Exploring the mechanism of physcion-1-O-β-D-monoglucoside against acute lymphoblastic leukaemia based on network pharmacology and experimental validation

Objective

To explore the mechanism of PG against acute lymphoblastic leukaemia (ALL) by network pharmacology and experimental verification in vitro.

Methods

First, the biological activity of PG against B-ALL was determined by CCK-8 and flow cytometry. Then, the potential targets of PG were obtained from the PharmMapper database. ALL-related genes were collected from the GeneCards, OMIM and PharmGkb databases. The two datasets were intersected to obtain the target genes of PG in ALL. Then, protein interaction networks were constructed using the STRING database. The key targets were obtained by topological analysis of the network with Cytoscape 3.8.0 software. In addition, the mechanism of PG in ALL was confirmed by protein‒protein interaction, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Furthermore, molecular docking was carried out by AutoDock Vina. Finally, Western blotting was performed to confirm the effect of PG on NALM6 cells.

Results

PG inhibited the proliferation of NALM6 cells. A total of 174 antileukaemic targets of PG were obtained by network pharmacology. The key targets included AKT1, MAPK14, EGFR, ESR1, LCK, PTPN11, RHOA, IGF1, MDM2, HSP90AA1, HRAS, SRC and JAK2. Enrichment analysis found that PG had antileukaemic effects by regulating key targets such as MAPK signalling, and PG had good binding activity with MAPK14 protein (-8.9 kcal/mol). PG could upregulate the expression of the target protein p-P38, induce cell cycle arrest, and promote the apoptosis of leukaemia cells.

Conclusion

MAPK14 was confirmed to be one of the key targets and pathways of PG by network pharmacology and molecular experiments.

Identification of phytochemical compounds of Fagopyrum dibotrys and their targets by metabolomics, network pharmacology and molecular docking studies

Acute lung injury (ALI) is a clinically severe lung illness with high incidence rate and mortality. Especially, coronavirus disease 2019 (COVID-19) poses a serious threat to world wide governmental fitness. It has distributed to almost from corner to corner of the universe, and the situation in the prevention and control of COVID-19 remains grave. Traditional Chinese medicine plays a vital role in the precaution and therapy of sicknesses. At present, there is a lack of drugs for treating these diseases, so it is necessary to develop drugs for treating COVID-19 related ALI. Fagopyrum dibotrys (D. Don) Hara is an annual plant of the Polygonaceae family and one of the long-history used traditional medicine in China. In recent years, its rhizomes (medicinal parts) have attracted the attention of scholars at home and abroad due to their significant anti-inflammatory, antibacterial and anticancer activities. It can work on SARS-COV-2 with numerous components, targets, and pathways, and has a certain effect on coronavirus disease 2019 (COVID-19) related acute lung injury (ALI). However, there are few systematic studies on its aerial parts (including stems and leaves) and its potential therapeutic mechanism has not been studied. The phytochemical constituents of rhizome of F. dibotrys were collected using TCMSP database. And metabolites of F. dibotrys' s aerial parts were detected by metabonomics. The phytochemical targets of F. dibotrys were predicted by the PharmMapper website tool. COVID-19 and ALI-related genes were retrieved from GeneCards. Cross targets and active phytochemicals of COVID-19 and ALI related genes in F. dibotrys were enriched by gene ontology (GO) and KEGG by metscape bioinformatics tools. The interplay network entre active phytochemicals and anti COVID-19 and ALI targets was established and broke down using Cytoscape software. Discovery Studio (version 2019) was used to perform molecular docking of crux active plant chemicals with anti COVID-19 and ALI targets. We identified 1136 chemicals from the aerial parts of F. dibotrys, among which 47 were active flavonoids and phenolic chemicals. A total of 61 chemicals were searched from the rhizome of F. dibotrys, and 15 of them were active chemicals. So there are 6 commonly key active chemicals at the aerial parts and the rhizome of F. dibotrys, 89 these phytochemicals's potential targets, and 211 COVID-19 and ALI related genes. GO enrichment bespoken that F. dibotrys might be involved in influencing gene targets contained numerous biological processes, for instance, negative regulation of megakaryocyte differentiation, regulation of DNA metabolic process, which could be put down to its anti COVID-19 associated ALI effects. KEGG pathway indicated that viral carcinogenesis, spliceosome, salmonella infection, coronavirus disease - COVID-19, legionellosis and human immunodeficiency virus 1 infection pathway are the primary pathways obsessed in the anti COVID-19 associated ALI effects of F. dibotrys. Molecular docking confirmed that the 6 critical active phytochemicals of F. dibotrys, such as luteolin, (+) -epicatechin, quercetin, isorhamnetin, (+) -catechin, and (-) -catechin gallate, can combine with kernel therapeutic targets NEDD8, SRPK1, DCUN1D1, and PARP1. In vitro activity experiments showed that the total antioxidant capacity of the aerial parts and rhizomes of F. dibotrys increased with the increase of concentration in a certain range. In addition, as a whole, the antioxidant capacity of the aerial part of F. dibotrys was stronger than that of the rhizome. Our research afford cues for farther exploration of the anti COVID-19 associated ALI chemical compositions and mechanisms of F. dibotrys and afford scientific foundation for progressing modern anti COVID-19 associated ALI drugs based on phytochemicals in F. dibotrys. We also fully developed the medicinal value of F. dibotrys' s aerial parts, which can effectively avoid the waste of resources. Meanwhile, our work provides a new strategy for integrating metabonomics, network pharmacology, and molecular docking techniques which was an efficient way for recognizing effective constituents and mechanisms valid to the pharmacologic actions of traditional Chinese medicine.

Identification and verification of eight cancer-associated fibroblasts related genes as a prognostic signature for head and neck squamous cell carcinoma

Cancer-associated fibroblasts (CAFs) can exert their immunosuppressive effects by secreting various effectors that are involved in the regulation of tumor-infiltrating immune cells as well as other immune components in the tumor immune microenvironment (TIME), thereby promoting tumorigenesis, progression, metastasis, and drug resistance. Although a large number of studies suggest that CAFs play a key regulatory role in the development of head and neck squamous cell carcinoma (HNSCC), there are limited studies on the relevance of CAFs to the prognosis of HNSCC. In this study, we identified a prognostic signature containing eight CAF-related genes for HNSCC by univariate Cox analysis, lasso regression, stepwise regression, and multivariate Cox analysis. Our validation in primary cultures of CAFs from human HNSCC and four human HNSCC cell lines confirmed that these eight genes are indeed characteristic markers of CAFs. Immune cell infiltration differences analysis between high-risk and low-risk groups according to the eight CAF-related genes signature hinted at CAFs regulatory roles in the TIME, further revealing its potential role on prognosis. The signature of the eight CAF-related genes was validated in different independent validation cohorts and all showed that it was a valid marker for prognosis. The significantly higher overall survival (OS) in the low-risk group compared to the high-risk group was confirmed by Kaplan-Meier (K-M) analysis, suggesting that the signature of CAF-related genes can be used as a non-invasive predictive tool for HNSCC prognosis. The low-risk group had significantly higher levels of tumor-killing immune cell infiltration, as confirmed by CIBERSORT analysis, such as CD8⁺ T cells, follicular helper T cells, and Dendritic cells (DCs) in the low-risk group. In contrast, the level of infiltration of pro-tumor cells such as M0 macrophages and activated Mast cells (MCs) was lower. It is crucial to delve into the complex mechanisms between CAFs and immune cells to find potential regulatory targets and may provide new evidence for subsequently targeted immunotherapy. These results suggest that the signature of the eight CAF-related genes is a powerful indicator for the assessment of the TIME of HNSCC. It may provide a new and reliable potential indicator for clinicians to predict the prognosis of HNSCC, which may be used to guide treatment and clinical decision-making in HNSCC patients. Meanwhile, CAF-related genes are expected to become tumor biomarkers and effective targets for HNSCC.

The NF-κB pathway plays a vital role in rat salivary gland atrophy model

Objective

The aim of this study was to explore the histopathological and genetic changes in the submandibular glands after duct ligation and provide important clues to functional regeneration.

Design

We established a rat salivary gland duct ligation model and observed pathological changes in the rat submandibular gland on day 1 and weeks 1, 2, 3, and 4 using hematoxylin and eosin staining, Alcian blue-periodic acid Schiff staining, Masson staining, terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL), and immunohistochemical staining. RNA sequencing was performed on normal salivary glands and those from the ligation model after 1 week. Significantly differentially expressed genes were selected, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed.

Results

Apoptosis levels and histological and functional KEGG pathway analyses showed that injury to the salivary gland after ligation gradually increased. The TGF-β pathway was activated and promoted fibrosis. RNA sequencing results and further verification of samples at week 1 showed that the NF-κB pathway plays a vital role in salivary gland atrophy.

Conclusions

Our results detailed the pathological changes in the submandibular gland after ligation and the important functions of the NF-κB pathway.

Immune gene patterns and characterization of the tumor immune microenvironment associated with cancer immunotherapy efficacy

Although immunotherapy has revolutionized cancer management, most patients do not derive benefits from it. Aiming to explore an appropriate strategy for immunotherapy efficacy prediction, we collected 6251 patients' transcriptome data from multicohort population and analyzed the data using a machine learning algorithm. In this study, we found that patients from three immune gene clusters had different overall survival when treated with immunotherapy (P < 0.001), and that these clusters had differential states of hypoxia scores and metabolism functions. The immune gene score showed good immunotherapy efficacy prediction (AUC was 0.737 at 20 months), which was well validated. The immune gene score, tumor mutation burden, and long non-coding RNA score were further combined to build a tumor immune microenvironment signature, which correlated more strongly with overall survival (AUC, 0.814 at 20 months) than when using a single variable. Thus, we recommend using the characterization of the tumor immune microenvironment associated with immunotherapy efficacy via a multi-omics analysis of cancer.

