Single-cell RNA sequencing reveals gene expression signatures of breast cancer-associated endothelial cells. Oncotarget. 2017;9:10945-10961. [PMID: 29541388 PMCID: PMC5834272 DOI: 10.18632/oncotarget.23760]

The in situ transcriptomic landscape of breast tumour-associated and normal adjacent endothelial cells

BACKGROUND AND AIMS

Triple Negative Breast Cancer (TNBC) is associated with increased angiogenesis, which is known to aid tumour growth and metastasis. Anti-angiogenic therapies that have been developed to target this feature have mostly generated disappointing clinical results. Further research into targeted approaches is limited by a lack of understanding of the in situ molecular profile of tumour-associated vasculature. In this study, we aimed to understand the differences in the molecular profiles of tumour endothelial cells vs normal-adjacent endothelial cells in TNBC tissues.

METHOD

We have applied unbiased whole transcriptome spatial profiling of in situ gene expressions of endothelial cells localized in full-face patient TNBC tissues (n = 4) and normal-adjacent regions of the same patient breast tissues.

RESULTS

Our comparative analysis revealed that 2412 genes were differentially expressed (padj < 0.05) between the tumour endothelial cells and normal-adjacent endothelial cells. Pathway enrichment showed the enrichment of gene sets related to cell-cell, cell-ECM adhesion, chromatin organization and remodeling, and protein-DNA complex subunit organization.

CONCLUSION

Overall, the results revealed unique molecular profiles and signalling pathways of tumour-associated vasculature, which is a critical step towards larger cohort studies investigating potential targets for TNBC prognosis and anti-angiogenic treatments.

Integrated bioinformatics approaches to investigate alterations in transcriptomic profiles of monkeypox infected human cell line model

BACKGROUND

The recent re-emergence of the monkeypox (mpox) epidemic in nonendemic regions has raised concerns regarding a potential global outbreak. The mpox virus (MPV) is a smallpox-like virus belonging to the genus Orthopoxvirus (family: Poxviridae). Although studies suggest that MPV infection suppresses the Toll-like receptor-3- and tumor necrosis factor-α-related signaling pathways, whether MPV regulates other immune-related pathways remains unclear.

METHODS

In this study, two distinct temporal patterns were used for establishing an MPV-infected human immortal epithelial cancer cell line (HeLa). These two durations 2 and 12 h of incubation were selected to identify the coregulated genes and pathways affected by MPV infection.

RESULTS

The use of the Gene Ontology framework, Kyoto Encyclopedia of Genes and Genome database, and MetaCore software yielded valuable insights. Specifically, various pathways were found to be enriched in HeLa cells infected with MPV for 2 and 12 h. These pathways included Notch, CD40, CD95, hypoxia-inducible factor-1-α, interleukin (IL)- 1, IL-6, phosphoinositide 3-kinase, nuclear factor-κB, mitogen-activated protein kinase, and oxidative stress-induced signalling pathways. Clusters and pathways of metabolism and viral replication cycles were significantly associated with the 2-hour infection group. This association was identified based on the regulation of genes such as HSPG2, RHPN2, MYL1, ASPHD2, CA9, VIPR1, SNX12, MGC2752, SLC25A1, PEX19, and AREG. Furthermore, clusters and pathways related to immunity and cell movement were found to be associated with the 12-hour infection group. This association was identified based on the regulation of genes such as C1orf21, C19orf48, HRK, IL8, GULP1, SCAND2, ATP5C1, FEZ1, SGSH, TACC2, CYP4X1, MMP1, CPB1, P2RY13, WDR27, PRPF4, and ENDOD1.

CONCLUSIONS

This study can improve our understanding of the mechanisms underlying the pathophysiology and post-infection sequelae of mpox. Our findings provide valuable insights into the various modes of MPV infection.

MicroRNAs in Tumor Endothelial Cells: Regulation, Function and Therapeutic Applications

Tumor endothelial cells (TECs) are key stromal components of the tumor microenvironment, and are essential for tumor angiogenesis, growth and metastasis. Accumulating evidence has shown that small single-stranded non-coding microRNAs (miRNAs) act as powerful endogenous regulators of TEC function and blood vessel formation. This systematic review provides an up-to-date overview of these endothelial miRNAs. Their expression is mainly regulated by hypoxia, pro-angiogenic factors, gap junctions and extracellular vesicles, as well as long non-coding RNAs and circular RNAs. In preclinical studies, they have been shown to modulate diverse fundamental angiogenesis-related signaling pathways and proteins, including the vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) pathway; the rat sarcoma virus (Ras)/rapidly accelerated fibrosarcoma (Raf)/mitogen-activated protein kinase kinase (MEK)/extracellular signal-regulated kinase (ERK) pathway; the phosphoinositide 3-kinase (PI3K)/AKT pathway; and the transforming growth factor (TGF)-β/TGF-β receptor (TGFBR) pathway, as well as krüppel-like factors (KLFs), suppressor of cytokine signaling (SOCS) and metalloproteinases (MMPs). Accordingly, endothelial miRNAs represent promising targets for future anti-angiogenic cancer therapy. To achieve this, it will be necessary to further unravel the regulatory and functional networks of endothelial miRNAs and to develop safe and efficient TEC-specific miRNA delivery technologies.

Understanding tumour endothelial cell heterogeneity and function from single-cell omics

Anti-angiogenic therapies (AATs) are used to treat different types of cancers. However, their success is limited owing to insufficient efficacy and resistance. Recently, single-cell omics studies of tumour endothelial cells (TECs) have provided new mechanistic insight. Here, we overview the heterogeneity of human TECs of all tumour types studied to date, at the single-cell level. Notably, most human tumour types contain varying numbers but only a small population of angiogenic TECs, the presumed targets of AATs, possibly contributing to the limited efficacy of and resistance to AATs. In general, TECs are heterogeneous within and across all tumour types, but comparing TEC phenotypes across tumours is currently challenging, owing to the lack of a uniform nomenclature for endothelial cells and consistent single-cell analysis protocols, urgently raising the need for a more consistent approach. Nonetheless, across most tumour types, universal TEC markers (ACKR1, PLVAP and IGFBP3) can be identified. Besides angiogenesis, biological processes such as immunomodulation and extracellular matrix organization are among the most commonly predicted enriched signatures of TECs across different tumour types. Although angiogenesis and extracellular matrix targets have been considered for AAT (without the hoped success), the immunomodulatory properties of TECs have not been fully considered as a novel anticancer therapeutic approach. Therefore, we also discuss progress, limitations, solutions and novel targets for AAT development.

