Gene Ontology Consortium: going forward

Integrated Transcriptomics-Proteomics Analysis Identifies Molecular Phenotypic Alterations Associated with Colorectal Cancer

Understanding the pathogenesis and finding diagnostic markers for colorectal cancer (CRC) are the key to its diagnosis and treatment. Integrated transcriptomics and proteomics analysis can be used to characterize alterations of molecular phenotypes and reveal the hidden pathogenesis of CRC. This study employed a novel strategy integrating transcriptomics and proteomics to identify pathological molecular pathways and diagnostic biomarkers of CRC. First, differentially expressed proteins and coexpressed genes generated from weighted gene coexpression network analysis (WGCNA) were intersected to obtain key genes of the CRC phenotype. In total, 63 key genes were identified, and pathway enrichment analysis showed that the process of coagulation and peptidase regulator activity could both play important roles in the development of CRC. Second, protein-protein interaction analysis was then conducted on these key genes to find the central genes involved in the metabolic pathways underpinning CRC. Finally, Itih3 and Lrg1 were further screened out as diagnostic biomarkers of CRC by applying statistical analysis on central genes combining transcriptomics and proteomics data. The deep involvement of central genes in tumorigenesis demonstrates the accuracy and reliability of this novel transcriptomics-proteomics integration strategy in biomarker discovery. The identified candidate biomarkers and enriched metabolic pathways provide insights for CRC diagnosis and treatment.

SORC: an integrated spatial omics resource in cancer

The interactions between tumor cells and the microenvironment play pivotal roles in the initiation, progression and metastasis of cancer. The advent of spatial transcriptomics data offers an opportunity to unravel the intricate dynamics of cellular states and cell-cell interactions in cancer. Herein, we have developed an integrated spatial omics resource in cancer (SORC, http://bio-bigdata.hrbmu.edu.cn/SORC), which interactively visualizes and analyzes the spatial transcriptomics data in cancer. We manually curated currently available spatial transcriptomics datasets for 17 types of cancer, comprising 722 899 spots across 269 slices. Furthermore, we matched reference single-cell RNA sequencing data in the majority of spatial transcriptomics datasets, involving 334 379 cells and 46 distinct cell types. SORC offers five major analytical modules that address the primary requirements of spatial transcriptomics analysis, including slice annotation, identification of spatially variable genes, co-occurrence of immune cells and tumor cells, functional analysis and cell-cell communications. All these spatial transcriptomics data and in-depth analyses have been integrated into easy-to-browse and explore pages, visualized through intuitive tables and various image formats. In summary, SORC serves as a valuable resource for providing an unprecedented spatially resolved cellular map of cancer and identifying specific genes and functional pathways to enhance our understanding of the tumor microenvironment.

CROST: a comprehensive repository of spatial transcriptomics

The development of spatial transcriptome sequencing technology has revolutionized our comprehension of complex tissues and propelled life and health sciences into an era of spatial omics. However, the current availability of databases for accessing and analyzing spatial transcriptomic data is limited. In response, we have established CROST (https://ngdc.cncb.ac.cn/crost), a comprehensive repository of spatial transcriptomics. CROST encompasses high-quality samples and houses 182 spatial transcriptomic datasets from diverse species, organs, and diseases, comprising 1033 sub-datasets and 48 043 tumor-related spatially variable genes (SVGs). Additionally, it encompasses a standardized spatial transcriptome data processing pipeline, integrates single-cell RNA sequencing deconvolution spatial transcriptomics data, and evaluates correlation, colocalization, intercellular communication, and biological function annotation analyses. Moreover, CROST integrates the transcriptome, epigenome, and genome to explore tumor-associated SVGs and provides a comprehensive understanding of their roles in cancer progression and prognosis. Furthermore, CROST provides two online tools, single-sample gene set enrichment analysis and SpatialAP, for users to annotate and analyze the uploaded spatial transcriptomics data. The user-friendly interface of CROST facilitates browsing, searching, analyzing, visualizing, and downloading desired information. Collectively, CROST offers fresh and comprehensive insights into tissue structure and a foundation for understanding multiple biological mechanisms in diseases, particularly in tumor tissues.

Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression

Immunotherapy with CAR T cells for pediatric solid and brain tumors is constrained by available targetable antigens. Cancer-specific exons (CSE) present a promising reservoir of targets; however, these have not been explored and validated systematically in a pan-cancer fashion. To identify CSE targets, we analyzed 1,532 RNA-seq datasets from 16 types of pediatric solid and brain tumors for comparison with normal tissues using a newly developed workflow. We found 2,933 exons in 157 genes encoding proteins of the surfaceome or matrisome with high cancer specificity either at the gene (n=148) or the alternatively spliced (AS) isoform (n=9) level. Expression of selected AS targets, including the EDB domain of FN1 (EDB), and gene targets, such as COL11A1, were validated in pediatric PDX tumors. We generated CAR T cells specific to EDB or COL11A1 and demonstrated that COL11A1-CAR T-cells have potent antitumor activity. The full target list, explorable via an interactive web portal (https://cseminer.stjude.org/), provides a rich resource for developing immunotherapy of pediatric solid and brain tumors using gene or AS targets with high expression specificity in cancer.

Expression of Interleukin-13 Receptor Alpha 2 in Brainstem Gliomas

The objective of this study was to investigate IL13Ra2 expression in brainstem glioma (BSG) and its correlation with key markers, functions, and prognostic implications, evaluating its therapeutic potential. A total of 80 tumor samples from BSG patients were analyzed. Multiplex immunofluorescence was used to examine six markers-IL13Ra2, H3.3K27M, CD133, Ki67, HLA-1, and CD4-establishing relationships between IL13Ra2 and these markers. Survival analysis, employing Kaplan-Meier and Cox proportional hazard regression models, encompassed 66 patients with complete follow-up. RNA-Seq data from a previously published study involving 98 patients were analyzed using the DESeq2 library to determine differential gene expression between groups. Gene Ontology (GO) enrichment and single-sample gene set enrichment analysis (ssGSEA) via the clusterProfiler library were used to delineate the gene functions of differentially expressed genes (DEGs). Nearly all the BSG patients displayed varying IL13Ra2 expression, with 45.0% (36/80) exhibiting over a 20% increase. Elevated IL13Ra2 levels were notably observed in pontine gliomas, diffuse intrinsic pontine gliomas (DIPGs), H3F3A-mutant gliomas, and WHO IV gliomas. IL13Ra2 expression was strongly correlated with H3.3K27M mutant protein, Ki67, and CD133. Patients with IL13Ra2 expression >20% showed shorter overall survival compared to those with ≤20% IL13Ra2 expression. The Cox proportional hazard regression model identified H3F3A mutations, rather than IL13Ra2 expression, as an independent prognostic factor. Analysis of RNA-Seq data from our prior cohort confirmed IL13Ra2's correlation with H3.3, CD133, and Ki67 levels. Widespread IL13Ra2 expression in BSG, particularly elevated in the H3F3A mutant group, was strongly correlated with H3F3A mutations, increased proliferation, and heightened tumor stemness. IL13Ra2 represents a promising therapeutic target for BSGs, potentially benefiting patients with H3K27M mutations, DIPGs, WHO Grade IV, and pontine location-specific BSGs, particularly those with H3K27M mutations.

Medicine for chronic atrophic gastritis: a systematic review, meta- and network pharmacology analysis

PURPOSE

The aim of this study is to determine the effectiveness and reliability of adding traditional Chinese medicine (TCM) in the clinical intervention and explore mechanisms of action for chronic atrophic gastritis (CAG) through meta- and network pharmacology analysis (NPAs).

METHODS

A predefined search strategy was used to retrieve literature from PubMed, Embase database, Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese BioMedical Literature Database (CBM), Wan Fang Data and China Science and Technology Journal Database (VIP). After applying inclusion and exclusion criteria, a total of 12 randomized controlled trials (RCTs) were included for meta-analysis to provide clinical evidence of the intervention effects. A network meta-analysis using Bayesian networks was conducted to observe the relative effects of different intervention measures and possible ranking of effects. The composition of the TCM formulation in the experimental group was analysed, and association rule mining was performed to identify hub herbal medicines. Target genes for CAG were searched in GeneCards, Online Mendelian Inheritance in Man, PharmGKB, Therapeutic Target Database and DrugBank. A regulatory network was constructed to connect the target genes with active ingredients of the hub herbal medicines. Enrichment analyses were performed using the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) to examine the central targets from a comprehensive viewpoint. Protein-protein interaction networks (PPINs) were constructed to identify hub genes and conduct molecular docking with differentially expressed genes (DEGs) and corresponding active molecules.

RESULTS

A total of 1140 participants from 12 RCTs were included in the statistical analysis, confirming that the experimental group receiving the addition of TCM intervention had better clinical efficacy. Seven hub TCMs (Paeonia lactiflora, Atractylodes macrocephala, Pinellia ternata, Citrus reticulata, Codonopsis pilosula, Salvia miltiorrhiza and Coptis chinensis) were identified through association rule analysis of all included TCMs. Thirteen hub genes (CDKN1A, CASP3, STAT1, TP53, JUN, MAPK1, STAT3, MAPK3, MYC, HIF1A, FOS, MAPK14 and AKT1) were obtained from 90 gene PPINs. Differential gene expression analysis between the disease and normal gastric tissue identified MAPK1 and MAPK3 as the significant genes. Molecular docking analysis revealed that naringenin, luteolin and quercetin were the main active compounds with good binding activities to the two hub targets. GO analysis demonstrated the function of the targets in protein binding, while KEGG analysis indicated their involvement in important pathways related to cancer.

CONCLUSIONS

The results of a meta-analysis of 12 RCTs indicate that TCM intervention can improve the clinical treatment efficacy of CAG. NPAs identified seven hub TCM and 13 target genes associated with their actions, while bioinformatics analysis identified two DEGs between normal and CAG gastric tissues. Finally, molecular docking was employed to reveal the mechanism of action of the active molecules in TCM on the DEGs. These findings not only reveal the mechanisms of action of the active components of the TCMs, but also provide support for the development of new drugs, ultimately blocking the progression from chronic gastritis to gastric cancer.

