Differential Analysis Research Articles

Exploring the predictive values of SERP4 and FRZB in dilated cardiomyopathy based on an integrated analysis

Background and objectiveThe aim of this study was to investigate potential hub genes for dilated cardiomyopathy (DCM).MethodsFive DCM-related microarray datasets were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were used for identification. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, disease ontology, gene ontology annotation and protein-protein interaction (PPI) network analysis were then performed, while a random forest was constructed to explore central genes. Artificial neural networks were used to compare with known genes and to develop new diagnostic models. 240 population blood samples were collected and expression of hub genes was verified in these samples using RT-PCR and demonstrated by Nomogram.ResultsAfter differential analysis, 33 genes were statistically significant (adjusted P < 0.05). Functional enrichment of these differential genes resulted in 85 Gene Ontology (GO) functions identified and 6 pathways enriched for the KEGG pathway. PPI networks and molecular complex assays identified 10 hub genes (adjusted P < 0.05). Random forest identified SMOC2 and SFRP4 as the most important, followed by FCER1G and FRZB. NeuraHF models (SMOC2, SFRP4, FCER1G and FRZB) were selected by artificial neural network model and had better diagnostic efficacy for the onset of DCM, compared with the traditional KG-DCM models (MYH7, ACTC1, TTN and LMNA). Finally, SFRP4 and FRZB were expressed higher in DCM verified by RT-PCR and as a factor for DCM identified by Nomogram.ConclusionsWe performed an integrated analysis and identified SFRP4 and FRZB as a new factor for DCM. But the exact mechanism still needs further experimental verification.

Enhancing barrier properties of cellulose propionate films through the integration of ionic liquid: A study on water pressure resistance

This study pioneers the production of porous cellulose propionate (CP) films enhanced with tetrabutylammonium styrenesulfonate ([N4444][SS]), an ionic liquid, to bolster their resistance against water pressure. In contrast to polymer films with ionic liquids that have high moisture permeability, the CP/[N4444][SS] films exhibit remarkable water resistance even under 8 bar pressure. This is due to the physical cross-linking between the [N4444] ions and CP's polar groups, limiting CP chain mobility and thus reducing water interaction. Fourier-transform infrared spectroscopy confirmed these interactions, while scanning electron microscopy revealed a dense, unconnected porous structure. Thermogravimetric and differential scanning calorimetry analyses showed that adding [N4444][SS] increases the CP film's glass transition temperature, indicating enhanced thermal stability. Overall, the study demonstrates that integrating an ionic liquid into CP films significantly improves their barrier capabilities against water and pressure, which has broad implications for various industrial applications.

Dynamic dysregulation of retrotransposons in neurodegenerative diseases at the single-cell level.

Retrotransposable elements (RTEs) are common mobile genetic elements comprising ∼42% of the human genome. RTEs play critical roles in gene regulation and function, but how they are specifically involved in complex diseases is largely unknown. Here, we investigate the cellular heterogeneity of RTEs using 12 single-cell transcriptome profiles covering three neurodegenerative diseases, Alzheimer's disease (AD), Parkinson's disease, and multiple sclerosis. We identify cell type marker RTEs in neurons, astrocytes, oligodendrocytes, and oligodendrocyte precursor cells that are related to these diseases. The differential expression analysis reveals the landscape of dysregulated RTE expression, especially L1s, in excitatory neurons of multiple neurodegenerative diseases. Machine learning algorithms for predicting cell disease stage using a combination of RTE and gene expression features suggests dynamic regulation of RTEs in AD. Furthermore, we construct a single-cell atlas of retrotransposable elements in neurodegenerative disease (scARE) using these data sets and features. scARE has six feature analysis modules to explore RTE dynamics in a user-defined condition. To our knowledge, scARE represents the first systematic investigation of RTE dynamics at the single-cell level within the context of neurodegenerative diseases.

SERPINH1 as a Novel Biomarker for Colon Cancer Bone Metastasis with Machine Learning and Immunohistochemistry Validation.

