Context-dependent gene regulatory network reveals regulation dynamics and cell trajectories using unspliced transcripts.

Gene regulatory networks govern complex gene expression programs in various biological phenomena, including embryonic development, cell fate decisions and oncogenesis. Single-cell techniques are increasingly being used to study gene expression, providing higher resolution than traditional approaches. However, inferring a comprehensive gene regulatory network across different cell types remains a challenge. Here, we propose to construct context-dependent gene regulatory networks (CDGRNs) from single-cell RNA sequencing data utilizing both spliced and unspliced transcript expression levels. A gene regulatory network is decomposed into subnetworks corresponding to different transcriptomic contexts. Each subnetwork comprises the consensus active regulation pairs of transcription factors and their target genes shared by a group of cells, inferred by a Gaussian mixture model. We find that the union of gene regulation pairs in all contexts is sufficient to reconstruct differentiation trajectories. Functions specific to the cell cycle, cell differentiation or tissue-specific functions are enriched throughout the developmental process in each context. Surprisingly, we also observe that the network entropy of CDGRNs decreases along differentiation trajectories, indicating directionality in differentiation. Overall, CDGRN allows us to establish the connection between gene regulation at the molecular level and cell differentiation at the macroscopic level.

BIC: a database for the transcriptional landscape of bacteria in cancer.

Microbial communities are massively resident in the human body, yet dysbiosis has been reported to correlate with many diseases, including various cancers. Most studies focus on the gut microbiome, while the bacteria that participate in tumor microenvironments on site remain unclear. Previous studies have acquired the bacteria expression profiles from RNA-seq, whole genome sequencing, and whole exon sequencing in The Cancer Genome Atlas (TCGA). However, small-RNA sequencing data were rarely used. Using TCGA miRNA sequencing data, we evaluated bacterial abundance in 32 types of cancer. To uncover the bacteria involved in cancer, we applied an analytical process to align unmapped human reads to bacterial references and developed the BIC database for the transcriptional landscape of bacteria in cancer. BIC provides cancer-associated bacterial information, including the relative abundance of bacteria, bacterial diversity, associations with clinical relevance, the co-expression network of bacteria and human genes, and their associated biological functions. These results can complement previously published databases. Users can easily download the result plots and tables, or download the bacterial abundance matrix for further analyses. In summary, BIC can provide information on cancer microenvironments related to microbial communities. BIC is available at: http://bic.jhlab.tw/.

Multiomics Reveals Induction of Neuroblastoma SK-N-BE(2)C Cell Death by Mitochondrial Division Inhibitor 1 through Multiple Effects.

Mitochondrial division inhibitor 1 (Mdivi-1) is a well-known synthetic compound aimed at inhibiting dynamin-related protein 1 (Drp1) to suppress mitochondrial fission, making it a valuable tool for studying mitochondrial dynamics. However, its specific effects beyond Drp1 inhibition remain to be confirmed. In this study, we employed integrative proteomics and phosphoproteomics to delve into the molecular responses induced by Mdivi-1 in SK-N-BE(2)C cells. A total of 3070 proteins and 1945 phosphorylation sites were identified, with 880 of them represented as phosphoproteins. Among these, 266 proteins and 97 phosphorylation sites were found to be sensitive to the Mdivi-1 treatment. Functional enrichment analysis unveiled their involvement in serine biosynthesis and extrinsic apoptotic signaling pathways. Through targeted metabolomics, we observed that Mdivi-1 enhanced intracellular serine biosynthesis while reducing the production of C24:1-ceramide. Within these regulated phosphoproteins, dynamic dephosphorylation of proteasome subunit alpha type 3 serine 250 (PSMA3-S250) occurred after Mdivi-1 treatment. Further site-directed mutagenesis experiments revealed that the dephosphorylation-deficient mutant PSMA3-S250A exhibited a decreased cell survival. This research confirms that Mdivi-1's inhibition of mitochondrial division leads to various side effects, ultimately influencing cell survival, rather than solely targeting Drp1 inhibition.

