{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Xu D"],"funding":["Innovative research project for Graduate students in Hainan Province","Major Science and Technology Program of Hainan Province","National Natural Science Foundation of China"],"pagination":["1205"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11656765"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["25(1)"],"pubmed_abstract":["Background
Aging and tumorigenesis share intricate regulatory processes, that alter the genome, epigenome, transcriptome and immune landscape of tissues. Discovering the link between aging and cancer in terms of multiomics characteristics remains a challenge for biomedical researchers.Methods
We collected high-throughput datasets for 57 human tumors and 20 normal tissues, including 23,125 samples with age information. On the basis of these sufficient omics data, we introduced six useful modules including genomic (somatic mutation and copy number variation), gene expression, DNA methylation, hallmarks (aging and cancer), immune landscape (immune infiltration, immune pathways, immune signatures, and antitumor immune activities) and survival analysis. Correlation and different"],"journal":["BMC genomics"],"pubmed_title":["Aging2Cancer: an integrated resource for linking aging to tumor multi-omics data."],"pmcid":["PMC11656765"],"funding_grant_id":["ZDKJ2021040","Qhys2023-489, Qhys2023-447, HYYB2023A36, HYYB2023A06","32160152, 32460161"],"pubmed_authors":["Tian G","Wang B","Jiang H","Xu D","Cai J","Zhang N","Li P","Li K","Deng G","Xu J","Wei Q","Shen Y","Zheng D"],"additional_accession":[]},"is_claimable":false,"name":"Aging2Cancer: an integrated resource for linking aging to tumor multi-omics data.","description":"Background
Aging and tumorigenesis share intricate regulatory processes, that alter the genome, epigenome, transcriptome and immune landscape of tissues. Discovering the link between aging and cancer in terms of multiomics characteristics remains a challenge for biomedical researchers.Methods
We collected high-throughput datasets for 57 human tumors and 20 normal tissues, including 23,125 samples with age information. On the basis of these sufficient omics data, we introduced six useful modules including genomic (somatic mutation and copy number variation), gene expression, DNA methylation, hallmarks (aging and cancer), immune landscape (immune infiltration, immune pathways, immune signatures, and antitumor immune activities) and survival analysis. Correlation and different","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Dec","modification":"2025-04-04T21:45:08.481Z","creation":"2025-04-04T21:45:08.481Z"},"accession":"S-EPMC11656765","cross_references":{"pubmed":["39695922"],"doi":["10.1186/s12864-024-11150-z"]}}