Background: Bone metastasis (BM) is a serious clinical symptom of advanced colorectal cancer. However, there is a lack of effective biomarkers for early diagnosis and treatment. Method: RNA-seq data from public databases (GSE49355, GSE101607) were collected and normalized and batch effects were removed using the combat package. Differential expression analysis was performed to identify significant genes. Robust Rank Aggregation and machine learning algorithms were used to pinpoint candidate biomarkers. These biomarkers were validated using immunohistochemistry and further analyzed for survival rates. Enrichment analysis was conducted to explore biological mechanisms. Additionally, drug sensitivity and immune infiltration analyses were performed to provide insights into potential therapeutic targets. Results: Analysis results revealed 386 genes elevated in primary versus normal tissues and 26 genes varying between primary and BM. Serpin Protease Inhibitor Clade H1 (SERPINH1) as a novel biomarker for colon cancer metastasis. High SERPINH1 expression correlates with poor survival outcomes and is linked to high lymphatic invasion and advanced cancer stages. Additionally, SERPINH1 expression influences immune infiltration and is not predictive of chemotherapy response, but potential new drugs are suggested for high-expression cases. The gene also enriches classical cancer pathways such as Hedgehog and transforming growth factor-β. Conclusions: We identified novel colon cancer BM markers, including SERPINH1, using machine learning algorithms combined with traditional transcriptomic data and validated their expression through immunohistochemistry. This biomarker could significantly assist clinicians in making more precise treatment decisions.

Novel combination therapy using recombinant oncolytic adenovirus silk hydrogel and PD-L1 inhibitor for bladder cancer treatment

Recombinant oncolytic adenovirus offers a novel and promising cancer treatment approach, but its standalone efficacy remains limited. This study investigates a combination treatment strategy by co-administering recombinant oncolytic Adv-loaded silk hydrogel with a PD-L1 inhibitor for patients with bladder cancer to enhance treatment outcomes. Bladder cancer tissues from mice were collected and subjected to single-cell sequencing, identifying CRB3 as a key gene in malignant cells. Differential expression and functional enrichment analyses were performed, validating CRB3’s inhibitory role through in vitro experiments showing suppression of bladder cancer cell proliferation, migration, and invasion. Recombinant oncolytic adenoviruses encoding CRB3 and GM-CSF were constructed and encapsulated in silk hydrogel to enhance drug loading and release efficiency. In vivo experiments demonstrated that the nano-composite hydrogel significantly inhibited tumor growth and increased immune infiltration in tumor tissues. Co-administration of adenovirus silk hydrogel (Adv-CRB3@gel) with a PD-L1 inhibitor significantly enhanced T-cell infiltration and tumor killing. The combination of recombinant oncolytic Adv-loaded nano-composite hydrogel encoding CRB3 and GM-CSF with a PD-L1 inhibitor improves bladder cancer treatment outcomes by effectively recruiting T cells, providing a novel therapeutic strategy.

The role of NOP58 in prostate cancer progression through SUMOylation regulation and drug response.

Prostate cancer is one of the leading causes of cancer-related deaths in men. Its molecular pathogenesis is closely linked to various genetic and epigenetic alterations, including posttranslational modifications like SUMOylation. Identifying biomarkers that predict outcomes and specific therapeutic targets depends on a comprehensive understanding of these processes. With growing interest in SUMOylation as a mechanism affecting prostate cancer-related genes, this study aimed to investigate the central role of SUMOylation in prostate cancer prognostics, focusing on the significance of NOP58. We conducted a comprehensive bioinformatics analysis, integrating differential expression analysis, survival analysis, gene set enrichment analysis (GSEA), and single-cell transcriptomic analyses using data from The Cancer Genome Atlas (TCGA). Key genes were identified through intersections of Venn diagrams, Boralta algorithm signatures, and machine learning models. These signaling mechanisms were validated through experimental studies, including immunohistochemical staining and gene ontology analyses. The dual-gene molecular subtype analysis with SUMO1, SUMO2, and XPO1 genes revealed significant differences in survival outcomes across molecular subtypes, further emphasizing the potential impact of NOP58 on SUMOylation, a key post-translational modification, in prostate cancer. NOP58 overexpression was strongly associated with shorter overall survival (OS), progression-free interval (PFI), and disease-specific death in prostate cancer patients. Immunohistochemical analysis confirmed that NOP58 was significantly overexpressed in prostate cancer tissues compared to normal tissues. ROC curve analysis demonstrated that NOP58 could distinguish prostate cancer from control samples with high diagnostic accuracy. Gene Ontology analysis, along with GSVA and GSEA, suggested that NOP58 may be involved in cell cycle regulation and DNA repair pathways. Moreover, NOP58 knockdown led to increased BCL2 expression and decreased Ki67 levels, promoting apoptosis and inhibiting cell proliferation. Colony formation assays further showed that NOP58 knockdown inhibited, while its overexpression promoted, colony formation, highlighting the critical role of NOP58 in prostate cancer cell growth and survival. Additionally, NOP58 was linked to drug responses, including Methotrexate, Rapamycin, Sorafenib, and Vorinostat. NOP58 is a key regulator of prostate cancer progression through its mediation of the SUMOylation pathway. Its expression level serves as a reliable prognostic biomarker and an actionable therapeutic target, advancing precision medicine for prostate cancer. Targeting NOP58 may enhance therapeutic efficacy and improve outcomes in oncology.

