Gene Signature Reveals Decreased SOX10-Dependent Transcripts in Malignant Cells From Immune Checkpoint Inhibitor-Resistant Cutaneous Melanomas
Document Type
Article
Publication Date
7-25-2023
Abstract
Evidence is mounting for cross-resistance between immune checkpoint and targeted kinase inhibitor therapies in cutaneous melanoma patients. Since the loss of the transcription factor, SOX10, causes tolerance to MAPK pathway inhibitors, we used bioinformatic techniques to determine if reduced SOX10 expression/activity is associated with immune checkpoint inhibitor resistance. We integrated SOX10 ChIP-seq, knockout RNA-seq, and knockdown ATAC-seq data from melanoma cell models to develop a robust SOX10 gene signature. We used computational methods to validate this signature as a measure of SOX10-dependent activity in independent single-cell and bulk RNA-seq SOX10 knockdown, cell line panel, and MAPK inhibitor drug-resistant datasets. Evaluation of patient single-cell RNA-seq data revealed lower levels of SOX10-dependent transcripts in immune checkpoint inhibitor-resistant tumors. Our results suggest that SOX10-deficient melanoma cells are associated with cross-resistance between targeted and immune checkpoint inhibitors and highlight the need to identify therapeutic strategies that target this subpopulation.
Recommended Citation
Purwin, Timothy J.; Caksa, Signe; Sacan, Ahmet; Capparelli, Claudia; and Aplin, Andrew E., "Gene Signature Reveals Decreased SOX10-Dependent Transcripts in Malignant Cells From Immune Checkpoint Inhibitor-Resistant Cutaneous Melanomas" (2023). Department of Pharmacology, Physiology, and Cancer Biology Faculty Papers. Paper 4.
https://jdc.jefferson.edu/ppcbfp/4
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Document S1. Figures S1–S5.
1-s2.0-S2589004223015493-mmc2.xlsx (19 kB)
Table S1. SOX10 gene signatures, related to Figures 1E and S1B.
Language
English
Comments
This article is the author's final published version in iScience, Volume 26, Issue 9, 15 September 2023, Article number 107472.
The published version is available at https://doi.org/10.1016/j.isci.2023.107472. Copyright © 2023 The Authors.