TP53-independent function of miR-34a via HDAC1 and p21(CIP1/WAF1.).

The tumor suppressor, microRNA-34 (miR-34), a transcriptional target of TP53, functions in a positive feedback loop to activate TP53. Although miR-34 can inhibit cancer cells carrying TP53 mutations, this feedback to TP53 may be a prerequisite for full miR-34 function and may restrict its therapeutic application to patients with intact TP53. To investigate the functional relationships between TP53 and miR-34, and that of other TP53-regulated miRNAs including miR-215/192, we have used a panel of isogenic cancer cell lines that differ only with respect to their endogenous TP53 status. miR-34-induced inhibition of cancer cell growth is the same in TP53-positive and TP53-negative cells. In contrast, miR-215/192 functions through TP53. In the absence of TP53, miR-34, but not miR-215/192, is sufficient to induce an upregulation of the cell cycle-dependent kinase inhibitor p21(CIP1/WAF1). We identify histone deacetylase 1 (HDAC1) as a direct target of miR-34 and demonstrate that repression of HDAC1 leads to an induction of p21(CIP1/WAF1) and mimics the miR-34 cellular phenotype. Depletion of p21(CIP1/WAF1) specifically interferes with the ability of miR-34 to inhibit cancer cell proliferation. The data suggest that miR-34 controls a tumor suppressor pathway previously reserved for TP53 and provides an attractive therapeutic strategy for cancer patients irrespective of TP53 status.

Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets.

The European Union multi-disciplinary Personalised RNA interference to Enhance the Delivery of Individualised Cytotoxic and Targeted therapeutics (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway inhibitor. Through the analysis of tumor tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumor-derived genomic data with personalized tumor-derived small hairpin RNA and high-throughput small interfering RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of chance associations that lead to overestimation of true clinical accuracy. These methods will identify molecular pathways important for survival and growth of RCC cells and particular targets suitable for therapeutic development. Importantly, our results may enable individualized treatment of RCC, reducing ineffective therapy in drug-resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate a European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding of molecular mechanisms driving resistance to anti-angiogenesis agents, the current limitations of laboratory and clinical trial strategies and how the PREDICT consortium will endeavor to identify a new generation of predictive biomarkers.