An approach for improvement of the accuracy of cancer gene panel testing.

BACKGROUND: Tissue-based comprehensive genomic profiling (CGP) is increasingly being employed for genotype-directed therapies in patients with advanced cancer. However, tissue availability may limit their potential applications. In Japan, the cost of cancer gene panel tests is covered by public insurance for patients diagnosed with advanced solid tumors once in their lifetime. Therefore, it is essential to improve the success rate (reportability) and accuracy of CGP tests. The purpose of this study was to identify the factors associated with efficient and accurate CGP testing using relevant information obtained from real-world data. METHODS: This study included 159 samples analyzed using tumor-only panel FoundationOne® CDx cancer genome profiling (F1CDx) and 85 samples analyzed using matched-pair panel OncoGuide™ NCC Oncopanel system (NCCOP) at St. Marianna University Hospital. Sample characteristics (fixation conditions, storage period, histology, tumor cell ratio, and genomic tumor cell content), CGP performance, and quality control status were evaluated across all 244 tested samples. RESULTS: In 237/244 samples (97.1%), CGP testing results were successfully obtained [F1CDx, 99.4% (158/159) and NCCOP, 92.9% (79/85)]. An increased number of fibroblasts, inflammatory cells, and necrotic tumor cells, long-term storage, and/or prolonged fixation of tissue sections were involved in the unreported results and/or qualified CGP results. In addition, a negative correlation between median insert size values and ΔΔCq was observed in the NCCOP system. CONCLUSION: We identified various factors associated with efficient and accurate CGP testing using relevant information obtained from real-world data, suggesting that thorough selection and preparation of tissue sections could optimize CGP and maximize useful information.

Droplet digital polymerase chain reaction assay and peptide nucleic acid-locked nucleic acid clamp method for RHOA mutation detection in angioimmunoblastic T-cell lymphoma.

Angioimmunoblastic T-cell lymphoma (AITL) is a subtype of nodal peripheral T-cell lymphoma (PTCL). Somatic RHOA mutations, most frequently found at the hotspot site c.50G > T, p.Gly17Val (G17V RHOA mutation) are a genetic hallmark of AITL. Detection of the G17V RHOA mutations assists prompt and appropriate diagnosis of AITL. However, an optimal detection method for the G17V RHOA mutation remains to be elucidated. We compared the sensitivity and concordance of next-generation sequencing (NGS), droplet digital PCR (ddPCR) and peptide nucleic acid-locked nucleic acid (PNA-LNA) clamp method for detecting the G17V RHOA mutation. G17V RHOA mutations were identified in 27 of 67 (40.3%) PTCL samples using NGS. ddPCR and PNA-LNA clamp method both detected G17V mutations in 4 samples in addition to those detected with NGS (31 of 67, 46.3%). Additionally, variant allele frequencies with ddPCR and those with NGS showed high concordance (P < .001). Three other RHOA mutations involving the p.Gly17 position (c.[49G > T;50G > T], p.Gly17Leu in PTCL198; c.[50G > T;51A > C], p.Gly17Val in PTCL216; and c.50G > A, p.Gly17Glu in PTCL223) were detected using NGS. These sequence changes could not appropriately be detected using the ddPCR assay and the PNA-LNA clamp method although both indicated that the samples might have mutations. In total, 34 out of 67 PTCL samples (50.7%) had RHOA mutations at the p.Gly17 position. In conclusion, our results suggested that a combination of ddPCR/PNA-LNA clamp methods and NGS are best method to assist the diagnosis of AITL by detecting RHOA mutations at the p.Gly17 position.