Single-cell RNA-sequencing of migratory breast cancer cells: discovering genes associated with cancer metastasis

ScRNA-seq revealed the tumor microenvironment heterogeneity related to the occurrence and metastasis in upper urinary tract urothelial carcinoma

Metastasis is the greatest clinical challenge for UTUCs, which may have distinct molecular and cellular characteristics from earlier cancers. Herein, we provide single-cell transcriptome profiles of UTUC para cancer normal tissue, primary tumor lesions, and lymphatic metastases to explore possible mechanisms associated with UTUC occurrence and metastasis. From 28,315 cells obtained from normal and tumor tissues of 3 high-grade UTUC patients, we revealed the origin of UTUC tumor cells and the homology between metastatic and primary tumor cells. Unlike the immunomicroenvironment suppression of other tumors, we found no immunosuppression in the tumor microenvironment of UTUC. Moreover, it is imperative to note that stromal cells are pivotal in the advancement of UTUC. This comprehensive single-cell exploration enhances our comprehension of the molecular and cellular dynamics of metastatic UTUCs and discloses promising diagnostic and therapeutic targets in cancer-microenvironment interactions.

Basal-epithelial subpopulations underlie and predict chemotherapy resistance in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, characterized by extensive intratumoral heterogeneity, high metastasis, and chemoresistance, leading to poor clinical outcomes. Despite progress, the mechanistic basis of these aggressive behaviors remains poorly understood. Using single-cell and spatial transcriptome analysis, here we discovered basal epithelial subpopulations located within the stroma that exhibit chemoresistance characteristics. The subpopulations are defined by distinct signature genes that show a frequent gain in copy number and exhibit an activated epithelial-to-mesenchymal transition program. A subset of these genes can accurately predict chemotherapy response and are associated with poor prognosis. Interestingly, among these genes, elevated ITGB1 participates in enhancing intercellular signaling while ACTN1 confers a survival advantage to foster chemoresistance. Furthermore, by subjecting the transcriptional signatures to drug repurposing analysis, we find that chemoresistant tumors may benefit from distinct inhibitors in treatment-naive versus post-NAC patients. These findings shed light on the mechanistic basis of chemoresistance while providing the best-in-class biomarker to predict chemotherapy response and alternate therapeutic avenues for improved management of TNBC patients resistant to chemotherapy.

Breast Cancer: Mitochondria-Centered Metabolic Alterations in Tumor and Associated Adipose Tissue

The close cooperation between breast cancer and cancer-associated adipose tissue (CAAT) shapes the malignant phenotype, but the role of mitochondrial metabolic reprogramming and obesity in breast cancer remains undecided, especially in premenopausal women. Here, we examined mitochondrial metabolic dynamics in paired biopsies of malignant versus benign breast tumor tissue and CAAT in normal-weight and overweight/obese premenopausal women. Lower protein level of pyruvate dehydrogenase and citrate synthase in malignant tumor tissue indicated decreased carbon flux from glucose into the Krebs cycle, whereas the trend was just the opposite in malignant CAAT. Simultaneously, stimulated lipolysis in CAAT of obese women was followed by upregulated β-oxidation, as well as fatty acid synthesis enzymes in both tumor tissue and CAAT of women with malignant tumors, corroborating their physical association. Further, protein level of electron transport chain complexes was generally increased in tumor tissue and CAAT from women with malignant tumors, respective to obesity. Preserved mitochondrial structure in malignant tumor tissue was also observed. However, mitochondrial DNA copy number and protein levels of PGC-1α were dependent on both malignancy and obesity in tumor tissue and CAAT. In conclusion, metabolic cooperation between breast cancer and CAAT in premenopausal women involves obesity-related, synchronized changes in mitochondrial metabolism.

Breast Cancer Circulating Tumor Cells: Current Clinical Applications and Future Prospects

BACKGROUND

Identification and characterization of circulating tumor markers, designated as "liquid biopsies," have greatly impacted the care of cancer patients. Although more recently referring to circulating tumor DNA (ctDNA), the term liquid biopsy initially was coined to refer to any blood-borne biomarker related to malignancy, including circulating tumor cells (CTCs) in blood. In this manuscript, we review the specific state of the art of CTCs in breast cancer.

CONTENT

Liquid biopsies might play a clinical role across the entire spectrum of breast cancer, from risk assessment, prevention, screening, and treatment. CTC counts have been shown to carry clear, independent prognostic information in the latter situation. However, the clinical utility of CTCs in breast cancer remains to be determined. Nonetheless, in addition to CTC enumeration, analyses of CTCs provide tumor molecular information representing the entire, often-heterogeneous disease, relatively noninvasively and longitudinally. Technological advances have allowed the interrogation of CTC-derived information, providing renewed hope for a clinical role in disease monitoring and precision oncology.

SUMMARY

This narrative review examines CTCs, their clinical validity, and current prospects of clinical utility in breast cancer with the goal of improving patient outcomes.

Systems immunology spanning tumors, lymph nodes, and periphery

The immune system defines a complex network of tissues and cell types that orchestrate responses across the body in a dynamic manner. The local and systemic interactions between immune and cancer cells contribute to disease progression. Lymphocytes are activated in lymph nodes, traffic through the periphery, and impact cancer progression through their interactions with tumor cells. As a result, therapeutic response and resistance are mediated across tissues, and a comprehensive understanding of lymphocyte dynamics requires a systems-level approach. In this review, we highlight experimental and computational methods that can leverage the study of leukocyte trafficking through an immunomics lens and reveal how adaptive immunity shapes cancer.

