Defining the roles of ERK MAPK in driving KRAS-mutant pancreatic cancer growth.

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KRAS mutations occur in ~95% of pancreatic ductal adenocarcinoma (PDAC) and are essential to support PDAC growth. The NCI has identified the development of anti-KRAS therapies is one of four major goals for the field. Among current directions, inhibitors of KRAS effector signaling through the RAF-MEK-ERK mitogen-activated protein kinase (MAPK) cascade have shown promise. Our laboratory recently validated ERK inhibitors as a promising strategy for PDAC treatment. However, normal cell toxicity and tumor cell innate/acquired resistance will likely limit the long-term efficacy of ERK inhibitor therapy. My studies will mine two unpublished omics data sets generated in my lab, to identify therapeutic strategies that may help overcome these limitations. First, in my Aim 1 studies I have evaluated data from a druggable genome RNAi screen to identify genes that modulate PDAC sensitivity to the ERK-specific inhibitor SCH772984 (ERKi). I chose to evaluate one of the top hits, CHEK1, that encodes the CHK1 serine/threonine kinase. CHK1 is required for checkpoint-mediated cell cycle arrest and activation of DNA repair in response to DNA damage. As such, CHK1 inhibitors are more conventionally combined with DNA damaging anticancer drugs. Yet I determined that concurrent treatment with ERKi and the clinical candidate CHK1 inhibitor prexasertib enhanced suppression of PDAC growth in vitro. My studies will determine the mechanistic basis for combining ERKi with prexasertib as a novel strategy to block KRAS- dependent PDAC growth. While I have already identified inhibitor convergence on blocking MYC oncogene function, I will also apply reverse phase protein array (RPPA) analyses for an unbiased profiling of signal transduction activity/expression changes to provide addition mechanistic insight on this combination therapy. I will also further evaluate the potential therapeutic value of this combination in more rigorous preclinical models, in patient-derived organoids and orthotopic PDAC mouse models. Second, in my Aim 2 studies, I evaluated an RNA-seq data set profiling the ERK-dependent transcriptome with the goal of identifying genes that drive ERK- dependent PDAC growth. I identified the 20 most up- and down-regulated genes, with EGR1 one of the most significantly suppressed genes. EGR1 is a transcription factor that has been implicated in cancer, but as either an oncogene or tumor suppressor, depending on the cancer type evaluated. Since EGR1 expression is suppressed upon ERK inhibition, and I have determined that EGR1 regulates expression of MYC, a key contributor to KRAS- and ERK-dependent PDAC growth, I hypothesize that EGR1 will be a critical component of ERK mediated gene expression. In parallel, I will also use an RNAi screen with the 20 downregulated genes to establish a more comprehensive identification of genes that contribute to ERK-mediated PDAC growth. My proposed studies will help advance targeting ERK for PDAC treatment as well as provide me with rigorous training to enhance my computational/bioinformatics skills.