Accurate Screening for Early-Stage Breast Cancer by Detection and Profiling of Circulating Tumor Cells.

breast cancer circulating tumor cells immunocytochemistry screening

Journal

Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829

Informations de publication

Date de publication:
09 Jul 2022
Historique:
received: 24 05 2022
revised: 04 07 2022
accepted: 07 07 2022
entrez: 27 7 2022
pubmed: 28 7 2022
medline: 28 7 2022
Statut: epublish

Résumé

The early detection of breast cancer (BrC) is associated with improved survival. We describe a blood-based breast cancer detection test based on functional enrichment of breast-adenocarcinoma-associated circulating tumor cells (BrAD-CTCs) and their identification via multiplexed fluorescence immunocytochemistry (ICC) profiling for GCDFP15, GATA3, EpCAM, PanCK, and CD45 status. The ability of the test to differentiate BrC cases ( The test accurately detects BrAD-CTCs in breast cancers, irrespective of age, ethnicity, disease stage, grade, or hormone receptor status. Analytical validation established the high accuracy and reliability of the test under intended use conditions. The test detects and differentiates BrC cases from healthy women with 100% specificity and 92.07% overall sensitivity in a case-control study. In a prospective clinical study, the test shows 93.1% specificity and 94.64% overall sensitivity in differentiating breast cancer cases ( The findings reported in this manuscript support the clinical potential of this test for blood-based BrC detection.

Sections du résumé

BACKGROUND BACKGROUND
The early detection of breast cancer (BrC) is associated with improved survival. We describe a blood-based breast cancer detection test based on functional enrichment of breast-adenocarcinoma-associated circulating tumor cells (BrAD-CTCs) and their identification via multiplexed fluorescence immunocytochemistry (ICC) profiling for GCDFP15, GATA3, EpCAM, PanCK, and CD45 status.
METHODS METHODS
The ability of the test to differentiate BrC cases (
RESULTS RESULTS
The test accurately detects BrAD-CTCs in breast cancers, irrespective of age, ethnicity, disease stage, grade, or hormone receptor status. Analytical validation established the high accuracy and reliability of the test under intended use conditions. The test detects and differentiates BrC cases from healthy women with 100% specificity and 92.07% overall sensitivity in a case-control study. In a prospective clinical study, the test shows 93.1% specificity and 94.64% overall sensitivity in differentiating breast cancer cases (
CONCLUSION CONCLUSIONS
The findings reported in this manuscript support the clinical potential of this test for blood-based BrC detection.

Identifiants

pubmed: 35884402
pii: cancers14143341
doi: 10.3390/cancers14143341
pmc: PMC9316476
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Timothy Crook (T)

Department of Oncology, The London Clinic, London W1G 6BW, UK.

Robert Leonard (R)

Department of Oncology, Cromwell Hospital, London SW5 0TU, UK.

Kefah Mokbel (K)

The London Breast Institute, Princess Grace Hospital, London W1U 5NY, UK.

Alastair Thompson (A)

Division of Surgical Oncology, Baylor College of Medicine, Houston, TX 77030, USA.

Michael Michell (M)

National Breast Screening Training Centre, King's College Hospital, London SE5 9RS, UK.

Raymond Page (R)

Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA.

Ashok Vaid (A)

Department of Medical and Haemato Oncology, Medanta-The Medicity, Gurugram 122001, India.

Ravi Mehrotra (R)

Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA.

Anantbhushan Ranade (A)

Department of Medical Oncology, Avinash Cancer Clinic, Pune 411030, India.

Sewanti Limaye (S)

Department of Medical and Precision Oncology, Sir HN Reliance Foundation Hospital and Research Centre, Mumbai 400004, India.

Darshana Patil (D)

Department of Research and Innovations, Datar Cancer Genetics, Nasik 422010, India.

Dadasaheb Akolkar (D)

Department of Research and Innovations, Datar Cancer Genetics, Nasik 422010, India.

Vineet Datta (V)

Department of Research and Innovations, Datar Cancer Genetics, Nasik 422010, India.

Pradip Fulmali (P)

Department of Research and Innovations, Datar Cancer Genetics, Nasik 422010, India.

Sachin Apurwa (S)

Department of Research and Innovations, Datar Cancer Genetics, Nasik 422010, India.

Stefan Schuster (S)

Department of Research and Innovations, Datar Cancer Genetics Europe GmbH, 95488 Eckersdorf, Germany.

Ajay Srinivasan (A)

Department of Research and Innovations, Datar Cancer Genetics, Nasik 422010, India.

Rajan Datar (R)

Department of Research and Innovations, Datar Cancer Genetics, Nasik 422010, India.

Classifications MeSH