Aug 24, 2023

Abstract Salivary gland cancers (SGCs) are rare, aggressive cancers without effective treatments when metastasized. We conducted a phase 2 trial evaluating nivolumab (nivo, anti-PD-1) and ipilimumab (ipi, anti-CTLA-4) in 64 patients with metastatic SGC enrolled in two histology-based cohorts (32 patients each): adenoid cystic carcinoma (ACC; cohort 1) and other SGCs (cohort 2). The primary efficacy endpoint (≥4 objective responses) was met in cohort 2 (5/32, 16%) but not in cohort 1 (2/32, 6%). Treatment safety/tolerability and progression-free survival (PFS) were secondary endpoints. Treatment-related adverse events grade ≥3 occurred in 24 of 64 (38%) patients across both cohorts, and median PFS was 4.4 months (95% confidence interval (CI): 2.4, 8.3) and 2.2 months (95% CI: 1.8, 5.3) for cohorts 1 and 2, respectively. We present whole-exome, RNA and T cell receptor (TCR) sequencing data from pre-treatment and on-treatment tumors and immune cell flow cytometry and TCR sequencing from peripheral blood at serial timepoints. Responding tumors universally demonstrated clonal expansion of pre-existing T cells and mutational contraction. Responding ACCs harbored neoantigens, including fusion-derived neoepitopes, that induced T cell responses ex vivo. This study shows that nivo+ipi has limited efficacy in ACC, albeit with infrequent, exceptional responses, and that it could be promising for non-ACC SGCs, particularly salivary duct carcinomas. ClinicalTrials.gov identifier: NCT03172624 . Access options Get Nature+, our best-value online-access subscription $29.99 / 30 days $189.00 per year Prices vary by article type from$1.95 Additional access options: Fig. 2: Pre-treatment and on-treatment immunogenomic profiles of SGCs in the context of treatment response. Fig. 3: Pre-treatment and on-treatment tumor and peripheral blood TCR repertoire analyses. Fig. 4: Neoantigen identification in responding patients with ACC and potential immune-evasion mechanisms in SGC. Data availability A de-identified dataset—containing the clinical features and processed data that underlie results reported in this article derived from tumor whole-exome, RNA and TCR sequencing—has been made available on Zenodo ( https://doi.org/10.5281/zenodo.8180441 ). The relevant sections of the trial protocol, including the statistical analysis plan, have been made available in the Supplementary Information . Raw whole-exome and RNA sequencing data generated in this study have been made publicly available at the Sequence Read Archive under BioProject number PRJNA940989 . The hg37 and hg19 reference genomes are available from https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_000001405.13/ , and the hg38 assembly is available from https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_000001405.26/ . References WHO Classification of Head and Neck Tumours 4th edn (eds EI-Naggar, A. K., Chan, J. K., Grandis, J. R., Takata, T. & Slootweg, P.) (IARC, 2017). Laurie, S. A., Ho, A. L., Fury, M. G., Sherman, E. & Pfister, D. G. Systemic therapy in the management of metastatic or locally recurrent adenoid cystic carcinoma of the salivary glands: a systematic review. Lancet Oncol. 12, 815–824 (2010). Laurie, S. A. & Licitra, L. Systemic therapy in the palliative management of advanced salivary gland cancers. J. Clin. Oncol. 24, 2673–2678 (2006). Fayette, J. et al. NISCAHN: a phase II, multicenter nonrandomized trial aiming at evaluating nivolumab (N) in two cohorts of patients (pts) with recurrent/metastatic (R/M) salivary gland carcinoma of the head and neck (SGCHN), on behalf of the Unicancer Head & Neck Group. J. Clin. Oncol. 37, 6083–6083 (2019). National Cancer Institute. Common Terminology Criteria for Adverse Events (CTCAE) v4.0 (2010). Zehir, A. et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat. Med. 23, 703–713 (2017). Benjamin, D. et al. Calling somatic SNVs and indels with Mutect2. Preprint at bioRxiv https://doi.org/10.1101/861054 (2019). Larson, D. E. et al. SomaticSniper: identification of somatic point mutations in whole genome sequencing data. Bioinformatics 28, 311–317 (2012). Chakravarty, D. et al. OncoKB: a precision oncology knowledge base. JCO Precis. Oncol. 