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Comparison of RNA-Seq and Microarray data from single cells. (A) A comparison of RNA-Seq and Affymetrix array data generated from the same amplified single cell samples. The overall correlation (Pearson) of the MCF7/MCF10A ratio between RNA-Seq and Affymetrix array data sets for the 157 genes examined was 0.95. (B) Venn diagrams showing overlaps of differentially expressed genes identified by RNA-Seq and Affymetrix array analysis (FC > 2, FDR < 0.05 for both data sets) highlighting the larger number of DE genes identified in the RNA-Seq data set. (C) A comparison of single cell RNA-Seq data and10 μg RNA Affymetrix array data showing the expression profiles of the top 30 differentially expressed genes identified by RNA-Seq or 10 μg RNA Affymetrix array data (all data FC > 2, FDR threshold 0.05). Heat map colour scheme for (A) and (C) as described in B.
Source publication
Background
Although profiling of RNA in single cells has broadened our understanding of development, cancer biology and mechanisms of disease dissemination, it requires the development of reliable and flexible methods. Here we demonstrate that the EpiStem RNA-AmpTM methodology reproducibly generates microgram amounts of cDNA suitable for RNA-Seq,...
Citations
... Four of the 28 datasets were removed because they were duplicates, 11 had insufficient sample size (MCF-7 = 1, MCF-10A = 1), and seven used microarray platforms with input data that was incompatible with GEO2R tools. The final six datasets: GSE59732 (Horton et al., 2015), GSE52712 (Rothwell et al., 2014), GSE48398, GSE41445, and GSE68651 had three probes each that corresponded to the OTUB1 gene while GSE5307 (Wong et al., 2008) had one, for a total number of 16 probes for analysis of OTUB1 expression. Some probes may be more specific than others, for example Affymetrix probe sets with -at designation against -s-at and -x-at probe sets (Dallas et al., 2005), but all probes were assessed accordingly. ...
Background
OTUB1 is a deubiquitin enzyme that plays important role in cancer-related events. Prompted by the lack of information about OTUB1’s potential as a breast cancer molecular marker, this study is conducted to evaluate the significance of OTUB1 as a diagnostic tool based on its expression in MCF-7, as well as to validate its potential as a therapeutic target using network-based analysis.
Methods
Relative expression of OTUB1 in MCF-7 and MCF-10A was compared using bioinformatics analysis on microarray datasets obtained from Gene Expression Omnibus and validated by qPCR experiment. Protein-protein interaction (PPI) network was constructed using Cytoscape ver3.6.0 to analyse the topological position of OTUB1 in cancer and differentially expressed genes (DEGs) neighbourhoods.
Results
Microarray datasets analysis showed that OTUB1 expression value is significantly higher in MCF-7 in seven out of 16 probes with log(FC) value ranging from 0.24 to 1.43. This result is consistent with qPCR analysis, with qPCR showing a larger log(FC) value of 2.44-4.95. Despite a significant difference in some microarray probes and qPCR experiment, the fold change value is too small to ensure sensitivity in breast cancer diagnosis. Meanwhile, PPI network analysis revealed that OTUB1 is the immediate neighbour for 31 cancer proteins and DEGs ESR1 and BIRC3, a strategic topological position for perturbing cancer interactome.
Conclusion
Taken together, our findings suggest that OTUB1 is an unfavourable candidate for breast cancer diagnosis, but it could be a very promising molecular target for breast cancer therapeutic intervention.
... Rothwell et al found metastasis-associated cancer-initiating cells in NSCLC PDX model and single-cell transcriptional profiling of these cells found increased expression of genes were related to ribosomal processing, cytoskeleton, glutathione transferase and stemness. 27 This study demonstrated the existence of metastatic initiating cells and delineated the gene expression of these cells and their potential drug resistance. ...
Single-cell sequencing (SCS) which has an unprecedentedly high resolution is an advanced technique for cancer research. Lung cancer still has a high mortality and morbidity. For further understanding the lung cancer, SCS is also been applied to lung cancer research to investigate its heterogeneity, metastasis, drug resistance, tumor microenvironment and many other issues. In this review, we summarized lung cancer research using SCS and their research achievements.
... To investigate these hypotheses further, we computed Spearman correlations between the compartment-specific gene expression profiles and median tissue-specific expression profiles from GTEx (53,54) and single cell RNA-seq profiles of MCF7 breast cancer cells (102) (Figure 5B; Supplemental Figure S15). Here, we find that C4 shows strong positive correlations with fibroblasts, lymphocytes, multiple collagenous organs (such as blood vessels, skin, mucosal esophagus, vagina, and uterus (103-105)), and MCF7 cells, breast tumor cells that cannot have ERBB2 gene amplification (106). ...