Disulfidptosis-related prognostic signature correlates with immunotherapy response in colorectal cancer

Disulfidptosis (DSP), a form of cell death caused by disulphide stress, plays an important role in tumour progression. However, the mechanisms by which DSP regulates the tumour microenvironment remain unclear. Thus, we analysed the transcriptome profiles and clinical data, which were obtained from the TCGA database, of 540 patients with colorectal cancer. Compared with the patients with low DSP expression, those with high DSP expression exhibited significantly better survival outcomes; lower stromal and ESTIMATE scores; significantly higher numbers of CD4+ T cells, M2 macrophages, dendritic cells, and neutrophils; higher expression of immune checkpoint-related genes; and lower Tregs and HLA-DQB2 levels. A prognostic signature established based on DSP-related genes demonstrated an increase in risk score with a higher clinical stage. Risk scores negatively correlated with dendritic cells, eosinophils, and CD4+ T cells and significantly positively correlated with Treg cells. Patients with higher risk scores experienced significantly worse survival outcomes and immunotherapy non-response. Our nomogram model, combining clinicopathological features and risk scores, exhibited robust prognostic and predictive power. In conclusion, DSP-related genes actively participated in regulating the tumour microenvironment. Thus, they can serve as biomarkers to provide targeted treatment for colorectal cancer.

Screening of novel tumor-associated antigens for lung adenocarcinoma mRNA vaccine development based on pyroptosis phenotype genes

This study aimed to identify new pyroptosis-associated tumor antigens for use in mRNA vaccines and the screening of sensitive LUAD populations suitable for vaccination. The association between tumor immune infiltrating cell abundance and potential tumor antigens was investigated and visualized using the analysis modules of gene expression, clinical outcomes, and somatic copy number variation. In addition, the pyroptosis-related genes (PRGs) were clustered, the relative pyroptosis subtypes (PSs) and gene modules were identified, and the prognostic value of the PSs was examined. The expression of key PRGs in two lung adenocarcinoma cell lines was verified by RT-qPCR. Four tumor pyroptosis-associated antigens, CARD8, NAIP, NLRP1, and NLRP3, were screened as potential candidates for LUAD mRNA vaccine development. In the construction of consensus clusters for PRGs, two PSs, PS1 and PS2, were classified, in which patients with PS1 LUAD had a better prognosis. In contrast, patients with PS2 LUAD may have better responsiveness to mRNA vaccine treatment. The key PRGs can be regarded as biomarkers to predict the LUAD prognosis and identify patients suitable for mRNA vaccines. The RT-qPCR results showed that the expression levels of CSMD3, LRP1B, MUC16 and TTN were significantly increased in the two lung adenocarcinoma cell lines, while the expression levels of CARD8, TP53 and ZFHX4 were significantly reduced. The antigens CARD8, NAIP, NLRP1, and NLRP3, which are associated with tumor pyroptosis, could be candidate molecules for LUAD mRNA vaccine development. Patients with PS2 LUAD may be suitable candidates for mRNA vaccine treatment.

Mechanisms analysis for Formononetin counteracted-Osimertinib resistance in non-small cell lung cancer cells: From the insight into the gene transcriptional level

Formononetin is one of the main isoflavone components, which has strong anti-cancer effects in non-small cell lung cancer (NSCLC). However, the potentials and the mechanisms of Formononetin to counteract the Osimertinib resistance in NSCLC are unclear. In this study, Formononetin-induced cell apoptosis, cell proliferation, and clonal formation were detected in Osimertinib-resistant NSCLC cells (H1975_OR). RNA sequencing analysis was conducted to study the gene expression profiles of Formononetin-induced H1975_OR cells. The results indicated that Formononetin could significantly induce cell apoptosis, whereas dramatically inhibited cell proliferation and clonal formation on H1975_OR cells. Furthermore, a total of 4309 differentially expressed genes (DEGs) between Formononetin-treated and nontreated H1975_OR cells were had been detected. Gene Ontology (GO) annotation enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and the Gene Set Enrichment Analysis (GSEA) showed that Formononetin affected the expression of genes involving in anatomical structure morphogenesis, anatomical structure development, and multicellular organism development via regulating inflammation- and metabolism-related signaling pathways. Taken together, our study preliminarily revealed the mechanisms of Formononetin to counteract the Osimertinib resistance in NSCLC cells from the transcriptional level and provided a potential treatment method for Osimertinib-resistant NSCLC patients.

Role of immune related genes in predicting prognosis and immune response in patients with hepatocellular carcinoma

Immunotherapy has developed rapidly in recent years. This study aimed to establish a prognostic signature for immune-related genes (IRGs) and explore related potential immunotherapies. The RNA-seq transcriptome profiles and clinicopathological information of patients were obtained from The Cancer Genome Atlas. Differentially expressed IRGs in tumors and normal tissues were screened and a risk score signature was constructed to predict the prognosis in patients with hepatocellular carcinoma (HCC). Receiver operating characteristic curves, survival analyses, and correlation analyses were used to explore the clinical application of this model. We further analyzed the differences in clinical characteristics, immune infiltration, somatic mutations, and treatment sensitivity between the high- and low-risk populations characterized by the prognostic models. The immune cell infiltration score and immune-related pathway activity were calculated using the single sample gene set enrichment analysis (ssGSEA) set enrichment analysis. Gene ontology (GO), Kyoto encyclopedia of genes and genomes, and GSEA were used to explore the underlying mechanisms. We constructed a nine-IRG formula to predict the prognosis in HCC patients. The higher the risk score, the higher the malignancy of the tumor and the worse the prognosis. There were significant differences in immune related processes between the high- and low-risk groups. TP53 and CTNNB1 mutations were significantly different between different risk groups. The expression of model gene was closely related to the sensitivity of tumor cells to chemotherapeutic drugs. This risk score model, which is helpful for the individualized treatment of patients with different risk factors, could be a reliable prognostic tool for HCC patients.

hdWGCNA and Cellular Communication Identify Active NK Cell Subtypes in Alzheimer's Disease and Screen for Diagnostic Markers through Machine Learning

BACKGROUND

Alzheimer's disease (AD) is a recognized complex and severe neurodegenerative disorder, presenting a significant challenge to global health. Its hallmark pathological features include the deposition of β-amyloid plaques and the formation of neurofibrillary tangles. Given this context, it becomes imperative to develop an early and accurate biomarker model for AD diagnosis, employing machine learning and bioinformatics analysis.

METHODS

In this study, single-cell data analysis was employed to identify cellular subtypes that exhibited significant differences between the diseased and control groups. Following the identification of NK cells, hdWGCNA analysis and cellular communication analysis were conducted to pinpoint NK cell subset with the most robust communication effects. Subsequently, three machine learning algorithms-LASSO, Random Forest, and SVM-RFE-were employed to jointly screen for NK cell subset modular genes highly associated with AD. A logistic regression diagnostic model was then designed based on these characterized genes. Additionally, a protein-protein interaction (PPI) networks of model genes was established. Furthermore, unsupervised cluster analysis was conducted to classify AD subtypes based on the model genes, followed by the analysis of immune infiltration in the different subtypes. Finally, Spearman correlation coefficient analysis was utilized to explore the correlation between model genes and immune cells, as well as inflammatory factors.

RESULTS

We have successfully identified three genes (RPLP2, RPSA, and RPL18A) that exhibit a high association with AD. The nomogram based on these genes provides practical assistance in diagnosing and predicting patients' outcomes. The interconnected genes screened through PPI are intricately linked to ribosome metabolism and the COVID-19 pathway. Utilizing the expression of modular genes, unsupervised cluster analysis unveiled three distinct AD subtypes. Particularly noteworthy is subtype C3, characterized by high expression, which correlates with immune cell infiltration and elevated levels of inflammatory factors. Hence, it can be inferred that the establishment of an immune environment in AD patients is closely intertwined with the heightened expression of model genes.

CONCLUSION

This study has not only established a valuable diagnostic model for AD patients but has also delved deeply into the pivotal role of model genes in shaping the immune environment of individuals with AD. These findings offer crucial insights into early AD diagnosis and patient management strategies.

Convert-Pheno: A software toolkit for the interconversion of standard data models for phenotypic data

Efficient sharing and integration of phenotypic data is crucial for advancing biomedical research and enhancing patient outcomes in precision medicine and public health. To achieve this, the health data community has developed standards to promote the harmonization of variable names and values. However, the use of diverse standards across different research centers can hinder progress. Here we present Convert-Pheno, an open-source software toolkit that enables the interconversion of common data models for phenotypic data such as Beacon v2 Models, CDISC-ODM, OMOP-CDM, Phenopackets v2, and REDCap. Along with the software, we have created a detailed documentation that includes information on deployment and installation.

Metatranscriptome analysis reveals the putative venom toxin repertoire of the biofouling hydroid Ectopleura larynx

Cnidarians thriving in biofouling communities on aquaculture net pens represent a significant health risk for farmed finfish due to their stinging cells. The toxins coming into contact with the fish, during net cleaning, can adversely affect their behavior, welfare, and survival, with a particularly serious health risk for the gills, causing direct tissue damage such as formation of thrombi and increasing risks of secondary infections. The hydroid Ectopleura larynx is one of the most common fouling organisms in Northern Europe. However, despite its significant economic, environmental, and operational impact on finfish aquaculture, biological information on this species is scarce and its venom composition has never been investigated. In this study, we generated a whole transcriptome of E. larynx, and identified its putative expressed venom toxin proteins (predicted toxin proteins, not functionally characterized) based on in silico transcriptome annotation mining and protein sequence analysis. The results uncovered a broad and diverse repertoire of putative toxin proteins for this hydroid species. Its toxic arsenal appears to include a wide and complex selection of toxin proteins, covering a large panel of potential biological functions that play important roles in envenomation. The putative toxins identified in this species, such as neurotoxins, GTPase toxins, metalloprotease toxins, ion channel impairing toxins, hemorrhagic toxins, serine protease toxins, phospholipase toxins, pore-forming toxins, and multifunction toxins may cause various major deleterious effects in prey, predators, and competitors. These results provide valuable new insights into the venom composition of cnidarians, and venomous marine organisms in general, and offer new opportunities for further research into novel and valuable bioactive molecules for medicine, agronomics and biotechnology.