Macrophages as determinants and regulators of systemic sclerosis-related interstitial lung disease.

BACKGROUND: Interstitial lung disease (ILD) is the primary cause of mortality in systemic sclerosis (SSc), an autoimmune disease characterized by tissue fibrosis. SSc-related ILD (SSc-ILD) occurs more frequently in females aged 30-55 years, whereas idiopathic pulmonary fibrosis (IPF) is more prevalent in males aged 60-75 years. SSc-ILD occurs earlier than IPF and progresses rapidly. FCN1, FABP4, and SPP1 macrophages are involved in the pathogenesis of lung fibrosis; SPP1 macrophages demonstrate upregulated expression in both SSc-ILD and IPF. To identify the differences between SSc-ILD and IPF using single-cell analysis, clarify their distinct pathogeneses, and propose directions for prevention and treatment. METHODS: We performed single-cell RNA sequencing on NCBI Gene Expression Omnibus (GEO) databases GSE159354 and GSE212109, and analyzed lung tissue samples across healthy controls, IPF, and SSc-ILD. The primary measures were the filtered genes integrated with batch correction and annotated cell types for distinguishing patients with SSc-ILD from healthy controls. We proposed an SSc-ILD pathogenesis using cell-cell interaction inferences, and predicted transcription factors regulating target genes using SCENIC. Drug target prediction of the TF gene was performed using Drug Bank Online. RESULTS: A subset of macrophages activates the MAPK signaling pathway under oxidative stress. Owing to the lack of inhibitory feedback from ANNEXIN and the autoimmune characteristics, this leads to an earlier onset of lung fibrosis compared to IPF. During initial lung injury, fibroblasts begin to activate the IL6 pathway under the influence of SPP1 alveolar macrophages, but IL6 appears unrelated to other inflammatory and immune cells. This may explain why tocilizumab (an anti-IL6-receptor antibody) only preserves lung function in patients with early SSc-ILD. Finally, we identified BCLAF1 and NFE2L2 as influencers of MAPK activation in macrophages. Metformin downregulates NFE2L2 and could serve as a repurposed drug candidate. CONCLUSIONS: SPP1 alveolar macrophages play a role in the profibrotic activity of IPF and SSc-ILD. However, SSc-ILD is influenced by autoimmunity and oxidative stress, leading to the continuous activation of MAPK in macrophages. This may result in an earlier onset of lung fibrosis than in IPF. Such differences could serve as potential research directions for early prevention and treatment.

Quantitative phosphoproteomics reveals ectopic ATP synthase on mesenchymal stem cells to promote tumor progression via ERK/c-Fos pathway activation.

The tumor microenvironment (TME), which comprises cellular and noncellular components, is involved in the complex process of cancer development. Emerging evidence suggests that mesenchymal stem cells (MSCs), one of the vital regulators of the TME, foster tumor progression through paracrine secretion. However, the comprehensive phosphosignaling pathways that are mediated by MSC-secreting factors have not yet been fully established. In this study, we attempt to dissect the MSC-triggered mechanism in lung cancer using quantitative phosphoproteomics. A total of 1958 phosphorylation sites are identified in lung cancer cells stimulated with MSC-conditioned medium. Integrative analysis of the identified phosphoproteins and predicted kinases demonstrates that MSC-conditioned medium functionally promotes the proliferation and migration of lung cancer via the ERK/phospho-c-Fos-S374 pathway. Recent studies have reported that extracellular ATP accumulates in the TME and stimulates the P2X7R on the cancer cell membrane via purinergic signaling. We observe that ectopic ATP synthase is located on the surface of MSCs and excreted extracellular ATP into the lung cancer microenvironment to trigger the ERK/phospho-c-Fos-S374 pathway, which is consistent with these previous findings. Our results suggest that ectopic ATP synthase on the surface of MSCs releases extracellular ATP into the TME, which promotes cancer progression via activation of the ERK/phospho-c-Fos-S374 pathway.

Phylotranscriptomic patterns of network stochasticity and pathway dynamics during embryogenesis.

