A high-resolution transcriptome map of cell cycle reveals novel connections between periodic genes and cancer

Assembly of a parts list of the human mitotic cell cycle machinery

The set of proteins required for mitotic division remains poorly characterized. Here, an extensive series of correlation analyses of human and mouse transcriptomics data were performed to identify genes strongly and reproducibly associated with cells undergoing S/G2-M phases of the cell cycle. In so doing, 701 cell cycle-associated genes were defined and while it was shown that many are only expressed during these phases, the expression of others is also driven by alternative promoters. Of this list, 496 genes have known cell cycle functions, whereas 205 were assigned as putative cell cycle genes, 53 of which are functionally uncharacterized. Among these, 27 were screened for subcellular localization revealing many to be nuclear localized and at least three to be novel centrosomal proteins. Furthermore, 10 others inhibited cell proliferation upon siRNA knockdown. This study presents the first comprehensive list of human cell cycle proteins, identifying many new candidate proteins.

Set2 methyltransferase facilitates cell cycle progression by maintaining transcriptional fidelity

Methylation of histone H3 lysine 36 (H3K36me) by yeast Set2 is critical for the maintenance of chromatin structure and transcriptional fidelity. However, we do not know the full range of Set2/H3K36me functions or the scope of mechanisms that regulate Set2-dependent H3K36 methylation. Here, we show that the APC/C^CDC20 complex regulates Set2 protein abundance during the cell cycle. Significantly, absence of Set2-mediated H3K36me causes a loss of cell cycle control and pronounced defects in the transcriptional fidelity of cell cycle regulatory genes, a class of genes that are generally long, hence highly dependent on Set2/H3K36me for their transcriptional fidelity. Because APC/C also controls human SETD2, and SETD2 likewise regulates cell cycle progression, our data imply an evolutionarily conserved cell cycle function for Set2/SETD2 that may explain why recurrent mutations of SETD2 contribute to human disease.

SNHG5 Promotes Breast Cancer Proliferation by Sponging the miR-154-5p/PCNA Axis

Breast cancer is the most common malignant tumor and the main cause of cancer-associated mortality in females worldwide. Long non-coding RNAs (lncRNAs) have been reported to play vital roles in breast cancer development and progression; however, our understanding of most lncRNAs in breast cancer is still limited. In this study, we demonstrated that small nucleolar RNA host gene 5 (SNHG5) promotes breast cancer cell proliferation both in vitro and in vivo, and depletion of SNHG5 significantly led to cell-cycle arrest at G1 phase. Accumulating evidence has shown that many lncRNA transcripts could function as competing endogenous RNAs (ceRNAs) by competitively binding common microRNAs (miRNAs). We found that SNHG5 acts as a sponge for miR-154-5p, reducing its ability to repress proliferating cell nuclear antigen (PCNA). SNHG5 promoted breast cancer proliferation and cell-cycle progression by upregulation of PCNA expression. Clinically, we observed an increased SNHG5 expression in breast cancer, whereas miR-154-5p was decreased in breast cancer tissues compared with the adjacent normal breast tissues. Furthermore, the SNHG5 expression was significantly negatively correlated with miR-154-5p expression. Taken together, our data uncover the SNHG5-miR-154-5p-PCNA axis and provide a novel mechanism to explain breast cancer proliferation.

High throughput gene expression profiling of yeast colonies with microgel-culture Drop-seq

Yeast can be engineered into "living foundries" for non-natural chemical production by reprogramming them via a "design-build-test" cycle. While methods for "design" and "build" are relatively scalable and efficient, "test" remains a bottleneck, limiting the effectiveness of the procedure. Here we describe isogenic colony sequencing (ICO-seq), a massively-parallel strategy to assess the gene expression, and thus engineered pathway efficacy, of large numbers of genetically distinct yeast colonies. We use the approach to characterize opaque-white switching in 658 C. albicans colonies. By profiling the transcriptomes of 1642 engineered S. cerevisiae strains, we assess gene expression heterogeneity in a protein mutagenesis library. Our approach will accelerate synthetic biology by allowing facile and cost-effective transcriptional profiling of large numbers of genetically distinct yeast strains.

