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Query: UMLS:C0004135 (ATM)
 13,001 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Pancreatic cancer requires many genetic mutations. Combinations of underlying germline variants and environmental factors may increase the risk of cancer and accelerate the oncogenic process. We systematically reviewed, annotated, and classified previously reported pancreatic cancer-associated germline variants in established risk genes. Variants were scored using multiple criteria and binned by evidence for pathogenicity, then annotated with published functional studies and associated biological systems/pathways. Twenty-two previously identified pancreatic cancer risk genes and 337 germline variants were identified from 97 informative studies that met our inclusion criteria. Fifteen of these genes contained 66 variants predicted to be pathogenic (APC, ATM, BRCA1, BRCA2, CDKN2A, CFTR, CHEK2, MLH1, MSH2, NBN, PALB2, PALLD, PRSS1, SPINK1, TP53). Pancreatic cancer risk genes were organized into key biological mechanisms that promote pancreatic oncogenesis within an oncogenic model. Development of precision medicine approaches requires updated variant information within the framework of an oncogenic progression model. Complex risk modeling may improve interpretation of early biomarkers and guide pathway-specific treatment for pancreatic cancer in the future. Precision medicine is within reach.
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PMID:Germline Variants and Risk for Pancreatic Cancer: A Systematic Review and Emerging Concepts. 3011 27

Endometriosis is characterized by ectopic endometrial tissue implantation, mostly within the peritoneum, and affects women in their reproductive age. Studies have been done to clarify its etiology, but the precise molecular mechanisms and pathophysiology remain unclear. We downloaded genome-wide mRNA expression and clinicopathological data of endometriosis patients and controls from NCBI's Gene Expression Omnibus, after a systematic search of multiple independent studies comprising 156 endometriosis patients and 118 controls to identify causative genes, risk factors, and potential diagnostic/therapeutic biomarkers. Comprehensive gene expression meta-analysis, pathway analysis, and gene ontology analysis was done using a bioinformatics-based approach. We identified 1590 unique differentially expressed genes (129 upregulated and 1461 downregulated) mapped by IPA as biologically relevant. The top upregulated genes were FOS, EGR1, ZFP36, JUNB, APOD, CST1, GPX3, and PER1, and the top downregulated ones were DIO2, CPM, OLFM4, PALLD, BAG5, TOP2A, PKP4, CDC20B, and SNTN. The most perturbed canonical pathways were mitotic roles of Polo-like kinase, role of Checkpoint kinase proteins in cell cycle checkpoint control, and ATM signaling. Protein-protein interaction analysis showed a strong network association among FOS, EGR1, ZFP36, and JUNB. These findings provide a thorough understanding of the molecular mechanism of endometriosis, identified biomarkers, and represent a step towards the future development of novel diagnostic and therapeutic options.
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PMID:Uncovering Potential Roles of Differentially Expressed Genes, Upstream Regulators, and Canonical Pathways in Endometriosis Using an In Silico Genomics Approach. 3257 62