Literature DB >> 30901264

Cancer Treatment in the Genomic Era.

Gary J Doherty1, Michele Petruzzelli1,2, Emma Beddowes1,3, Saif S Ahmad1,2,3, Carlos Caldas1,3, Richard J Gilbertson1,3.   

Abstract

The complexity of human cancer underlies its devastating clinical consequences. Drugs designed to target the genetic alterations that drive cancer have improved the outcome for many patients, but not the majority of them. Here, we review the genomic landscape of cancer, how genomic data can provide much more than a sum of its parts, and the approaches developed to identify and validate genomic alterations with potential therapeutic value. We highlight notable successes and pitfalls in predicting the value of potential therapeutic targets and discuss the use of multi-omic data to better understand cancer dependencies and drug sensitivity. We discuss how integrated approaches to collecting, curating, and sharing these large data sets might improve the identification and prioritization of cancer vulnerabilities as well as patient stratification within clinical trials. Finally, we outline how future approaches might improve the efficiency and speed of translating genomic data into clinically effective therapies and how the use of unbiased genome-wide information can identify novel predictive biomarkers that can be either simple or complex.

Entities:  

Keywords:  cancer genomics; cancer treatment; personalized cancer medicine; precision oncology; therapeutic actionability

Mesh:

Year:  2019        PMID: 30901264     DOI: 10.1146/annurev-biochem-062917-011840

Source DB:  PubMed          Journal:  Annu Rev Biochem        ISSN: 0066-4154            Impact factor:   27.258


  8 in total

1.  DDX3X Suppresses the Susceptibility of Hindbrain Lineages to Medulloblastoma.

Authors:  Deanna M Patmore; Amir Jassim; Erica Nathan; Reuben J Gilbertson; Daniel Tahan; Nadin Hoffmann; Yiai Tong; Kyle S Smith; Thirumala-Devi Kanneganti; Hiromichi Suzuki; Michael D Taylor; Paul Northcott; Richard J Gilbertson
Journal:  Dev Cell       Date:  2020-06-17       Impact factor: 12.270

Review 2.  ATP and Adenosine Metabolism in Cancer: Exploitation for Therapeutic Gain.

Authors:  Gennady G Yegutkin; Detlev Boison
Journal:  Pharmacol Rev       Date:  2022-07       Impact factor: 18.923

3.  Multi-Approach Bioinformatics Analysis of Curated Omics Data Provides a Gene Expression Panorama for Multiple Cancer Types.

Authors:  Bruno César Feltes; Joice de Faria Poloni; Itamar José Guimarães Nunes; Sara Socorro Faria; Marcio Dorn
Journal:  Front Genet       Date:  2020-11-23       Impact factor: 4.599

4.  Identification and validation of ADME genes as prognosis and therapy markers for hepatocellular carcinoma patients.

Authors:  Jukun Wang; Ke Han; Chao Zhang; Xin Chen; Yu Li; Linzhong Zhu; Tao Luo
Journal:  Biosci Rep       Date:  2021-05-28       Impact factor: 3.840

5.  Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review.

Authors:  Cheng Lu; Rakesh Shiradkar; Zaiyi Liu
Journal:  Chin J Cancer Res       Date:  2021-10-31       Impact factor: 4.026

Review 6.  Combining Molecular, Imaging, and Clinical Data Analysis for Predicting Cancer Prognosis.

Authors:  Barbara Lobato-Delgado; Blanca Priego-Torres; Daniel Sanchez-Morillo
Journal:  Cancers (Basel)       Date:  2022-06-30       Impact factor: 6.575

7.  Expression profile analysis identifies IER3 to predict overall survival and promote lymph node metastasis in tongue cancer.

Authors:  Fang Xiao; Yinhua Dai; Yujiao Hu; Mengmeng Lu; Qun Dai
Journal:  Cancer Cell Int       Date:  2019-11-21       Impact factor: 5.722

8.  Lnc2Cancer 3.0: an updated resource for experimentally supported lncRNA/circRNA cancer associations and web tools based on RNA-seq and scRNA-seq data.

Authors:  Yue Gao; Shipeng Shang; Shuang Guo; Xin Li; Hanxiao Zhou; Hongjia Liu; Yue Sun; Junwei Wang; Peng Wang; Hui Zhi; Xia Li; Shangwei Ning; Yunpeng Zhang
Journal:  Nucleic Acids Res       Date:  2021-01-08       Impact factor: 16.971

  8 in total

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