Combined TCR Repertoire Profiles and Blood Cell Phenotypes Predict Melanoma Patient Response to Personalized Neoantigen Therapy plus Anti-PD-1
Asaf Poran, Julian Scherer, Meghan E Bushway, Rana Besada, Kristen N Balogh, Amy Wanamaker, Reid G Williams, Jasmina Prabhakara, Patrick A Ott, Siwen Hu-Lieskovan, Zakaria S Khondker, Richard B Gaynor, Michael S Rooney, Lakshmi Srinivasan, Asaf Poran, Julian Scherer, Meghan E Bushway, Rana Besada, Kristen N Balogh, Amy Wanamaker, Reid G Williams, Jasmina Prabhakara, Patrick A Ott, Siwen Hu-Lieskovan, Zakaria S Khondker, Richard B Gaynor, Michael S Rooney, Lakshmi Srinivasan
Abstract
T cells use highly diverse receptors (TCRs) to identify tumor cells presenting neoantigens arising from genetic mutations and establish anti-tumor activity. Immunotherapy harnessing neoantigen-specific T cells to target tumors has emerged as a promising clinical approach. To assess whether a comprehensive peripheral mononuclear blood cell analysis predicts responses to a personalized neoantigen cancer vaccine combined with anti-PD-1 therapy, we characterize the TCR repertoires and T and B cell frequencies in 21 patients with metastatic melanoma who received this regimen. TCR-α/β-chain sequencing reveals that prolonged progression-free survival (PFS) is strongly associated with increased clonal baseline TCR repertoires and longitudinal repertoire stability. Furthermore, the frequencies of antigen-experienced T and B cells in the peripheral blood correlate with repertoire characteristics. Analysis of these baseline immune features enables prediction of PFS following treatment. This method offers a pragmatic clinical approach to assess patients' immune state and to direct therapeutic decision making.
Trial registration: ClinicalTrials.gov NCT02897765.
Keywords: NEO-PV-01; T cell clonality; TCR repertoire; anti-PD-1; cancer vaccines; flow cytometry; immunotherapy; melanoma; predictive biomarkers.
Conflict of interest statement
A.P., J.S., M.E.B., R.B., K.N.B., A.W., R.G.W., J.P., Z.S.K., M.S.R., and L.S. are/were all employees and/or equity holders at BioNTech US (formerly Neon Therapeutics, Inc.). P.A.O.: research funding paid to the institution: BMS, Merck, AstraZeneca, Celldex, CytomX, Glaxo Smith Kline, ARMO Biosciences; Neon Therapeutics, Consultant: Array, BMS, Merck, Genentech, Pfizer, Novartis, Neon Therapeutics, CytomX, Celldex. S.H.-L.: consultant to Amgen, BMS, Genmab, Xencor; Research support from BMS, Merck and Vaccinex. R.B.G.: Board of Directors, Alkermes plc and Infinity Pharmaceuticals and Scientific Advisory Board, Leap Therapeutics; stockholder and employee of BioNTech US (formerly Neon Therapeutics, Inc.).
© 2020 The Author(s).
Figures
References
- Coley W.B. II. Contribution to the Knowledge of Sarcoma. Ann. Surg. 1891;14:199–220.
- Ehrlich P. Über den jetzigen Stand der Chemotherapie. Ber. Dtsch. Chem. Ges. 1909;42:17–47.
- Finn O.J. Immuno-oncology: understanding the function and dysfunction of the immune system in cancer. Ann. Oncol. 2012;23:viii6–viii9.
- Matsushita H., Vesely M.D., Koboldt D.C., Rickert C.G., Uppaluri R., Magrini V.J., Arthur C.D., White J.M., Chen Y.-S., Shea L.K. Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature. 2012;482:400–404.
- Schumacher T.N., Schreiber R.D. Neoantigens in cancer immunotherapy. Science. 2015;348:69–74.
- Gubin M.M., Artyomov M.N., Mardis E.R., Schreiber R.D. Tumor neoantigens: building a framework for personalized cancer immunotherapy. J. Clin. Invest. 2015;125:3413–3421.
- Ott P.A., Hu-Lieskovan S., Chmielowski B., Govindan R., Naing A., Bhardwaj N., Margolin K., Awad M.M., Hellmann M.D., Lin J.J. A Phase Ib Trial of Personalized Neoantigen Therapy Plus Anti-PD-1 in Patients with Advanced Melanoma, Non-small Cell Lung Cancer, or Bladder Cancer. Cell. 2020;183:347–362.
- Postow M.A., Manuel M., Wong P., Yuan J., Dong Z., Liu C., Perez S., Tanneau I., Noel M., Courtier A. Peripheral T cell receptor diversity is associated with clinical outcomes following ipilimumab treatment in metastatic melanoma. J. Immunother. Cancer. 2015;3:23.