Exploration of prognosis-related microRNA and transcription factor co-regulatory networks across cancer types

The study of cancer prognosis serves as an important part of cancer research. Large-scale cancer studies have identified numerous genes and microRNAs (miRNAs) associated with prognosis. These informative genes and miRNAs represent potential biomarkers to predict survival and to elucidate the molecular mechanism of tumour progression. MiRNAs and transcription factors (TFs) can work cooperatively as essential mediators of gene expression, and their dysregulation affects cancer prognosis. A panoramic view of cancer prognosis at the system level, considering the co-regulation roles of miRNA and TF, remains elusive. Here, we establish 12 prognosis-related miRNA-TF co-regulatory networks. The characteristics of prognostic target genes and their regulators in the network are depicted. Although the target genes and co-regulatory patterns exhibit cancer-specific properties, some miRNAs and TFs are highly conserved across cancers. We illustrate and interpret the roles of these conserved regulators by building a model associated with cancer hallmarks, functional enrichment analysis, network community detection, and exhaustive literature research. The elaborated system-level prognostic miRNA-TF co-regulation landscape, including the highlighted roles of conserved regulators, provides a novel and powerful insights into further biological and medical discoveries.

Understanding Human-Virus Protein-Protein Interactions Using a Human Protein Complex-Based Analysis Framework

Although human protein complexes have been reported to be directly related to viral infection, previous studies have not systematically investigated human-virus PPIs from the perspective of human protein complexes. To the best of our knowledge, we have presented here the most comprehensive and in-depth analysis of human-virus PPIs in the context of VTCs. Our findings confirm that human protein complexes are heavily involved in viral infection. The observed preferences of virally targeted subunits within complexes reflect the mechanisms used by viruses to manipulate host protein complexes. The identified periodic expression patterns of the VTCs and the corresponding candidates could increase our understanding of how viruses manipulate the host cell cycle. Finally, our proposed conceptual application framework of VTCs and the developed VTcomplex could provide new hints to develop antiviral drugs for the clinical treatment of viral infections.

Computational analysis of human-virus protein-protein interaction (PPI) data is an effective way toward systems understanding the molecular mechanism of viral infection. Previous work has mainly focused on characterizing the global properties of viral targets within the entire human PPI network. In comparison, how viruses manipulate host local networks (e.g., human protein complexes) has been rarely addressed from a computational perspective. By mainly integrating information about human-virus PPIs, human protein complexes, and gene expression profiles, we performed a large-scale analysis of virally targeted complexes (VTCs) related to five common human-pathogenic viruses, including influenza A virus subtype H1N1, human immunodeficiency virus type 1, Epstein-Barr virus, human papillomavirus, and hepatitis C virus. We found that viral targets are enriched within human protein complexes. We observed in the context of VTCs that viral targets tended to have a high within-complex degree and to be scaffold and housekeeping proteins. Complexes that are essential for viral propagation were simultaneously targeted by multiple viruses. We characterized the periodic expression patterns of VTCs and provided the corresponding candidates that may be involved in the manipulation of the host cell cycle. As a potential application of the current analysis, we proposed a VTC-based antiviral drug target discovery strategy. Finally, we developed an online VTC-related platform known as VTcomplex (http://zzdlab.com/vtcomplex/index.php or http://systbio.cau.edu.cn/vtcomplex/index.php). We hope that the current analysis can provide new insights into the global landscape of human-virus PPIs at the VTC level and that the developed VTcomplex will become a vital resource for the community.

IMPORTANCE Although human protein complexes have been reported to be directly related to viral infection, previous studies have not systematically investigated human-virus PPIs from the perspective of human protein complexes. To the best of our knowledge, we have presented here the most comprehensive and in-depth analysis of human-virus PPIs in the context of VTCs. Our findings confirm that human protein complexes are heavily involved in viral infection. The observed preferences of virally targeted subunits within complexes reflect the mechanisms used by viruses to manipulate host protein complexes. The identified periodic expression patterns of the VTCs and the corresponding candidates could increase our understanding of how viruses manipulate the host cell cycle. Finally, our proposed conceptual application framework of VTCs and the developed VTcomplex could provide new hints to develop antiviral drugs for the clinical treatment of viral infections.

Defining a Characteristic Gene Expression Set Responsible for Cancer Stem Cell-Like Features in a Sub-Population of Ewing Sarcoma Cells CADO-ES1

One of the still open questions in Ewing sarcoma, a rare bone tumor with weak therapeutic options, is to identify the tumor-driving cell (sub) population and to understand the specifics in the biological network of these cells. This basic scientific insight might foster the development of more specific therapeutic target patterns. The experimental approach is based on a side population (SP) of Ewing cells, based on the model cell line CADO-ES1. The SP is established by flow cytometry and defined by the idea that tumor stem-like cells can be identified by the time-course in clearing a given artificial dye. The SP was characterized by a higher colony forming activity, by a higher differentiation potential, by higher resistance to cytotoxic drugs, and by morphology. Several SP and non-SP cell fractions and bone marrow-derived mesenchymal stem cell reference were analyzed by short read sequencing of the full transcriptome. The double-differential analysis leads to an altered expression structure of SP cells centered around the AP-1 and APC/c complex. The SP cells share only a limited proportion of the full mesenchymal stem cell stemness set of genes. This is in line with the expectation that tumor stem-like cells share only a limited subset of stemness features which are relevant for tumor survival.

