ArticleImmunity, inflammation and disease2024
Exploring the prognostic significance of immunogenic cell death-related genes as risk biomarkers in cervical cancer.
Article in Immunity, inflammation and disease, 2024. 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.
- Exploring the prognostic significance of immunogenic cell death-related genes as risk biomarkers in cervical cancer.Immunity, inflammation and disease · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundImmunogenic cell death (ICD) is a process in which dying cells stimulate an immune response. It is a regulated form of cell death that can remodel the tumor microenvironment (TME) and activate the immune system, making immunotherapy more effective. This work was designed to identify prognostic gene features associated with ICD in cervical cancer (CC).
methodsBased on CC datasets and a set of ICD-related genes obtained from public databases, we first filtered out ICD-related genes unrelated to CC survival using univariate analysis. Subsequently, LASSO regression and multivariate Cox regression analysis were employed to develop prognostic feature genes based on ICD. For the construction and validation of the model, eight genes (CXCL1, IL1B, TNF, YKT6, PDIA3, ROCK1, CXCR3, and CLEC9A) were chosen. A nomogram was created to forecast the prognosis of CC individuals, and Kaplan-Meier curves were utilized to explore the survival disparities among different risk groups of CC individuals.
resultsssGSEA analysis was employed to investigate immune differences between two risk groups, revealing that the low-risk group exhibited elevated levels of immune cell infiltration, enhanced activation of immune function, and a higher immunophenoscore compared with the other group, which highlighted the relevance of ICD to TME.
conclusionWe constructed a prognostic model based on genetic biomarkers of ICD for prognostic prediction of CC patients. Our model demonstrated excellent discriminative and calibration capabilities, providing a valuable tool for prognostic prediction and assessing the potential efficacy of immunotherapy in CC.
Indexed as
Identifiers
What Socratic 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 Socratic graph.