Transcriptomics secondary analysis of severe human infection with SARS-CoV-2 identifies gene expression changes and predicts three transcriptional biomarkers in leukocytes

SARS-CoV-2 is the causative agent of COVID-19, which has greatly affected human health since it first emerged. Defining the human factors and biomarkers that differentiate severe SARS-CoV-2 infection from mild infection has become of increasing interest to clinicians. To help address this need, we retrieved 269 public RNA-seq human transcriptome samples from GEO that had qualitative disease severity metadata. We then subjected these samples to a robust RNA-seq data processing workflow to calculate gene expression in PBMCs, whole blood, and leukocytes, as well as to predict transcriptional biomarkers in PBMCs and leukocytes. This process involved using Salmon for read mapping, edgeR to calculate significant differential expression levels, and gene ontology enrichment using Camera. We then performed a random forest machine learning analysis on the read counts data to identify genes that best classified samples based on the COVID-19 severity phenotype. This approach produced a ranked list of leukocyte genes based on their Gini values that includes TGFBI, TTYH2, and CD4, which are associated with both the immune response and inflammation. Our results show that these three genes can potentially classify samples with severe COVID-19 with accuracy of ∼88% and an area under the receiver operating characteristic curve of 92.6--indicating acceptable specificity and sensitivity. We expect that our findings can help contribute to the development of improved diagnostics that may aid in identifying severe COVID-19 cases, guide clinical treatment, and improve mortality rates.

MAPKAPK2-centric transcriptome profiling reveals its major role in governing molecular crosstalk of IGFBP2, MUC4, and PRKAR2B during HNSCC pathogenesis

Transcriptome analysis of head and neck squamous cell carcinoma (HNSCC) has been pivotal to comprehending the convoluted biology of HNSCC tumors. MAPKAPK2 or MK2 is a critical modulator of the mRNA turnover of crucial genes involved in HNSCC progression. However, MK2-centric transcriptome profiles of tumors are not well known. This study delves into HNSCC progression with MK2 at the nexus to delineate the biological relevance and intricate crosstalk of MK2 in the tumor milieu. We performed next-generation sequencing-based transcriptome profiling of HNSCC cells and xenograft tumors to ascertain mRNA expression profiles in MK2-wild type and MK2-knockdown conditions. The findings were validated using gene expression assays, immunohistochemistry, and transcript turnover studies. Here, we identified a pool of crucial MK2-regulated candidate genes by annotation and differential gene expression analyses. Regulatory network and pathway enrichment revealed their significance and involvement in the HNSCC pathogenesis. Additionally, 3'-UTR-based filtering recognized important MK2-regulated downstream target genes and validated them by nCounter gene expression assays. Finally, immunohistochemistry and transcript stability studies revealed the putative role of MK2 in regulating the transcript turnover of IGFBP2, MUC4, and PRKAR2B in HNSCC. Conclusively, MK2-regulated candidate genes were identified in this study, and their plausible involvement in HNSCC pathogenesis was elucidated. These genes possess investigative values as targets for diagnosis and therapeutic interventions for HNSCC.

Integrative network analysis reveals subtype-specific long non-coding RNA regulatory mechanisms in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSC) is one of most common malignancies with high mortality worldwide. Importantly, the molecular heterogeneity of HNSC complicates the clinical diagnosis and treatment, leading to poor overall survival outcomes. To dissect the complex heterogeneity, recent studies have reported multiple molecular subtyping systems. For instance, HNSC can be subdivided to four distinct molecular subtypes: atypical, basal, classical, and mesenchymal, of which the mesenchymal subtype is characterized by upregulated epithelial-mesenchymal transition (EMT) and associated with poorer survival outcomes. Despite a wealth of studies into the complex molecular heterogeneity, the regulatory mechanism specific to this aggressive subtype remain largely unclear. Herein, we developed a network-based bioinformatics framework that integrates lncRNA and mRNA expression profiles to elucidate the subtype-specific regulatory mechanisms. Applying the framework to HNSC, we identified a clinically relevant lncRNA LNCOG as a key master regulator mediating EMT underlying the mesenchymal subtype. Five genes with strong prognostic values, namely ANXA5, ITGA5, CCBE1, P4HA2, and EPHX3, were predicted to be the putative targets of LNCOG and subsequently validated in other independent datasets. By integrative analysis of the miRNA expression profiles, we found that LNCOG may act as a ceRNA to sponge miR-148a-3p thereby upregulating ITGA5 to promote HNSC progression. Furthermore, our drug sensitivity analysis demonstrated that the five putative targets of LNCOG were also predictive of the sensitivities of multiple FDA-approved drugs. In summary, our bioinformatics framework facilitates the dissection of cancer subtype-specific lncRNA regulatory mechanisms, providing potential novel biomarkers for more optimized treatment of HNSC.

Integration of genomic variants and bioinformatic-based approach to drive drug repurposing for multiple sclerosis

Multiple sclerosis (MS) is a chronic autoimmune disease in the central nervous system (CNS) marked by inflammation, demyelination, and axonal loss. Currently available MS medication is limited, thereby calling for a strategy to accelerate new drug discovery. One of the strategies to discover new drugs is to utilize old drugs for new indications, an approach known as drug repurposing. Herein, we first identified 421 MS-associated SNPs from the Genome-Wide Association Study (GWAS) catalog (p-value < 5 × 10-8), and a total of 427 risk genes associated with MS using HaploReg version 4.1 under the criterion r 2  > 0.8. MS risk genes were then prioritized using bioinformatics analysis to identify biological MS risk genes. The prioritization was performed based on six defined categories of functional annotations, namely missense mutation, cis-expression quantitative trait locus (cis-eQTL), molecular pathway analysis, protein-protein interaction (PPI), genes overlap with knockout mouse phenotype, and primary immunodeficiency (PID). A total of 144 biological MS risk genes were found and mapped into 194 genes within an expanded PPI network. According to the DrugBank and the Therapeutic Target Database, 27 genes within the list targeted by 68 new candidate drugs were identified. Importantly, the power of our approach is confirmed with the identification of a known approved drug (dimethyl fumarate) for MS. Based on additional data from ClinicalTrials.gov, eight drugs targeting eight distinct genes are prioritized with clinical evidence for MS disease treatment. Notably, CD80 and CD86 pathways are promising targets for MS drug repurposing. Using in silico drug repurposing, we identified belatacept as a promising MS drug candidate. Overall, this study emphasized the integration of functional genomic variants and bioinformatic-based approach that reveal important biological insights for MS and drive drug repurposing efforts for the treatment of this devastating disease.

From sequence to function through structure: Deep learning for protein design

The process of designing biomolecules, in particular proteins, is witnessing a rapid change in available tooling and approaches, moving from design through physicochemical force fields, to producing plausible, complex sequences fast via end-to-end differentiable statistical models. To achieve conditional and controllable protein design, researchers at the interface of artificial intelligence and biology leverage advances in natural language processing (NLP) and computer vision techniques, coupled with advances in computing hardware to learn patterns from growing biological databases, curated annotations thereof, or both. Once learned, these patterns can be used to provide novel insights into mechanistic biology and the design of biomolecules. However, navigating and understanding the practical applications for the many recent protein design tools is complex. To facilitate this, we 1) document recent advances in deep learning (DL) assisted protein design from the last three years, 2) present a practical pipeline that allows to go from de novo-generated sequences to their predicted properties and web-powered visualization within minutes, and 3) leverage it to suggest a generated protein sequence which might be used to engineer a biosynthetic gene cluster to produce a molecular glue-like compound. Lastly, we discuss challenges and highlight opportunities for the protein design field.

Immunopeptidome of hepatocytes isolated from patients with HBV infection and hepatocellular carcinoma

Background & Aims

Antigen-specific immunotherapy is a promising strategy to treat HBV infection and hepatocellular carcinoma (HCC). To facilitate killing of malignant and/or infected hepatocytes, it is vital to know which T cell targets are presented by human leucocyte antigen (HLA)-I complexes on patient-derived hepatocytes. Here, we aimed to reveal the hepatocyte-specific HLA-I peptidome with emphasis on peptides derived from HBV proteins and tumour-associated antigens (TAA) to guide development of antigen-specific immunotherapy.

Methods

Primary human hepatocytes were isolated with high purity from (HBV-infected) non-tumour and HCC tissues using a newly designed perfusion-free procedure. Hepatocyte-derived HLA-bound peptides were identified by unbiased mass spectrometry (MS), after which source proteins were subjected to Gene Ontology and pathway analysis. HBV antigen and TAA-derived HLA peptides were searched for using targeted MS, and a selection of peptides was tested for immunogenicity.

Results

Using unbiased data-dependent acquisition (DDA), we acquired a high-quality HLA-I peptidome of 2 × 10⁵ peptides that contained 8 HBV-derived peptides and 14 peptides from 8 known HCC-associated TAA that were exclusive to tumours. Of these, 3 HBV- and 12 TAA-derived HLA peptides were detected by targeted MS in the sample they were originally identified in by DDA. Moreover, 2 HBV- and 2 TAA-derived HLA peptides were detected in samples in which no identification was made using unbiased MS. Finally, immunogenicity was demonstrated for 5 HBV-derived and 3 TAA-derived peptides.