Identification and validation of core genes associated with polycystic ovary syndrome and metabolic syndrome.

Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder affecting women of reproductive age, affecting reproductive health, and increasing the incidence of diabetes mellitus and hypertension. Metabolic syndrome (MetS) is the most common metabolic disorder. Although clinical studies have shown a close association between PCOS and MetS, the molecular mechanisms are unknown. In this study, datasets of PCOS and MetS were obtained from the Gene Expression Omnibus database; differential expression analysis and weighted gene coexpression network analysis (WGCNA) were performed; and gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses also performed of differentially expressed genes (DEGs). The PCOS- and MetS-coexpressed DEGs were subsequently intersected with the coexpressed genes in the WGCNA module to obtain the core genes. By constructing receiver operating characteristic curves, we verified the predictive effects of the core genes. We also validated the expression of the core genes in the datasets. Finally, we verified the expression of the core genes by quantitative polymerase chain reaction in human follicular fluid granulosa cells. In addition, we used Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts to analyze the immune infiltration of immune cells in PCOS and MetS. Finally, we obtained 52 coexpressed DEGs of PCOS and MetS and 3 coexpressed genes in the WGCNA module. By taking the intersection of coexpressed DEGs and coexpressed genes of the WGCNA module, we get ELOVL fatty acid elongase 7 (ELOVL7) as the core gene. Receiver operating characteristic curve analysis showed that ELOVL7 is a reliable biological marker for PCOS and MetS. The expression level of ELOVL7 in human follicular fluid granulosa cells from PCOS patients was significantly higher than that of controls, as verified by quantitative polymerase chain reaction. This study provides the first evidence of the role of ELOVL7 in developing PCOS and MetS. This gene may serve as a potential diagnostic marker and therapeutic target for both conditions.

Decoding the Methylation Patterns of ABC Transporters in Colorectal Cancer

Colorectal cancer (CRC) is a significant global health concern, posing a major threat to morbidity and mortality rates. The molecular mechanisms that drive CRC, particularly the DNA methylation patterns in ATP-binding cassette (ABC) genes, have attracted considerable attention because of their potential roles in CRC drug resistance, initiation, and progression. This study aimed to investigate the methylation patterns of ABC genes in CRC using a high-throughput microarray technology. Microarray methylation data from CRC and adjacent normal tissues were subjected to preprocessing, differential methylation analysis, and correlation analysis using the MethSurv tool for a detailed study of methylation patterns. The study revealed global hypomethylation of 43 ABC transporters and two pseudogenes in CRC compared to normal tissues. Receiver operating characteristic curve analysis identified 369 CpG sites as potential biomarkers for CRC diagnosis, with area under the curve values ranging from acceptable to outstanding. Survival analysis demonstrated the correlation between DNA methylation of individual CpG sites and patient survival probability in colon and rectal adenocarcinoma datasets from The Cancer Genome Atlas. The study provides insights into the epigenetic landscape of ABC genes in CRC, highlighting their potential roles in drug resistance, disease initiation, and progression. The findings offer opportunities for developing innovative therapeutic approaches and improving patient outcomes in the fight against CRC. Further research is needed to validate these results and investigate the functional implications of ABC gene methylation in CRC pathogenesis and treatment response.

Exploring the role of aggrephagy-related signatures in immune microenvironment, prognosis, and therapeutic strategies of breast cancer.