MOTIVATION: The hourglass model is a popular evo-devo model depicting that the developmental constraints in the middle of a developmental process are higher, and hence the phenotypes are evolutionarily more conserved, than those that occur in early and late ontogeny stages. Although this model has been supported by studies analyzing developmental gene expression data, the evolutionary explanation and molecular mechanism behind this phenomenon are not fully understood yet. To approach this problem, Raff proposed a hypothesis and claimed that higher interconnectivity among elements in an organism during organogenesis resulted in the larger constraints at the mid-developmental stage. By employing stochastic network analysis and gene-set pathway analysis, we aim to demonstrate such changes of interconnectivity claimed in Raff's hypothesis. RESULTS: We first compared the changes of network randomness among developmental processes in different species by measuring the stochasticity within the biological network in each developmental stage. By tracking the network entropy along each developmental process, we found that the network stochasticity follows an anti-hourglass trajectory, and such a pattern supports Raff's hypothesis in dynamic changes of interconnections among biological modules during development. To understand which biological functions change during the transition of network stochasticity, we sketched out the pathway dynamics along the developmental stages and found that species may activate similar groups of biological processes across different stages. Moreover, higher interspecies correlations are found at the mid-developmental stages. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Ensemble learning model for identifying the hallmark genes of NFκB/TNF signaling pathway in cancers.

BACKGROUND: The nuclear factor kappa B (NFκB) regulatory pathways downstream of tumor necrosis factor (TNF) play a critical role in carcinogenesis. However, the widespread influence of NFκB in cells can result in off-target effects, making it a challenging therapeutic target. Ensemble learning is a machine learning technique where multiple models are combined to improve the performance and robustness of the prediction. Accordingly, an ensemble learning model could uncover more precise targets within the NFκB/TNF signaling pathway for cancer therapy. METHODS: In this study, we trained an ensemble learning model on the transcriptome profiles from 16 cancer types in the TCGA database to identify a robust set of genes that are consistently associated with the NFκB/TNF pathway in cancer. Our model uses cancer patients as features to predict the genes involved in the NFκB/TNF signaling pathway and can be adapted to predict the genes for different cancer types by switching the cancer type of patients. We also performed functional analysis, survival analysis, and a case study of triple-negative breast cancer to demonstrate our model's potential in translational cancer medicine. RESULTS: Our model accurately identified genes regulated by NFκB in response to TNF in cancer patients. The downstream analysis showed that the identified genes are typically involved in the canonical NFκB-regulated pathways, particularly in adaptive immunity, anti-apoptosis, and cellular response to cytokine stimuli. These genes were found to have oncogenic properties and detrimental effects on patient survival. Our model also could distinguish patients with a specific cancer subtype, triple-negative breast cancer (TNBC), which is known to be influenced by NFκB-regulated pathways downstream of TNF. Furthermore, a functional module known as mononuclear cell differentiation was identified that accurately predicts TNBC patients and poor short-term survival in non-TNBC patients, providing a potential avenue for developing precision medicine for cancer subtypes. CONCLUSIONS: In conclusion, our approach enables the discovery of genes in NFκB-regulated pathways in response to TNF and their relevance to carcinogenesis. We successfully categorized these genes into functional groups, providing valuable insights for discovering more precise and targeted cancer therapeutics.

DockCoV2: a drug database against SARS-CoV-2.

The current state of the COVID-19 pandemic is a global health crisis. To fight the novel coronavirus, one of the best-known ways is to block enzymes essential for virus replication. Currently, we know that the SARS-CoV-2 virus encodes about 29 proteins such as spike protein, 3C-like protease (3CLpro), RNA-dependent RNA polymerase (RdRp), Papain-like protease (PLpro), and nucleocapsid (N) protein. SARS-CoV-2 uses human angiotensin-converting enzyme 2 (ACE2) for viral entry and transmembrane serine protease family member II (TMPRSS2) for spike protein priming. Thus in order to speed up the discovery of potential drugs, we develop DockCoV2, a drug database for SARS-CoV-2. DockCoV2 focuses on predicting the binding affinity of FDA-approved and Taiwan National Health Insurance (NHI) drugs with the seven proteins mentioned above. This database contains a total of 3,109 drugs. DockCoV2 is easy to use and search against, is well cross-linked to external databases, and provides the state-of-the-art prediction results in one site. Users can download their drug-protein docking data of interest and examine additional drug-related information on DockCoV2. Furthermore, DockCoV2 provides experimental information to help users understand which drugs have already been reported to be effective against MERS or SARS-CoV. DockCoV2 is available at https://covirus.cc/drugs/.

