Identification of the Shared Gene Signatures and Biological Mechanism in Type 2 Diabetes and Pancreatic Cancer

Yifang Hu; Ni Zeng; Yaoqi Ge; Dan Wang; Xiaoxuan Qin; Wensong Zhang; Feng Jiang; Yun Liu

doi:10.3389/fendo.2022.847760

Identification of the Shared Gene Signatures and Biological Mechanism in Type 2 Diabetes and Pancreatic Cancer

Front Endocrinol (Lausanne). 2022 Mar 31:13:847760. doi: 10.3389/fendo.2022.847760. eCollection 2022.

Authors

Yifang Hu¹, Ni Zeng², Yaoqi Ge¹, Dan Wang¹, Xiaoxuan Qin³, Wensong Zhang⁴, Feng Jiang⁵, Yun Liu^{1

6}

Affiliations

¹ Department of Geriatric Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
² Department of Dermatology, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
³ Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
⁴ Department of Pharmacy, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
⁵ Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China.
⁶ Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China.

Abstract

Background: The relationship between pancreatic cancer (PC) and type 2 diabetes mellitus (T2DM) has long been widely recognized, but the interaction mechanisms are still unknown. This study was aimed to investigate the shared gene signatures and molecular processes between PC and T2DM.

Methods: The Gene Expression Omnibus (GEO) database was used to retrieve the RNA sequence and patient information of PC and T2DM. Weighted gene co-expression network analysis (WGCNA) was performed to discover a co-expression network associated with PC and T2DM. Enrichment analysis of shared genes present in PC and T2DM was performed by ClueGO software. These results were validated in the other four cohorts based on differential gene analysis. The predictive significance of S100A6 in PC was evaluated using univariate and multivariate Cox analyses, as well as Kaplan-Meier plots. The biological process of S100A6 enrichment in PC was detected using Gene Set Enrichment Analysis (GSEA). The involvement of S100A6 in the tumor immune microenvironment (TIME) was assessed by CIBERSORT. In vitro assays were used to further confirm the function of S100A6 in PC.

Results: WGCNA recognized three major modules for T2DM and two major modules for PC. There were 44 shared genes identified for PC and T2DM, and Gene Ontology (GO) analysis showed that regulation of endodermal cell fate specification was primarily enriched. In addition, a key shared gene S100A6 was derived in the validation tests. S100A6 was shown to be highly expressed in PC compared to non-tumor tissues. PC patients with high S100A6 expression had worse overall survival (OS) than those with low expression. GSEA revealed that S100A6 is involved in cancer-related pathways and glycometabolism-related pathways. There is a strong relationship between S100A6 and TIME. In vitro functional assays showed that S100A6 helped to induce the PC cells' proliferation and migration. We also proposed a diagram of common mechanisms of PC and T2DM.

Conclusions: This study firstly revealed that the regulation of endodermal cell fate specification may be common pathogenesis of PC and T2DM and identified S100A6 as a possible biomarker and therapeutic target for PC and T2DM patients.

Keywords: S100A6; WGCNA; endodermal cell fate specification; pancreatic cancer; type 2 diabetes.

MeSH terms

Diabetes Mellitus, Type 2* / complications
Diabetes Mellitus, Type 2* / genetics
Gene Ontology
Gene Regulatory Networks
Humans
Pancreatic Neoplasms* / complications
Pancreatic Neoplasms* / genetics
Tumor Microenvironment / genetics