Durvalumab in Combination with Olaparib in Patients with Relapsed SCLC: Results from a Phase II Study.


Journal

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
ISSN: 1556-1380
Titre abrégé: J Thorac Oncol
Pays: United States
ID NLM: 101274235

Informations de publication

Date de publication:
08 2019
Historique:
received: 05 02 2019
revised: 19 03 2019
accepted: 10 04 2019
pubmed: 8 5 2019
medline: 24 7 2020
entrez: 8 5 2019
Statut: ppublish

Résumé

Despite high tumor mutationburden, immune checkpoint blockade has limited efficacy in SCLC. We hypothesized that poly (ADP-ribose) polymerase inhibition could render SCLC more susceptible to immune checkpoint blockade. A single-arm, phase II trial (NCT02484404) enrolled patients with relapsed SCLC who received durvalumab, 1500 mg every 4 weeks, and olaparib, 300 mg twice a day. The primary outcome was objective response rate. Correlative studies included mandatory collection of pretreatment and during-treatment biopsy specimens, which were assessed to define SCLC immunephenotypes: desert (CD8-positive T-cell prevalence low), excluded (CD8-positive T cells in stroma immediately adjacent/within tumor), and inflamed (CD8-positive T cells in direct contact with tumor). A total of 20 patients were enrolled. Their median age was 64 years, and most patients (60%) had platinum-resistant/refractory disease. Of 19 evaluable patients, two were observed to have partial or complete responses (10.5%), including a patient with EGFR-transformed SCLC. Clinical benefit was observed in four patients (21.1% [95% confidence interval: 6.1%-45.6%]) with confirmed responses or prolonged stable disease (≥8 months). The most common treatment-related adverse events were anemia (80%), lymphopenia (60%), and leukopenia (50%). Nine of 14 tumors (64%) exhibited an excluded phenotype; 21% and 14% of tumors exhibited the inflamed and desert phenotypes, respectively. Tumor responses were observed in all instances in which pretreatment tumors showed an inflamed phenotype. Of the five tumors without an inflamed phenotype at baseline, no during-treatment increase in T-cell infiltration or programmed death ligand 1 expression on tumor-infiltrating immune cells was observed. The study combination did not meet the preset bar for efficacy. Pretreatment and during-treatment biopsy specimens suggested that tumor immune phenotypes may be relevant for SCLC responses to immune checkpoint blockade combinations. The predictive value of preexisting CD8-positive T-cell infiltrates observed in this study needs to be confirmed in larger cohorts.

Identifiants

pubmed: 31063862
pii: S1556-0864(19)30361-2
doi: 10.1016/j.jtho.2019.04.026
pmc: PMC6660419
mid: NIHMS1528600
pii:
doi:

Substances chimiques

Antibodies, Monoclonal 0
Antineoplastic Agents, Immunological 0
Phthalazines 0
Piperazines 0
durvalumab 28X28X9OKV
olaparib WOH1JD9AR8

Types de publication

Clinical Trial, Phase II Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1447-1457

Subventions

Organisme : Intramural NIH HHS
ID : ZIA BC011793
Pays : United States
Organisme : Intramural NIH HHS
ID : ZIA BC011793-01
Pays : United States

Commentaires et corrections

Type : CommentIn
Type : CommentIn
Type : CommentIn

Informations de copyright

Published by Elsevier Inc.

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Auteurs

Anish Thomas (A)

Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland. Electronic address: anish.thomas@nih.gov.

Rasa Vilimas (R)

Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

Christopher Trindade (C)

Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

Rebecca Erwin-Cohen (R)

Cancer and Inflammation Program, Center for Cancer Research, National Cancer Institute, Frederick, Maryland.

Nitin Roper (N)

Thoracic and Gastrointestinal Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

Liqiang Xi (L)

Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

Venkatesh Krishnasamy (V)

Interventional Radiology, National Institutes of Health Clinical Center, Bethesda, Maryland.

Elliot Levy (E)

Interventional Radiology, National Institutes of Health Clinical Center, Bethesda, Maryland.

Andy Mammen (A)

Muscle Disease Unit, National Institute of Arthritis and Musculoskeletal and Skin Diseases, Bethesda, Maryland.

Samantha Nichols (S)

Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

Yuanbin Chen (Y)

Cancer and Hematology Centers of Western Michigan, Grand Rapids, Michigan.

Vamsidhar Velcheti (V)

Thoracic Medical Oncology, Perlmutter Cancer Center, New York University, New York, New York.

Faye Yin (F)

Western Maryland Regional Medical Center, Schwab Family Cancer Center, Cumberland, Maryland.

Eva Szabo (E)

Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland.

Yves Pommier (Y)

Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

Seth M Steinberg (SM)

Biostatistics and Data Management Section, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

Jane B Trepel (JB)

Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

Mark Raffeld (M)

Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

Howard A Young (HA)

Cancer and Inflammation Program, Center for Cancer Research, National Cancer Institute, Frederick, Maryland.

Javed Khan (J)

Genetics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

Stephen Hewitt (S)

Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

Jung-Min Lee (JM)

Women's Malignancies Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland.

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Classifications MeSH