Complement C1q mediates the expansion of periportal hepatic progenitor cells in senescence-associated inflammatory liver.

Most hepatocellular carcinomas (HCCs) develop in patients with chronic hepatitis, which creates a microenvironment for the growth of hepatic progenitor cells (HPCs) at the periportal area and subsequent development of HCCs. We investigated the signal from the inflammatory liver for this pathogenic process in the hepatic conditional ß-catenin knockout mouse model. Senescent ß-catenin-depleted hepatocytes in aged mice create an inflammatory microenvironment that stimulates periportal HPC expansion but arrests differentiation, which predisposes mice to the development of liver tumors. The release of complement C1q from macrophages in the inflammatory niche was identified as the unorthodox signal that activated the ß-catenin pathway in periportal HPCs and was responsible for their expansion and de-differentiation. C1q inhibitors blocked the ß-catenin pathway in both the expanding HPCs and the liver tumors but spared its orthodox pathway in pericentral normal hepatocytes. This mechanism has been validated in human liver specimens from patients with chronic hepatitis. Taken together, these results demonstrate that C1q- mediated activation of ß-catenin pathway in periportal HPCs is a previously unrecognized mechanism for replenishing hepatocytes in the inflammatory liver and, if unchecked, for promoting hepatocarcinogenesis. C1q may become a new target for blocking carcinogenesis in patients with chronic hepatitis.

Multiomics Reveals Ectopic ATP Synthase Blockade Induces Cancer Cell Death via a lncRNA-mediated Phospho-signaling Network.

The EGFR tyrosine kinase inhibitor gefitinib is commonly used for lung cancer patients. However, some patients eventually become resistant to gefitinib and develop progressive disease. Here, we indicate that ecto-ATP synthase, which ectopically translocated from mitochondrial inner membrane to plasma membrane, is considered as a potential therapeutic target for drug-resistant cells. Quantitative multi-omics profiling reveals that ecto-ATP synthase inhibitor mediates CK2-dependent phosphorylation of DNA topoisomerase IIα (topo IIα) at serine 1106 and subsequently increases the expression of long noncoding RNA, GAS5. Additionally, we also determine that downstream of GAS5, p53 pathway, is activated by ecto-ATP synthase inhibitor for regulation of programed cell death. Interestingly, GAS5-proteins interactomic profiling elucidates that GAS5 associates with topo IIα and subsequently enhancing the phosphorylation level of topo IIα. Taken together, our findings suggest that ecto-ATP synthase blockade is an effective therapeutic strategy via regulation of CK2/phospho-topo IIα/GAS5 network in gefitinib-resistant lung cancer cells.

Identification of cell states using super-enhancer RNA.

BACKGROUND: A new class of regulatory elements called super-enhancers, comprised of multiple neighboring enhancers, have recently been reported to be the key transcriptional drivers of cellular, developmental, and disease states. RESULTS: Here, we defined super-enhancer RNAs as highly expressed enhancer RNAs that are transcribed from a cluster of localized genomic regions. Using the cap analysis of gene expression sequencing data from FANTOM5, we systematically explored the enhancer and messenger RNA landscapes in hundreds of different cell types in response to various environments. Applying non-negative matrix factorization (NMF) to super-enhancer RNA profiles, we found that different cell types were well classified. In addition, through the NMF of individual time-course profiles from a single cell-type, super-enhancer RNAs were clustered into several states with progressive patterns. We further investigated the enriched biological functions of the proximal genes involved in each pattern, and found that they were associated with the corresponding developmental process. CONCLUSIONS: The proposed super-enhancer RNAs can act as a good alternative, without the complicated measurement of histone modifications, for identifying important regulatory elements of cell type specification and identifying dynamic cell states.

