Nivolumab and sunitinib combination in advanced soft tissue sarcomas: a multicenter, single-arm, phase Ib/II trial

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Abstract

Background

Sarcomas exhibit low expression of factors related to immune response, which could explain the modest activity of PD-1 inhibitors. A potential strategy to convert a cold into an inflamed microenvironment lies on a combination therapy. As tumor angiogenesis promotes immunosuppression, we designed a phase Ib/II trial to test the double inhibition of angiogenesis (sunitinib) and PD-1/PD-L1 axis (nivolumab).

Methods

This single-arm, phase Ib/II trial enrolled adult patients with selected subtypes of sarcoma. Phase Ib established two dose levels: level 0 with sunitinib 37.5 mg daily from day 1, plus nivolumab 3 mg/kg intravenously on day 15, and then every 2 weeks; and level −1 with sunitinib 37.5 mg on the first 14 days (induction) and then 25 mg per day plus nivolumab on the same schedule. The primary endpoint was to determine the recommended dose for phase II (phase I) and the 6-month progression-free survival rate, according to Response Evaluation Criteria in Solid Tumors 1.1 (phase II).

Results

From May 2017 to April 2019, 68 patients were enrolled: 16 in phase Ib and 52 in phase II. The recommended dose of sunitinib for phase II was 37.5 mg as induction and then 25 mg in combination with nivolumab. After a median follow-up of 17 months (4–26), the 6-month progression-free survival rate was 48% (95% CI 41% to 55%). The most common grade 3–4 adverse events included transaminitis (17.3%) and neutropenia (11.5%).

Conclusions

Sunitinib plus nivolumab is an active scheme with manageable toxicity in the treatment of selected patients with advanced soft tissue sarcoma, with almost half of patients free of progression at 6 months.

Trial registration number NCT03277924.

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Most cited references 35

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Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression

Etienne Becht, Nicolas A Giraldo, Laetitia Lacroix … (2017)

We introduce the Microenvironment Cell Populations-counter (MCP-counter) method, which allows the robust quantification of the absolute abundance of eight immune and two stromal cell populations in heterogeneous tissues from transcriptomic data. We present in vitro mRNA mixture and ex vivo immunohistochemical data that quantitatively support the validity of our method’s estimates. Additionally, we demonstrate that MCP-counter overcomes several limitations or weaknesses of previously proposed computational approaches. MCP-counter is applied to draw a global picture of immune infiltrates across human healthy tissues and non-hematopoietic human tumors and recapitulates microenvironment-based patient stratifications associated with overall survival in lung adenocarcinoma and colorectal and breast cancer. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1070-5) contains supplementary material, which is available to authorized users.

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Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden

Zachary Chalmers, Caitlin Connelly, David Fabrizio … (2017)

Background High tumor mutational burden (TMB) is an emerging biomarker of sensitivity to immune checkpoint inhibitors and has been shown to be more significantly associated with response to PD-1 and PD-L1 blockade immunotherapy than PD-1 or PD-L1 expression, as measured by immunohistochemistry (IHC). The distribution of TMB and the subset of patients with high TMB has not been well characterized in the majority of cancer types. Methods In this study, we compare TMB measured by a targeted comprehensive genomic profiling (CGP) assay to TMB measured by exome sequencing and simulate the expected variance in TMB when sequencing less than the whole exome. We then describe the distribution of TMB across a diverse cohort of 100,000 cancer cases and test for association between somatic alterations and TMB in over 100 tumor types. Results We demonstrate that measurements of TMB from comprehensive genomic profiling are strongly reflective of measurements from whole exome sequencing and model that below 0.5 Mb the variance in measurement increases significantly. We find that a subset of patients exhibits high TMB across almost all types of cancer, including many rare tumor types, and characterize the relationship between high TMB and microsatellite instability status. We find that TMB increases significantly with age, showing a 2.4-fold difference between age 10 and age 90 years. Finally, we investigate the molecular basis of TMB and identify genes and mutations associated with TMB level. We identify a cluster of somatic mutations in the promoter of the gene PMS2, which occur in 10% of skin cancers and are highly associated with increased TMB. Conclusions These results show that a CGP assay targeting ~1.1 Mb of coding genome can accurately assess TMB compared with sequencing the whole exome. Using this method, we find that many disease types have a substantial portion of patients with high TMB who might benefit from immunotherapy. Finally, we identify novel, recurrent promoter mutations in PMS2, which may be another example of regulatory mutations contributing to tumorigenesis. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0424-2) contains supplementary material, which is available to authorized users.