Targeted mRNA expression panels, measuring up to 800 genes, are used in academic and clinical settings due to low cost and high sensitivity for archived samples. Most samples assayed on targeted panels originate from bulk tissue comprised of many cell types, and cell-type heterogeneity confounds biological signals. Reference-free methods are used when cell-type-specific expression references are unavailable, but limited feature spaces render implementation challenging in targeted panels. Here, we present DeCompress, a semi-reference-free deconvolution method for targeted panels. DeCompress leverages a reference RNA-seq or microarray dataset from similar tissue to expand the feature space of targeted panels using compressed sensing. Ensemble reference-free deconvolution is performed on this artificially expanded dataset to estimate cell-type proportions and gene signatures. In simulated mixtures, four public cell line mixtures, and a targeted panel (1199 samples; 406 genes) from the Carolina Breast Cancer Study, DeCompress recapitulates cell-type proportions with less error than reference-free methods and finds biologically relevant compartments. We integrate compartment estimates into cis-eQTL mapping in breast cancer, identifying a tumor-specific cis-eQTL for CCR3 (C-C Motif Chemokine Receptor 3) at a risk locus. DeCompress improves upon reference-free methods without requiring expression profiles from pure cell populations, with applications in genomic analyses and clinical settings.
... The mRNA from the lysed DO11.10 CD4 T cells were isolated and amplified for microarray analysis. Because of the expected low numbers of CD4 memory T cells in 6 and 10.5 months, we used the Miltenyi μMACS™ SuperAmp™ technology established for RNA amplification of rare cells [2,57]. We used the criteria of nominal pvalue < 0.01 and fold change cutoff > 2 to obtain a list of differentially expressed genes from the microarray data. ...
While memory T-cells represent a hallmark of adaptive immunity, little is known about the genetic mechanisms regulating the longevity of memory CD4 T cells. Here, we studied the dynamics of gene expression in antigen specific CD4 T cells during infection, memory differentiation, and long-term survival up to nearly a year in mice. We observed that differentiation into long lived memory cells is associated with increased expression of genes inhibiting cell proliferation and apoptosis as well as genes promoting DNA repair response, lipid metabolism, and insulin resistance. We identified several transmembrane proteins in long-lived murine memory CD4 T cells, which co-localized exclusively within the responding antigen-specific memory CD4 T cells in human. The unique gene signatures of long-lived memory CD4 T cells, along with the new markers that we have defined, will enable a deeper understanding of memory CD4 T cell biology and allow for designing novel vaccines and therapeutics.
Cellular Immunology (2020), doi: https://doi.
... • cDNA amplification of RNA samples was carried out using Epistem's proprietary amplification kits (Single Cell RNA-Amp™) 5 with each whole section reaction receiving 1 ng total RNA input. Laser capture RNA samples were used in their entirety. ...
Immune checkpoints define an evolving class of inhibitory mediators that are expressed by tumour cells and infiltrating leucocytes to down-modulate the effector immune response against tumour cells. Therefore, the most recent efforts in cancer therapy centre on targeting immune-mediated mechanisms of tumour evasion. The ability to assess gene expression profiles from isolated populations of tumour-infiltrating lymphocytes (TILs) can assist in monitoring checkpoint inhibitor therapy efficacy and provide a better understanding of clinical outcomes. Ideally, transcriptional profiles should be obtained from pure isolated cell populations of interest, free from contaminating cell populations that may create adverse background noise. Micro sampling by laser capture microdissection is a powerful tool that allows for specific analysis from whole tissues, particularly in a heterogeneous microenvironment such as in a tumour, where less well represented target cells are dwarfed in abundance by tissue stroma and other cell types. However, whilst the application is potentially powerful for target discovery and mechanistic understanding, the process is notoriously difficult, particularly in clinical specimens. We use a methodology to analyse target cells, organelles or other tissue subsets by transcriptional profiling (TxP) using immunostain-mediated laser capture microscopy (LCM). Thorough optimisation of traditional immunohistochemistry techniques enabled us to select target cell populations of interest from positive stained tissue sections whilst minimising degradation of mRNA and miRNA allowing us to perform downstream genomic and pathway interrogation using microarray and/or RT-qPCR analysis. Our technique allows multiple capture types per slide, sample pooling when required, high capture throughput and capture image documentation. Here we exhibit immunostaining histology images using methods sympathetic to RNA integrity which allow for target selection by specific staining or target morphology, and demonstrate comparative analysis of matched pairs of disease and healthy sections of colon tumours. We used a Palm MicroBeam 4 LCM platform to efficiently identify, cut and specifically capture CD8a+ and CD3e+ tumour-infiltrating lymphocytes from frozen embedded tissue. This approach enabled us to isolate discrete targeted cell populations free from contaminating cells. Epistem’s Single Cell RNA-Amp™ was then used to provide robust and linear amplification of RNA and enable comparative analysis in applications such as target discovery and pharmacodynamics. The results indicated that transcriptional profiling was technically robust observing significantly differentially expressed genes despite the limited input obtained by micro-sampling.