2017, PO.17.00011 (2017). Shen, R. & Seshan, V. E. FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Nucleic Acids Res. 44, e131 (2016). Nazarov, V. et al. Immunarch: bioinformatics analysis of T-cell and B-cell immune repertoires. GitHub https://immunarch.com/ , https://github.com/immunomind/immunarch (2023). Cimen Bozkus, C., Blazquez, A. B., Enokida, T. & Bhardwaj, N. A T-cell-based immunogenicity protocol for evaluating human antigen-specific responses. STAR Protoc. 2, 100758 (2021). Valero, C. et al. Pretreatment neutrophil-to-lymphocyte ratio and mutational burden as biomarkers of tumor response to immune checkpoint inhibitors. Nat. Commun. 12, 729 (2021). Mayakonda, A., Lin, D. C., Assenov, Y., Plass, C. & Koeffler, H. P. Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res. 28, 1747–1756 (2018). Acknowledgements We are grateful to our patients and their families for their bravery and support of cancer research. This study was supported, in part, by National Institutes of Health (NIH) grant R01 DE027738 (to L.G.T.M., A.L.H. and T.A.C. ); the Geoffrey Beene Cancer Research Center (to L.G.T.M. and A.L.H. ); the Jayme and Peter Flowers Fund; the Sebastian Nativo Fund; Congressionally Directed Medical Research Programs Award CA210784 and the MSK Population Science Research Program (to L.G.T.M. ); the Overman Fund (to A.L.H. ); NIH grants R37 CA259177, R01 CA269733 and P50 CA217694 (to C.A.K. ); and NIH/NCI Cancer Center Support Grant P30 CA008748 (institutional, to MSKCC). Bristol Myers Squibb provided the study drugs and funding (institutional, to MSKCC) to support conduct of the clinical trial, including research biopsies, but was not involved in data analysis,manuscript writing or the decision to submit this manuscript. In addition, we acknowledge using the MSKCC Integrated Genomics Operation Core, funded by NCI Cancer Center Support Grant P30 CA08748, Cycle for Survival and the Marie-Josée and Henry R. Kravis Center for Molecular Oncology. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Author information These authors jointly supervised this work: Alan L. Ho, Luc G. T. Morris. Authors and Affiliations Head and Neck Service and Immunogenomic Oncology Platform, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA Joris L. Vos, Swati Jain, Conall W. R. Fitzgerald, Fengshen Kuo, Catherine Y. Han, Zaineb Nadeem, Wei Yang, Manu Prasad & Luc G. T. Morris Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA Bharat Burman, Eric J. Sherman, Lara A. Dunn, James V. Fetten, Loren S. Michel, Anuja Kriplani, Kenneth K. Ng, Juliana Eng, David G. Pfister, Christopher A. Klebanoff & Alan L. Ho Department of Medicine, Maine Medical Center–Tufts University School of Medicine, Portland, ME, USA Vatche Tchekmedyian Sofia Haque Nora Katabi Vladimir Makarov, Raghvendra M. Srivastava & Timothy A. Chan Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA Irina Ostrovnaya Department of Head and Neck Oncology and Surgery, The Netherlands Cancer Institute – Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands Charlotte L. Zuur Charlotte L. Zuur Nadeem Riaz Christopher A. Klebanoff Christopher A. Klebanoff Bharat Burman Swati Jain Conall W. R. Fitzgerald Eric J. Sherman Lara A. Dunn James V. Fetten Loren S. Michel Anuja Kriplani Kenneth K. Ng Juliana Eng Vatche Tchekmedyian Sofia Haque Nora Katabi Fengshen Kuo Catherine Y. Han Zaineb Nadeem Wei Yang Vladimir Makarov Raghvendra M. Srivastava Irina Ostrovnaya Manu Prasad Charlotte L. Zuur Nadeem Riaz David G. Pfister Christopher A. Klebanoff Timothy A. Chan Alan L. Ho Luc G. T. Morris Contributions Trial conceptualization: A.L.H. and L.G.T.M. Methodology and protocol writing: A.L.H. and L.G.T.M. Investigation (clinical trial): A.L.H., L.G.T.M., D.G.P., N.K., S.H., J.E., K.K.N., A.K., L.S.M., J.V.F., L.A.D. and E.J.S. Investigation (experimental): S.J., W.Y. and M.P. Data curation: J.L.V., B.B., C.W.R.F., V.T., A.L.H. and L.G.T.M. Formal analysis: J.L.V., B.B., S.J., F.K., V.M. and I.O. Resources: C.A.K., A.L.H. and L.G.T.M. Writing (original draft): J.L.V., B.B., S.J., A.L.H. and L.G.T.M. Writing (review and editing): all authors. Visualization: J.L.V., S.J., A.L.H. and L.G.T.M. Supervision: A.L.H. and L.G.T.M. Project administration: Z.N. Funding acquisition: A.L.H. and L.G.T.M. Corresponding authors Competing interests A.L.H. reports research funding for clinical trials from Allos Therapeutics, Astellas Pharma, AstraZeneca, Bayer, Ayala Pharmaceuticals, Bristol Myers Squibb, Genentech, Celldex Therapeutics, Daiichi Sankyo, Eisai., Elevar Therapeutics, Eli Lilly & Company, Genentech/Roche, Hoikpia, Kolltan Pharmaceuticals, Kura