Microfluidic single-cell migration chip reveals insights into the impact of extracellular matrices on cell movement

Cell migration is a complex process that plays a crucial role in normal physiology and pathologies such as cancer, autoimmune diseases, and mental disorders. Conventional cell migration assays face limitations in tracking a large number of individual migrating cells. To address this challenge, we have developed a high-throughput microfluidic cell migration chip, which seamlessly integrates robotic liquid handling and computer vision to swiftly monitor the movement of 3200 individual cells, providing unparalleled single-cell resolution for discerning distinct behaviors of the fast-moving cell population. This study focuses on the ECM's role in regulating cellular migration, utilizing this cutting-edge microfluidic technology to investigate the impact of ten different ECMs on triple-negative breast cancer cell lines. We found that collagen IV, collagen III, and collagen I coatings were the top enhancers of cell movement. Combining these ECMs increased cell motility, but the effect was sub-additive. Furthermore, we examined 87 compounds and found that while some compounds inhibited migration on all substrates, significantly distinct effects on differently coated substrates were observed, underscoring the importance of considering ECM coating. We also utilized cells expressing a fluorescent actin reporter and observed distinct actin structures in ECM-interacting cells. ScRNA-Seq analysis revealed that ECM coatings induced EMT and enhanced cell migration. Finally, we identified genes that were particularly up-regulated by collagen IV and the selective inhibitors successfully blocked cell migration on collagen IV. Overall, the study provides insights into the impact of various ECMs on cell migration and dynamics of cell movement with implications for developing therapeutic strategies to combat diseases related to cell motility.

Oncostatin-M and OSM-Receptor Feed-Forward Activation of MAPK Induces Separable Stem-like and Mesenchymal Programs

Patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) frequently present with advanced metastatic disease and exhibit a poor response to therapy, resulting in poor outcomes. The tumor microenvironment cytokine Oncostatin-M (OSM) initiates PDAC plasticity, inducing the reprogramming to a stem-like/mesenchymal state, which enhances metastasis and therapy resistance. Using a panel of PDAC cells driven through epithelial-mesenchymal transition (EMT) by OSM or the transcription factors ZEB1 or SNAI1, we find that OSM uniquely induces tumor initiation and gemcitabine resistance independently of its ability to induce a CD44HI/mesenchymal phenotype. In contrast, while ZEB1 and SNAI1 induce a CD44HI/mesenchymal phenotype and migration comparable with OSM, they are unable to promote tumor initiation or robust gemcitabine resistance. Transcriptomic analysis identified that OSM-mediated stemness requires MAPK activation and sustained, feed-forward transcription of OSMR. MEK and ERK inhibitors prevented OSM-driven transcription of select target genes and stem-like/mesenchymal reprogramming, resulting in reduced tumor growth and resensitization to gemcitabine. We propose that the unique properties of OSMR, which hyperactivates MAPK signaling when compared with other IL6 family receptors, make it an attractive therapeutic target, and that disrupting the OSM-OSMR-MAPK feed-forward loop may be a novel way to therapeutically target the stem-like behaviors common to aggressive PDAC.

IMPLICATIONS

Small-molecule MAPK inhibitors may effectively target the OSM/OSMR-axis that leads to EMT and tumor initiating properties that promote aggressive PDAC.

Targeted Single-cell Isolation of Spontaneously Escaping Live Melanoma Cells for Comparative Transcriptomics

Solid cancer cells escape the primary tumor mass by transitioning from an epithelial-like state to an invasive migratory state. As they escape, metastatic cancer cells employ interchangeable modes of invasion, transitioning between fibroblast-like mesenchymal movement to amoeboid migration, where cells display a rounded morphology and navigate the extracellular matrix in a protease-independent manner. However, the gene transcripts that orchestrate the switch between epithelial, mesenchymal, and amoeboid states remain incompletely mapped, mainly due to a lack of methodologies that allow the direct comparison of the transcriptomes of spontaneously invasive cancer cells in distinct migratory states. Here, we report a novel single-cell isolation technique that provides detailed three-dimensional data on melanoma growth and invasion, and enables the isolation of live, spontaneously invasive cancer cells with distinct morphologies and invasion parameters. Via the expression of a photoconvertible fluorescent protein, compact epithelial-like cells at the periphery of a melanoma mass, elongated cells in the process of leaving the mass, and rounded amoeboid cells invading away from the mass were tagged, isolated, and subjected to single-cell RNA sequencing. A total of 462 differentially expressed genes were identified, from which two candidate proteins were selected for further pharmacologic perturbation, yielding striking effects on tumor escape and invasion, in line with the predictions from the transcriptomics data. This work describes a novel, adaptable, and readily implementable method for the analysis of the earliest phases of tumor escape and metastasis, and its application to the identification of genes underpinning the invasiveness of malignant melanoma.

Significance

This work describes a readily implementable method that allows for the isolation of individual live tumor cells of interest for downstream analyses, and provides the single-cell transcriptomes of melanoma cells at distinct invasive states, both of which open avenues for in-depth investigations into the transcriptional regulation of the earliest phases of metastasis.