Increased Trimethylation of histone H3K36 associates with biliary differentiation and predicts poor prognosis in resectable hepatocellular carcinoma

INTRODUCTION

Trimethylation of histone H3K36 (H3K36me3), an epigenetic marker of transcription-associated histone modification and stem cell regulation, is expressed in a variety of human cancers. This study elucidated the prognostic significance of H3K36me3 in patients with resectable hepatocellular carcinoma (HCC).

METHODS

Expression of H3K36me3 was retrospectively evaluated through immunohistochemistry in 152 surgically resected primary HCCs.

RESULTS

In nontumorous liver parenchyma, H3K36Me3 was detected in bile ducts but not in hepatocytes. H3K36me3 was positive in 104 (68.4%) of the HCCs. Positivity for H3K36me3 was associated with high level of serum α-fetoprotein (>200 ng/mL, P = 0.0148), high tumor grade (P = 0.0017), and high tumor stage (P = 0.0008). Patients with H3K36me3-positive tumors were more likely to have lower 5-year disease-free survival and 5-year overall survival than those with H3K36me3-negative tumors (P = 0.0484 and P = 0.0213, respectively). Multivariate analysis showed that H3K36me3 positivity was an independent predictor of high tumor grade (P = 0.0475) and high tumor stage (P = 0.0114) and thus contributed to poor prognosis. Furthermore, H3K36me3 positivity was significantly correlated with the expression of biliary markers cytokeratin 19 (CK19) and hepatocyte nuclear factor 1β (HNF1β) (P < 0.0001 and P = 0.0005, respectively). Combinatorial analysis revealed that CK19 and HNF1β expression individually exerted additive prognostic adverse effects on HCCs with H3K36me3 positivity.

CONCLUSIONS

Our study indicates that H3K36me3 positivity is associated with the expression of biliary markers and is a crucial predictor of poor prognosis in resectable HCC.

Pseudotime Ordering of Single Human β-Cells Reveals States of Insulin Production and Unfolded Protein Response

Proinsulin is a misfolding-prone protein, making its biosynthesis in the endoplasmic reticulum (ER) a stressful event. Pancreatic β-cells overcome ER stress by activating the unfolded protein response (UPR) and reducing insulin production. This suggests that β-cells transition between periods of high insulin biosynthesis and UPR-mediated recovery from cellular stress. We now report the pseudotime ordering of single β-cells from humans without diabetes detected by large-scale RNA sequencing. We identified major states with 1) low UPR and low insulin gene expression, 2) low UPR and high insulin gene expression, or 3) high UPR and low insulin gene expression. The latter state was enriched for proliferating cells. Stressed human β-cells do not dedifferentiate and show little propensity for apoptosis. These data suggest that human β-cells transition between states with high rates of biosynthesis to fulfill the body's insulin requirements to maintain normal blood glucose levels and UPR-mediated recovery from ER stress due to high insulin production.

Gene Signature of Proliferating Human Pancreatic α Cells

Pancreatic α cells proliferate at a low rate, and little is known about the control of this process. Here we report the characterization of human α cells by large-scale, single-cell RNA sequencing coupled with pseudotime ordering. We identified two large subpopulations and a smaller cluster of proliferating α cells with increased expression of genes involved in cell-cycle regulation. The proliferating α cells were differentiated, had normal levels of GCG expression, and showed no signs of cellular stress. Proliferating α cells were detected in both the G1S and G2M phases of the cell cycle. Human α cells proliferate at a fivefold higher rate than human β cells and express lower levels of the cell-cycle inhibitors CDKN1A and CDKN1C. Collectively, this study provides the gene signatures of human α cells and the genes involved in their cell division. The lower expression of two cell-cycle inhibitors in human α cells could account for their higher rate of proliferation compared with their insulin-producing counterparts.

