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Tumour growth rate improves tumour assessment and first-line systemic treatment decision-making for immunotherapy in patients with liver metastatic uveal melanoma

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Abstract

Background

The RECIST-based response variably matches the clinical benefit of systemic therapies for liver metastatic uveal melanoma (LMUM). The aims were to determine whether the tumour growth rate (TGR) can help predict the survival in patients with LMUM and to provide information for the management of first-line systemic treatment.

Methods

This retrospective study included 147 (training: n = 110, validation: n = 37) patients with LMUM treated with first-line systemic treatment between 2010 and 2021. Two TGR-derived parameters were calculated, TGR0 and TGR3m. Multivariate Cox analyses identified independent predictors of progression-free survival (PFS) and overall survival (OS).

Results

TGR3m was a strong independent prognostic factor of PFS and OS (p < 0.001). The RECIST-based response was no longer significant in the OS analyses. Only immunotherapy regimens correlated with higher OS (HR = 0.2; 95% CI, 0.1–0.5; p < 0.001) in the low-TGR3m (≤50%/m) subgroup. These findings were confirmed in the validation cohort. TGR0, disease-free interval (DFI), and the sum of target lesions at baseline were predictive factors of low TGR3m.

Discussion

The use of TGR3m would improve tumour assessment by identifying patients who would benefit from first-line immunotherapy regimens despite PD. TGR0, DFI and the sum of target lesions were correlated with TGR3m, which can support first-line treatment decision-making for immunotherapy.

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Fig. 1
Fig. 2: Changes in TGR and correlation with RECIST-based response at 3 months in the training cohort.
Fig. 3: Survival analyses by TGR-derived parameters in the training cohort (n = 110).
Fig. 4: Overall survival by systemic treatment (second-line immunotherapy excluded) stratified by TGR3m in the training cohort.

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Data availability

The data generated in this study are available upon request from the corresponding author.

References

  1. Singh AD, Turell ME, Topham AK. Uveal melanoma: trends in incidence, treatment, and survival. Ophthalmology. 2011;118:1881–5.

    Article  Google Scholar 

  2. Rantala ES, Hernberg M, Kivelä TT. Overall survival after treatment for metastatic uveal melanoma: a systematic review and meta-analysis. Melanoma Res. 2019;29:561–8.

    Article  Google Scholar 

  3. Mariani P, Piperno-Neumann S, Servois V, Berry MG, Dorval T, Plancher C, et al. Surgical management of liver metastases from uveal melanoma: 16 years’ experience at the Institut Curie. Eur J Surg Oncol. 2009;35:1192–7.

    Article  CAS  Google Scholar 

  4. Carvajal RD, Schwartz GK, Tezel T, Marr B, Francis JH, Nathan PD. Metastatic disease from uveal melanoma: treatment options and future prospects. Br J Ophthalmol. 2017;101:38–44.

    Article  Google Scholar 

  5. Pelster MS, Gruschkus SK, Bassett R, Gombos D, Shephard M, Posada L, et al. Nivolumab and ipilimumab in metastatic uveal melanoma: results from a single-arm phase II study. J Clin Oncol. 2021;39:599–607.

    Article  CAS  Google Scholar 

  6. Piulats JM, Espinosa E, de la Cruz Merino L, Varela M, Carrión L, Martín-Algarra S, et al. Nivolumab plus ipilimumab for treatment-naïve metastatic uveal melanoma: an open-label, multicenter, phase II trial by the Spanish Multidisciplinary Melanoma Group (GEM-1402). J Clin Oncol. 2021;39:586–98.

    Article  CAS  Google Scholar 

  7. Nathan P, Hassel JC, Rutkowski P, Baurain J-F, Butler MO, Schlaak M, et al. Overall Survival benefit with tebentafusp in metastatic uveal melanoma. N Engl J Med. 2021;385:1196–206.

    Article  CAS  Google Scholar 

  8. Schwartz LH, Litière S, de Vries E, Ford R, Gwyther S, Mandrekar S, et al. RECIST 1.1—Update and clarification: from the RECIST committee. Eur J Cancer. 2016;62:132–7.

    Article  Google Scholar 

  9. Ferté C, Fernandez M, Hollebecque A, Koscielny S, Levy A, Massard C, et al. Tumor growth rate is an early indicator of antitumor drug activity in phase I clinical trials. Clin Cancer Res. 2014;20:246–52.

    Article  Google Scholar 

  10. Carter BW, Murthy R, Balmes G, Wachter EA, Patel S. Response assessment of metastatic uveal melanoma treated with rose bengal disodium. Ann Oncol. 2019;30:xi46.

