INCISOR: An Algorithm to Identify Synthetic Rescue Mediators of Resistance to Targeted and Immunotherapy

Xiaoman Wang; Frederick Sagayaraj Vizeacoumar; Avinash Das Sahu

doi:10.1007/978-1-0716-1740-3_11

INCISOR: An Algorithm to Identify Synthetic Rescue Mediators of Resistance to Targeted and Immunotherapy

Methods Mol Biol. 2021:2381:203-215. doi: 10.1007/978-1-0716-1740-3_11.

Authors

Xiaoman Wang^{1

2}, Frederick Sagayaraj Vizeacoumar^{3

4}, Avinash Das Sahu^{5

6

7}

Affiliations

¹ Dana Farber Cancer Institute, Boston, MA, USA.
² State Key Laboratory of Medical Molecular Biology, Department of Biochemistry and Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
³ Department of Health Sciences, Cancer Cluster, College of Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
⁴ Department of Pathology and Laboratory Medicine, College of Medicine, University of Saskatchewan, Saskatoon, SK, Canada.
⁵ Dana Farber Cancer Institute, Boston, MA, USA. Avinash_Sahu@DFCI.HARVARD.EDU.
⁶ Department of Biostatistics and Computational Biology, Harvard School of Public Health, Boston, MA, USA. Avinash_Sahu@DFCI.HARVARD.EDU.
⁷ Massachusetts General Hospital Cancer Center, Department of Medicine, Harvard Medical School, Boston, MA, USA. Avinash_Sahu@DFCI.HARVARD.EDU.

PMID: 34590278
DOI: 10.1007/978-1-0716-1740-3_11

Abstract

Despite the success of targeted therapies including immunotherapies in cancer treatments, tumor resistance to targeted therapies remains a fundamental challenge. Tumors can evolve resistance to a therapy that targets one gene by acquiring compensatory alterations in another gene, such compensatory interaction between two genes is referred to as synthetic rescue (SR) interactions. To identify SRs, here we describe an algorithm, INCISOR, that leverages tumor transcriptomics and clinical information from 10,000 patients as well as data from experimental screens. INCISOR can identify SRs that are common across several cancer-types in genome-wide fashion by sifting through half a billion possible gene-gene combinations and provide a framework to design therapies to tackle resistance.

Keywords: Genetic interactions; Precision oncology; Synthetic rescue; Targeted therapies; Treatment resistance.

MeSH terms

Algorithms
Humans
Immunotherapy
Molecular Targeted Therapy
Neoplasms* / drug therapy
Neoplasms* / therapy
Transcriptome