FACS Isolation of Viable Cells in Different Cell Cycle Stages from Asynchronous Culture for RNA Sequencing

Recently developed high-throughput analytical techniques (e.g., protein mass spectrometry and nucleic acid sequencing) allow unprecedentedly sensitive, in-depth studies in molecular biology of cell proliferation, differentiation, aging, and death. However, the initial population of asynchronous cultured cells is highly heterogeneous by cell cycle stage, which complicates immediate analysis of some biological processes. Widely used cell synchronization protocols are time-consuming and can affect the finely tuned biochemical pathways leading to biased results. Besides, certain cell lines cannot be effectively synchronized. The current methodological challenge is thus to provide an effective tool for cell cycle phase-based population enrichment compatible with other required experimental procedures. Here, we describe an optimized approach to live cell FACS based on Hoechst 33342 cell-permeable DNA-binding fluorochrome staining. The proposed protocol is fast compared to traditional synchronization methods and yields reasonably pure fractions of viable cells for further experimental studies including high-throughput RNA-seq analysis.

Comparative cell cycle transcriptomics reveals synchronization of developmental transcription factor networks in cancer cells

The cell cycle coordinates core functions such as replication and cell division. However, cell-cycle-regulated transcription in the control of non-core functions, such as cell identity maintenance through specific transcription factors (TFs) and signalling pathways remains unclear. Here, we provide a resource consisting of mapped transcriptomes in unsynchronized HeLa and U2OS cancer cells sorted for cell cycle phase by Fucci reporter expression. We developed a novel algorithm for data analysis that enables efficient visualization and data comparisons and identified cell cycle synchronization of Notch signalling and TFs associated with development. Furthermore, the cell cycle synchronizes with the circadian clock, providing a possible link between developmental transcriptional networks and the cell cycle. In conclusion we find that cell cycle synchronized transcriptional patterns are temporally compartmentalized and more complex than previously anticipated, involving genes, which control cell identity and development.

Cell cycle time series gene expression data encoded as cyclic attractors in Hopfield systems

Modern time series gene expression and other omics data sets have enabled unprecedented resolution of the dynamics of cellular processes such as cell cycle and response to pharmaceutical compounds. In anticipation of the proliferation of time series data sets in the near future, we use the Hopfield model, a recurrent neural network based on spin glasses, to model the dynamics of cell cycle in HeLa (human cervical cancer) and S. cerevisiae cells. We study some of the rich dynamical properties of these cyclic Hopfield systems, including the ability of populations of simulated cells to recreate experimental expression data and the effects of noise on the dynamics. Next, we use a genetic algorithm to identify sets of genes which, when selectively inhibited by local external fields representing gene silencing compounds such as kinase inhibitors, disrupt the encoded cell cycle. We find, for example, that inhibiting the set of four kinases AURKB, NEK1, TTK, and WEE1 causes simulated HeLa cells to accumulate in the M phase. Finally, we suggest possible improvements and extensions to our model.

Cell cycle—the process in which a parent cell replicates its DNA and divides into two daughter cells—is an upregulated process in many forms of cancer. Identifying gene inhibition targets to regulate cell cycle is important to the development of effective therapies. Although modern high throughput techniques offer unprecedented resolution of the molecular details of biological processes like cell cycle, analyzing the vast quantities of the resulting experimental data and extracting actionable information remains a formidable task. Here, we create a dynamical model of the process of cell cycle using the Hopfield model (a type of recurrent neural network) and gene expression data from human cervical cancer cells and yeast cells. We find that the model recreates the oscillations observed in experimental data. Tuning the level of noise (representing the inherent randomness in gene expression and regulation) to the “edge of chaos” is crucial for the proper behavior of the system. We then use this model to identify potential gene targets for disrupting the process of cell cycle. This method could be applied to other time series data sets and used to predict the effects of untested targeted perturbations.

Overexpression of HN1L promotes cell malignant proliferation in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is a progressive malignant disease, involving the activation of oncogenes and inactivation of tumor suppressors. In this study, we identified and characterized a novel oncogene hematopoietic- and neurologic-expressed sequence 1-like (HN1L) in human NSCLC. Overexpression of HN1L was frequently detected in primary NSCLC compared with their non-tumor counterparts (P < 0.001), which was significantly associated with tumor size (P = 0.022). In addition, Kaplan-Meier analysis showed that upregulation of HN1L correlated with worse overall survival (P = 0.029) and disease-free survival (P = 0.011) for NSCLC patients. Both in vitro and in vivo studies demonstrated that inhibition of HN1L expression with shRNA dramatically inhibited cell growth, adherent and non-adherent colony formation, and tumorigenicity in nude mice. The positive correlation of HN1L expression and Ki67 level in a large NSCLC samples further suggested the key role of HN1L in the regulation of cell growth. Further study showed that knockdown of HN1L resulted in dramatic cell cycle arrest by interfering with MAPK pathway via interacting with RASA4 protein. In conclusion, HN1L plays a crucial role in the progression of NSCLC by contributing to malignant proliferation, with possible use as a new intervention point for therapeutic strategies.

