A prognostic model for anoikis-related genes in pancreatic cancer

Abstract Anoikis, a distinct form of programmed cell death, is crucial for both organismal development and maintaining tissue equilibrium. Its role extends to the proliferation and progression of cancer cells. This study aimed to establish an anoikis-related prognostic model to predict the prognosis...

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Bibliographic Details
Published inScientific reports Vol. 14; no. 1; pp. 15200 - 16
Main Authors Song, Wenbin, Hu, Haiyang, Yuan, Zhengbo, Yao, Hao
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group 02.07.2024
Nature Publishing Group UK
Nature Portfolio
Subjects
Adenocarcinoma
Anoikis
Apoptosis
Cell death
Cell proliferation
Gene expression
Genomes
Genotypes
ICGC-PACA
Medical prognosis
Metastases
Mutation
Pancreatic cancer
Patients
Prognosis
Prognostic model
Risk groups
TCGA-PAAD
Tumors
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Summary:Abstract Anoikis, a distinct form of programmed cell death, is crucial for both organismal development and maintaining tissue equilibrium. Its role extends to the proliferation and progression of cancer cells. This study aimed to establish an anoikis-related prognostic model to predict the prognosis of pancreatic cancer (PC) patients. Gene expression data and patient clinical profiles were sourced from The Cancer Genome Atlas (TCGA-PAAD: Pancreatic Adenocarcinoma) and the International Cancer Genome Consortium (ICGC-PACA: Pancreatic Ductal Adenocarcinoma). Non-cancerous pancreatic tissue gene expression data were obtained from the Genotype-Tissue Expression (GTEx) project. The R package was used to construct anoikis-related PC prognostic models, which were later validated with the ICGC-PACA database. Survival analyses demonstrated a poorer prognosis for patients in the high-risk group, consistent across both TCGA-PAAD and ICGC-PACA datasets. A nomogram was designed as a predictive tool to estimate patient mortality. The study also analyzed tumor mutations and immune infiltration across various risk groups, uncovering notable differences in tumor mutation patterns and immune landscapes between high- and low-risk groups. In conclusion, this research successfully developed a prognostic model centered on anoikis-related genes, offering a novel tool for predicting the clinical trajectory of PC patients.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-65981-7