Literature DB >> 26677427

Current dichotomy between traditional molecular biological and omic research in cancer biology and pharmacology.

William C Reinhold1.   

Abstract

There is currently a split within the cancer research community between traditional molecular biological hypothesis-driven and the more recent "omic" forms or research. While the molecular biological approach employs the tried and true single alteration-single response formulations of experimentation, the omic employs broad-based assay or sample collection approaches that generate large volumes of data. How to integrate the benefits of these two approaches in an efficient and productive fashion remains an outstanding issue. Ideally, one would merge the understandability, exactness, simplicity, and testability of the molecular biological approach, with the larger amounts of data, simultaneous consideration of multiple alterations, consideration of genes both of known interest along with the novel, cross-sample comparisons among cell lines and patient samples, and consideration of directed questions while simultaneously gaining exposure to the novel provided by the omic approach. While at the current time integration of the two disciplines remains problematic, attempts to do so are ongoing, and will be necessary for the understanding of the large cell line screens including the Developmental Therapeutics Program's NCI-60, the Broad Institute's Cancer Cell Line Encyclopedia, and the Wellcome Trust Sanger Institute's Cancer Genome Project, as well as the the Cancer Genome Atlas clinical samples project. Going forward there is significant benefit to be had from the integration of the molecular biological and the omic forms or research, with the desired goal being improved translational understanding and application.

Entities:  

Keywords:  Cancer; Integration; Molecular biology; Omic; Pharmacology

Year:  2015        PMID: 26677427      PMCID: PMC4675899          DOI: 10.5306/wjco.v6.i6.184

Source DB:  PubMed          Journal:  World J Clin Oncol        ISSN: 2218-4333


  31 in total

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Authors:  D P Lane
Journal:  Nature       Date:  1992-07-02       Impact factor: 49.962

2.  Network-constrained regularization and variable selection for analysis of genomic data.

Authors:  Caiyan Li; Hongzhe Li
Journal:  Bioinformatics       Date:  2008-03-01       Impact factor: 6.937

3.  Predicting cancer drug response by proteomic profiling.

Authors:  Yan Ma; Zhenyu Ding; Yong Qian; Xianglin Shi; Vince Castranova; E James Harner; Lan Guo
Journal:  Clin Cancer Res       Date:  2006-08-01       Impact factor: 12.531

4.  An information-intensive approach to the molecular pharmacology of cancer.

Authors:  J N Weinstein; T G Myers; P M O'Connor; S H Friend; A J Fornace; K W Kohn; T Fojo; S E Bates; L V Rubinstein; N L Anderson; J K Buolamwini; W W van Osdol; A P Monks; D A Scudiero; E A Sausville; D W Zaharevitz; B Bunow; V N Viswanadhan; G S Johnson; R E Wittes; K D Paull
Journal:  Science       Date:  1997-01-17       Impact factor: 47.728

5.  Reactome: a database of reactions, pathways and biological processes.

Authors:  David Croft; Gavin O'Kelly; Guanming Wu; Robin Haw; Marc Gillespie; Lisa Matthews; Michael Caudy; Phani Garapati; Gopal Gopinath; Bijay Jassal; Steven Jupe; Irina Kalatskaya; Shahana Mahajan; Bruce May; Nelson Ndegwa; Esther Schmidt; Veronica Shamovsky; Christina Yung; Ewan Birney; Henning Hermjakob; Peter D'Eustachio; Lincoln Stein
Journal:  Nucleic Acids Res       Date:  2010-11-09       Impact factor: 16.971

6.  Identification of genotype-correlated sensitivity to selective kinase inhibitors by using high-throughput tumor cell line profiling.

Authors:  Ultan McDermott; Sreenath V Sharma; Lori Dowell; Patricia Greninger; Clara Montagut; Jennifer Lamb; Heidi Archibald; Raul Raudales; Angela Tam; Diana Lee; S Michael Rothenberg; Jeffrey G Supko; Raffaella Sordella; Lindsey E Ulkus; A John Iafrate; Shyamala Maheswaran; Ching Ni Njauw; Hensin Tsao; Lisa Drew; Jeff H Hanke; Xiao-Jun Ma; Mark G Erlander; Nathanael S Gray; Daniel A Haber; Jeffrey Settleman
Journal:  Proc Natl Acad Sci U S A       Date:  2007-12-06       Impact factor: 11.205

7.  American founder mutation for attenuated familial adenomatous polyposis.

Authors:  Deborah W Neklason; Jeffery Stevens; Kenneth M Boucher; Richard A Kerber; Nori Matsunami; Jahn Barlow; Geraldine Mineau; Mark F Leppert; Randall W Burt
Journal:  Clin Gastroenterol Hepatol       Date:  2007-12-11       Impact factor: 11.382

8.  High resolution copy number variation data in the NCI-60 cancer cell lines from whole genome microarrays accessible through CellMiner.

Authors:  Sudhir Varma; Yves Pommier; Margot Sunshine; John N Weinstein; William C Reinhold
Journal:  PLoS One       Date:  2014-03-26       Impact factor: 3.240

9.  Temozolomide resistance in glioblastoma cells occurs partly through epidermal growth factor receptor-mediated induction of connexin 43.

Authors:  J L Munoz; V Rodriguez-Cruz; S J Greco; S H Ramkissoon; K L Ligon; P Rameshwar
Journal:  Cell Death Dis       Date:  2014-03-27       Impact factor: 8.469

10.  A software application for comparing large numbers of high resolution MALDI-FTICR MS spectra demonstrated by searching candidate biomarkers for glioma blood vessel formation.

Authors:  Mark K Titulaer; Dana A N Mustafa; Ivar Siccama; Marco Konijnenburg; Peter C Burgers; Arno C Andeweg; Peter A E Sillevis Smitt; Johan M Kros; Theo M Luider
Journal:  BMC Bioinformatics       Date:  2008-03-01       Impact factor: 3.169

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