Regulatory feedback loops bridge the human gene regulatory network and regulate carcinogenesis.

The development of disease involves a systematic disturbance inside cells and is associated with changes in the interactions or regulations among genes forming biological networks. The bridges inside a network are critical in shortening the distances between nodes. We observed that, inside the human gene regulatory network, one strongly connected core bridged the whole network. Other regulations outside the core formed a weakly connected component surrounding the core like a peripheral structure. Furthermore, the regulatory feedback loops (FBLs) inside the core compose an interface-like structure between the core and periphery. We then denoted the regulatory FBLs as the interface core. Notably, both the cancer-associated and essential biomolecules and regulations were significantly overrepresented in the interface core. These results implied that the interface core is not only critical for the network structure but central in cellular systems. Furthermore, the enrichment of the cancer-associated and essential regulations in the interface core might be attributed to its bridgeness in the network. More importantly, we identified one regulatory FBL between HNF4A and NR2F2 that possesses the highest bridgeness in the interface core. Further investigation suggested that the disturbance of the HNF4A-NR2F2 FBL might protect tumor cells from apoptotic processes. Our results emphasize the relevance of the regulatory network properties to cellular systems and might reveal a critical role of the interface core in cancer.

Phosphoproteome Analysis Reveals Dynamic Heat Shock Protein 27 Phosphorylation in Tanshinone IIA-Induced Cell Death.

Gastric cancer is one of the most common types of cancer worldwide. Nevertheless, effective therapeutic strategies have not yet been discovered. Several studies have shown that tanshinone IIA (TIIA), which is extracted from the traditional herbal medicine plant Danshen (Salvia miltiorrhiza), has potential activity against many kinds of cancer. Our previous research demonstrated that TIIA can induce cell death in gastric cancer. However, the exact signaling pathway response is still unclear. Post-translational modification (PTM) plays a significant role in a wide range of physiological processes in cancer, via regulation of both signal transduction cascades and many cellular pathways. Here, we integrated multilayer omics-transcriptomics and dynamic phosphoproteomics-to elucidate the regulatory networks triggered by TIIA in gastric cancer. We identified the phosphorylation of heat shock protein 27 (HSP27) at serine 82 in response to TIIA, which caused reactive oxygen species (ROS) production and unfolded protein response (UPR). Moreover, the accumulation of cellular stress increased the expression of heat shock factor 1 (HSF1). In addition, the downstream targets of HSF1, which were involved in heat shock stress and apoptosis, were also activated in TIIA-treated cells. In conclusion, this study performs a multiomic approach to clarify a comprehensive TIIA-responsive network leading to cell death in gastric cancer.

Characterizing the cancer-associated microbiome with small RNA sequencing data.

The microbiome is recognized as a quasi-organ in the human body. When dysbiosis of the microbiome occurs, this variation may contribute to alterations in the microenvironment, potentially inducing an inflammatory immune response and providing a niche for neoplastic growth. However, there is limited evidence regarding the correlation and interaction between the microbiome and tumorigenesis. By utilizing microRNA sequencing data of patients with colon and rectal cancer from The Cancer Genome Atlas, we designed a novel analytical process to extract non-human small RNA sequences and align them with the microbial genome to obtain a comprehensive view of the cancer-associated microbiome. In the present study, we identified >1000 genera among 630 colorectal samples and clustered these samples into three distinctive colorectal enterotypes. Furthermore, we found 12 genera from these clusters that are associated with cancer stages and revealed their putative functions. Our results indicate that the proposed analytical approach can effectively determine the cancer-associated microbiome. It may be readily applied to explore other types of cancer, in which specimens of the microbiome are difficult to collect.

ZNF322A-mediated protein phosphorylation induces autophagosome formation through modulation of IRS1-AKT glucose uptake and HSP-elicited UPR in lung cancer.

