Multimodal pooled Perturb-CITE-seq screens in patient models define mechanisms of cancer immune evasion
Name
2020.09.01.267211v1.full.pdf
Description
Submitted version
Size
1.8 MB
Format
Unknown
Checksum (MD5)
11a9c10d6ede78512155daa78f21854b
Author(s)
Frangieh, Chris J.
Melms, Johannes C.
Thakore, Pratiksha I.
Geiger-Schuller, Kathryn R.
Ho, Patricia
Luoma, Adrienne M.
Cleary, Brian
Jerby-Arnon, Livnat
Malu, Shruti
Cuoco, Michael S.
Date Issued
March 2021
Journal
Nature Genetics
Publisher
Springer Science and Business Media LLC
Version
Original manuscript
Abstract
© 2021, The Author(s), under exclusive licence to Springer Nature America, Inc. Resistance to immune checkpoint inhibitors (ICIs) is a key challenge in cancer therapy. To elucidate underlying mechanisms, we developed Perturb-CITE-sequencing (Perturb-CITE-seq), enabling pooled clustered regularly interspaced short palindromic repeat (CRISPR)–Cas9 perturbations with single-cell transcriptome and protein readouts. In patient-derived melanoma cells and autologous tumor-infiltrating lymphocyte (TIL) co-cultures, we profiled transcriptomes and 20 proteins in ~218,000 cells under ~750 perturbations associated with cancer cell-intrinsic ICI resistance (ICR). We recover known mechanisms of resistance, including defects in the interferon-γ (IFN-γ)–JAK/STAT and antigen-presentation pathways in RNA, protein and perturbation space, and new ones, including loss/downregulation of CD58. Loss of CD58 conferred immune evasion in multiple co-culture models and was downregulated in tumors of melanoma patients with ICR. CD58 protein expression was not induced by IFN-γ signaling, and CD58 loss conferred immune evasion without compromising major histocompatibility complex (MHC) expression, suggesting that it acts orthogonally to known mechanisms of ICR. This work provides a framework for the deciphering of complex mechanisms by large-scale perturbation screens with multimodal, single-cell readouts, and discovers potentially clinically relevant mechanisms of immune evasion.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Biology
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1038/s41588-021-00779-1
