Transcriptome analysis of MCF-7 breast cancer cell population to reveal the transcriptional diversity at the single cell level
Ontology highlight
ABSTRACT: We constructed four single cell transcriptome (SCT) libraries from MCF-7 breast cancer cells and characterized their transcriptome profiles using the expression of 143 housekeeping genes as a control.
Project description:We constructed four single cell transcriptome (SCT) libraries from MCF-7 breast cancer cells and characterized their transcriptome profiles using the expression of 143 housekeeping genes as a control.
Project description:Esophageal squamous cell carcinoma (ESCC) is a tumor composed of heterogeneous cells that easily become radioresistant, which leads to tumor recurrence. The most commonly used treatment for ESCC is fractionated irradiation (FIR) therapy that utilizes ionizing radiation to directly induce cytotoxic cell death. However, this treatment may not be able to eliminate all cancer cells due to high adaptive evolution. To determine whether the transcriptome dynamics during ESCC recurrence formation are associated with FIR response, an in vitro cell culture model for ESCC radioresistance that mimics the common radiotherapy process in patients with ESCC was established in the present study. High‑throughput sequencing analysis of in vitro cultured ESCC cells was performed using different cumulative irradiation doses, as well as tumor samples from FIR‑treated patients with ESCC before and after the development of radioresistance. Radioresistance‑associated genes and signaling pathways that were aberrantly expressed in radioresistant ESCC cells were identified, including autophagy‑related 9B (regulation of autophagy), DNA damage‑inducible transcript 4, myoglobin and plasminogen activator tissue type, which are associated with response to hypoxia, Bcl2‑binding component 3, tumor protein P63 and interferon γ‑inducible protein 16, which are associated with DNA damage response. The heterogeneity and dynamic gene expression of ESCC cells during acquired radioresistance were further studied in primary (41 single cells), 12 Gy FIR‑treated (87 single cells) and 30 Gy FIR‑treated (89 single cells) cancer cells using a single‑cell RNA sequencing approach. The results of the present study comprehensively characterized the transcriptome dynamics during acquired radioresistance in an in vitro model of ESCC and patient tumor samples at the population and single cell level. Single‑cell RNA sequencing revealed the heterogeneity of irradiated ESCC cells and an increase in the radioresistant ESCC cell subpopulation during acquired radioresistance. Overall, these results are of potential clinical relevance as they identify a number of signaling molecules associated with radioresistance, as well as opportunities for the development of novel therapeutic options for the treatment of ESCC.
Project description:The human brain is a tissue of vast complexity in terms of the cell types it comprises. Conventional approaches to classifying cell types in the human brain at single cell resolution have been limited to exploring relatively few markers and therefore have provided a limited molecular characterization of any given cell type. We used single cell RNA sequencing on 466 cells to capture the cellular complexity of the adult and fetal human brain at a whole transcriptome level. Healthy adult temporal lobe tissue was obtained during surgical procedures where otherwise normal tissue was removed to gain access to deeper hippocampal pathology in patients with medical refractory seizures. We were able to classify individual cells into all of the major neuronal, glial, and vascular cell types in the brain. We were able to divide neurons into individual communities and show that these communities preserve the categorization of interneuron subtypes that is typically observed with the use of classic interneuron markers. We then used single cell RNA sequencing on fetal human cortical neurons to identify genes that are differentially expressed between fetal and adult neurons and those genes that display an expression gradient that reflects the transition between replicating and quiescent fetal neuronal populations. Finally, we observed the expression of major histocompatibility complex type I genes in a subset of adult neurons, but not fetal neurons. The work presented here demonstrates the applicability of single cell RNA sequencing on the study of the adult human brain and constitutes a first step toward a comprehensive cellular atlas of the human brain.
Project description:An emerging view regarding cancer metabolism is that it is heterogeneous and context-specific, but it remains to be elucidated in breast cancers. In this study, we characterized the energy-related metabolic features of breast cancers through integrative analyses of multiple datasets with genomics, transcriptomics, metabolomics, and single-cell transcriptome profiling. Energy-related metabolic signatures were used to stratify breast tumors into two prognostic clusters: cluster 1 exhibits high glycolytic activity and decreased survival rate, and the signatures of cluster 2 are enriched in fatty acid oxidation and glutaminolysis. The intertumoral metabolic heterogeneity was reflected by the clustering among three independent large cohorts, and the complexity was further verified at the metabolite level. In addition, we found that the metabolic status of malignant cells rather than that of nonmalignant cells is the major contributor at the single-cell resolution, and its interactions with factors derived from the tumor microenvironment are unanticipated. Notably, among various immune cells and their clusters with distinguishable metabolic features, those with immunosuppressive function presented higher metabolic activities. Collectively, we uncovered the heterogeneity in energy metabolism using a classifier with prognostic and therapeutic value. Single-cell transcriptome profiling provided novel metabolic insights that could ultimately tailor therapeutic strategies based on patient- or cell type-specific cancer metabolism.
Project description:We used single cell RNA sequencing on 466 cells to capture the cellular complexity of the adult and fetal human brain at a whole transcriptome level. Healthy adult temporal lobe tissue was obtained from epileptic patients during temporal lobectomy for medically refractory seizures. We were able to classify individual cells into all of the major neuronal, glial, and vascular cell types in the brain. Examination of cell types in healthy human brain samples.
