Abstract 1898
Background
Limitations of integrating biological knowledgebases with genomics impedes the development of predictive correlates that would help in personalization of immunotherapy. Non-small cell lung cancer (NSCLC) patients treated with atezolizumab, an antiprogrammed death-ligand 1 (PDL1) antibody, have better overall survival when compared to patients receiving docetaxel chemotherapy in Poplar (Lancet, 2016) and Oak (Lancet, 2017). We hypothesized that patterns in the mutations of immune signatures would correlate with the immunotherapeutic effect of atezolizumab in NSCLC.
Methods
Sequencing data from Poplar (n = 277 patients) and Oak (n = 725 patients) trials was analyzed for understanding genomic alterations in relation to patient outcomes. Signatures from publicly-available knowledgebases were integrated with the genomics and clinicopathological data into an algorithm for identifying patterns correlative of immunotherapeutic response.
Results
Patients benefitting from atezolizumab were more likely to have mutations in oncoimmunity-related genes which were significantly overlapping between the two trials. These overlapping genes were used to develop a de novo signature comprising of CDKN1A, ERRFI1, JAK2, NOTCH2, ACVR1B, NFKBIA, GNA13, MERTK, BTG1, CDKN1B, FOXP1, PDK1, ETV6, MLL2, SMAD3, DICER1 and BRCA2. Mutations in any of the genes within the signature identified patient subpopulations with higher immunotherapeutic response to Atezolizumab in both Oak (HR = 0.3, P = 1.8e-6 versus HR = 0.76, P = 5.5e-3 for entire cohort) and Poplar (HR = 0.18 and P = 3.6e-2 versus HR = 0.71, P = 0.023 for all patients) trials. Prediction efficiency of the signature was significantly better than established biomarkers such as PDL1 staining (Nature, 2014) in both Oak (HR: 0.58 and P = 1.8e-6) and Poplar (HR: 0.58 and P = 0.04) trials indicating that genomic correlates could add significant value to existing modalities in predicting immunotherapy response.
Conclusions
In summary, integration of biological knowledgebases with genomics suggests that a rheostat of mutational burden in non-overlapping genesets is associated with immunotherapeutic effect and identifies novel genomic correlates for response to Atezolizumab.
Clinical trial identification
NCT02008227; NCT01903993.
Editorial acknowledgement
Legal entity responsible for the study
Roche.
Funding
Roche.
Disclosure
D.R. Gandara: Research grant: Bristol-Myers Squibb, Roche-Genentech, Novartis, Merck; Consultancy: AstraZeneca, Celgene, CellMax Life, FujiFilm, Roche-Genentech, Guardant Health, Inviata, IO Biotech, Lilly, Liquid Genomics, Merck, Samsung Bioepis, Pfizer. All other authors have declared no conflicts of interest.
Resources from the same session
5105 - Fresh blood Immune cell monitoring in patients treated with nivolumab in the GETUG-AFU26 NIVOREN study: association with toxicity and treatment outcome
Presenter: Aude DESNOYER
Session: Poster Display session 3
Resources:
Abstract
1877 - Advanced clear-cell renal cell carcinoma (accRCC): association of microRNAs (miRNAs) with molecular subtypes, mRNA targets and outcome.
Presenter: Annelies Verbiest
Session: Poster Display session 3
Resources:
Abstract
5543 - Prior tyrosine kinase inhibitors (TKI) and antibiotics (ATB) use are associated with distinct gut microbiota ‘guilds’ in renal cell carcinoma (RCC) patients
Presenter: Valerio Iebba
Session: Poster Display session 3
Resources:
Abstract
2689 - mTOR mutations are not associated with shorter PFS and OS in patients treated with mTOR inhibitors
Presenter: Cristina Suarez Rodriguez
Session: Poster Display session 3
Resources:
Abstract
3069 - Efficacy of immune checkpoint inhibitors (ICI) and genomic alterations by body mass index (BMI) in Advanced Renal Cell Carcinoma (RCC)
Presenter: Aly-Khan Lalani
Session: Poster Display session 3
Resources:
Abstract
5089 - Finding the Right Biomarker for Renal Cell Carcinoma (RCC): Nivolumab treatment induces the expression of specific peripheral lymphocyte microRNAs in patients with durable and complete response.
Presenter: Lorena Incorvaia
Session: Poster Display session 3
Resources:
Abstract
2594 - Algorithms derived from quantitative pathology can be a gatekeeper in patient selection for clinical trials in localised clear cell renal cell carcinoma (ccRCC)
Presenter: In Hwa Um
Session: Poster Display session 3
Resources:
Abstract
2566 - High baseline blood volume is an independent favorable prognostic factor for overall and progression-free survival in patients with metastatic renal cell carcinoma
Presenter: Aska Drljevic-nielsen
Session: Poster Display session 3
Resources:
Abstract
2675 - Impact of estimand selection on adjuvant treatment outcomes in renal cell carcinoma (RCC)
Presenter: Daniel George
Session: Poster Display session 3
Resources:
Abstract
1541 - TERT gene fusions characterize a subset of metastatic Leydig cell tumors
Presenter: Bozo Kruslin
Session: Poster Display session 3
Resources:
Abstract