Implementation Benchmark of Tumor-Agnostic Eligibility Signals Across Routine Comprehensive Genomic Profiling Platforms in Japan: A Nationwide C-CAT Analysis

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Authors: Shinya Kajiura, Naohiko Nakamura, Ryuji Hayashi
Cited by: 1
References: 16

Abstract

Routine precision oncology requires realistic benchmarks for tumor-agnostic eligibility signals observed in heterogeneous comprehensive genomic profiling (CGP) pathways. We performed a retrospective descriptive analysis of anonymized aggregated nationwide Center for Cancer Genomics and Advanced Therapeutics (C-CAT) data in Japan, including 97,343 CGP-tested cases summarized across five routine CGP platforms and categorized into 12 prespecified organ groups for analysis. The primary strict approved set endpoint was the case-level union of MSI-H, TMB-H, NTRK fusion/rearrangement, RET fusion/rearrangement, and ERBB2 amplification; the expanded practical set endpoint additionally included ALK fusion/rearrangement and BRAF V600E. The primary strict approved set endpoint was observed in 14,005 cases (14.4%), and the expanded practical set endpoint in 15,911 cases (16.3%), adding 1906 cases and increasing the observed rate by 2.0 percentage points. Signals varied across organ groups and platform/specimen contexts. TMB-H and ERBB2 amplification numerically dominated the primary set signal, whereas NTRK and RET fusion/rearrangement remained rare. These observed frequencies should be interpreted as case-level implementation signals surfaced through routine CGP rather than assay superiority evidence, biological prevalence estimates, or treatment-benefit data. This nationwide, platform-aware benchmark supports practical interpretation of tumor-agnostic eligibility signals in routine CGP practice in Japan.

Fields of Study & Subjects

Cancer Genomics and Diagnostics Lung Cancer Treatments and Mutations Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
Current Oncology
Publisher
MDPI AG
Volume
33
Issue
6
Pages
324–324
Publication date
30 May 2026
Language
EN