Cellular heterogeneity and stem cells of vascular endothelial cells in blood vessel formation and homeostasis: Insights from single-cell RNA sequencing

Vascular endothelial cells (ECs) that constitute the inner surface of blood vessels are essential for new vessel formation and organ homeostasis. ECs display remarkable phenotypic heterogeneity across different organs and the vascular tree during angiogenesis and homeostasis. Recent advances in single cell RNA sequencing (scRNA-seq) technologies have allowed a new understanding of EC heterogeneity in both mice and humans. In particular, scRNA-seq has identified new molecular signatures for arterial, venous and capillary ECs in different organs, as well as previously unrecognized specialized EC subtypes, such as the aerocytes localized in the alveolar capillaries of the lung. scRNA-seq has also revealed the gene expression profiles of specialized tissue-resident EC subtypes that are capable of clonal expansion and contribute to adult angiogenesis, a process of new vessel formation from the pre-existing vasculature. These specialized tissue-resident ECs have been identified in various different mouse tissues, including aortic endothelium, liver, heart, lung, skin, skeletal muscle, retina, choroid, and brain. Transcription factors and signaling pathways have also been identified in the specialized tissue-resident ECs that control angiogenesis. Furthermore, scRNA-seq has also documented responses of ECs in diseases such as cancer, age-related macular degeneration, Alzheimer's disease, atherosclerosis, and myocardial infarction. These new findings revealed by scRNA-seq have the potential to provide new therapeutic targets for different diseases associated with blood vessels. In this article, we summarize recent advances in the understanding of the vascular endothelial cell heterogeneity and endothelial stem cells associated with angiogenesis and homeostasis in mice and humans, and we discuss future prospects for the application of scRNA-seq technology.

The tumor microenvironment and triple-negative breast cancer aggressiveness: shedding light on mechanisms and targeting

INTRODUCTION

In contrast to other breast cancer subtypes, there are currently limited options of targeted therapies for triple-negative breast cancer (TNBC). Immense research has demonstrated that not only cancer cells but also stromal cells and immune cells in the tumor microenvironment (TME) play significant roles in the progression of TNBC. It is thus critical to understand the components of the TME of TNBC and the interactions between the various cell populations.

AREAS COVERED

The components of the TME of TNBC identified by single-cell technologies are reviewed. Furthermore, the molecular interactions between the cells and the potential therapeutic targets contributing to the progression of TNBC are discussed.

EXPERT OPINION

Single-cell omics studies have contributed to the classification of cells in the TME and the identification of important cell types involved in the progression and the treatment of the tumor. The interactions between cancer cells and stromal cells/immune cells in the TME have led to the discovery of potential therapeutic targets. Experimental data with spatial and temporal resolution will further boost the understanding of the TME of TNBC.

The single cell transcriptional landscape of esophageal adenocarcinoma and its modulation by neoadjuvant chemotherapy

Immune checkpoint blockade has recently proven effective in subsets of patients with esophageal adenocarcinoma (EAC) but little is known regarding the EAC immune microenvironment. We determined the single cell transcriptional profile of EAC in 8 patients who were treatment-naive (n = 4) or had received neoadjuvant chemotherapy (n = 4). Analysis of 52,387 cells revealed 10 major cell subsets of tumor, immune and stromal cells. Prior to chemotherapy tumors were heavy infiltrated by T regulatory cells and exhausted effector T cells whilst plasmacytoid dendritic cells were markedly expanded. Two dominant cancer-associated fibroblast populations were also observed whilst endothelial populations were suppressed. Pathological remission following chemotherapy associated with broad reversal of immune abnormalities together with fibroblast transition and an increase in endothelial cells whilst a chemoresistant epithelial stem cell population correlated with poor response. These findings reveal features that underlie and limit the response to current immunotherapy and identify a range of novel opportunities for targeted therapy.

Chemotherapy-Induced Collagen IV Drives Cancer Cell Motility through Activation of Src and Focal Adhesion Kinase

Triple-negative breast cancer (TNBC) is the most aggressive and deadly subtype of breast cancer, accounting for 30,000 cases annually in the United States. While there are several clinical trials ongoing to identify new agents to treat TNBC, the majority of patients with TNBC are treated with anthracycline- or taxane-based chemotherapies in the neoadjuvant setting, followed by surgical resection and adjuvant chemotherapy. While many patients respond well to this approach, as many as 25% will suffer local or metastatic recurrence within 5 years. Understanding the mechanisms that drive recurrence after chemotherapy treatment is critical to improving survival for patients with TNBC. It is well established that the extracellular matrix (ECM), which provides structure and support to tissues, is a major driver of tumor growth, local invasion, and dissemination of cancer cells to distant metastatic sites. In the present study, we show that decellularized ECM (dECM) obtained from chemotherapy-treated mice increases motility of treatment-naïve breast cancer cells compared with vehicle-treated dECM. Tandem-mass-tag proteomics revealed that anthracycline- and taxane-based chemotherapies induce drug-specific changes in tumor ECM composition. The basement membrane protein collagen IV was significantly upregulated in the ECM of chemotherapy-treated mice and patients treated with neoadjuvant chemotherapy. Collagen IV drove invasion via activation of Src and focal adhesion kinase signaling downstream of integrin α1 and α2, and inhibition of collagen IV-driven signaling decreased motility in chemotherapy-treated dECM. These studies provide a novel mechanism by which chemotherapy may induce metastasis via its effects on ECM composition.

SIGNIFICANCE

Cytotoxic chemotherapy induces significant changes in the composition of tumor ECM, inducing a more invasive and aggressive phenotype in residual tumor cells following chemotherapy.

Angiogenesis goes computational – The future way forward to discover new angiogenic targets?

Multi-omics technologies are being increasingly utilized in angiogenesis research. Yet, computational methods have not been widely used for angiogenic target discovery and prioritization in this field, partly because (wet-lab) vascular biologists are insufficiently familiar with computational biology tools and the opportunities they may offer. With this review, written for vascular biologists who lack expertise in computational methods, we aspire to break boundaries between both fields and to illustrate the potential of these tools for future angiogenic target discovery. We provide a comprehensive survey of currently available computational approaches that may be useful in prioritizing candidate genes, predicting associated mechanisms, and identifying their specificity to endothelial cell subtypes. We specifically highlight tools that use flexible, machine learning frameworks for large-scale data integration and gene prioritization. For each purpose-oriented category of tools, we describe underlying conceptual principles, highlight interesting applications and discuss limitations. Finally, we will discuss challenges and recommend some guidelines which can help to optimize the process of accurate target discovery.