Single-cell transcriptome sequencing reveals heterogeneity of gastric cancer: progress and prospects

Gastric cancer is one of the most serious malignant tumor and threatens the health of people worldwide. Its heterogeneity leaves many clinical problems unsolved. To treat it effectively, we need to explore its heterogeneity. Single-cell transcriptome sequencing, or single-cell RNA sequencing (scRNA-seq), reveals the complex biological composition and molecular characteristics of gastric cancer at the level of individual cells, which provides a new perspective for understanding the heterogeneity of gastric cancer. In this review, we first introduce the current procedure of scRNA-seq, and discuss the advantages and limitations of scRNA-seq. We then elaborate on the research carried out with scRNA-seq in gastric cancer in recent years, and describe how it reveals cell heterogeneity, the tumor microenvironment, oncogenesis and metastasis, as well as drug response in to gastric cancer, to facilitate early diagnosis, individualized therapy, and prognosis evaluation.

Aldose reductase inhibition decelerates optic nerve degeneration by alleviating retinal microglia activation

As part of the central nervous system (CNS), retinal ganglion cells (RGCs) and their axons are the only neurons in the retina that transmit visual signals from the eye to the brain via the optic nerve (ON). Unfortunately, they do not regenerate upon injury in mammals. In ON trauma, retinal microglia (RMG) become activated, inducing inflammatory responses and resulting in axon degeneration and RGC loss. Since aldose reductase (AR) is an inflammatory response mediator highly expressed in RMG, we investigated if pharmacological inhibition of AR can attenuate ocular inflammation and thereby promote RGC survival and axon regeneration after ON crush (ONC). In vitro, we discovered that Sorbinil, an AR inhibitor, attenuates BV2 microglia activation and migration in the lipopolysaccharide (LPS) and monocyte chemoattractant protein-1 (MCP-1) treatments. In vivo, Sorbinil suppressed ONC-induced Iba1 + microglia/macrophage infiltration in the retina and ON and promoted RGC survival. Moreover, Sorbinil restored RGC function and delayed axon degeneration one week after ONC. RNA sequencing data revealed that Sorbinil protects the retina from ONC-induced degeneration by suppressing inflammatory signaling. In summary, we report the first study demonstrating that AR inhibition transiently protects RGC and axon from degeneration, providing a potential therapeutic strategy for optic neuropathies.

Crosstalk between SOX Genes and Long Non-Coding RNAs in Glioblastoma

Glioblastoma (GBM) continues to be the most devastating primary brain malignancy. Despite significant advancements in understanding basic GBM biology and enormous efforts in developing new therapeutic approaches, the prognosis for most GBM patients remains poor with a median survival time of 15 months. Recently, the interplay between the SOX (SRY-related HMG-box) genes and lncRNAs (long non-coding RNAs) has become the focus of GBM research. Both classes of molecules have an aberrant expression in GBM and play essential roles in tumor initiation, progression, therapy resistance, and recurrence. In GBM, SOX and lncRNAs crosstalk through numerous functional axes, some of which are part of the complex transcriptional and epigenetic regulatory mechanisms. This review provides a systematic summary of current literature data on the complex interplay between SOX genes and lncRNAs and represents an effort to underscore the effects of SOX/lncRNA crosstalk on the malignant properties of GBM cells. Furthermore, we highlight the significance of this crosstalk in searching for new biomarkers and therapeutic approaches in GBM treatment.

A machine learning based approach for quantitative evaluation of cell migration in Transwell assays based on deformation characteristics

Many pathological and physiological processes, including embryonic development, immune response and cancer metastasis, involve studies on cell migration, and especially detection methods, for which it is difficult to satisfy the requirements for rapid and quantitative evaluation and analysis. In view of the shortcomings in simultaneously quantifying the number of migrated cells and non-migrated cells using Transwell assays, we propose a novelty approach for the evaluation of cell migration by distinguishing whether the cells have migrated based on the regularity of the cell morphology changes. Traditionally, the status of living cells and dead cells are detected and analyzed by machine learning using some common morphological characteristics, e.g., area and perimeter of the cells. However, the accuracy of detecting whether cells have migrated or not using these common characteristics is not high, and the characteristics are not appropriate for our studies. Therefore, from the point of view of mechanism analysis for the migration behavior, we examined the regularity of different morphology changes of migrated cells and non-migrated cells, and thus discovered the distinguishable morphological characteristics. Then, two deformation characteristics, deformation index and taper index are proposed. Then, a machine learning based algorithm that can identify migrated cells according to the proposed deformation characteristics was devised. In addition, images of migrated cells and non-migrated cells were obtained from the Transwell assays. This algorithm was trained, and was able to successfully identify migrated cells with an accuracy of 84% using the proposed morphological characteristics. This method greatly improves the identification accuracy when compared with the identification of traditional characteristics of which the accuracy was about 54.7%. This machine learning based method might be employed as a potential tool for cell counting and evaluation of cell migration with the aim of reducing time and improving automation compared with the traditional method. This method is effective, rapid, and incorporate advances in artificial intelligence which could be used for adapting the current evaluation methods.

High-Throughput Cellular Heterogeneity Analysis in Cell Migration at the Single-Cell Level

Cancer cell migration represents an essential step toward metastasis and cancer deaths. However, conventional drug discovery focuses on cytotoxic and growth-inhibiting compounds rather than inhibitors of migration. Drug screening assays generally measure the average response of many cells, masking distinct cell populations that drive metastasis and resist treatments. Here, this work presents a high-throughput microfluidic cell migration platform that coordinates robotic liquid handling and computer vision for rapidly quantifying individual cellular motility. Using this innovative technology, 172 compounds were tested and a surprisingly low correlation between migration and growth inhibition was found. Notably, many compounds were found to inhibit migration of most cells while leaving fast-moving subpopulations unaffected. This work further pinpoints synergistic drug combinations, including Bortezomib and Danirixin, to stop fast-moving cells. To explain the observed cell behaviors, single-cell morphological and molecular analysis were performed. These studies establish a novel technology to identify promising migration inhibitors for cancer treatment and relevant applications.

