Culture Adaptation Alters Transcriptional Hierarchies among Single Human Embryonic Stem Cells Reflecting Altered Patterns of Differentiation

We have used single cell transcriptome analysis to re-examine the substates of early passage, karyotypically Normal, and late passage, karyotypically Abnormal (‘Culture Adapted’) human embryonic stem cells characterized by differential expression of the cell surface marker antigen, SSEA3. The results confirmed that culture adaptation is associated with alterations to the dynamics of the SSEA3(+) and SSEA3(-) substates of these cells, with SSEA3(-) Adapted cells remaining within the stem cell compartment whereas the SSEA3(-) Normal cells appear to have differentiated. However, the single cell data reveal that these substates are characterized by further heterogeneity that changes on culture adaptation. Notably the Adapted population includes cells with a transcriptome substate suggestive of a shift to a more naïve-like phenotype in contrast to the cells of the Normal population. Further, a subset of the Normal SSEA3(+) cells expresses genes typical of endoderm differentiation, despite also expressing the undifferentiated stem cell genes, POU5F1 (OCT4) and NANOG, whereas such apparently lineage-primed cells are absent from the Adapted population. These results suggest that the selective growth advantage gained by genetically variant, culture adapted human embryonic stem cells may derive in part from a changed substate structure that influences their propensity for differentiation

Low concentrations of nitric oxide delay the differentiation of embryonic stem cells and promote their survival

Nitric oxide (NO) is an intracellular messenger in several cell systems, but its contribution to embryonic stem cell (ESC) biology has not been characterized. Exposure of ESCs to low concentrations (2–20 μM) of the NO donor diethylenetriamine NO adduct confers protection from apoptosis elicited by leukaemia inhibitory factor (LIF) withdrawal. NO blocked caspase 3 activation, PARP degradation, downregulation of the pro-apoptotic genes Casp7, Casp9, Bax and Bak1 and upregulation of the anti-apoptotic genes Bcl-2 111, Bcl-2 and Birc6. These effects were also observed in cells overexpressing eNOS. Exposure of LIF-deprived mESCs to low NO prevented the loss of expression of self-renewal genes (Oct4, Nanog and Sox2) and the SSEA marker. Moreover, NO blocked the differentiation process promoted by the absence of LIF and bFGF in mouse and human ESCs. NO treatment decreased the expression of differentiation markers, such as Brachyury, Gata6 and Gata4. Constitutive overexpression of eNOS in cells exposed to LIF deprivation maintained the expression of self-renewal markers, whereas the differentiation genes were repressed. These effects were reversed by addition of the NOS inhibitor L-NMMA. Altogether, the data suggest that low NO has a role in the regulation of ESC differentiation by delaying the entry into differentiation, arresting the loss of self-renewal markers and promoting cell survival by inhibiting apoptosis

Gene Expression Profile of Neuronal Progenitor Cells Derived from hESCs: Activation of Chromosome 11p15.5 and Comparison to Human Dopaminergic Neurons

BACKGROUND: We initiated differentiation of human embryonic stem cells (hESCs) into dopamine neurons, obtained a purified population of neuronal precursor cells by cell sorting, and determined patterns of gene transcription. METHODOLOGY: Dopaminergic differentiation of hESCs was initiated by culturing hESCs with a feeder layer of PA6 cells. Differentiating cells were then sorted to obtain a pure population of PSA-NCAM-expressing neuronal precursors, which were then analyzed for gene expression using Massive Parallel Signature Sequencing (MPSS). Individual genes as well as regions of the genome which were activated were determined. PRINCIPAL FINDINGS: A number of genes known to be involved in the specification of dopaminergic neurons, including MSX1, CDKN1C, Pitx1 and Pitx2, as well as several novel genes not previously associated with dopaminergic differentiation, were expressed. Notably, we found that a specific region of the genome located on chromosome 11p15.5 was highly activated. This region contains several genes which have previously been associated with the function of dopaminergic neurons, including the gene for tyrosine hydroxylase (TH), the rate-limiting enzyme in catecholamine biosynthesis, IGF2, and CDKN1C, which cooperates with Nurr1 in directing the differentiation of dopaminergic neurons. Other genes in this region not previously recognized as being involved in the functions of dopaminergic neurons were also activated, including H19, TSSC4, and HBG2. IGF2 and CDKN1C were also found to be highly expressed in mature human TH-positive dopamine neurons isolated from human brain samples by laser capture. CONCLUSIONS: The present data suggest that the H19-IGF2 imprinting region on chromosome 11p15.5 is involved in the process through which undifferentiated cells are specified to become neuronal precursors and/or dopaminergic neurons

