Pathology Features in Bethesda Guidelines Predict Colorectal Cancer Microsatellite Instability: A Population-Based Study

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Organisation, information et performance

Comment comprendre les évolutions actuelles des entreprises et les modifications en cours qui les accompagnent en matière de logistique, de systèmes d’information et de pilotage de la performance ? Une quarantaine d’auteurs – pour la plupart enseignants-chercheurs à l’université de Nantes ou à l’École des Mines de Nantes – ont tenté de répondre à cette question par le biais de dix-huit contributions organisées en cinq parties : les métamorphoses de la chaîne de valeur intra et inter organisationnelle, au niveau des flux physiques et d’information ; les outils et méthodes d’évaluation de la performance économique et de la responsabilité globale ; les impacts des normes et des nouvelles technologies sur la gestion des entreprises et sur le comportement des managers ; une analyse des opérations, des relations et des situations de gestion dans plusieurs secteurs ; la finalisation financière et sociétale de la gestion des entreprises au regard des enjeux contemporains de gouvernance et durabilité des entreprises

Pathology features in Bethesda guidelines predict colorectal cancer microsatellite instability: A population-based study

Copyright © 2007 AGA Institute Published by Elsevier Inc.Background & Aims: The revised Bethesda guidelines for Lynch syndrome recommend microsatellite instability (MSI) testing all colorectal cancers in patients diagnosed before age 50 years and colorectal cancers diagnosed in patients between ages 50 and 59 years with particular pathology features. Our aim was to identify pathology and other features that independently predict high MSI (MSI-H). Methods: Archival tissue from 1098 population-based colorectal cancers diagnosed before age 60 years was tested for MSI. Pathology features, site, and age at diagnosis were obtained. Multiple logistic regression was performed to determine the predictive value of each feature, as measured by an odds ratio (OR), from which a scoring system (MsPath) was developed to estimate the probability a colorectal cancer is MSI-H. Results: Fifteen percent of tumors (162) were MSI-H. Independent predictors were tumor-infiltrating lymphocytes (OR, 9.1; 95% confidence interval [CI], 5.9–14.1), proximal subsite (OR, 4.7; 95% CI, 3.1–7.3), mucinous histology (OR, 2.8; 95% CI, 1.7–4.8), poor differentiation (OR, 1.9; 95% CI, 1.2–3.1), Crohn’s-like reaction (OR, 1.9; 95% CI, 1.2–2.9), and diagnosis before age 50 years (OR, 1.9; 95% CI, 1.3–2.9). MsPath score ≥1.0 had a sensitivity of 93% and a specificity of 55% for MSI-H. Conclusions: The probability an individual colorectal cancer is MSI-H is predicted well by the MsPath score. There is little value in testing for DNA mismatch repair loss in tumors, or for germline mismatch repair mutations, for colorectal cancers diagnosed in patients before age 60 years with an MSPath score <1 (approximately 50%). Pathology can identify almost all MSI-H colorectal cancers diagnosed before age 60 years.http://www.elsevier.com/wps/find/journaldescription.cws_home/623297/description#descriptio

A Transcriptome-Wide Association Study Identifies Novel Candidate Susceptibility Genes for Pancreatic Cancer

International audienceBACKGROUND: Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. METHODS: To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples). RESULTS: We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. CONCLUSIONS: By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation. Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the