Diverse ultrastructural landscape of atherosclerotic endothelium

BACKGROUND AND AIMS

The endothelium plays a major role in atherosclerosis, yet the endothelial plaque surface is a largely uncharted territory. Here we hypothesize that atherosclerosis-driven remodeling of the endothelium is a dynamic process, involving both damaging and regenerative mechanisms.

METHODS

Using scanning electron microscopy (SEM) and immuno-SEM, we studied endothelial junction ultrastructure, endothelial openings and immune cell-endothelium interactions in eight apoe^-/- mice and two human carotid plaques.

RESULTS

The surface of early mouse plaques (n = 11) displayed a broad range of morphological alterations, including junctional disruptions and large transcellular endothelial pores with the average diameter between 0.6 and 3 μm. The shoulder region of advanced atherosclerotic lesions (n = 7) had a more aggravated morphology with 8 μm-size paracellular openings at two-fold higher density. In contrast, the central apical surface of advanced plaques, i.e., the plaque body (n = 7), displayed endothelial normalization, as shown by a significantly higher frequency of intact endothelial junctions and a lower incidence of paracellular pores. This normalized endothelial phenotype correlated with low immune cell density (only 5 cells/mm²). The human carotid plaque surface (n = 2) displayed both well-organized and disrupted endothelium with similar features as described above. In addition, they were accompanied by extensive thrombotic areas.

CONCLUSIONS

Our study unveils the spectrum of endothelial abnormalities associated with the development of atherosclerosis. These were highly abundant in early lesions and in the shoulder region of advanced plaques, while normalized at the advanced plaque's body. Similar endothelial features were observed in human atherosclerotic plaques, underlining the versatility of endothelial transformations in atherosclerosis.

Novel Insights into the Prognosis and Immunological Value of the SLC35A (Solute Carrier 35A) Family Genes in Human Breast Cancer

According to statistics 2020, female breast cancer (BRCA) became the most commonly diagnosed malignancy worldwide. Prognosis of BRCA patients is still poor, especially in population with advanced or metastatic. Particular functions of each members of the solute carrier 35A (SLC35A) gene family in human BRCA are still unknown regardless of awareness that they play critical roles in tumorigenesis and progression. Using integrated bioinformatics analyses to identify therapeutic targets for specific cancers based on transcriptomics, proteomics, and high-throughput sequencing, we obtained new information and a better understanding of potential underlying molecular mechanisms. Leveraging BRCA dataset that belongs to The Cancer Genome Atlas (TCGA), which were employed to clarify SLC35A gene expression levels. Then we used a bioinformatics approach to investigate biological processes connected to SLC35A family genes in BRCA development. Beside that, the Kaplan-Meier estimator was leveraged to explore predictive values of SLC35A family genes in BCRA patients. Among individuals of this family gene, expression levels of SLC35A2 were substantially related to poor prognostic values, result from a hazard ratio of 1.3 (with 95 percent confidence interval (95% CI: 1.18-1.44), the p for trend (ptrend) is 3.1 × 10-7). Furthermore, a functional enrichment analysis showed that SLC35A2 was correlated with hypoxia-inducible factor 1A (HIF1A), heat shock protein (HSP), E2 transcription factor (E2F), DNA damage, and cell cycle-related signaling. Infiltration levels observed in specific types of immune cell, especially the cluster of differentiation found on macrophages and neutrophils, were positively linked with SLC35A2 expression in multiple BRCA subclasses (luminal A, luminal B, basal, and human epidermal growth factor receptor 2). Collectively, SLC35A2 expression was associated with a lower recurrence-free survival rate, suggesting that it could be used as a biomarker in treating BRCA.

Prognostic and immune infiltration signatures of proteasome 26S subunit, non-ATPase (PSMD) family genes in breast cancer patients

The complexity of breast cancer includes many interacting biological processes that make it difficult to find appropriate therapeutic treatments. Therefore, identifying potential diagnostic and prognostic biomarkers is urgently needed. Previous studies demonstrated that 26S proteasome delta subunit, non-ATPase (PSMD) family members significantly contribute to the degradation of damaged, misfolded, abnormal, and foreign proteins. However, transcriptional expressions of PSMD family genes in breast cancer still remain largely unexplored. Consequently, we used a holistic bioinformatics approach to explore PSMD genes involved in breast cancer patients by integrating several high-throughput databases, including The Cancer Genome Atlas (TCGA), cBioPortal, Oncomine, and Kaplan-Meier plotter. These data demonstrated that PSMD1, PSMD2, PSMD3, PSMD7, PSMD10, PSMD12, and PSMD14 were expressed at significantly higher levels in breast cancer tissue compared to normal tissues. Notably, the increased expressions of PSMD family genes were correlated with poor prognoses of breast cancer patients, which suggests their roles in tumorigenesis. Meanwhile, network and pathway analyses also indicated that PSMD family genes were positively correlated with ubiquinone metabolism, immune system, and cell-cycle regulatory pathways. Collectively, this study revealed that PSMD family members are potential prognostic biomarkers for breast cancer progression and possible promising clinical therapeutic targets.

Vascular Endothelial Cells: Heterogeneity and Targeting Approaches

Forming the inner layer of the vascular system, endothelial cells (ECs) facilitate a multitude of crucial physiological processes throughout the body. Vascular ECs enable the vessel wall passage of nutrients and diffusion of oxygen from the blood into adjacent cellular structures. ECs regulate vascular tone and blood coagulation as well as adhesion and transmigration of circulating cells. The multitude of EC functions is reflected by tremendous cellular diversity. Vascular ECs can form extremely tight barriers, thereby restricting the passage of xenobiotics or immune cell invasion, whereas, in other organ systems, the endothelial layer is fenestrated (e.g., glomeruli in the kidney), or discontinuous (e.g., liver sinusoids) and less dense to allow for rapid molecular exchange. ECs not only differ between organs or vascular systems, they also change along the vascular tree and specialized subpopulations of ECs can be found within the capillaries of a single organ. Molecular tools that enable selective vascular targeting are helpful to experimentally dissect the role of distinct EC populations, to improve molecular imaging and pave the way for novel treatment options for vascular diseases. This review provides an overview of endothelial diversity and highlights the most successful methods for selective targeting of distinct EC subpopulations.

