Literature DB >> 27550448

The Greater Genomic Landscape: The Heterogeneous Evolution of Cancer.

Luay M Almassalha1, Greta M Bauer1, John E Chandler1, Scott Gladstein1, Igal Szleifer2, Hemant K Roy3, Vadim Backman2.   

Abstract

Results have historically shown a broad plasticity in the origin of tumors and their functions, with significant heterogeneity observed in both morphologies and functional capabilities. Largely unknown, however, are the mechanisms by which these variations occur and how these events influence tumor formation and behavior. Contemporary views on the origin of tumors focus mainly on the role of particular sets of driver transformations, mutational or epigenetic, with the occurrence of the observed heterogeneity as an accidental byproduct of oncogenesis. As such, we present a hypothesis that tumors form due to heterogeneous adaptive selection in response to environmental stress through intrinsic genomic sampling mechanisms. Specifically, we propose that eukaryotic cells intrinsically explore their available genomic information, the greater genomic landscape (GGL), in response to stress under normal conditions, long before the formation of a cancerous lesion. Finally, considering the influence of chromatin heterogeneity on the GGL, we propose a new class of compounds, chromatin-protective therapies (CPT), which target the physical variations in chromatin topology. In this approach, CPTs reduce the overall information space available to limit the formation of tumors or the development of drug-resistant phenotypes. Cancer Res; 76(19); 5605-9. ©2016 AACR. ©2016 American Association for Cancer Research.

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Year:  2016        PMID: 27550448      PMCID: PMC5084919          DOI: 10.1158/0008-5472.CAN-16-0585

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  30 in total

Review 1.  Control of apoptosis by the BCL-2 protein family: implications for physiology and therapy.

Authors:  Peter E Czabotar; Guillaume Lessene; Andreas Strasser; Jerry M Adams
Journal:  Nat Rev Mol Cell Biol       Date:  2014-01       Impact factor: 94.444

2.  Macromolecular crowding as a regulator of gene transcription.

Authors:  Hiroaki Matsuda; Gregory Garbès Putzel; Vadim Backman; Igal Szleifer
Journal:  Biophys J       Date:  2014-04-15       Impact factor: 4.033

Review 3.  Mitochondrial and postmitochondrial survival signaling in cancer.

Authors:  Neelu Yadav; Dhyan Chandra
Journal:  Mitochondrion       Date:  2013-12-10       Impact factor: 4.160

4.  Cancer etiology. Variation in cancer risk among tissues can be explained by the number of stem cell divisions.

Authors:  Cristian Tomasetti; Bert Vogelstein
Journal:  Science       Date:  2015-01-02       Impact factor: 47.728

5.  Aneuploidy theory explains tumor formation, the absence of immune surveillance, and the failure of chemotherapy.

Authors:  David Rasnick
Journal:  Cancer Genet Cytogenet       Date:  2002-07-01

6.  Optical methodology for detecting histologically unapparent nanoscale consequences of genetic alterations in biological cells.

Authors:  Hariharan Subramanian; Prabhakar Pradhan; Yang Liu; Ilker R Capoglu; Xu Li; Jeremy D Rogers; Alexander Heifetz; Dhananjay Kunte; Hemant K Roy; Allen Taflove; Vadim Backman
Journal:  Proc Natl Acad Sci U S A       Date:  2008-12-10       Impact factor: 11.205

7.  Extremely high genetic diversity in a single tumor points to prevalence of non-Darwinian cell evolution.

Authors:  Shaoping Ling; Zheng Hu; Zuyu Yang; Fang Yang; Yawei Li; Pei Lin; Ke Chen; Lili Dong; Lihua Cao; Yong Tao; Lingtong Hao; Qingjian Chen; Qiang Gong; Dafei Wu; Wenjie Li; Wenming Zhao; Xiuyun Tian; Chunyi Hao; Eric A Hungate; Daniel V T Catenacci; Richard R Hudson; Wen-Hsiung Li; Xuemei Lu; Chung-I Wu
Journal:  Proc Natl Acad Sci U S A       Date:  2015-11-11       Impact factor: 11.205

Review 8.  Intratumor heterogeneity: evolution through space and time.

Authors:  Charles Swanton
Journal:  Cancer Res       Date:  2012-09-20       Impact factor: 12.701

Review 9.  Cancer stem cells: impact, heterogeneity, and uncertainty.