Conclusions

We present a first HLA-I immunopeptidome of isolated primary human hepatocytes, devoid of immune cells. Identified HBV-derived and TAA-derived peptides directly aid development of antigen-specific immunotherapy for chronic HBV infection and HCC. The described methodology can also be applied to personalise immunotherapeutic treatment of liver diseases in general.

Lay summary

Immunotherapy that aims to induce immune responses against a virus or tumour is a promising novel treatment option to treat chronic HBV infection and liver cancer. For the design of successful therapy, it is essential to know which fragments (i.e. peptides) of virus-derived and tumour-specific proteins are presented to the T cells of the immune system by diseased liver cells and are thus good targets for immunotherapy. Here, we have isolated liver cells from patients who have chronic HBV infection and/or liver cancer, analysed what peptides are presented by these cells, and assessed which peptides are able to drive immune responses.

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We developed a perfusion-free method to isolate primary hepatocytes that are depleted of immune cells.

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We derived a large-scale unbiased hepatocyte HLA ligandome from patients with HBV and/or HCC.

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The ligandome included peptides derived from HBV proteins and tumour-associated antigens (TAA).

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Using a targeted MS regime, the detection sensitivity of several HBV and TAA-derived peptides could be increased.

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Immunogenicity was demonstrated for a selection of TAA- and HBV-derived HLA peptides.

Organophosphate esters cause thyroid dysfunction via multiple signaling pathways in zebrafish brain

Organophosphate esters (OPEs) are widespread in various environmental media, and can disrupt thyroid endocrine signaling pathways. Mechanisms by which OPEs disrupt thyroid hormone (TH) signal transduction are not fully understood. Here, we present in vivo-in vitro-in silico evidence establishing OPEs as environmental THs competitively entering the brain to inhibit growth of zebrafish via multiple signaling pathways. OPEs can bind to transthyretin (TTR) and thyroxine-binding globulin, thereby affecting the transport of TH in the blood, and to the brain by TTR through the blood-brain barrier. When GH3 cells were exposed to OPEs, cell proliferation was significantly inhibited given that OPEs are competitive inhibitors of TH. Cresyl diphenyl phosphate was shown to be an effective antagonist of TH. Chronic exposure to OPEs significantly inhibited the growth of zebrafish by interfering with thyroperoxidase and thyroglobulin to inhibit TH synthesis. Based on comparisons of modulations of gene expression with the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, signaling pathways related to thyroid endocrine functions, such as receptor-ligand binding and regulation of hormone levels, were identified as being affected by exposure to OPEs. Effects were also associated with the biosynthesis and metabolism of lipids, and neuroactive ligand-receptor interactions. These findings provide a comprehensive understanding of the mechanisms by which OPEs disrupt thyroid pathways in zebrafish.

Interaction between mono-(2-ethylhexyl) phthalate and retinoic acid alters Sertoli cell development during fetal mouse testis cord morphogenesis

Phthalic acid esters (phthalates) are a class of industrial chemicals that cause developmental and reproductive toxicity, but there are significant gaps in knowledge of phthalate toxicity mechanisms. There is evidence that phthalates disrupt retinoic acid signaling in the fetal testis, potentially disrupting control of spatial and temporal patterns of testis development. Our goal was to determine how a phthalate would interact with retinoic acid signaling during fetal mouse testis development. We hypothesized that mono-(2-ethylhexyl) phthalate (MEHP) would exacerbate the adverse effect of all-trans retinoic acid (ATRA) on seminiferous cord development in the mouse fetal testis. To test this hypothesis, gestational day (GD) 14 C57BL/6 mouse testes were isolated and cultured on media containing MEHP, ATRA, or a combination of both compounds. Cultured testes were collected for global transcriptome analysis after one day in culture and for histology and immunofluorescent analysis of Sertoli cell differentiation after three days in culture. ATRA disrupted seminiferous cord morphogenesis and induced aberrant FOXL2 expression. MEHP alone had no significant effect on cord development, but combined exposure to MEHP and ATRA increased the number of FOXL2-positive cells, reduced seminiferous cord number, and increased testosterone levels, beyond the effect of ATRA alone. In RNA-seq analysis, ATRA treatment and MEHP treatment resulted in differential expression of genes 510 and 134 genes, respectively, including 70 common differentially expressed genes (DEGs) between the two treatments, including genes with known roles in fetal testis development. MEHP DEGs included RAR target genes, genes involved in angiogenesis, and developmental patterning genes, including members of the homeobox superfamily. These results support the hypothesis that MEHP modulates retinoic acid signaling in the mouse fetal testis and provide insight into potential mechanisms by which phthalates disrupt seminiferous cord morphogenesis.

Identifies microtubule-binding protein CSPP1 as a novel cancer biomarker associated with ferroptosis and tumor microenvironment

Centrosome and spindle pole-associated protein (CSPP1) is a centrosome and microtubule-binding protein that plays a role in cell cycle-dependent cytoskeleton organization and cilia formation. Previous studies have suggested that CSPP1 plays a role in tumorigenesis; however, no pan-cancer analysis has been performed. This study systematically investigates the expression of CSPP1 and its potential clinical outcomes associated with diagnosis, prognosis, and therapy. CSPP1 is widely present in tissues and cells and its aberrant expression serves as a diagnostic biomarker for cancer. CSPP1 dysregulation is driven by multi-dimensional mechanisms involving genetic alterations, DNA methylation, and miRNAs. Phosphorylation of CSPP1 at specific sites may play a role in tumorigenesis. In addition, CSPP1 correlates with clinical features and outcomes in multiple cancers. Take brain low-grade gliomas (LGG) with a poor prognosis as an example, functional enrichment analysis implies that CSPP1 may play a role in ferroptosis and tumor microenvironment (TME), including regulating epithelial-mesenchymal transition, stromal response, and immune response. Further analysis confirms that CSPP1 dysregulates ferroptosis in LGG and other cancers, making it possible for ferroptosis-based drugs to be used in the treatment of these cancers. Importantly, CSPP1-associated tumors are infiltrated in different TMEs, rendering immune checkpoint blockade therapy beneficial for these cancer patients. Our study is the first to demonstrate that CSPP1 is a potential diagnostic and prognostic biomarker associated with ferroptosis and TME, providing a new target for drug therapy and immunotherapy in specific cancers.

Violations of proportional hazard assumption in Cox regression model of transcriptomic data in TCGA pan-cancer cohorts

Background

Cox proportional hazard regression (CPH) model relies on the proportional hazard (PH) assumption: the hazard of variables is independent of time. CPH has been widely used to identify prognostic markers of the transcriptome. However, the comprehensive investigation on PH assumption in transcriptomic data has lacked.

Results

The whole transcriptomic data of the 9,056 patients from 32 cohorts of The Cancer Genome Atlas and the 3 lung cancer cohorts from Gene Expression Omnibus were collected to construct CPH model for each gene separately for fitting the overall survival. An average of 8.5% gene CPH models violated the PH assumption in TCGA pan-cancer cohorts. In the gene interaction networks, both hub and non-hub genes in CPH models were likely to have non-proportional hazards. Violations of PH assumption for the same gene models were not consistent in 5 non-small cell lung cancer datasets (all kappa coefficients < 0.2), indicating that the non-proportionality of gene CPH models depended on the datasets. Furthermore, the introduction of log(t) or sqrt(t) time-functions into CPH improved the performance of gene models on overall survival fitting in most tumors. The time-dependent CPH changed the significance of log hazard ratio of the 31.9% gene variables.

Conclusions

Our analysis resulted that non-proportional hazards should not be ignored in transcriptomic data. Introducing time interaction term ameliorated performance and interpretability of non-proportional hazards of transcriptome data in CPH.

MicroRNAs based regulation of cytokine regulating immune expressed genes and their transcription factors in COVID-19

Background

Coronavirus disease 2019 is characterized by the elevation of a broad spectrum of inflammatory mediators associated with poor disease outcomes. We aimed at an in-silico analysis of regulatory microRNA and their transcription factors (TF) for these inflammatory genes that may help to devise potential therapeutic strategies in the future.

Methods

The cytokine regulating immune-expressed genes (CRIEG) were sorted from literature and the GEO microarray dataset. Their co-differentially expressed miRNA and transcription factors were predicted from publicly available databases. Enrichment analysis was done through mienturnet, MiEAA, Gene Ontology, and pathways predicted by KEGG and Reactome pathways. Finally, the functional and regulatory features were analyzed and visualized through Cytoscape.

Results

Sixteen CRIEG were observed to have a significant protein-protein interaction network. The ontological analysis revealed significantly enriched pathways for biological processes, molecular functions, and cellular components. The search performed in the miRNA database yielded ten miRNAs that are significantly involved in regulating these genes and their transcription factors.

Conclusion

An in-silico representation of a network involving miRNAs, CRIEGs, and TF, which take part in the inflammatory response in COVID-19, has been elucidated. Thus, these regulatory factors may have potentially critical roles in the inflammatory response in COVID-19 and may be explored further to develop targeted therapeutic strategies and mechanistic validation.

Ablation of liver Fxr results in an increased colonic mucus barrier in mice

Background & Aims

The interorgan crosstalk between the liver and the intestine has been the focus of intense research. Key in this crosstalk are bile acids, which are secreted from the liver into the intestine, interact with the microbiome, and upon absorption reach back to the liver. The bile acid-activated farnesoid X receptor (Fxr) is involved in the gut-to-liver axis. However, liver-to-gut communication and the roles of bile acids and Fxr remain elusive. Herein, we aim to get a better understanding of Fxr-mediated liver-to-gut communication, particularly in colon functioning.

