Literature DB >> 23550209

The scientific drunk and the lamppost: massive sequencing efforts in cancer discovery and treatment.

Michael B Yaffe1.   

Abstract

The massive resources devoted to genome sequencing of human tumors have produced important data sets for the cancer biology community. Paradoxically, however, these studies have revealed very little new biology. Despite this, additional resources in the United States are slated to continue such work and to expand similar efforts in genome sequencing to mouse tumors. It may be that scientists are "addicted" to the large amounts of data that can be relatively easily obtained, even though these data seem unlikely, on their own, to unveil new cancer treatment options or result in the ultimate goal of a cancer cure. Rather than using more tumor genetic sequences, a better strategy for identifying new treatment options may be to develop methods for analyzing the signaling networks that underlie cancer development, progression, and therapeutic resistance at both a personal and systems-wide level.

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Year:  2013        PMID: 23550209     DOI: 10.1126/scisignal.2003684

Source DB:  PubMed          Journal:  Sci Signal        ISSN: 1945-0877            Impact factor:   8.192


  37 in total

1.  Drug-induced death signaling strategy rapidly predicts cancer response to chemotherapy.

Authors:  Joan Montero; Kristopher A Sarosiek; Joseph D DeAngelo; Ophélia Maertens; Jeremy Ryan; Dalia Ercan; Huiying Piao; Neil S Horowitz; Ross S Berkowitz; Ursula Matulonis; Pasi A Jänne; Philip C Amrein; Karen Cichowski; Ronny Drapkin; Anthony Letai
Journal:  Cell       Date:  2015-02-26       Impact factor: 41.582

2.  Functional Proteomics and Deep Network Interrogation Reveal a Complex Mechanism of Action of Midostaurin in Lung Cancer Cells.

Authors:  Claudia Ctortecka; Vinayak Palve; Brent M Kuenzi; Bin Fang; Natalia J Sumi; Victoria Izumi; Silvia Novakova; Fumi Kinose; Lily L Remsing Rix; Eric B Haura; John Matthew Koomen; Uwe Rix
Journal:  Mol Cell Proteomics       Date:  2018-09-14       Impact factor: 5.911

3.  Xenopatients 2.0: reprogramming the epigenetic landscapes of patient-derived cancer genomes.

Authors:  Javier A Menendez; Tomás Alarcón; Bruna Corominas-Faja; Elisabet Cuyàs; Eugeni López-Bonet; Angel G Martin; Luciano Vellon
Journal:  Cell Cycle       Date:  2014-01-09       Impact factor: 4.534

4.  Normal cell phenotypes of breast epithelial cells provide the foundation of a breast cancer taxonomy.

Authors:  Sandro Santagata; Tan A Ince
Journal:  Expert Rev Anticancer Ther       Date:  2014-09-27       Impact factor: 4.512

5.  Cancer cell profiling by barcoding allows multiplexed protein analysis in fine-needle aspirates.

Authors:  Adeeti V Ullal; Vanessa Peterson; Sarit S Agasti; Suan Tuang; Dejan Juric; Cesar M Castro; Ralph Weissleder
Journal:  Sci Transl Med       Date:  2014-01-15       Impact factor: 17.956

6.  Enhanced Response of Acute Monocytic Leukemia Cells to Low-dose Cytarabine by 1,25-dihydroxyvitamin D3.

Authors:  Hao Guo; Sheng-Yan Lin; Wen-Xiang Ren; Qian Lei; Zhi-Chao Chen; Lu Zhang; Qiu-Bai Li
Journal:  Curr Med Sci       Date:  2018-03-15

7.  Nearing saturation of cancer driver gene discovery.

Authors:  David Hsiehchen; Antony Hsieh
Journal:  J Hum Genet       Date:  2018-06-15       Impact factor: 3.172

Review 8.  Personalized Cancer Models for Target Discovery and Precision Medicine.

Authors:  Carla Grandori; Christopher J Kemp
Journal:  Trends Cancer       Date:  2018-08-08

Review 9.  Bioinformatic approaches to augment study of epithelial-to-mesenchymal transition in lung cancer.

Authors:  Tim N Beck; Adaeze J Chikwem; Nehal R Solanki; Erica A Golemis
Journal:  Physiol Genomics       Date:  2014-08-05       Impact factor: 3.107

10.  Taxonomy of breast cancer based on normal cell phenotype predicts outcome.

Authors:  Sandro Santagata; Ankita Thakkar; Ayse Ergonul; Bin Wang; Terri Woo; Rong Hu; J Chuck Harrell; George McNamara; Matthew Schwede; Aedin C Culhane; David Kindelberger; Scott Rodig; Andrea Richardson; Stuart J Schnitt; Rulla M Tamimi; Tan A Ince
Journal:  J Clin Invest       Date:  2014-01-27       Impact factor: 14.808

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