AI Article Synopsis
- Pyroptosis is a newly identified type of programmed cell death that plays a role in cancer development, particularly in colorectal cancer (CRC).
- Researchers focused on long non-coding RNAs (lncRNAs) associated with pyroptosis to create a new risk model for CRC patient survival using data from The Cancer Genome Atlas (TCGA) and other databases.
- The study shows that specific pyroptosis-related lncRNAs can predict treatment responses and prognosis for CRC patients, potentially aiding in targeted immunotherapy development.
Article Abstract
Pyroptosis is a newly discovered programmed cell death mechanism involved in tumorigenesis. Long non-coding RNAs (lncRNAs) have been implicated in colorectal cancer (CRC). However, the potential role of pyroptosis-related lncRNAs (PRLs) in CRC remains unelucidated. Therefore, we retrieved transcriptomic data of CRC patients from The Cancer Genome Atlas (TCGA). With the use of univariate and multivariate Cox proportional hazards regression models and the random forest algorithm, a new risk model was constructed based on eight PRLs: , and . Then, according to the Kaplan-Meier plots, the relationship of PRLs with the survival of CRC patients was explored and validated with our risk model in external datasets (Gene Expression Omnibus (GEO) databases; GEO17536, n = 177, and GSE161158, n = 250). To improve its clinical utility, a nomogram combining PRLs that could predict the clinical outcome of CRC patients was established. A full-spectrum immune landscape of CRC patients mediated by PRLs could be described. The PRLs were stratified into two molecular subtypes involved in immune modulators, immune infiltration of tumor immune microenvironment, and inflammatory pathways. Afterward, Tumor Immune Dysfunction and Exclusion (TIDE) and microsatellite instability (MSI) scores were analyzed. Three independent methods were applied to predict PRL-related sensitivity to chemotherapeutic drugs. Our comprehensive analysis of PRLs in CRC patients demonstrates a potential role of PRLs in predicting response to treatment and prognosis of CRC patients, which may provide a better understanding of molecular mechanisms underlying CRC pathogenesis and facilitate the development of effective immunotherapy.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748486 | PMC |
| http://dx.doi.org/10.3389/fonc.2022.983895 | DOI Listing |
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