A Gene Expression High-Throughput Screen (GE-HTS) for Coordinated Detection of Functionally Similar Effectors in Cancer
by
, , , , , and
Chaitra Rao
1,†
,
Dianna H. Huisman
1,†
,
Heidi M. Vieira
1
,
Danielle E. Frodyma
1,
Beth K. Neilsen
1
,
Binita Chakraborty
2,
Suzie K. Hight
3,
Michael A. White
4,
Kurt W. Fisher
5 and
Robert E. Lewis
1,* 1
Eppley Institute, Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE 68198, USA
2
Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC 27710, USA
3
Moores Cancer Center, University of California San Diego, La Jolla, CA 92037, USA
4
Chief Scientific Officer, Samumed, LLC, San Diego, CA 92121, USA
5
Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68198, USA
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Cancers 2020, 12(11), 3143; https://doi.org/10.3390/cancers12113143
Submission received: 29 September 2020
/
Revised: 23 October 2020
/
Accepted: 25 October 2020
/
Published: 27 October 2020
(This article belongs to the Special Issue The Study of Cancer Susceptibility Genes)
Simple Summary
Approximately 30% of human cancer patients carry active Ras mutations, which play a central role in cancer cell malignancy. Although Ras serves as an excellent drug target, significant challenges still exist to directly inhibit all forms of oncogenic Ras. Identifying functionally similar proteins with known inhibitors may overcome this bottleneck in Ras-driven cancers. In this review, we investigate the use of a functional genome-scale screen termed Functional Signature Ontology (FUSION) to screen small interfering RNAs (siRNA), microRNA mimics, and small molecules or complex mixtures of natural products for coordinated detection of new targets and small molecules for cancer therapy. After computational filtering and prioritizing of targets identified in FUSION, biological validation was performed to elucidate their mechanism of action in cancer and to provide an initial evaluation of their potential to serve as therapeutic targets. We also discuss the guidelines for design, optimization, and analysis to increase the applicability and generalizability of future FUSION screens.
Abstract
Genome-wide, loss-of-function screening can be used to identify novel vulnerabilities upon which specific tumor cells depend for survival. Functional Signature Ontology (FUSION) is a gene expression-based high-throughput screening (GE-HTS) method that allows researchers to identify functionally similar proteins, small molecules, and microRNA mimics, revealing novel therapeutic targets. FUSION uses cell-based high-throughput screening and computational analysis to match gene expression signatures produced by natural products to those produced by small interfering RNA (siRNA) and synthetic microRNA libraries to identify putative protein targets and mechanisms of action (MoA) for several previously undescribed natural products. We have used FUSION to screen for functional analogues to Kinase suppressor of Ras 1 (KSR1), a scaffold protein downstream of Ras in the Raf-MEK-ERK kinase cascade, and biologically validated several proteins with functional similarity to KSR1. FUSION incorporates bioinformatics analysis that may offer higher resolution of the endpoint readout than other screens which utilize Boolean outputs regarding a single pathway activation (i.e., synthetic lethal and cell proliferation). Challenges associated with FUSION and other high-content genome-wide screens include variation, batch effects, and controlling for potential off-target effects. In this review, we discuss the efficacy of FUSION to identify novel inhibitors and oncogene-induced changes that may be cancer cell-specific as well as several potential pitfalls within FUSION and best practices to avoid them.