The Potential Mechanism of Eriodictyol in Treating Alzheimer's Disease: A Study on Computer-assisted Investigational Strategies

BACKGROUND

At present, drug development for treating Alzheimer's disease (AD) is still highly challenging. Eriodictyol (ERD) has shown great potential in treating AD, but its molecular mechanism is unknown.

OBJECTIVE

We aimed to explore the potential targets and mechanisms of ERD in the treatment of AD through network pharmacology, molecular docking, and molecular dynamics simulations.

METHODS

ERD-related targets were predicted based on the CTD, SEA, PharmMapper, Swiss TargetPrediction, and ETCM databases, and AD-related targets were predicted through the TTD, OMIM, DrugBank, GeneCards, Disgenet, and PharmGKB databases. Protein-protein interaction, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomics analyses (KEGG) were used to analyse the potential targets and key pathways of the anti-AD effect of ERD. Subsequently, potential DEGs affected by AD were analysed using the AlzData database, and their relationships with ERD were evaluated through molecular docking and molecular dynamics simulations.

RESULTS

A total of 198 ERD-related targets, 3716 AD-related targets, and 122 intersecting targets were identified. GO annotation analysis revealed 1497 biological processes, 78 cellular components, and 132 molecular functions of 15 core targets. KEGG enrichment analysis identified 168 signalling pathways. We ultimately identified 9 DEGs associated with AD through analysis of the AlzData data. Molecular docking results showed good affinity between the selected targets and ERD, with PTGS2, HSP90AA1, and BCL2. The interactions were confirmed by molecular dynamics simulations.

CONCLUSION

ERD exerts anti-AD effects through multiple targets, pathways, and levels, providing a theoretical foundation and valuable reference for the development of ERD as a natural anti-AD drug.

Screening of tumor antigens and immunogenic cell death landscapes of prostate adenocarcinoma for exploration of mRNA vaccine

BACKGROUND

In this study, effective antigens of mRNA vaccine were excavated from the perspective of ICD, and ICD subtypes of PRAD were further distinguished to establish an ICD landscape, thereby determining suitable vaccine recipients.

RESEARCH DESIGN AND METHODS

TCGA and MSKCC databases were applied to acquire RNA-seq data and corresponding clinical data of 554 and 131 patients, respectively. GEPIA was employed to measure prognostic indices. Then, a comparison of genetic alterations was performed utilizing cBioPortal, and correlation of identified ICD antigens with immune infiltrating cells was analyzed employing TIMER. Moreover, ICD subtypes were identified by means of consensus cluster, and ICD landscape of PRAD was depicted utilizing graph learning-based dimensional reduction.

RESULTS

In total, 4 PRAD antigens were identified in PRAD, including FUS, LMNB2, RNPC3, and ZNF700, which had association with adverse prognosis and infiltration of APCs. PRAD patients were classified as two ICD subtypes based on their differences in molecular, cellular, and clinical features. Furthermore, ICD modulators and immune checkpoints were also differentially expressed between two ICD subtype tumors. Finally, the ICD landscape of PRAD showed substantial heterogeneity among individual patients.

CONCLUSIONS

In summary, the research may provide a theoretical foundation for developing mRNA vaccine against PRAD as well as determining appropriate vaccine recipients.

Exploring the Therapeutic Potential of Triptonide in Salivary Adenoid Cystic Carcinoma: A Comprehensive Approach Involving Network Pharmacology and Experimental Validation

BACKGROUND

Salivary Adenoid Cystic Carcinoma (ACC) is characterized by a highly invasive and slow-growing pattern, and its etiology remains unidentified. Triptonide (TN) has demonstrated efficacy as a pharmacotherapeutic agent against ACC. Nonetheless, the specific targets and mechanism of molecular action underlying the effectiveness of TN in treating ACC have not been elucidated.

OBJECTIVES

By integrating network pharmacology within laboratory experiments, this research delves into the prospective targets and molecular mechanisms associated with the application of TN in treating ACC.

METHODS

Initially, pertinent targets associated with TN against ACC were acquired from public databases. Subsequently, a combination of network pharmacology and bioinformatics analysis was utilized to screen the top 10 hub targets and key signal pathways of TN-treating ACC. Finally, in vitro experiments involving various molecular assays were conducted to evaluate the biological phenotypes of cells following TN treatment, encompassing assessments of apoptosis levels, plate migration, and other parameters, thereby validating pivotal genes and pathways.

RESULTS

A total of 23 pertinent targets for TN in relation to ACC were identified, with the top 10 hub genes being MAPK8, PTGS2, RELA, MAPK14, NR3C1, HDAC1, PPARG, NFKBIA, AR, and PGR. There was a significant correlation between the TNF signaling pathway and the treatment of ACC with TN. In vitro experiments demonstrated that TN treatment elevated RELA phosphorylation while concurrently reducing MAPK14 phosphorylation and inducing G2/M arrest. TN exhibited the ability to enhance the apoptosis rate through increased caspase-3 activity, elevated levels of Reactive Oxygen Species (ROS), mitochondrial dysfunction, and inhibition of cell migration.

CONCLUSION

There is a potential therapeutic role for TN in the treatment of ACC through the activation of the TNF signaling pathway. Among the identified candidates, MAPK8, HDAC1, PTGS2, RELA, NR3C1, PPARG, NFKBIA, AR, and PGR emerge as the most pertinent therapeutic targets for TN in the context of ACC treatment.

Transcriptional differences between vesicular hand eczema and atopic dermatitis

BACKGROUND

Transcriptome analyses of vesicular hand eczema (VHE) indicated a large overlap with atopic dermatitis (AD). However, differentially expressed genes (DEGs) that differentiate VHE from AD are unknown.

OBJECTIVE

To identify distinctive transcriptional features of VHE in comparison to AD.

METHODS

We re-analysed RNA sequencing data of 10 lesional palmar VHE epidermal biopsies and performed DEG analyses. We adjusted the obtained DEG results of 57 lesional whole AD skin biopsies of the upper extremities or trunk to our criteria. Up- and down-regulated DEGs in both skin diseases, VHE-only, AD-only, and opposite regulated DEGs were identified. Enrichment analyses and Chi-squared tests were conducted to test for differences in gene set enrichment between both skin diseases.

RESULTS

Comparing 3028 DEGs in VHE (1645 up; 1383 down) with 5391 DEGs in AD (3842 up; 1549 down), revealed 1516 shared DEGs (1179 up; 337 down) and 1512 DEGs unique to VHE (466 up, 1046 down). Interferon signalling and necroptosis were significantly more prominent in VHE compared to AD. Downregulated genes identified only in VHE (like DNASE1L2, KRT2, KRT9 and KRT25) indicate an aberrant epidermal differentiation.

CONCLUSION

Our study indicates a common pathophysiology between VHE and AD, but also reveals transcriptional differences between VHE and AD.

Explore novel molecular mechanisms of FNDC5 in ischemia-reperfusion (I/R) injury by analyzing transcriptome changes in mouse model of skeletal muscle I/R injury with FNDC5 knockout

BACKGROUND

Irisin, a myokine derived from proteolytic cleavage of the fibronectin type III domain-containing protein 5 (FNDC5) protein, is crucial in protecting tissues and organs from ischemia-reperfusion (I/R) injury. However, the underlying mechanism of its action remains elusive. In this study, we investigated the expression patterns of genes associated with FNDC5 knockout to gain insights into its molecular functions.

METHODS

We employed a mouse model of skeletal muscle I/R injury with FNDC5 knockout to examine the transcriptional profiles using RNA sequencing. Differentially expressed genes (DEGs) were identified and subjected to further analyses, including gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein-protein interaction (PPI) network analysis, and miRNA-transcription factor network analysis. The bioinformatics findings were validated using qRT-PCR and Western blotting.

RESULTS

Comparative analysis of skeletal muscle transcriptomes between wild-type (WT; C57BL/6), WT-I/R, FNDC5 knockout (KO), and KO-I/R mice highlighted the significance of FNDC5 in both physiological conditions and I/R injury. Through PPI network analysis, we identified seven key genes (Col6a2, Acta2, Col4a5, Fap, Enpep, Mmp11, and Fosl1), which facilitated the construction of a TF-hub genes-miRNA regulatory network. Additionally, our results suggested that the PI3K-Akt pathway is predominantly involved in FNDC5 deletion-mediated I/R injury in skeletal muscle. Animal studies revealed reduced FNDC5 expression in skeletal muscle following I/R injury, and the gastrocnemius muscle with FNDC5 knockout exhibited larger infarct size and more severe tissue damage after I/R. Moreover, Western blot analysis confirmed the upregulation of Col6a2, Enpep, and Mmp11 protein levels following I/R, particularly in the KO-I/R group. Furthermore, FNDC5 deletion inhibited the PI3K-Akt signaling pathway.

CONCLUSION

This study demonstrates that FNDC5 deletion exacerbates skeletal muscle I/R injury, potentially involving the upregulation of Col6a2, Enpep, and Mmp11. Additionally, the findings suggest the involvement of the PI3K-Akt pathway in FNDC5 deletion-mediated skeletal muscle I/R injury, providing novel insights into the molecular mechanisms underlying FNDC5's role in this pathological process.

Comprehensive analysis of autophagy associated genes and immune infiltrates in cervical cancer

Objectives

Cervical cancer (CC) is the most common gynecological malignant tumor and the fourth leading cause of cancer-related death in women. The progression of CC is significantly affected by autophagy. Our objective was to use bioinformatics analysis to explore the expression, prognostic significance, and immune infiltration of autophagy-related genes in CC.

Materials and Methods

We identified a set of autophagy-related differentially expressed genes (ARDEGs) from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. ARDEGs were further validated by The Human Protein Atlas (HPA), GSE52903, and GSE39001 dataset. Hub genes were found by the STRING network and Cytoscape. We performed Gene Set Enrichment Analysis (GSEA), Gene ontology analysis (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and immune infiltration analysis to further understand the functions of the hub genes. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) were used to check the hub genes.