Potential Therapeutic and Prognostic Values of LSM Family Genes in Breast Cancer

In recent decades, breast cancer (BRCA) has become one of the most common diseases worldwide. Understanding crucial genes and their signaling pathways remain an enormous challenge in evaluating the prognosis and possible therapeutics. The "Like-Smith" (LSM) family is known as protein-coding genes, and its member play pivotal roles in the progression of several malignancies, although their roles in BRCA are less clear. To discover biological processes associated with LSM family genes in BRCA development, high-throughput techniques were applied to clarify expression levels of LSMs in The Cancer Genome Atlas (TCGA)-BRCA dataset, which was integrated with the cBioPortal database. Furthermore, we investigated prognostic values of LSM family genes in BCRA patients using the Kaplan-Meier database. Among genes of this family, LSM4 expression levels were highly associated with poor prognostic outcomes with a hazard ratio of 1.35 (95% confidence interval 1.21-1.51, p for trend = 3.4 × 10-7). MetaCore and GlueGo analyses were also conducted to examine transcript expression signatures of LSM family members and their coexpressed genes, together with their associated signaling pathways, such as "Cell cycle role of APC in cell cycle regulation" and "Immune response IL-15 signaling via MAPK and PI3K cascade" in BRCA. Results showed that LSM family members, specifically LSM4, were significantly correlated with oncogenesis in BRCA patients. In summary, our results suggested that LSM4 could be a prospective prognosticator of BRCA.

Single-cell evaluation reveals shifts in the tumor-immune niches that shape and maintain aggressive lesions in the breast

There is an unmet clinical need for stratification of breast lesions as indolent or aggressive to tailor treatment. Here, single-cell transcriptomics and multiparametric imaging applied to a mouse model of breast cancer reveals that the aggressive tumor niche is characterized by an expanded basal-like population, specialization of tumor subpopulations, and mixed-lineage tumor cells potentially serving as a transition state between luminal and basal phenotypes. Despite vast tumor cell-intrinsic differences, aggressive and indolent tumor cells are functionally indistinguishable once isolated from their local niche, suggesting a role for non-tumor collaborators in determining aggressiveness. Aggressive lesions harbor fewer total but more suppressed-like T cells, and elevated tumor-promoting neutrophils and IL-17 signaling, disruption of which increase tumor latency and reduce the number of aggressive lesions. Our study provides insight into tumor-immune features distinguishing indolent from aggressive lesions, identifies heterogeneous populations comprising these lesions, and supports a role for IL-17 signaling in aggressive progression.

Prognoses and genomic analyses of proteasome 26S subunit, ATPase (PSMC) family genes in clinical breast cancer

Breast cancer is a complex disease, and several processes are involved in its development. Therefore, potential therapeutic targets need to be discovered for these patients. Proteasome 26S subunit, ATPase gene (PSMC) family members are well reported to be involved in protein degradation. However, their roles in breast cancer are still unknown and need to be comprehensively researched. Leveraging publicly available databases, such as cBioPortal and Oncomine, for high-throughput transcriptomic profiling to provide evidence-based targets for breast cancer is a rapid and robust approach. By integrating the aforementioned databases with the Kaplan–Meier plotter database, we investigated potential roles of six PSMC family members in breast cancer at the messenger RNA level and their correlations with patient survival. The present findings showed significantly higher expression profiles of PSMC2, PSMC3, PSMC4, PSMC5, and PSMC6 in breast cancer compared to normal breast tissues. Besides, positive correlations were also revealed between PSMC family genes and ubiquinone metabolism, cell cycle, and cytoskeletal remodeling. Meanwhile, we discovered that high levels of PSMC1, PSMC3, PSMC4, PSMC5, and PSMC6 transcripts were positively correlated with poor survival, which likely shows their importance in breast cancer development. Collectively, PSMC family members have the potential to be novel and essential prognostic biomarkers for breast cancer development.

Single-cell RNA sequencing in human lung cancer: Applications, challenges, and pathway towards personalized therapy

Lung cancer is one of the most prevalent human cancers, and single-cell RNA sequencing (scRNA-seq) has been widely used to study human lung cancer at the cellular, genetic, and molecular level. Even though there are published reviews, which summarized the applications of scRNA-seq in human cancers like breast cancer, there is lack of a comprehensive review, which could effectively highlight the broad use of scRNA-seq in studying lung cancer. This review, therefore, was aimed to summarize the various applications of scRNA-seq in human lung cancer research based on the findings from different published in vitro, in vivo, and clinical studies. The review would first briefly outline the concept and principle of scRNA-seq, followed by the discussion on the applications of scRNA-seq in studying human lung cancer. Finally, the challenges faced when using scRNA-seq to study human lung cancer would be discussed, and the potential applications and challenges of scRNA-seq to facilitate the development of personalized cancer therapy in the future would be explored.

Endothelial cell plasticity at the single-cell level

The vascular endothelium is characterized by a remarkable level of plasticity, which is the driving force not only of physiological repair/remodeling of adult tissues but also of pathological angiogenesis. The resulting heterogeneity of endothelial cells (ECs) makes targeting the endothelium challenging, no less because many EC phenotypes are yet to be identified and functionally inventorized. Efforts to map the vasculature at the single-cell level have been instrumental to capture the diversity of EC types and states at a remarkable depth in both normal and pathological states. Here, we discuss new EC subtypes and functions emerging from recent single-cell studies in health and disease. Interestingly, such studies revealed distinct metabolic gene signatures in different EC phenotypes, which deserve further consideration for therapy. We highlight how this metabolic targeting strategy could potentially be used to promote (for tissue repair) or block (in tumor) angiogenesis in a tissue or even vascular bed-specific manner.

