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Zhang H, Lee S, Muthakana RR, Lu B, Boone DN, Lee D, Wang XS. Intragenic Rearrangement Burden Associates with Immune Cell Infiltration and Response to Immune Checkpoint Blockade in Cancer. Cancer Immunol Res 2024; 12:287-295. [PMID: 38345376 DOI: 10.1158/2326-6066.cir-22-0637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 02/27/2023] [Accepted: 12/21/2023] [Indexed: 03/06/2024]
Abstract
Immune checkpoint blockade (ICB) can induce durable cancer remission. However, only a small subset of patients gains benefits. While tumor mutation burden (TMB) differentiates responders from nonresponders in some cases, it is a weak predictor in tumor types with low mutation rates. Thus, there is an unmet need to discover a new class of genetic aberrations that predict ICB responses in these tumor types. Here, we report analyses of pan-cancer whole genomes which revealed that intragenic rearrangement (IGR) burden is significantly associated with immune infiltration in breast, ovarian, esophageal, and endometrial cancers, particularly with increased M1 macrophage and CD8+ T-cell signatures. Multivariate regression against spatially counted tumor-infiltrating lymphocytes in breast, endometrial, and ovarian cancers suggested that IGR burden is a more influential covariate than other genetic aberrations in these cancers. In the MEDI4736 trial evaluating durvalumab in esophageal adenocarcinoma, IGR burden correlated with patient benefits. In the IMVigor210 trial evaluating atezolizumab in urothelial carcinoma, IGR burden increased with platinum exposure and predicted patient benefit among TMB-low, platinum-exposed tumors. Altogether, we have demonstrated that IGR burden correlates with T-cell inflammation and predicts ICB benefit in TMB-low, IGR-dominant tumors, and in platinum-exposed tumors.
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Affiliation(s)
- Han Zhang
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Sanghoon Lee
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Renee R Muthakana
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Binfeng Lu
- Center for Discovery and Innovation, Hackensack Meridian Health, Nutley, New Jersey
| | - David N Boone
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Daniel Lee
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Xiao-Song Wang
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania
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