Dataset Information

Genomic Landscape of Pancreatic Adenocarcinoma in Younger versus Older Patients: Does Age Matter?

ABSTRACT: PURPOSE:State-of-the-art genomic analyses of pancreatic adenocarcinoma (PDAC) have yielded insight into signaling pathways underlying carcinogenesis. PDAC is characterized by substantial genomic heterogeneity. We aimed to determine whether early-onset PDAC (EOPC; ?55 years) displays a distinctive molecular landscape from average-age onset PDAC (AOPC; ?70 years). EXPERIMENTAL DESIGN:Three distinct datasets for PDAC were analyzed. In the first, patients undergoing treatment at Memorial Sloan Kettering (MSK) were consented for MSK-IMPACT next-generation sequencing. The second cohort analyzed was The Cancer Genome Atlas (TCGA) dataset for differences in somatic mutations, gene expression, and protein expression. The third dataset was an Australian cohort of PDAC. Clinical data were correlated with genomic analyses. RESULTS:A total of 293 samples were analyzed, yielding 90 patients aged ?55 years and 203 patients aged ?70 years. Among the genes known to be associated with carcinogenesis, SMAD4 displayed higher mutation rates in younger patients. Comprehensive transcriptomic analysis of cellular pathways indicated that the TGF? pathway has increased activation, and the expression levels of phospho-GSK3 were higher in EOPC. Survival outcomes revealed no differences between age groups. CONCLUSIONS:These exploratory analyses suggest that there may be somatic gene alterations within the population of patients with early-onset PDAC that involve unique cellular pathways compared with average-onset PDAC. Former studies imply these cellular pathways may play a role in smoking-related PDAC carcinogenesis. Larger genomic datasets are warranted for future evaluation to extend these observations.

SUBMITTER: Ben-Aharon I

PROVIDER: S-EPMC6786265 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Genomic Landscape of Pancreatic Adenocarcinoma in Younger versus Older Patients: Does Age Matter?

Ben-Aharon Irit I Elkabets Moshe M Pelossof Raphael R Yu Kenneth H KH Iacubuzio-Donahue Christine A CA Leach Steven D SD Lowery Maeve A MA Goodman Karyn A KA O'Reilly Eileen M EM

Clinical cancer research : an official journal of the American Association for Cancer Research 20190107 7

<h4>Purpose</h4>State-of-the-art genomic analyses of pancreatic adenocarcinoma (PDAC) have yielded insight into signaling pathways underlying carcinogenesis. PDAC is characterized by substantial genomic heterogeneity. We aimed to determine whether early-onset PDAC (EOPC; ≤55 years) displays a distinctive molecular landscape from average-age onset PDAC (AOPC; ≥70 years).<h4>Experimental design</h4>Three distinct datasets for PDAC were analyzed. In the first, patients undergoing treatment at Memor ...[more]

PMID: 30617137

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Project description:Pancreatic Ductal Adenocarcinoma (PDAC) is an aggressive form of pancreatic cancer that typically manifests itself at an advanced stage and does not respond to most treatment modalities. The survival rate of a PDAC patient is less than 5%, with a median survival of just a couple of months. A better understanding of the molecular pathology of PDAC is needed to guide research for the development of better clinical treatment modalities for PDAC patients. Gene expression studies performed to date have identified different subtypes of PDAC with prognostic and clinical relevance. Subtypes identified to date are highly heterogeneous since pancreatic cancer is heterogeneous cancer. Tumor microenvironment and stroma constitute a major chunk of PDAC and contribute to the heterogeneity. Better subtyping methods are need of the hour for better prognosis and classification of PDAC for future personalized treatment. In this work, we have performed an integrated analysis of DNA methylation and gene expression datasets to provide better mechanistic and molecular insights into Pancreatic cancers, especially PDAC. The use of varied and diverse datasets has provided valuable insights into different cancer types and can play an integral role in revealing the complex nature of underlying biological mechanisms. We performed subtyping of TCGA-PAAD gene expression and methylation datasets into different subtypes using state-of-the-art normalization methods and unsupervised clustering methods that reveal latent hidden factors, leading to additional insights for subtyping. Differential expression and differential methylation were performed for each of the subtypes obtained from clustering. Our analysis gave a consensus of five cluster solution with relevant pathways like MAPK, MET. The five subtypes corresponded to the tumor and stromal subtypes. This analysis helps in distinguishing and identifying different subtypes based on enriched putative genes. These results help propose novel experimentally-verifiable PDAC subtyping and demonstrate that using varied data sets and integrated methods can contribute to disease prognostication and precision medicine in PDAC treatment.

Project description:PurposeHypodensity of pancreatic ductal adenocarcinoma (PDAC) during contrast-enhanced computed tomography (CECT) examination is common, but a minority of PDAC patients exhibit hyperdense images. The present study examined the clinical characteristics and protein landscape of PDAC with hyperdensity.Materials and methodsA total of 844 pathologically confirmed PDAC patients who underwent CECT before surgery were included. During the parenchymal phase of CECT, patients were assigned to the hyperdense or hypodense group based on CT values. Clinical and CT characteristics for predicting relapse-free survival (RFS) and overall survival (OS) were analyzed using the Kaplan-Meier method and Cox proportional hazards model. The expression of the tumor angiogenesis marker CD31 and stroma-related protein CTHRC1 were analyzed using immunohistochemistry (IHC) assay to evaluate differences between the two groups. Proteomics was performed to compare the possible mechanisms underlying the differential enhancement on CT scans.ResultsBased on CECT, 43 and 801 PDAC patients had hyperdense and hypodense lesions, respectively. All 43 patients presented a hyperdense lesion in the parenchymal phase. The mean CECT values of the hyperdense group were higher than the hypodense group (102.5 ± 17.4 and 53.7 ± 18.7, respectively, P < 0.001). The hyperdense group had a better prognosis than the hypodense group (median RFS, 19.97 vs. 12.34 months, P = 0.0176; median OS, 33.6 vs. 20.3 months, P = 0.047). Multivariate analysis showed that age, higher CA19-9 levels (> 300 U/ml), tumor stage, tumor differentiation, tumor CT density, and adjuvant chemotherapy were significant independent prognostic factors for OS. CD31 immunohistochemical staining showed that the hyperdense PDACs had a higher microvessel density than the hypodense group (P < 0.001). CTHRC1 expression was higher in the hypodense group (P = 0.019). Sixty-eight differentially expressed proteins were found using the tandem mass tag labeling-based quantification of the proteomes of PDAC tissue samples, and 7 proteins (POFUT1, PKP2, P0DOX4, ITPR1, HBG2, IGLC3, SAA2) were related to angiogenesis.ConclusionPatients who presented with a hyperdense mass on CECT had a higher microvessel density and better prognosis. Anti-angiogenic therapy may be suitable for these patients.

Dataset Information

Genomic Landscape of Pancreatic Adenocarcinoma in Younger versus Older Patients: Does Age Matter?

Publications

Genomic Landscape of Pancreatic Adenocarcinoma in Younger versus Older Patients: Does Age Matter?

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