Results

A total of 10 up-regulated (CXCR4, BAX, SPHK1, EIF2AK2, TBK1, TNFSF10, ITGB4, CDKN2A, IL24, and BIRC5) and 19 down-regulated (PINK1, ATG16L2, ATG4D, IKBKE, MLST8, MAPK3, ERBB2, ULK3, TP53INP2, MTMR14, BNIP3, FOS, CCL2, FAS, CAPNS1, HSPB8, PTK6, FKBP1B , and DNAJB1) ARDEGs were identified. The ARDEGs were enriched in cell growth, apoptosis, human papillomavirus infection, and cytokine-mediated. Then, we found that low expression of MAPK3 was associated with poor prognosis in CC patients and was significantly enriched in immune pathways. In addition, the expression of MAPK3 was significantly positively correlated with the infiltration levels of macrophages, B cells, mast cell activation, and cancer-associated fibroblasts. Furthermore, MAPK3 was positively correlated with LGALS9, and negatively correlated with CTLA4 and CD40.

Conclusion

Our results show that MAPK3 can be used as a new prognostic biomarker to predict the prognosis of patients with CC.

Purifying selection drives distinctive arsenic metabolism pathways in prokaryotic and eukaryotic microbes

Microbes play a crucial role in the arsenic biogeochemical cycle through specific metabolic pathways to adapt to arsenic toxicity. However, the different arsenic-detoxification strategies between prokaryotic and eukaryotic microbes are poorly understood. This hampers our comprehension of how microbe-arsenic interactions drive the arsenic cycle and the development of microbial methods for remediation. In this study, we utilized conserved protein domains from 16 arsenic biotransformation genes (ABGs) to search for homologous proteins in 670 microbial genomes. Prokaryotes exhibited a wider species distribution of arsenic reduction- and arsenic efflux-related genes than fungi, whereas arsenic oxidation-related genes were more prevalent in fungi than in prokaryotes. This was supported by significantly higher acr3 (arsenite efflux permease) expression in bacteria (upregulated 3.72-fold) than in fungi (upregulated 1.54-fold) and higher aoxA (arsenite oxidase) expression in fungi (upregulated 5.11-fold) than in bacteria (upregulated 2.05-fold) under arsenite stress. The average values of nonsynonymous substitutions per nonsynonymous site to synonymous substitutions per synonymous site (dN/dS) of homologous ABGs were higher in archaea (0.098) and bacteria (0.124) than in fungi (0.051). Significant negative correlations between the dN/dS of ABGs and species distribution breadth and gene expression levels in archaea, bacteria, and fungi indicated that microbes establish the distinct strength of purifying selection for homologous ABGs. These differences contribute to the distinct arsenic metabolism pathways in prokaryotic and eukaryotic microbes. These observations facilitate a significant shift from studying individual or several ABGs to characterizing the comprehensive microbial strategies of arsenic detoxification.

Alterations in Synaptic Connectivity and Synaptic Transmission in Alzheimer's Disease with High Physical Activity

Background

Alzheimer's disease (AD) is a progressive neurodegeneration disease. Physical activity is one of the most promising modifiable lifestyles that can be effective in slowing down the progression of AD at an early stage.

Objective

Explore the molecular processes impaired in AD that were conversely preserved and enhanced by physical activity.

Methods

Integrated transcriptomic analyses were performed in datasets that contain AD patients and elders with different degrees of physical activity. The changes of the hub genes were validated through analyzing another two datasets. The expression of the hub genes was further detected in the hippocampus and cortexes of APP/PS1 transgenic mice with or without physical activity by Quantitative polymerase chain reaction (qPCR).

Results

Cross-comparison highlighted 195 DEGs displaying opposed regulation patterns between AD and high physical activity (HPA). The common DEGs were predominantly involved in synaptic vesicle recycling and synaptic transmission, largely downregulated in AD patients but upregulated in the elders with HPA. Two key modules and four hub genes that were related to synaptic vesicle turnover were obtained from the PPI network. The expression of these hub genes (SYT1, SYT4, SH3GL2, and AP2M1) was significantly decreased in AD transgenic mice and was reversed by HPA training.

Conclusions

HPA may reverse AD pathology by upregulating a range of synaptic vesicle transport related proteins which might improve the efficiency of synaptic vesicle turnover and facilitate inter-neuronal information transfer. The study provides novel insights into the mechanisms underlining the protective effects of HPA on AD.

Exploration of Key Genes Combining with Immune Infiltration Level andTumor Mutational Burden in Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a lethal malignancy due to its heterogeneity and aggressive behavior. Recently, somatic mutations and tumor cell interactions with the surrounding tumor immune microenvironment (TIME) have been reported to participate in HCC carcinogenesis and predict HCC progression. In this study, we aimed to investigate the association between tumor mutational burden (TMB) and TIME in HCC. Additionally, we sought to identify differentially expressed genes (DEGs) associated with HCC prognosis and progression.

METHODS

The expression, clinical, and mutational data were downloaded from the cancer genome atlas (TCGA) database. The immune infiltration levels and TMB levels of the HCC samples were estimated and the samples were divided into immune cluster (ICR)-1 and 2 based on immune infiltration score and high and low TMB groups based on TMB score. Thereafter, differential gene expression analysis was conducted to identify the DEGs in the ICR1/2 and high/low TMB groups, and the intersecting DEGs were selected. Thereafter, Cox regression analysis was performed on 89 significant DEGs, among which 19 were associated with prognosis. These 19 DEGs were then used to construct a prognostic model based on their expression levels and regression coefficients. Thereafter, we analyzed the DEGs in mutant and wildtype TP53 HCC samples and identified high BCL10 and TRAF3 expression in the mutant TP53 samples. BCL10 and TRAF3 expression was detected by real-time quantitative reverse transcription PCR and immunohistochemistry, and their clinical correlation, biological function, and immune infiltration levels were analyzed by chi-square analyses, Gene Set Enrichment Analysis (GSEA), and "ssGSEA", respectively.

RESULTS

The results of our study revealed that immune infiltration level was correlated with TMB and that they synergistically predicted poor prognosis of HCC patients. DEGs enriched in immune-related pathways could serve as indicators of immunotherapy response in HCC. Among these DEGs, BCL10 and TRAF3 were highly expressed in HCC tissues, especially in the mutant TP53 group, and they co-operatively exhibited immunological function, thereby affecting HCC progression and prognosis.

CONCLUSION

In this study, we identified BCL10 and TRAF3 as potential prognostic indicators in HCC patients. Additionally, we found that BCL10 and TRAF3 influence TMB and TIME in HCC patients and can be used for the development of immune-based therapies for improving the long-term survival of HCC patients.

Lymph node metastasis-related lncRNA GAS6-AS1 facilitates the progression of esophageal squamous cell carcinoma

Background

Lymph node metastasis is the main type of metastasis in esophageal squamous cell carcinoma (ESCC), especially when the primary tumor invasion depth reaches above the adventitia layer (T3 stage), the incidence of lymph node metastasis increases sharply. Abnormal expression of long non-coding RNAs (lncRNAs) has been confirmed in ESCC, but there are still many unknown connections between lncRNAs and lymph node metastasis.

Methods

We used transcriptome sequencing (RNA-seq) to analyze 10 pairs of ESCC tissues with primary tumor stage T3 and their paired normal epithelium. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to further verify the sequencing results, and survival curve analysis, logistic regression analysis, and receiver operating characteristic (ROC) curve analysis were used to investigate its clinical application value. We investigated the growth and metastasis effects of lncRNA GAS6-AS1 on ESCC cell lines TE-1 and KYSE410 in vitro and in vivo. Other functional experiments included cell apoptosis and cell cycle experiments.

Results

Based on our RNA-seq data, lncRNA GAS6-AS1 is highly expressed in ESCC tissues, especially in cancer tissues with lymph node metastasis. The qRT-PCR experiment analysis showed that high expression of GAS6-AS1 was related to poor tumor differentiation and tumor stage. Logistic regression analysis showed that it was an independent risk factor for lymph node metastasis, and ROC analysis validated that it could predict lymph node metastasis. Further survival analysis suggested that high expression of GAS6-AS1 was associated with patients' poor prognosis. In vitro experiments, knocking down GAS6-AS1 inhibited the growth and metastasis of ESCC cells and inhibited tumor growth in vivo. In addition, knocking down GAS6-AS1 can inhibit cell cycle and promote cell apoptosis.

Conclusions

Our results revealed that lncRNA GAS6-AS1 obtained from RNA-seq can be used as an independent risk factor for ESCC lymph node metastasis and an effective biomarker to predict, and that it was related to the growth and metastasis of ESCC. It may represent a new biomarker to aid in the assessment of the lymph node metastasis of ESCC.

Elucidation of the anti-colon cancer mechanism of Phellinus baumii polyphenol by an integrative approach of network pharmacology and experimental verification

Colon cancer, a prevalent malignant tumor affecting the digestive system, presents a substantial risk to human health due to its high occurrence and mortality rates. Phellinus baumii polyphenol (PBP), a natural product derived from traditional Chinese medicine, has gained widespread popularity due to its low toxicity and minimal side effects, compared to radiation and chemotherapy. This study used an integrated approach of network pharmacology and experimental verification to elucidate the anti-colon cancer effects of PBP and its potential mechanisms. In network pharmacology, the identification of relevant targets involved a comprehensive search across multiple databases using keywords such as "active components of PBP" and "colon cancer". Venn diagram analysis was subsequently performed to ascertain the shared targets. To identify the key active components and core targets, we constructed a network of "Disease-Drug-Pathways-Targets" and a protein-protein interaction (PPI) network among the targets using Cytoscape 3.9.1. Furthermore, molecular docking was carried out to predict the binding affinity and conformation between the main active compounds (davallialactone and citrinin) of PBP and the core targets (TP53, STAT3, CASP3, CTNNB1, PARP1, MYC). To validate our findings, in vitro experiments were conducted. We verified that PBP exerted an anti-colon cancer effect on human colon cancer HCT116 cells by significantly inhibiting cell proliferation, promoting apoptosis and arresting the cell cycle in S phase by using Cell Counting Kit-8 (CCK-8) and flow cytometry. Finally, we determined the key regulatory proteins related to apoptosis and the cell cycle by western blot analysis, and proposed the potential mechanism by which PBP exerts an anti-colon cancer effect by inducing the caspase-dependent mitochondrial-mediated intrinsic apoptotic pathway and arresting the cell cycle in S phase in HCT116 cells. These results suggest that PBP possesses substantial potential for the treatment of colon cancer and may serve as a viable alternative therapeutic strategy in colon cancer treatment.