Analysis of LAGEs Family Gene Signature and Prognostic Relevance in Breast Cancer

Breast cancer (BRCA) is one of the most complex diseases and involves several biological processes. Members of the L-antigen (LAGE) family participate in the development of various cancers, but their expressions and prognostic values in breast cancer remain to be clarified. High-throughput methods for exploring disease progression mechanisms might play a pivotal role in the improvement of novel therapeutics. Therefore, gene expression profiles and clinical data of LAGE family members were acquired from the cBioportal database, followed by verification using the Oncomine and The Cancer Genome Atlas (TCGA) databases. In addition, the Kaplan-Meier method was applied to explore correlations between expressions of LAGE family members and prognoses of breast cancer patients. MetaCore, GlueGo, and GluePedia were used to comprehensively study the transcript expression signatures of LAGEs and their co-expressed genes together with LAGE-related signal transduction pathways in BRCA. The result indicated that higher LAGE3 messenger (m)RNA expressions were observed in BRCA tissues than in normal tissues, and they were also associated with the stage of BRCA patients. Kaplan-Meier plots showed that overexpression of LAGE1, LAGE2A, LAGE2B, and LAGE3 were highly correlated to poor survival in most types of breast cancer. Significant associations of LAGE family genes were correlated with the cell cycle, focal adhesion, and extracellular matrix (ECM) receptor interactions as indicated by functional enrichment analyses. Collectively, LAGE family members’ gene expression levels were related to adverse clinicopathological factors and prognoses of BRCA patients; therefore, LAGEs have the potential to serve as prognosticators of BRCA patients.

Novel signaling pathways regulate SARS-CoV and SARS-CoV-2 infectious disease

Severe acute respiratory syndrome coronavirus (SARS-CoV)-2 induces severe infection, and it is responsible for a worldwide disease outbreak starting in late 2019. Currently, there are no effective medications against coronavirus. In the present study, we utilized a holistic bioinformatics approach to study gene signatures of SARS-CoV- and SARS-CoV-2-infected Calu-3 lung adenocarcinoma cells. Through the Gene Ontology platform, we determined that several cytokine genes were up-regulated after SARS-CoV-2 infection, including TNF, IL6, CSF2, IFNL1, IL-17C, CXCL10, and CXCL11. Differentially regulated pathways were detected by the Kyoto Encyclopedia of Genes and Genomes, gene ontology, and Hallmark platform, including chemokines, cytokines, cytokine receptors, cytokine metabolism, inflammation, immune responses, and cellular responses to the virus. A Venn diagram was utilized to illustrate common overlapping genes from SARS-CoV- and SARS-CoV-2-infected datasets. An Ingenuity pathway analysis discovered an enrichment of tumor necrosis factor- (TNF-) and interleukin (IL)-17-related signaling in a gene set enrichment analysis. Downstream networks were predicted by the Database for Annotation, Visualization, and Integrated Discovery platform also revealed that TNF and TNF receptor 2 signaling elicited leukocyte recruitment, activation, and survival of host cells after coronavirus infection. Our discovery provides essential evidence for transcript regulation and downstream signaling of SARS-CoV and SARS-CoV-2 infection.

CCDC167 as a potential therapeutic target and regulator of cell cycle-related networks in breast cancer

According to cancer statistics reported in 2020, breast cancer constitutes 30% of new cancer cases diagnosed in American women. Histological markers of breast cancer are expressions of the estrogen receptor (ER), the progesterone receptor (PR), and human epidermal growth factor receptor (HER)-2. Up to 80% of breast cancers are grouped as ER-positive, which implies a crucial role for estrogen in breast cancer development. Therefore, identifying potential therapeutic targets and investigating their downstream pathways and networks are extremely important for drug development in these patients. Through high-throughput technology and bioinformatics screening, we revealed that coiled-coil domain-containing protein 167 (CCDC167) was upregulated in different types of tumors; however, the role of CCDC167 in the development of breast cancer still remains unclear. Integrating many kinds of databases including ONCOMINE, MetaCore, IPA, and Kaplan-Meier Plotter, we found that high expression levels of CCDC167 predicted poor prognoses of breast cancer patients. Knockdown of CCDC167 attenuated aggressive breast cancer growth and proliferation. We also demonstrated that treatment with fluorouracil, carboplatin, paclitaxel, and doxorubicin resulted in decreased expression of CCDC167 and suppressed growth of MCF-7 cells. Collectively, these findings suggest that CCDC167 has high potential as a therapeutic target for breast cancer.

Severe acute respiratory syndrome coronavirus (SARS-CoV)-2 infection induces dysregulation of immunity: in silico gene expression analysis

Highly pathogenic coronaviruses (CoVs) induce acute respiratory distress syndrome, and the severe acute respiratory syndrome coronavirus (SARS-CoV)-2 has caused a pandemic since late 2019. The diversity of clinical manifestations after SARS-CoV-2 infection results in great challenges to diagnose CoV disease 2019 (COVID-19). There is a growing body of published research on this topic; however, effective medications are still undergoing a long process of being assessed. In the search for potential genetic targets for this infection, we applied a holistic bioinformatics approach to study alterations of gene signatures between SARS-CoV-2-infected cells and mock-infected controls. Two different kinds of lung epithelial cells, A549 with angiotensin-converting enzyme 2 (ACE2) overexpression and normal human bronchial epithelial (NHBE) cells, were infected with SARS-CoV-2. We performed bioinformatics analyses of RNA-sequencing in this study. Through a Venn diagram, Database for Annotation, Visualization and Integrated Discovery, Gene Ontology, Ingenuity Pathway Analysis, and Gene Set Enrichment Analysis, the pathways and networks were constructed from commonly upregulated genes in SARS-CoV-2-infected lung epithelial cells. Genes associated with immune-related pathways, responses of host cells after intracellular infection, steroid hormone biosynthesis, receptor signaling, and the complement system were enriched. Dysregulation of the immune system and malfunction of interferon contribute to a failure to kill SARS-CoV-2 and exacerbate respiratory distress in severely ill patients. Current findings from this study provide a comprehensive investigation of SARS-CoV-2 infection using high-throughput technology.

Upregulation of peroxisome proliferator-activated receptor-α and the lipid metabolism pathway promotes carcinogenesis of ampullary cancer