Breast cancer (BC) is 1 of the most common malignant tumors among women globally. This study aimed to develop a prognostic signature based on aggrephagy-related genes (ARGs). Transcriptomic and clinical data for BC patients were downloaded from the cancer genome atlas and GEO databases. Differential expression analysis, univariate Cox proportional hazards regression and least absolute shrinkage and selection operator Cox regression were employed to construct a prognostic signature. Consensus clustering, evaluation of immune infiltration and drug sensitivity, and gene set enrichment analysis, and development of nomogram were performed. The expression of ARGs was validated using data from the Cancer Cell Line Encyclopedia and clinical samples. Eleven ARGs were abnormally expressed in BC, with 5 showing significant correlations with BC prognosis. Consensus clustering identified 2 molecular subtypes with distinct prognoses. A prognostic signature including 5 ARGs (VIM, TUBB1, TUBA3E, TUBA3D, TUBA1C) was developed, which showed high performance in predicting BC prognosis. The low-risk group showed enrichment in extracellular matrix organization and cell migration processes while chromosome separation was suppressed. Additionally, patients in this group also show activation in several signaling pathways including MAPK, PI3K-AKT, and cAMP pathways, whereas cell cycle and neutrophil extracellular trap formation were significantly inhibited. The signature was also associated with immune infiltration and drug sensitivity. A nomogram incorporating the risk signature, clinical stage and chemotherapy was constructed, demonstrating excellent performance in predicting prognosis. The expression of signature-related genes were validated in patients with BC. This study successfully constructed molecular subtypes and a prognostic signature based on ARGs in BC, and developed a nomogram.

Unveiling new protein biomarkers and therapeutic targets for acne through integrated analysis of human plasma proteomics and genomics.

The current landscape of acne therapeutics is notably lacking in targeted treatments, highlighting a critical need for the discovery of new drug targets to improve treatment outcomes. This study aims to investigate the connections between proteomics and genetics in relation to acne across extensive population cohorts, aspiring to identify innovative preventive and therapeutic approaches. Employing a longitudinal cohort of 54,306 participants from the UK Biobank Pharmacological Proteomics Project (UKB-PPP), we performed an exhaustive evaluation of the associations between 2,923 serum proteins and acne risk. Initial multivariate Cox regression analyses assessed the relationship between protein expression levels and acne onset, followed by two-sample Mendelian Randomization (TSMR), Summary-data-based Mendelian Randomization (SMR), and colocalization to identify genetic correlations with potential protein targets. Within the UKB cohort, we identified 19 proteins significantly associated with the risk of acne. Subsequent analysis using Two-Sample Mendelian Randomization (TSMR) refined this to two specific proteins: FSTL1 and ANXA5. Each one-standard deviation increase in the expression levels of FSTL1 and ANXA5 was associated with a 24% and 32% increase in acne incidence, respectively. These results were further validated by additional Summary-data-based Mendelian Randomization (SMR) and differential expression analyses. Our comprehensive analysis of proteomic and genetic data from a European adult cohort provides compelling causal evidence that several proteins are promising targets for novel acne treatments.

Sirtuin 1 regulates the phenotype and functions of dendritic cells through Ido1 pathway in obesity

Sirtuin 1 (SIRT1) is a class III histone deacetylase (HDAC3) that plays a crucial role in regulating the activation and differentiation of dendritic cells (DCs) as well as controlling the polarization and activation of T cells. Obesity, a chronic inflammatory condition, is characterized by the activation of immune cells in various tissues. We hypothesized that SIRT1 might influence the phenotype and functions of DCs through the Ido1 pathway, ultimately leading to the polarization towards pro-inflammatory T cells in obesity. In our study, we observed that SIRT1 activity was reduced in bone marrow-derived DCs (BMDCs) from obese animals. These BMDCs exhibited elevated oxidative phosphorylation (OXPHOS) and increased extracellular acidification rates (ECAR), along with enhanced expression of class II MHC, CD86, and CD40, and elevated secretion of IL-12p40, while the production of TGF-β was reduced. The kynurenine pathway activity was decreased in BMDCs from obese animals, particularly under SIRT1 inhibition. SIRT1 positively regulated the expression of Ido1 in DCs in a PPARγ-dependent manner. To support these findings, ATAC-seq analysis revealed that BMDCs from obese mice had differentially regulated open chromatin regions compared to those from lean mice, with reduced chromatin accessibility at the Sirt1 genomic locus in BMDCs from obese WT mice. Gene Ontology (GO) enrichment analysis indicated that BMDCs from obese animals had disrupted metabolic pathways, including those related to GTPase activity and insulin response. Differential expression analysis showed reduced levels of Pparg and Sirt1 in BMDCs from obese mice, which was challenged and confirmed using BMDCs from mice with conditional knockout of Sirt1 in dendritic cells (SIRT1∆). This study highlights that SIRT1 controls the metabolism and functions of DCs through modulation of the kynurenine pathway, with significant implications for obesity-related inflammation.

