2021
DOI: 10.1038/s41467-021-22560-y
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An integrative analysis of the age-associated multi-omic landscape across cancers

Abstract: Age is the most important risk factor for cancer, as cancer incidence and mortality increase with age. However, how molecular alterations in tumours differ among patients of different age remains largely unexplored. Here, using data from The Cancer Genome Atlas, we comprehensively characterise genomic, transcriptomic and epigenetic alterations in relation to patients’ age across cancer types. We show that tumours from older patients present an overall increase in genomic instability, somatic copy-number altera… Show more

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Cited by 84 publications
(83 citation statements)
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References 81 publications
(114 reference statements)
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“…High-throughput molecular data from atlas studies provide new opportunities to comprehensively characterize the immune landscape of tumors ( Thorsson et al, 2018 ) and are now sufficiently powered to evaluate aging-related changes ( Wu et al, 2019 ; Shah et al, 2020 ; Chatsirisupachai et al, 2021 ). This study leverages genomics and clinical data from 9,523 patients across 31 cancer types from The Cancer Genome Atlas (TCGA); 37,961 patients across 8 cancer types from the Genomics Evidence Neoplasia Information Exchange (GENIE); 15,557 patients with breast, colon, or head and neck cancers from Caris Life Sciences (CLS); 1,818 patients with breast cancer from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC); and genomics data from a pan-tissue reference of 948 non-cancer individuals from the Genotype-Tissue Expression (GTEx) Project (see Supplemental Data S1 for a summary of patient characteristics in each cohort) to evaluate such age-related changes in the tumor immune landscape.…”
Section: Introductionmentioning
confidence: 99%
“…High-throughput molecular data from atlas studies provide new opportunities to comprehensively characterize the immune landscape of tumors ( Thorsson et al, 2018 ) and are now sufficiently powered to evaluate aging-related changes ( Wu et al, 2019 ; Shah et al, 2020 ; Chatsirisupachai et al, 2021 ). This study leverages genomics and clinical data from 9,523 patients across 31 cancer types from The Cancer Genome Atlas (TCGA); 37,961 patients across 8 cancer types from the Genomics Evidence Neoplasia Information Exchange (GENIE); 15,557 patients with breast, colon, or head and neck cancers from Caris Life Sciences (CLS); 1,818 patients with breast cancer from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC); and genomics data from a pan-tissue reference of 948 non-cancer individuals from the Genotype-Tissue Expression (GTEx) Project (see Supplemental Data S1 for a summary of patient characteristics in each cohort) to evaluate such age-related changes in the tumor immune landscape.…”
Section: Introductionmentioning
confidence: 99%
“…Especially, accumulated studies have demonstrated that somatic variations, such as single-nucleotide variations and CNVs, could contribute to tumorigenesis ( Wang et al, 2020 ) and used to infer individual medications based on the RNA interaction network ( Zhang et al, 2018 ). Based on the notion that the instability of the genome is related to age ( Chatsirisupachai et al, 2021 ), it is crucial to investigate the relationship between the stability of the genome and the physiological mechanism of the patient. More recently, large-scale biomedical data, including multidimensional molecular profiles of tumor samples of LIHC generated by The Cancer Genome Atlas (TCGA; Tomczak et al, 2015 ) project, provide opportunities to uncover mutation-driven potential therapeutic targets and potential prognostic markers for liver cancer.…”
Section: Introductionmentioning
confidence: 99%
“…Combined with similar reports of sex- and ancestry-associated differences in cancer genomes 53 , 54 , these data reveal a set of host influences on the mutational characteristics of tumours. Indeed, a study by Chatsirisupachai et al describes corroborating evidence of age-associated differences in the genome and transcriptome, as well as age-specific differences in methylation and gene expression control 73 . Together, we find that characteristics of the tumour host appears to influence all aspects of the tumour molecular profile and that some of these lead to age-specific transcriptomic and clinical impacts.…”
Section: Discussionmentioning
confidence: 80%