Abstract 219P
Background
Molecular profiling of tumors is an essential step in the management of cancer patients, enabling personalized treatment decisions. Oncomine Comprehensive Assay Plus (OCA+) is an amplicon-based next-generation sequencing solution that can detect multiple biomarkers, including complex biomarkers, in a single assay. Here, we aimed to evaluate the sensitivity, specificity, and concordance of this comprehensive genomic profiling solution in detecting various types of biomarkers in a multicentric study using a cohort of 190 pre-characterized clinical tumor samples.
Methods
DNA and/or RNA were obtained from formalin-fixed paraffin-embedded (FFPE) tumor samples from patients with different cancer types from 5 different centers. Samples studied addressed the complete variety of genomic alterations targeted by the Oncomine Comprehensive Assay Plus. OCA+ was used to generate libraries that were sequenced using the Ion S5 Prime system and analyzed using Ion Reporter Oncomine Comprehensive Plus - w3.0 workflow. Single nucleotide variants (SNVs), insertions/deletions (indels), copy number alterations (CNAs), gene fusions, tumor mutation burden (TMB), microsatellite instability (MSI) and Genomic instability (GIN related to HRD) results were compared to orthogonal and gold standard methods.
Results
OCA+ demonstrated a total success rate of 97.2%. High sensitivity and specificity were obtained in detecting multiple biomarkers, including complex biomarkers. The assay detected >95% of SNVs and indels with a variant allele frequency (VAF) of ≥5%, and identified gene fusions, TMB, MSI and GIN with high concordance to orthogonal methods, 90%, 70%, 84% and 93% respectively.
Conclusions
OCA+ is a sensitive and specific platform for molecular tumor profiling, including the detection of complex biomarkers. The high concordance rate with orthogonal methods highlights the assay's potential in guiding clinical decision-making for personalized cancer care. OCA+ may provide comprehensive genomic information for cancer management and may be a valuable tool for further implementing precision medicine in oncology.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Thermo Fisher.
Funding
Thermo Fisher.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
185P - Real-world data analysis of genomic profiling-matched targeted therapy outcomes in patients with fusion-positive NSCLC
Presenter: Jyoti Patel
Session: Poster session 01
186P - Pooled efficacy and safety data of alectinib (A) vs. crizotinib (C) from the randomized phase III ALEX and J-ALEX trials
Presenter: Marco Tagliamento
Session: Poster session 01
187P - Ipatasertib and atezolizumab in cancers with increased PI3K-AKT pathway activity: First results from the CRAFT trial
Presenter: Christoph Heilig
Session: Poster session 01
188P - The landscape of SMARCA2 genomic alterations in Chinese cancer patients
Presenter: Chen Jiaqi
Session: Poster session 01
189P - Design and enrollment for a classifier development study for a blood-based multi-cancer early detection (MCED) test
Presenter: Christopher Douville
Session: Poster session 01
190P - Quantitative serum tumor markers (CEA, CA19-9, and CA-125) are independently predictive of survival in patients with appendiceal adenocarcinoma
Presenter: John Paul Shen
Session: Poster session 01
191P - Novel approach to proficiency testing demonstrates wide gaps in biomarker quality for colon cancer treatment
Presenter: Kassandra Bisson, Brandon Sheffield
Session: Poster session 01
192P - Impact of oncogenic fibroblast growth factor receptor (FGFR) alterations in patients with advanced solid tumors in a real-world setting
Presenter: Hussein Sweiti
Session: Poster session 01
194P - Early kinetics of C-reactive protein for cancer-agnostic prediction of therapy response and mortality in patients treated with immune checkpoint inhibitors: A multi-center cohort study
Presenter: Dominik Barth
Session: Poster session 01
195P - Identification of biomarkers associated with checkpoint inhibitor pneumonitis based on serum proteomic approach and construction of an online interactive visual prediction model
Presenter: Xiaohui Jia
Session: Poster session 01