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Pathological response and survival with neoadjuvant therapy in melanoma: a pooled analysis from the International Neoadjuvant Melanoma Consortium (INMC)

Abstract

The association among pathological response, recurrence-free survival (RFS) and overall survival (OS) with neoadjuvant therapy in melanoma remains unclear. In this study, we pooled data from six clinical trials of anti-PD-1-based immunotherapy or BRAF/MEK targeted therapy. In total, 192 patients were included; 141 received immunotherapy (104, combination of ipilimumab and nivolumab; 37, anti-PD-1 monotherapy), and 51 received targeted therapy. A pathological complete response (pCR) occurred in 40% of patients: 47% with targeted therapy and 33% with immunotherapy (43% combination and 20% monotherapy). pCR correlated with improved RFS (pCR 2-year 89% versus no pCR 50%, P < 0.001) and OS (pCR 2-year OS 95% versus no pCR 83%, P = 0.027). In patients with pCR, near pCR or partial pathological response with immunotherapy, very few relapses were seen (2-year RFS 96%), and, at this writing, no patient has died from melanoma, whereas, even with pCR from targeted therapy, the 2-year RFS was only 79%, and OS was only 91%. Pathological response should be an early surrogate endpoint for clinical trials and a new benchmark for development and approval in melanoma.

Data availability

The data that support the findings of this study are available upon reasonable request from the corresponding authors. The International Neoadjuvant Melanoma Consortium, via Melanoma Institute Australia, will promptly review all data requests to ensure that intellectual property and confidentiality obligations are met. A Material Transfer Agreement will be used to transfer any and all data that can be shared.

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Acknowledgements

A.M.M. is supported by a Cancer Institute NSW Fellowship and Melanoma Institute Australia. R.P.M.S. is supported by Melanoma Institute Australia. M.A.D. is supported by NIH/NCI grant (1 P50 CA221703-02), the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation and philanthropic contributions to the Melanoma Moon Shots Program of MD Anderson Cancer Center. G.V.L. and R.A.S. are supported by NHMRC Practitioner Fellowships. G.V.L. is supported by the University of Sydney Medical Foundation and Melanoma Institute Australia. Support from the Melanoma Research Alliance/Rising Tide Foundation for a Clinical Cancer Research Grant for “Predictor of response to neoadjuvant therapy in melanoma” for salary support for A.M.M., N.R.A., M.T.T., M.A.D., R.A.S., G.V.L. is gratefully acknowledged. Support from colleagues at Melanoma Institute Australia, Mater Hospital, Royal North Shore Hospital, Royal Prince Alfred Hospital and NSW Health Pathology is gratefully acknowledged.

Author information

Author notes

  1. These authors contributed equally: Alexander M. Menzies, Rodabe N. Amaria, Elisa A. Rozeman, Alexander C. Huang, Michael T. Tetzlaff, Bart A. van de Wiel, Serigne Lo.

  2. These authors jointly supervised this work: Michael A. Davies, Tara C. Mitchell, Hussein A. Tawbi, Richard A. Scolyer, Jennifer A. Wargo, Christian U. Blank, Georgina V. Long.

Affiliations

  1. Melanoma Institute Australia, The University of Sydney, Sydney, Australia

    Alexander M. Menzies, Serigne Lo, Thomas E. Pennington, Robyn P. M. Saw, Andrew J. Spillane, Richard A. Scolyer & Georgina V. Long

  2. Faculty of Medicine and Health, The University of Sydney, Sydney, Australia

    Alexander M. Menzies, Serigne Lo, Thomas E. Pennington, Robyn P. M. Saw, Andrew J. Spillane, Richard A. Scolyer & Georgina V. Long

  3. Royal North Shore and Mater Hospitals, Sydney, Australia

    Alexander M. Menzies, Andrew J. Spillane & Georgina V. Long

  4. University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Rodabe N. Amaria, Michael T. Tetzlaff, Elizabeth M. Burton, Michael A. Davies, Hussein A. Tawbi & Jennifer A. Wargo

  5. Netherlands Cancer Institute, Amsterdam, The Netherlands

    Elisa A. Rozeman, Bart A. van de Wiel, Alexander C. J. van Akkooi & Christian U. Blank

  6. Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Alexander C. Huang, Xiaowei Xu, Giorgos C. Karakousis & Tara C. Mitchell

  7. Parker Institute for Cancer Immunotherapy at University of Pennsylvania, Philadelphia, PA, USA

    Alexander C. Huang

  8. H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA

    Ahmad A. Tarhini

  9. Royal Prince Alfred Hospital, Sydney, Australia

    Thomas E. Pennington & Robyn P. M. Saw

  10. Istituto Nazionale Tumori IRCCS Fondazione ‘G. Pascale’, Napoli, Italy

    Paolo A. Ascierto

  11. Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and New Health Pathology, Sydney, Australia

    Richard A. Scolyer

Contributions

Study concept (G.V.L.) and study design (A.M.M., R.N.A., M.A.D., J.A.W., C.U.B. and G.V.L.). A.M.M., R.N.A., E.A.R. and A.C.H. collected the clinical data. S.L. performed statistical analyses. A.M.M. and G.V.L. wrote the manuscript. All authors were involved in the individual trials (roles outlined in original publications) and critically revised and approved the manuscript.

