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As an indicator of clinical prognosis, lymph node metastasis of breast cancer has drawn great attention. Many reports have revealed the characteristics of metastatic breast cancer cells, however, the effect of breast cancer cells on the microenvironment components of lymph nodes and spatial transcriptome atlas remains unclear. In this study, by integrating single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics, we investigate the transcriptional profiling of six surgically excised lymph node samples and the spatial organization of one positive lymph node. We identify the existence of osteoclast-like giant cells (OGC) which have high expressions of CD68 and CD163, the biomarkers of tumor-associated macrophages (TAMs). Through a spatially resolved transcriptomic method, we find that OGCs are scattered among metastatic breast cancer cells. In the lymph node microenvironment with breast cancer cell infiltration, TAMs are enriched in protumoral pathways including NF-κB signaling pathways and NOD-like receptor signaling pathways. Further subclustering demonstrates the potential differentiation trajectory in which macrophages develop from a state of active chemokine production to a state of active lymphocyte activation. This study is the first to integrate scRNA-seq and spatial transcriptomics in the tumor microenvironment of axillary lymph nodes, offering a systematic approach to delve into breast cancer lymph node metastasis.

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. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BC) is one of the most common cancers worldwide and patients with lymph node metastasis always suffer from a worse prognosis. Tumor mutation burden (TMB) has been reported as a potential predictor for tumor behaviors. However, the correlation between TMB and lymph node metastasis of BC remains unclear. This study aimed to explore TMB-related biomarkers to predict the lymph node metastasis in BC patients., Methods: A total of 949 BC patients with RNA-seq data, mutation data and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. We visualized mutation data by "maftools" package. We calculated TMB of each patient and investigated its association with lymph node metastasis. BC patients were divided into lymph node positive and negative groups and we respectively identified TMB-related and lymph node-related differentially expressed genes (DEGs) to figure out intersected genes. Functional enrichment analysis and protein-protein interaction (PPI) network were performed to observe relevant biological functions. We constructed a TMB-related signature for predicting lymph node metastasis through Logistic regression analysis. A validation database (GSE102484) from the Gene Expression Omnibus (GEO) database was downloaded to verify the accuracy., Results: Single nucleotide polymorphism (SNP) occupied the highest proportion in variant types while C>T appeared most frequently in single nucleotide variant (SNV). TMB was regarded as negatively correlated with lymph node metastasis in BC (P=0.003). We identified 125 common DEGs through venn diagram, which were enriched in vesicle localization, calcium signaling pathway and salmonella infection. A TMB-related signature based on six genes (BAHD1, PPM1A, PQLC3, SMPD3, EEF1A1 and S100B) had reliable efficacy for predicting lymph node metastasis in BC and was proven as an independent predictive factor. The accuracy of this signature was further validated by GSE102484 database., Conclusions: Our results indicated that TMB was associated with lymph node metastasis of BC. We built a TMB-related signature consisting of six genes which might function as a novel biomarker for predicting lymph node metastasis in BC., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tcr-20-3471). The authors have no conflicts of interest to declare., (2021 Translational Cancer Research. All rights reserved.)

The potentially different genetics and epigenetics in the primary tumors and metastases affect the efficacy of treatment in breast cancer patients. Nevertheless, the cellular and molecular mechanisms of breast cancer lymph node metastasis still remain elusive. Here, we employed single-cell RNA sequencing to acquire the transcriptomic profiles of individual cells from primary tumors, negative lymph nodes (NLs) and positive lymph nodes (PLs). We also performed a single-cell assay for transposase-accessible chromatin (ATAC) sequencing (scATAC-seq) of the positive and NL samples to get the chromatin accessibility profile. We identified a novel cell subpopulation with an abnormally high expression level of CXCL14 in the PL of breast cancer patients. Cell trajectory analysis also revealed that CXCL14 was increased expressed in the late pseudo-time. Moreover, based on a tissue microarray of 55 patients and the Oncomine database, we validated that CXCL14 expression was significantly higher in breast cancer patients with lymph node metastasis. Furthermore, scATAC-seq identified several transcription factors that may be potential regulation factors for the lymph node metastasis of breast cancer. Thus, our findings will improve our current understanding of the mechanism for lymph node metastasis, and they are potentially valuable in providing novel prognosis markers for the lymphatic metastasis of breast cancer., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)