ArticleJournal of cellular and molecular medicine2025
Identification and Validation of a Prognostic Model Based on Tumour Necrosis Factor-Related mRNAs for Kidney Renal Clear Cell Carcinoma.
Article in Journal of cellular and molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Synergistic Profiling of Programmed Cell Death and Immune Responses Identifies a Novel Prognostic Index for Cervical Cancer.ACS omega · 2026Article
- Identification and Validation of a Prognostic Model Based on Tumour Necrosis Factor-Related mRNAs for Kidney Renal Clear Cell Carcinoma.Journal of cellular and molecular medicine · 2025Article
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
Abstract
Tumour necrosis factor (TNF) plays a critical role in tumour progression, but the specific involvement of mRNA in this process, particularly in kidney renal clear cell carcinoma (KIRC) remains insufficiently understood. Our study aims to develop a TNF-related mRNA (TRmRNA) model to predict prognosis and inform treatment strategies in KIRC. KIRC expression data from The Cancer Genome Atlas (TCGA) and TNF-related genes (TRGs) from the Genecards database were used to construct and validate a TRmRNA prognostic model. A nomogram integrating clinical features with the risk model was also developed to enhance prognostic accuracy. Enrichment analysis, drug sensitivity analysis and RT-qPCR validation were performed to further explore the biological mechanisms and clinical applicability of the model. A prognostic signature consisting of nine TRmRNAs was identified. Kaplan-Meier analysis showed that the high-risk (HRK) group had significantly shorter overall survival (OS) compared to the low-risk (LRG) group (p < 0.001). The nomogram, incorporating the risk model, yielded an area under the curve (AUC) of 0.766, indicating robust prognostic accuracy. Enrichment analysis identified solute sodium symporter and proximal tubule transport pathways enriched in the LRG group, whereas the HRK group exhibited enrichment in CD22-mediated BCR regulation and immunoglobulin complex pathways. The HRK group also showed a higher tumour mutational burden (TMB), correlating with a poorer prognosis. RT-qPCR confirmed the differential expression of mRNAs in KIRC cells. The TRmRNA-based prognostic model holds significant promise for predicting patient outcomes and guiding personalised treatment strategies in KIRC.
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.