- Hosoi A., Takeda K., Nagaoka K., Iino T., Matsushita H., Ueha S., Aoki S., Matsushima K., Kubo M., Morikawa T. Increased diversity with reduced “diversity evenness” of tumor infiltrating T-cells for the successful cancer immunotherapy. Sci. Rep. 2018;8:1058.
- Kirsch I., Vignali M., Robins H. T-cell receptor profiling in cancer. Mol. Oncol. 2015;9:2063–2070.
- Fairfax B.P., Taylor C.A., Watson R.A., Nassiri I., Danielli S., Fang H., Mahé E.A., Cooper R., Woodcock V., Traill Z. Peripheral CD8+ T cell characteristics associated with durable responses to immune checkpoint blockade in patients with metastatic melanoma. Nat. Med. 2020;26:193–199.
- Hogan S.A., Courtier A., Cheng P.F., Jaberg-Bentele N.F., Goldinger S.M., Manuel M., Perez S., Plantier N., Mouret J.-F., Nguyen-Kim T.D.L. Peripheral Blood TCR Repertoire Profiling May Facilitate Patient Stratification for Immunotherapy against Melanoma. Cancer Immunol. Res. 2019;7:77–85.
- Hopkins A.C., Yarchoan M., Durham J.N., Yusko E.C., Rytlewski J.A., Robins H.S., Laheru D.A., Le D.T., Lutz E.R., Jaffee E.M. T cell receptor repertoire features associated with survival in immunotherapy-treated pancreatic ductal adenocarcinoma. JCI Insight. 2018;3:e122092.
- Valpione S., Galvani E., Tweedy J., Mundra P.A., Banyard A., Middlehurst P., Barry J., Mills S., Salih Z., Weightman J. Immune-awakening revealed by peripheral T cell dynamics after one cycle of immunotherapy. Nat. Can. 2020;1:210–221.
- Hogan S.A., Levesque M.P., Cheng P.F. Melanoma Immunotherapy: Next-Generation Biomarkers. Front. Oncol. 2018;8:178.
- Nixon A.B., Schalper K.A., Jacobs I., Potluri S., Wang I.-M., Fleener C. Peripheral immune-based biomarkers in cancer immunotherapy: can we realize their predictive potential? J. Immunother. Cancer. 2019;7:325.
- Krieg C., Nowicka M., Guglietta S., Schindler S., Hartmann F.J., Weber L.M., Dummer R., Robinson M.D., Levesque M.P., Becher B. High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy. Nat. Med. 2018;24:144–153.
- Lalani A.A., Xie W., Martini D.J., Steinharter J.A., Norton C.K., Krajewski K.M., Duquette A., Bossé D., Bellmunt J., Van Allen E.M. Change in Neutrophil-to-lymphocyte ratio (NLR) in response to immune checkpoint blockade for metastatic renal cell carcinoma. J. Immunother. Cancer. 2018;6:5.
- Sacdalan D.B., Lucero J.A., Sacdalan D.L. Prognostic utility of baseline neutrophil-to-lymphocyte ratio in patients receiving immune checkpoint inhibitors: a review and meta-analysis. OncoTargets Ther. 2018;11:955–965.
- Weber R., Fleming V., Hu X., Nagibin V., Groth C., Altevogt P., Utikal J., Umansky V. Myeloid-Derived Suppressor Cells Hinder the Anti-Cancer Activity of Immune Checkpoint Inhibitors. Front. Immunol. 2018;9:1310.
- Wang C., Sanders C.M., Yang Q., Schroeder H.W., Jr., Wang E., Babrzadeh F., Gharizadeh B., Myers R.M., Hudson J.R., Jr., Davis R.W., Han J. High throughput sequencing reveals a complex pattern of dynamic interrelationships among human T cell subsets. Proc. Natl. Acad. Sci. USA. 2010;107:1518–1523.
- Britanova O.V., Putintseva E.V., Shugay M., Merzlyak E.M., Turchaninova M.A., Staroverov D.B., Bolotin D.A., Lukyanov S., Bogdanova E.A., Mamedov I.Z. Age-related decrease in TCR repertoire diversity measured with deep and normalized sequence profiling. J. Immunol. 2014;192:2689–2698.
- Lindau P., Mukherjee R., Gutschow M.V., Vignali M., Warren E.H., Riddell S.R., Makar K.W., Turtle C.J., Robins H.S. Cytomegalovirus Exposure in the Elderly Does Not Reduce CD8 T Cell Repertoire Diversity. J. Immunol. 2019;202:476–483.
- Thomas P.G., Handel A., Doherty P.C., La Gruta N.L. Ecological analysis of antigen-specific CTL repertoires defines the relationship between naive and immune T-cell populations. Proc. Natl. Acad. Sci. USA. 2013;110:1839–1844.
