Protocol for using Multiomics2Targets to identify targets and driver kinases for cancer cohorts profiled with multi-omics assays

Giacomo B Marino; Eden Z Deng; Daniel J B Clarke; Ido Diamant; Adam C Resnick; Weiping Ma; Pei Wang; Avi Ma'ayan

doi:10.1016/j.xpro.2024.103457

Protocol for using Multiomics2Targets to identify targets and driver kinases for cancer cohorts profiled with multi-omics assays

STAR Protoc. 2024 Nov 19;5(4):103457. doi: 10.1016/j.xpro.2024.103457. Online ahead of print.

Authors

Giacomo B Marino¹, Eden Z Deng¹, Daniel J B Clarke¹, Ido Diamant¹, Adam C Resnick², Weiping Ma³, Pei Wang³, Avi Ma'ayan⁴

Affiliations

¹ Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA.
² Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1498, New York, NY 10029, USA.
³ Center for Data Driven Discovery in Biomedicine, Division of Neurosurgery, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
⁴ Department of Pharmacological Sciences, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY 10029, USA. Electronic address: avi.maayan@mssm.edu.

Abstract

The availability of multi-omics data applied to profile cancer cohorts is rapidly increasing. Here, we present a protocol for Multiomics2Targets, a computational pipeline that can identify driver cell signaling pathways, protein kinases, and cell-surface targets for immunotherapy. We describe steps for preparing the data, uploading files, and tuning parameters. We then detail procedures for running the workflow, visualizing the results, and exporting and sharing reports containing the analysis. For complete details on the use and execution of this protocol, please refer to Deng et al.¹.

Keywords: bioinformatics; cancer; computer sciences; systems biology.