Authors:  Jeffrey A Magee; Elena Piskounova; Sean J Morrison
Journal:  Cancer Cell       Date:  2012-03-20       Impact factor: 31.743

10.  Bet hedging in yeast by heterogeneous, age-correlated expression of a stress protectant.

Authors:  Sasha F Levy; Naomi Ziv; Mark L Siegal
Journal:  PLoS Biol       Date:  2012-05-08       Impact factor: 8.029

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  12 in total

1.  Macrogenomic engineering via modulation of the scaling of chromatin packing density.

Authors:  Luay M Almassalha; Greta M Bauer; Wenli Wu; Lusik Cherkezyan; Di Zhang; Alexis Kendra; Scott Gladstein; John E Chandler; David VanDerway; Brandon-Luke L Seagle; Andrey Ugolkov; Daniel D Billadeau; Thomas V O'Halloran; Andrew P Mazar; Hemant K Roy; Igal Szleifer; Shohreh Shahabi; Vadim Backman
Journal:  Nat Biomed Eng       Date:  2017-11-06       Impact factor: 25.671

2.  Measuring Nanoscale Chromatin Heterogeneity with Partial Wave Spectroscopic Microscopy.

Authors:  Scott Gladstein; Andrew Stawarz; Luay M Almassalha; Lusik Cherkezyan; John E Chandler; Xiang Zhou; Hariharan Subramanian; Vadim Backman
Journal:  Methods Mol Biol       Date:  2018

3.  The Global Relationship between Chromatin Physical Topology, Fractal Structure, and Gene Expression.

Authors:  L M Almassalha; A Tiwari; P T Ruhoff; Y Stypula-Cyrus; L Cherkezyan; H Matsuda; M A Dela Cruz; J E Chandler; C White; C Maneval; H Subramanian; I Szleifer; H K Roy; V Backman
Journal:  Sci Rep       Date:  2017-01-24       Impact factor: 4.379

4.  Simulation framework for generating intratumor heterogeneity patterns in a cancer cell population.

Authors:  Watal M Iwasaki; Hideki Innan
Journal:  PLoS One       Date:  2017-09-06       Impact factor: 3.240

5.  Ancient genes establish stress-induced mutation as a hallmark of cancer.

Authors:  Luis Cisneros; Kimberly J Bussey; Adam J Orr; Milica Miočević; Charles H Lineweaver; Paul Davies
Journal:  PLoS One       Date:  2017-04-25       Impact factor: 3.240

6.  Correlating colorectal cancer risk with field carcinogenesis progression using partial wave spectroscopic microscopy.

Authors:  Scott Gladstein; Dhwanil Damania; Luay M Almassalha; Lauren T Smith; Varun Gupta; Hariharan Subramanian; Douglas K Rex; Hemant K Roy; Vadim Backman
Journal:  Cancer Med       Date:  2018-03-23       Impact factor: 4.452

7.  Estimating the number of genetic mutations (hits) required for carcinogenesis based on the distribution of somatic mutations.

Authors:  Ramu Anandakrishnan; Robin T Varghese; Nicholas A Kinney; Harold R Garner
Journal:  PLoS Comput Biol       Date:  2019-03-07       Impact factor: 4.475

8.  Identifying multi-hit carcinogenic gene combinations: Scaling up a weighted set cover algorithm using compressed binary matrix representation on a GPU.

Authors:  Qais Al Hajri; Sajal Dash; Wu-Chun Feng; Harold R Garner; Ramu Anandakrishnan
Journal:  Sci Rep       Date:  2020-02-06       Impact factor: 4.379

Review 9.  The transformation of the nuclear nanoarchitecture in human field carcinogenesis.

Authors:  Greta M Bauer; Yolanda Stypula-Cyrus; Hariharan Subramanian; Lusik Cherkezyan; Parvathi Viswanathan; Di Zhang; Radha Iyengar; Saurabh Bagalkar; Justin Derbas; Taylor Graff; Scott Gladstein; Luay M Almassalha; John E Chandler; Hemant K Roy; Vadim Backman
Journal:  Future Sci OA       Date:  2017-05-05

10.  Differentiating between cancer and normal tissue samples using multi-hit combinations of genetic mutations.

Authors:  Sajal Dash; Nicholas A Kinney; Robin T Varghese; Harold R Garner; Wu-Chun Feng; Ramu Anandakrishnan
Journal:  Sci Rep       Date:  2019-01-30       Impact factor: 4.379

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