Methods

Fxr floxed/floxed mice were crossed with cre-expressing mice to yield Fxr ablation in the intestine (Fxr-intKO), liver (Fxr-livKO), or total body (Fxr-totKO). The effects on colonic gene expression (RNA sequencing), the microbiome (16S sequencing), and mucus barrier function by ex vivo imaging were analysed.

Results

Despite relatively small changes in biliary bile acid concentration and composition, more genes were differentially expressed in the colons of Fxr-livKO mice than in those of Fxr-intKO and Fxr-totKO mice (3272, 731, and 1824, respectively). The colons of Fxr-livKO showed increased expression of antimicrobial genes, Toll-like receptors, inflammasome-related genes and genes belonging to the ‘Mucin-type O-glycan biosynthesis’ pathway. Fxr-livKO mice have a microbiome profile favourable for the protective capacity of the mucus barrier. The thickness of the inner sterile mucus layer was increased and colitis symptoms reduced in Fxr-livKO mice.

Conclusions

Targeting of FXR is at the forefront in the battle against metabolic diseases. We show that ablation of Fxr in the liver greatly impacts colonic gene expression and increased the colonic mucus barrier. Increasing the mucus barrier is of utmost importance to battle intestinal diseases such as inflammatory bowel disease, and we show that this might be done by antagonising FXR in the liver.

Lay summary

This study shows that the communication of the liver to the intestine is crucial for intestinal health. Bile acids are key players in this liver-to-gut communication, and when Fxr, the master regulator of bile acid homoeostasis, is ablated in the liver, colonic gene expression is largely affected, and the protective capacity of the mucus barrier is increased.

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Fxr ablation in the mouse liver has a major impact on colonic gene expression.

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Fxr signalling is induced in the colons of liver Fxr knockout (Fxr-livKO) mice.

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In Fxr-livKO colons, expression of antimicrobial and mucus genes is increased.

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Microbiome of Fxr-livKO mice is indicative of enhanced mucus barrier function.

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Fxr-livKO mice have an increased mucus barrier.

Identifying key genes and screening therapeutic agents associated with diabetes mellitus and HCV-related hepatocellular carcinoma by bioinformatics analysis

Objective

Incidence of both Type 2 diabetes mellitus (T2DM) and hepatocellular carcinoma (HCC) are rapidly increasing worldwide. One of the leading causes of HCC is hepatitis C virus (HCV), which is a resource of blood-borne viral infection. HCV increases the risk for HCC probably by promoting fibrosis and cirrhosis. Association among T2DM and HCV related HCC remains significant, indicating that such association is clinically reliable and robust. Lawson was the first who uncovered HCC in person suffered from T2DM. Until now, genetic association between HCV related HCC and T2DM is poorly known. Current work was designed to figure out the molecular mechanisms of both diseases by identifying the hub genes and therapeutic drugs using integrated bioinformatics analysis.

Methods

Four microarray datasets were downloaded from GEO database and analyzed using R in order to obtain different expressed genes (DEGs). Protein–protein interaction (PPI) networks was constructed using STRING tool and visualized by Cytoscape. Moreover, hub genes were identified on the basis of their degree of connectivity. Finally, Networkanalyst and DGIdb were used for the identification of transcription factors (TFs) and selection of candidate drugs, respectively.

Results

A total of 53 DEGs were identified, of which 41 were upregulated genes and 12 were downregulated genes. PPI network obtained from STRING were subjected to Cytoscape plugin cytoHubba, and top 10 genes (AURKA, JUN, AR, MELK, NCOA2, CENPF, NCAPG, PCK1, RAD51AP1, and GTSE1) were chosen as the target hub genes based on the highest degree of connectivity. Furthermore, 47 drugs of AURKA, JUN, AR, MELK, and NCOA2 were found having therapeutic potential to treat HCV-HCC in patients with T2DM.

Conclusion

This study updates the information and yield a new perspective in context of understanding the pathogenesis and development of HCV related HCC in affected persons with T2DM. In vivo and in vitro investigation of hub genes and pathway interaction is essential to delineate the specific roles of the novel hub genes, which may help to reveal the genetic association between HCV-HCC and T2DM. In future, hub genes along with their candidate drugs might be capable of improving the personalized detection and therapies for both diseases.

MCDB: A comprehensive curated mitotic catastrophe database for retrieval, protein sequence alignment, and target prediction

Mitotic catastrophe (MC) is a form of programmed cell death induced by mitotic process disorders, which is very important in tumor prevention, development, and drug resistance. Because rapidly increased data for MC is vigorously promoting the tumor-related biomedical and clinical study, it is urgent for us to develop a professional and comprehensive database to curate MC-related data. Mitotic Catastrophe Database (MCDB) consists of 1214 genes/proteins and 5014 compounds collected and organized from more than 8000 research articles. Also, MCDB defines the confidence level, classification criteria, and uniform naming rules for MC-related data, which greatly improves data reliability and retrieval convenience. Moreover, MCDB develops protein sequence alignment and target prediction functions. The former can be used to predict new potential MC-related genes and proteins, and the latter can facilitate the identification of potential target proteins of unknown MC-related compounds. In short, MCDB is such a proprietary, standard, and comprehensive database for MC-relate data that will facilitate the exploration of MC from chemists to biologists in the fields of medicinal chemistry, molecular biology, bioinformatics, oncology and so on. The MCDB is distributed on http://www.combio-lezhang.online/MCDB/index_html/.

Autophagy-mediated reduction of miR-345 contributes to hepatic cystogenesis in polycystic liver disease

Background & Aims

Polycystic liver disease (PLD) is characterised by increased autophagy and reduced miRNA levels in cholangiocytes. Given that autophagy has been implicated in miRNA regulation, we tested the hypothesis that increased autophagy accounts for miRNA reduction in PLD cholangiocytes (PLDCs) and accelerated hepatic cystogenesis.

Methods

We assessed miRNA levels in cultured normal human cholangiocytes (NHCs), PLDCs, and isolated PLDC autophagosomes by miRNA-sequencing (miRNA-seq), and miRNA targets by mRNA-seq. Levels of miR-345 and miR-345-targeted proteins in livers of animals and humans with PLD, in NHCs and PLDCs, and in PLDCs transfected with pre-miR-345 were assessed by in situ hybridisation (ISH), quantitative PCR, western blotting, and fluorescence confocal microscopy. We also assessed cell proliferation and cyst growth in vitro, and hepatic cystogenesis in vivo.

Results

In total, 81% of miRNAs were decreased in PLDCs, with levels of 10 miRNAs reduced by more than 10 times; miR-345 was the most-reduced miRNA. In silico analysis and luciferase reporter assays showed that miR-345 targets included cell-cycle and cell-proliferation-related genes [i.e. cell division cycle 25A (CDC25A), cyclin-dependent kinase 6 (CDK6), E2F2, and proliferating cell nuclear antigen (PCNA)]; levels of 4 studied miR-345 targets were increased in PLDCs at both the mRNA and protein levels. Transfection of PLDCs with pre-miR-345 increased miR-345 and decreased the expression of miR-345-targeted proteins, cell proliferation, and cyst growth in vitro. MiR-345 accumulated in autophagosomes in PLDCs but not NHCs. Inhibition of autophagy increased miR-345 levels, decreased the expression of miR-345-targeted proteins, and reduced hepatic cystogenesis in vitro and in vivo.

Conclusion

Autophagy-mediated reduction of miR-345 in PLDCs (i.e. miRNAutophagy) accelerates hepatic cystogenesis. Inhibition of autophagy restores miR-345 levels, decreases cyst growth, and is beneficial for PLD.

Lay summary

Polycystic liver disease (PLD) is an incurable genetic disorder characterised by the progressive growth of hepatic cysts. We found that hepatic cystogenesis is increased when the levels of miR-345 in PLD cholangiocytes (PLDCs) are reduced by autophagy. Restoration of miR-345 in PLDCs via inhibition of autophagy decreases hepatic cystogenesis and thus, is beneficial for PLD.

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The miRNA profile is altered in PLD.

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MiR-345 is the most-reduced miRNA in PLDCs.

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The reduction of miR-345 increases PLDC proliferation and hepatic cystogenesis.

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MiR-345 in PLDCs is regulated by autophagy, termed ‘miRNAutophagy’.

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Restoration of miR-345 in PLDC is beneficial for PLD.

MicroRNA-regulated transcriptome analysis identifies four major subtypes with prognostic and therapeutic implications in prostate cancer

MicroRNA (miRNA) deregulation plays a critical role in the heterogeneous development of prostate cancer (PCa) by tuning mRNA levels. Herein, we aimed to characterize the molecular features of PCa by clustering the miRNA-regulated transcriptome with non-negative matrix factorization. Using 478 PCa samples from The Cancer Genome Atlas, four molecular subtypes (S-I, S-II, S-III, and S-IV) were identified and validated in two merged microarray and RNAseq datasets with 656 and 252 samples, respectively. Interestingly, the four subtypes showed distinct clinical and biological features after comprehensive analyses of clinical features, multiomic profiles, immune infiltration, and drug sensitivity. S-I is basal/stem/mesenchymal-like and immune-excluded with marked transforming growth factor β, epithelial-mesenchymal transition and hypoxia signals, increased sensitivity to olaparib, and intermediate prognosis. S-II is luminal/metabolism-active and responsive to androgen deprivation therapy with frequent TMPRSS2-ERG fusion and a good prognosis. S-III is characterized by moderate proliferative and metabolic activity, sensitivity to taxane-based chemotherapy, and intermediate prognosis. S-IV is highly proliferative with moderate EMT and stemness, frequent deletions of TP53, PTEN and RB, and the poorest prognosis; it is also immune-inflamed and sensitive to anti-PD-L1 therapy. Overall, based on miRNA-regulated gene profiles, this study identified four distinct PCa subtypes that could improve risk stratification at diagnosis and provide therapeutic guidance.