Imputation of single-cell transcriptome data enables the reconstruction of networks predictive of breast cancer metastasis

Single-cell transcriptome data provide a unique opportunity to explore the gene networks of a particular cell type. However, insufficient capture rate and high dimensionality of single-cell RNA sequencing (scRNA-seq) data challenge cell-type-specific gene network (CGN) reconstruction. Here, we demonstrated that the imputation of scRNA-seq data enables reconstruction of CGNs by effective retrieval of gene functional associations. We reconstructed CGNs for seven primary and nine metastatic breast cancer cell lines using scRNA-seq data with imputation. Key genes for primary or metastatic cell lines were prioritized based on network centrality measures and CGN hub genes that were presumed to be the major determinant of cell type characteristics. To identify novel genes in breast cancer metastasis, we used the average rank difference of centrality between the primary and metastatic cell lines. Genes predicted using CGN centrality analysis were more enriched for known breast cancer metastatic genes than those predicted using differential expression. The molecular chaperone CCT2 was identified as a novel gene for breast metastasis during knockdown assays of several candidate genes. Overall, our study demonstrated an effective CGN reconstruction technique with imputation of scRNA-seq data and the feasibility of identifying key genes for particular cell subsets using single-cell network analysis.

One Step Nucleic Acid Amplification (OSNA) Lysate Samples Are Suitable to Establish a Transcriptional Metastatic Signature in Patients with Early Stage Hormone Receptors-Positive Breast Cancer

The One Step Nucleic Acid Amplification (OSNA) is being adopted worldwide for sentinel lymph nodes (SLNs) staging in breast cancer (BC). As major disadvantage, OSNA precludes prognostic information based on structural evaluation of SLNs. Our aim is to identify biomarkers related to tumor-microenvironment interplay exploring gene expression data from the OSNA remaining lysate. This study included 32 patients with early stage hormone receptors-positive BC. Remaining OSNA lysates were prepared for targeted RNA-sequencing analysis. Identification of differentially expressed genes (DEGs) was performed by DESeq2 in R and data analysis in STATA. The results show that, in metastatic SLNs, several genes were upregulated: KRT7, VTCN1, CD44, GATA3, ALOX15B, RORC, NECTIN2, LRG1, CD276, FOXM1 and IGF1R. Hierarchical clustering analysis revealed three different clusters. The identified DEGs codify proteins mainly involved in cancer aggressiveness and with impact in immune response. The overexpression of the immune suppressive genes VTCN1 and CD276 may explain that no direct evidence of activation of immune response in metastatic SLNs was found. We show that OSNA results may be improved incorporating microenvironment-related biomarkers that may be useful in the future for prognosis stratification and immunotherapy selection. As OSNA assay is being implemented for SLNs staging in other cancers, this approach could also have a wider utility.

C/EBPδ Suppresses Motility-Associated Gene Signatures and Reduces PDAC Cell Migration

Pancreatic Ductal Adenocarcinoma (PDAC) is among the most aggressive human cancers and occurs globally at an increasing incidence. Metastases are the primary cause of cancer-related death and, in the majority of cases, PDAC is accompanied by metastatic disease at the time of diagnosis, making it a particularly lethal cancer. Regrettably, to date, no curative treatment has been developed for patients with metastatic disease, resulting in a 5-year survival rate of only 11%. We previously found that the protein expression of the transcription factor CCAAT/Enhancer-Binding Protein Delta (C/EBPδ) negatively correlates with lymph node involvement in PDAC patients. To better comprehend the etiology of metastatic PDAC, we explored the role of C/EBPδ at different steps of the metastatic cascade, using established in vitro models. We found that C/EBPδ has a major impact on cell motility, an important prerequisite for tumor cells to leave the primary tumor and to reach distant sites. Our data suggest that C/EBPδ induces downstream pathways that modulate actin cytoskeleton dynamics to reduce cell migration and to induce a more epithelial-like cellular phenotype. Understanding the mechanisms dictating epithelial and mesenchymal features holds great promise for improving the treatment of PDAC.

Recent advances in microfluidics-based cell migration research

Cell migration is crucial for many biological processes, including normal development, immune response, and tissue homeostasis and many pathological processes such as cancer metastasis and wound healing. Microfluidics has revolutionized the research in cell migration since its inception as it reduces the cost of studies and allows precise manipulation of different parameters that affect cell migratory response. Over the past decade, the field has made great strides in many directions, such as techniques for better control of the cellular microenvironment, application-oriented physiological-like models, and machine-assisted cell image analysis methods. Here we review recent developments in the field of microfluidic cell migration through the following aspects: 1) the co-culture models for studying host-pathogen interactions at single-cell resolution; 2) the spatiotemporal manipulation of the chemical gradients guiding cell migration; 3) the organ-on-chip models to study cell transmigration; and 4) the deep learning image processing strategies for cell migration data analysis. We further discuss the challenges, possible improvement and future perspectives of using microfluidic techniques to study cell migration.

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

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.