Sustainable Composites from Waste Polypropylene Added with Thermoset Composite Waste or Recovered Carbon Fibres

In order to limit the ever-increasing consumption of new resources for material formulations, regulations and legislation require us to move from a linear to a circular economy and to find efficient ways to recycle, reuse and recover materials. Taking into account the principles of material circularity and waste reuse, this research study aims to produce thermoplastic composites using two types of industrial waste from neighbouring companies, namely waste polypropylene (wPP) from household production and carbon-fibre-reinforced epoxy composite scrap from a pultrusion company. The industrial scrap of the carbon-fibre-reinforced epoxy composites was either machined/ground to powder (pCFRC) and used directly as a reinforcement agent or subjected to a chemical digestion process to recover the carbon fibres (rCFs). Both pCFRC and rCF, at different weight ratios, were melt-blended with wPP. Prior to melt blending, both pCFRC and rCF were analysed for morphology by scanning electron microscopy (SEM). The pCFRC powder contains epoxy resin fragments with spherical to ellipsoidal shape and carbon fibre fragments. The rCFs are clean from the matrix, but they are slightly thicker and corrugated after the matrix digestion. Further, the morphologies of wPP/pCFRC and wPP/rCF were also investigated by SEM, while the thermal behaviour, i.e., transitions and changes in crystallinity, and thermal resistance were evaluated by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA), respectively. The strength of the interaction between the filler (i.e., pCFRC or rCF) and the wPP matrix and the processability of these composites were assessed by rheological studies. Finally, the mechanical properties of the systems were characterised by tensile tests, and as found, both pCFRC and rCF exert reinforcement effects, although better results were obtained using rCF. The wPP/pCFRC results are more heterogeneous than those of the wPP/rCF due to the presence of epoxy and carbon fibre fragments, and this heterogeneity could be considered responsible for the mechanical behaviour. Further, the presence of both pCFRC and rCF leads to a restriction of polymer chain mobility, which leads to an overall reduction in ductility. All the results obtained suggest that both pCFRC and rCF are good candidates as reinforcing fillers for wPP and that these complex systems could potentially be processed by injection or compression moulding.

Transcriptional variation and RNA polymorphism among different Lentinula edodes (Berk.) Pegler strains.

Lentinula edodes is a commercially important mushroom known for its nutritional and therapeutic values. However, the molecular mechanisms underlying the distinct nutritional and physiological attributes of various L. edodes strains are not well understood. This study focused on three Lentinula strains (DMRO-356, DMRO-623, and DMRO-388s) with different nutritional and productivity profiles. Illumina sequencing was used to perform a whole-transcriptome analysis, conducting 100-base pair paired-end sequencing of total messenger RNA (mRNA) in duplicate, resulting in 28-48 million sequencing reads per strain. After rigorous data filtering, over 99% of high-quality reads were retained, and more than 95% were aligned to the Lentinula genome. Differential gene expression analyses identified 2210 differentially expressed genes between DMRO-356 and DMRO-623, 862 between DMRO-356 and DMRO-388s, and 2212 between DMRO-623 and DMRO-388s. Significant genetic variations were found among the strains, including 7753 single nucleotide polymorphisms (SNPs) in DMRO-356 versus DMRO-623 and 4080 SNPs in DMRO-356 versus DMRO-388s. Additionally, 349 insertions/deletions (InDels) were found in DMRO-356/DMRO-623 and 218 in DMRO-356/DMRO-388 s. Non-synonymous SNPs, which alter amino acid compositions, were analyzed, showing a preference for polar over charged amino acids. These differentially expressed genes were associated with various nutritional and developmental processes, highlighting the importance of genetic variations in shaping amino acid composition and potentially affecting protein function. This study is the first comprehensive exploration of transcriptional differences among Lentinula strains available for its cultivation, providing valuable insights to enhance mushroom quality and productivity. © 2024 Society of Chemical Industry.