A review on machine learning approaches and trends in drug discovery

Drug discovery aims at finding new compounds with specific chemical properties for the treatment of diseases. In the last years, the approach used in this search presents an important component in computer science with the skyrocketing of machine learning techniques due to its democratization. With the objectives set by the Precision Medicine initiative and the new challenges generated, it is necessary to establish robust, standard and reproducible computational methodologies to achieve the objectives set. Currently, predictive models based on Machine Learning have gained great importance in the step prior to preclinical studies. This stage manages to drastically reduce costs and research times in the discovery of new drugs. This review article focuses on how these new methodologies are being used in recent years of research. Analyzing the state of the art in this field will give us an idea of where cheminformatics will be developed in the short term, the limitations it presents and the positive results it has achieved. This review will focus mainly on the methods used to model the molecular data, as well as the biological problems addressed and the Machine Learning algorithms used for drug discovery in recent years.

YPIBP: A repository for phosphoinositide-binding proteins in yeast

Phosphoinositides (PIs) are a family of eight lipids consisting of phosphatidylinositol (PtdIns) and its seven phosphorylated forms. PIs have important regulatory functions in the cell including lipid signaling, protein transport, and membrane trafficking. Yeast has been recognized as a eukaryotic model system to study lipid-protein interactions. Hundreds of yeast PI-binding proteins have been identified, but this research knowledge remains scattered. Besides, the complete PI-binding spectrum and potential PI-binding domains have not been interlinked. No comprehensive databases are available to support the lipid-protein interaction research on phosphoinositides. Here we constructed the first knowledgebase of Yeast Phosphoinositide-Binding Proteins (YPIBP), a repository consisting of 679 PI-binding proteins collected from high-throughput proteome-array and lipid-array studies, QuickGO, and a rigorous literature mining. The YPIBP also contains protein domain information in categories of lipid-binding domains, lipid-related domains and other domains. The YPIBP provides search and browse modes along with two enrichment analyses (PI-binding enrichment analysis and domain enrichment analysis). An interactive visualization is given to summarize the PI-domain-protein interactome. Finally, three case studies were given to demonstrate the utility of YPIBP. The YPIBP knowledgebase consolidates the present knowledge and provides new insights of the PI-binding proteins by bringing comprehensive and in-depth interaction network of the PI-binding proteins. YPIBP is available at http://cosbi7.ee.ncku.edu.tw/YPIBP/.

A bioinformatics approach for identifying potential molecular mechanisms and key genes involved in COVID-19 associated cardiac remodeling

In 2019 coronavirus disease (COVID-19), whose main complication is respiratory involvement, different organs may also be affected in severe cases. However, COVID-19 associated cardiovascular manifestations are limited at present. The main purpose of this study was to identify potential candidate genes involved in COVID-19-associated heart damage by bioinformatics analysis. Differently expressed genes (DEGs) were identified using transcriptome profiles (GSE150392 and GSE4172) downloaded from the GEO database. After gene and pathway enrichment analyses, PPI network visualization, module analyses, and hub gene extraction were performed using Cytoscape software. A total of 228 (136 up and 92 downregulated) overlapping DEGs were identified at these two microarray datasets. Finally, the top hub genes (FGF2, JUN, TLR4, and VEGFA) were screened out as the critical genes among the DEGs from the PPI network. Identification of critical genes and mechanisms in any disease can lead us to better diagnosis and targeted therapy. Our findings identified core genes shared by inflammatory cardiomyopathy and SARS-CoV-2. The findings of the current study support the idea that these key genes can be used in understanding and managing the long-term cardiovascular effects of COVID-19.

Gene expression analysis of MCF7 cell lines of breast cancer treated with herbal extract of Cissampelos pareira revealed association with viral diseases

BACKGROUND

It is necessary to assess the cellular, molecular, and pathogenetic characteristics of COVID-19 and attention is required to understand highly effective gene targets and mechanisms. In this study, we suggest understandings into the fundamental pathogenesis of COVID-19 through gene expression analyses using the microarray data set GSE156445 publicly reachable at NIH/NCBI Gene Expression Omnibus database. The data set consists of MCF7 which is a human breast cancer cell line with estrogen, progesterone and glucocorticoid receptors. The cell lines treated with different quantities of Cissampelos pareira (Cipa). Cipa is a traditional medicinal plant which would possess an antiviral potency in preventing viral diseases such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

METHODS

Utilizing Biobase, GEOquery, gplots packages in R studio, the differentially expressed genes (DEGs) were identified. The gene ontology (GO) of pathway enrichments employed by utilizing DAVID and KEGG enrichment analyses were studied. We further constructed a human protein-protein interaction (PPI) network and performed, based upon that, a subnetwork module analysis for significant signaling pathways.

RESULTS

The study identified 418 differentially expressed genes (DEGs) using bioinformatics tools. The gene ontology of pathway enrichments employed by GO and KEGG enrichment analyses of down-regulated and up-regulated DEGs were studied. Gene expression analysis utilizing gene ontology and KEGG results uncovered biological and signaling pathways such as "cell adhesion molecules", "plasma membrane adhesion molecules", "synapse assembly", and "Interleukin-3-mediated signaling" which are mostly linked to COVID-19. Our results provide in silico evidence for candidate genes which are vital for the inhibition, adhesion, and encoding cytokine protein including LYN, IGFBP5, IL-1R1, and IL-13RA1 that may have strong biomarker potential for infectious diseases such as COVID-19 related therapy targets.

Multi-omics approaches identify SF3B3 and SIRT3 as candidate autophagic regulators and druggable targets in invasive breast carcinoma

Autophagy is a critical cellular homeostatic mechanism, and its dysfunction is linked to invasive breast carcinoma (BRCA). Recently, several omics methods have been applied to explore autophagic regulators in BRCA; however, more reliable and robust approaches for identifying crucial regulators and druggable targets remain to be discovered. Thus, we report here the results of multi-omics approaches to identify potential autophagic regulators in BRCA, including gene expression (EXP), DNA methylation (MET) and copy number alterations (CNAs) from The Cancer Genome Atlas (TCGA). Newly identified candidate genes, such as SF3B3, TRAPPC10, SIRT3, MTERFD1, and FBXO5, were confirmed to be involved in the positive or negative regulation of autophagy in BRCA. SF3B3 was identified firstly as a negative autophagic regulator, and siRNA/shRNA-SF3B3 were shown to induce autophagy-associated cell death in in vitro and in vivo breast cancer models. Moreover, a novel small-molecule activator of SIRT3, 1-methylbenzylamino amiodarone, was discovered to induce autophagy in vitro and in vivo. Together, these results provide multi-omics approaches to identify some key candidate autophagic regulators, such as the negative regulator SF3B3 and positive regulator SIRT3 in BRCA, and highlight SF3B3 and SIRT3 as new druggable targets that could be used to fill the gap between autophagy and cancer drug development.

Network pharmacology-based analysis of the role of tacrolimus in liver transplantation

Background

Tacrolimus is a powerful immunosuppressant and has been widely used in organ transplantation. In order to further explore the role of tacrolimus in liver transplantation, we conducted network pharmacology analysis.

Methods

GSE100155 was obtained from the GEO database, and the DEGs of liver transplantation were analyzed. The 2D structure of tacrolimus was obtained from the National Library of Medicine, and the pharmacophore model of tacrolimus was predicted using the online tool pharmmapper. Then a network of tacrolimus and target genes was constructed through network pharmacology, and visualization and GO enrichment analysis was performed through Cytoscape. In addition, we also analyzed the correlation between key genes and immune infiltrating cells. The data of GSE84908 was used to verify the changes of key gene expression levels after tacrolimus treatment.

Results

The results of network pharmacological analysis showed that tacrolimus had 43 target genes, and the GO enrichment results showed many potential functions. Further analysis found that there were 5 key target genes in DEGs, and these 5 genes were significantly down-regulated in liver transplant patients. Another important finding was that 5 genes were significantly related to some immune infiltrating cells. The results of the GSE84908 data analysis showed that after tacrolimus treatment, the expression of DAAM1 was significantly increased (p = 0.015).

Conclusion

Tacrolimus may inhibit the human immune response by affecting the expression of DAAM1 in liver transplant patients.

Network pharmacology-based analysis of Zukamu granules for the treatment of COVID-19

Introduction

Zukamu granules may play a potential role in the fight against the Coronavirus, COVID-19. The purpose of this study was to explore the mechanisms of Zukamu granules using network pharmacology combined with molecular docking.

Methods

The Traditional Chinese Medicine systems pharmacology (TCMSP) database was used to filter the active compounds and the targets of each drug in the prescription. The Genecards and OMIM databases were used for identifying the targets related to COVID-19. The STRING database was used to analyze the intersection targets. Compound - target interaction and protein-protein interaction networks were constructed using Cytoscape to decipher the anti-COVID-19 mechanisms of action of the prescription. The Kyoto Encyclopedia of Genes and Genome (KEGG) pathway and Gene Ontology (GO) enrichment analysis was performed to investigate the molecular mechanisms of action. Finally, the interaction between the targets and the active compounds was verified by molecular docking technology.