Potential epigenetic modifications implicated in triple- to quadruple-negative breast cancer transition: a review

Current research on triple-negative breast cancer (TNBC) has resulted in delineation into the quadruple-negative breast cancer (QNBC) subgroup. Epigenetic modifications such as DNA methylation, histone posttranslational modifications and associated changes in chromatin architecture have been implicated in breast cancer pathogenesis. Herein, the authors highlight genes with observed epigenetic modifications that are associated with more aggressive TNBC/QNBC pathogenesis and possible interventions. Advanced literature searches were done on PubMed/MEDLINE, Scopus and Google Scholar. The results suggest that nine epigenetically altered genes/differentially expressed proteins in addition to the downregulated androgen receptor are associated with TNBC aggressiveness and could be implicated in the TNBC to QNBC transition. Thus, restoring the normal expression of these genes via epigenetic reprogramming could be therapeutically beneficial to TNBC and QNBC patients.

XGBoost-based and tumor-immune characterized gene signature for the prediction of metastatic status in breast cancer

Background

For a long time, breast cancer has been a leading cancer diagnosed in women worldwide, and approximately 90% of cancer-related deaths are caused by metastasis. For this reason, finding new biomarkers related to metastasis is an urgent task to predict the metastatic status of breast cancer and provide new therapeutic targets.

Methods

In this research, an efficient model of eXtreme Gradient Boosting (XGBoost) optimized by a grid search algorithm is established to realize auxiliary identification of metastatic breast tumors based on gene expression. Estimated by ten-fold cross-validation, the optimized XGBoost classifier can achieve an overall higher mean AUC of 0.82 compared to other classifiers such as DT, SVM, KNN, LR, and RF.

Results

A novel 6-gene signature (SQSTM1, GDF9, LINC01125, PTGS2, GVINP1, and TMEM64) was selected by feature importance ranking and a series of in vitro experiments were conducted to verify the potential role of each biomarker. In general, the effects of SQSTM in tumor cells are assigned as a risk factor, while the effects of the other 5 genes (GDF9, LINC01125, PTGS2, GVINP1, and TMEM64) in immune cells are assigned as protective factors.

Conclusions

Our findings will allow for a more accurate prediction of the metastatic status of breast cancer and will benefit the mining of breast cancer metastasis-related biomarkers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03369-9.

Unravelling glioblastoma heterogeneity by means of single-cell RNA sequencing

Glioblastoma (GBM) is the most invasive and deadliest brain cancer in adults. Its inherent heterogeneity has been designated as the main cause of treatment failure. Thus, a deeper understanding of the diversity that shapes GBM pathobiology is of utmost importance. Single-cell RNA sequencing (scRNA-seq) technologies have begun to uncover the hidden composition of complex tumor ecosystems. Herein, a semi-systematic search of reference literature databases provided all existing publications using scRNA-seq for the investigation of human GBM. We compared and discussed findings from these works to build a more robust and unified knowledge base. All aspects ranging from inter-patient heterogeneity to intra-tumoral organization, cancer stem cell diversity, clonal mosaicism, and the tumor microenvironment (TME) are comprehensively covered in this report. Tumor composition not only differs across patients but also involves a great extent of heterogeneity within itself. Spatial and cellular heterogeneity can reveal tumor evolution dynamics. In addition, the discovery of distinct cell phenotypes might lead to the development of targeted treatment approaches. In conclusion, scRNA-seq expands our knowledge of GBM heterogeneity and helps to unravel putative therapeutic targets.

Microfluidics applications for high-throughput single cell sequencing

The inherent heterogeneity of individual cells in cell populations plays significant roles in disease development and progression, which is critical for disease diagnosis and treatment. Substantial evidences show that the majority of traditional gene profiling methods mask the difference of individual cells. Single cell sequencing can provide data to characterize the inherent heterogeneity of individual cells, and reveal complex and rare cell populations. Different microfluidic technologies have emerged for single cell researches and become the frontiers and hot topics over the past decade. In this review article, we introduce the processes of single cell sequencing, and review the principles of microfluidics for single cell analysis. Also, we discuss the common high-throughput single cell sequencing technologies along with their advantages and disadvantages. Lastly, microfluidics applications in single cell sequencing technology for the diagnosis of cancers and immune system diseases are briefly illustrated.

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

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.

Cancer biology deciphered by single-cell transcriptomic sequencing

Tumors are complex ecosystems in which heterogeneous cancer cells interact with their microenvironment composed of diverse immune, endothelial, and stromal cells. Cancer biology had been studied using bulk genomic and gene expression profiling, which however mask the cellular diversity and average the variability among individual molecular programs. Recent advances in single-cell transcriptomic sequencing have enabled a detailed dissection of tumor ecosystems and promoted our understanding of tumorigenesis at single-cell resolution. In the present review, we discuss the main topics of recent cancer studies that have implemented single-cell RNA sequencing (scRNA-seq). To study cancer cells, scRNA-seq has provided novel insights into the cancer stem-cell model, treatment resistance, and cancer metastasis. To study the tumor microenvironment, scRNA-seq has portrayed the diverse cell types and complex cellular states of both immune and non-immune cells interacting with cancer cells, with the promise to discover novel targets for future immunotherapy.

Single-cell RNA sequencing in cancer: Applications, advances, and emerging challenges

Cancer has become one of the greatest threats to human health, and new technologies are urgently needed to further clarify the mechanisms of cancer so that better detection and treatment strategies can be developed. At present, extensive genomic analysis and testing of clinical specimens shape the insights into carcinoma. Nevertheless, carcinoma of humans is a complex ecosystem of cells, including carcinoma cells and immunity-related and stroma-related subsets, with accurate characteristics obscured by extensive genome-related approaches. A growing body of research shows that sequencing of single-cell RNA (scRNA-seq) is emerging to be an effective way for dissecting human tumor tissue at single-cell resolution, presenting one prominent way for explaining carcinoma biology. This review summarizes the research progress of scRNA-seq in the field of tumors, focusing on the application of scRNA-seq in tumor circulating cells, tumor stem cells, tumor drug resistance, the tumor microenvironment, and so on, which provides a new perspective for tumor research.