Identifying critical modules and biomarkers of intervertebral disc degeneration by using weighted gene co-expression network.

Intervertebral disc degeneration (IVDD) is an age-related orthopedic degenerative disease characterized by recurrent episodes of lower back pain, the pathogenesis of which is not fully understood. This study aimed to identify key biomarkers of IVDD and its causes. We acquired three gene expression profiles from the Gene Expression Omnibus (GEO) database, GSE56081, GSE124272, and GSE153761, and used limma fast differential analysis to identify differentially expressed genes (DEGs) between normal and IVDD samples after removing batch effects. We applied weighted gene co-expression network (WGCNA) to identify the key modular genes in GSE124272 and intersected these with DEGs. Next, A protein-protein interaction network (PPI) was constructed, and Cytoscape was used to identify the Top 10 hub genes. Functional enrichment analyses were performed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Three key genes were validated using Western Blot (WB) and qRT-PCR. Additionally, we predicted miRNAs involved in hub gene co-regulation and analyzed miRNA microarray data from GSE116726 to identify four differentially expressed miRNAs. We identified 10 hub genes using bioinformatics analysis, gene function enrichment analysis revealed that they were primarily enriched in pathways, such as the TNF signaling pathway. We chose JUNB, SOCS3, and CEBPB as hub genes and used WB and qRT-PCR to confirm their expression. All three genes were overexpressed in the IVDD model group compared to the control group. Furthermore, we identified four miRNAs involved in the co-regulation of the hub genes using miRNet prediction: mir-191-5p, mir-20a-5p, mir-155-5p, and mir-124-3p. Using limma difference analysis, we discovered that mir-191-5p, mir-20a-5p, and mir-155-5p were all down-regulated and expressed in IVDD samples, but mir-124-3p showed no significant change. JUNB, SOCS3, and CEBPB were identified as key genes in IVDD, regulated by specific miRNAs, providing potential biomarkers for early diagnosis and therapeutic targets.

Set2 and H3K36 regulate the Drosophila male X chromosome in a context-specific manner, independent from MSL complex spreading.

Dosage compensation in Drosophila involves upregulating male X-genes two-fold. This process is carried out by the MSL (male-specific lethal) complex, which binds high-affinity sites and spreads to surrounding genes. Current models of MSL spreading focus on interactions betwen MSL3 (male-specific lethal 3) and Set2-dependent histone marks like trimethylated H3 lysine-36 (H3K36me3). However, Set2 could affect DC via another target, or there could be redundancy between canonical H3.2 and variant H3.3 histones. Furthermore, it is important to parse male-specific effects from those that are X-specific. To discriminate among these possibilities, we employed genomic approaches in H3K36 'residue' and Set2 'writer' mutants. The results confirm a role for Set2 in X-gene regulation, but show that expression trends in males are often mirrored in females. Instead of global, male-specific reduction of X-genes in Set2 or H3K36 mutants, we observe heterogeneous effects. Interestingly, we identified groups of differentially expressed genes (DEGs) whose changes were in opposite directions following loss of H3K36 or Set2, suggesting that H3K36me states have reciprocal functions. In contrast to H4K16R controls, differential expression analysis of combined H3.2K36R/H3.3K36R mutants showed neither consistent reduction in X-gene expression, nor correlation with MSL3 binding. Motif analysis of the DEGs implicated BEAF-32 and other insulator proteins in Set2/H3K36-dependent regulation. Overall, the data are inconsistent with the prevailing model wherein H3K36me3 is essential for spreading the MSL complex to genes along the male X. Rather, we propose that Set2 and H3K36 support DC indirectly, via processes that are utilized by MSL but common to both sexes.

The translatome of glioblastoma.