BICDL1 Predicts Poor Prognosis and is Correlated with Methylation and Immune Infiltration in Colorectal Cancer

Background

Bicaudal-D (BICD) Family Like Cargo Adaptor 1 (BICDL1) is an essential component of the molecular mechanism during neuronal development. However, BICDL1 has not been reported in cancer. Using bioinformatics analysis, we systematically evaluated the potential role of BICDL1 in CRC.

Methods

Colorectal cancer (CRC) and normal tissue samples were retrieved from the Gene Expression Omnibus (GEO), Genotype-Tissue Expression (GTEx), and Cancer Genome Atlas (TCGA) databases. Kaplan-Meier (K-M) analysis, nomogram, COX analysis, and receiver operating characteristic (ROC) curves were used to evaluate the prognostic power. Correlation analysis was also conducted to explore the correlation between mRNA expression and the methylation level of BICDL1 using cBioPortal, and the correlation between immune infiltration and BICDL1. RT-qPCR and Western blot assays were performed to analyze BICDL1 expression level between human colorectal cancer cell lines and normal colonic epithelial cells.

Results

BICDL1 had a higher expression in CRC tissues than in normal tissues (p < 0.001) in TCGA and GES 74602 datasets. Kaplan-Meier survival analysis revealed that patients with high BICDL1 expression had lower overall survival (OS) (1.53, 95% confidence interval: 1.07-2.17, p=0.019). The ROC curves demonstrated that BICDL1 has high specificity and efficiency in diagnosis (AUC=0.919, CI: 0.895-0.943). The expression level of BICDL1 was significantly correlated with the infiltrating levels of Treg (R=0.146, p <0.001), TFH (R=0.080, p=0.043), NK CD56bright cells (R=0.149, p <0.001), aDC (R=0.095, p=0.016), and T helper cell infiltration (R=-0.084, p=0.034). The correlation between BICDL1 expression and methylation levels was negative (R2=0.134, p <0.001), and CRC patients had lower methylation levels than normal people (p=0.036). BICDL1 mRNA and its protein expression levels in CRC cell lines (SW620) was markedly increased compared with that of normal colonic epithelial cells (NCM460) (p < 0.001).

Conclusion

BICDL1 may be a potential biomarker for evaluating immune infiltration levels and prognosis of CRC.

Large-scale functional inference for skin-expressing lncRNAs using expression and sequence information

Long noncoding RNAs (lncRNAs) regulate the expression of protein-coding genes and have been shown to play important roles in inflammatory skin diseases. However, we still have limited understanding of the functional impact of lncRNAs in skin, partly due to their tissue specificity and lower expression levels compared with protein-coding genes. We compiled a comprehensive list of 18,517 lncRNAs from different sources and studied their expression profiles in 834 RNA-Seq samples from multiple inflammatory skin conditions and cytokine-stimulated keratinocytes. Applying a balanced random forest to predict involvement in biological functions, we achieved a median AUROC of 0.79 in 10-fold cross-validation, identifying significant DNA binding domains (DBDs) for 39 lncRNAs. G18244, a skin-expressing lncRNA predicted for IL-4/IL-13 signaling in keratinocytes, was highly correlated in expression with F13A1, a protein-coding gene involved in macrophage regulation, and we further identified a significant DBD in F13A1 for G18244. Reflecting clinical implications, AC090198.1 (predicted for IL-17 pathway) and AC005332.6 (predicted for IFN-γ pathway) had significant negative correlation with the SCORAD metric for atopic dermatitis. We also utilized single-cell RNA and spatial sequencing data to validate cell type specificity. Our research demonstrates lncRNAs have important immunological roles and can help prioritize their impact on inflammatory skin diseases.

Efficient analysis of toxicity and mechanisms of environmental pollutants with network toxicology and molecular docking strategy: Acetyl tributyl citrate as an example

The study aims to promote network toxicology strategy to efficiently investigate the putative toxicity and underlying molecular mechanisms of environmental pollutants through an example of exploring brain injury induced by ATBC exposure. By utilizing ChEMBL, STITCH, GeneCards, and OMIM databases, we identified 213 potential targets associated with ATBC exposure and brain injury. Further refinements via STRING and Cytoscape software highlight 23 core targets, including AKT1, CASP3, and HSP90AA1. GO and KEGG pathway analysis conducted through DAVID and FUMA databases reveal that core targets of ATBC-induced brain toxicity are predominantly enriched in cancer signaling and neuroactive ligand receptor interaction pathways. Molecular docking was performed with Autodock, which confirmed robust binding between ATBC and core targets. Together, these findings suggest that ATBC may impact the occurrence and development of brain cancer and brain related inflammation, whereas pose risks for cognitive impairment and neurodegeneration, by modulating the apoptosis and proliferation of brain cancer cells, activating inflammatory signaling pathways, and regulating neuroplasticity. This research provides a theoretical basis for understanding the molecular mechanism of ATBC-induced brain toxicity, as well as establishing a foundation for the prevention and treatment of prostatic diseases associated with exposure to plastic products containing ATBC and certain ATBC-overwhelmed environments. Moreover, our network toxicology approach also expedites the elucidation of toxicity pathways for uncharacterized environmental chemicals.

Machine learning and experimental screening of chromatin regulator signatures and potential drugs in hepatitis B related hepatocellular carcinoma

Many evidences have confirmed that chromatin regulator factors (CRs) are involved in the progression of cancer, but its potential mechanism of affecting hepatitis B related hepatocellular carcinoma still needs to be studied. Our study detected the CRs that affect hepatitis B related hepatocellular carcinoma (HBV-HCC) through machine learning analysis, conducted the analysis of immune cells, constructed the relevant risk model and immune function infiltration, and predicted the potential therapeutic drugs. We found that these CRs were significantly related to the immune cells of Macrophages, B cells, CD8+T cells, etc., and PBK, AURKA, TOP2A and AURKB were the potential risk CRs of HBV-HCC. The expression levels of these four CRs increased in HepG2.2.15 cells and the liver of HBV-HCC patients, consistent with the predicted risk model. Subsequently, ten potential drugs closely related to the risk CRs were finally obtained, experimental research on resveratrol has shown that it can inhibit the proliferation of HepG2.2.15 cells and potentially inhibit the occurrence and development of HBV-HCC. Our study provides novel insights into the function of CRs in HBV-HCC and certain ideas for more accurate targeted therapy.Communicated by Ramaswamy H. Sarma.

Network based approach to identify interactions between Type 2 diabetes and cancer comorbidities

High blood sugar and insulin insensitivity causes the lifelong chronic metabolic disease called Type 2 diabetes (T2D) which has a higher chance of developing different malignancies. T2D with comorbidities like Cancers can make normal medications for those disorders more difficult. There may be a significant correlation between comorbidities and have an impact on one another's health. These associations may be due to a number of direct and indirect mechanisms. Such molecular mechanisms that underpin T2D and cancer are yet unknown. However, the large volumes of data available on these diseases allowed us to use analytical tools for uncovering their interrelated pathways. Here, we tried to present a system for investigating potential comorbidity relationships between T2D and Cancer disease by looking at the molecular processes involved, analyzing a huge number of freely accessible transcriptomic datasets of various disorders using bioinformatics. Using semantic similarity and gene set enrichment analysis, we created an informatics pipeline that evaluates and integrates Gene Ontology (GO), expression of genes, and biological process data. We discovered genes that are common in T2D and Cancer along with molecular pathways and GOs. We compared the top 200 Differentially Expressed Genes (DEGs) from each selected T2D and cancer dataset and found the most significant common genes. Among all the common genes 13 genes were found most frequent. We also found 4 common GO terms: GO:0000003, GO:0000122, GO:0000165, and GO:0000278 among all the common GO terms between T2d and different cancers. Using these genes and GO term semantic similarity, we calculated the distance between these two diseases. The semantic similarity results of our study showed a higher association of Liver Cancer (LiC), Breast Cancer (BreC), Colorectal Cancer (CC), and Bladder Cancer (BlaC) with T2D. Furthermore we found KIF4A, NUSAP1, CENPF, CCNB1, TOP2A, CCNB2, RRM2, HMMR, NDC80, NCAPG, and IGFBP5 common hub proteins among different cancers correlated to T2D. AGE-RAGE signaling pathway in diabetic complications, Osteoclast differentiation, TNF signaling pathway, IL-17 signaling pathway, p53 signaling pathway, MAPK signaling pathway, Human T-cell leukemia virus 1 infection, and Non-alcoholic fatty liver disease are the 8 most significant pathways found among 18 common pathways between T2D and selected cancers. As a result of our technique, we now know more about disease pathways that are critical between T2D and cancer.

The Prognostic and Immune Significance of CILP2 in Pan-Cancer and Its Relationship with the Progression of Pancreatic Cancer

Cartilage intermediate layer protein 2 (CILP2) facilitates interactions between matrix components in cartilage and has emerged as a potential prognostic biomarker for cancer. This study aimed to investigate the function and mechanisms of CILP2 in pan-cancer. We evaluated the pan-cancer expression, methylation, and mutation data of CILP2 for its clinical prognostic value. Additionally, we explored the immunological characteristics of CILP2 in pan-cancer and then focused specifically on pancreatic ductal adenocarcinoma (PAAD). The subtype analysis of PAAD identified subtype-specific expression and immunological characteristics. Finally, in vitro and in vivo experiments assessed the impact of CILP2 on pancreatic cancer progression. CILP2 exhibited high expression in most malignancies, with significant heterogeneity in epigenetic modifications across multiple cancer types. The abnormal methylation and copy number variations in CILP2 were correlated with poor prognoses. Upregulated CILP2 was associated with TGFB/TGFBR1 and more malignant subtypes. CILP2 exhibited a negative correlation with immune checkpoints in PAAD, suggesting potential for immunotherapy. CILP2 activated the AKT pathway, and it increased proliferation, invasion, migration, and epithelial-mesenchymal transition (EMT) in pancreatic cancer. We demonstrated that CILP2 significantly contributes to pancreatic cancer progression. It serves as a prognostic biomarker and a potential target for immunotherapy.

