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Basal subtype cancers are deadly malignancies but the molecular events driving tumor lethality are not completely understood. Ataxia-telangiectasia group D complementing gene (ATDC, also known as TRIM29), is highly expressed and drives tumor formation and invasion in human bladder cancers but the factor(s) regulating its expression in bladder cancer are unknown. Molecular subtyping of bladder cancer has identified an aggressive basal subtype, which shares molecular features of basal/squamous tumors arising in other organs and is defined by activation of a TP63-driven gene program. Here, we demonstrate that ATDC is linked with expression of TP63 and highly expressed in basal bladder cancers. We find that TP63 binds to transcriptional regulatory regions of ATDC and KRT14 directly, increasing their expression, and that ATDC and KRT14 execute a TP63-driven invasive program. In vivo, ATDC is required for TP63-induced bladder tumor invasion and metastasis. These results link TP63 and the basal gene expression program to ATDC and to aggressive tumor behavior. Defining ATDC as a molecular determinant of aggressive, basal cancers may lead to improved biomarkers and therapeutic approaches.

Cancer is an evolutionary process. Mutated cells undergo selection for abnormal growth and survival creating a tumor. We model this process with cellular automata that use a simplified genetic regulatory network simulation to control cell behavior and predict cancer etiology. Our genetic model gives us the ability to relate genetic mutation to cancerous outcomes. The simulation uses known histological morphology, cell types, and stochastic behavior to specifically model ductal carcinoma in situ (DCIS), a common form of non-invasive breast cancer. Using this model we examine the effects of hereditary predisposition on DCIS incidence and aggressiveness. Results show that we are able to reproduce in vivo pathological features to hereditary forms of breast cancer: earlier incidence and increased aggressiveness. We also show that a contributing factor to the different pathology of hereditary breast cancer results from the ability of progenitor cells to pass cancerous mutations on to offspring.

The Systems Biology for Infectious Diseases Research program was established by the U.S. National Institute of Allergy and Infectious Diseases to investigate host-pathogen interactions at a systems level. This program generated 47 transcriptomic and proteomic datasets from 30 studies that investigate in vivo and in vitro host responses to viral infections. Human pathogens in the Orthomyxoviridae and Coronaviridae families, especially pandemic H1N1 and avian H5N1 influenza A viruses and severe acute respiratory syndrome coronavirus (SARS-CoV), were investigated. Study validation was demonstrated via experimental quality control measures and meta-analysis of independent experiments performed under similar conditions. Primary assay results are archived at the GEO and PeptideAtlas public repositories, while processed statistical results together with standardized metadata are publically available at the Influenza Research Database (www.fludb.org) and the Virus Pathogen Resource (www.viprbrc.org). By comparing data from mutant versus wild-type virus and host strains, RNA versus protein differential expression, and infection with genetically similar strains, these data can be used to further investigate genetic and physiological determinants of host responses to viral infection.