Cell Identity and Signaling (CIS)

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Cell Identity and Signaling (CIS) Research Program Project Summary The key scientific goals of the Cell Identity and Signaling (CIS) Research Program are to advance discovery of novel molecular mechanisms of cell identity and cell signaling, to apply this knowledge towards understanding cancer pathogenesis, and to use this knowledge to develop novel, mechanism-based approaches to prevent or interfere with cancer cell growth, aiming for cancer solutions. It is well-established that cancer cells hijack normal regulation of cell growth, differentiation, and embryonic development, via genetic and epigenetic mechanisms. The CIS Program aims to understand these fundamental mechanisms and shepherd them toward cancer solutions. The CIS Program has 27 members, $5.5 million in cancer-focused, peer-reviewed extramural funding, with 38% of the total funding from the NCI. CIS research themes span a spectrum from basic discovery, using simple model organisms and cellular and animal cancer models, to cancer solutions. CIS members are highly productive with 202 cancer-related publications since July 2015, and highly interactive with a 70% increase in collaborative publications. Importantly, 73% of all cancer-relevant CIS publications are collaborative. In the previous funding cycle, the CIS Program, supported by competitive pilot grants from the Purdue Center for Cancer Research (PCCR), successfully fostered highly collaborative, cancer-relevant studies linking CIS Program themes (intra- programmatic) with other PCCR programs (inter-programmatic), and also with external partners (inter- institutional). For the next funding period, the goal of the CIS Program is to advance the breadth and depth of our understanding of cancer-relevant mechanisms and to maximize their transition to cancer solutions. The approach towards this goal is to enable and foster collaborative and transdisciplinary studies by providing competitive PCCR pilot grants, and access to state-of-the-art, PCCR-supported Shared Resources, and modern technology in structural biology, drug discovery, cancer genomics, bioinformatics and computational biology. Three specific aims are proposed. Aim 1: To further enhance discovery of basic and cancer-relevant mechanisms by strengthening the integration of computational genomics and bioinformatics and increasing expertise and training in computational biology. Aim 2: To enhance discovery of cancer-relevant mechanisms of signal transduction, gene expression and epigenetics by supporting collaborative, transdisciplinary approaches and modern technologies. Aim 3: To accelerate transition of newly discovered cancer-relevant mechanisms towards cancer solutions, by developing essential mechanisms as therapy targets, and by employing transdisciplinary approaches.