Corresponding author

Correspondence to
Georgina V. Long.

Ethics declarations

Competing interests

A.M.M.—advisory board: BMS, MSD, Novartis, Roche and Pierre-Fabre. R.N.A.—research funding from Merck, BMS, Novartis and Iovance; consultant to Nektar and Iovance. E.A.R.—travel support from NanoString and MSD. R.A.S. has received fees for professional services from Merck Sharp & Dohme, GlaxoSmithKline, Bristol-Myers Squibb, Novartis, Myriad, NeraCare and Amgen. H.A.T.—advisory board: BMS, Merck, Novartis, Roche and Array; research support to institution: BMS, Merck, Roche, Celgene and GSK. R.P.M.S.—advisory board: MSD and Novartis, and speaking honoraria: BMS. T.C.M.—advisory board: Merck, BMS and Array. A.v.A.—advisory boards/consultancy honoraria: Amgen, BMS, Novartis, MSD-Merck, Merck-Pfizer, Sanofi and 4SC, all paid to institute and unrelated to present work; research grants: Amgen, BMS and Novartis, all paid to institute and unrelated to present work. M.A.D.—advisory board member/consultant for BMS, Novartis, Array, Roche/Genentech, GSK and Sanofi-Aventis; principal investigator of research grant to institution from AstraZeneca, Roche/Genentech, GSK, Myriad, Oncothyreon and Sanofi-Aventis. C.U.B.—advisory role: BMS, MSD, Roche, Novartis, GSK, AstraZeneca, Pfizer, Lilly, GenMab, Pierre Fabre and Third Rock Ventures; research funding: BMS, Novartis and NanoString; stockownership: Uniti Cars. G.V.L.—consultant advisor to Aduro, Amgen, Array, BMS, MSD, Novartis, Roche, Pierre-Fabre and Sandoz. P.A.A.—consultant/advisory to Bristol Myers-Squibb, Roche-Genentech, Merck Sharp & Dohme, Array, Novartis, Merck Serono, Pierre Fabre, Incyte, NewLink Genetics, Genmab, Medimmune, AstraZeneca, Syndax, SunPharma, Sanofi, Idera, Ultimovacs, Sandoz, Immunocore, 4SC, Alkermes, Italfarmaco, Nektar and Boehringer-Ingelheim; research funding from Bristol Myers-Squibb, Roche-Genentech and Array; travel support from MSD. J.A.W. is an inventor on a US patent application (PCT/US17/53.717) submitted by the University of Texas MD Anderson Cancer Center that covers methods to enhance immune checkpoint blockade responses by modulating the microbiome and on a patent Targeting B Cells To Enhance Response To Immune Checkpoint Blockade UTSC.P1412US.P1 – MDA19-023. J.A.W. reports compensation for speaker’s bureau and honoraria from Imedex, Dava Oncology, Omniprex, Illumina, Gilead, PeerView, Physician Education Resource, MedImmune and Bristol-Myers Squibb. J.A.W. serves as a consultant/advisory board member for Roche/Genentech, Novartis, AstraZeneca, GlaxoSmithKline, Bristol-Myers Squibb, Merck, and Ella Therapeutics. The authors have no additional competing interests.

Additional information

Peer review information Javier Carmona was the primary editor on this article, and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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

Extended data

Extended Data Fig. 1 Duration of therapy in modern neoadjuvant melanoma trials (weeks).

Neoadjuvant and adjuvant treatment durations on the six neoadjuvant trials of targeted therapy and immunotherapy in melanoma. TT, targeted therapy, IT, immunotherapy.

Extended Data Fig. 2 CONSORT diagram.

CONSORT diagram demonstrating of all patients recruited to trials (N = 211), 19 were initially excluded as they had stage IV disease or in-transit metastases (ITMs) only, leaving 192 for analysis. 3 patients did not undergo surgery, and were excluded from pathological response analyses.

Extended Data Fig. 3 Kaplan-Meier estimates of RFS by pathological response (AJCC substages).