Ampullary cancer is a rare periampullary cancer currently with no targeted therapeutic agent. It is important to develop a deeper understanding of the carcinogenesis of ampullary cancer. We attempted to explore the characteristics of ampullary cancer in our dataset and a public database, followed by a search for potential drugs. We used a bioinformatics pipeline to analyze complementary (c)DNA microarray data of ampullary cancer and surrounding normal duodenal tissues from five patients. A public database from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) was applied for external validation. Bioinformatics tools used included the Gene Set Enrichment Analysis (GSEA), Database for Annotation, Visualization and Integrated Discovery (DAVID), MetaCore, Kyoto Encyclopedia of Genes and Genomes (KEGG), Hallmark, BioCarta, Reactome, and Connectivity Map (CMap). In total, 9097 genes were upregulated in the five ampullary cancer samples compared to normal duodenal tissues. From the MetaCore analysis, genes of peroxisome proliferator-activated receptor alpha (PPARA) and retinoid X receptor (RXR)-regulated lipid metabolism were overexpressed in ampullary cancer tissues. Further a GSEA of the KEGG, Hallmark, Reactome, and Gene Ontology databases revealed that PPARA and lipid metabolism-related genes were enriched in our specimens of ampullary cancer and in the NCBI GSE39409 database. Expressions of PPARA messenger (m)RNA and the PPAR-α protein were higher in clinical samples and cell lines of ampullary cancer. US Food and Drug Administration (FDA)-approved drugs, including alvespimycin, trichostatin A (a histone deacetylase inhibitor), and cytochalasin B, may have novel therapeutic effects in ampullary cancer patients as predicted by the CMap analysis. Trichostatin A was the most potent agent for ampullary cancer with a half maximal inhibitory concentration of < 0.3 μM. According to our results, upregulation of PPARA and lipid metabolism-related genes are potential pathways in the carcinogenesis and development of ampullary cancer. Results from the CMap analysis suggested potential drugs for patients with ampullary cancer.

Vascular Heterogeneity With a Special Focus on the Hepatic Microenvironment

Utilizing single-cell sequencing, recent studies were able to analyze at a greater resolution the heterogeneity of the vasculature and its complex composition in different tissues. Differing subpopulations have been detected, distinguishable only by their transcriptome. Designed to provide further insight into the heterogeneity of the functional vascular tissue, endothelial cells have been the main target of those studies. This review aims to present a synopsis of the variability of the different vascular beds, their endothelial variety, and the supporting cells that allow the vessels to serve their various purposes. Firstly, we are going to chart vascular tissue heterogeneity on a cellular level, describing endothelial diversity as well as stromal microenvironmental variety and interaction in a physiological setting. Secondly, we will summarize the current knowledge of pathological vessel formation in the context of cancer. Conventional anti-tumor therapeutic targets as well as anti-angiogenetic therapy is frequently limited by poor response of the tumor tissue. Reasons for moderate response and resistance to treatment can be found through different drivers of angiogenesis, different mechanisms of blood supply, but also in poorly understood tissue diversity. Based on this, we are comparing how pathologies alter the normal structure of vascular tissues highlighting the involved mechanisms. Lastly, illustrating the concept above, we will focus on the hepatic microenvironment, an organ of frequent metastatic spreading (e.g., from colorectal, breast, and lung cancers). We will address how the hepatic vasculature usually develops and subsequently we will describe how common liver metastases vary in their vasculature and the way they supply themselves (e.g., angiogenesis versus vessel co-option).

Identification of the key gene and pathways associated with osteoarthritis via single-cell RNA sequencing on synovial fibroblasts

Osteoarthritis (OA) is a chronic degenerative joint disease with its onset closely related to the growth of synovial fibroblasts (SFs), yet the genes involved in are few reported. In our study, we aimed to identify the OA-associated key gene and pathways via the single-cell RNA sequencing (scRNA-seq) analysis on SFs.scRNA-seq data of SFs from OA sufferers were accessed from GEO database, then the genes involved in were subjected to principal component analysis (PCA) and T-Stochastic Neighbor Embedding (TSNE) Analysis. GO and KEGG enrichment analyses were performed to find the most enriched functions and pathways associated with marker genes and a PPI network was constructed to identify the key gene associated with OA occurrence.Findings revealed that marker genes in three cell types identified by TSNE were mainly activated in pathways firmly related to fibroblasts growth, such as extracellular matrix, immune and cell adhesion molecule binding-associated functions and pathways. Moreover, fibronectin1 (FN1) was validated as the key gene that was tightly related to the growth of SFs, as well as had the potential to play a key role in OA occurrence.Our study explored the key gene and pathways associated with OA occurrence, which were of great value in further investigation of OA diagnosis as well as pathogenesis.

Understanding angiodiversity: insights from single cell biology

Blood vessels have long been considered as passive conduits for delivering blood. However, in recent years, cells of the vessel wall (endothelial cells, smooth muscle cells and pericytes) have emerged as active, highly dynamic components that orchestrate crosstalk between the circulation and organs. Encompassing the whole body and being specialized to the needs of distinct organs, it is not surprising that vessel lining cells come in different flavours. There is calibre-specific specialization (arteries, arterioles, capillaries, venules, veins), but also organ-specific heterogeneity in different microvascular beds (continuous, discontinuous, sinusoidal). Recent technical advances in the field of single cell biology have enabled the profiling of thousands of single cells and, hence, have allowed for the molecular dissection of such angiodiversity, yielding a hitherto unparalleled level of spatial and functional resolution. Here, we review how these approaches have contributed to our understanding of angiodiversity.

Single-Cell Transcriptional Profiling of Aortic Endothelium Identifies a Hierarchy from Endovascular Progenitors to Differentiated Cells

The cellular and molecular profiles that govern the endothelial heterogeneity of the circulatory system have yet to be elucidated. Using a data-driven approach to study the endothelial compartment via single-cell RNA sequencing, we characterized cell subpopulations within and assigned them to a defined endothelial hierarchy. We show that two transcriptionally distinct endothelial populations exist within the aorta and, using two independent trajectory analysis methods, confirm that they represent transitioning cells rather than discrete cell types. Gene co-expression analysis revealed crucial regulatory networks underlying each population, including significant metabolic gene networks in progenitor cells. Using mitochondrial activity assays and phenotyping, we confirm that endovascular progenitors display higher mitochondrial content compared to differentiated endothelial cells. The identities of these populations were further validated against bulk RNA sequencing (RNA-seq) data obtained from normal and tumor-derived vasculature. Our findings validate the heterogeneity of the aortic endothelium and previously suggested hierarchy between progenitor and differentiated cells.

DECENT: differential expression with capture efficiency adjustmeNT for single-cell RNA-seq data

Motivation

Dropout is a common phenomenon in single-cell RNA-seq (scRNA-seq) data, and when left unaddressed it affects the validity of the statistical analyses. Despite this, few current methods for differential expression (DE) analysis of scRNA-seq data explicitly model the process that gives rise to the dropout events. We develop DECENT, a method for DE analysis of scRNA-seq data that explicitly and accurately models the molecule capture process in scRNA-seq experiments.

Results

We show that DECENT demonstrates improved DE performance over existing DE methods that do not explicitly model dropout. This improvement is consistently observed across several public scRNA-seq datasets generated using different technological platforms. The gain in improvement is especially large when the capture process is overdispersed. DECENT maintains type I error well while achieving better sensitivity. Its performance without spike-ins is almost as good as when spike-ins are used to calibrate the capture model.

