Literature DB >> 30616753

A Road Map to Personalizing Targeted Cancer Therapies Using Synthetic Lethality.

Sreejit Parameswaran1, Deeksha Kundapur1, Frederick S Vizeacoumar2, Andrew Freywald3, Maruti Uppalapati4, Franco J Vizeacoumar5.   

Abstract

Targeted therapies rely on the genetic and epigenetic status of the tumor cells and are seen as the most promising approach to treat cancer today. However, current targeted therapies focus on directly inhibiting those molecules that are altered in tumor cells. Unfortunately, targeting these molecules, even with specific inhibitors, is challenging as tumor cells rewire their genetic circuitry to eliminate genetic dependency on these targets. Here, we describe how synthetic lethality approaches can be used to identify genetic dependencies and develop personalized targeted therapies. We also discuss strategies to specifically target these genetic dependencies, using small molecule and biologic drugs.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  shRNA vs CRISPR; synthetic lethality; targeting intracellular molecules

Mesh:

Substances:

Year:  2018        PMID: 30616753     DOI: 10.1016/j.trecan.2018.11.001

Source DB:  PubMed          Journal:  Trends Cancer        ISSN: 2405-8025


  9 in total

Review 1.  Synthetic Lethality through the Lens of Medicinal Chemistry.

Authors:  Samuel H Myers; Jose Antonio Ortega; Andrea Cavalli
Journal:  J Med Chem       Date:  2020-11-02       Impact factor: 7.446

2.  Identification of Synthetic Lethal Interactions Using High-Throughput, Arrayed CRISPR/Cas9-Based Platforms.

Authors:  MacKenzie J MacAuley; Omar Abuhussein; Frederick S Vizeacoumar
Journal:  Methods Mol Biol       Date:  2021

3.  Generation of Protein Inhibitors for Validation of Cancer Drug Targets Identified in Functional Genomic Screens.

Authors:  Sherin McDonald; Arunkumar Annan Sudarsan; Hanan Babeker; Kiranmayee Budharaju; Maruti Uppalapati
Journal:  Methods Mol Biol       Date:  2021

4.  Computational Prediction of Chemical Tools for Identification and Validation of Synthetic Lethal Interaction Networks.

Authors:  Kalpana K Bhanumathy; Omar Abuhussein; Frederick S Vizeacoumar; Andrew Freywald; Franco J Vizeacoumar; Christopher P Phenix; Eric W Price; Ran Cao
Journal:  Methods Mol Biol       Date:  2021

Review 5.  Computational methods, databases and tools for synthetic lethality prediction.

Authors:  Jing Wang; Qinglong Zhang; Junshan Han; Yanpeng Zhao; Caiyun Zhao; Bowei Yan; Chong Dai; Lianlian Wu; Yuqi Wen; Yixin Zhang; Dongjin Leng; Zhongming Wang; Xiaoxi Yang; Song He; Xiaochen Bo
Journal:  Brief Bioinform       Date:  2022-05-13       Impact factor: 13.994

6.  Humanized yeast genetic interaction mapping predicts synthetic lethal interactions of FBXW7 in breast cancer.

Authors:  Morgan W B Kirzinger; Frederick S Vizeacoumar; Bjorn Haave; Cristina Gonzalez-Lopez; Keith Bonham; Anthony Kusalik; Franco J Vizeacoumar
Journal:  BMC Med Genomics       Date:  2019-07-27       Impact factor: 3.063

7.  Synthetic lethality across normal tissues is strongly associated with cancer risk, onset, and tumor suppressor specificity.

Authors:  Kuoyuan Cheng; Nishanth Ulhas Nair; Joo Sang Lee; Eytan Ruppin
Journal:  Sci Adv       Date:  2021-01-01       Impact factor: 14.136

8.  Identification of novel genes involved in apoptosis of HIV-infected macrophages using unbiased genome-wide screening.

Authors:  Simon X M Dong; Frederick S Vizeacoumar; Kalpana K Bhanumathy; Nezeka Alli; Cristina Gonzalez-Lopez; Niranjala Gajanayaka; Ramon Caballero; Hamza Ali; Andrew Freywald; Edana Cassol; Jonathan B Angel; Franco J Vizeacoumar; Ashok Kumar
Journal:  BMC Infect Dis       Date:  2021-07-07       Impact factor: 3.090

9.  Downregulation of ATM and BRCA1 Predicts Poor Outcome in Head and Neck Cancer: Implications for ATM-Targeted Therapy.

Authors:  Yu-Chu Wang; Ka-Wo Lee; Yi-Shan Tsai; Hsing-Han Lu; Si-Yun Chen; Hsin-Ying Hsieh; Chang-Shen Lin
Journal:  J Pers Med       Date:  2021-05-10
  9 in total

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