ArticleScientific reports2023
Identification of the ageing-related prognostic gene signature, and the associated regulation axis in skin cutaneous melanoma.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 3 citations in OpenAlex.
- Exploration in association between vitamin D and cutaneous melanoma and explainable machine learning prediction.Frontiers in oncology · 2025Article
- A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma.Briefings in bioinformatics · 2024Article
- Construction of a tumor mutational burden-derived LncRNA prognostic computational framework associated with therapy sensitivity in skin cutaneous melanoma.Journal of translational medicine · 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
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Skin cutaneous melanoma (SKCM) has substantial malignancy and a poor prognosis. The function of ageing-related genes (ARGs) in SKCM is unknown. In this study, a prognostic risk-scoring model for ARG was constructed based on SKCM RNA-seq, mutation, and clinical data in The Cancer Genome Atlas. Our novel prognostic model, which included four ARGs (IRS2, PDGFRA, TFAP2A, and SOD2), could distinguish between low-risk and high-risk groups. Low-risk patients benefited more from immunotherapy and commonly used targeted and chemotherapy drugs than high-risk patients. There were also considerable differences in immunocyte infiltration and tumour microenvironment between the two groups. Furthermore, multivariate Cox regression analysis revealed that age, pT_stage, pM_stage, body mass index, tumour mutation burden, and risk score were independent factors influencing the prognosis of patients with SKCM; therefore, we devised a prognosis nomogram. Last, a long non-coding (lncRNA) NEAT1/miR-33a-5p/IRS2 regulatory axis of the competing endogenous RNA network was built to investigate the mechanisms of SKCM metastasis progression. Grouping based on the scoring system could predict the prognosis of SKCM and predict the sensitivity of patients to immunotherapy, targeted therapy, and chemotherapy. This could facilitate the formulation of individualised treatment strategies and help drug research and development. These findings highlight the regulatory axis of the lncRNA NEAT1/miR-33a-5p/IRS2, which may play a role in SKCM metastasis.
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.