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<p>Circulating tumor DNA (ctDNA) enables noninvasive tumor genotyping, yet its concordance with tissue remains unclear. Using a 437-gene panel in 1111 pan-cancer patients, we compared somatic variants between ctDNA and matched tissues. ctDNA detection sensitivity (61.5%) correlated with advanced stage (<i>r</i> = 0.955, <i>p</i> = 0.045) and tumor size (<i>r</i> = 0.955, <i>p</i> = 0.045). Actionable alterations were detected in 49.2% (ctDNA) and 77.1% (tissue) of patients. Both shared frequently mutated genes (<i>TP53</i>, APC, <i>KRAS</i>, <i>LRP1B</i>, <i>PIK3CA</i>) and pathways (RTK-RAS, p53, DNA repair). ctDNA-specific mutations were predominantly subclonal (61.5% vs. 9.7% in tissue-concordant variants) and less frequently drivers. Machine learning linked elevated concordance to progressive disease, liver metastasis, and larger tumors. ctDNA-positivity predicted worse prognosis (HR = 2.019, <i>p</i> &lt; 0.001), exacerbated by subclonal enrichment. These findings underscore ctDNA’s capacity to reveal subclonality for risk stratification. While tissue remains superior for initial detection, ctDNA complements biopsies by capturing clonal heterogeneity.</p>

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Pan-cancer analysis of tissue-plasma genomic concordance reveals enhanced concordance with liver metastasis and plasma clonality as predictor of poorer overall survival

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月3日

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  • Meng Zhang,
  • Yi Feng,
  • Xue Du,
  • Changda Qu,
  • Meizhu Meng,
  • Meiying Ye,
  • Min Liang,
  • Ziran Yang,
  • Wenjuan Gong,
  • Xingyu Ma,
  • Jialiang Guo,
  • Wenmei Li,
  • Sha Wang,
  • Hua Bao,
  • Shuqin Jia

摘要

Circulating tumor DNA (ctDNA) enables noninvasive tumor genotyping, yet its concordance with tissue remains unclear. Using a 437-gene panel in 1111 pan-cancer patients, we compared somatic variants between ctDNA and matched tissues. ctDNA detection sensitivity (61.5%) correlated with advanced stage (r = 0.955, p = 0.045) and tumor size (r = 0.955, p = 0.045). Actionable alterations were detected in 49.2% (ctDNA) and 77.1% (tissue) of patients. Both shared frequently mutated genes (TP53, APC, KRAS, LRP1B, PIK3CA) and pathways (RTK-RAS, p53, DNA repair). ctDNA-specific mutations were predominantly subclonal (61.5% vs. 9.7% in tissue-concordant variants) and less frequently drivers. Machine learning linked elevated concordance to progressive disease, liver metastasis, and larger tumors. ctDNA-positivity predicted worse prognosis (HR = 2.019, p < 0.001), exacerbated by subclonal enrichment. These findings underscore ctDNA’s capacity to reveal subclonality for risk stratification. While tissue remains superior for initial detection, ctDNA complements biopsies by capturing clonal heterogeneity.