Literature DB >> 33879792

An integrative analysis of the age-associated multi-omic landscape across cancers.

Kasit Chatsirisupachai1, Tom Lesluyes2, Luminita Paraoan3, Peter Van Loo2, João Pedro de Magalhães4.   

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 alterations (SCNAs) and somatic mutations. Age-associated SCNAs and mutations are identified in several cancer-driver genes across different cancer types. The largest age-related genomic differences are found in gliomas and endometrial cancer. We identify age-related global transcriptomic changes and demonstrate that these genes are in part regulated by age-associated DNA methylation changes. This study provides a comprehensive, multi-omics view of age-associated alterations in cancer and underscores age as an important factor to consider in cancer research and clinical practice.

Entities:  

Year:  2021        PMID: 33879792     DOI: 10.1038/s41467-021-22560-y

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  59 in total

1.  Comprehensive Characterization of Molecular Differences in Cancer between Male and Female Patients.

Authors:  Yuan Yuan; Lingxiang Liu; Hu Chen; Yumeng Wang; Yanxun Xu; Huzhang Mao; Jun Li; Gordon B Mills; Yongqian Shu; Liang Li; Han Liang
Journal:  Cancer Cell       Date:  2016-05-09       Impact factor: 31.743

2.  The clonal evolution of tumor cell populations.

Authors:  P C Nowell
Journal:  Science       Date:  1976-10-01       Impact factor: 47.728

3.  Sex Differences in Cancer Driver Genes and Biomarkers.

Authors:  Constance H Li; Syed Haider; Yu-Jia Shiah; Kevin Thai; Paul C Boutros
Journal:  Cancer Res       Date:  2018-10-01       Impact factor: 12.701

Review 4.  How ageing processes influence cancer.

Authors:  João Pedro de Magalhães
Journal:  Nat Rev Cancer       Date:  2013-05       Impact factor: 60.716

5.  Half or more of the somatic mutations in cancers of self-renewing tissues originate prior to tumor initiation.

Authors:  Cristian Tomasetti; Bert Vogelstein; Giovanni Parmigiani
Journal:  Proc Natl Acad Sci U S A       Date:  2013-01-23       Impact factor: 11.205

Review 6.  How the ageing microenvironment influences tumour progression.

Authors:  Mitchell Fane; Ashani T Weeraratna
Journal:  Nat Rev Cancer       Date:  2019-12-13       Impact factor: 60.716

7.  A human tissue-specific transcriptomic analysis reveals a complex relationship between aging, cancer, and cellular senescence.

Authors:  Kasit Chatsirisupachai; Daniel Palmer; Susana Ferreira; João Pedro de Magalhães
Journal:  Aging Cell       Date:  2019-09-27       Impact factor: 9.304

8.  Clock-like mutational processes in human somatic cells.

Authors:  Ludmil B Alexandrov; Philip H Jones; David C Wedge; Julian E Sale; Peter J Campbell; Serena Nik-Zainal; Michael R Stratton
Journal:  Nat Genet       Date:  2015-11-09       Impact factor: 38.330

9.  Age-related somatic mutations in the cancer genome.

Authors:  Brandon Milholland; Adam Auton; Yousin Suh; Jan Vijg
Journal:  Oncotarget       Date:  2015-09-22

Review 10.  Cancer as a disease of old age: changing mutational and microenvironmental landscapes.

Authors:  Ezio Laconi; Fabio Marongiu; James DeGregori
Journal:  Br J Cancer       Date:  2020-02-11       Impact factor: 7.640

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  9 in total

Review 1.  Sex Differences in Cancer Genomes: Much Learned, More Unknown.

Authors:  Chenghao Zhu; Paul C Boutros
Journal:  Endocrinology       Date:  2021-11-01       Impact factor: 5.051

Review 2.  Making sense of the ageing methylome.

Authors:  Kirsten Seale; Steve Horvath; Andrew Teschendorff; Nir Eynon; Sarah Voisin
Journal:  Nat Rev Genet       Date:  2022-05-02       Impact factor: 59.581

3.  Geographic encoding of transcripts enabled high-accuracy and isoform-aware deep learning of RNA methylation.

Authors:  Daiyun Huang; Kunqi Chen; Bowen Song; Zhen Wei; Jionglong Su; Frans Coenen; João Pedro de Magalhães; Daniel J Rigden; Jia Meng
Journal:  Nucleic Acids Res       Date:  2022-10-14       Impact factor: 19.160

4.  S-phase fraction, lymph node status and disease staging as the main prognostic factors to differentiate between young and older patients with invasive breast carcinoma.

Authors:  António E Pinto; João Matos; Teresa Pereira; Giovani L Silva; Saudade André
Journal:  Oncol Lett       Date:  2022-08-04       Impact factor: 3.111

5.  Age influences on the molecular presentation of tumours.

Authors:  Constance H Li; Syed Haider; Paul C Boutros
Journal:  Nat Commun       Date:  2022-01-11       Impact factor: 17.694

6.  Evaluating the impact of age on immune checkpoint therapy biomarkers.

Authors:  Rossin Erbe; Zheyu Wang; Sharon Wu; Joanne Xiu; Neeha Zaidi; Jennifer La; David Tuck; Nathanael Fillmore; Nicolas A Giraldo; Michael Topper; Stephen Baylin; Marc Lippman; Claudine Isaacs; Reva Basho; Ilya Serebriiskii; Heinz-Josef Lenz; Igor Astsaturov; John Marshall; Josephine Taverna; Jerry Lee; Elizabeth M Jaffee; Evanthia T Roussos Torres; Ashani Weeraratna; Hariharan Easwaran; Elana J Fertig
Journal:  Cell Rep       Date:  2021-08-24       Impact factor: 9.423

7.  Positive Selection and Enhancer Evolution Shaped Lifespan and Body Mass in Great Apes.

Authors:  Daniela Tejada-Martinez; Roberto A Avelar; Inês Lopes; Bruce Zhang; Guy Novoa; João Pedro de Magalhães; Marco Trizzino
Journal:  Mol Biol Evol       Date:  2022-02-03       Impact factor: 16.240

Review 8.  Transcriptional Heterogeneity of Cellular Senescence in Cancer.

Authors:  Muhammad Junaid; Aejin Lee; Jaehyung Kim; Tae Jun Park; Su Bin Lim
Journal:  Mol Cells       Date:  2022-08-19       Impact factor: 4.250

9.  TP73-AS1 is induced by YY1 during TMZ treatment and highly expressed in the aging brain.

Authors:  Gal Mazor; Dmitri Smirnov; Hila Ben David; Ekaterina Khrameeva; Debra Toiber; Barak Rotblat
Journal:  Aging (Albany NY)       Date:  2021-06-11       Impact factor: 5.682

  9 in total

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