Gene expression profiling of 1200 pancreatic ductal adenocarcinoma reveals novel subtypes

• Published in: BMC cancer Vol. 18; no. 1; pp. 603 - 13
• Main Authors: Zhao, Lan, Zhao, Hongya, Yan, Hong
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 29.05.2018; BioMed Central; BMC
• Subjects: Adenocarcinoma; Aged; Algorithms; Biclustering; Bioinformatics; Biological markers; Biomarkers; Biomarkers, Tumor - genetics; Breast cancer; Cancer therapies; Cancer treatment; Carbohydrate metabolism; Carcinoma, Pancreatic Ductal - genetics; Carcinoma, Pancreatic Ductal - mortality; Carcinoma, Pancreatic Ductal - pathology; Carcinoma, Pancreatic Ductal - therapy; Cell proliferation; Classification; Cluster Analysis; Collagen; Data Analysis; Datasets; Datasets as Topic; Deep Learning; Female; Gene expression; Gene Expression Profiling - methods; Gene Expression Regulation, Neoplastic; Gene set enrichment analysis; Genomes; Genomics; Heterogeneity; Humans; Insulin; Insulin secretion; Islet cells; Lipid metabolism; Male; Microarray Analysis; Middle Aged; Ovarian cancer; Pancreas; Pancreatic cancer; Pancreatic ductal adenocarcinoma; Pancreatic Neoplasms - genetics; Pancreatic Neoplasms - mortality; Pancreatic Neoplasms - pathology; Pancreatic Neoplasms - therapy; Patient outcomes; Precision Medicine - methods; Prognosis; Protein turnover; Retrospective Studies; Risk factors; Stroma; Studies; Subtype; Survival Analysis; Transcriptome - genetics; Tumors; Deep learning; Biomarkers; Heterogeneity; Biclustering; Subtype; Pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer related death in the world with a five-year survival rate of less than 5%. Not all PDAC are the same, because there exist intra-tumoral heterogeneity between PDAC, which poses a great challenge to personalized treatments f...