Abstract 226P
Background
Yttrium-90 (Y90)-resin microspheres radioembolization followed by nivolumab (Nivo) has shown encouraging response rate in advanced hepatocellular carcinoma (HCC), but only a subset of patients benefit from it. Predictive biomarkers help to identify patients for the treatment.
Methods
Longitudinal plasma and peripheral blood mononuclear cells (PBMCs) collection from HCC patients who received sequential Y90-RE followed by nivolumab (CA209-678; NCT03033446) allowed assessment of dynamics changes. Predictor selection procedure includes individual timepoint comparison, average analysis, trajectory description, responsiveness prediction, and combined modalities validation. 65-plex Human ProcartaPlex Luminex panel was employed to examine the concentration of cytokines and chemokines in 187 plasma samples collected at eight timepoints (responder [R]=11, non-responder [NR]=22). Immunomonitoring of PBMCs (NR=12, R=5) was assessed with a 39-plex Cytek panel followed by dimension reduction analysis. CXCL9 was reported impacting the immune treatment response, thus we focused on CXCL9+ CD8 cluster. Mixed models were fitted for responsiveness represented by Luminex analytes and CD8 phenotypes. Logistic regression and Cox model were fitted for the association between analytes and treatment response and 3-year overall survival (OS). Biomarkers showed significant association (P<0.05) and AUC > 0.7 were selected as the potential predictors.
Results
All Luminex biomarkers showed difference between the R and NR groups 14 days after Y90 treatment (P<0.05). The higher increment of IL-18, IL-12p70, and CCL24 after Y90 treatment related to better treatment response and 3-year OS. CXCL9+ and CXCR3+ CD8 clusters differed between R and NR on the 21st and 35th day after Y90-RE, respectively. IL-18 and IL-12p70 were significantly associated with CXCL9+ and CXCR3+ CD8 clusters in the Rs, but not NRs.
Conclusions
IL-18, IL-12p70, and CCL24 were potential predictors for treatment response as well as 3-year OS for HCC patients treated by Y90-Nivo.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
175P - Radiomic biomarker of vessel tortuosity for monitoring treatment change: Preliminary findings in prospective evaluation of ECOG-ACRIN EA5163
Presenter: Pushkar Mutha
Session: Poster session 01
176P - Enhancing immunotherapy response prediction via multimodal integration of radiology and pathology deep learning models
Presenter: Marta Ligero
Session: Poster session 01
177P - Revealing differences in radiosensitivity of advanced non-small cell lung cancer (NSCLC)through single-cell sequencing data
Presenter: Peimeng You
Session: Poster session 01
178P - Explainable radiomics, machine and deep learning models to predict immune-checkpoint inhibitor treatment efficacy in advanced non-small cell lung cancer patients
Presenter: Leonardo Provenzano
Session: Poster session 01
179P - Molecular tumor board directed treatment for patients with advanced stage solid tumors: A case-control study
Presenter: Dhruv Bansal
Session: Poster session 01
180P - An HLA-diet-oriented system unveiling organ-specific occurrence of multiple primary cancers (MPC) with prevention strategy: A large cohort study of 47,550 cancer patients
Presenter: Zixuan Rong
Session: Poster session 01
181P - GeNeo: Agnostic comprehensive genomic profiling versus limited panel organ-directed next-generation sequencing within the Belgian PRECISION initiative
Presenter: Philippe Aftimos
Session: Poster session 01
182P - ALK fusion detection by RNA next-generation sequencing (NGS) compared to DNA in a large, real-world non-small cell lung cancer (NSCLC) dataset
Presenter: Wade Iams
Session: Poster session 01
183P - Frequency of actionable fusions in 7,735 patients with solid tumors
Presenter: Kevin McDonnell
Session: Poster session 01
184P - Patient-specific HLA-I genotypes predict response to immune checkpoint blockade
Presenter: Kyrillus Shohdy
Session: Poster session 01