Alternative splicing in cancers: From aberrant regulation to new therapeutics

Alternative splicing is one of the most common mechanisms for gene regulation in humans, and plays a vital role to increase the complexity of functional proteins. In this article, we seek to provide a general review on the relationships between alternative splicing and tumorigenesis. We briefly introduce the basic rules for regulation of alternative splicing, and discuss recent advances on dynamic regulation of alternative splicing in cancers by highlighting the roles of a variety of RNA splicing factors in tumorigenesis. We further discuss several important questions regarding the splicing of long noncoding RNAs and back-splicing of circular RNAs in cancers. Finally, we discuss the current technologies that can be used to manipulate alternative splicing and serve as potential cancer treatment.

Differential landscape of non-CpG methylation in embryonic stem cells and neurons caused by DNMT3s

Methylated non-CpGs (mCpH; H means A, C, and T) have emerged as key epigenetic marks in mammalian embryonic stem cells (ESCs) and neurons, regulating cell type-specific functions. In these two cell types, mCpHs show distinct motifs and correlations to transcription that could be a key in understanding the cell type-specific regulations. Thus, we attempted to uncover the underlying mechanism of the differences in ESCs and neurons by conducting a comprehensive analysis of public whole genome bisulfite sequencing data. Remarkably, there were cell type-specific mCpH patterns around methylated CpGs (mCpGs), resulted from preferential methylation at different contexts by DNA methyltransferase (DNMT) 3a and 3b. These DNMTs are differentially expressed in ESCs and brain tissues, resulting in distinct mCpH motifs in these two cell types. Furthermore, in ESCs, DNMT3b interacts with histone H3 tri-methylated at lysine 36 (H3K36me3), resulting in hyper-methylation at CpHs upon actively transcribed genes, including those involved in embryo development. Based on the results, we propose a model to explain the differential establishment of mCpHs in ESCs and neurons, providing insights into the mechanism underlying cell type-specific formation and function of mCpHs.

Cell cycle transcription control: DREAM/MuvB and RB-E2F complexes

The precise timing of cell cycle gene expression is critical for the control of cell proliferation; de-regulation of this timing promotes the formation of cancer and leads to defects during differentiation and development. Entry into and progression through S phase requires expression of genes coding for proteins that function in DNA replication. Expression of a distinct set of genes is essential to pass through mitosis and cytokinesis. Expression of these groups of cell cycle-dependent genes is regulated by the RB pocket protein family, the E2F transcription factor family, and MuvB complexes together with B-MYB and FOXM1. Distinct combinations of these transcription factors promote the transcription of the two major groups of cell cycle genes that are maximally expressed either in S phase (G1/S) or in mitosis (G2/M). In this review, we discuss recent work that has started to uncover the molecular mechanisms controlling the precisely timed expression of these genes at specific cell cycle phases, as well as the repression of the genes when a cell exits the cell cycle.

MRG15-mediated tethering of PALB2 to unperturbed chromatin protects active genes from genotoxic stress

The partner and localiser of BRCA2 (PALB2) plays important roles in the maintenance of genome integrity and protection against cancer. Although PALB2 is commonly described as a repair factor recruited to sites of DNA breaks, recent studies provide evidence that PALB2 also associates with unperturbed chromatin. Here, we investigated the previously poorly described role of chromatin-associated PALB2 in undamaged cells. We found that PALB2 associates with active genes through its major binding partner, MRG15, which recognizes histone H3 trimethylated at lysine 36 (H3K36me3) by the SETD2 methyltransferase. Missense mutations that ablate PALB2 binding to MRG15 confer elevated sensitivity to the topoisomerase inhibitor camptothecin (CPT) and increased levels of aberrant metaphase chromosomes and DNA stress in gene bodies, which were suppressed by preventing DNA replication. Remarkably, the level of PALB2 at genic regions was frequently decreased, rather than increased, upon CPT treatment. We propose that the steady-state presence of PALB2 at active genes, mediated through the SETD2/H3K36me3/MRG15 axis, ensures an immediate response to DNA stress and therefore effective protection of these regions during DNA replication. This study provides a conceptual advance in demonstrating that the constitutive chromatin association of repair factors plays a key role in the maintenance of genome stability and furthers our understanding of why PALB2 defects lead to human genome instability syndromes.