Gene signature for prognosis in comparison of pancreatic cancer patients with diabetes and non-diabetes

Author:

Yang Mingjun1,Song Boni12,Liu Juxiang3,Bing Zhitong24,Wang Yonggang1,Yu Linmiao1

Affiliation:

1. School of Life Science and Engineering, Lanzhou University of Technology, Lanzhou, Gansu, China

2. Institute of Modern Physics of Chinese Academy of Sciences, Lanzhou, China

3. Gansu Key Laboratory of Endocrine and metabolism, Department of Endocrinology, Gansu Provincial People’s Hospital, Lanzhou, Gansu, China

4. Evidence Based Medicine Center, School of Basic Medical Science of Lanzhou University,, Lanzhou, China

Abstract

Background Pancreatic cancer (PC) has much weaker prognosis, which can be divided into diabetes and non-diabetes. PC patients with diabetes mellitus will have more opportunities for physical examination due to diabetes, while pancreatic cancer patients without diabetes tend to have higher risk. Identification of prognostic markers for diabetic and non-diabetic pancreatic cancer can improve the prognosis of patients with both types of pancreatic cancer. Methods Both types of PC patients perform differently at the clinical and molecular levels. The Cancer Genome Atlas (TCGA) is employed in this study. The gene expression of the PC with diabetes and non-diabetes is used for predicting their prognosis by LASSO (Least Absolute Shrinkage and Selection Operator) Cox regression. Furthermore, the results are validated by exchanging gene biomarker with each other and verified by the independent Gene Expression Omnibus (GEO) and the International Cancer Genome Consortium (ICGC). The prognostic index (PI) is generated by a combination of genetic biomarkers that are used to rank the patient’s risk ratio. Survival analysis is applied to test significant difference between high-risk group and low-risk group. Results An integrated gene prognostic biomarker consisted by 14 low-risk genes and six high-risk genes in PC with non-diabetes. Meanwhile, and another integrated gene prognostic biomarker consisted by five low-risk genes and three high-risk genes in PC with diabetes. Therefore, the prognostic value of gene biomarker in PC with non-diabetes and diabetes are all greater than clinical traits (HR = 1.102, P-value < 0.0001; HR = 1.212, P-value < 0.0001). Gene signature in PC with non-diabetes was validated in two independent datasets. Conclusions The conclusion of this study indicated that the prognostic value of genetic biomarkers in PCs with non-diabetes and diabetes. The gene signature was validated in two independent databases. Therefore, this study is expected to provide a novel gene biomarker for predicting prognosis of PC with non-diabetes and diabetes and improving clinical decision.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Gansu Province, China

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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