Therapeutic Monoclonal Antibodies against Cancer: Present and Future

A series of monoclonal antibodies with therapeutic potential against cancer have been generated and developed. Ninety-one are currently used in the clinics, either alone or in combination with chemotherapeutic agents or other antibodies, including immune checkpoint antibodies. These advances helped to coin the term personalized medicine or precision medicine. However, it seems evident that in addition to the current work on the analysis of mechanisms to overcome drug resistance, the use of different classes of antibodies (IgA, IgE, or IgM) instead of IgG, the engineering of the Ig molecules to increase their half-life, the acquisition of additional effector functions, or the advantages associated with the use of agonistic antibodies, to allow a broad prospective usage of precision medicine successfully, a strategy change is required. Here, we discuss our view on how these strategic changes should be implemented and consider their pros and cons using therapeutic antibodies against cancer as a model. The same strategy can be applied to therapeutic antibodies against other diseases, such as infectious or autoimmune diseases.

Comprehensive analysis of the prognostic implication and immune infiltration of CISD2 in diffuse large B-cell lymphoma

Background

Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell lymphoma in adults. CDGSH iron sulfur domain 2 (CISD2) is an iron-sulfur protein and plays a critical role of cell proliferation. The aberrant expression of CISD2 is associated with the progression of multiple cancers. However, its role in DLBCL remains unclear.

Methods

The differential expression of CISD2 was identified via public databases, and quantitative real-time PCR (qRT-PCR) and western blot were used to identifed the expression of CISD2. We estimated the impact of CISD2 on clinical prognosis using the Kaplan-Meier plotter. Meanwhile, the drug sensitivity of CISD2 was assessed using CellMiner database. The 100 CISD2-related genes from STRING obtained and analyzed using the LASSO Cox regression. A CISD2 related signature for risk model (CISD2Risk) was established. The PPI network of CISD2Risk was performed, and functional enrichment was conducted through the DAVID database. The impacts of CISD2Risk on clinical features were analyzed. ESTIMATE, CIBERSORT, and MCP-counter algorithm were used to identify CISD2Risk associated with immune infiltration. Subsequently, Univariate and multivariate Cox regression analysis were applied, and a prognostic nomogram, accompanied by a calibration curve, was constructed to predict 1-, 3-, and 5-years survival probabilities.

Results

CISD2 was upregulated in DLBCL patients comparing with normal controls via public datasets, similarly, CISD2 was highly expressed in DLBCL cell lines. Overexpression of CISD2 was associated with poor prognosis in DLBCL patients based on the GSE31312, the GSE32918, and GSE93984 datasets (P<0.05). Nine drugs was considered as a potential therapeutic agents for CISD2. By using the LASSO cox regression, twenty seven genes were identified to construct CISD2Risk, and biological functions of these genes might be involved in apoptosis and P53 signaling pathway. The high CISD2Risk value had a worse prognosis and therapeutic effect (P<0.05). The higher stromal score, immune score, and ESTIMATE score were associated with lowe CISD2Risk value, CISD2Risk was negatively correlated with several immune infiltrating cells (macrophages M0 and M1, CD8 T cells, CD4 naïve T cells, NK cell, etc) that might be correlated with better prognosis. Additionally, The high CISD2Risk was identified as an independent prognostic factor for DLBCL patients using both univariate and multivariate Cox regression. The nomogram produced accurate predictions and the calibration curves were in good agreement.

Conclusion

Our study demonstrates that high expression of CISD2 in DLBCL patients is associated with poor prognosis. We have successfully constructed and validated a good prognostic prediction and efficacy monitoring for CISD2Risk that included 27 genes. Meanwhile, CISD2Risk may be a promising evaluator for immune infiltration and serve as a reference for clinical decision-making in DLBCL patients.

Microarray meta-analysis reveals comprehensive effects of 3,4,5-tricaffeolyquinic acid in cell differentiation and signaling

Caffeoylquinic acids (CQA) are polyphenolic compounds found in fruits, vegetables, coffee, and spices that have exhibited several beneficial activities, including antioxidant, antibacterial, neuroprotective, anti-inflammatory, anticancer, antiviral, antidiabetic, and cardiovascular effects. A derivative, TCQA (3,4,5-Tri-O-caffeoylquinic acid), has also shown both neurogenic and pigment differentiation potential. A transcriptomic-based meta-analysis was conducted to explore potential biochemical processes and molecular targets of TCQA. This approach involved integrating data from various cell and tissue types, including human amniotic stem cells, human neural stem cells, human dermal papilla cells, and the brain cortex of aging model mice. It offered a comprehensive perspective on the significant gene regulations in response to TCQA treatment. The objective was to uncover the mechanism and novel targets of TCQA, facilitating a further understanding of its functions. New areas of interest found were TCQA's effect on adipogenesis, heart, and muscle tissue development. In addition, significantly enhanced biological activities found through meta-analysis included cell cycle, VEGFA-VEGFR2 pathway, and BMP signaling. Overall, a comprehensive functional and visual analysis using available biological databases uncovered the multi-target potential of this natural compound.

Stroma-associated FSTL3 is a factor of calcium channel-derived tumor fibrosis

Hepatocellular carcinoma (HCC) is the most widespread histological form of primary liver cancer, and it faces great diagnostic and therapeutic difficulties owing to its tumor diversity. Herein, we aim to establish a unique prognostic molecular subtype (MST) and based on this to find potential therapeutic targets to develop new immunotherapeutic strategies. Using calcium channel molecules expression-based consensus clustering, we screened 371 HCC patients from The Cancer Genome Atlas to screen for possible MSTs. We distinguished core differential gene modules between varying MSTs, and Tumor Immune Dysfunction and Exclusion scores were employed for the reliable assessment of HCC patient immunotherapeutic response rate. Immunohistochemistry and Immunofluorescence staining were used for validation of predicted immunotherapy outcomes and underlying biological mechanisms, respectively. We identified two MSTs with different clinical characteristics and prognoses. Based on the significant differences between the two MSTs, we further identified Follistatin-like 3 (FSTL3) as a potential indicator of immunotherapy resistance and validated this result in our own cohort. Finally, we found that FSTL3 is predominantly expressed in HCC stromal components and that it is a factor in enhancing fibroblast-M2 macrophage signaling crosstalk, the function of which is relevant to the pathogenesis of HCC. The presence of two MSTs associated with the calcium channel phenotype in HCC patients may provide promising directions for overcoming immunotherapy resistance in HCC, and the promotion of FSTL3 expressed in stromal components for HCC hyperfibrosis may be responsible for the poor response rate to immunotherapy in Cluster 2 (C2) patients.

Immune cell-specific and common molecular signatures in rheumatoid arthritis through molecular network approaches

Rheumatoid arthritis (RA) is an autoimmune disorder and common symptom of RA is chronic synovial inflammation. The pathogenesis of RA is not fully understood. Therefore, we aimed to identify underlying common and distinct molecular signatures and pathways among ten types of tissue and cells obtained from patients with RA. In this study, transcriptomic data including synovial tissues, macrophages, blood, T cells, CD4+T cells, CD8+T cells, natural killer T (NKT), cells natural killer (NK) cells, neutrophils, and monocyte cells were analyzed with an integrative and comparative network biology perspective. Each dataset yielded a list of differentially expressed genes as well as a reconstruction of the tissue-specific protein-protein interaction (PPI) network. Molecular signatures were identified by a statistical test using the hypergeometric probability density function by employing the interactions of transcriptional regulators and PPI. Reporter metabolites of each dataset were determined by using genome-scale metabolic networks. It was defined as the common hub proteins, novel molecular signatures, and metabolites in two or more tissue types while immune cell-specific molecular signatures were identified, too. Importantly, miR-155-5p is found as a common miRNA in all tissues. Moreover, NCOA3, PRKDC and miR-3160 might be novel molecular signatures for RA. Our results establish a novel approach for identifying immune cell-specific molecular signatures of RA and provide insights into the role of common tissue-specific genes, miRNAs, TFs, receptors, and reporter metabolites. Experimental research should be used to validate the corresponding genes, miRNAs, and metabolites.

Construction and Validation of a Prognostic Model Based on Novel Senescence-Related Genes in Non-Small Cell Lung Cancer Patients with Drug Sensitivity and Tumor Microenvironment

Cellular senescence contributes to cancer pathogenesis and immune regulation. Using the LASSO Cox regression, we developed a 12-gene prognostic signature for lung adenocarcinoma (LUAD) from The Cancer Genome Atlas (TCGA) and a Gene Expression Omnibus (GEO) dataset. We assessed gene expression, drug sensitivity, immune infiltration, and conducted cell line experiments. High-risk LUAD patients showed increased mortality risk and shorter survival (P < 0.001). Senescence-related gene analysis indicated differences in protein phosphorylation and DNA methylation between normal individuals and LUAD patients. The high-risk group showed a positive association with PD-L1 expression (P = 0.003). Single-cell sequencing data suggested PEBP1 might significantly impact T cell infiltration. We predicted potential sensitive compounds for 12 senescence genes and found GAPDH promoted cell line proliferation. We established a novel prognostic system based on a newly identified senescence gene. High-risk patients had elevated immunosuppressive markers, and PEBP1 might influence T cell infiltration significantly. GAPDH, expressed at higher levels in tumors, could affect cancer progression. Our drug prediction model may guide treatment selection.

Association of biological age with health outcomes and its modifiable factors

Identifying the clinical implications and modifiable and unmodifiable factors of aging requires the measurement of biological age (BA) and age gap. Leveraging the biomedical traits involved with physical measures, biochemical assays, genomic data, and cognitive functions from the healthy participants in the UK Biobank, we establish an integrative BA model consisting of multi-dimensional indicators. Accelerated aging (age gap >3.2 years) at baseline is associated incident circulatory diseases, related chronic disorders, all-cause, and cause-specific mortality. We identify 35 modifiable factors for age gap (p < 4.81 × 10-4 ), where pulmonary functions, body mass, hand grip strength, basal metabolic rate, estimated glomerular filtration rate, and C-reactive protein show the most significant associations. Genetic analyses replicate the possible associations between age gap and health-related outcomes and further identify CST3 as an essential gene for biological aging, which is highly expressed in the brain and is associated with immune and metabolic traits. Our study profiles the landscape of biological aging and provides insights into the preventive strategies and therapeutic targets for aging.

