Identification of the Novel Pyroptosis-Related Gene Signature in Patients with Esophageal Adenocarcinoma
Zeng, R.; Huang, S.; Zhuo, Z.; Wu, H.; Sha, W.; Chen, H.
Show abstract
Esophageal adenocarcinoma (EAC) is a highly malignant type of digestive tract cancers with a poor prognosis despite therapeutic advances. Pyroptosis is an inflammatory form of programmed cell death, whereas the role of pyroptosis in EAC remains largely unknown. Herein, we identified a pyroptosis-related five-gene signature that was significantly correlated with the survival of EAC patients in The Cancer Genome Atlas (TCGA) cohort and an independent validation dataset. In addition, a nomogram based on the five-gene signature was constructed with novel prognostic values. Moreover, the genes in the pyroptosis-related signature, CASP1, GSDMB, IL1B, PYCARD, and ZBP1, might be involved in immune response and regulation of the tumor microenvironment. Our findings indicate that the five-gene signature provides insights into the involvement of pyroptosis in EAC progression, and is promising in the risk assessment as well as prognosis for EAC patients in clinical practice.
Matching journals
The top 14 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Deeper insights into long-term survival heterogeneity of Pancreatic Ductal Adenocarcinoma (PDAC) patients using integrative individual- and group-level transcriptome network analyses 95%
- Immune Classification of Clear Cell Renal Cell Carcinoma 95%
- Novel cancer subtyping method based on patient-specific gene regulatory network 94%
Similar papers in this journal
- Tumor Purity-Related Genes for Predicting the Prognosis and Drug Sensitivity of DLBCL Patients 96%
- Single-cell Sequencing Highlights Heterogeneity and Malignant Progression in Actinic Keratosis and Cutaneous Squamous Cell Carcinoma 96%
- Mapping of single-cell landscape of acral melanoma and analysis of molecular regulatory network of tumor microenvironment 95%
Similar papers in this journal
- Finding new cancer epigenetic and genetic biomarkers from cell-free DNA by combining SALP-seq and machine learning:esophageal cancer as an example 97%
- Mime: A flexible machine-learning framework to construct and visualize models for clinical characteristics prediction and feature selection 94%
- Mechanistic insights into zearalenone-accelerated colorectal cancer in mice using integrative multi-omics approaches 92%
Similar papers in this journal
- Establishment of a prognosis prediction model based on pyroptosis-related signatures associated with the immune microenvironment and molecular heterogeneity in clear cell renal carcinoma 98%
- Pyroptosis-related gene signatures can robustly diagnose skin cutaneous melanoma and predict the prognosis 97%
- BNIP3 upregulation characterizes cancer cell subpopulation with increased fitness and proliferation 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.