Results

A total of 66 targets were identified. Further analysis identified 10 most important targets and 12 key compounds. Besides, 1340 biological processes, 43 cell compositions, and 87 molecular function items were obtained (P < 0.05). One hundred and thirty pathways were obtained (P < 0.05). The results of molecular docking showed that there was a stable binding between the active compounds and the targets.

Conclusion

Analysis of the constructed pharmacological network results allowed for the prediction and interpretation of the multi-constituent, multi-targeted, and multi-pathway mechanisms of Zukamu granules as a potential source for supportive treatment of COVID-19.

Can network pharmacology identify the anti-virus and anti- inflammatory activities of Shuanghuanglian oral liquid used in Chinese medicine for respiratory tract infection?

Introduction

Shuanghuanglian (SHL) oral liquid is a well-known traditional Chinese medicine preparation administered for respiratory tract infections in China. However, the underlying pharmacological mechanisms remain unclear. The present study aims to determine the potential pharmacological mechanisms of SHL oral liquid based on network pharmacology.

Methods

A network pharmacology-based strategy including collection and analysis of putative compounds and target genes, network construction, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Gene Ontology (GO) enrichment, identification of key compounds and target genes, and molecule docking was performed in this study.

Results

A total of 82 bioactive compounds and 226 putative target genes of SHL oral liquid were collected. Of note, 28 hub target genes including 4 major hub target genes: estrogen receptor 1 (ESR1), nuclear receptor coactivator 2 (NCOA2), nuclear receptor coactivator 1 (NCOA1), androgen receptor (AR) and 5 key compounds (quercetin, luteolin, baicalein, kaempferol and wogonin) were identified based on network analysis. The hub target genes mainly enriched in pathways including PI3K-Akt signaling pathway, human cytomegalovirus infection, and human papillomavirus infection, which could be the underlying pharmacological mechanisms of SHL oral liquid for treating diseases. Moreover, the key compounds had great molecule docking binding affinity with the major hub target genes.

Conclusion

Using network pharmacology analysis, SHL oral liquid was found to contain anti-virus, anti-inflammatory, and “multi-compounds and multi-targets” with therapeutic actions. These findings may provide a valuable direction for further clinical application and research.

Whole-exome mutational landscape of metastasis in patient-derived hepatocellular carcinoma cells

In order to explore the genomic basis for liver cancer metastasis, whole-exome sequencing (WES) was performed on patient-derived hepatocellular carcinoma (HCC) cell lines with differential metastatic potentials and analyzed their clonal evolution relationships. An evolutionary tree based on genomic single nucleotide polymorphism (SNP) was constructed in MegaX software. The WES data showed that the average percentage of heterogeneous mutations in each HCC cell lines was 16.55% (range, 15.38%–18.17%). C: G > T: A and T: A > C: G somatic transitions were the two most frequent substitutions. In these metastatic HCC cell lines, non-silent gene mutations were found in 21.88% of known driver genes and 10 classical signaling pathways. The protein interaction network was constructed by STRING, and hub genes were found in the shared trunk mutation genes and the heterogeneous branch mutations respectively. In cBioPortal database, some of the selected hub genes were found to be associated with poor overall survival (OS) of HCC patients. Among the mutated HCC driver genes, a novel KEAP1 mutation with a homozygous frameshift truncation at the c-terminal Nrf2 binding region was detected and verified in MHCC97-H and HCC97LM3 cells. In conclusion, WES data demonstrate that HCC cell lines from tumor biopsy specimens of the same patient have obtained different metastatic potentials through repeated selection in rodents in vivo, and they do indeed have a genetic relationship at the genomic level.

RNA-seq data analysis of stimulated hepatocellular carcinoma cells treated with epigallocatechin gallate and fisetin reveals target genes and action mechanisms

Hepatocellular carcinoma (HCC) is an essentially incurable inflammation-related cancer. We have previously shown by network analysis of proteomic data that the flavonoids epigallocatechin gallate (EGCG) and fisetin (FIS) efficiently downregulated pro-tumor cytokines released by HCC through inhibition of Akt/mTOR/RPS6 phospho-signaling. However, their mode of action at the global transcriptome level remains unclear. Herein, we endeavor to compare gene expression alterations mediated by these compounds through a comprehensive transcriptome analysis based on RNA-seq in HEP3B, a responsive HCC cell line, upon perturbation with a mixture of prototypical stimuli mimicking conditions of tumor microenvironment or under constitutive state.

Analysis of RNA-seq data revealed extended changes on HEP3B transcriptome imposed by test nutraceuticals. Under stimulated conditions, EGCG and FIS significantly modified, compared to the corresponding control, the expression of 922 and 973 genes, respectively, the large majority of which (695 genes), was affected by both compounds. Hierarchical clustering based on the expression data of shared genes demonstrated an almost identical profile in nutraceutical-treated stimulated cells which was virtually opposite in cells exposed to stimuli alone. Downstream enrichment analyses of the co-modified genes uncovered significant associations with cancer-related transcription factors as well as terms of Gene Ontology/Reactome Pathways and highlighted ECM dynamics as a nodal modulation point by nutraceuticals along with angiogenesis, inflammation, cell motility and growth. RNA-seq data for selected genes were independently confirmed by RT-qPCR.

Overall, the present systems approach provides novel evidence stepping up the mechanistic understanding of test nutraceuticals, thus rationalizing their clinical exploitation in new preventive/therapeutic modalities against HCC.

Modulation of non-coding RNAs by resveratrol in ovarian cancer cells: In silico analysis and literature review of the anti-cancer pathways involved

Background and aim

Non-coding RNAs control cell functioning through affecting gene expression and translation and their dysregulation is associated with altered cell homeostasis and diseases, including cancer. Nutraceuticals with anti-cancer therapeutic potential have been shown to modulate non-coding RNAs expression that could impact on the expression of genes involved in the malignant phenotype.

Experimental procedure

Here, we report on the microarray profiling of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) and on the associated biochemical pathways and functional processes potentially modulated in OVCAR-3 ovarian cancer cells exposed for 24 h to Resveratrol (RV), a nutraceutical that has been shown to inhibit carcinogenesis and cancer progression in a variety of human and animal models, both in vitro and in vivo. Diana tools and Gene Ontology (GO) pathway analyses along with Pubmed literature search were employed to identify the cellular processes possibly affected by the dysregulated miRNAs and lncRNAs.

Results and conclusion

The present data consistently support the contention that RV could exert anti-neoplastic activity via non-coding RNAs epigenetic modulation of the pathways governing cell homeostasis, cell proliferation, cell death and cell motility.

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Nutraceuticals with anti-cancer therapeutic potential have been shown to modulate non-coding RNAs expression that could impact on the expression of genes involved in the malignant phenotype.

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Here, we report on the microarray profiling of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) and on the associated biochemical pathways and functional processes potentially modulated in OVCAR-3 ovarian cancer cells exposed for 24 h to Resveratrol (RV), a nutraceutical that has been shown to inhibit carcinogenesis and cancer progression in a variety of human and animal models.

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The data here reported consistently support the contention that RV could exert anti-neoplastic activity via non-coding RNAs epigenetic modulation of the pathways governing cell homeostasis, cell proliferation, cell death and cell motility.

Identification of novel microRNAs and their targets in Chlorophytum borivilianum by small RNA and degradome sequencing

Plant specific miRNAs (Novel miRNAs) are well known to perform distinctive functions in biological processes. Identification of new miRNAs is necessary to understand their gene regulation. Degradome provides an opportunity to explore the miRNA functions by comparing the miRNA population and their degraded products. In the present study, Small RNA sequencing data was used to identify novel miRNAs. Further, degradome sequencing was carried out to identify miRNAs targets in the plant, Chlorophytum borivilianum. The present study supplemented 40 more novel miRNAs correlating degradome data with smallRNAome. Novel miRNAs, complementary to mRNA partial sequences obtained from degradome sequencing were actually targeting the later. A big pool of miRNA was established by using Oryza sativa, Arabidopsis thaliana, Populus trichocarpa, Ricinus communis, and Vitis vinifera genomic data. Targets were identified for novel miRNAs and total 109 targets were predicted. BLAST2GO analysis elaborate about localization of novel miRNAs’ targets and their corresponding KEGG (Kyoto Encyclopedia for Genes and Genomes) pathways. Identified targets were annotated and were found to be involved in significant biological processes like Nitrogen metabolism, Pyruvate metabolism, Citrate cycle (TCA cycle), photosynthesis, and Glycolysis/Gluconeogenesis. The present study provides an overall view of the miRNA regulation in multiple metabolic pathways that are involved in plant growth, pathogen resistance and secondary metabolism of C. borivilianum.

Metabolomes and transcriptomes revealed the saponin distribution in root tissues of Panax quinquefolius and Panax notoginseng

Background

Panax quinquefolius and Panax notoginseng are widely used and well known for their pharmacological effects. As main pharmacological components, saponins have different distribution patterns in the root tissues of Panax plants.

Methods

In this study, the representative ginsenosides were detected and quantified by desorption electrospray ionization mass spectrometry and high-performance liquid chromatography analysis to demonstrate saponin distribution in the root tissues of P. quinquefolius and P. notoginseng, and saponin metabolite profiles were analyzed by metabolomes to obtain the biomarkers of different root tissues. Finally, the transcriptome analysis was performed to demonstrate the molecular mechanisms of saponin distribution by gene profiles.