BACKGROUND: ZNF322A is an oncogenic transcription factor that belongs to the Cys2His2-type zinc-finger protein family. Accumulating evidence suggests that ZNF322A may contribute to the tumorigenesis of lung cancer, however, the ZNF322A-mediated downstream signaling pathways remain unknown. METHODS: To uncover ZNF322A-mediated functional network, we applied phosphopeptide enrichment and isobaric labeling strategies with mass spectrometry-based proteomics using A549 lung cancer cells, and analyzed the differentially expressed proteins of phosphoproteomic and proteomic profiles to determine ZNF322A-modulated pathways. RESULTS: ZNF322A highlighted a previously unidentified insulin signaling, heat stress, and signal attenuation at the post-translational level. Consistently, protein-phosphoprotein-kinase interaction network analysis revealed phosphorylation of IRS1 and HSP27 were altered upon ZNF322A-silenced lung cancer cells. Thus, we further investigated the molecular regulation of ZNF322A, and found the inhibitory transcriptional regulation of ZNF322A on PIM3, which was able to phosphorylate IRS1 at serine1101 in order to manipulate glucose uptake via the PI3K/AKT/mTOR signaling pathway. Moreover, ZNF322A also affects the unfolded protein response by phosphorylation of HSP27S82 and eIF2aS51, and triggers autophagosome formation in lung cancer cells. CONCLUSIONS: These findings not only give new information about the molecular regulation of the cellular proteins through ZNF322A at the post-translational level, but also provides a resource for the study of lung cancer therapy.

Quantitative Phosphoproteomics Reveals Cell Alignment and Mitochondrial Length Change under Cyclic Stretching in Lung Cells.

Lung cancer is a leading cause of death. Most previous studies have been based on traditional cell-culturing methods. However, lung cells are periodically subjected to mechanical forces during breathing. Understanding the mechanisms underlying the cyclic stretching induced in lung cells may be important for lung cancer therapy. Here, we applied cyclic stretching to stimulate the continual contraction that is present under physiological conditions in lung cells. We first uncovered the stretching-induced phosphoproteome in lung cancer cell line A549 and fibroblast cell line IMR-90. We identified 2048 and 2604 phosphosites corresponding to 837 and 1008 phosphoproteins in A549 and IMR-90, respectively. Furthermore, we combined our phosphoproteomics and public gene expression data to identify the biological functions in response to cyclic stretching. Interestingly, cytoskeletal and mitochondrial reorganization were enriched. We further used cell imaging analysis to validate the profiling results and found that this physical force changed cell alignment and mitochondrial length. This study not only reveals the molecular mechanism of cyclic stretching but also provides evidence that cell stretching causes cellular rearrangement and mitochondrial length change.

RNA-Binding Proteomics Reveals MATR3 Interacting with lncRNA SNHG1 To Enhance Neuroblastoma Progression.

The interaction of long noncoding RNAs (lncRNAs) with one or more RNA-binding proteins (RBPs) is important to a plethora of cellular and physiological processes. The lncRNA SNHG1 was reported to be aberrantly expressed and associated with poor patient prognosis in several cancers including neuroblastoma. However, the interacting RBPs and biological functions associated with SNHG1 in neuroblastoma remain unknown. In this study, we identified 283, 31, and 164 SNHG1-interacting proteins in SK-N-BE(2)C, SK-N-DZ, and SK-N-AS neuroblastoma cells, respectively, using a RNA-protein pull-down assay coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Twenty-four SNHG1-interacting RBPs were identified in common from these three neuroblastoma cell lines. RBPs MATR3, YBX1, and HNRNPL have the binding sites for SNHG1 predicted by DeepBind motif analysis. Furthermore, the direct binding of MATR3 with SNHG1 was validated by Western blot and confirmed by RNA immunoprecipitation assay (RIP). Coexpression analysis revealed that the expression of SNHG1 is positively correlated with MATR3 ( P = 3.402 × 10-13). The high expression of MATR3 is associated with poor event-free survival ( P = 0.00711) and overall survival ( P = 0.00064). Biological functions such as ribonucleoprotein complex biogenesis, RNA processing, and RNA splicing are significantly enriched and in common between SNHG1 and MATR3. In conclusion, we identified MATR3 as binding to SNHG1 and the interaction might be involved in splicing events that enhance neuroblastoma progression.

