Abstract 1310
Background
Although immunotherapy with immune checkpoint inhibitors (ICIs) has been remarkably effective across multiple cancer types. Several reports showed the gut microbiome is a possible factor proposed to impact the efficacy of ICI. The relationship between gut microbiome and immune status in tumor microenvironment remains unclear. Short-chain fatty acids (SCFAs) are major end products of gut microbiota metabolites and are known to wide-ranging impacts on host physiology. The objective of this study was to evaluate the fecal SCFA (fSCFA) in solid cancer patients treated with anti-programmed death-1 inhibitor (PD1i).
Methods
This was a prospective study of patients with cancer who were treated with nivolumab (2 mg/kg, every 3 weeks; 3 mg/kg, every 2 weeks; or 240 mg/body, every 2 weeks) or pembrolizumab (200 mg/body, every 3 weeks) at Kyoto University Hospital between July 2016 and April 2018. Patients were classified into two groups: responder (R) with an objective response and non-responder (NR) according to the Response Evaluation Criteria in Solid Tumors version 1.1. Fecal samples were collected before administration of PD-1 inhibitor and were analyzed by the ultra-high performance liquid chromatography-tandem mass spectrometry system.
Results
A total of 40 patients (melanoma 19; head and neck cancer 7; gastrointestinal cancer 7; genitourinary cancer 4; other 3) were enrolled. The response rate was 22.5%. The fSCFAs in R patients (n = 9) were significantly higher than that in NR patients (n = 31) (p < 0.001). Progression-free survival (PFS) was significantly longer in patients with high fSCFAs than patients with lower fSCFAs (median 5.5 vs. 1.4 months, hazard ratio [HR] 0.35, 95% confidence interval [CI] 0.17-0.72). In melanoma patients, PFS was also significantly longer in patients with high fSCFAs than that with lower fSCFAs (median 6.1 vs. 1.4 months, HR 0.30, 95% CI 0.10-0.89).
Conclusions
The fSCFA could predict the efficacy of PD1i.
Clinical trial identification
UMIN000023303.
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Novartis Pharma.
Disclosure
M. Nomura: Research grant / Funding (self): Novartis Pharma. All other authors have declared no conflicts of interest.
Resources from the same session
5517 - Molecular fingerprinting in breast cancer (BC) screening using Quantum Optics (QO) technology combined with an artificial intelligence (AI) approach applying the concept of “molecular profiles at n variables (MPnV)”: a prospective pilot study.
Presenter: Jean-Marc Nabholtz
Session: Poster Display session 3
Resources:
Abstract
2152 - Inferring the correlation between incidence rates of melanoma and the average tumor-specific epitope binding ability of HLA class I molecules in different populations
Presenter: Istvan Miklos
Session: Poster Display session 3
Resources:
Abstract
4382 - Thermal Liquid Biopsy as a Valuable Tool in Lung Cancer Screening Programs
Presenter: Alberto Rodrigo
Session: Poster Display session 3
Resources:
Abstract
2465 - Towards a screening test for cancer by circulating DNA analysis
Presenter: Rita Tanos
Session: Poster Display session 3
Resources:
Abstract
3788 - Evaluation of a successful launch of the MammaPrint and BluePrint NGS kit
Presenter: Leonie Delahaye
Session: Poster Display session 3
Resources:
Abstract
3863 - Analysis of prognostic factors on overall survival in elderly women treated for early breast cancer using data mining and machine learning
Presenter: Pierre Heudel
Session: Poster Display session 3
Resources:
Abstract
1993 - Circulating tumor cell detection in epithelial ovarian cancer using dual-component antibodies targeting EpCAM and FRα
Presenter: Na Li
Session: Poster Display session 3
Resources:
Abstract
4281 - CEUS of the breast: Is it feasible in improved performance of BI-RADS evaluation of critical breast lesions?——A multi-center prospective study in China
Presenter: Jun Luo
Session: Poster Display session 3
Resources:
Abstract
2268 - Classification of abnormal findings on ring-type dedicated breast PET for detecting breast cancer
Presenter: Shinsuke Sasada
Session: Poster Display session 3
Resources:
Abstract
4035 - Prediction of benign and malignant breast masses using digital mammograms texture features
Presenter: Cui Yanhua
Session: Poster Display session 3
Resources:
Abstract