A Pipeline for Drug Target Identification and Validation

Manchado, E., Huang, C. H., Tasdemir, N., Tschaharganeh, D. F., Wilkinson, J. E., Lowe, S. W. (January 2017) A Pipeline for Drug Target Identification and Validation. Cold Spring Harb Symp Quant Biol, 81. pp. 257-267. ISSN 1943-4456 (Electronic)0091-7451 (Linking)

Abstract

Rapid and affordable tumor profiling has led to an explosion of genomic data that is facilitating the development of new cancer therapies. The potential of therapeutic strategies aimed at inactivating the oncogenic lesions that contribute to the aberrant survival and proliferation of tumor cells has yielded remarkable success in some malignancies such as BRAF-mutant melanoma and BCR-ABL expressing chronic myeloid leukemia. However, the direct inhibition of several well-established oncoproteins in some of these cancers is not possible or produces only transient benefits. Functional genomics represents a powerful approach for the identification of vulnerabilities linked to specific genetic alterations and has provided substantial insights into cancer signaling networks. Still, as inhibition of gene function can have diverse effects on both tumor and normal tissues, information on the potency of target inhibition on tumor growth as well as the toxic side effects of target inhibition are also needed. Here, we discuss our RNA interference (RNAi) pipeline for cancer target discovery based on our optimized short-hairpin RNA (shRNA) tools for negative selection screens and inducible RNAi platform that, in combination with embryonic stem cell (ESC)-based genetically engineered mouse models (GEMMs), enable deep in vivo target validation.

Item Type: Paper
Subjects: diseases & disorders > cancer > drugs and therapies
CSHL Authors:
Communities: CSHL labs > Lowe lab
School of Biological Sciences > Publications
Depositing User: Matt Covey
Date: 5 January 2017
Date Deposited: 10 Jan 2017 21:45
Last Modified: 01 Mar 2024 15:15
PMCID: PMC5469697
Related URLs:
URI: https://repository.cshl.edu/id/eprint/33958

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