Abstract
Abstract Metastatic lung cancer is the leading cause of cancer related death in the world and novel approaches are necessary to elucidate specific genes that drive lung cancer progression and metastasis. Lung cancers commonly demonstrate genetic alteration of potent drivers like Kras, p53 or EGFR accompanied with hundreds of low frequency gene aberrations which are a mix of key driver events and nascent passenger mutations. We established a robust screening platform to selectively identify these functionally critical “driver” genes in lung cancers from a prioritized list of candidates selected by a multi-level cross-species comparison of our published high confidence transcriptome data from genetically-engineered mouse models and genomic data of human lung cancers from TCGA, focusing on elevated gene expression and/or gene amplification. We identified 225 putative candidate driver genes which were used to construct a lentiviral based cDNA expression library with unique molecular barcoding of individual cDNAs. Using a non-metastatic syngeneic mouse lung cancer model we generated individually transduced stable over-expressing lines for each gene. These candidate lines were used for a unique in vivo positive selection screen to identify functional metastasis drivers. We transplanted pools of 20 cDNA expressing lines into syngeneic mice and observed for primary tumor growth and occurrence of metastases in lungs and other organs. Metastatic drivers were identified by the relative enrichment of the unique barcode sequences in the genomic DNA from metastatic lesions over primary tumors. We have identified both known (e.g. MYC) and several novel (e.g. THRA, TMEM106B, GNAS) potential oncogenic and metastatic drivers. We validated our top hits for their individual in vivo metastatic potencies by gain-of-function/loss-of-function studies and identified TMEM106B as one of the primary drivers of metastasis. TMEM106B is a transmembrane protein localizing to the lysosomes and has been shown to drive expression of lysosomal genes. We hypothesize that elevated levels of TMEM106B is able to drive the expression and secretion of lysosomal enzymes thus making cancer cells hyper invasive and metastatic. We found strong correlation for expression of TMEM106B with several lysosomal genes in a panel of 1016 human lung cancers and are currently performing in depth studies to understand these mechanisms of TMEM106B driven metastasis. We are also analyzing the clinical relevance of TMEM106B based upon their expression pattern and prognostic utility across TCGA and other public datasets, along with in-house patient samples and tissue microarrays of resected and biopsy specimens. Identification of such novel players will significantly advance the field of cancer target discovery by identifying new drug targets and biomarkers, essential for effective treatment options for lung cancer patients. Citation Format: Samrat Kundu, Caitlin Grzeskowiak, Chad J. Creighton, Kenneth L. Scott, Don L. Gibbons. Identifying TMEM106B as a novel metastasis driver in non-small cell lung cancers through an in vivo gain-of-function screen. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 688.
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