Literature DB >> 23708210

Adapting clinical paradigms to the challenges of cancer clonal evolution.

Nirupa Murugaesu1, Su Kit Chew, Charles Swanton.   

Abstract

Emerging evidence suggests that cancer branched evolution may affect biomarker validation, clinical outcome, and emergence of drug resistance. The changing spatial and temporal nature of cancer subclonal architecture during the disease course suggests the need for longitudinal prospective studies of cancer evolution and robust and clinically implementable pathologic definitions of intratumor heterogeneity, genetic diversity, and chromosomal instability. Furthermore, subclonal heterogeneous events in tumors may evade detection through conventional biomarker strategies and influence clinical outcome. Minimally invasive methods for the study of cancer evolution and new approaches to clinical study design, incorporating understanding of the dynamics of tumor clonal architectures through treatment and during acquisition of drug resistance, have been suggested as important areas for development. Coordinated efforts will be required by the scientific and clinical trial communities to adapt to the challenges of detecting infrequently occurring somatic events that may influence clinical outcome and to understand the dynamics of cancer evolution and the waxing and waning of tumor subclones over time in advanced metastatic epithelial malignancies.
Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2013        PMID: 23708210     DOI: 10.1016/j.ajpath.2013.02.026

Source DB:  PubMed          Journal:  Am J Pathol        ISSN: 0002-9440            Impact factor:   4.307


  17 in total

1.  Data-driven identification of prognostic tumor subpopulations using spatially mapped t-SNE of mass spectrometry imaging data.

Authors:  Walid M Abdelmoula; Benjamin Balluff; Sonja Englert; Jouke Dijkstra; Marcel J T Reinders; Axel Walch; Liam A McDonnell; Boudewijn P F Lelieveldt
Journal:  Proc Natl Acad Sci U S A       Date:  2016-10-10       Impact factor: 11.205

Review 2.  Integration of cancer genomics with treatment selection: from the genome to predictive biomarkers.

Authors:  Thomas J Ow; Vlad C Sandulache; Heath D Skinner; Jeffrey N Myers
Journal:  Cancer       Date:  2013-08-20       Impact factor: 6.860

3.  Intra-tumor genetic heterogeneity and mortality in head and neck cancer: analysis of data from the Cancer Genome Atlas.

Authors:  Edmund A Mroz; Aaron D Tward; Aaron M Tward; Rebecca J Hammon; Yin Ren; James W Rocco
Journal:  PLoS Med       Date:  2015-02-10       Impact factor: 11.069

4.  The first five years of single-cell cancer genomics and beyond.

Authors:  Nicholas E Navin
Journal:  Genome Res       Date:  2015-10       Impact factor: 9.043

5.  Massively parallel sequencing fails to detect minor resistant subclones in tissue samples prior to tyrosine kinase inhibitor therapy.

Authors:  Carina Heydt; Niklas Kumm; Jana Fassunke; Helen Künstlinger; Michaela Angelika Ihle; Andreas Scheel; Hans-Ulrich Schildhaus; Florian Haller; Reinhard Büttner; Margarete Odenthal; Eva Wardelmann; Sabine Merkelbach-Bruse
Journal:  BMC Cancer       Date:  2015-04-15       Impact factor: 4.430

Review 6.  APOBEC Enzymes: Mutagenic Fuel for Cancer Evolution and Heterogeneity.

Authors:  Charles Swanton; Nicholas McGranahan; Gabriel J Starrett; Reuben S Harris
Journal:  Cancer Discov       Date:  2015-06-19       Impact factor: 39.397

Review 7.  Intra-tumor heterogeneity: lessons from microbial evolution and clinical implications.

Authors:  Elza C de Bruin; Tiffany B Taylor; Charles Swanton
Journal:  Genome Med       Date:  2013-11-22       Impact factor: 11.117

Review 8.  Proteomic approaches in biomarker discovery: new perspectives in cancer diagnostics.

Authors:  Petra Hudler; Nina Kocevar; Radovan Komel
Journal:  ScientificWorldJournal       Date:  2014-01-14

Review 9.  Zebrafish as a model to assess cancer heterogeneity, progression and relapse.

Authors:  Jessica S Blackburn; David M Langenau
Journal:  Dis Model Mech       Date:  2014-07       Impact factor: 5.758

10.  The translation of cancer genomics: time for a revolution in clinical cancer care.

Authors:  Elaine R Mardis
Journal:  Genome Med       Date:  2014-03-26       Impact factor: 11.117

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.