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Deciphering the molecular crosstalk between type 2 diabetes and pancreatic cancer through cross-disease co-expression network analysis.

2/5 보강
Biochemistry and biophysics reports 📖 저널 OA 100% 2024: 4/4 OA 2025: 41/41 OA 2026: 37/37 OA 2024~2026 2026 Vol.46() p. 102562 OA Pancreatic and Hepatic Oncology Rese
Retraction 확인
출처
PubMed DOI PMC OpenAlex 마지막 보강 2026-04-28

PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문
P · Population 대상 환자/모집단
환자: pancreatic ductal adenocarcinoma (PDAC), PDAC patients with diabetes (DP), patients with diabetes mellitus (DM), and healthy controls were analyzed
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
Similarly, expression was significantly elevated in the DP group compared with the DM group (p < 0.01) and healthy controls (p < 0.0001). The survival analysis also suggests that high expression is a favorable prognostic biomarker.
OpenAlex 토픽 · Pancreatic and Hepatic Oncology Research Ferroptosis and cancer prognosis Bioinformatics and Genomic Networks

Dehghanian F, Khalilian S, Mousavian Z, Alavi S, Bahreini A

📝 환자 설명용 한 줄

Multiple complex mechanisms link type 2 diabetes mellitus (T2DM) with the pathogenesis, development, and progression of pancreatic cancer (PC).

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • p-value p < 0.01
  • p-value p < 0.0001

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↓ .bib ↓ .ris
APA Fariba Dehghanian, Sheyda Khalilian, et al. (2026). Deciphering the molecular crosstalk between type 2 diabetes and pancreatic cancer through cross-disease co-expression network analysis.. Biochemistry and biophysics reports, 46, 102562. https://doi.org/10.1016/j.bbrep.2026.102562
MLA Fariba Dehghanian, et al.. "Deciphering the molecular crosstalk between type 2 diabetes and pancreatic cancer through cross-disease co-expression network analysis.." Biochemistry and biophysics reports, vol. 46, 2026, pp. 102562.
PMID 41970630 ↗

Abstract

Multiple complex mechanisms link type 2 diabetes mellitus (T2DM) with the pathogenesis, development, and progression of pancreatic cancer (PC). This study aims to elucidate these complex relationships using cross-disease co-expression analysis of PC and T2DM. Transcriptomic data from peripheral blood samples of patients with pancreatic ductal adenocarcinoma (PDAC), PDAC patients with diabetes (DP), patients with diabetes mellitus (DM), and healthy controls were analyzed. Following differential expression analysis (DEA), four disease-specific gene co-expression networks were constructed using weighted gene co-expression network analysis (WGCNA). Pearson correlation analysis was then applied to identify modules significantly associated with each clinical trait. In the experimental phase, peripheral blood samples from 20 PDAC patients, 20 DP patients, 20 DM patients, and 20 healthy controls were included. The co-expression network analysis identified modules highly associated with PDAC, DP, and DM. Among the 11 overlapping genes shared between these modules, the high-confidence hub genes , , and were selected for quantitative real-time PCR (qPCR) validation. Comparative analysis of expression among the four study groups showed significantly higher expression in the PDAC group than in the DM group (p < 0.01) and healthy controls (p < 0.0001). Similarly, expression was significantly elevated in the DP group compared with the DM group (p < 0.01) and healthy controls (p < 0.0001). The survival analysis also suggests that high expression is a favorable prognostic biomarker.

🏷️ 키워드 / MeSH 📖 같은 키워드 OA만

🏷️ 같은 키워드 · 무료전문 — 이 논문 MeSH/keyword 기반

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