Results

There was saponin distribution in the root tissues differed between P. quinquefolius and P. notoginseng. Eight-eight and 24 potential biomarkers were detected by metabolome analysis, and a total of 340 and 122 transcripts involved in saponin synthesis that were positively correlated with the saponin contents (R > 0.6, P < 0.05) in the root tissues of P. quinquefolius and P. notoginseng, respectively. Among them, GDPS1, CYP51, CYP64, and UGT11 were significantly correlated with the contents of Rg1, Re, Rc, Rb2, and Rd in P. quinquefolius. UGT255 was markedly related to the content of R1; CYP74, CYP89, CYP100, CYP103, CYP109, and UGT190 were markedly correlated with the Rd content in P. notoginseng.

Conclusions

These results provided the visual and quantitative profiles of and confirmed the pivotal transcripts of CYPs and UGTs regulating the saponin distribution in the root tissues of P. quinquefolius and P. notoginseng.

Discovery of Novel Hemocyanin-Like Genes in Metazoans

Among animals, two major groups of oxygen-binding proteins are found: proteins that use iron to bind oxygen (hemoglobins and hemerythrins) and two non-homologous hemocyanins that use copper. Although arthropod and mollusc hemocyanins bind oxygen in the same manner, they are distinct in their molecular structures. In order to better understand the range of natural variation in hemocyanins, we searched for them in a diverse array of metazoan transcriptomes by using bioinformatics tools to examine hemocyanin evolutionary history and to consequently revive the discussion about whether all metazoan hemocyanins shared a common origin with frequent losses or whether they originated separately after the divergence of Lophotrochozoa and Ecdysozoa. We confirm that the distribution of hemocyanin-like genes is more widespread than previously reported, including five putative novel mollusc hemocyanin genes in two annelid species from Chaetopteridae. For arthropod hemocyanins, 16 putative novel genes were retained, and the presence of arthropod hemocyanins in 11 annelid species represents a novel observation. Interestingly, Annelida is the lineage that presents the greatest repertoire of oxygen transport proteins reported to date, possessing all the main superfamily proteins, which could be explained partially by the immense variability of lifestyles and habitats. Work presented here contradicts the canonical view that hemocyanins are restricted to molluscs and arthropods, suggesting that the occurrence of copper-based blood pigments in metazoans has been underestimated. Our results also support the idea of the presence of oxygen carrier hemocyanins being widespread across metazoans with an evolutionary history characterized by frequent losses.

E47 Governs the MYC-CDKN1B/p27KIP1-RB Network to Growth Arrest PDA Cells Independent of CDKN2A/p16INK4A and Wild-Type p53

BACKGROUND & AIMS

Oncogenic mutations in KRAS, coupled with inactivation of p53, CDKN2A/p16INK4A, and SMAD4, drive progression of pancreatic ductal adenocarcinoma (PDA). Overexpression of MYC and deregulation of retinoblastoma (RB) further promote cell proliferation and make identifying a means to therapeutically alter cell-cycle control pathways in PDA a significant challenge. We previously showed that the basic helix-loop-helix transcription factor E47 induced stable growth arrest in PDA cells in vitro and in vivo. Here, we identified molecular mechanisms that underlie E47-induced growth arrest in low-passage, patient-derived primary and established PDA cell lines.

METHODS

RNA sequencing was used to profile E47-dependent transcriptomes in 5 PDA cell lines. Gene Ontology analysis identified cell-cycle control as the most altered pathway. Small interfering RNA/short hairpin RNA knockdown, small-molecule inhibitors, and viral expression were used to examine the function of E47-dependent genes in cell-cycle arrest. Cell morphology, expression of molecular markers, and senescence-associated β-galactosidase activity assays identified cellular senescence.

RESULTS

E47 uniformly inhibited PDA cell-cycle progression by decreasing expression of MYC, increasing the level of CDKN1B/p27KIP1, and restoring RB tumor-suppressor function. The molecular mechanisms by which E47 elicited these changes included altering both RNA transcript levels and protein stability of MYC and CDKN1B/p27KIP1. At the cellular level, E47 elicited a senescence-like phenotype characterized by increased senescence-associated β-galactosidase activity and altered expression of senescence markers.

CONCLUSIONS

E47 governs a highly conserved network of cell-cycle control genes, including MYC, CDKN1B/p27KIP1, and RB, which can induce a senescence-like program in PDA cells that lack CDKN2A/p16INK4A and wild-type p53. RNA sequencing data are available at the National Center for Biotechnology Information GEO at https://www.ncbi.nlm.nih.gov/geo/; accession number: GSE100327.

Bioinformatic identification of key genes and pathways that may be involved in the pathogenesis of HBV-associated acute liver failure

In order to explore the molecular mechanisms behind the pathogenesis of acute liver failure (ALF) associated with hepatitis B virus (HBV) infection, the present study aimed to identify potential key genes and pathways involved using samples from patients with HBV-associated ALF. The GSE38941 array dataset was downloaded from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) between 10 liver samples from 10 healthy donors and 17 liver specimens from 4 patients with HBV-associated ALF were analyzed using the Linear Models for Microarray Data package. Gene Ontology and KEGG pathway enrichment analyses of the DEGs were performed, followed by functional annotation of the genes and construction of a protein–protein interaction (PPI) network. Subnetwork modules were subsequently identified and analyzed. In total, 3142 DEGs were identified, of which 1755 were upregulated and 1387 were downregulated. The extracellular exosome, immune response, and inflammatory response pathways may potentially be used as biomarkers of ALF pathogenesis. In total, 17 genes (including CCR5, CXCR4, ALB, C3, VGEFA, and IGF1) were identified as hub genes in the PPI network and may therefore be potential marker genes for HBV-associated ALF.

Parental obesity leads to metabolic changes in the F2 generation in Drosophila

OBJECTIVE

A significant portion of the heritable risk for complex metabolic disorders cannot be attributed to classic Mendelian genetic factors. At least some of this missing heritability is thought to be due to the epigenetic influence of parental and grandparental metabolic state on offspring health. Previous work suggests that this transgenerational phenomenon is evolutionarily conserved in Drosophila. These studies, however, have all depended on dietary paradigms to alter parental metabolic state, which can have inconsistent heritable effects on the metabolism of offspring.

METHODS

Here we use AKHR null alleles to induce obesity in the parental generation and then score both metabolic parameters and genome-wide transcriptional responses in AKHR heterozygote F1 progeny and genetically wild-type F2 progeny.

RESULTS

Unexpectedly, we observe elevated glycogen levels and changes in gene expression in AKHR heterozygotes due to haploinsufficiency at this locus. We also show that genetic manipulation of parental metabolism using AKHR mutations results in significant physiological changes in F2 wild-type offspring of the grandpaternal/maternal lineage.

CONCLUSIONS

Our results demonstrate that genetic manipulation of parental metabolism in Drosophila can have an effect on the health of F2 progeny, providing a non-dietary paradigm to better understand the mechanisms behind the transgenerational inheritance of metabolic state.

Genome-wide analysis of core promoter structures in Schizosaccharomyces pombe with DeepCAGE

The core promoter, which immediately flanks the transcription start site (TSS), plays a critical role in transcriptional regulation of eukaryotes. Recent studies on higher eukaryotes have revealed an unprecedented complexity of core promoter structures that underscores diverse regulatory mechanisms of gene expression. For unicellular eukaryotes, however, the structures of core promoters have not been investigated in detail. As an important model organism, Schizosaccharomyces pombe still lacks the precise annotation for TSSs, thus hampering the analysis of core promoter structures and their relationship to higher eukaryotes. Here we used a deep sequencing-based approach (DeepCAGE) to generate 16 million uniquely mapped tags, corresponding to 93,736 positions in the S. pombe genome. The high-resolution TSS landscape enabled identification of over 8,000 core promoters, characterization of 4 promoter classes and observation of widespread alternative promoters. The landscape also allowed precise determination of the representative TSSs within core promoters, thus redefining the 5' UTR for 82.8% of S. pombe genes. We further identified the consensus initiator (Inr) sequence--PyPyPuN(A/C)(C/A), the TATA-enriched region (between position -25 and -37) and an Inr immediate downstream motif--CC(T/A)(T/C)(T/C/A)(A/G)CCA(A/T/C), all of which were associated with highly expressed promoters. In conclusion, the detailed analysis of core promoters not only significantly improves the genome annotation of S. pombe, but also reveals that this unicellular eukaryote shares a highly similar organization in the core promoters with higher eukaryotes. These findings lend additional evidence for the power of this model system in delineating complex regulatory processes in multicellular organisms, despite its perceived simplicity.