Oncology, Merck, Novartis, Pfizer, Poseida and Verastem; service in consulting/advisory roles for AffyImmune Therapeutics, AstraZeneca, Ayala Pharmaceuticals, Bristol Myers Squibb, Cellestia Biotech, Coherus, CureVac, Eisai, Elevar Therapeutics, Exelixis, Expert Conncet, Genzyme, InxMed, Kura Oncology, McGivney Global Advisors, Merck, Novartis, CureVac, Prelude Therapeutics, Regeneron, Rgenta, Remix Therapeutics, Sanofi, Sun Pharma, the Chemotherapy Foundation and TRM Oncology; service on speakers’ bureaus for Medscape, Omniprex America, Novartis and Physician Education Resource; and receipt of travel/accommodations expenses from Janssen Oncology, Merck, Kura Oncology, Ignyta, Ayala Pharmaceuticals and KLUS Pharma, outside the submitted work. A.L.H. is also inventor on a patent for the use of lesional dosimetry methods for tailoring targeted radiotherapy in cancer. L.G.T.M. is listed as an inventor on intellectual property held by MSK on using tumor mutation burden to predict immunotherapy response, with pending patent, which has been licensed to Personal Genome Diagnostics. T.A.C. reports, all outside the submitted work, being a co-founder of Gritstone Oncology and holding equity; holding equity in An2H and acknowledging grant funding from Bristol Myers Squibb, AstraZeneca, Illumina, Pfizer, An2H and Eisai; having served as an advisor for Bristol Myers, MedImmune, Squibb, Illumina, Eisai, AstraZeneca and An2H; andd being an inventor on intellectual property held by MSK on using tumor mutation burden to predict immunotherapy response, with pending patent, which has been licensed to Personal Genome Diagnostics. C.A.K. is a scientific co-founder and equity holder of Affini-T Therapeutics; is a compensated member of the scientific and/or clinical advisory boards for Achilles Therapeutics, Affini-T Therapeutics, Aleta BioTherapeutics, Bellicum Pharmaceuticals, Catamaran Bio, Obsidian Therapeutics and T-knife; has consulted for Bristol Myers Squibb, Decheng Capital, PACT Pharma and Roche/Genentech; and has patents broadly related to cell and gene therapy outside the scope of this work. N.R. reports research funding from ArcherDx and Repare Therapeutics and personal fees from Illumina, PaigeAI and Pfizer Canada, outside the submitted work. E.J.S. reports institutional research funding from Merck, outside the submitted work, and personal fees from Eli Lilly & Company, Blueprint Medicines Corporation, Regeneron Pharmaceuticals, Loxo Oncology and Eisai, outside the submitted work. L.A.D. reports research funding and personal fees from CUE-101, Eisai, CUE-101, Replimune Group and Regeneron Pharmaceuticals and service on an advisory board at Merck, outside the submitted work. V.T. reports holding stock in Infinity Pharmaceuticals, Bluebird Bio and Mersana Therapeutics. C.L.Z. is linked to investigator-initiated clinical trials in collaboration with Bristol Myers Squibb, outside the submitted work. D.G.P. reports grants from the National Institutes of Health (NIH) and the Philanthropy–Serra Fund; research support from Hookipa Pharma; and personal fees from Nykode and Hookipa Pharma, outside the submitted work. B.B. is an employee of AstraZeneca. Z.N. is an employee of PPD, part of Thermo Fisher Scientific. W.Y. is an employee of Eli Lilly & Company. V.M. is listed as an inventor on a patent assigned to MSK broadly related to determinants of cancer response to immunotherapy. J.L.V., S.J., C.W.R.F., F.K., C.Y.H., M.P., N.K., R.M.S., I.O., A.K., L.S.M., J.V.F., K.K.N., J.E. and S.H. declare no competing interests. Peer review Peer review information Nature Medicine thanks Clint Allen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary handling editors: Ulrike Harjes and Saheli Sadanand, in collaboration with the Nature Medicine team. Additional information Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Extended data In b and c, all 64 patients are shown. Patients are grouped per cohort and according to the molecular profile method used (WES or targeted next-generation sequencing (tNGS) with the MSK-IMPACT panel); non-ACC patients are further grouped by histologic subtype. Tracks for genes were limited to show only the genes included in the MSK-IMPACT468 panel (Supplementary Table  4 ). a. Trial overview flowchart. The numbers for WES, RNAseq, and TCRseq refer to the samples that were subject to these investigations and passed quality control. Cartoons