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Rapid Identification of Pathogens

MALDI-TOF MS has transformed clinical microbiology by offering a rapid and reliable method for pathogen identification. The traditional approach to microbial identification typically involves time-consuming culture techniques and biochemical tests, which can delay the initiation of appropriate antimicrobial therapy. MALDI-TOF MS avoids these delays by using characteristic ribosomal protein mass patterns of microbial cells, enabling accurate species-level identification within minutes.Principle...

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Related Experiment Video

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Rapid Isolation of Viable Circulating Tumor Cells from Patient Blood Samples
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Minimizing false positives for CTC identification.

Adriana Carneiro1, Paulina Piairo2, Beatriz Matos3

  • 1International Iberian Nanotechnology Laboratory, Avenida Mestre José Veiga s/n, 4715-330, Braga, Portugal; Experimental Pathology and Therapeutics Group, Research Center of IPO Porto (CI IPOP) / RISE @ CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto), Porto Comprehensive Cancer Center (Porto.CCC), 4200-072, Porto, Portugal; Instituto de Ciências Biomédicas Abel Salazar (ICBAS) da Universidade do Porto, Porto, Portugal.

Analytica Chimica Acta
|January 14, 2024
PubMed
Summary

Improved detection of Circulating Tumour Cells (CTCs) is crucial for cancer monitoring. This study introduces a double exclusion method using CD15 and CD45 antibodies to accurately identify CTCs by excluding white blood cells.

Keywords:
Circulating tumour cellsGranulocytesLiquid biopsyMicrofluidics

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Area of Science:

  • Oncology
  • Immunology
  • Biotechnology

Background:

  • Cancer metastasis is a major cause of death globally.
  • Circulating Tumour Cells (CTCs) offer real-time insights into tumor heterogeneity and evolution.
  • Current CTC isolation relies on cytokeratin (positive) and CD45 (exclusion) biomarkers, but some white blood cells (WBCs) can be misclassified.

Purpose of the Study:

  • To improve the accuracy of Circulating Tumour Cell (CTC) detection and enumeration.
  • To develop robust exclusion criteria for unequivocally eliminating interfering white blood cell (WBC) populations.
  • To enhance the clinical utility of CTCs in cancer diagnosis and monitoring.

Main Methods:

  • Utilized immunocytochemistry for CTC identification.
  • Employed flow cytometry to confirm antibody specificity.
  • Developed a double exclusion strategy combining CD15 and CD45 antibodies to differentiate WBCs from CTCs.
  • Optimized cytokeratin antibody selection for improved specificity.

Main Results:

  • Identified granulocyte subpopulations expressing low CD45 and non-specific cytokeratin, leading to false positive CTC classification.
  • Demonstrated that CD15 expression specifically identifies these granulocytes as WBCs.
  • Reduced false positive rates from 25% to 0.2% using CD15 and CD45 double exclusion.
  • Achieved complete elimination of false positives with double exclusion and improved cytokeratin antibody selection.

Conclusions:

  • Misclassification of granulocytes significantly impacts CTC evaluation accuracy.
  • High-performing antibodies and dual biomarker exclusion enhance CTC detection sensitivity and specificity.
  • Improved CTC identification facilitates more comprehensive clinical applications.