Identification of differentially expressed genes between developing seeds of different soybean cultivars

Soybean is a major source of protein and oil and a primary feedstock for biodiesel production. Research on soybean seed composition and yield has revealed that protein, oil and yield are controlled quantitatively and quantitative trait loci (QTL) have been identified for each of these traits. However, very limited information is available regarding the genetic mechanisms controlling seed composition and yield. To help address this deficiency, we used Affymetrix Soybean GeneChips® to identify genes that are differentially expressed between developing seeds of the Minsoy and Archer soybean cultivars, which differ in seed weight, yield, protein content and oil content. A total of 700 probe sets were found to be expressed at significantly different (defined as having an adjusted p-value below or equal to 0.05 and an at least 2-fold difference) levels between the two cultivars at one or more of the three developmental stages and in at least one of the two years assayed. Comparison of data from soybeans collected in two different years revealed that 97 probe sets were expressed at significantly different levels in both years. Functional annotations were assigned to 78% of these 97 probe sets based on the SoyBase Affymetrix™ GeneChip® Soybean Genome Array Annotation. Genes involved in receptor binding/activity and protein binding are overrepresented among the group of 97 probe sets that were differentially expressed in both years assayed. Probe sets involved in growth/development, signal transduction, transcription, defense/stress response and protein and lipid metabolism were also identified among the 97 probe sets and their possible implications in the regulation of agronomic traits are discussed. As the Minsoy and Archer soybean cultivars differ with respect to seed size, yield, protein content and lipid content, some of the differentially expressed probe sets identified in this study may thus play important roles in controlling these traits. Others of these probe sets may be involved in regulation of general seed development or metabolism. All microarray data and expression values after GCRMA are available at the Gene Expression Omnibus (GEO) at NCBI (http://www.ncbi.nlm.nih.gov/geo), under accession number GSE21598.

eIF2 kinases mediate β-lapachone toxicity in yeast and human cancer cells

β-Lapachone (β-lap) is a novel anticancer agent that selectively induces cell death in human cancer cells, by activation of the NQO1 NAD(P)H dehydrogenase and radical oxygen species (ROS) generation. We characterized the gene expression profile of budding yeast cells treated with β-lap using cDNA microarrays. Genes involved in tolerance to oxidative stress were differentially expressed in β-lap treated cells. β-lap treatment generated reactive oxygen species (ROS), which were efficiently blocked by dicoumarol, an inhibitor of NADH dehydrogenases. A yeast mutant in the mitochondrial NADH dehydrogenase Nde2p was found to be resistant to β-lap treatment, despite inducing ROS production in a WT manner. Most interestingly, DNA damage responses triggered by β-lap were abolished in the nde2Δ mutant. Amino acid biosynthesis genes were also induced in β-lap treated cells, suggesting that β-lap exposure somehow triggered the General Control of Nutrients (GCN) pathway. Accordingly, β-lap treatment increased phosphorylation of eIF2α subunit in a manner dependent on the Gcn2p kinase. eIF2α phosphorylation required Gcn1p, Gcn20p and Nde2p. Gcn2p was also required for cell survival upon exposure to β-lap and to elicit checkpoint responses. Remarkably, β-lap treatment increased phosphorylation of eIF2α in breast tumor cells, in a manner dependent on the Nde2p ortholog AIF, and the eIF2 kinase PERK. These findings uncover a new target pathway of β-lap in yeast and human cells and highlight a previously unknown functional connection between Nde2p, Gcn2p and DNA damage responses.

Gene expression profiles identify both MyD88-independent and MyD88-dependent pathways involved in the maturation of dendritic cells mediated by heparan sulfate: a novel adjuvant

The traditional vaccine adjuvant research is mainly based on the trial and error method, and the mechanisms underlying the immune system stimulation remaining largely unknown. We previously demonstrated that heparan sulfate (HS), a TLR-4 ligand and endogenous danger signal, effectively enhanced humoral and cellular immune responses in mice immunized by HBsAg. This study aimed to evaluate whether HS induces better humoral immune responses against inactivated Hepatitis A or Rabies Vaccines, respectively, compared with traditional adjuvants (e.g. Alum and complete Freund's adjuvant). In order to investigate the molecular mechanisms of its adjuvanticity, the gene expression pattern of peripheral blood monocytes derived DCs (dendritic cells) stimulated with HS was analyzed at different times points. Total RNA was hybridized to Agilent SurePrint G3 Human Gene Expression 8×60 K one-color oligo-microarray. Through intersection analysis of the microarray results, we found that the Toll-like receptor signaling pathway was significantly activated, and NF-kB, TRAF3 and IRF7 were activated as early as 12 h, and MyD88 was activated at 48 h post-stimulation. Furthermore, the expression of the surface marker CD83 and the co-stimulatory molecules CD80 and CD86 was up-regulated as early as 24 h. Therefore, we speculated that HS-induced human monocyte-derived DC maturation may occur through both MyD88-independent and dependent pathways, but primarily through the former (TRIF pathway). These data provide an important basis for understanding the mechanisms underlying HS enhancement of the immune response.

Chromosome segregation and organization are targets of 5'-Fluorouracil in eukaryotic cells

The antimetabolite 5'-Fluorouracil (5FU) is an analog of uracil commonly employed as a chemotherapeutic agent in the treatment of a range of cancers including colorectal tumors. To assess the cellular effects of 5FU, we performed a genome-wide screening of the haploid deletion library of the eukaryotic model Schizosaccharomyces pombe. Our analysis validated previously characterized drug targets including RNA metabolism, but it also revealed unexpected mechanisms of action associated with chromosome segregation and organization (post-translational histone modification, histone exchange, heterochromatin). Further analysis showed that 5FU affects the heterochromatin structure (decreased levels of histone H3 lysine 9 methylation) and silencing (down-regulation of heterochromatic dg/dh transcripts). To our knowledge, this is the first time that defects in heterochromatin have been correlated with increased cytotoxicity to an anticancer drug. Moreover, the segregation of chromosomes, a process that requires an intact heterochromatin at centromeres, was impaired after drug exposure. These defects could be related to the induction of genes involved in chromatid cohesion and kinetochore assembly. Interestingly, we also observed that thiabendazole, a microtubule-destabilizing agent, synergistically enhanced the cytotoxic effects of 5FU. These findings point to new targets and drug combinations that could potentiate the effectiveness of 5FU-based treatments.

Pathways commonly dysregulated in mouse and human obese adipose tissue: FAT/CD36 modulates differentiation and lipogenesis

Obesity is linked to adipose tissue hypertrophy (increased adipocyte cell size) and hyperplasia (increased cell number). Comparative analyses of gene datasets allowed us to identify 1426 genes which may represent common adipose phenotype in humans and mice. Among them we identified several adipocyte-specific genes dysregulated in obese adipose tissue, involved in either fatty acid storage (acyl CoA synthase ACSL1, hormone-sensitive lipase LIPE, aquaporin 7 AQP7, perilipin PLIN) or cell adhesion (fibronectin FN1, collagens COL1A1, COL1A3, metalloprotein MMP9, or both (scavenger receptor FAT/CD36). Using real-time analysis of cell surface occupancy on xCELLigence system we developed a new method to study lipid uptake and differentiation of mouse 3T3L1 fibroblasts and human adipose stem cells. Both processes are regulated by insulin and fatty acids such as oleic acid. We showed that fatty acid addition to culture media increased the differentiation rate and was required for full differentiation into unilocular adipocytes. Significant activation of lipogenesis, i.e. lipid accumulation, by either insulin or oleic acid was monitored in times ranging from 1 to 24 h, depending on differentiation state, whereas significant effects on adipogenesis, i.e., surperimposed lipid accumulation and gene transcriptional regulations were measured after 3 to 4 d. Combination of selected times for analysis of lipid contents, cell counts, size fractionations, and gene transcriptional regulations showed that FAT/CD36 specific inhibitor AP5258 significantly increased cell survival of oleic acid-treated mouse and human adipocytes, and partially restored the transcriptional response to oleic acid in the presence of insulin through JNK pathway. Taken together, these data open new perspectives to study the molecular mechanisms commonly dysregulated in mouse and human obesity at the level of lipogenesis linked to hypertrophy and adipogenesis linked to hyperplasia.

Quantitative proteomics reveals novel therapeutic and diagnostic markers in hypertension

Hypertension is a prevalent disorder in the world representing one of the major risk factors for heart attack and stroke. These risks are increased in salt sensitive individuals. Hypertension and salt sensitivity are complex phenotypes whose pathophysiology remains poorly understood and, remarkably, salt sensitivity is still laborious to diagnose.

Here we present a urinary proteomic study specifically designed to identify urinary proteins relevant for the pathogenesis of hypertension and salt sensitivity. Despite previous studies that underlined the association of UMOD gene variants with hypertension, this work provides novel evidence showing different uromodulin protein level in the urine of hypertensive patients compared to healthy individuals. Notably, we also show that patients with higher level of uromodulin are homozygous for UMOD risk variant and display a decreased level of salt excretion, highlighting the essential role of UMOD in the regulation of salt reabsorption in hypertension. Additionally, we found that urinary nephrin 1, a marker of glomerular slit diaphragm, may predict a salt sensitive phenotype and positively correlate with increased albuminuria associated with this type of hypertension.

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We identified urinary proteins differently excreted in hypertensive patients.

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Nephrin 1 might predict salt sensitive phenotype and glomerular complications.

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Uromodulin impacts salt homeostasis in hypertension.

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We provide new insights into the pathogenesis of hypertension and salt sensitivity.

The ALS/FTLD-related RNA-binding proteins TDP-43 and FUS have common downstream RNA targets in cortical neurons

TDP-43 and FUS are linked to amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD), and loss of function of either protein contributes to these neurodegenerative conditions. To elucidate the TDP-43- and FUS-regulated pathophysiological RNA metabolism cascades, we assessed the differential gene expression and alternative splicing profiles related to regulation by either TDP-43 or FUS in primary cortical neurons. These profiles overlapped by >25% with respect to gene expression and >9% with respect to alternative splicing. The shared downstream RNA targets of TDP-43 and FUS may form a common pathway in the neurodegenerative processes of ALS/FTLD.