representing tumor and blood samples were created using BioRender.com. b. From top to bottom: patient trial ID, MYB-NFIB fusion gene presence, percentage of tumor cells (TC) staining positive for PD-L1, objective response (OR), mutation status for the top 15 most frequently mutated genes, the molecular profiling method used for each sample, the WES-based (FACETS) ploidy and purity estimate, and number of mutations per exome (WES-based) or TMB score (tNGS-based). c. From top to bottom: patient trial ID, the histologic subtype per the WHO classification, PD-L1 %TC staining, androgen and HER2-receptor status (performed as part of routine clinical care; only on suspected salivary duct carcinomas), OR, status for the top 15 most frequently mutated genes, the molecular profiling method used for that sample, the FACETS-based ploidy and purity estimate, and number of mutations per exome (WES-based) or TMB score (tNGS-based). Pos, positive; Neg, negative; OR, objective response; R, response; NR, no response; NE, not evaluable; SDC, salivary duct carcinoma; ca, carcinoma; NOS, not otherwise specified; CAMSG, cribriform adenocarcinoma of the minor salivary gland; SWI/SNF, SWItch/Sucrose Non-Fermentable; ex pleo, ex pleomorphic adenoma; AR, androgen receptor; WES, whole-exome sequencing; tNGS, targeted next-generation sequencing. Box plots defined in  Methods . Individual dot colors in a, b, d–f indicate SGC histology. A Kruskal-Wallis (a, b) or two-sided Wilcoxon rank-sum test (d–f) was used to calculate exact P-values. P-values in a, b, d were adjusted for multiplicity ( Methods ), yielding q-values. a. Non-synonymous mutation count per exome in ACC (n = 21), SDC (n = 5), and SGCs of other histologies (n = 10). b. Z-scores for the ESTIMATE T cell and immune infiltration score (TIS and IIS), ImmuneScore, Reactome interferon gamma (IFN-γ), and cytolytic activity (CYT) RNA signatures in ACC (n = 15), SDC (n = 4), and SGCs of other histologies (n = 8). c. Heatmap of the signatures shown in b. Top tracks represent sample histology and objective response of n = 27 samples. d. Values for the MDSC, M2 TAM, and CAF RNA signatures in NR (n = 23) and R tumor samples (n = 4). e. Mean evolutionary divergence of germline HLA (HED), obtained from healthy control WES data, in NR (n = 31) and R patients (n = 5). f. Peripheral blood neutrophil-to-lymphocyte ratio (NLR) in NR (n = 56) and R patients (n = 8). Box plots defined in  Methods . Dot colors in b, e indicate histology and two-sided Wilcoxon rank-sum tests were used to calculate exact P-values. Panel f shows linear models with regression lines flanked by 95% CIs. Spearman’s rho and two-tailed P-values are printed in f. P-values in b, e were multiplicity-adjusted ( Methods ), yielding q-values. a. Waterfall plot of the log2-fold change in mutation count from pre-treatment to on-treatment. Bar colors represent response. Top track shows histology. b. Log2-fold change in mutation count from pre-treatment to on-treatment in sample pairs for in R (n = 4) and NR patients (n = 20). c. Proportion of lost mutations with a variant allele frequency of ≥0.10, 0.08–0.09, 0.05–0.07, and <0.05. The denominator is the sum of variants that were lost upon treatment, in NR and R patients. Comparisons of proportions between NR and R patients are printed to the right of the plot; P-values were calculated using a χ2 test. d. Waterfall plot showing the absolute change in tumor purity from pre-treatment to on-treatment. Color indicates if the WES-based FACETS or RNAseq-based ESTIMATE tool was used. The order of samples in the plot is identical to the waterfall plot in a. Two samples are marked NA (no RNAseq and a diploid copy number precluding purity estimation from FACETS). e. Absolute change in tumor purity for sample pairs from pre- to on-treatment (see d) in R (n = 3) and NR patients (n = 19). f. Linear regression of the TCR-enumerated T cell count versus the ImmuneScore, IIS, CYT, IFN-γ, and TIS RNA signatures (n = 13 pre-treatment and n = 13 on-treatment combined). g. Heatmap of the change (on-treatment minus pre-treatment) in immune cell populations, checkpoints, and antigen presentation machinery (APM) RNA signatures. h. Correlation matrix of the change in immune-related RNA signatures. Circle color represents Spearman’s rho (also printed). All correlations were statistically significant (P < 0.05). Boxes are defined in  Methods . Panels a and b show