Applications of single-cell sequencing in cancer research: progress and perspectives

Single-cell sequencing, including genomics, transcriptomics, epigenomics, proteomics and metabolomics sequencing, is a powerful tool to decipher the cellular and molecular landscape at a single-cell resolution, unlike bulk sequencing, which provides averaged data. The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions. In this review, we summarize emerging single-cell sequencing technologies and recent cancer research progress obtained by single-cell sequencing, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and the underlying mechanisms of tumor biological behaviors. Overall, the prospects of single-cell sequencing in facilitating diagnosis, targeted therapy and prognostic prediction among a spectrum of tumors are bright. In the near future, advances in single-cell sequencing will undoubtedly improve our understanding of the biological characteristics of tumors and highlight potential precise therapeutic targets for patients.

Single cell RNA sequencing for breast cancer: present and future

Breast cancer is one of the most common malignant tumors in women. It is a heterogeneous disease related to genetic and environmental factors. Presently, the treatment of breast cancer still faces challenges due to recurrence and metastasis. The emergence of single-cell RNA sequencing (scRNA-seq) technology has brought new strategies to deeply understand the biological behaviors of breast cancer. By analyzing cell phenotypes and transcriptome differences at the single-cell level, scRNA-seq reveals the heterogeneity, dynamic growth and differentiation process of cells. This review summarizes the application of scRNA-seq technology in breast cancer research, such as in studies on cell heterogeneity, cancer cell metastasis, drug resistance, and prognosis. scRNA-seq technology is of great significance to deeply analyze the mechanism of breast cancer occurrence and development, identify new therapeutic targets and develop new therapeutic approaches for breast cancer.

Identifying Molecular Signatures of Distinct Modes of Collective Migration in Response to the Microenvironment Using Three-Dimensional Breast Cancer Models

Simple Summary

The objective of this study was to investigate the role of two microenvironmental factors, namely, tumor-intrinsic hypoxia and secretome in inducing collective migration. We utilized three-dimensional (3D) discrete-sized microtumor models, which recapitulate hallmarks of transition of ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC). Tumor-intrinsic hypoxia induced directional migration in large hypoxic microtumors while secretome from large microtumors induced radial migration in non-hypoxic microtumors. This highlights the emergence phenotypic heterogeneity and plasticity in cancer cells in response to different microenvironmental stimuli. To unravel mechanisms underlying these two distinct modes of migration, we performed differential gene expression analysis of hypoxia- and secretome-induced migratory phenotypes using non-migratory, non-hypoxic microtumors as controls. We proposed unique gene signature sets related to tumor-intrinsic hypoxia, hypoxia-induced epithelial-mesenchymal transition (EMT), as well as hypoxia-induced directional migration and secretome-induced radial migration.

Abstract

Collective cell migration is a key feature of transition of ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) among many other cancers, yet the microenvironmental factors and underlying mechanisms that trigger collective migration remain poorly understood. Here, we investigated two microenvironmental factors, tumor-intrinsic hypoxia and tumor-secreted factors (secretome), as triggers of collective migration using three-dimensional (3D) discrete-sized microtumor models that recapitulate hallmarks of DCIS-IDC transition. Interestingly, the two factors induced two distinct modes of collective migration: directional and radial migration in the 3D microtumors generated from the same breast cancer cell line model, T47D. Without external stimulus, large (600 µm) T47D microtumors exhibited tumor-intrinsic hypoxia and directional migration, while small (150 µm), non-hypoxic microtumors exhibited radial migration only when exposed to the secretome of large microtumors. To investigate the mechanisms underlying hypoxia- and secretome-induced directional vs. radial migration modes, we performed differential gene expression analysis of hypoxia- and secretome-induced migratory microtumors compared with non-hypoxic, non-migratory small microtumors as controls. We propose unique gene signature sets related to tumor-intrinsic hypoxia, hypoxia-induced epithelial-mesenchymal transition (EMT), as well as hypoxia-induced directional migration and secretome-induced radial migration. Gene Set Enrichment Analysis (GSEA) and protein-protein interaction (PPI) network analysis revealed enrichment and potential interaction between hypoxia, EMT, and migration gene signatures for the hypoxia-induced directional migration. In contrast, hypoxia and EMT were not enriched in the secretome-induced radial migration, suggesting that complete EMT may not be required for radial migration. Survival analysis identified unique genes associated with low survival rate and poor prognosis in TCGA-breast invasive carcinoma dataset from our tumor-intrinsic hypoxia gene signature (CXCR4, FOXO3, LDH, NDRG1), hypoxia-induced EMT gene signature (EFEMP2, MGP), and directional migration gene signature (MAP3K3, PI3K3R3). NOS3 was common between hypoxia and migration gene signature. Survival analysis from secretome-induced radial migration identified ATM, KCNMA1 (hypoxia gene signature), and KLF4, IFITM1, EFNA1, TGFBR1 (migration gene signature) to be associated with poor survival rate. In conclusion, our unique 3D cultures with controlled microenvironments respond to different microenvironmental factors, tumor-intrinsic hypoxia, and secretome by adopting distinct collective migration modes and their gene expression analysis highlights the phenotypic heterogeneity and plasticity of epithelial cancer cells.

