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Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients

SIMPLE SUMMARY: Ovarian Cancer (OC) is one of the leading causes of death among gynecological tumors and there is still an insufficient understanding of its evolution. Blood, as a minimal invasive tool, allows multiple sampling over the treatment course and genomic single circulating tumor cell (sCT...

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Autores principales: Salmon, Carolin, Levermann, Janina, Neves, Rui P. L., Liffers, Sven-Thorsten, Kuhlmann, Jan Dominik, Buderath, Paul, Kimmig, Rainer, Kasimir-Bauer, Sabine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8345187/
https://www.ncbi.nlm.nih.gov/pubmed/34359649
http://dx.doi.org/10.3390/cancers13153748
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author Salmon, Carolin
Levermann, Janina
Neves, Rui P. L.
Liffers, Sven-Thorsten
Kuhlmann, Jan Dominik
Buderath, Paul
Kimmig, Rainer
Kasimir-Bauer, Sabine
author_facet Salmon, Carolin
Levermann, Janina
Neves, Rui P. L.
Liffers, Sven-Thorsten
Kuhlmann, Jan Dominik
Buderath, Paul
Kimmig, Rainer
Kasimir-Bauer, Sabine
author_sort Salmon, Carolin
collection PubMed
description SIMPLE SUMMARY: Ovarian Cancer (OC) is one of the leading causes of death among gynecological tumors and there is still an insufficient understanding of its evolution. Blood, as a minimal invasive tool, allows multiple sampling over the treatment course and genomic single circulating tumor cell (sCTC) data provide the opportunity to investigate the genetic tumor evolution. CTC detection in OC remains difficult, due to epithelial-mesenchymal transition (EMT). This proof of principle study presents a workflow to generate sCTC genomic data, with the need of further studies to improve the CTC detection rate and enable insights into tumor evolution on a sCTC resolution to identify new treatment targets and/or biomarkers for an early treatment intervention. ABSTRACT: In Ovarian Cancer (OC), the analysis of single circulating tumor cells (sCTCs) might help to investigate genetic tumor evolution during the course of treatment. Since common CTC identification features failed to reliably detect CTCs in OC, we here present a workflow for their detection and genomic analysis. Blood of 13 high-grade serous primary OC patients was analyzed, using negative immunomagnetic enrichment, followed by immunofluorescence staining and imaging for Hoechst, ERCC1, CD45, CD11b and cytokeratin (CK) and sCTC sorting with the DEPArray(TM) NxT. The whole genome of single cells was amplified and profiled for copy number variation (CNV). We detected: Type A-cells, epithelial (Hoechst(pos), ERCC1(pos), CD45(neg), CD11b(pos), CK(pos)); Type B-cells, potentially epithelial (Hoechst(pos), ERCC1(pos), CD45(neg), CD11b(pos), CK(neg)) and Type C-cells, potentially mesenchymal (Hoechst(pos), ERCC1(pos), CD45(neg), CD11b(neg), CK(neg)). In total, we identified five (38.5%) patients harboring sCTCs with an altered CN profile, which were mainly Type A-cells (80%). In addition to inter-and intra-patient genomic heterogeneity, high numbers of Type B- and C-cells were identified in every patient with their aberrant character only confirmed in 6.25% and 4.76% of cases. Further identification markers and studies in the course of treatment are under way to expand sCTC analysis for the identification of tumor evolution in OC.
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spelling pubmed-83451872021-08-07 Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients Salmon, Carolin Levermann, Janina Neves, Rui P. L. Liffers, Sven-Thorsten Kuhlmann, Jan Dominik Buderath, Paul Kimmig, Rainer Kasimir-Bauer, Sabine Cancers (Basel) Article SIMPLE SUMMARY: Ovarian Cancer (OC) is one of the leading causes of death among gynecological tumors and there is still an insufficient understanding of its evolution. Blood, as a minimal invasive tool, allows multiple sampling over the treatment course and genomic single circulating tumor cell (sCTC) data provide the opportunity to investigate the genetic tumor evolution. CTC detection in OC remains difficult, due to epithelial-mesenchymal transition (EMT). This proof of principle study presents a workflow to generate sCTC genomic data, with the need of further studies to improve the CTC detection rate and enable insights into tumor evolution on a sCTC resolution to identify new treatment targets and/or biomarkers for an early treatment intervention. ABSTRACT: In Ovarian Cancer (OC), the analysis of single circulating tumor cells (sCTCs) might help to investigate genetic tumor evolution during the course of treatment. Since common CTC identification features failed to reliably detect CTCs in OC, we here present a workflow for their detection and genomic analysis. Blood of 13 high-grade serous primary OC patients was analyzed, using negative immunomagnetic enrichment, followed by immunofluorescence staining and imaging for Hoechst, ERCC1, CD45, CD11b and cytokeratin (CK) and sCTC sorting with the DEPArray(TM) NxT. The whole genome of single cells was amplified and profiled for copy number variation (CNV). We detected: Type A-cells, epithelial (Hoechst(pos), ERCC1(pos), CD45(neg), CD11b(pos), CK(pos)); Type B-cells, potentially epithelial (Hoechst(pos), ERCC1(pos), CD45(neg), CD11b(pos), CK(neg)) and Type C-cells, potentially mesenchymal (Hoechst(pos), ERCC1(pos), CD45(neg), CD11b(neg), CK(neg)). In total, we identified five (38.5%) patients harboring sCTCs with an altered CN profile, which were mainly Type A-cells (80%). In addition to inter-and intra-patient genomic heterogeneity, high numbers of Type B- and C-cells were identified in every patient with their aberrant character only confirmed in 6.25% and 4.76% of cases. Further identification markers and studies in the course of treatment are under way to expand sCTC analysis for the identification of tumor evolution in OC. MDPI 2021-07-26 /pmc/articles/PMC8345187/ /pubmed/34359649 http://dx.doi.org/10.3390/cancers13153748 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Salmon, Carolin
Levermann, Janina
Neves, Rui P. L.
Liffers, Sven-Thorsten
Kuhlmann, Jan Dominik
Buderath, Paul
Kimmig, Rainer
Kasimir-Bauer, Sabine
Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients
title Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients
title_full Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients
title_fullStr Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients
title_full_unstemmed Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients
title_short Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients
title_sort image-based identification and genomic analysis of single circulating tumor cells in high grade serous ovarian cancer patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8345187/
https://www.ncbi.nlm.nih.gov/pubmed/34359649
http://dx.doi.org/10.3390/cancers13153748
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