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Cellular senescence related gene signature predicts prognosis and immune features in skin cutaneous melanoma.

Mengna Li | Xintao Cen | Yan Yan | Li Li | Wei Lai
Discover oncology | 2025

Skin cutaneous melanoma (SKCM) is the deadliest skin cancer, with rising global incidence. Cellular senescence plays an essential role in tumorigenesis, progression, and immune modulation in cancer, however, its role in SKCM prognosis and immunotherapy response remains unclear.

Pubmed ID: 41275062

Associated grants

  • Agency: the National Natural Science Foundation of China,
    Id: 82203901
  • Agency: the National Natural Science Foundation of China,
    Id: 82373497

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This is a list of tools and resources that we have found mentioned in this publication.


GTEx eQTL Browser (tool)

RRID:SCR_001618

Database and browser that provides a central resource to archive and display association between genetic variation and high-throughput molecular-level phenotypes. This effort originated with the NIH GTEx roadmap project: however the scope of this resource will be extended to include any available genotype/molecular phenotype datasets.

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Cytoscape (tool)

RRID:SCR_003032

Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

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Gene Set Enrichment Analysis (tool)

RRID:SCR_003199

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

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Gene Expression Omnibus (GEO) (tool)

RRID:SCR_005012

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

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The Cancer Immunome Database (tool)

RRID:SCR_014508

A database which provides results of comprehensive immunogenomic analyses of next generation sequencing data for 19 solid cancers from The Cancer Genome Atlas and other datasources. The database can be queried for the gene expression of specific immune-related gene sets, cellular composition of immune infiltrates (characterized using gene set enrichment analyses and deconvolution), neoantigens and cancer-germline antigens, HLA types, and tumor heterogeneity (estimated from cancer cell fractions). It also provides survival analyses for different types immunological parameters.

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Genomic Data Commons Data Portal (GDC Data Portal) (tool)

RRID:SCR_014514

A unified data repository of the National Cancer Institute (NCI)'s Genomic Data Commons (GDC) that enables data sharing across cancer genomic studies in support of precision medicine. The GDC supports several cancer genome programs at the NCI Center for Cancer Genomics (CCG), including The Cancer Genome Atlas (TCGA), Therapeutically Applicable Research to Generate Effective Treatments (TARGET), and the Cancer Genome Characterization Initiative (CGCI). The GDC Data Portal provides a platform for efficiently querying and downloading high quality and complete data. The GDC also provides a GDC Data Transfer Tool and a GDC API for programmatic access.

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UALCAN (tool)

RRID:SCR_015827

Web application and database for analyzing cancer transcriptome data. It also has applications is facilitating tumor subgroup gene expression and survival analyses.

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Gene Expression Profiling Interactive Analysis 2 (tool)

RRID:SCR_026154

Enhanced web server for large-scale expression profiling and interactive analysis. GEPIA2 is updated and enhanced version of GEPIA, offering more functionalities, higher resolution data analysis, and additional features like ability to analyze specific cancer subtypes, quantify gene signatures based on single-cell sequencing studies, and allow users to upload their own RNA-seq data for comparison with the TCGA and GTEx datasets; essentially providing more comprehensive and advanced platform for gene expression analysis compared to the original GEPIA version.

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