Single-cell RNA sequencing in cancer research

Single-cell RNA sequencing (scRNA-seq), a technology that analyzes transcriptomes of complex tissues at single-cell levels, can identify differential gene expression and epigenetic factors caused by mutations in unicellular genomes, as well as new cell-specific markers and cell types. scRNA-seq plays an important role in various aspects of tumor research. It reveals the heterogeneity of tumor cells and monitors the progress of tumor development, thereby preventing further cellular deterioration. Furthermore, the transcriptome analysis of immune cells in tumor tissue can be used to classify immune cells, their immune escape mechanisms and drug resistance mechanisms, and to develop effective clinical targeted therapies combined with immunotherapy. Moreover, this method enables the study of intercellular communication and the interaction of tumor cells and non-malignant cells to reveal their role in carcinogenesis. scRNA-seq provides new technical means for further development of tumor research and is expected to make significant breakthroughs in this field. This review focuses on the principles of scRNA-seq, with an emphasis on the application of scRNA-seq in tumor heterogeneity, pathogenesis, and treatment.

Biophysical Informatics Approach For Quantifying Phenotypic Heterogeneity In Cancer Cell Migration In Confined Microenvironments

MOTIVATION

Cancer cell heterogeneity can manifest genetically and phenotypically. Bioinformatics methods have been used to analyze complex genomics and transcriptomics data, but have not been well-established for analyzing biophysical data of phenotypically heterogeneous tumor cells. Here, we take an informatics approach to analyze the biophysical data of MDA-MB-231 cells, a widely used breast cancer cell line, during their spontaneous migration through confined environments. Experimentally, we vary the constriction microchannel geometries (wide channel, short constriction, and long constriction) and apply drug treatments. We find that cells in the short constriction are similar in morphology to the cells in the wide channel. However, their fluorescence profiles are comparable to those in the long constriction. We demonstrate that the cell migratory phenotype is correlated more to mitochondria in a non-confined environment and more to actin in a confined environment. We demonstrate that the cells' migratory phenotypes are altered by ciliobrevin D, a dynein inhibitor, in both confined and non-confined environments. Overall, our approach elucidates phenotypic heterogeneity in cancer cells under confined microenvironments at single-cell resolution.

RESULTS

Here, we apply a bioinformatics approach to a single cell invasion assay. We demonstrate that this method can determine distinctions in morphology, cytoskeletal activities, and mitochondrial activities under various geometric constraints and for cells of different speeds. Our approach can be readily adapted to various heterogeneity studies for different types of input biophysical data. In addition, this approach can be applied to studies related to biophysical changes due to differences in external stimuli, such as treatment effects on cellular and subcellular activities, at single-cell resolution. Finally, as similar bioinformatics methods have been widely applied in studies of genetic heterogeneity, biophysical information extracted using this approach can be analyzed together with the genetic data to relate genetic and phenotypic heterogeneity.

AVAILABILITY

The data that support the findings of this study are available from the corresponding author upon reasonable request.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Involvement of the ERK/HIF-1α/EMT Pathway in XCL1-Induced Migration of MDA-MB-231 and SK-BR-3 Breast Cancer Cells

Chemokine–receptor interactions play multiple roles in cancer progression. It was reported that the overexpression of X-C motif chemokine receptor 1 (XCR1), a specific receptor for chemokine X-C motif chemokine ligand 1 (XCL1), stimulates the migration of MDA-MB-231 triple-negative breast cancer cells. However, the exact mechanisms of this process remain to be elucidated. Our study found that XCL1 treatment markedly enhanced MDA-MB-231 cell migration. Additionally, XCL1 treatment enhanced epithelial–mesenchymal transition (EMT) of MDA-MB-231 cells via E-cadherin downregulation and upregulation of N-cadherin and vimentin as well as increases in β-catenin nucleus translocation. Furthermore, XCL1 enhanced the expression of hypoxia-inducible factor-1α (HIF-1α) and phosphorylation of extracellular signal-regulated kinase (ERK) 1/2. Notably, the effects of XCL1 on cell migration and intracellular signaling were negated by knockdown of XCR1 using siRNA, confirming XCR1-mediated actions. Treating MDA-MB-231 cells with U0126, a specific mitogen-activated protein kinase kinase (MEK) 1/2 inhibitor, blocked XCL1-induced HIF-1α accumulation and cell migration. The effect of XCL1 on cell migration was also evaluated in ER^-/HER2⁺ SK-BR-3 cells. XCL1 also promoted cell migration, EMT induction, HIF-1α accumulation, and ERK phosphorylation in SK-BR-3 cells. While XCL1 did not exhibit any significant impact on the matrix metalloproteinase (MMP)-2 and -9 expressions in MDA-MB-231 cells, it increased the expression of these enzymes in SK-BR-3 cells. Collectively, our results demonstrate that activation of the ERK/HIF-1α/EMT pathway is involved in the XCL1-induced migration of both MDA-MB-231 and SK-BR-3 breast cancer cells. Based on our findings, the XCL1–XCR1 interaction and its associated signaling molecules may serve as specific targets for the prevention of breast cancer cell migration and metastasis.