Construction of cuproptosis signature based on bioinformatics and experimental validation in clear cell renal cell carcinoma

BACKGROUND

Cuproptosis was defined as a novel nonapoptotic cell death pathway and its potential function in clear cell renal cell carcinoma (ccRCC) remains unclear.

METHODS

We obtained gene expression profiles, somatic mutation and corresponding clinical information of 881 ccRCC samples from 3 cohorts including the cancer genome atlas cohort, GSE29609 cohort and CheckMate 025 cohort. As described in the latest published article, we enrolled 16 genes as cuproptosis-related genes (CRGs). We explored the expression level, variants and copy number variation of the CRGs. Univariate and multi-variate regression were utilized to assess the prognostic significance of the CRGs. Non-negative matrix factorization was used to identify potential subgroup and gene set variation analysis was used to explore the potential biological functions. CIBERSORT, ESTIMATE algorithm and single sample gene set enrichment analysis were used to evaluate the tumor microenvironment. In vitro experiments including CCK-8, transwell and wound healing assays were utilized to explore the potential biological function of DLAT in ccRCC.

RESULTS

We found that except for CDKN2A, the CRGs were positively associated with patients' OS. Cuproptosis cluster, cuproptosis gene cluster and cuproptosis score were established, respectively, and higher cuproptosis score was significantly associated with a worse OS in ccRCC (p < 0.001). The area under the receiver operating characteristic curve of the cuproptosis-related nomogram at 1 year, 3 years, 5 years was 0.858, 0.821 and 0.78, respectively. In addition, we found that the cuproptosis score was positively associated with PDCD1, CTLA4 expression level, thus the cuproptosis score may also reflect the dysfunction of tumor infiltrating immune cells. In vitro experiments indicated that overexpression of DLAT could inhibited the migration and proliferation ability of ccRCC cells.

CONCLUSION

Our findings identify a novel cuproptosis-related signature and the cuproptosis characteristics may influence the anti-tumor immunity though complex regulating networks, and thus cuproptosis may play a role in developing novel therapeutic target of ccRCC.

Senkyunolide B exhibits broad-spectrum antifungal activity against plant and human pathogenic fungi via inhibiting spore germination and destroying the mature biofilm

BACKGROUND

Aspergillus infection seriously jeopardizes the health and safety of life of immunocompromised patients. The emergences of antifungal resistance highlight a demand to find new effective antifungal drugs. Angelica sinensis is a medicine-food herb and phthalides are its characteristic components. A few of the phthalides have been reported to display satisfactory antifungal activities against plant pathogenic fungi. However, the structure-activity relationships and antifungal action mechanism of phthalides remain to be further explored and elucidated.

RESULTS

The antifungal activities of five natural phthalides and four artificial analogs were investigated, and their structure-activity relationships were preliminarily elucidated in the current study. The benzene ring moiety played an essential role in their antifungal activities; the oxygen-containing substituents on the benzene ring obviously impacted their activities, the free hydroxyl was favorable to the activity. Typical phthalide senkyunolide B (SENB) exhibited broad antifungal activities against human and plant pathogenic fungi, especially, Aspergillus fumigatus. SENB affected the spore germination and hyphae growth of Aspergillus fumigatus via down-regulating phosphatidylinositol-PKC-calcineurin axis and the expression of ENG genes. Moreover, SENB disturbed the oxidation-reduction process in Aspergillus fumigatus to destroy the mature biofilms. In vivo experiments indicated SENB significantly prolonged survival and decreased fungal burden in mouse model of invasive pulmonary aspergillosis.

CONCLUSIONS

Phthalides could be considered as the valuable leads for the development of antifungal drug to cure plant and human disease. © 2023 Society of Chemical Industry.

Exploration of the biomarkers of comorbidity of psoriasis with inflammatory bowel disease and their association with immune infiltration

BACKGROUND

There was evidence that significant bidirectional associations between psoriasis and inflammatory bowel diseases (IBDs), which influences management strategy of the patients, so the investigation on the mechanisms by which these two diseases co-occur is important.

METHODS

The Gene Expression Omnibus (GEO) database was used to download gene expression profiles of psoriasis and IBD. The differentially expressed genes (DEGs) between disease and health control groups for each data set were calculated, and Venn diagram was used to obtain for intersection. We performed Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the intersection, followed by developing a protein-protein interaction network and module construction, and identified hub genes by cytoHubba. Thereafter, least absolute shrinkage and selection operator algorithms was used to identify the co-biomarkers of psoriasis and IBD from the top 50 hub genes. The biomarkers were used to construct a screening model, the discriminatory capacity of which was verified by receiver operating characteristic (ROC) curves. CIBERSORT algorithm was utilized to estimate the compositional patterns of immune cell infiltration in biomarkers of psoriasis and IBD. Spearman rank correlation analysis was used to further evaluate the correlation between the identified biomarkers and immune cells.

RESULTS

A total of 271 shared DEGs were screened. The GO and KEGG enrichment analysis indicated that the shared DEGs were mainly enriched in response to lipopolysaccharide, secretory granule lumen, cytokine activity, and interleukin (IL)-17 signaling pathway. Fifty genes such as IL1B, IL6, were identified as hub genes, based on which, FOS, IFI44, MMP9, MNDA, PTGS2, S100A9, and STAT1 were identified as biomarkers of psoriasis. CCL20, CD274, CTGF, CXCL1, CXCL10, CXCL2, CXCL9, FCGR3B, FOS, GBP1, GZMB, IFI27, IFI6, IL1RN, ISG15, ISG20, LCN2, LILRB2, MMP12, MMP7, S100A8, TLR8, and TNFSF13B were identified as biomarkers of IBD. FOS was the common biomarker of psoriasis and IBD. Screening models were validated in the validation data set (Psoriasis: area under the curve (AUC) = 1.000, IBD: AUC = 0.870). Immunocyte infiltration analysis showed the macrophages cells, mast cells resting, and T cells CD4 memory activated have the common characteristics in psoriasis and IBD.

CONCLUSIONS

FOS may play a key role in the occurrence and development of psoriasis complicated with IBD and macrophages cells may be an entrance for treating this comorbidity.

CPVL suppresses metastasis of nasopharyngeal carcinoma through inhibiting epithelial-mesenchymal transition

PURPOSE

Distant metastasis is the main obstacle to treating nasopharyngeal carcinoma (NPC). Tumor distance metastasis is a complex process involving the jointly participation of multiple oncogenes, tumor suppressor genes, and metastasis-associated genes. Enough accurate prognostic genes for evaluating metastasis risk are lacking. We aimed to identify more precise biomarkers for NPC metastasis.

METHODS

We performed weighted gene co-expression network analysis, differentially expressed gene analysis, univariate and multivariate stepwise Cox regression, and Kaplan-Meier (K-M) survival analyses, on data obtained from RNA sequencing of 10 NPC samples and the public database, to identify key genes correlated with NPC metastasis. Wound healing assays, transwell assays, and immunohistochemistry were conducted to validate our bioinformatic conclusions. Western blotting was performed to evaluate and quantify the effect of identified EMT genes on epithelial-mesenchymal transition (EMT) of NPC.

RESULTS

Combined our own RNA sequencing data and public data, we determined carboxypeptidase vitellogenic-like protein (CPVL) as a tumor suppressor for NPC. Pathway enrichment analyses indicated that genes associated with CPVL are involved in EMT. NPC with low CPVL expression had high tumor purity and low levels of immune cells. Experimental results showed that CPVL protein predominantly expressed in cytoplasmic and membranous and it exhibited higher expression levels in NPC tissues without distant metastasis than those with distant metastasis. CPVL inhibits the migration and invasive capability of NPC cells. Overexpression of CPVL upregulates E-cadherin and ZO-1, whereas it downregulates vimentin, suggesting that CPVL suppresses tumor metastasis by inhibiting EMT.

CONCLUSION

CPVL inhibits migration and invasion of NPC cells and is associated with tumor metastasis suppression through upregulating epithelial marker and inhibiting mesenchymal marker expression and could be a prognostic biomarker for metastasis risk evaluation in NPC.

Celastrol as a candidate drug for silicosis: From bioinformatics and network pharmacology to experimental validation

Silicosis, a highly lethal occupational respiratory disease characterized by irreversible pulmonary fibrosis, remains challenging to treat due to its unclear pathogenesis. In this study, bioinformatics, network pharmacology, and experimental validation were combined to explore potential mechanisms and therapeutic drugs for silicosis. First, the differentially expressed genes（DEGs）and pathway enrichment in pulmonary fibrosis were identified by GO and KEGG analysis. Next, the differential genes were submitted to cMap database for drug prediction and celastrol stood out as the most promising candidate drug. Then, network pharmacology analysis identified pharmacological targets of celastrol and demonstrated that celastrol could regulate JAK-STAT, MAPK, and Toll-like receptor signaling pathways. Finally, we verified the therapeutic role and mechanism of celastrol on silicosis. In vivo, celastrol significantly ameliorated CS-induced inflammation and fibrosis in silicosis mice, including inflammatory cell infiltration, collagen fiber and extracellular matrix deposition, fibroblast activation and related factor expression. Moreover, it dramatically improved lung respiratory function of silicosis mice. In vitro, celastrol suppressed CS-induced cytokine expression, apoptosis of macrophages and activation of Stat3 and Erk1/2 signals. Overall, our research identified and verified celastrol as a novel and promising candidate drug for silicosis.

Identification of circulating miRNA as early diagnostic molecular markers in malignant glioblastoma base on decision tree joint scoring algorithm

PURPOSE

The lack of clinical markers prevents early diagnosis of glioblastoma (GBM). Many studies have found that circulating microRNAs (miRNAs) can be used as early diagnostic markers of malignant tumours. Therefore, the identification of novel circulating miRNA biomolecular markers could be beneficial to clinicians in the early diagnosis of GBM.

METHODS

We developed a decision tree joint scoring algorithm (DTSA), systematically integrating significance analysis of microarray (SAM), Pearson hierarchical clustering, T test, Decision tree and Entropy weight score algorithm, to screen out circulating miRNA molecular markers with high sensitivity and accuracy for early diagnosis of GBM.

