ArticleApoptosis : an international journal on programmed cell death2024
Exploring a specialized programmed-cell death patterns to predict the prognosis and sensitivity of immunotherapy in cutaneous melanoma via machine learning.
Article in Apoptosis : an international journal on programmed cell death, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 18 citations in OpenAlex.
- Uncovering the Targets of Pueraria Associated with Programmed Cell Death and the Construction of a Diagnostic Model in Septic Cardiomyopathy.Biomedicines · 2026Article
- Deciphering programmed cell death for gastric cancer prognosis: AKR1B1 as a key player.Journal of applied genetics · 2026Article
- Multiple programmed cell death patterns predict the prognosis and therapeutic sensitivity in head and neck squamous cell carcinoma.Discover oncology · 2026Article
- c-MAF Transcriptionally Activates Slc40a1 to Repress Ferroptosis in Sepsis-Associated Encephalopathy.CNS neuroscience & therapeutics · 2026Article
- Association of programmed cell death with atrial fibrillation risk: A multi-omics Mendelian randomization study.Medicine · 2026Article
- Harnessing machine learning-driven multiomics integration: deciphering programmed cell death networks for prognostication and immunotherapy prediction in lung adenocarcinoma.Cell biology and toxicology · 2026Article
- [Machine learning-based programmed cell death signature model for precise prediction of prognosis and treatment response in melanoma].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025Article
- Identification of prognostic biomarkers in colorectal cancer through multi-omics profiling of programmed cell death pathways.Journal of gastrointestinal oncology · 2025Article
- Article
- Identification of clusters related to programmed cell death and potential prognostic biomarkers for immunotherapy response in endometrial cancer.Scientific reports · 2025Article
- Development of a machine learning-derived programmed cell death index for prognostic prediction and immune insights in colorectal cancer.Discover oncology · 2025Article
- Linking Parkinson's disease and melanoma: the impact of copper-driven cuproptosis and related mechanisms.NPJ Parkinson's disease · 2025Article
- Article
- Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma.Scientific reports · 2025Article
- Machine learning-driven SLC prognostic signature for glioma: predicting survival and immunotherapy response.Frontiers in pharmacology · 2025Article
- Integration of machine learning and experimental validation to identify the prognostic signature related to diverse programmed cell deaths in breast cancer.Frontiers in oncology · 2024Article
- Exploring the impact of deubiquitination on melanoma prognosis through single-cell RNA sequencing.Frontiers in genetics · 2024Article
- Machine learning-driven transcriptomic and single-cell profiling of programed cell death patterns in colon cancer.Science progressArticle
Corrections and comments
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Authors and funding
12 authors at 6 institutions in 2 countries.
Funding
Abstract
The mortality and therapeutic failure in cutaneous melanoma (CM) are mainly caused by wide metastasis and chemotherapy resistance. Meanwhile, immunotherapy is considered a crucial therapy strategy for CM patients. However, the efficiency of currently available methods and biomarkers in predicting the response of immunotherapy and prognosis of CM is limited. Programmed cell death (PCD) plays a significant role in the occurrence, development, and therapy of various malignant tumors. In this research, we integrated fourteen types of PCD, multi-omics data from TCGA-SKCM and other cohorts in GEO, and clinical CM patients to develop our analysis. Based on significant PCD patterns, two PCD-related CM clusters with different prognosis, tumor microenvironment (TME), and response to immunotherapy were identified. Subsequently, seven PCD-related features, especially CD28, CYP1B1, JAK3, LAMP3, SFN, STAT4, and TRAF1, were utilized to establish the prognostic signature, namely cell death index (CDI). CDI accurately predicted the response to immunotherapy in both CM and other cancers. A nomogram with potential superior predictive ability was constructed, and potential drugs targeting CM patients with specific CDI have also been identified. Given all the above, a novel CDI gene signature was indicated to predict the prognosis and exploit precision therapeutic strategies of CM patients, providing unique opportunities for clinical intelligence and new management methods for the therapy of CM.
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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.