Lactate Metabolism in Breast Cancer Microenvironment: Contribution Focused on Associated Adipose Tissue and Obesity

Metabolic reprogramming that favors high glycolytic flux with lactate production in normoxia is among cancer hallmarks. Lactate is an essential oncometabolite regulating cellular redox homeostasis, energy substrate partitioning, and intracellular signaling. Moreover, malignant phenotype's chief characteristics are dependent on the interaction between cancer cells and their microenvironment. In breast cancer, mammary adipocytes represent an essential cellular component of the tumor milieu. We analyzed lactate concentration, lactate dehydrogenase (LDH) activity, and isozyme pattern, and LDHA/LDHB protein expression and tissue localization in paired biopsies of breast cancer tissue and cancer-associated adipose tissue in normal-weight and overweight/obese premenopausal women, compared to benign breast tumor tissue and adipose tissue in normal-weight and overweight/obese premenopausal women. We show that higher lactate concentration in cancer tissue is concomitant with a shift in isozyme pattern towards the "muscle-type" LDH and corresponding LDHA and LDHB protein expression changes. In contrast, significantly higher LDH activity in cancer-associated adipose tissue seems to be directed towards lactate oxidation. Moreover, localization patterns of LDH isoforms varied substantially across different areas of breast cancer tissue. Invasive front of the tumor showed cell-specific protein localization of LDHA in breast cancer cells and LDHB in cancer-associated adipocytes. The results suggest a specific, lactate-centric relationship between cancer tissue and cancer-associated adipose tissue and indicate how cancer-adipose tissue cross-talk may be influenced by obesity in premenopausal women.

Breast cancers, mammary stem cells, and cancer stem cells, characteristics, and hypotheses

The cellular heterogeneity of breast cancers still represents a major therapeutic challenge. The latest genomic studies have classified breast cancers in distinct clusters to inform the therapeutic approaches and predict clinical outcomes. The mammary epithelium is composed of luminal and basal cells, and this seemingly hierarchical organization is dependent on various stem cells and progenitors populating the mammary gland. Some cancer cells are conceptually similar to the stem cells as they can self-renew and generate bulk populations of nontumorigenic cells. Two models have been proposed to explain the cell of origin of breast cancer and involve either the reprogramming of differentiated mammary cells or the dysregulation of mammary stem cells or progenitors. Both hypotheses are not exclusive and imply the accumulation of independent mutational events. Cancer stem cells have been isolated from breast tumors and implicated in the development, metastasis, and recurrence of breast cancers. Recent advances in single-cell sequencing help deciphering the clonal evolution within each breast tumor. Still, few clinical trials have been focused on these specific cancer cell populations.

Single-cell RNA sequencing in breast cancer: Understanding tumor heterogeneity and paving roads to individualized therapy

Single‐cell RNA sequencing (scRNA‐seq) is a novel technology that allows transcriptomic analyses of individual cells. During the past decade, scRNA‐seq sensitivity, accuracy, and efficiency have improved due to innovations including more sensitive, automated, and cost‐effective single‐cell isolation methods with higher throughput as well as ongoing technological development of scRNA‐seq protocols. Among the variety of current approaches with distinct features, researchers can choose the most suitable method to carry out their research. By profiling single cells in a complex population mix, scRNA‐seq presents great advantages over traditional sequencing methods in dissecting heterogeneity in cell populations hidden in bulk analysis and exploring rare cell types associated with tumorigenesis and metastasis. scRNA‐seq studies in recent years in the field of breast cancer research have clustered breast cancer cell populations with different molecular subtypes to identify distinct populations that may correlate with poor prognosis and drug resistance. The technology has also been used to explain tumor microenvironment heterogeneity by identifying distinct immune cell subsets that may be associated with immunosurveillance and are potential immunotherapy targets. Moreover, scRNA‐seq has diverse applications in breast cancer research besides exploring heterogeneity, including the analysis of cell‐cell communications, regulatory single‐cell states, immune cell distributions, and more. scRNA‐seq is also a promising tool that can facilitate individualized therapy due to its ability to define cell subsets with potential treatment targets. Although scRNA‐seq studies of therapeutic selection in breast cancer are currently limited, the application of this technology in this field is prospective. Joint efforts and original ideas are needed to better implement scRNA‐seq technologies in breast cancer research to pave the way for individualized treatment management. This review provides a brief introduction on the currently available scRNA‐seq approaches along with their corresponding strengths and weaknesses and may act as a reference for the selection of suitable methods for research. We also discuss the current applications of scRNA‐seq in breast cancer research for tumor heterogeneity analysis, individualized therapy, and the other research directions mentioned above by reviewing corresponding published studies. Finally, we discuss the limitations of current scRNA‐seq technologies and technical problems that remain to be overcome.

Combating metastasis of breast cancer cells with a carboplatin analogue containing an all-trans retinoic acid ligand

Pt-ATRA, a carboplatin analogue containing an all-trans retinoic acid (ATRA) derivative ligand, was synthesized via a click reaction. Upon cellular internalization, Pt-ATRA exhibits a dual function, releasing an active Pt(ii) moiety to induce cell apoptosis and ATRA to inhibit tumor metastasis.

Cancer cell lines show high heritability for motility but not generation time

Tumour evolution depends on heritable differences between cells in traits affecting cell survival or replication. It is well established that cancer cells are genetically and phenotypically heterogeneous; however, the extent to which this phenotypic variation is heritable is far less well explored. Here, we estimate the broad-sense heritability (H ²) of two cell traits related to cancer hallmarks--cell motility and generation time--within populations of four cancer cell lines in vitro and find that motility is strongly heritable. This heritability is stable across multiple cell generations, with heritability values at the high end of those measured for a range of traits in natural populations of animals or plants. These findings confirm a central assumption of cancer evolution, provide a first quantification of the evolvability of key traits in cancer cells and indicate that there is ample raw material for experimental evolution in cancer cell lines. Generation time, a trait directly affecting cell fitness, shows substantially lower values of heritability than cell speed, consistent with its having been under directional selection removing heritable variation.