RESULTS

DTSA was developed and applied for GBM datasets and three circulating miRNA molecular markers were identified, namely, hsa-miR-2278, hsa-miR-555 and hsa-miR-892b. We have found that hsa-miR-2278 and hsa-miR-892b regulate the GBM pathway through target genes, promoting the development of GBM and affecting the survival of patients. DTSA has better classification effect in all data sets than other classification algorithms, and identified miRNAs are better than existing markers of GBM.

CONCLUSION

These results suggest that DTSA can effectively identify circulating miRNA, thus contributing to the early diagnosis and personalised treatment of GBM.

Identification of differentially methylated genes for severe acne by genome-wide DNA methylation and gene expression analysis

Severe acne is a chronic inflammatory skin condition that is affected by both genetic and environmental factors. DNA methylation is associated with a variety of inflammatory skin diseases, but its role in severe acne is unclear. In this study, we conducted a two-stage epigenome correlation study using 88 blood samples to identify disease-related differential methylation sites. We found close associations between the DNA methylation at 23 differentially methylated sites (DMSs) and severe acne, including PDGFD, ARHGEF10, etc. Further analysis revealed that differentially methylated genes (PARP8 and MAPKAPK2) were also expressed differently between severe acne and health control groups. These findings lead us to speculation that epigenetic mechanisms may play an important role in the pathogenesis of severe acne.

CXCL8 as a Potential Biomarker for Crohn's Disease is Associated with Immune Infiltration and RNA Methylation

TRP channels have an important role in regulating the function of gastrointestinal epithelial cells. The aim of this study was to investigate the molecular mechanisms of genes associated with TRP channels in Crohn's disease (CD) by bioinformatics approach and to identify potential key biomarkers. In our study, we identified TRP channel-related differentially expressed genes (DEGs) based on the GSE95095 dataset and the TRP channel-related gene set from the GeneCards database. Hub genes (CXCL8, HIF1A, NGF, JUN, IL1A) were identified by the PPI network and validated by the external GSE52746 dataset. Immune infiltration analysis revealed that CXCL8 was significantly correlated with B cells memory, NK cells activated, Mast cells resting, Mast cells activated, and Neutrophils. GSEA of CXCL8 results showed inositol phosphate metabolism, RNA polymerase, propanoate metabolism, MAPK signaling pathway, base excision repair, and Calcium signaling pathway. In addition, we constructed a lncRNA-miRNA-mRNA ceRNA network and a drug-gene interaction network. Finally, we performed in vitro experiments to verify that LPS induced CXCL8 expression in HT-29 cells and that knockdown of CXCL8 inhibited the inflammatory stimulatory effects of LPS. This study reveals that CXCL8 plays an important role in the pathogenesis of Crohn's disease and is expected to be a novel biomarker.

Identification of the mechanisms underlying per- and polyfluoroalkyl substance-induced hippocampal neurotoxicity as determined by network pharmacology and molecular docking analyses

Background

Per- and polyfluoroalkyl substances (PFASs) are a class of environmental contaminants that pose significant health risks to both animals and humans. Although the hippocampal neurotoxic effects of numerous PFASs have been reported, the underlying mechanisms of combined exposure to PFASs-induced hippocampal neurotoxicity remain unclear.

Methods

In this study, network pharmacology analysis was performed to identify the intersectional targets of PFASs for possible associations with hippocampal neurotoxicity. The evaluation of the influence of PFASs on intersectional targets was assessed using a weighted method. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the screened targets were performed, the intersected hub targets calculated by various algorithms were screened in the network and molecular docking was also used to analyze binding activities.

Results

Our results indicated that eight PFASs, which acted on key targets (MYC, ESR1, STAT3, RELA, MAPK3) impacted the NF-κB signaling pathway, STAT3 signaling pathway, and MAPK signaling pathways to exert neurotoxicity in the hippocampus. The molecular docking results revealed that PFASs have strong binding potential to the hub targets.

Conclusions

Our findings provided a basis for future studies to investigate the detailed mechanisms of PFASs-induced hippocampal neurotoxicity and to develop preventative and control strategies.

Do testosterone and sex hormone-binding globulin affect cancer risk? A Mendelian randomization and bioinformatics study

Using Mendelian Randomization (MR) and large-scale Genome-Wide Association Study (GWAS) data, this study aimed to investigate the potential causative relationship between testosterone and sex hormone-binding globulin (SHBG) levels and the onset of several cancers, including pathway enrichment analyses of single nucleotide polymorphisms (SNPs) associated with cancer allowed for a comprehensive bioinformatics approach, which offered a deeper biological understanding of these relationships. The results indicated that increased testosterone levels in women were associated with a higher risk of breast and cervical cancers but a lower risk of ovarian cancer. Conversely, increased testosterone was linked to lower stomach cancer risk for men, whereas high SHBG levels were related to decreased risks of breast and prostate cancers. The corresponding genes of the identified SNPs, as revealed by pathway enrichment analysis, were involved in significant metabolic and proliferative pathways. These findings emphasize the need for further research into the biological mechanisms behind these associations, paving the way for potential targeted interventions in preventing and treating these cancers.

Comprehensive analysis of necroptotic patterns and associated immune landscapes in individualized treatment of skin cutaneous melanoma

Skin cutaneous melanoma (SKCM) constitutes a malignant cutaneous neoplasm characterized by an exceedingly unfavorable prognosis. Over the past years, necroptosis, a manifestation of inflammatory programmed cell demise, has gained substantial traction in its application. However, a conclusive correlation between the expression of necroptosis-related genes (NRGs) and SKCM patient's prognosis remains elusive. In this endeavor, we have undertaken an integrative analysis of genomic data, aiming to provide an exhaustive evaluation of the intricate interplay between melanoma necroptosis and immune-infiltration nuances within the tumor microenvironment. Through meticulous scrutiny, we have endeavored to discern the prognostic potency harbored by individual necroptosis-associated genes. Our efforts culminated in the establishment of a risk stratification framework, allowing for the appraisal of necroptosis irregularities within each afflicted cutaneous melanoma patient. Notably, those SKCM patients classified within the low-risk cohort exhibited a markedly elevated survival quotient, in stark contrast to their high-risk counterparts (p < 0.001). Remarkably, the low-risk cohort not only displayed a more favorable survival rate but also exhibited an enhanced responsiveness to immunotherapeutic interventions, relative to their high-risk counterparts. The outcomes of this investigation proffer insights into a conceivable mechanistic underpinning linking necroptosis-related attributes to the intricacies of the tumor microenvironment. This prompts a conjecture regarding the plausible association between necroptosis characteristics and the broader tumor microenvironmental milieu. However, it is imperative to emphasize that the pursuit of discerning whether the expression profiles of NRG genes can indeed be regarded as viable therapeutic targets necessitates further comprehensive exploration and scrutiny. In conclusion, our study sheds light on the intricate interrelationship between necroptosis-related factors and the tumor microenvironment, potentially opening avenues for therapeutic interventions. However, the prospect of translating these findings into clinical applications mandates rigorous investigation.

Neuronal-specific methylome and hydroxymethylome analysis reveal replicated and novel loci associated with alcohol use disorder

Alcohol use disorder (AUD) is a complex condition associated with adverse health consequences that affect millions of individuals worldwide. Epigenetic modifications, including DNA methylation (5mC), have been associated with AUD and other alcohol-related traits. Epigenome-wide association studies (EWAS) have identified differentially methylated genes associated with AUD in human peripheral and brain tissue. More recently, epigenetic studies of AUD have also evaluated DNA hydroxymethylation (5hmC) in the human brain. However, most of the epigenetic work in postmortem brain tissue has examined bulk tissue. In this study, we investigated neuronal-specific 5mC and 5hmC alterations at CpG sites associated with AUD in the human orbitofrontal cortex (OFC). Neuronal nuclei from the OFC were evaluated in 34 human postmortem brain samples (10 AUD, 24 non-AUD). Reduced representation oxidative bisulfite sequencing was used to assess 5mC and 5hmC at the genome-wide level. Differential 5mC and 5hmC were evaluated using the methylKit R package and significance was set at false discovery rate <0.05 and differential methylation >2. Functional enrichment analyses were performed and replication was evaluated replication in an independent dataset that assessed 5mC and 5hmC of AUD in bulk cortical tissue. We identified 417 5mC and 363 5hmC genome-wide significant differential CpG sites associated with AUD, with 59% in gene promoters. We also identified genes previously implicated in alcohol consumption, such as SYK, CHRM2, DNMT3A, and GATA4, for 5mC and GATA4, and GAD1, GATA4, DLX1 for 5hmC. Replication was observed for 28 CpG sites from a previous AUD 5mC and 5hmC study, including FOXP1. Lastly, GWAS enrichment analysis showed an association with AUD for differential 5mC genes. This study reveals neuronal-specific methylome and hydroxymethylome dysregulation associated with AUD. We replicated previous findings and identified novel associations with AUD for both 5mC and 5hmC marks within the OFC. Our findings provide new insights into the epigenomic dysregulation of AUD in the human brain.

The protein interactome of the citrus Huanglongbing pathogen Candidatus Liberibacter asiaticus

The bacterium Candidatus Liberibacter asiaticus (CLas) causes citrus Huanglongbing disease. Our understanding of the pathogenicity and biology of this microorganism remains limited because CLas has not yet been cultivated in artificial media. Its genome is relatively small and encodes approximately 1136 proteins, of which 415 have unknown functions. Here, we use a high-throughput yeast-two-hybrid (Y2H) screen to identify interactions between CLas proteins, thus providing insights into their potential functions. We identify 4245 interactions between 542 proteins, after screening 916 bait and 936 prey proteins. The false positive rate of the Y2H assay is estimated to be 2.9%. Pull-down assays for nine protein-protein interactions (PPIs) likely involved in flagellar function support the robustness of the Y2H results. The average number of PPIs per node in the CLas interactome is 15.6, which is higher than the numbers previously reported for interactomes of free-living bacteria, suggesting that CLas genome reduction has been accompanied by increased protein multi-functionality. We propose potential functions for 171 uncharacterized proteins, based on the PPI results, guilt-by-association analyses, and comparison with data from other bacterial species. We identify 40 hub-node proteins, including quinone oxidoreductase and LysR, which are known to protect other bacteria against oxidative stress and might be important for CLas survival in the phloem. We expect our PPI database to facilitate research on CLas biology and pathogenicity mechanisms.