Availability and implementation

The method is implemented as a publicly available R package available from https://github.com/cz-ye/DECENT.

Supplementary information

Supplementary data are available at Bioinformatics online.

Modulation of the tumor microenvironment by natural agents: implications for cancer prevention and therapy

The development of cancer is not just the growth and proliferation of a single transformed cell, but its surrounding environment also coevolves with it. Indeed, successful cancer progression depends on the ability of the tumor cells to develop a supportive tumor microenvironment consisting of various types of stromal cells. The interactions between the tumor and stromal cells are bidirectional and mediated through a variety of growth factors, cytokines, metabolites, and other biomolecules secreted by these cells. Tumor-stromal crosstalk creates optimal conditions for the tumor growth, metastasis, evasion of immune surveillance, and therapy resistance, and its targeting is being explored for clinical management of cancer. Natural agents from plants and marine life have been at the forefront of traditional medicine. Numerous epidemiological studies have reported the health benefits imparted on the consumption of certain fruits, vegetables, and their derived products. Indeed, a significant majority of anti-cancer drugs in clinical use are either naturally occurring compounds or their derivatives. In this review, we describe fundamental cellular and non-cellular components of the tumor microenvironment and discuss the significance of natural compounds in their targeting. Existing literature provides hope that novel prevention and therapeutic approaches will emerge from ongoing scientific efforts leading to the reduced tumor burden and improve clinical outcomes in cancer patients.

Dimension Reduction and Clustering Models for Single-Cell RNA Sequencing Data: A Comparative Study

With recent advances in single-cell RNA sequencing, enormous transcriptome datasets have been generated. These datasets have furthered our understanding of cellular heterogeneity and its underlying mechanisms in homogeneous populations. Single-cell RNA sequencing (scRNA-seq) data clustering can group cells belonging to the same cell type based on patterns embedded in gene expression. However, scRNA-seq data are high-dimensional, noisy, and sparse, owing to the limitation of existing scRNA-seq technologies. Traditional clustering methods are not effective and efficient for high-dimensional and sparse matrix computations. Therefore, several dimension reduction methods have been introduced. To validate a reliable and standard research routine, we conducted a comprehensive review and evaluation of four classical dimension reduction methods and five clustering models. Four experiments were progressively performed on two large scRNA-seq datasets using 20 models. Results showed that the feature selection method contributed positively to high-dimensional and sparse scRNA-seq data. Moreover, feature-extraction methods were able to promote clustering performance, although this was not eternally immutable. Independent component analysis (ICA) performed well in those small compressed feature spaces, whereas principal component analysis was steadier than all the other feature-extraction methods. In addition, ICA was not ideal for fuzzy C-means clustering in scRNA-seq data analysis. K-means clustering was combined with feature-extraction methods to achieve good results.

Single Cell Sequencing in Cancer Diagnostics

Personalized medicine has been driven by improvements in genomic sequencing and analysis. For several diseases, in particular cancers, it has for nearly a decade been standard clinical practice to analyze the genome and expression of the genes of patients. The results are reflected directly in the treatment plan for the patient, in targeted medical inventions. This specialized mode of diagnostics has been restricted to account for averaged trends in the tumor. The approach sharply contrasts our knowledge on heterogeneity within tumors. Several studies further describe how treatment against one tumor subclone in some cases merely serves to provide space and support for uncontrolled growth of more aggressive subclones. In this chapter, we describe current possibilities for implementation of single cell sequencing of malignomas in clinic, as well as discuss hands-on practical advice for single cell routine diagnostics that allows for full delineation of tumor clonality.

Gene signatures and potential therapeutic targets of amino acid metabolism in estrogen receptor-positive breast cancer

Increased activity of amino acid transporters has been observed in a wide variety of cancers. However, whether amino acid metabolism is related to estrogen receptor-positive (ER⁺) breast cancer has been less well studied. We identified the rate-limiting enzyme involved in amino acid metabolism associated with ER⁺ breast cancer by integrating numerous bioinformatics tools and laboratory studies. The bioinformatics analysis revealed that highly expressed genes in ER⁺ breast cancer patients were correlated with breast cancer-related pathways, including ESR1 and PI3K signaling. The metabolic signaling and the amino acid metabolism were significantly regulated in breast neoplasms. We used the ER⁺ breast cancer cell line MCF-7 and breast cancer tissue from National Cheng Kung University Hospital to validate our findings in bioinformatics. In estradiol-treated MCF-7 cells, genes associated with anabolic metabolism of serine and methionine and genes associated with catabolic metabolism of tyrosine, phenylalanine and arginine were upregulated. Furthermore, the expression levels of ARG2, PSAT1, PSPH, TH, PAH, and MAT1A mRNA were increased in breast cancer patients relative to controls. The aforementioned genes were also found to be highly correlated with distant metastasis-free survival in breast cancer patients. High expression levels of ARG2, CBS, PHGDH, AHCY, HAL, TDO2, SHMT2, MAT1A, MAT2A, GLDC, GLS2, BCAT2, GLUD1, PAH and MTR contributed to poor prognoses, whereas high mRNA expression levels of HECA, CTH, PRODH, TAT, and MAT2B were correlated with good prognoses. FDA-approved drugs, including piperlongumine, ellipticine, etidronic acid, harmine, and meclozine, may have novel therapeutic effects in ER⁺ patients based on connectivity map (CMap) analyses. Collectively, our present study demonstrated that amino acid metabolism genes play crucial roles in tumor development and may serve as prospective drug targets or biomarkers for ER⁺ breast cancer.

