Literature DB >> 27296652

Individualized network-based drug repositioning infrastructure for precision oncology in the panomics era.

Feixiong Cheng, Huixiao Hong, Shengyong Yang, Yuquan Wei.   

Abstract

Advances in next-generation sequencing technologies have generated the data supporting a large volume of somatic alterations in several national and international cancer genome projects, such as The Cancer Genome Atlas and the International Cancer Genome Consortium. These cancer genomics data have facilitated the revolution of a novel oncology drug discovery paradigm from candidate target or gene studies toward targeting clinically relevant driver mutations or molecular features for precision cancer therapy. This focuses on identifying the most appropriately targeted therapy to an individual patient harboring a particularly genetic profile or molecular feature. However, traditional experimental approaches that are used to develop new chemical entities for targeting the clinically relevant driver mutations are costly and high-risk. Drug repositioning, also known as drug repurposing, re-tasking or re-profiling, has been demonstrated as a promising strategy for drug discovery and development. Recently, computational techniques and methods have been proposed for oncology drug repositioning and identifying pharmacogenomics biomarkers, but overall progress remains to be seen. In this review, we focus on introducing new developments and advances of the individualized network-based drug repositioning approaches by targeting the clinically relevant driver events or molecular features derived from cancer panomics data for the development of precision oncology drug therapies (e.g. one-person trials) to fully realize the promise of precision medicine. We discuss several potential challenges (e.g. tumor heterogeneity and cancer subclones) for precision oncology. Finally, we highlight several new directions for the precision oncology drug discovery via biotherapies (e.g. gene therapy and immunotherapy) that target the 'undruggable' cancer genome in the functional genomics era.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  cancer genomics; drug repositioning; panomics; precision oncology; systems biology; systems pharmacology

Mesh:

Year:  2017        PMID: 27296652     DOI: 10.1093/bib/bbw051

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  25 in total

1.  Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2.

Authors:  Yadi Zhou; Yuan Hou; Jiayu Shen; Yin Huang; William Martin; Feixiong Cheng
Journal:  Cell Discov       Date:  2020-03-16       Impact factor: 10.849

2.  Quantitative and Systems Pharmacology. 1. In Silico Prediction of Drug-Target Interactions of Natural Products Enables New Targeted Cancer Therapy.

Authors:  Jiansong Fang; Zengrui Wu; Chuipu Cai; Qi Wang; Yun Tang; Feixiong Cheng
Journal:  J Chem Inf Model       Date:  2017-10-13       Impact factor: 4.956

3.  deepDR: a network-based deep learning approach to in silico drug repositioning.

Authors:  Xiangxiang Zeng; Siyi Zhu; Xiangrong Liu; Yadi Zhou; Ruth Nussinov; Feixiong Cheng
Journal:  Bioinformatics       Date:  2019-12-15       Impact factor: 6.937

4.  Pharmacogenomics meets precision cardio-oncology: is there synergistic potential?

Authors:  Jennifer K Hockings; Jessica A Castrillon; Feixiong Cheng
Journal:  Hum Mol Genet       Date:  2020-10-20       Impact factor: 6.150

5.  In silico prediction of chemical mechanism of action via an improved network-based inference method.

Authors:  Zengrui Wu; Weiqiang Lu; Dang Wu; Anqi Luo; Hanping Bian; Jie Li; Weihua Li; Guixia Liu; Jin Huang; Feixiong Cheng; Yun Tang
Journal:  Br J Pharmacol       Date:  2016-11-01       Impact factor: 8.739

6.  Pharmacogenomics for immunotherapy and immune-related cardiotoxicity.

Authors:  Jessica A Castrillon; Charis Eng; Feixiong Cheng
Journal:  Hum Mol Genet       Date:  2020-10-20       Impact factor: 6.150

7.  SperoPredictor: An Integrated Machine Learning and Molecular Docking-Based Drug Repurposing Framework With Use Case of COVID-19.

Authors:  Faheem Ahmed; Jae Wook Lee; Anupama Samantasinghar; Young Su Kim; Kyung Hwan Kim; In Suk Kang; Fida Hussain Memon; Jong Hwan Lim; Kyung Hyun Choi
Journal:  Front Public Health       Date:  2022-06-16

Review 8.  Harnessing endophenotypes and network medicine for Alzheimer's drug repurposing.

Authors:  Jiansong Fang; Andrew A Pieper; Ruth Nussinov; Garam Lee; Lynn Bekris; James B Leverenz; Jeffrey Cummings; Feixiong Cheng
Journal:  Med Res Rev       Date:  2020-07-13       Impact factor: 12.944

9.  Deep learning of pharmacogenomics resources: moving towards precision oncology.

Authors:  Yu-Chiao Chiu; Hung-I Harry Chen; Aparna Gorthi; Milad Mostavi; Siyuan Zheng; Yufei Huang; Yidong Chen
Journal:  Brief Bioinform       Date:  2020-12-01       Impact factor: 11.622

10.  Structure-based drug repurposing against COVID-19 and emerging infectious diseases: methods, resources and discoveries.

Authors:  Yosef Masoudi-Sobhanzadeh; Aysan Salemi; Mohammad M Pourseif; Behzad Jafari; Yadollah Omidi; Ali Masoudi-Nejad
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 11.622

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