    Article  Google Scholar 

  11. Shoushtari AN, Collins L, Espinosa E, Sethi H, Stanhope S, Abdullah S, et al. 1757O Early reduction in ctDNA, regardless of best RECIST response, is associated with overall survival (OS) on tebentafusp in previously treated metastatic uveal melanoma (mUM) patients. Ann Oncol. 2021;32:S1210.

    Article  Google Scholar 

  12. Gomez-Roca C, Koscielny S, Ribrag V, Dromain C, Marzouk I, Bidault F, et al. Tumour growth rates and RECIST criteria in early drug development. Eur J Cancer. 2011;47:2512–6.

    Article  Google Scholar 

  13. Lamarca A, Ronot M, Moalla S, Crona J, Opalinska M, Lopez Lopez C, et al. Tumor growth rate as a validated early radiological biomarker able to reflect treatment-induced changes in neuroendocrine tumors: The GREPONET-2 Study. Clin Cancer Res. 2019;25:6692–9.

    Article  Google Scholar 

  14. Ramtohul T, Ait Rais K, Gardrat S, Barnhill R, Román-Román S, Cassoux N, et al. Prognostic implications of mri melanin quantification and cytogenetic abnormalities in liver metastases of uveal melanoma. Cancers. 2021;13:2728.

    Article  CAS  Google Scholar 

  15. McShane LM, Altman DG, Sauerbrei W, Taube S, Gion M, Clark G, et al. REporting recommendations for tumor MARKer prognostic studies (REMARK). Nat Rev Clin Oncol. 2005;2:416–22.

    CAS  Google Scholar 

  16. on behalf of the CLARINET Study Group, Dromain C, Pavel ME, Ruszniewski P, Langley A, Massien C, et al. Tumor growth rate as a metric of progression, response, and prognosis in pancreatic and intestinal neuroendocrine tumors. BMC Cancer. 2019;19:66.

    Article  Google Scholar 

  17. Algazi AP, Tsai KK, Shoushtari AN, Munhoz RR, Eroglu Z, Piulats JM, et al. Clinical outcomes in metastatic uveal melanoma treated with PD-1 and PD-L1 antibodies: PD-1 Blockade in Uveal Melanoma. Cancer. 2016;122:3344–53.

    Article  CAS  Google Scholar 

  18. Najjar YG, Navrazhina K, Ding F, Bhatia R, Tsai K, Abbate K, et al. Ipilimumab plus nivolumab for patients with metastatic uveal melanoma: a multicenter, retrospective study. J Immunother Cancer. 2020;8:e000331.

    Article  Google Scholar 

  19. Heppt MV, Amaral T, Kähler KC, Heinzerling L, Hassel JC, Meissner M, et al. Combined immune checkpoint blockade for metastatic uveal melanoma: a retrospective, multi-center study. J Immunother Cancer. 2019;7:299.

    Article  Google Scholar 

  20. Eskelin S, Pyrhonen S, Summanen P, Hahka-Kemppinen M, Kivela T. Tumor doubling times in metastatic malignant melanoma of the uvea. Ophthalmology. 2000;107:1443–9.

    Article  CAS  Google Scholar 

  21. Ferté C, Koscielny S, Albiges L, Rocher L, Soria J-C, Iacovelli R, et al. Tumor growth rate provides useful information to evaluate sorafenib and everolimus treatment in metastatic renal cell carcinoma patients: an integrated analysis of the TARGET and RECORD Phase 3 Trial Data. Eur Urol. 2014;65:713–20.

    Article  Google Scholar 

  22. ten Berge DMHJ, Hurkmans DP, den Besten I, Kloover JS, Mathijssen RHJ, Debets RJEMA, et al. Tumour growth rate as a tool for response evaluation during PD-1 treatment for non-small cell lung cancer: a retrospective analysis. ERJ Open Res. 2019;5:00179–2019.

    Article  Google Scholar 

  23. Khoja L, Atenafu EG, Suciu S, Leyvraz S, Sato T, Marshall E, et al. Meta-analysis in metastatic uveal melanoma to determine progression free and overall survival benchmarks: an international rare cancers initiative (IRCI) ocular melanoma study. Ann Oncol. 2019;30:1370–80.

    Article  CAS  Google Scholar 

  24. Weber J, Mandala M, Del Vecchio M, Gogas HJ, Arance AM, Cowey CL, et al. Adjuvant Nivolumab versus ipilimumab in resected stage III or IV melanoma. N Engl J Med. 2017;377:1824–35.

    Article  CAS  Google Scholar 

  25. Eggermont AMM, Blank CU, Mandala M, Long GV, Atkinson V, Dalle S, et al. Adjuvant pembrolizumab versus placebo in resected stage III melanoma. N Engl J Med. 2018;378:1789–801.

    Article  CAS  Google Scholar 

  26. Robert C, Ribas A, Hamid O, Daud A, Wolchok JD, Joshua AM, et al. Durable complete response after discontinuation of pembrolizumab in patients with metastatic melanoma. J Clin Oncol. 2018;36:1668–74.

    Article  CAS  Google Scholar 

  27. Beaver JA, Hazarika M, Mulkey F, Mushti S, Chen H, He K, et al. Patients with melanoma treated with an anti-PD-1 antibody beyond RECIST progression: a US Food and Drug Administration pooled analysis. Lancet Oncol. 2018;19:229–39.

    Article  CAS  Google Scholar 

  28. Kim JH. Comparison of the RECIST 1.0 and RECIST 1.1 in patients treated with targeted agents: a pooled analysis and review. Oncotarget. 2016;7:13680–7.

    Article  Google Scholar 

  29. Mehrara E, Forssell-Aronsson E, Ahlman H, Bernhardt P. Specific growth rate versus doubling time for quantitative characterization of tumor growth rate. Cancer Res. 2007;67:3970–5.

    Article  CAS  Google Scholar 

  30. Wagner NB, Lenders MM, Kühl K, Reinhardt L, André F, Dudda M, et al. Pretreatment metastatic growth rate determines clinical outcome of advanced melanoma patients treated with anti-PD-1 antibodies: a multicenter cohort study. J Immunother Cancer. 2021;9:e002350.

    Article  Google Scholar 

  31. Maitland ML, Wilkerson J, Karovic S, Zhao B, Flynn J, Zhou M, et al. Enhanced detection of treatment effects on metastatic colorectal cancer with volumetric CT measurements for tumor burden growth rate evaluation. Clin Cancer Res. 2020;26:6464–74.

    Article  CAS  Google Scholar 

  32. Gerlee P. The model muddle: in search of tumor growth laws. Cancer Res. 2013;73:2407–11.

    Article  CAS  Google Scholar 

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Funding

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Author information

Authors and Affiliations

  1. Department of Radiology, Institut Curie, Paris, PSL Research University, Paris, France

    Toulsie Ramtohul, Axel Cohen & Vincent Servois

  2. Department of Medical Oncology, Institut Curie, PSL Research University, Paris and St. Cloud, Paris, France

    Manuel Rodrigues, Sophie Piperno-Neumann & Luc Cabel

  3. INSERM U830, DNA Repair and Uveal Melanoma (D.R.U.M.), Paris, France

    Manuel Rodrigues & Sophie Gardrat

  4. Department of Ocular Oncology, Institut Curie, PSL Research University, Paris, France

    Nathalie Cassoux, Livia Lumbroso-Le Rouic & Denis Malaise

  5. UMR 144 CNRS, Université de Paris, Paris, France

    Nathalie Cassoux

  6. INSERM U1288, PSL Research University, Laboratoire d’Imagerie Translationnelle en Oncologie, 91400, Orsay, France

    Denis Malaise

  7. Department of Biopathology, Institut Curie, PSL Research University, Paris, France

    Sophie Gardrat

  8. Somatic Genetic Unit, Department of Genetics, Institut Curie, PSL University, Paris, France

    Gaëlle Pierron

  9. Department of Surgical Oncology, Institut Curie, PSL Research University, Paris, France

    Pascale Mariani

Authors
  1. Toulsie Ramtohul
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  2. Axel Cohen
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  3. Manuel Rodrigues
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  4. Sophie Piperno-Neumann
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  5. Luc Cabel
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  9. Sophie Gardrat
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  10. Gaëlle Pierron
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  11. Pascale Mariani
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  12. Vincent Servois
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Contributions

Conceptualisation: TR and VS; methodology: TR, AC and VS; software: TR; validation: all authors; formal analysis: TR and VS; investigation: all authors; resources: SP, NC, LL, DM, SG, GP, PM and VS; data curation: TR, AC and VS; writing—original draft preparation: TR; writing—review and editing: TR, AC, MR, LC, PM and VS; visualisation: all authors; supervision: VS; project administration: VS; funding acquisition: VS. All authors have read and agreed to the published version of the manuscript.

Corresponding authors

Correspondence to Toulsie Ramtohul or Vincent Servois.

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The authors declare no competing interests.

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Institutional Review Board approval was obtained from the Institut Curie prior to the initiation of this study.

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Ramtohul, T., Cohen, A., Rodrigues, M. et al. Tumour growth rate improves tumour assessment and first-line systemic treatment decision-making for immunotherapy in patients with liver metastatic uveal melanoma. Br J Cancer 127, 258–267 (2022). https://doi.org/10.1038/s41416-022-01793-8

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