Kaplan–Meier estimates of recurrence-free survival by two-sided log-rank are shown for patients in the following AJCC substage cohorts based upon pathological response a) IIIB cohort, b) IIIC cohort. The numbers under the graphs indicate the number of patients with each pathological response outcome and at risk for the event at each time point. In figure (a) 12-month RFS was 98% (95% CI 93–100%) for pCR and 73% (62–86%) for no pCR, while 24-month RFS was 94% (86–100%) and 54% (40–73%), respectively p < 0.001. In figure (b) 12-month RFS was 87% (75–100%) for pCR and 63% (52–77%) for no pCR, while 24-month RFS was 82% (69–98%) and 47 (34–65%), respectively p = 0.006.

Extended Data Fig. 4 Kaplan-Meier estimates of RFS by pathological response category (immunotherapy cohort).

Kaplan–Meier estimates of RFS by two-sided log-rank are shown for patients treated with immunotherapy with any response (pCR, near pCR, pPR) vs no response (pNR). The numbers under the graphs indicate the number of patients with each pathological response outcome and at risk for the event at each time point. 12-month RFS was 97% (95% CI 93–100%) for pCR/near pCR/pPR and 47% (34–64%) for pNR, while 24-month RFS was 97% (93–100%) and 37% (24–58%), respectively p= <0.001.

Extended Data Fig. 5 Kaplan-Meier estimates of RFS by radiological response.

Kaplan–Meier estimates of RFS by two-sided log-rank are shown for patients based upon RECIST radiological response categories a) Whole cohort, b) Targeted therapy cohort, c) Immunotherapy cohort. The numbers under the graphs indicate the number of patients with each pathological response outcome and at risk for the event at each time point. In figure (a) 12-month RFS was 91% (95% CI 81–100%) for RECIST CR, 88% (74–100%) for PR, 71% (59–86%) for SD and 29% (13–65%) for PD, while 24-month RFS was 65% (44–94%), 75% (65–87%), 58% (42–79%) and 29% (13–65%) respectively, p < 0.001. In figure (b) 12-month RFS was 88% (74–100%) for CR, 72% (58–91%) for PR and 40% (14–100%) for SD, while 24-month RFS was 60% (39–93%), 44% (28–68%) and 20% (3–100%) respectively, p = 0.077. In figure (c) 12-month RFS was 100% (N/A) for CR, 96% (91–100%) for PR, 75% (63–90%) for SD and 29% (13–65%) for PD, while 24-month RFS was 100% (N/A), 96% (91–100%), 62% (45–85%) and 29% (13–65%) respectively, p < 0.001.

Extended Data Fig. 6 Kaplan-Meier estimates of RFS in those with pNR to immunotherapy based upon radiological response.

Kaplan–Meier estimates of RFS by two-sided log-rank are shown for patients treated with immunotherapy who had no pathological response based upon RECIST response to therapy. The numbers under the graphs indicate the number of patients with each pathological response outcome and at risk for the event at each time point. 12-month RFS was 100% (95% CI N/A) for RECIST PR, 40% (22–72%) for SD and 27% (10–72%) for PD, while 24-month RFS was 100% (N/A), 20% (6–63%) and 27% (10–72%) respectively, p = 0.045.

Extended Data Fig. 7 Kaplan-Meier estimates of Overall Survival.

Kaplan–Meier estimates of OS a) Whole cohort, b) by two-sided log-rank for Immunotherapy and Targeted Therapy cohorts. The numbers under the graphs indicate the number of patients with each pathological response outcome and at risk for the event at each time point. In figure (a) 12-month OS was 90% (95% CI 86–95%), while 24-month RFS was 87% (82–92%). In figure (b) 12-month OS was 98% (95–100%) for immunotherapy and 98% (94–100%) for targeted therapy, while 24-month OS was 88% (82–95%) and 86% (77–97%) respectively, p = 0.320.

Extended Data Fig. 8 Kaplan-Meier estimates of OS by pathological response.

Kaplan–Meier estimates of OS by two-sided log-rank are shown for patients based upon pathological response a) Targeted therapy cohort, b) Immunotherapy cohort. The numbers under the graphs indicate the number of patients with each pathological response outcome and at risk for the event at each time point. No patient in the targeted therapy cohort had a near-pCR. In figure (a) 12-month OS was 100% (95% CI N/A) for pCR, 100% (N/A) for pPR and 94% (84–100%) for pNR, while 24-month OS was 91% (80–100%), 80% (52-100%) and 81% (63-100%) respectively, p = 0.146. In figure (b) 12-month OS was 98% (94–100%) for pCR, 100% (N/A) for near pCR, 100% (N/A) for pPR and 98% (94–100%) for pNR, while 24-month OS was 98% (94–100%), 100% (N/A), 100% (N/A) and 72% (58–90%) respectively, p = 0.003.

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Menzies, A.M., Amaria, R.N., Rozeman, E.A. et al. Pathological response and survival with neoadjuvant therapy in melanoma: a pooled analysis from the International Neoadjuvant Melanoma Consortium (INMC).
Nat Med (2021). https://doi.org/10.1038/s41591-020-01188-3

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