... The medium of all the cells was supplemented with 10% fetal bovine serum (Invitrogen™; Thermo Fisher Scientific, Inc., Waltham, MA, USA), penicillin/streptomycin (100X; Euroclone Ltd, Paignton, UK), Glutamax (100X; Invit-rogen™) and non-essential amino acids (100X; Invitrogen™) at 37˚C in a humidified atmosphere of 5% CO 2 . In addition, for MCF-10A cells, DMEM was supplemented with human insulin (10 µg/ml; Thermo Fisher Scientific, Inc.), human epidermal growth factor (20 ng/ml; Thermo Fisher Scientific, Inc.) and hydrocortisone (0.5 µg/ml; Sigma-Aldrich, St. Louis, MO, USA), according to a previously reported procedure (20). ...
Breast cancer is the second most common cause of mortality in women; therefore, the identification of novel putative markers is required to improve its diagnosis and prognosis. Selenium is known to protect mammary epithelial cells from oxidative DNA damage, and to inhibit the initiation phase of carcinogenesis by stimulating DNA repair and apoptosis regulation. Consequently, the present study has focused attention on the selenoprotein family and their involvement in breast cancer. The present study performed a global analysis of the seleno-transcriptome expression in human breast cancer MCF-7 and MDA-MB231 cell lines compared with healthy breast MCF-10A cells using reverse transcription-quantitative polymerase chain reaction. The present data revealed the presence of differently expressed genes in MCF-7 and MDA-MB231 cells compared with MCF-10A cells: Four downregulated [glutathione peroxidase (GPX)1, GPX4, GPX5 and GPX7] and three upregulated (deiodinase iodothyronine, type II, GPX2 and GPX3) genes. Additionally, interactomic investigation were performed by the present study to evaluate the association between the downregulated and upregulated genes, and to identify putative HUB nodes, which represent the centers of association between the genes that are capable of direct control over the gene networks. Network analysis revealed that all differentially regulated genes, with the exception of selenoprotein T, are implicated in the same network that presents three HUB nodes interconnected to the selenoprotein mRNAs, including TP53, estrogen receptor 1 and catenin-β1 (CTNNB1). Overall, these data demonstrated for the first time, a profile of seleno-mRNAs specific for human breast cells, indicating that these genes alter their expression on the basis of the ER-positivity or negativity of breast cancer cells.
... We then graphically compared the resulting regression coefficients, which estimate fold changes of expression, between (1) genes located physically nearest to each mutation, (2) genes whose promoter directly overlaps a mutation or is directly connected to a network node overlapping a mutation (i.e., direct interaction), and (3) genes whose promoter is connected to a network node separated by 2 to 4 links (i.e., indirect interaction), after filtering out instances where the nearest TSS was also part of the network, and making sure no gene was duplicated in either of these three categories. Finally, we repeated the above procedure comparing expression data between MCF7 and MCF10A bulk mRNA-seq samples [13] obtained from the Gene Expression Omnibus, accession number GSE52712, using the online tool GEO2R to compute regression coefficients and P-values. ...
... Moreover, we have also observed that even indirect targets of the NCVs could be disease relevant, which highlights the system-level impact of disease-causing variants and the importance of studying these interactions at the network level. Similarly, we observed that gene targets discovered using ChIA-PET tend to show more differential expression between the MCF-7 line and MCF-10A, a non-cancer mammary epithelial cell line, using both single-cell and bulk RNA-seq datasets [38] (GSE52712) (S5 Fig). As an example, Fig 3B and S6 Fig show a simplified subnetwork revealing the indirect relationships of a region harboring an NCV to genes associated with cancer, including the well-known tumor repressor TP53 and multiple breast cancer-associated genes, such as EIF4A [39], EIF5A [40,41], AURKB [42] and CLDN7 [43]. ...