Mutation of the PTCH1 gene predicts recurrence of breast cancer

Breast cancer is the most common cancer in women, and some patients develop recurrence after standard therapy. Effective predictors are urgently needed to detect recurrence earlier. The activation of Hedgehog signaling in breast cancer is correlated with poor prognosis. PTCH1 is an essential membrane receptor of Hedgehog. However, there are few reports about mutations in Hedgehog genes in breast cancer. We conducted a comprehensive study via an experimental and bioinformatics approach to detect mutated genes in breast cancer. Twenty-two breast cancer patients who developed recurrence within 24 months postoperatively were enrolled with 22 control cancer patients. Targeted deep sequencing was performed to assess the mutations among individuals with breast cancer using a panel of 143 cancer-associated genes. Bioinformatics and public databases were used to predict the protein functions of the mutated genes. Mutations were identified in 44 breast cancer specimens, and the most frequently mutated genes were BRCA2, APC, ATM, BRCA1, NF1, TET2, TSC1, TSC2, NOTCH1, MSH2, PTCH1, TP53, PIK3CA, FBXW7, and RB1. Mutation of these genes was correlated with protein phosphorylation and autophosphorylation, such as peptidyl-tyrosine and protein kinase C phosphorylation. Among these highly mutated genes, mutations of PTCH1 were associated with poor prognosis and increased recurrence of breast cancer, especially mutations in exons 22 and 23. The public sequencing data from the COSMIC database were exploited to predict the functions of the mutations. Our findings suggest that mutation of PTCH1 is correlated with early recurrence of breast cancer patients and will become a powerful predictor for recurrence of breast cancer.

Applications of single cell RNA sequencing to research of stem cells

Stem cells (SCs) with their self-renewal and pluripotent differentiation potential, show great promise for therapeutic applications to some refractory diseases such as stroke, Parkinsonism, myocardial infarction, and diabetes. Furthermore, as seed cells in tissue engineering, SCs have been applied widely to tissue and organ regeneration. However, previous studies have shown that SCs are heterogeneous and consist of many cell subpopulations. Owing to this heterogeneity of cell states, gene expression is highly diverse between cells even within a single tissue, making precise identification and analysis of biological properties difficult, which hinders their further research and applications. Therefore, a defined understanding of the heterogeneity is a key to research of SCs. Traditional ensemble-based sequencing approaches, such as microarrays, reflect an average of expression levels across a large population, which overlook unique biological behaviors of individual cells, conceal cell-to-cell variations, and cannot understand the heterogeneity of SCs radically. The development of high throughput single cell RNA sequencing (scRNA-seq) has provided a new research tool in biology, ranging from identification of novel cell types and exploration of cell markers to the analysis of gene expression and predicating developmental trajectories. scRNA-seq has profoundly changed our understanding of a series of biological phenomena. Currently, it has been used in research of SCs in many fields, particularly for the research of heterogeneity and cell subpopulations in early embryonic development. In this review, we focus on the scRNA-seq technique and its applications to research of SCs.

Role of the Microenvironment in Regulating Normal and Cancer Stem Cell Activity: Implications for Breast Cancer Progression and Therapy Response

The epithelial cells in an adult woman’s breast tissue are continuously replaced throughout their reproductive life during pregnancy and estrus cycles. Such extensive epithelial cell turnover is governed by the primitive mammary stem cells (MaSCs) that proliferate and differentiate into bipotential and lineage-restricted progenitors that ultimately generate the mature breast epithelial cells. These cellular processes are orchestrated by tightly-regulated paracrine signals and crosstalk between breast epithelial cells and their tissue microenvironment. However, current evidence suggests that alterations to the communication between MaSCs, epithelial progenitors and their microenvironment plays an important role in breast carcinogenesis. In this article, we review the current knowledge regarding the role of the breast tissue microenvironment in regulating the special functions of normal and cancer stem cells. Understanding the crosstalk between MaSCs and their microenvironment will provide new insights into how an altered breast tissue microenvironment could contribute to breast cancer development, progression and therapy response and the implications of this for the development of novel therapeutic strategies to target cancer stem cells.

Emerging approaches and technologies in transplantation: the potential game changers

Newly emerging technologies are rapidly changing conventional approaches to organ transplantation. In the modern era, the key challenges to transplantation include (1) how to best individualize and possibly eliminate the need for life-long immunosuppression and (2) how to expand the donor pool suitable for human transplantation. This article aims to provide readers with an updated review of three new technologies that address these challenges. First, single-cell RNA sequencing technology is rapidly evolving and has recently been employed in settings related to transplantation. The new sequencing data indicate an unprecedented cellular heterogeneity within organ transplants, as well as exciting new molecular signatures involved in alloimmune responses. Second, sophisticated nanotechnology platforms provide a means of therapeutically delivering immune modulating reagents to promote transplant tolerance. Tolerogenic nanoparticles with regulatory molecules and donor antigens are capable of targeting host immune responses with tremendous precision, which, in some cases, results in donor-specific tolerance. Third, CRISPR/Cas9 gene editing technology has the potential to precisely remove immunogenic molecules while inserting desirable regulatory molecules. This technology is particularly useful in generating genetically modified pigs for xenotransplantation to solve the issue of the shortage of human organs. Collectively, these new technologies are positioning the transplant community for major breakthroughs that will significantly advance transplant medicine.

Support of Tumor Endothelial Cells by Chemokine Receptors

Tumor-associated vascular endothelium comprises a specialized and diverse group of endothelial cells that, although not cancer themselves, are integral to cancer progression. Targeting the tumor vasculature can have significant efficacy in reducing tumor burden, although loss of efficacy due to acquisition of resistance mechanisms is common. Here we review mechanisms by which tumor endothelial cells (TEC) utilize chemokine receptors to support tumor progression. We illustrate how chemokine receptors support and may serve as functional markers of the diverse TEC population. We focus on ACKR1 (DARC), ACKR3 (CXCR7), CXCR4, and CCR2, as these are the best studied chemokine receptors in TEC; and suggest that targeting these receptors on the tumor vasculature may prove efficacious in slowing or reversing tumor growth. We also mention CXCR2 and CXCR3 as important mediators or tumor angiogenesis, given their distinct roles with angiogenic and angiostatic chemokines, respectively.

An Introduction to the Analysis of Single-Cell RNA-Sequencing Data

The recent development of single-cell RNA sequencing has deepened our understanding of the cell as a functional unit, providing new insights based on gene expression profiles of hundreds to hundreds of thousands of individual cells, and revealing new populations of cells with distinct gene expression profiles previously hidden within analyses of gene expression performed on bulk cell populations. However, appropriate analysis and utilization of the massive amounts of data generated from single-cell RNA sequencing experiments are challenging and require an understanding of the experimental and computational pathways taken between preparation of input cells and output of interpretable data. In this review, we will discuss the basic principles of these new technologies, focusing on concepts important in the analysis of single-cell RNA-sequencing data. Specifically, we summarize approaches to quality-control measures for determination of which single cells to include for further examination, methods of data normalization and scaling to overcome the relatively inefficient capture rate of mRNA from each cell, and clustering and visualization algorithms used for dimensional reduction of the data to a two-dimensional plot.