Letter | Published:

A single dose of neoadjuvant PD-1 blockade predicts clinical outcomes in resectable melanoma

Abstract

Immunologic responses to anti-PD-1 therapy in melanoma patients occur rapidly with pharmacodynamic T cell responses detectable in blood by 3 weeks. It is unclear, however, whether these early blood-based observations translate to the tumor microenvironment. We conducted a study of neoadjuvant/adjuvant anti-PD-1 therapy in stage III/IV melanoma. We hypothesized that immune reinvigoration in the tumor would be detectable at 3 weeks and that this response would correlate with disease-free survival. We identified a rapid and potent anti-tumor response, with 8 of 27 patients experiencing a complete or major pathological response after a single dose of anti-PD-1, all of whom remain disease free. These rapid pathologic and clinical responses were associated with accumulation of exhausted CD8 T cells in the tumor at 3 weeks, with reinvigoration in the blood observed as early as 1 week. Transcriptional analysis demonstrated a pretreatment immune signature (neoadjuvant response signature) that was associated with clinical benefit. In contrast, patients with disease recurrence displayed mechanisms of resistance including immune suppression, mutational escape, and/or tumor evolution. Neoadjuvant anti-PD-1 treatment is effective in high-risk resectable stage III/IV melanoma. Pathological response and immunological analyses after a single neoadjuvant dose can be used to predict clinical outcome and to dissect underlying mechanisms in checkpoint blockade.

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Code availability

Custom code used to analyze tumor whole exome sequencing data is available at https://zenodo.org/badge/latestdoi/162582612

Data availability

NanoString data that support the findings have been deposited in the NCBI Gene Expression Omnibus and are accessible through GEO Series accession number GSE123728. DNA whole exome sequencing data have been deposited in SRA and are accessible under SRA accession number PRJNA510621. All other relevant data are available from the corresponding author upon reasonable request.

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Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Acknowledgements

Clinical and correlative studies were supported in part by the SPORE in Skin Cancer: P50-CA174523 (X.X., K.L.N., L.M.S., R.K.A., R.M., G.C.K.), P01-CA114046 (X.X.), T32-2T32CA009615 (A.C.H.); the NIH/NCI Cancer Center Support Grant P30-CA016520 (R.K.A., K.L.N., L.M.S., R.M.), and NIH grants AI105343, AI108545, AI117950, AI082630, CA210944 (E.J.W.), and AI114852 (R.S.H.); the Tara Miller Foundation (A.C.H.); the Melanoma Research Alliance (E.J.W.); the David and Hallee Adelman Immunotherapy Research Fund (E.J.W.); the Heisenberg program BE5496/2-1 of the DFG (B.B.); and the Parker Institute for Cancer Immunotherapy Bridge Scholar Award (A.C.H.). Merck, Inc. supplied drugs and supported clinical and translational aspects of this study. The Human Immunology Core and the Tumor Tissue and Biospecimen Bank of the University of Pennsylvania (supported by P30-CA016520) assisted in tissue collection, processing, and storage.

Author information

A.C.H., T.C.M., and E.J.W. conceived and designed the overall studies. A.C.H. and T.C.M. designed the clinical trial at Penn. A.C.H., T.C.M., R.J.O., X.X., M.D.F., and G.C.K. implemented the clinical trial at Penn, and T.C.M. was principal investigator of this clinical trial. X.X. and S.L. performed pathologic response and TIL assessments. A.C.H., R.J.O., P.K.Y., S.M.G., B.B., and R.S.H. performed immune assessment assays. A.C.H., R.J.O., P.K.Y., S.M.G., and M.W.K. analyzed immune assessment data. R.Mick performed biostatistical analyses. S.Manne, Q.Z., W.M.B., R.Mogg, and J.H.Y. performed NanoString assay and/or computational analysis of NanoString data. A.A.K., L.D., B.M.W., B.W., K.D’A., and K.L.N. performed mutational analysis and neoepitope prediction. W.X., L.G., M.C., S.McGettigan, and K.K. assisted in the Penn clinical trial. A.K. and M.D.F. performed radiographic assessments. L.A. and J.H.Y. performed and/or analyzed immunohistochemistry and immunofluorescent assays. G.P.L., R.K.A., G.C.K., M.D.F., and L.M.S. were investigators on the trial. A.C.H., T.C.M., and E.J.W. interpreted the data. A.C.H., T.C.M., and E.J.W. wrote the manuscript. E.J.W. and T.C.M. designed, interpreted, and oversaw the study.

Competing interests

Merck provided funding and drugs for the clinical trial. Merck performed immunohistochemistry, immunofluorescence, and NanoString assays, and played a role in the analysis of these data. Merck played no role in the design, data collection, decision to publish, or preparation of the manuscript. R.J.O. was at Penn while engaged in this project, but is now currently employed at Merck. L.A., Q.Z., R.M., W.M.B., and J.H.Y. are currently or were employed at Merck when engaged in this project. E.J.W. is a member of the Parker Institute for Cancer Immunotherapy which supported the UPenn cancer immunotherapy program. E.J.W. has consulting agreements with and/or is on the scientific advisory board for Merck, Roche, Pieris, Elstar, and Surface Oncology. E.J.W. has a patent licensing agreement on the PD-1 pathway with Roche/Genentech. E.J.W. is a founder of Arsenal Biosciences. T.C.M. has had advisory roles with Bristol-Myers Squibb, Merck, Incyte, Aduro Biotech, and Regeneron.