Quantitative Proteomics of Th-MYCN Transgenic Mice Reveals Aurora Kinase Inhibitor Altered Metabolic Pathways and Enhanced ACADM To Suppress Neuroblastoma Progression.

Neuroblastoma is a neural crest-derived embryonal tumor and accounts for about 15% of all cancer deaths in children. MYCN amplification is associated with aggressive and advanced stage of high-risk neuroblastoma, which remains difficult to treat and exhibits poor survival under current multimodality treatment. Here, we analyzed the transcriptomic profiles of neuroblastoma patients and showed that aurora kinases lead to poor survival and had positive correlation with MYCN amplification and high-risk disease. Further, pan-aurora kinase inhibitor (tozasertib) treatment not only induces cell-cycle arrest and suppresses cell proliferation, migration, and invasion ability in MYCN-amplified (MNA) neuroblastoma cell lines, but also inhibits tumor growth and prolongs animal survival in Th-MYCN transgenic mice. Moreover, we performed quantitative proteomics and identified 150 differentially expressed proteins after tozasertib treatment in the Th-MYCN mouse model. The functional and network-based enrichment revealed that tozasertib alters metabolic processes and identified a mitochondrial flavoenzyme in fatty acid ß-oxidation, ACADM, which is correlated with aurora kinases and neuroblastoma patient survival. Our findings indicate that the aurora kinase inhibitor could cause metabolic imbalance, possibly by disturbing carbohydrate and fatty acid metabolic pathways, and ACADM may be a potential target in MNA neuroblastoma.

Investigating the role of super-enhancer RNAs underlying embryonic stem cell differentiation.

BACKGROUND: Super-enhancer RNAs (seRNAs) are a kind of noncoding RNA transcribed from super-enhancer regions. The regulation mechanism and functional role of seRNAs are still unclear. Although super-enhancers play a critical role in the core transcriptional regulatory circuity of embryonic stem cell (ESC) differentiation, whether seRNAs have similar properties should be further investigated. RESULTS: We analyzed cap analysis gene expression sequencing (CAGE-seq) datasets collected during the differentiation of embryonic stem cells (ESCs) to cardiomyocytes to identify the seRNAs. A non-negative matrix factorization algorithm was applied to decompose the seRNA profiles and reveal two hidden stages during the ESC differentiation. We further identified 95 and 78 seRNAs associated with early- and late-stage ESC differentiation, respectively. We found that the binding sites of master regulators of ESC differentiation, including NANOG, FOXA2, and MYC, were significantly observed in the loci of the stage-specific seRNAs. Based on the investigation of genes coexpressed with seRNA, these stage-specific seRNAs might be involved in cardiac-related functions such as myofibril assembly and heart development and act in trans to regulate the co-expressed genes. CONCLUSIONS: In this study, we used a computational approach to demonstrate the possible role of seRNAs during ESC differentiation.

Dynamics of alternative polyadenylation in human preimplantation embryos.

Alternative polyadenylation (APA) affects the length of the 3' untranslated region (3'-UTR) and the regulation of microRNAs. Previous studies have shown that cancer cells tend to have shorter 3'-UTRs than normal cells. A plausible explanation for this is that it enables cancer cells to escape the regulation of microRNAs. Here, we extend this concept to an opposing context: changes in 3'-UTR length in the development of the human preimplantation embryo. Unlike cancer cells, during early development 3'-UTRs tended to become longer, and gene expression was negatively correlated with 3'-UTR length. Moreover, our functional enrichment results showed that length changes are part of the development mechanism. We also investigated the analogy of 3'-UTR length variation with respect to lncRNAs and found that, similarly, lncRNA length tended to increase during embryo development.