Glioblastoma (GB), the most common and aggressive brain tumor, demonstrates intrinsic resistance to current therapies, resulting in poor clinical outcomes. Cancer progression can be partially attributed to the deregulation of protein translation mechanisms that drive cancer cell growth. In this study, we present the translatome landscape of GB as a valuable data resource. Eight patient-derived GB sphere cultures (GSCs) were analyzed using ribosome profiling and messenger RNA (mRNA) sequencing. We investigated inter-cell-line differences through differential expression analysis at both the translatome and transcriptome levels. Translational changes post-radiotherapy were assessed at 30 and 60 min. The translation of non-coding RNAs (ncRNAs) was validated using in-house and public mass spectrometry (MS) data, whereas RNA expression was confirmed by quantitative PCR (qPCR). Our findings demonstrate that ribosome sequencing provides more detailed information than MS or transcriptional analyses. Transcriptional similarities among GSCs correlate with translational similarities, aligning with previously defined subtypes such as proneural and mesenchymal. Additionally, we identified a broad spectrum of open reading frame types in both coding and non-coding mRNA regions, including long non-coding RNAs (lncRNAs) and pseudogenes undergoing active translation. Translation of ncRNAs into peptides was independently confirmed by in-house data and external MS data. We also observed that translational regulation of histones (downregulated) and splicing factors (upregulated) occurs in response to radiotherapy. These data offer new insights into genome-wide protein synthesis, identifying translationally regulated genes and alternative translation initiation sites in GB under normal and radiotherapeutic conditions, providing a rich resource for GB research. Further functional validation of differentially expressed genes after radiotherapy is needed. Understanding translational control in GB can reveal mechanistic insights and identify currently unknown biomarkers, ultimately enhancing the diagnosis and treatment of this aggressive brain cancer.

5-hydroxymethylcytosine sequencing in plasma cell-free DNA identifies unique epigenomic features in prostate cancer patients resistant to androgen deprivation therapies.

Currently, no biomarkers are available to identify resistance to androgen-deprivation therapies (ADT) in men with hormone-naive prostate cancer. Since 5-hydroxymethylcytosines (5hmC) in gene body are associated with gene activation, in this study, we evaluated whether 5hmC signatures in cell-free DNA (cfDNA) predicts early resistance to ADT. We collected a total of 139 serial plasma samples from 55 prostate cancer patients receiving ADT at three time points including baseline (prior to initiating ADT, N=55), 3-month (after initiating ADT, N=55), and disease progression (N=15) within 24 months or 24-month if no progression was detected (N=14). To quantify 5hmC abundance across the genome, we used selective chemical labeling sequencing and mapped sequence reads to individual genes. Differential methylation analysis in baseline samples identified significant 5hmC difference in 1,642 of 23,433 genes between patients with and without progression (false discovery rate, FDR<0.1). Patients with disease progression showed significant 5hmC enrichments in multiple hallmark gene sets with androgen responses as top enriched gene set (FDR=1.19E-13). Interestingly, this enrichment was driven by a subgroup of patients featuring a significant 5hmC hypermethylation in the gene sets involving AR , FOXA1 and GRHL2 . To quantify overall activities of these gene sets, we developed a gene set activity scoring algorithm and observed significant association of high activity scores with poor progression-free survival (P<0.05). Longitudinal analysis showed that the high activity scores were significantly reduced after 3-months of initiating ADT (P<0.0001) but returned to higher levels when the disease was progressed (P<0.05). This study demonstrates that 5hmC-based activity scores from gene sets involved in AR , FOXA1 and GRHL2 may be used as biomarkers to determine early treatment resistance, monitor disease progression, and potentially identify patients who would benefit from upfront treatment intensification.

Computational approaches for identifications of altered ion channels in keratoconus.