A novel single-cell based method for breast cancer prognosis

Breast cancer prognosis is challenging due to the heterogeneity of the disease. Various computational methods using bulk RNA-seq data have been proposed for breast cancer prognosis. However, these methods suffer from limited performances or ambiguous biological relevance, as a result of the neglect of intra-tumor heterogeneity. Recently, single cell RNA-sequencing (scRNA-seq) has emerged for studying tumor heterogeneity at cellular levels. In this paper, we propose a novel method, scPrognosis, to improve breast cancer prognosis with scRNA-seq data. scPrognosis uses the scRNA-seq data of the biological process Epithelial-to-Mesenchymal Transition (EMT). It firstly infers the EMT pseudotime and a dynamic gene co-expression network, then uses an integrative model to select genes important in EMT based on their expression variation and differentiation in different stages of EMT, and their roles in the dynamic gene co-expression network. To validate and apply the selected signatures to breast cancer prognosis, we use them as the features to build a prediction model with bulk RNA-seq data. The experimental results show that scPrognosis outperforms other benchmark breast cancer prognosis methods that use bulk RNA-seq data. Moreover, the dynamic changes in the expression of the selected signature genes in EMT may provide clues to the link between EMT and clinical outcomes of breast cancer. scPrognosis will also be useful when applied to scRNA-seq datasets of different biological processes other than EMT.Xiaomei Li, Lin Liu, Gregory J. Goodall, Andreas Schreiber, Taosheng Xu, Jiuyong Li, Thuc D. L

Lymphocyte depletion and repopulation after chemotherapy for primary breast cancer

Background: Approximately 30 % of breast cancer patients receive chemotherapy, yet little is known about influences of current regimens on circulating lymphocyte levels and phenotypes. Similarly, clinico-pathological factors that modify these influences, and implications for future immune health remain mainly unexplored. Methods: We used flow-cytometry to assess circulating lymphocyte levels and phenotypes in 88 primary breast cancer patients before chemotherapy and at time-points from 2 weeks to 9 months after chemotherapy completion. We examined circulating titres of antibodies against pneumococcal and tetanus antigens using ELISAs. Results: Levels of B, T and NK cells were significantly reduced 2 weeks after chemotherapy (p < 0.001). B cells demonstrated particularly dramatic depletion, falling to 5.4 % of pre-chemotherapy levels. Levels of all cells recovered to some extent, although B and CD4+ T cells remained significantly depleted even 9 months post-chemotherapy (p < 0.001). Phenotypes of repopulating B and CD4+ T cells were significantly different from, and showed no sign of returning to pre-chemotherapy profiles. Repopulating B cells were highly depleted in memory cells, with proportions of memory cells falling from 38 % to 10 % (p < 0.001). Conversely, repopulating CD4+ T cells were enriched in memory cells, which increased from 63 % to 75 % (p < 0.001). Differences in chemotherapy regimen and patient smoking were associated with significant differences in depletion extent or repopulation dynamics. Titres of anti-pneumococcal and anti-tetanus antibodies were both significantly reduced post-chemotherapy and did not recover during the study (p < 0.001). Conclusion: Breast cancer chemotherapy is associated with long-term changes in immune parameters that should be considered during clinical management

Application guide for omics approaches to cell signaling

Research in signal transduction aims to identify the functions of different signaling pathways in physiological and pathological states. Traditional techniques using biochemical, genetic or cell biological approaches have made important contributions to our understanding of cellular signaling. However, the single-gene approach does not take into account the full complexity of cell signaling. With the availability of omics techniques, great progress has been made in understanding signaling networks. Omics approaches can be classified into two categories: 'molecular profiling', including genomic, proteomic, post-translational modification and interactome profiling; and 'molecular perturbation', including genetic and functional perturbations