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Background <p>Curebest™ 95GC breast is a multigene assay independently developed in Japan, that utilizes DNA microarray technology to analyze the expression patterns of the 95 genes in breast cancer tissue. It calculates a 95GC score and classifies postoperative recurrence risk into two categories: Low and High. This study aimed to evaluate whether the 95GC score can also be calculated using RNA sequencing (RNAseq), and to assess the clinical utility of mutational profiles derived from RNAseq data.</p> Methods <p>To transition the 95GC scoring method from microarray to RNAseq, we analyzed a total of 151 breast cancer cases, comprising a training set of 34 cases and a validation set of 117 cases. Whole RNAseq was performed using residual RNA samples after microarray analysis. The 95GC scores calculated from RNAseq were compared with those from microarray, and comprehensive mutation profiling was conducted.</p> Results <p>The correlation coefficients between the 95GC score (microarray) and the 95GC score (RNAseq) were high in both the training set (<i>R</i> = 0.96, R² = 0.93) and the validation set (<i>R</i> = 0.95, R² = 0.90). Comprehensive mutation analysis identified eight frequently mutated genes (each mutated in &gt; 10% of cases): <i>SCAMP1</i> (66%), <i>FLNB</i> (61%), <i>TTN</i> (40%), <i>BLCAP</i> (31%), <i>FLNA</i> (25%), <i>PIK3CA</i> (18%), <i>CDK13</i> (11%), and <i>OBSCN</i> (10%). Furthermore, it was feasible to analyze mutations in the 309 genes included in the FoundationOne<sup>®</sup>CDx panel and the 124 genes included in the OncoGuide™ NCC Oncopanel System.</p> Conclusions <p>This study demonstrates the potential of RNAseq-based analysis to enable both recurrence risk prediction and companion diagnostics for treatment selection in breast cancer, suggesting a novel direction for the development of next-generation multigene assays. Further accumulation of cases is warranted to evaluate the concordance of mutation profiles between DNAseq and RNAseq in breast cancer-related genes.</p>

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Integration of gene expression profiling and mutation analysis via RNA sequencing: transitioning the 95-gene classifier to a next-generation platform in early-stage HR+/HER2- breast cancer

  • 期刊论文

  • 发表日期：

    2026年4月1日

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  • Chikage Kato,
  • Yoshiaki Sota,
  • Sae Kitano,
  • Akira Watanabe,
  • Maiko Nishida,
  • Daitho Motonari,
  • Yuria Saito,
  • Masaki Kobayashi,
  • Midori Morita,
  • Koichi Sakaguchi,
  • Kenzo Shimazu,
  • Yasuto Naoi

摘要

Background

Curebest™ 95GC breast is a multigene assay independently developed in Japan, that utilizes DNA microarray technology to analyze the expression patterns of the 95 genes in breast cancer tissue. It calculates a 95GC score and classifies postoperative recurrence risk into two categories: Low and High. This study aimed to evaluate whether the 95GC score can also be calculated using RNA sequencing (RNAseq), and to assess the clinical utility of mutational profiles derived from RNAseq data.

Methods

To transition the 95GC scoring method from microarray to RNAseq, we analyzed a total of 151 breast cancer cases, comprising a training set of 34 cases and a validation set of 117 cases. Whole RNAseq was performed using residual RNA samples after microarray analysis. The 95GC scores calculated from RNAseq were compared with those from microarray, and comprehensive mutation profiling was conducted.

Results

The correlation coefficients between the 95GC score (microarray) and the 95GC score (RNAseq) were high in both the training set (R = 0.96, R² = 0.93) and the validation set (R = 0.95, R² = 0.90). Comprehensive mutation analysis identified eight frequently mutated genes (each mutated in > 10% of cases): SCAMP1 (66%), FLNB (61%), TTN (40%), BLCAP (31%), FLNA (25%), PIK3CA (18%), CDK13 (11%), and OBSCN (10%). Furthermore, it was feasible to analyze mutations in the 309 genes included in the FoundationOne®CDx panel and the 124 genes included in the OncoGuide™ NCC Oncopanel System.

Conclusions

This study demonstrates the potential of RNAseq-based analysis to enable both recurrence risk prediction and companion diagnostics for treatment selection in breast cancer, suggesting a novel direction for the development of next-generation multigene assays. Further accumulation of cases is warranted to evaluate the concordance of mutation profiles between DNAseq and RNAseq in breast cancer-related genes.