- Hanson A.L., Nel H.J., Bradbury L., Phipps J., Thomas R., Lê Cao K.A., Kenna T.J., Brown M.A. Altered Repertoire Diversity and Disease-Associated Clonal Expansions Revealed by T Cell Receptor Immunosequencing in Ankylosing Spondylitis Patients. Arthritis Rheumatol. 2020;72:1289–1302.
- Jia Q., Zhou J., Chen G., Shi Y., Yu H., Guan P., Lin R., Jiang N., Yu P., Li Q.-J., Wan Y. Diversity index of mucosal resident T lymphocyte repertoire predicts clinical prognosis in gastric cancer. OncoImmunology. 2015;4:e1001230.
- Thapa D.R., Tonikian R., Sun C., Liu M., Dearth A., Petri M., Pepin F., Emerson R.O., Ranger A. Longitudinal analysis of peripheral blood T cell receptor diversity in patients with systemic lupus erythematosus by next-generation sequencing. Arthritis Res. Ther. 2015;17:132.
- Morris H., DeWolf S., Robins H., Sprangers B., LoCascio S.A., Shonts B.A., Kawai T., Wong W., Yang S., Zuber J. Tracking donor-reactive T cells: Evidence for clonal deletion in tolerant kidney transplant patients. Sci. Trans. Med. 2015;7:272ra10.
- Putintseva E.V., Britanova O.V., Staroverov D.B., Merzlyak E.M., Turchaninova M.A., Shugay M., Bolotin D.A., Pogorelyy M.V., Mamedov I.Z., Bobrynina V. Mother and child T cell receptor repertoires: deep profiling study. Front. Immunol. 2013;4:463.
- Oakes T., Heather J.M., Best K., Byng-Maddick R., Husovsky C., Ismail M., Joshi K., Maxwell G., Noursadeghi M., Riddell N. Quantitative Characterization of the T Cell Receptor Repertoire of Naïve and Memory Subsets Using an Integrated Experimental and Computational Pipeline Which Is Robust, Economical, and Versatile. Front. Immunol. 2017;8:1267.
- Helmink B.A., Reddy S.M., Gao J., Zhang S., Basar R., Thakur R., Yizhak K., Sade-Feldman M., Blando J., Han G. B cells and tertiary lymphoid structures promote immunotherapy response. Nature. 2020;577:549–555.
- Ochsenreither S., Fusi A., Wojtke S., Busse A., Nüssler N.C., Thiel E., Keilholz U., Nagorsen D. Comparison of T-cell receptor repertoire restriction in blood and tumor tissue of colorectal cancer patients. J. Transl. Med. 2010;8:35.
- Reuben A., Zhang J., Chiou S.-H., Gittelman R.M., Li J., Lee W.-C., Fujimoto J., Behrens C., Liu X., Wang F. Comprehensive T cell repertoire characterization of non-small cell lung cancer. Nat. Commun. 2020;11:603.
- Bolotin D.A., Poslavsky S., Mitrophanov I., Shugay M., Mamedov I.Z., Putintseva E.V., Chudakov D.M. MiXCR: software for comprehensive adaptive immunity profiling. Nat. Methods. 2015;12:380–381.
- Signorell A. 2020. DescTools: Tools for Descriptive Statistics.R package version 0.99.32.
- Drost H.-G. Philentropy: Information Theory and Distance Quantification with R. J. Open Source Softw. 2018;3:765.
- Warnes G.R., Bolker B., Bonebakker L., Gentleman R., Liaw W.H.A., Lumley T., Maechler M., Magnusson A., Moeller S., Schwartz M. 2015. gplots: Various R Programming Tools for Plotting Data.
- R Core Team . R Foundation for Statistical Computing; 2018. R: A Language and Environment for Statistical Computing.
- Therneau T.M., Grambsch P.M. Springer; 2000. Modeling Survival Data: Extending the Cox Model.
- Kassambara A., Kosinski M., Biecek P. 2019. survminer: Drawing Survival Curves using “ggplot2”. R package version 0.4.6.
- Banu N., Chia A., Ho Z.Z., Garcia A.T., Paravasivam K., Grotenbreg G.M., Bertoletti A., Gehring A.J. Building and optimizing a virus-specific T cell receptor library for targeted immunotherapy in viral infections. Sci. Rep. 2014;4:4166.
- Cohen C.J., Li Y.F., El-Gamil M., Robbins P.F., Rosenberg S.A., Morgan R.A. Enhanced antitumor activity of T cells engineered to express T-cell receptors with a second disulfide bond. Cancer Res. 2007;67:3898–3903.
- Kuball J., Dossett M.L., Wolfl M., Ho W.Y., Voss R.-H., Fowler C., Greenberg P.D. Facilitating matched pairing and expression of TCR chains introduced into human T cells. Blood. 2007;109:2331–2338.
- Wickham H. Springer; 2009. Ggplot2: Elegant Graphics for Data Analysis.
Source: PubMed