Mutational analysis of circulating tumor cells in breast cancer patients by targeted clonal sequencing.

10516 Background: The molecular signature of circulating tumor cells (CTCs) may serve as a surrogate marker for accurate description of the metastatic tumor of interest, especially in the setting of treatment response and selection. We present a method for mutational analysis of CTCs in metastatic breast cancer (MBC) patients by using an emulsion-formulated, semiconductor-based, targeted clonal sequencing platform. Methods: CTCs in MBC patients were enriched by a microfluidic OncoCEE device using antibodies against both epithelial and mesenchymal markers. Genomic DNA was extracted from enriched CTC samples. Emulsion-based multiplex-PCR targeted for various cancer genes was performed, after which semiconductor-based deep sequencing was completed. The read error rates were analyzed based on quality score and context of sequence including homopolymers. Statistical significance for each mutational analysis was assessed using a method based on beta-binomial distribution. Results: Of the 17 patients samples obtained, we were able to enrich CTC samples in 9 of them (CTC range 1-1063, median=12). Multiplex targeted sequencing was performed on DNA from the enriched CTC patient samples (purity range 0.3-6%). Greater than 3000-fold coverage was accomplished. Missense mutations at E545D on PIK3CA (p= 2.0e-07), F354L on STK11 (p=2.0e-04), and Q61R on NRAS (p=2.0e-07) were detected. Novel mutations of L540F and Q1033K within the hot spot regions of PIK3CA were observed (p=1.3e-04). Genomic DNA from WBCs from a healthy female was analyzed concurrently as a negative control, in which none of the mutations were observed. Conclusions: Mutational analysis of CTCs in MBC patients can be accomplished by deep sequencing. We developed a de novo protocol for clonal mutation analysis on CTCs in MBC and detected various significant and novel mutations. We anticipate reporting sequencing results on CTCs and matched WBCs, as negative controls, from 40 MBC patients. This will provide the foundation for the future studies in which we will compare the mutational profile between CTCs and primary/metastatic tumors. We intend to validate clonal mutational analysis of CTCs as a predictive blood-based biomarker in subsequent trials.

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The Mechanical Fingerprint of Circulating Tumor Cells (CTCs) in Breast Cancer Patients

Cancers ◽

10.3390/cancers13051119 ◽

2021 ◽

Vol 13 (5) ◽

pp. 1119

Author(s):

Ivonne Nel ◽

Erik W. Morawetz ◽

Dimitrij Tschodu ◽

Josef A. Käs ◽

Bahriye Aktas

Keyword(s):

Breast Cancer ◽

Cancer Cells ◽

Cancer Patients ◽

Tumor Cells ◽

Circulating Tumor Cells ◽

Hematopoietic Cells ◽

Surrogate Marker ◽

Clinical Samples ◽

Breast Cancer Patients ◽

Shape Restoration

Circulating tumor cells (CTCs) are a potential predictive surrogate marker for disease monitoring. Due to the sparse knowledge about their phenotype and its changes during cancer progression and treatment response, CTC isolation remains challenging. Here we focused on the mechanical characterization of circulating non-hematopoietic cells from breast cancer patients to evaluate its utility for CTC detection. For proof of premise, we used healthy peripheral blood mononuclear cells (PBMCs), human MDA-MB 231 breast cancer cells and human HL-60 leukemia cells to create a CTC model system. For translational experiments CD45 negative cells—possible CTCs—were isolated from blood samples of patients with mamma carcinoma. Cells were mechanically characterized in the optical stretcher (OS). Active and passive cell mechanical data were related with physiological descriptors by a random forest (RF) classifier to identify cell type specific properties. Cancer cells were well distinguishable from PBMC in cell line tests. Analysis of clinical samples revealed that in PBMC the elliptic deformation was significantly increased compared to non-hematopoietic cells. Interestingly, non-hematopoietic cells showed significantly higher shape restoration. Based on Kelvin–Voigt modeling, the RF algorithm revealed that elliptic deformation and shape restoration were crucial parameters and that the OS discriminated non-hematopoietic cells from PBMC with an accuracy of 0.69, a sensitivity of 0.74, and specificity of 0.63. The CD45 negative cell population in the blood of breast cancer patients is mechanically distinguishable from healthy PBMC. Together with cell morphology, the mechanical fingerprint might be an appropriate tool for marker-free CTC detection.

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