Literature DB >> 31070984

Meta-Analysis of 1,200 Transcriptomic Profiles Identifies a Prognostic Model for Pancreatic Ductal Adenocarcinoma.

Vandana Sandhu1,2, Knut Jorgen Labori3, Ayelet Borgida4, Ilinca Lungu5, John Bartlett5, Sara Hafezi-Bakhtiari1, Robert E Denroche5, Gun Ho Jang5, Danielle Pasternack5, Faridah Mbaabali5, Matthew Watson5, Julie Wilson5, Elin H Kure2,6, Steven Gallinger1,5, Benjamin Haibe-Kains1,5,7.   

Abstract

PURPOSE: With a dismal 8% median 5-year overall survival, pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy. Only 10% to 20% of patients are eligible for surgery, and more than 50% of these patients will die within 1 year of surgery. Building a molecular predictor of early death would enable the selection of patients with PDAC who are at high risk.
MATERIALS AND METHODS: We developed the Pancreatic Cancer Overall Survival Predictor (PCOSP), a prognostic model built from a unique set of 89 PDAC tumors in which gene expression was profiled using both microarray and sequencing platforms. We used a meta-analysis framework that was based on the binary gene pair method to create gene expression barcodes that were robust to biases arising from heterogeneous profiling platforms and batch effects. Leveraging the largest compendium of PDAC transcriptomic data sets to date, we show that PCOSP is a robust single-sample predictor of early death-1 year or less-after surgery in a subset of 823 samples with available transcriptomics and survival data.
RESULTS: The PCOSP model was strongly and significantly prognostic, with a meta-estimate of the area under the receiver operating curve of 0.70 (P = 2.6E-22) and d-index (robust hazard ratio) of 1.9 (range, 1.6 to 2.3; ( = 1.4E-04) for binary and survival predictions, respectively. The prognostic value of PCOSP was independent of clinicopathologic parameters and molecular subtypes. Over-representation analysis of the PCOSP 2,619 gene pairs-1,070 unique genes-unveiled pathways associated with Hedgehog signaling, epithelial-mesenchymal transition, and extracellular matrix signaling.
CONCLUSION: PCOSP could improve treatment decisions by identifying patients who will not benefit from standard surgery/chemotherapy but who may benefit from a more aggressive treatment approach or enrollment in a clinical trial.

Entities:  

Mesh:

Substances:

Year:  2019        PMID: 31070984     DOI: 10.1200/CCI.18.00102

Source DB:  PubMed          Journal:  JCO Clin Cancer Inform        ISSN: 2473-4276


  4 in total

1.  Transcriptomic analysis reveals high ITGB1 expression as a predictor for poor prognosis of pancreatic cancer.

Authors:  Yosuke Iwatate; Hajime Yokota; Isamu Hoshino; Fumitaka Ishige; Naoki Kuwayama; Makiko Itami; Yasukuni Mori; Satoshi Chiba; Hidehito Arimitsu; Hiroo Yanagibashi; Wataru Takayama; Takashi Uno; Jason Lin; Yuki Nakamura; Yasutoshi Tatsumi; Osamu Shimozato; Hiroki Nagase
Journal:  PLoS One       Date:  2022-06-01       Impact factor: 3.752

2.  Distinguishing Kawasaki Disease from Febrile Infectious Disease Using Gene Pair Signatures.

Authors:  Jiayong Zhong; Qingsheng Huang; Yanfei Wang; Huan Gao; Hongling Jia; Jun Fan; Huiying Liang
Journal:  Biomed Res Int       Date:  2020-04-26       Impact factor: 3.411

3.  Changes and prognostic impact of inflammatory nutritional factors during neoadjuvant chemoradiotherapy for patients with resectable and borderline resectable pancreatic cancer.

Authors:  Minoru Oshima; Keiichi Okano; Hironobu Suto; Yasuhisa Ando; Hideki Kamada; Tsutomu Masaki; Shigeo Takahashi; Toru Shibata; Yasuyuki Suzuki
Journal:  BMC Gastroenterol       Date:  2020-12-14       Impact factor: 3.067

4.  Orchestrating and sharing large multimodal data for transparent and reproducible research.

Authors:  Anthony Mammoliti; Petr Smirnov; Minoru Nakano; Zhaleh Safikhani; Christopher Eeles; Heewon Seo; Sisira Kadambat Nair; Arvind S Mer; Ian Smith; Chantal Ho; Gangesh Beri; Rebecca Kusko; Eva Lin; Yihong Yu; Scott Martin; Marc Hafner; Benjamin Haibe-Kains
Journal:  Nat Commun       Date:  2021-10-04       Impact factor: 14.919

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.