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Background <p>Osteosarcoma is a highly metastatic bone malignancy, with hematogenous spread as the leading cause of mortality. Circulating tumor cells (CTCs) offer a minimally invasive window to detect metastatic potential and real-time tumor dynamics. However, detecting osteosarcoma CTCs is challenging due to their rarity in the bloodstream and eligibility for positive-enrichment methods targeting epithelial markers.</p> Methods <p>We developed MALDI Technology Enabling Classification of Circulating Tumor Cell (MALDITEC-CTC), a novel platform that combines negative-selection CTC enrichment with MALDI-TOF mass spectrometry for osteosarcoma CTC detection. A custom main spectrum profile (MSP) database was generated from normal cells, carcinoma and sarcoma cell lines, patient-derived osteosarcoma cells (PDCs), and peripheral blood mononuclear cells (PBMCs). Using the MALDI Biotyper, CTCs in blood samples were identified by log(score) matching against the MSP database. Diagnostic performance was evaluated in 12 osteosarcoma patients and 11 healthy donors.</p> Results <p>CTC-enriched samples from patients showed high log(score) matches to their corresponding PDCs, supporting accurate identification. At the cut-off score of 1.625, MALDITEC-CTC achieved 67% sensitivity and 90.9% specificity with an area under the curve of 0.871 for distinguishing patients from healthy donors. Importantly, CTC-positive patients showed a higher tendency to develop metastasis than CTC-negative patients, indicating potential prognostic value.</p> Conclusions <p>MALDITEC-CTC demonstrates the clinical feasibility of a rapid, label-free, proteomics-based approach for detecting osteosarcoma CTCs. This platform may enable early risk stratification for metastasis and non-invasive monitoring of tumor progression in osteosarcoma patients.</p>

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Performance and pilot clinical validation of MALDITEC-CTC: a circulating tumor cell detection platform using whole-cell MALDI-TOF MS fingerprinting in osteosarcoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月16日

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  • Santhasiri Orrapin,
  • Nutnicha Sirikaew,
  • Wararat Chiangjong,
  • Somchai Chutipongtanate,
  • Pimpisa Teeyakasem,
  • Sasimol Udomruk,
  • Sutpirat Moonmuang,
  • Songphon Sutthitthasakul,
  • Petlada Yongpitakwattana,
  • Areerak Phanphaisarn,
  • Pathacha Suksakit,
  • Arnat Pasena,
  • Ratikorn Kamngoen,
  • Jisnuson Svasti,
  • Voraratt Champattanachai,
  • Jongkolnee Settakorn,
  • Dumnoensun Pruksakorn,
  • Parunya Chaiyawat

摘要

Background

Osteosarcoma is a highly metastatic bone malignancy, with hematogenous spread as the leading cause of mortality. Circulating tumor cells (CTCs) offer a minimally invasive window to detect metastatic potential and real-time tumor dynamics. However, detecting osteosarcoma CTCs is challenging due to their rarity in the bloodstream and eligibility for positive-enrichment methods targeting epithelial markers.

Methods

We developed MALDI Technology Enabling Classification of Circulating Tumor Cell (MALDITEC-CTC), a novel platform that combines negative-selection CTC enrichment with MALDI-TOF mass spectrometry for osteosarcoma CTC detection. A custom main spectrum profile (MSP) database was generated from normal cells, carcinoma and sarcoma cell lines, patient-derived osteosarcoma cells (PDCs), and peripheral blood mononuclear cells (PBMCs). Using the MALDI Biotyper, CTCs in blood samples were identified by log(score) matching against the MSP database. Diagnostic performance was evaluated in 12 osteosarcoma patients and 11 healthy donors.

Results

CTC-enriched samples from patients showed high log(score) matches to their corresponding PDCs, supporting accurate identification. At the cut-off score of 1.625, MALDITEC-CTC achieved 67% sensitivity and 90.9% specificity with an area under the curve of 0.871 for distinguishing patients from healthy donors. Importantly, CTC-positive patients showed a higher tendency to develop metastasis than CTC-negative patients, indicating potential prognostic value.

Conclusions

MALDITEC-CTC demonstrates the clinical feasibility of a rapid, label-free, proteomics-based approach for detecting osteosarcoma CTCs. This platform may enable early risk stratification for metastasis and non-invasive monitoring of tumor progression in osteosarcoma patients.