strengths are suboptimal for clinical utility. A novel, multidimensional approach overcomes these deficiencies. Newly derived multidimensional biomarkers have the potential to meaningfully guide the selection of therapeutic agents for individual patients while elucidating molecular mechanisms driving disease progression. Citation Format: Marisa Mariani, Shiquan He, Mark McHugh, Mirko Andreoli, Deep Pandya, Steven Sieber, Zheyang Wu, Paul Fiedler, Shohreh Shahabi, Cristiano Ferlini. A multidimensional analysis of predictive biomarkers in colorectal cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 916. doi:10.1158/1538-7445.AM2014-916