Correspondence to Alexander C. Huang or E. John Wherry or Tara C. Mitchell.

Extended data

  1. Extended Data Fig. 1 TIL score associated with pathologic response.

    Percentage viable tumor between brisk (n = 9) versus non-brisk/absent tumors (n = 11). P value calculated using two-sided Mann–Whitney test.

  2. Extended Data Fig. 2 Immune response to anti-PD-1 for T cell subsets in blood and tumor.

    a, Percentage Ki67 expression in CD8, conventional CD4, and Treg (FoxP3+ CD4) T cells pre and post in blood (n = 28 independent paired patient samples for CD8 comparisons, n = 17 independent paired patient samples for CD4 comparisons, and n = 27 independent patient samples for Treg comparisons). Two-sided Wilcoxon matched-pairs test was performed for CD8 and Treg comparisons. Two-sided t-test was performed for CD4 comparison. b, Percentage Ki67 expression in CD8, conventional CD4, and Treg (FoxP3+ CD4) T cells pre and post in tumor (n = 26 independent paired patient samples for CD8 comparisons, n = 15 independent paired patient samples for CD4 comparisons, and n = 25 independent paired patient samples for Treg comparisons). Two-sided Wilcoxon matched-pairs test was performed for CD4 and Treg comparisons. Two-sided t-test was performed for CD8 comparison.

  3. Extended Data Fig. 3 Cellular determinants of response and resistance to anti-PD-1.

    a, Changes in tumor PD-L1 pre- versus post-treatment using immunohistochemistry staining (n = 9 independent paired patient samples). **P <0.01 using two-sided Wilcoxon matched-pairs test. b, Correlation of percentage of Ki67+ in non-naïve CD8 T cells versus percentage of Ki67+ in Tregs (FoxP3+CD4) (n = 21 independent patient samples); R score and P value generated using Pearson’s correlation. c, Thirty-three post-treatment immune parameters classified by recurrence using random forest analysis and ranked by importance score (n = 21 independent patient samples). Error bar denotes mean ± s.d. for 1,000 random forest iterations. d, Percentage expression of selected markers in tumor between patients with recurrence (9 independent patient samples) and no recurrence (12 independent patient samples). P value calculated using two-sided Mann–Whitney test. e, Correlation of percentage of Ki67+ in Tregs (FoxP3+ CD4) versus percentage of Eomes+ T-bet- in non-naïve CD8 (n = 21 independent patient samples); R score and P value generated using Pearson’s correlation. f, Twenty-five pretreatment immune parameters classified by recurrence using random forest analysis and ranked by importance score (n = 21 independent patient samples). Error bar denotes mean ± s.d. for 1,000 random forest iterations. g, Percentage expression of selected markers in tumor between patients with recurrence (9 independent patient samples) and no recurrence (12 independent patient samples). Two-sided t-test was used for CD45RA-CD27+ and CD45RA+CD27+ comparisons. Two-sided Mann–Whitney test was used for CD8 Ki67+ and CD4 Ki67+ comparisons. Error bar denotes mean ± s.d. h, Scatter plot of percentage of Ki67+ in non-naïve CD8 versus percentage of Ki67+in FoxP3+ CD4 (Tregs) at pretreatment stratified by recurrence status. Dotted line denotes non-naïve CD8 Ki67+ of 5.5 calculated by CART analysis as the optimal cut point separating recurrence versus no recurrence (n = 21 independent patient samples).

  4. Extended Data Fig. 4 Immune signatures associated with clinical response.

    a, Heatmap of differentially expressed genes between pretreatment and post-treatment tumor (n = 11 independent paired patient samples). Differentially expressed genes identified using an FDR cut-off of P = 0.05 after adjusting for multiple comparisons. b, Heatmap and GEP score between patients with recurrence (n = 5 independent patient samples) and no recurrence (n = 8 independent patient samples). P value calculated using two-sided Mann–Whitney test. Error bar denotes mean ± s.d. c, GSEA of NRS genes that were enriched in TEFF, TMEM, and TEX versus TNAIVE cell signatures from ref. 19. d, Heatmap of angiogenesis-associated genes from gene ontology. e, Heatmap of B cell receptor-associated genes from gene ontology.

  5. Extended Data Fig. 5 Clinical progression and neoantigen quantity and quality.

    a, DFS of patients that recurred. b, CT image before and after of a patient with recurrent metastatic disease. c, Neoantigen load based on predicted binding (predicted kD of < 500 nM and mutant kD <wild-type kD). d, Number of high-quality neoantigens that are likely to be recognized by TCRs based on neoantigen fitness model42 at post-treatment versus recurrence time points.

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    Supplementary Tables 1–5

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Further reading

Fig. 1: Pathologic response and TILs are predictive of clinical outcome after a single dose of anti-PD-1.
Fig. 2: Early radiographic, pathologic, and immune response to anti-PD-1.
Fig. 3: Pembrolizumab targets TEX in tumor.
Fig. 4: Mechanisms of response and resistance to anti-PD-1 therapy.
Extended Data Fig. 1: TIL score associated with pathologic response.
Extended Data Fig. 2: Immune response to anti-PD-1 for T cell subsets in blood and tumor.
Extended Data Fig. 3: Cellular determinants of response and resistance to anti-PD-1.
Extended Data Fig. 4: Immune signatures associated with clinical response.
Extended Data Fig. 5: Clinical progression and neoantigen quantity and quality.