linear models with regression lines flanked by 95% CIs; Spearman’s rho and exact, two-tailed P-values are printed. In a and b, squares and circles represent NR and R samples, respectively. Dot colors in a, b, d, and line colors in c indicate SGC histology. P-values in c, d, and g were calculated using two-sided Wilcoxon rank-sum tests and adjusted for multiplicity ( Methods ), yielding q-values. a. Absolute change in mutation count per exome versus the absolute change in TCR-enumerated T cell count (n = 18). b. Absolute change in WES-based sample purity estimates versus the absolute change in TCR-enumerated T cell count (n = 16). c. Productive Simpson TCR repertoire clonality of pre-treatment and on-treatment R (n = 3) and NR (n = 15) samples. Lines connect a sample pair. d. Morisita-Horn similarity index between the pre-treatment and on-treatment TCR repertoires in R (n = 3) and NR (n = 15) patients. e. On-treatment trajectories of T-cell clonotypes considered predominant (top 1% of the productive frequency distribution in that sample) in pre-treatment tumors, for R (n = 3) and NR (n = 15) samples. Clones maintained upon treatment are shown in orange, lost clones in gray. P-value was calculated using a χ2-test and adjusted for multiplicity ( Methods ). f. Total number of TCR clones considered significantly expanded (see Fig. 3g,h ) in individual patients. The fraction that is pre-existing or novel is indicated. Patients’ trial IDs are printed. g. Total number of expanded TCR clonotypes in responders (n = 3) and non-responders (n = 15). h. TCR repertoire overlap between the tumor and peripheral blood for three responding patients (44, 5, and 41) at pre-treatment and on-treatment. For patient 5 with an additional, 336 d blood sample available (‘1 yr’), the TCR overlap between the 336 d sample and the early on-treatment (week 6) tumor was calculated. Gating strategy available in the  Supplementary Information . Boxes are defined in the  Methods . Line and dot colors indicate response. Two-tailed, exact P-values were calculated using a Wilcoxon signed rank (a, c) or rank sum test (b). Nominal P-values were adjusted for multiplicity ( Methods ). a. The percentage of peripheral CD8+ T cells expressing Ki-67 (left plot) or ICOS (right plot) at the pre-treatment and week 6 on-treatment time point for 27 ACC patients. b. Log2-fold change in Ki-67 (left plot) and ICOS (right plot) surface expression in peripheral CD8+PD1– and CD8+PD1+ T cells for 27 ACC patients. c. Box plots showing the percentage of peripheral CD8+Ki67+ T cells expressing immune checkpoints CTLA-4, LAG-3, PD-1, or TIM-3 at the pre-treatment and on-treatment time points for 27 ACC patients. Data in a and c–e are representative of two independent experiments with either n = 3 (a, d) or n = 2 (c, e) technical replicates. In a and c–e, the black horizontal bars indicate the mean of replicate experiments, and the dotted gray lines represent the mean of the negative control experiment. In a and d, the whiskers represent the standard deviation. a. Autologous T cells from patient 41 were co-cultured with a pool of HLA and individual TMG co-transfected COS-7 cells. T cell responses were measured by IFN-γ ELISpot assay. Untransfected COS-7 cells (no TMG) were co-cultured with T cells for background response determination. b. Representative flow cytometry plots showing CD137 upregulation on CD8+ T cells as an activation marker after restimulation with MYB-NFIB fusion breakpoint-derived short peptides (SP1–4). The DMSO-stimulated T cell response was used to estimate the background activity. Fluorescence minus one (FMO) control was used to set the gate for CD137 expression. c. Interferon-γ production from T cells in ELISpot assay after co-culture with autologous DCs electroporated with TMGs in patient 5. The negative control consisted of co-culture with DCs only. d. Repeat IFN-γ ELISpot from peripheral blood effector memory T cells (CD3+CD45RA–CCR7–) in patient 5, after co-culture with autologous DCs electroporated with TMG constructs. The negative control consisted of co-culture with DCs only. e. IFN-γ ELISpot from patient 5’s peripheral blood T cells upon co-culture with autologous DCs pulsed with peptides translated from the variants from two SNV TMGs and one in-frame INDEL TMG. The negative control consisted of co-culture with DCs only. Extended Data Table 1 BORs for cohort 1 (ACC) and cohort 2 (non-ACC) patients