Molecular mechanisms underlying breast cancer lymph node metastasis remain unclear. Using single-cell sequencing, we investigated the transcriptome profile of 96,796 single cells from 15 paired samples of primary tumors and axillary lymph nodes. We identified nine cancer cell subclusters including CD44 + / ALDH2 + /ALDH6A1 + breast cancer stem cells (BCSCs), which had a copy-number variants profile similar to that of normal breast tissue. Importantly, BCSCs existed only in primary tumors and evolved into metastatic clusters infiltrating into lymph nodes. Furthermore, transcriptome data suggested that NECTIN2-TIGIT-mediated interactions between metastatic breast cancer cells and tumor microenvironment (TME) cells, which promoted immune escape and lymph node metastasis. This study is the first to delineate the transcriptome profile of breast cancer lymph node metastasis using single-cell RNA sequencing. Our findings offer novel insights into the mechanisms underlying breast cancer metastasis and have implications in developing novel therapies to inhibit the initiation of breast cancer metastasis.

/pdf/single-cell-rna-sequencing-reveals-cell-heterogeneity-and-4w7hoh6o3g.pdf

Single-cell RNA sequencing reveals cell heterogeneity and transcriptome profile of breast cancer lymph node metastasis.

The prognostic management of bladder cancer (BLCA) remains a great challenge for clinicians. Recently, bulk RNA-seq sequencing data have been used as a prognostic marker for many cancers but do not accurately detect core cellular and molecular functions in tumor cells. In the current study, bulk RNA-seq and single-cell RNA sequencing (scRNA-seq) data were combined to construct a prognostic model of BLCA.BLCA scRNA-seq data were downloaded from Gene Expression Omnibus (GEO) database. Bulk RNA-seq data were obtained from the UCSC Xena. The R package "Seurat" was used for scRNA-seq data processing, and the uniform manifold approximation and projection (UMAP) were utilized for downscaling and cluster identification. The FindAllMarkers function was used to identify marker genes for each cluster. The limma package was used to obtain differentially expressed genes (DEGs) affecting overall survival (OS) in BLCA patients. Weighted gene correlation network analysis (WGCNA) was used to identify BLCA key modules. The intersection of marker genes of core cells and genes of BLCA key modules and DEGs was used to construct a prognostic model by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) analyses. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and chemotherapeutic drug sensitivity between the high and low-risk groups were also investigated.scRNA-seq data were analyzed to identify 19 cell subpopulations and 7 core cell types. The ssGSEA showed that all 7 core cell types were significantly downregulated in tumor samples of BLCA. We identified 474 marker genes from the scRNA-seq dataset, 1556 DEGs from the Bulk RNA-seq dataset, and 2334 genes associated with a key module identified by WGCNA. After performing intersection, univariate Cox, and LASSO analysis, we obtained a prognostic model based on the expression levels of 3 signature genes, namely MAP1B, PCOLCE2, and ELN. The feasibility of the model was validated by an internal training set and two external validation sets. Moreover, patients with high-risk scores are predisposed to experience poor OS, a larger prevalence of stage III-IV, a greater TMB, a higher infiltration of immune cells, and a lesser likelihood of responding favorably to immunotherapy.By integrating scRNA-seq and bulk RNA-seq data, we constructed a novel prognostic model to predict the survival of BLCA patients. The risk score is a promising independent prognostic factor that is closely correlated with the immune microenvironment and clinicopathological characteristics. 

/pdf/comprehensive-analysis-of-scrna-seq-and-bulk-rna-seq-reveals-1hlrk6tw.pdf

Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals dynamic changes in the tumor immune microenvironment of bladder cancer and establishes a prognostic model

Bulk sequencing methodologies have allowed us to make great progress in cancer research. Unfortunately, these techniques lack the resolution to fully unravel the epigenetic mechanisms that govern tumor heterogeneity. Consequently, many novel single cell-sequencing methodologies have been developed over the past decade, allowing us to explore the epigenetic components that regulate different aspects of cancer heterogeneity, namely: clonal heterogeneity, tumor microenvironment (TME), spatial organization, intratumoral differentiation programs, metastasis, and resistance mechanisms. In this review, we explore the different sequencing techniques that enable researchers to study different aspects of epigenetics (DNA methylation, chromatin accessibility, histone modifications, DNA-protein interactions, and chromatin 3D architecture) at the single cell level, their potential applications in cancer, and their current technical limitations. 

Single cell cancer epigenetics.

Abstract Single-cell sequencing (SCS) is an emerging high-throughput technology that can be used to study the genomics, transcriptomics, and epigenetics at a single cell level. SCS is widely used in the diagnosis and treatment of various diseases, including cancer. Over the years, SCS has gradually become an effective clinical tool for the exploration of tumor metastasis mechanisms and the development of treatment strategies. Currently, SCS can be used not only to analyze metastasis-related malignant biological characteristics, such as tumor heterogeneity, drug resistance, and microenvironment, but also to construct metastasis-related cell maps for predicting and monitoring the dynamics of metastasis. SCS is also used to identify therapeutic targets related to metastasis as it provides insights into the distribution of tumor cell subsets and gene expression differences between primary and metastatic tumors. Additionally, SCS techniques in combination with artificial intelligence (AI) are used in liquid biopsy to identify circulating tumor cells (CTCs), thereby providing a novel strategy for treating tumor metastasis. In this review, we summarize the potential applications of SCS in the field of tumor metastasis and discuss the prospects and limitations of SCS to provide a theoretical basis for finding therapeutic targets and mechanisms of metastasis. 

https://jhoonline.biomedcentral.com/track/pdf/10.1186/s13045-022-01280-w

Single-cell sequencing: a promising approach for uncovering the mechanisms of tumor metastasis

Breast cancer is one of the most important causes of premature mortality among women and it is one of the most frequently diagnosed tumours worldwide. For this reason, routine screening for prevention and early diagnosis is important for the quality of life of patients. Breast cancer cells can enter blood and lymphatic capillaries, then metastasizing to the regional lymph nodes in the axilla and to both visceral and non-visceral sites. Rather than at the primary site, they seem to enter the systemic circulation mainly through the sentinel lymph node and the biopsy of this indicator can influence the axillary dissection during the surgical approach to the pathology. Furthermore, secondary lymphoedema is another important issue for women following breast cancer surgical treatment or radiotherapy. Considering these fundamental aspects, the present article aims to describe new methodological approaches to assess the anatomy of the lymphatic network in the axillary region, as well as the molecular and physiological control of lymphatic vessel function, in order to understand how the lymphatic system contributes to breast cancer disease. Due to their clinical implications, the understanding of the molecular mechanisms governing lymph node metastasis in breast cancer are also examined. Beyond the investigation of breast lymphatic networks and lymphatic molecular mechanisms, the discovery of new effective anti-lymphangiogenic drugs for future clinical settings appears essential to support any future development in the treatment of breast cancer.

https://biblio.ugent.be/publication/8727696/file/8727697.pdf

The Lymphatic System in Breast Cancer: Anatomical and Molecular Approaches

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

Integrative analyses of scRNA-seq and scATAC-seq reveal CXCL14 as a key regulator of lymph node metastasis in breast cancer.

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Integrative analyses of scRNA-seq and scATAC-seq reveal CXCL14 as a key regulator of lymph node metastasis in breast cancer.