Literature DB >> 33727690

Genetic and non-genetic clonal diversity in cancer evolution.

James R M Black1,2, Nicholas McGranahan3,4.   

Abstract

The observation and analysis of intra-tumour heterogeneity (ITH), particularly in genomic studies, has advanced our understanding of the evolutionary forces that shape cancer growth and development. However, only a subset of the variation observed in a single tumour will have an impact on cancer evolution, highlighting the need to distinguish between functional and non-functional ITH. Emerging studies highlight a role for the cancer epigenome, transcriptome and immune microenvironment in functional ITH. Here, we consider the importance of both genetic and non-genetic ITH and their role in tumour evolution, and present the rationale for a broad research focus beyond the cancer genome. Systems-biology analytical approaches will be necessary to outline the scale and importance of functional ITH. By allowing a deeper understanding of tumour evolution this will, in time, encourage development of novel therapies and improve outcomes for patients.

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Year:  2021        PMID: 33727690     DOI: 10.1038/s41568-021-00336-2

Source DB:  PubMed          Journal:  Nat Rev Cancer        ISSN: 1474-175X            Impact factor:   60.716


  150 in total

Review 1.  Cancer chromosomal instability: therapeutic and diagnostic challenges.

Authors:  Nicholas McGranahan; Rebecca A Burrell; David Endesfelder; Marco R Novelli; Charles Swanton
Journal:  EMBO Rep       Date:  2012-06-01       Impact factor: 8.807

2.  The clonal evolution of tumor cell populations.

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

Review 3.  Clonal evolution in cancer.

Authors:  Mel Greaves; Carlo C Maley
Journal:  Nature       Date:  2012-01-18       Impact factor: 49.962

Review 4.  Intratumor Heterogeneity: The Rosetta Stone of Therapy Resistance.

Authors:  Andriy Marusyk; Michalina Janiszewska; Kornelia Polyak
Journal:  Cancer Cell       Date:  2020-04-13       Impact factor: 31.743

5.  Inferring tumor progression from genomic heterogeneity.

Authors:  Nicholas Navin; Alexander Krasnitz; Linda Rodgers; Kerry Cook; Jennifer Meth; Jude Kendall; Michael Riggs; Yvonne Eberling; Jennifer Troge; Vladimir Grubor; Dan Levy; Pär Lundin; Susanne Månér; Anders Zetterberg; James Hicks; Michael Wigler
Journal:  Genome Res       Date:  2009-11-10       Impact factor: 9.043

6.  Functional versus non-functional intratumor heterogeneity in cancer.

Authors:  Marc J Williams; Benjamin Werner; Trevor A Graham; Andrea Sottoriva
Journal:  Mol Cell Oncol       Date:  2016-04-22

7.  Karyotypic comparisons of multiple tumorous and macroscopically normal surrounding tissue samples from patients with breast cancer.

Authors:  M R Teixeira; N Pandis; G Bardi; J A Andersen; S Heim
Journal:  Cancer Res       Date:  1996-02-15       Impact factor: 12.701

8.  Cytogenetic and flow cytometry DNA analysis of regional heterogeneity in a low grade human glioma.

Authors:  S W Coons; P C Johnson; J R Shapiro
Journal:  Cancer Res       Date:  1995-04-01       Impact factor: 12.701

Review 9.  Resolving genetic heterogeneity in cancer.

Authors:  Samra Turajlic; Andrea Sottoriva; Trevor Graham; Charles Swanton
Journal:  Nat Rev Genet       Date:  2019-07       Impact factor: 53.242

10.  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

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  25 in total

1.  Deep whole-genome ctDNA chronology of treatment-resistant prostate cancer.

Authors:  Cameron Herberts; Matti Annala; Joonatan Sipola; Sarah W S Ng; Xinyi E Chen; Anssi Nurminen; Olga V Korhonen; Aslı D Munzur; Kevin Beja; Elena Schönlau; Cecily Q Bernales; Elie Ritch; Jack V W Bacon; Nathan A Lack; Matti Nykter; Rahul Aggarwal; Eric J Small; Martin E Gleave; David A Quigley; Felix Y Feng; Kim N Chi; Alexander W Wyatt
Journal:  Nature       Date:  2022-07-20       Impact factor: 69.504

2.  Comparison of approaches to transcriptomic analysis in multi-sampled tumors.

Authors:  Anson T Ku; Scott Wilkinson; Adam G Sowalsky
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 13.994

Review 3.  Cell competition in development, homeostasis and cancer.

Authors:  Sanne M van Neerven; Louis Vermeulen
Journal:  Nat Rev Mol Cell Biol       Date:  2022-09-29       Impact factor: 113.915

4.  Dissecting liver tumor heterogeneity to improve health equity.

Authors:  Lichun Ma; Xin Wei Wang
Journal:  Trends Cancer       Date:  2022-01-07

5.  Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution.

Authors:  Dian Yang; Matthew G Jones; Santiago Naranjo; William M Rideout; Kyung Hoi Joseph Min; Raymond Ho; Wei Wu; Joseph M Replogle; Jennifer L Page; Jeffrey J Quinn; Felix Horns; Xiaojie Qiu; Michael Z Chen; William A Freed-Pastor; Christopher S McGinnis; David M Patterson; Zev J Gartner; Eric D Chow; Trever G Bivona; Michelle M Chan; Nir Yosef; Tyler Jacks; Jonathan S Weissman
Journal:  Cell       Date:  2022-05-05       Impact factor: 66.850

Review 6.  Molecular pathogenesis and systemic therapies for hepatocellular carcinoma.

Authors:  Josep M Llovet; Roser Pinyol; Robin K Kelley; Anthony El-Khoueiry; Helen L Reeves; Xin Wei Wang; Gregory J Gores; Augusto Villanueva
Journal:  Nat Cancer       Date:  2022-04-28

7.  The Combination of Single-Cell and Next-Generation Sequencing Can Reveal Mosaicism for BRCA2 Mutations and the Fine Molecular Details of Tumorigenesis.

Authors:  Alexandra Gráf; Márton Zsolt Enyedi; Lajos Pintér; Éva Kriston-Pál; Gábor Jaksa; Árpád Bálind; Éva Ezer; Péter Horváth; Farkas Sükösd; Ernő Kiss; Lajos Haracska
Journal:  Cancers (Basel)       Date:  2021-05-13       Impact factor: 6.639

Review 8.  Breast cancer heterogeneity through the lens of single-cell analysis and spatial pathologies.

Authors:  Na Zhao; Jeffrey M Rosen
Journal:  Semin Cancer Biol       Date:  2021-07-16       Impact factor: 17.012

9.  m6A Regulator-Mediated Methylation Modification Model Predicts Prognosis, Tumor Microenvironment Characterizations and Response to Immunotherapies of Clear Cell Renal Cell Carcinoma.

Authors:  Wenhao Xu; Xi Tian; Wangrui Liu; Aihetaimujiang Anwaier; Jiaqi Su; Wenkai Zhu; Fangning Wan; Guohai Shi; Gaomeng Wei; Yuanyuan Qu; Hailiang Zhang; Dingwei Ye
Journal:  Front Oncol       Date:  2021-07-06       Impact factor: 6.244

10.  Rapid signaling reactivation after targeted BRAF inhibition predicts the proliferation of individual melanoma cells from an isogenic population.

Authors:  Payam Khoshkenar; Emily Lowry; Amir Mitchell
Journal:  Sci Rep       Date:  2021-07-29       Impact factor: 4.379

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