Circulating Tumor Cells and Breast Cancer Metastasis: From Enumeration to Somatic Mutational Profile

Abstract

Aims: This study investigates the association between circulating tumor cells (CTCs) and breast cancer metastasis. Methods: A retrospective study was conducted using patients with histologically confirmed breast cancer recruited from the First Affiliated Hospital of Nanjing Medical University during the period of August 2017–October 2020. We used adjusted logistic regression, the random forest algorithm, and sensitivity analysis to study the association between CTC enumeration and tumor metastasis. Further, we performed next-generation sequencing (NGS) on the CTCs obtained from two patients with breast cancer brain metastasis. Results: A total of 41 out of 116 enrolled patients were identified with tumor metastasis. CTC enumeration was significantly higher in patients with liver metastasis than in those without liver metastasis. Patients with CTCs ≥ 5 exhibited a higher risk of tumor metastasis than those with CTCs < 5 in the adjusted model (odds ratios (OR) = 6.25, 95% confidence interval (CI) = 2.63–15.58). The random forest model identified CTC enumeration as a significant metastasis-related variable with the highest mean decrease accuracy and mean decrease Gini score. No significant association was found between CTCs and visceral metastasis with an OR of 1.29 (95% CI = 0.98–2.05, p = 0.232). Upon further investigating organ-specific metastasis, we found that patients with high CTC levels were more likely to develop liver metastasis (OR = 4.87, 95% CI = 1.34–20.17, p = 0.021). The NGS study of CTCs identified a total of 120 indel mutations (e.g., CNGB1, NTSR1, ZG16). The enriched biological processes were mechanoreceptor differentiation and macrophage activation involved in the immune response. The enriched KEGG pathways included focal adhesion, the PI3K-Akt signaling pathway, and microRNAs involved in cancer. Conclusions: Our study revealed that CTCs ≥ 5 are a risk factor for tumor metastasis in breast cancer patients. In addition, we reported that CTCs ≥ 5 might be associated with a higher risk of liver metastasis in patients with metastatic breast cancer. We have provided the mutational profiles of CTCs based on next-generation sequencing.

Review of the relationship between tumor receptor subtypes and preference for visceral and/or serosal metastasis in breast cancer patients

“…[7,8] Therefore, it is important to identify patients at high risk of tumor metastasis in advance, if possible, to ensure timely intervention. [9][10][11][12][13][14] 2. Material and Methods…”

Screening of novel biomarkers for breast cancer based on WGCNA and multiple machine learning algorithms

“…With the remarkable development of sequencing technologies, bioinformatics has gained significant applications in several fields, especially in medicine. Bioinformatics is most commonly used in medical research to identify prospective biomarkers in tumor and nontumor diseases to support doctors to predict prognosis and response to therapy ( 2 , 3 ). For example, Weighted Gene Coexpression Network Analysis (WGCNA) combined with Support Vector Machine-Recursive Elimination Feature (SVM-REF), Least Absolute Shrinkage and Selection Operator (LASSO) regression models, and Gaussian mixture model (GMM) algorithms identified early diagnostic genes for tendinopathy ( 4 ).…”