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Nivolumab in Previously Untreated Melanoma withoutBRAFMutation

Caroline Robert, Georgina V Long, Benjamin Brady … (2015)

Nivolumab was associated with higher rates of objective response than chemotherapy in a phase 3 study involving patients with ipilimumab-refractory metastatic melanoma. The use of nivolumab in previously untreated patients with advanced melanoma has not been tested in a phase 3 controlled study. We randomly assigned 418 previously untreated patients who had metastatic melanoma without a BRAF mutation to receive nivolumab (at a dose of 3 mg per kilogram of body weight every 2 weeks and dacarbazine-matched placebo every 3 weeks) or dacarbazine (at a dose of 1000 mg per square meter of body-surface area every 3 weeks and nivolumab-matched placebo every 2 weeks). The primary end point was overall survival. At 1 year, the overall rate of survival was 72.9% (95% confidence interval [CI], 65.5 to 78.9) in the nivolumab group, as compared with 42.1% (95% CI, 33.0 to 50.9) in the dacarbazine group (hazard ratio for death, 0.42; 99.79% CI, 0.25 to 0.73; P<0.001). The median progression-free survival was 5.1 months in the nivolumab group versus 2.2 months in the dacarbazine group (hazard ratio for death or progression of disease, 0.43; 95% CI, 0.34 to 0.56; P<0.001). The objective response rate was 40.0% (95% CI, 33.3 to 47.0) in the nivolumab group versus 13.9% (95% CI, 9.5 to 19.4) in the dacarbazine group (odds ratio, 4.06; P<0.001). The survival benefit with nivolumab versus dacarbazine was observed across prespecified subgroups, including subgroups defined by status regarding the programmed death ligand 1 (PD-L1). Common adverse events associated with nivolumab included fatigue, pruritus, and nausea. Drug-related adverse events of grade 3 or 4 occurred in 11.7% of the patients treated with nivolumab and 17.6% of those treated with dacarbazine. Nivolumab was associated with significant improvements in overall survival and progression-free survival, as compared with dacarbazine, among previously untreated patients who had metastatic melanoma without a BRAF mutation. (Funded by Bristol-Myers Squibb; CheckMate 066 ClinicalTrials.gov number, NCT01721772.).

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Author and article information

Journal

Journal ID (nlm-ta): J Immunother Cancer

Journal ID (iso-abbrev): J Immunother Cancer

Journal ID (hwp): jitc

Journal ID (publisher-id): jitc

Title: Journal for Immunotherapy of Cancer

Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )

ISSN (Electronic): 2051-1426

Publication date Collection: 2020

Publication date (Electronic): 17 November 2020

Volume: 8

Issue: 2

Electronic Location Identifier: e001561

Affiliations

[1 ]departmentMedical Oncology Department , University Hospital Virgen del Rocio , Sevilla, Spain

[2 ]Institute of Biomedicine of Sevilla (IBIS, HUVR, CSIC, Universidad de Sevilla) , Sevilla, Spain

[3 ]departmentDivision of Medical Oncology , Candiolo Cancer Institute, FPO - IRCCS - Str. Prov.le 142, km. 3,95 - Candiolo (TO) 10060 , Candiolo, Italy

[4 ]departmentMedical Oncology Department , Miguel Servet University Hospital , Zaragoza, Spain

[5 ]departmentDepartment of Medical Oncology , Hospital Universitario La Paz , Madrid, Spain

[6 ]departmentDepartment of Medical Oncology , Vall d’Hebron University Hospital , Barcelona, Spain

[7 ]departmentCancer Medicine Department , Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale Tumori, Via Venezian 1 , Milan, Italy

[8 ]departmentMedical Oncology Department , Sant Pau Hospital , Barcelona, Spain

[9 ]departmentMedical Hematology Department , University Hospital Son Espases , Mallorca, Spain

[10 ]departmentRadiology Department , University Hospital Virgen del Rocio , Sevilla, Spain

[11 ]Institute of Biomedicine of Sevilla (IBiS), Virgen del Rocio University Hospital /CSIC/University of Sevilla/CIBERONC , Sevilla, Spain

[12 ]departmentDepartment of Normal and Pathological Cytology and Histology , School of Medicine, University of Seville, 41009 , Sevilla, Spain

[13 ]departmentSoft Tissue and Bone Pathology, Histopathology and Pediatric Pathology Unit, Diagnostic Pathology and Laboratory Medicine Department , Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Istituto Nazionale Tumori , Milan, Italy

[14 ]departmentClinical Bioinformatics Area , Fundación Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio , Sevilla, Spain

[15 ]departmentBioinformatics in Rare Diseases (BiER) , Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocio , Sevilla, Spain

[16 ]departmentINB-ELIXIR-es , FPS, Hospital Virgen del Rocío , Sevilla, Spain

[17 ]departmentMedical Oncology Department , Hospital 12 de Octubre , Madrid, Spain

[18 ]Instituto de Investigación Sanitaria Hospital 12 de Octubre (i+12) , Madrid, Spain

Author notes

[Correspondence to ] Dr Javier Martin-Broto; jmartin@ 123456mustbesevilla.org

Author information

Javier Martin-Broto http://orcid.org/0000-0001-7350-6916

Giovanni Grignani http://orcid.org/0000-0001-5515-569X

Article

Publisher ID: jitc-2020-001561

DOI: 10.1136/jitc-2020-001561

PMC ID: 7674086

PubMed ID: 33203665

SO-VID: ee138a10-b232-4263-9756-11b4ebf4cda5

License:

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/.

History

Date accepted : 19 October 2020

Funding

Funded by: Beca Buesa;

Award ID: NA

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Keywords: sarcoma,immunotherapy,clinical trials as topic,translational medical research

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Keywords: sarcoma, immunotherapy, clinical trials as topic, translational medical research

Nivolumab and sunitinib combination in advanced soft tissue sarcomas: a multicenter, single-arm, phase Ib/II trial

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Abstract

Background

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Cancer Immunotherapy

Most cited references 35

Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression

Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden

Nivolumab in Previously Untreated Melanoma withoutBRAFMutation

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