Dataset Information

Single-Cells Isolation and Molecular Analysis: Focus on HER2-Low CTCs in Metastatic Breast Cancer.

ABSTRACT: Although the detection of CTCs expressing HER2 at low intensity (HER2-low CTCs) has been shown to have a negative prognostic value in metastatic breast cancer (MBC) patients, the biological intrinsic nature of HER2-low CTCs remains unexplored. Considering the technical challenges behind the selective collection of immunophenotype-specific CTCs, we developed a pipeline to individually capture HER2-low CTCs. Four different breast cancer cell lines (MDA-MB-231, T47D, MDA-MB-453, and SKBR3), that are known to express HER2 at different immunohistochemistry levels (respectively classified as 0, 1+, 2+, and 3+), were spiked in healthy donor blood tubes (7.5 mL) and processed with the CellSearch^® (Menarini Silicon Biosystems, Bologna, Italy) for enrichment and the DEPArray NxT^™ for single cell selection. The HER2 signal-intensities of each cell line was compared using the nonparametric Mann-Whitney U test. The optimal cut-offs to distinguish HER2 1+ from 0 and 2+ cells were calculated performing the Receiver operating characteristic (ROC) curve. Median HER2 signal-intensities detected with the DEPArray NxT^™ were: 2.59 (0), 3.58 (1+), 5.23 (2+) and 38.37 (3+). DEPArray NxT efficiently differentiated each single cell line (p < 0.001). The area under the ROC curve was 0.69 and 0.70 (respectively 0 vs. 1+ and 1+ vs. 2+) and the optimal calculated cut-offs were 2.85 (lower) and 4.64 (upper). HER2-low CTCs can be detected and separately collected using predetermined intensity cut-offs. This study will allow standardized single-cell or pooled collection of HER2-low CTCs for downstream molecular analyses.

SUBMITTER: D'Amico P

PROVIDER: S-EPMC8750036 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundCirculating tumor cells (CTCs) existing in peripheral blood can be used to predict the prognosis and survival of cancer patients. The study was designed to detect circulating tumor cells and circulating tumor single cell genes by applying microfluidic chip technology. It was used to explore the clinical application value in breast cancer.MethodsWe have developed a size-based CTCs sorting microfluidic chip, which contains a hexagonal array and a micro-pipe channel array to isolate and confirm both single CTCs and CTCs clusters. The sorting performance of the as-fabricated chip was tested by analyzing the clinical samples collected from 129 breast cancer patients and 50 healthy persons.ResultsIn this study, the chip can detect different immunophenotypes of CTCs in breast cancer patients. It was found that the new microfluidic device had high sensitivity (73.6%) and specificity (82.0%) in detecting CTCs. By detecting the blood samples of 129 breast cancer patients and 50 healthy blood donors, it was found that the number of CTCs was not associated with clinical factors such as age, gender, pathological type, and tumor size of breast cancer patients (P > 0.05), but was associated with TNM staging of breast cancer, with or without metastasis (P < 0.005). There was a statistically significant difference in the number of CTCs between luminal A (ER+/PR+/HER2-) and HER-2+ (ER-/PR-/HER2+) (P < 0.05). The best cut-off level distinguished by CTC between the breast cancer patients and the healthy persons was 3.5 cells/mL, with 0.845 for AUC-ROC, 0.790-0.901 for 95% CI, 73.6% for sensitivity, and 82% for specificity (P = 0.000). The combination of CTC, CEA, CA125 and CA153 can provide more effective breast cancer screening.ConclusionsThe CTCs analysis method presented here doesn't rely on the specific antibody, such as anti-EpCAM, which would avoid the missed inspection caused by antibody-relied methods and offer more comprehensive biological information for clinical breast cancer diagnosis and treatment.

Dataset Information

Single-Cells Isolation and Molecular Analysis: Focus on HER2-Low CTCs in Metastatic Breast Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets