Background: High tumor mutation burden (TMB-H) has been proposed as a predictive biomarker for response to immune checkpoint blockade (ICB), largely due to the potential for tumor mutations to generate immunogenic neoantigens. Despite recent pan-cancer approval of ICB treatment for any TMB-H tumor, as assessed by the targeted FoundationOne CDx assay in nine tumor types, the utility of this biomarker has not been fully demonstrated across all cancers. Patients and methods: Data from over 10 000 patient tumors included in The Cancer Genome Atlas were used to compare approaches to determine TMB and identify the correlation between predicted neoantigen load and CD8 T cells. Association of TMB with ICB treatment outcomes was analyzed by both objective response rates (ORRs, N ¼ 1551) and overall survival (OS, N ¼ 1936). Results: In cancer types where CD8 T-cell levels positively correlated with neoantigen load, such as melanoma, lung, and bladder cancers, TMB-H tumors exhibited a 39.8% ORR to ICB [95% confidence interval (CI) 34.9-44.8], which was significantly higher than that observed in low TMB (TMB-L) tumors [odds ratio (OR) ¼ 4.1, 95% CI 2.9-5.8, P < 2 Â 10 À16 ]. In cancer types that showed no relationship between CD8 T-cell levels and neoantigen load, such as breast cancer, prostate cancer, and glioma, TMB-H tumors failed to achieve a 20% ORR (ORR ¼ 15.3%, 95% CI 9.2-23.4, P ¼ 0.95), and exhibited a significantly lower ORR relative to TMB-L tumors (OR ¼ 0.46, 95% CI 0.24-0.88, P ¼ 0.02). Bulk ORRs were not significantly different between the two categories of tumors (P ¼ 0.10) for patient cohorts assessed. Equivalent results were obtained by analyzing OS and by treating TMB as a continuous variable. Conclusions: Our analysis failed to support application of TMB-H as a biomarker for treatment with ICB in all solid cancer types. Further tumor type-specific studies are warranted.

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Immune checkpoint blockade (ICT) has provided robust, durable responses to a subset of patients. Many initial ICT trials were focused on highly mutated cancer types, such as melanoma and lung cancer, largely predicated on the idea that mutation-derived neoantigens would allow for generation of tumor-specific T cells. Subsequent analysis of patient responses in these highly mutated cancer types confirmed that increased tumor mutation burden (TMB) corresponded with improved patient outcomes. Further clinical studies identified additional predictive biomarkers, such as PD-L1 protein expression, and various gene expression signatures. Based on the success of ICT in hypermutated cancer types, further clinical trials with ICT were performed in cancers with overall lower mutational burden. These studies have indicated that many non-hypermutated cancer types with relatively low TMB may be effectively treated with ICT. For example, patients with clear cell renal cell carcinoma (ccRCC) display relatively low TMB overall, and a narrow distribution of TMB across patients, yet clinical response rates to ICT are ~30%, with some durable responses seen. Other tumor types with minimal mutation burdens, including glioblastoma (GBM) and triple negative breast cancer (TNBC), have likewise shown encouraging clinical responses to ICT. We recently demonstrated distinct tumor immunobiology between hypermutated and non-hypermutated tumor types, notably that relative neoantigen load/tumor mutation burden was only a relevant factor for immune infiltration in hypermutated tumor types. Consistent with this, clinical trials have demonstrated that TMB does not predict response to ICT in tumor types with minimal mutational load, such as breast cancer, ccRCC, and GBM. Thus, there remains a critical gap in knowledge as to how to identify which patients with non-hypermutated cancer may benefit from ICT. Here, we demonstrate that a replication stress response (RSR) defect gene expression signature accurately predicts ICT response in 11 independent non-hypermutated patient cohorts from 6 tumor types for which other biomarkers failed. Pre-clinical studies indicate that aberrant origin firing in RSR deficient tumor cells causes exhaustion of replication protein A, resulting in accumulation of immunostimulatory cytosolic DNA. Induction or suppression of RSR deficiencies was sufficient to modulate response to ICT. Taken together, the RSR defect gene signature can accurately identify patients who will benefit from ICT across numerous non-hypermutated tumor types, and pharmacological induction of RSR defects may further expand the benefits of ICT to more patients. Citation Format: D McGrail, P Pilié, XHF Zhang, J Rosen, L Voorwerk, M Kok, A Heimberger, C Peterson, E Jonasch, S Lin. Replication stress response defects predict responses to ICT in non-hypermutated tumors [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr SP084.