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Molecular classification of human cholangiocarcinoma

ABSTRACT: Transcriptomic profiling Background Cholangiocarcinoma accounts for 5-10% of primary hepatic cancers. The etiology is unclear and patients are often diagnosed without risk factors. Resection is the only curative treatment although patients frequently remain undiagnosed until advanced stage of disease. Methods To construct molecular classification of cholangiocarcinoma, we profiled the transcriptomes of 104 freshly-frozen tumors and 59 matched non-cancerous livers obtained from Australia, Europe and the United States. We also performed mutational analysis of KRAS, EGFR and BRAF, and used laser-capture microdissection to obtain independent gene expression profiles for epithelial and stromal compartments in a subset of tumors. The selected target genes were validated by western blotting and immunohistochemistry. Results Transcriptomic profiling classified cholangiocarcinoma into two distinct subclasses defined by survival (P<0.0007) and early recurrence (P<0.001). Applying leave-one-out cross-validation, we optimized the prognostic classifier to 238 genes which were positively enriched in the epithelial tumor compartment. A deregulated HER2 network was associated with the epithelial compartment which also showed a frequent overexpression of Ki67, EGFR, MET and pRPS6 whereas inflammatory cytokines were enriched in tumor stroma specifically in patients with poor prognosis. KRAS mutations were found in 24.6% of patients with poor disease outcome. Conclusion Our study presents new insights into pathogenesis of cholangiocarcinoma and stratification of the patients according to survival and recurrence. Identification of a subgroup of patients among the poor prognostic cohort characterized by KRAS mutations and oncogenic-addiction may provide a novel therapeutic opportunity for this treatment-refractory malignancy. Profiling of individual cholangiocarcinomas and non-cancerous matched surrounding livers using normal bile ducts as reference

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PROVIDER: S-DIXA-D-1079 | biostudies-other |

REPOSITORIES: biostudies-other

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Project description:Transcriptomic profiling Background Cholangiocarcinoma accounts for 5-10% of primary hepatic cancers. The etiology is unclear and patients are often diagnosed without risk factors. Resection is the only curative treatment although patients frequently remain undiagnosed until advanced stage of disease. Methods To construct molecular classification of cholangiocarcinoma, we profiled the transcriptomes of 104 freshly-frozen tumors and 59 matched non-cancerous livers obtained from Australia, Europe and the United States. We also performed mutational analysis of KRAS, EGFR and BRAF, and used laser-capture microdissection to obtain independent gene expression profiles for epithelial and stromal compartments in a subset of tumors. The selected target genes were validated by western blotting and immunohistochemistry. Results Transcriptomic profiling classified cholangiocarcinoma into two distinct subclasses defined by survival (P<0.0007) and early recurrence (P<0.001). Applying leave-one-out cross-validation, we optimized the prognostic classifier to 238 genes which were positively enriched in the epithelial tumor compartment. A deregulated HER2 network was associated with the epithelial compartment which also showed a frequent overexpression of Ki67, EGFR, MET and pRPS6 whereas inflammatory cytokines were enriched in tumor stroma specifically in patients with poor prognosis. KRAS mutations were found in 24.6% of patients with poor disease outcome. Conclusion Our study presents new insights into pathogenesis of cholangiocarcinoma and stratification of the patients according to survival and recurrence. Identification of a subgroup of patients among the poor prognostic cohort characterized by KRAS mutations and oncogenic-addiction may provide a novel therapeutic opportunity for this treatment-refractory malignancy. Profiling of individual cholangiocarcinomas and non-cancerous matched surrounding livers using normal bile ducts as reference

Project description:Background & aimsCholangiocarcinoma (CCA), a deadly malignancy of the bile ducts, can be classified based on its anatomical location into either intrahepatic (iCCA) or extrahepatic (eCCA), each with different pathogenesis and clinical management. There is limited understanding of the molecular landscape of eCCA and no targeted therapy with clinical efficacy has been approved. We aimed to provide a molecular classification of eCCA and identify potential targets for molecular therapies.MethodsAn integrative genomic analysis of an international multicenter cohort of 189 eCCA cases was conducted. Genomic analysis included whole-genome expression, targeted DNA-sequencing and immunohistochemistry. Molecular findings were validated in an external set of 181 biliary tract tumors from the ICGC.ResultsKRAS (36.7%), TP53 (34.7%), ARID1A (14%) and SMAD4 (10.7%) were the most prevalent mutations, with ∼25% of tumors having a putative actionable genomic alteration according to OncoKB. Transcriptome-based unsupervised clustering helped us define 4 molecular classes of eCCA. Tumors classified within the Metabolic class (19%) showed a hepatocyte-like phenotype with activation of the transcription factor HNF4A and enrichment in gene signatures related to bile acid metabolism. The Proliferation class (23%), more common in patients with distal CCA, was characterized by enrichment of MYC targets, ERBB2 mutations/amplifications and activation of mTOR signaling. The Mesenchymal class (47%) was defined by signatures of epithelial-mesenchymal transition, aberrant TGFβ signaling and poor overall survival. Finally, tumors in the Immune class (11%) had a higher lymphocyte infiltration, overexpression of PD-1/PD-L1 and molecular features associated with a better response to immune checkpoint inhibitors.ConclusionAn integrative molecular characterization identified distinct subclasses of eCCA. Genomic traits of each class provide the rationale for exploring patient stratification and novel therapeutic approaches.Lay summaryTargeted therapies have not been approved for the treatment of extrahepatic cholangiocarcinoma. We performed a multi-platform molecular characterization of this tumor in a cohort of 189 patients. These analyses revealed 4 novel transcriptome-based molecular classes of extrahepatic cholangiocarcinoma and identified ∼25% of tumors with actionable genomic alterations, which has potential prognostic and therapeutic implications.

Project description:Mesenchymal stromal cells (MSC) are widely used for the study of mesenchymal tissue repair, and increasingly adopted for cell therapy, despite the lack of consensus on the identity of these cells. In part this is due to the lack of specificity of MSC markers. Distinguishing MSC from other stromal cells such as fibroblasts is particularly difficult using standard analysis of surface proteins, and there is an urgent need for improved classification approaches. Transcriptome profiling is commonly used to describe and compare different cell types; however, efforts to identify specific markers of rare cellular subsets may be confounded by the small sample sizes of most studies. Consequently, it is difficult to derive reproducible, and therefore useful markers. We addressed the question of MSC classification with a large integrative analysis of many public MSC datasets. We derived a sparse classifier (The Rohart MSC test) that accurately distinguished MSC from non-MSC samples with >97% accuracy on an internal training set of 635 samples from 41 studies derived on 10 different microarray platforms. The classifier was validated on an external test set of 1,291 samples from 65 studies derived on 15 different platforms, with >95% accuracy. The genes that contribute to the MSC classifier formed a protein-interaction network that included known MSC markers. Further evidence of the relevance of this new MSC panel came from the high number of Mendelian disorders associated with mutations in more than 65% of the network. These result in mesenchymal defects, particularly impacting on skeletal growth and function. The Rohart MSC test is a simple in silico test that accurately discriminates MSC from fibroblasts, other adult stem/progenitor cell types or differentiated stromal cells. It has been implemented in the www.stemformatics.org resource, to assist researchers wishing to benchmark their own MSC datasets or data from the public domain. The code is available from the CRAN repository and all data used to generate the MSC test is available to download via the Gene Expression Omnibus or the Stemformatics resource.

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Molecular classification of human cholangiocarcinoma

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