ArticleOncology letters2025
Molecular characteristics, clinical significance and cancer‑immune interactions of pyroptosis‑related genes in colorectal cancer.
Article in Oncology letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Machine Learning Reveals the Association Between Gene Expression and Immune Infiltration in Colorectal Cancer: A Comprehensive Study From Single-Cell to Survival Analysis.Journal of cellular and molecular medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) is a malignant tumor with poor prognosis. Pyroptosis is a newly discovered type of programmed cell death that is typically accompanied by a strong inflammatory response. Accumulating evidence suggests that pyroptosis-related genes (PRGs) may have important roles in the development of malignant tumors. However, the association between PRG expression and clinical outcomes in CRC remain unclear. In the present study, the genetic variations and transcriptional patterns of 52 PRGs were comprehensively analyzed using cohorts from The Cancer Genome Atlas and Gene Expression Omnibus and the mRNA expression levels of 7 PRGs in collected CRC samples were validated using reverse transcription-quantitative PCR. Using LASSO-Cox analysis, a PRG score was then generated and the relationship between the PRG score and prognosis, immune cell infiltration and drug sensitivity in CRC was uncovered. In the present study, the mutation and expression patterns of PRGs were analyzed and it was found that these genes were differentially expressed in CRC tissues compared with normal tissues. Based on the expression patterns of the PRGs, patients with CRC were divided into two subtypes (cluster A and B), of which cluster B had an improved prognosis and a higher abundance of immune cells. Next, differentially expressed genes between clusters A and B were identified and a PRG risk score closely related to the prognosis of CRC was constructed. Then, a nomogram for evaluating the overall survival of patients was constructed. Furthermore, a low PRG risk score was characterized by immune activation and closely related to the microsatellite instability-high pattern. Additionally, the PRG risk score was notably correlated with drug sensitivity. In conclusion, the mutation and expression characteristics of PRGs in CRC were comprehensively analyzed and a prognostic PRG signature was constructed in the present study. This signature may predict immune cell infiltration and therapeutic response in CRC, providing new insights into the prognosis and treatment of CRC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.