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<p>Comprehensive genomic profiling (CGP) is widely used to identify actionable alterations and guide precision oncology, yet only a minority of tested patients receive genome-matched therapies, underscoring a gap between genomic findings and clinical benefit. We hypothesized that this gap may partly reflect variation in the reliability and interpretability of genomic information generated from specimens of different quality and by different assay modalities. To examine this possibility, we performed a retrospective multicenter analysis of 2002 CGP tests conducted between 2019 and 2025 across 13 institutions in Japan. Detection of short variants, copy number alterations (CNAs), structural variants, and genomic signatures, including microsatellite instability, tumor mutational burden, and homologous recombination deficiency signature, was compared among FoundationOne CDx specimens classified as pass (F1-pass) or qualified (F1-qual) and liquid-based CGP (liq-CGP). Short variant detection remained largely preserved in F1-qual specimens, whereas CNA and genomic signature detection were substantially reduced. In pancreatic adenocarcinoma, <i>KRAS</i> variants were detected in 93% of F1-pass, 88% of F1-qual, and 57% of liq-CGP cases. These differences affected the proportion of patients offered genome-matched therapies. Machine learning models predicted QC status with area-under-the-curve values of 0.72–0.78. Our findings support QC-aware CGP selection in routine precision oncology.</p>

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Specimen quality shapes the actionable genomic landscape in comprehensive cancer genomic profiling

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月11日

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  • Hikaru Nakahara,
  • Hiroaki Niitsu,
  • Masanori Motonaga,
  • Hiroaki Matsuo,
  • Koji Arihiro,
  • C.Nelson Hayes,
  • Takao Hinoi

摘要

Comprehensive genomic profiling (CGP) is widely used to identify actionable alterations and guide precision oncology, yet only a minority of tested patients receive genome-matched therapies, underscoring a gap between genomic findings and clinical benefit. We hypothesized that this gap may partly reflect variation in the reliability and interpretability of genomic information generated from specimens of different quality and by different assay modalities. To examine this possibility, we performed a retrospective multicenter analysis of 2002 CGP tests conducted between 2019 and 2025 across 13 institutions in Japan. Detection of short variants, copy number alterations (CNAs), structural variants, and genomic signatures, including microsatellite instability, tumor mutational burden, and homologous recombination deficiency signature, was compared among FoundationOne CDx specimens classified as pass (F1-pass) or qualified (F1-qual) and liquid-based CGP (liq-CGP). Short variant detection remained largely preserved in F1-qual specimens, whereas CNA and genomic signature detection were substantially reduced. In pancreatic adenocarcinoma, KRAS variants were detected in 93% of F1-pass, 88% of F1-qual, and 57% of liq-CGP cases. These differences affected the proportion of patients offered genome-matched therapies. Machine learning models predicted QC status with area-under-the-curve values of 0.72–0.78. Our findings support QC-aware CGP selection in routine precision oncology.