Back to Search
Start Over
Multi-Algorithm Analysis Reveals Pyroptosis-Linked Genes as Pancreatic Cancer Biomarkers.
- Source :
- Cancers; Jan2024, Vol. 16 Issue 2, p372, 17p
- Publication Year :
- 2024
-
Abstract
- Simple Summary: Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at advanced stages, resulting in limited treatment options and poor survival rates. To address this challenge, we conducted a comprehensive analysis of pyroptosis-related genes using advanced algorithms. Our study, involving 1273 PDAC cases, identified 357 pyroptosis-related genes. Notably, BHLHE40, IL18, BIRC3, and APOL1 were found to be related to unfavourable PDAC outcomes and were validated through experiments and multiple datasets. We developed a novel model and an accessible nomogram to predict PDAC prognosis. Our research enhances our understanding of PDAC and has significant implications for both research and clinical practice. Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at late stages, limiting treatment options and survival rates. Pyroptosis-related gene signatures hold promise as PDAC prognostic markers, but limited gene pools and small sample sizes hinder their utility. We aimed to enhance PDAC prognosis with a comprehensive multi-algorithm analysis. Using R, we employed natural language processing and latent Dirichlet allocation on PubMed publications to identify pyroptosis-related genes. We collected PDAC transcriptome data (n = 1273) from various databases, conducted a meta-analysis, and performed differential gene expression analysis on tumour and non-cancerous tissues. Cox and LASSO algorithms were used for survival modelling, resulting in a pyroptosis-related gene expression-based prognostic index. Laboratory and external validations were conducted. Bibliometric analysis revealed that pyroptosis publications focus on signalling pathways, disease correlation, and prognosis. We identified 357 pyroptosis-related genes, validating the significance of BHLHE40, IL18, BIRC3, and APOL1. Elevated expression of these genes strongly correlated with poor PDAC prognosis and guided treatment strategies. Our accessible nomogram model aids in PDAC prognosis and treatment decisions. We established an improved gene signature for pyroptosis-related genes, offering a novel model and nomogram for enhanced PDAC prognosis. [ABSTRACT FROM AUTHOR]
- Subjects :
- PANCREATIC tumors
SAMPLE size (Statistics)
STRATEGIC planning
POPULATION genetics
NATURAL language processing
BIBLIOMETRICS
MACHINE learning
PROGNOSIS
SURVIVAL rate
TREATMENT effectiveness
GENE expression
CELLULAR signal transduction
APOLIPOPROTEINS
GENE expression profiling
DESCRIPTIVE statistics
RESEARCH funding
TUMOR markers
ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 20726694
- Volume :
- 16
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Cancers
- Publication Type :
- Academic Journal
- Accession number :
- 175048098
- Full Text :
- https://doi.org/10.3390/cancers16020372