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Peer-reviewedCC BY 4.0NPJ Precision Oncology

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

3 more authors
  1. 1Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Center for Molecular Diagnostics, Peking University Cancer Hospital & Institute, Beijing, China
  2. 2Geneseeq Research Institute, Nanjing Geneseeq Technology Inc, Nanjing, Jiangsu China
  3. 3State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Center for Molecular Diagnostics, Peking University Cancer Hospital & Institute, Beijing, China

Abstract

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.

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BibTeX
@article{zhang2026pancancer,
  title = {{Pan-cancer analysis of tissue-plasma genomic concordance reveals enhanced concordance with liver metastasis and plasma clonality as predictor of poorer overall survival}},
  author = {Meng Zhang and Yi Feng and Xue Du and Changda Qu and Meizhu Meng and Meiying Ye and Min Liang and Ziran Yang and Wenjuan Gong and Xingyu Ma and Jialiang Guo and Wenmei Li and Sha Wang and Hua Bao and Shuqin Jia},
  journal = {NPJ Precision Oncology},
  year = {2026},
  month = jul,
  doi = {10.1038/s41698-026-01549-0},
  url = {https://doi.org/10.1038/s41698-026-01549-0},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Pan-cancer analysis of tissue-plasma genomic concordance reveals enhanced concordance with liver metastasis and plasma clonality as predictor of poorer overall survival
AU  - Meng Zhang
AU  - Yi Feng
AU  - Xue Du
AU  - Changda Qu
AU  - Meizhu Meng
AU  - Meiying Ye
AU  - Min Liang
AU  - Ziran Yang
AU  - Wenjuan Gong
AU  - Xingyu Ma
AU  - Jialiang Guo
AU  - Wenmei Li
AU  - Sha Wang
AU  - Hua Bao
AU  - Shuqin Jia
PY  - 2026
DA  - 2026/07/03
JO  - NPJ Precision Oncology
DO  - 10.1038/s41698-026-01549-0
UR  - https://doi.org/10.1038/s41698-026-01549-0
AB  - 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.
SN  - 2397-768X
ER  -