Project description:The somatosensory nervous system is critical for the organism's ability to respond to mechanical, thermal, and nociceptive stimuli. Somatosensory neurons are functionally and anatomically diverse but their molecular profiles are not well-defined. Here, we used transcriptional profiling to analyze the detailed molecular signatures of dorsal root ganglion (DRG) sensory neurons. We used two mouse reporter lines and surface IB4 labeling to purify three major non-overlapping classes of neurons: 1) IB4(+)SNS-Cre/TdTomato(+), 2) IB4(-)SNS-Cre/TdTomato(+), and 3) Parv-Cre/TdTomato(+) cells, encompassing the majority of nociceptive, pruriceptive, and proprioceptive neurons. These neurons displayed distinct expression patterns of ion channels, transcription factors, and GPCRs. Highly parallel qRT-PCR analysis of 334 single neurons selected by membership of the three populations demonstrated further diversity, with unbiased clustering analysis identifying six distinct subgroups. These data significantly increase our knowledge of the molecular identities of known DRG populations and uncover potentially novel subsets, revealing the complexity and diversity of those neurons underlying somatosensation.
Project description:BackgroundTo improve cancer therapy, it is critical to target metastasizing cells. Circulating tumor cells (CTCs) are rare cells found in the blood of patients with solid tumors and may play a key role in cancer dissemination. Uncovering CTC phenotypes offers a potential avenue to inform treatment. However, CTC transcriptional profiling is limited by leukocyte contamination; an approach to surmount this problem is single cell analysis. Here we demonstrate feasibility of performing high dimensional single CTC profiling, providing early insight into CTC heterogeneity and allowing comparisons to breast cancer cell lines widely used for drug discovery.Methodology/principal findingsWe purified CTCs using the MagSweeper, an immunomagnetic enrichment device that isolates live tumor cells from unfractionated blood. CTCs that met stringent criteria for further analysis were obtained from 70% (14/20) of primary and 70% (21/30) of metastatic breast cancer patients; none were captured from patients with non-epithelial cancer (n = 20) or healthy subjects (n = 25). Microfluidic-based single cell transcriptional profiling of 87 cancer-associated and reference genes showed heterogeneity among individual CTCs, separating them into two major subgroups, based on 31 highly expressed genes. In contrast, single cells from seven breast cancer cell lines were tightly clustered together by sample ID and ER status. CTC profiles were distinct from those of cancer cell lines, questioning the suitability of such lines for drug discovery efforts for late stage cancer therapy.Conclusions/significanceFor the first time, we directly measured high dimensional gene expression in individual CTCs without the common practice of pooling such cells. Elevated transcript levels of genes associated with metastasis NPTN, S100A4, S100A9, and with epithelial mesenchymal transition: VIM, TGFß1, ZEB2, FOXC1, CXCR4, were striking compared to cell lines. Our findings demonstrate that profiling CTCs on a cell-by-cell basis is possible and may facilitate the application of 'liquid biopsies' to better model drug discovery.
Project description:Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation is challenging. Here, we demonstrate a simple, yet robust, determinant of developmental potential-the number of expressed genes per cell-and leverage this measure of transcriptional diversity to develop a computational framework (CytoTRACE) for predicting differentiation states from scRNA-seq data. When applied to diverse tissue types and organisms, CytoTRACE outperformed previous methods and nearly 19,000 annotated gene sets for resolving 52 experimentally determined developmental trajectories. Additionally, it facilitated the identification of quiescent stem cells and revealed genes that contribute to breast tumorigenesis. This study thus establishes a key RNA-based feature of developmental potential and a platform for delineation of cellular hierarchies.
Project description:Breast cancer is the second leading cause of cancer-related mortality worldwide as most patients often suffer cancer relapse. The reason is often attributed to the presence of cancer stem cells (CSCs). Recent studies revealed that dysregulation of microRNA (miRNA) are closely linked to breast cancer recurrence and metastasis. However, no specific study has comprehensively characterised the CSC characteristic and miRNA transcriptome in spheroid-enriched breast cells. This study described the generation of spheroid MCF-7 cell in serum-free condition and the comprehensive characterisation for their CSC properties. Subsequently, miRNA expression differences between the spheroid-enriched CSC cells and their parental cells were evaluated using next generation sequencing (NGS). Our results showed that the MCF-7 spheroid cells were enriched with CSCs properties, indicated by the ability to self-renew, increased expression of CSCs markers, and increased resistance to chemotherapeutic drugs. Additionally, spheroid-enriched CSCs possessed greater cell proliferation, migration, invasion, and wound healing ability. A total of 134 significantly (p<0.05) differentially expressed miRNAs were identified between spheroids and parental cells using miRNA-NGS. MiRNA-NGS analysis revealed 25 up-regulated and 109 down-regulated miRNAs which includes some miRNAs previously reported in the regulation of breast CSCs. A number of miRNAs (miR-4492, miR-4532, miR-381, miR-4508, miR-4448, miR-1296, and miR-365a) which have not been previously reported in breast cancer were found to show potential association with breast cancer chemoresistance and self-renewal capability. The gene ontology (GO) analysis showed that the predicted genes were enriched in the regulation of metabolic processes, gene expression, DNA binding, and hormone receptor binding. The corresponding pathway analyses inferred from the GO results were closely related to the function of signalling pathway, self-renewability, chemoresistance, tumorigenesis, cytoskeletal proteins, and metastasis in breast cancer. Based on these results, we proposed that certain miRNAs identified in this study could be used as new potential biomarkers for breast cancer stem cell diagnosis and targeted therapy.