Unlabelled:
Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions.
Availability:
QuIN's web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.
... In details, MCF7 and MCF10A were expanded at 37˝C in a humidified atmosphere of 5% CO 2 in culture medium DMEM (Dulbecco's Modified Eagle's Medium, Lonza), whereas MDA-MB231 in RPMI 1640 (Lonza), supplemented with FBS (Invitrogen, Camarillo, CA, USA) at 10%, Penicillin/Streptomycin 100ˆ(Euroclone, Devon, UK), Glutamax 100ˆ(Invitrogen) non-essential amino acids 100ˆ(Invitrogen). Moreover, in the case of MCF10A the DMEM was supplemented also with human insulin 10 µg/mL (Life Technologies Corporation, Carlsbad, CA, USA), human epidermal growth factor 20 ng/mL (Life Technologies), and hydrocortisone 0.5 µg/mL (Sigma-Aldrich) according to the procedure reported in Rothwell et al. [42]. We know that the presence of insulin and hydrocortisone, which are required for culturing of MCF10 cells, can have effect on antioxidant capacity of cells, therefore we have used these cells because they represent one of the internationally models used for these types of studies. ...
Many studies have evidenced that the phenolic components from flaxseed (FS) oil have potential health benefits. The effect of the phenolic extract from FS oil has been evaluated on two human breast cancer cell lines, MCF7 and MDA-MB231, and on the human non-cancerous breast cell line, MCF10A, by SRB assay, cellular death, cell cycle, cell signaling, lipid peroxidation and expression of some key genes. We have evidenced that the extract shows anti-proliferative activity on MCF7 cells by inducing cellular apoptosis, increase of the percentage of cells in G0/G1 phase and of lipid peroxidation, activation of the H2AX signaling pathway, and upregulation of a six gene signature. On the other hand, on the MDA-MB2131 cells we verified only an anti-proliferative activity, a weak lipid peroxidation, the activation of the PI3K signaling pathway and an up-regulation of four genes. Overall these data suggest that the extract has both cytotoxic and pro-oxidant effects only on MCF7 cells, and can act as a metabolic probe, inducing differences in the gene expression. For this purpose, we have performed an interactomic analysis, highlighting the existing associations. From this approach, we show that the phenotypic difference between the two cell lines can be explained through their differential response to the phenolic extract.
... Technological advances in blood borne cancer biomarkers now make it possible to routinely analyse RNA and DNA from single cells (Rothwell et al., 2014; Ramskold et al., 2012; Guzvic et al., 2014) including isolated circulating tumour cells (CTC)s and the minute amounts of tumour derived DNA present in patient blood samples (reviewed in Krebs et al., 2014; Diaz and Bardelli, 2014). Circulating cell-free DNA (cfDNA) analysis is emerging as a relatively simple yet powerful biomarker for monitoring disease status and reporting mechanisms of treatment resistance in cancer patients, with the important advantage of being minimally invasive and suitable for longitudinal sampling (Murtaza et al., 2013). ...
Molecular information obtained from cancer patients' blood is an emerging and powerful research tool with immense potential as a companion diagnostic for patient stratification and monitoring. Blood, which can be sampled routinely, provides a means of inferring the current genetic status of patients' tumours via analysis of circulating tumour cells (CTCs) or circulating tumour DNA (ctDNA). However, accurate assessment of both CTCs and ctDNA requires all blood cells to be maintained intact until samples are processed. This dictates for ctDNA analysis EDTA blood samples must be processed with 4 h of draw, severely limiting the use of ctDNA in multi-site trials. Here we describe a blood collection protocol that is amenable for analysis of both CTCs and ctDNA up to four days after blood collection. We demonstrate that yields of circulating free DNA (cfDNA) obtained from whole blood CellSave samples are equivalent to those obtained from conventional EDTA plasma processed within 4 h of blood draw. Targeted and genome-wide NGS revealed comparable DNA quality and resultant sequence information from cfDNA within CellSave and EDTA samples. We also demonstrate that CTCs and ctDNA can be isolated from the same patient blood sample, and give the same patterns of CNA enabling direct analysis of the genetic status of patients' tumours.
In summary, our results demonstrate the utility of a simple approach that enabling robust molecular analysis of CTCs and cfDNA for genotype-directed therapies in multi-site clinical trials and represent a significant methodological improvement for clinical benefit.
