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PAC-5 Gene Expression Signature for Predicting Prognosis of Patients with Pancreatic Adenocarcinoma.
Kim, Jieun; Jo, Yong Hwa; Jang, Miran; Nguyen, Ngoc Ngo Yen; Yun, Hyeong Rok; Ko, Seok Hoon; Shin, Yoonhwa; Lee, Ju-Seog; Kang, Insug; Ha, Joohun; Choi, Tae Gyu; Kim, Sung Soo.
Afiliação
  • Kim J; Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Korea.
  • Jo YH; Biomedical Science Institute, Kyung Hee University, Seoul 02447, Korea.
  • Jang M; Biomedical Science Institute, Kyung Hee University, Seoul 02447, Korea.
  • Nguyen NNY; Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Korea.
  • Yun HR; Biomedical Science Institute, Kyung Hee University, Seoul 02447, Korea.
  • Ko SH; Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Korea.
  • Shin Y; Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Korea.
  • Lee JS; Biomedical Science Institute, Kyung Hee University, Seoul 02447, Korea.
  • Kang I; Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Korea.
  • Ha J; Biomedical Science Institute, Kyung Hee University, Seoul 02447, Korea.
  • Choi TG; Department of Emergency Medicine, School of Medicine, Kyung Hee University, Seoul 02447, Korea.
  • Kim SS; Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Korea.
Cancers (Basel) ; 11(11)2019 Nov 07.
Article em En | MEDLINE | ID: mdl-31703415
ABSTRACT
Pancreatic adenocarcinoma (PAC) is one of the most aggressive malignancies. Intratumoural molecular heterogeneity impedes improvement of the overall survival rate. Current pathological staging system is not sufficient to accurately predict prognostic outcomes. Thus, accurate prognostic model for patient survival and treatment decision is demanded. Using differentially expressed gene analysis between normal pancreas and PAC tissues, the cancer-specific genes were identified. A prognostic gene expression model was computed by LASSO regression analysis. The PAC-5 signature (LAMA3, E2F7, IFI44, SLC12A2, and LRIG1) that had significant prognostic value in the overall dataset was established, independently of the pathological stage. We provided evidence that the PAC-5 signature further refined the selection of the PAC patients who might benefit from postoperative therapies. SLC12A2 and LRIG1 interacted with the proteins that were implicated in resistance of EGFR kinase inhibitor. DNA methylation was significantly involved in the gene regulations of the PAC-5 signature. The PAC-5 signature provides new possibilities for improving the personalised therapeutic strategies. We suggest that the PAC-5 genes might be potential drug targets for PAC.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2019 Tipo de documento: Article