Keratoconus is an etiologically complex, degenerative corneal disease that eventually leads to loss of corneal integrity. Cells in corneal epithelium and endothelium express various types of ion channels that play important roles in ocular pathology. This emphasizes the need of understanding alterations of ion channels in keratoconus. Differential gene expression analysis was performed to identify deregulated ion channels in keratoconus patients using transcriptomic data. Thereafter correlation analysis of ion channel expression was performed to obtain the changed correlation between ion channels' expression in keratoconus patients versus control samples. Moreover, Protein-protein interaction networks and a pathway map was constructed to identify cellular processes altered due to the deregulation of ion channels. Furthermore, drugs interacting with deregulated ion channels were identified. Total 75 ion channels were found to be deregulated in keratoconus, of which 12 were upregulated and 63 were downregulated. Correlations between ion channel expressions found to be different in control and keratoconus samples. Thereafter, protein-protein interactions network was generated to identify hub ion channels in network. Furthermore, the pathway map was constructed to depict calcium signalling, MAPK signalling, synthesis and secretion of cortisol, and cAMP signalling. The 19 FDA- approved drugs that interact with the 6 deregulated ion channels were identified. Down-regulation of voltage-gated calcium channels can be attributed to reduced cell proliferation and differentiation. Additionally, deregulated ion channels in 3',5'- cyclic adenosine monophosphate signalling may be responsible for elevated cortisol level in progressive keratoconus patients.

PhenoMultiOmics: an enzymatic reaction inferred multi-omics network visualization web server.

Enzymatic reactions play a pivotal role in regulating cellular processes with a high degree of specificity to biological functions. When enzymatic reactions are disrupted by gene, protein, or metabolite dysfunctions in diseases, it becomes crucial to visualize the resulting perturbed enzymatic reaction-induced multi-omics network. Multi-omics network visualization aids in gaining a comprehensive understanding of the functionality and regulatory mechanisms within biological systems. In this study, we designed PhenoMultiOmics, an enzymatic reaction-based multi-omics web server designed to explore the scope of the multi-omics network across various cancer types. We first curated the PhenoMultiOmics Database (PMODB), which enables the retrieval of cancer-gene-protein-metabolite relationships based on the enzymatic reactions. We then developed the MultiOmics network visualization module to depict the interplay between genes, proteins, and metabolites in response to specific cancer-related enzymatic reactions. The biomarker discovery module facilitates functional analysis through differential omic feature expression and pathway enrichment analysis. PhenoMultiOmics has been applied to analyze transcriptomics data of gastric cancer and metabolomics data of lung cancer, providing insights into interrupted enzymatic reactions and the associated multi-omics network. PhenoMultiOmics is freely accessed at https://phenomultiomics.shinyapps.io/cancer/ with a user-friendly and interactive web interface. Supplementary data are available at Bioinformatics online.

Potential liquid biopsy markers of exosomal microRNAs in renal interstitial fibrosis blood and urine

ABSTRACT Objective: To explore more and better liquid biopsy markers of exosomal microRNAs (exo-miRNAs) in renal interstitial fibrosis (RIF) and to preliminary investigate the biological functions and signaling pathways involved in these markers. MATERIALS AND METHODS: High-throughput miRNA sequencing was performed on blood and urine exo-miRNAs from three RIF patients and three healthy volunteers, and differential expression analysis and bioinformatic processing were performed. Results: There were 13 differentially expressed exo-miRNA (DEexo-miRNA) between RIF and healthy blood, and 20 DEexo-miRNAs in urine. These were various DEexo-miRNAs in different specimens, and the former included PC-3p-213532_58, hsa-miR-338-5p_R-1, PC-5p-34127_410, pal-miR-9993a-3p_L+2R-1, and hsa-miR-26a-1-3p with intermediate expression levels; the latter involved hsa-miR-126-3p, hsa-miR-217-5p, hsa-miR-199b-3p_R-1, mmu-miR-5106_R-4_1ss1AG, and PC-5p-39041_356, and others, while hsa-miR-378a-3p, hsa-miR-143-3p_R+1, hsa-miR-183-5p, hsa-miR-126-3p, hsa-miR-155-5p_R-1, mmu-miR-5106_R-4_1ss1AG, hsa-miR-126-5p, and hsa-miR-199b-3p_R-1 had high expression levels. Bioinformatics analysis of the up-regulated DEmiRNA with high expression in urine showed that there are 291 target corresponding mRNAs for six of eight DEexo-miRNAs, with mmu-miR-5106_R-4_1ss1AG and hsa-miR-199b-3p_R-1 having no target gene found in TargetScan and miRanda. GO annotation revealed that GO:0005515 (protein binding) had the lowest P value, involving the most genes. KEGG analysis revealed that the signaling included the mTOR signaling pathway, autophagy - animal, etc., and hsa05200 (pathways in cancer) had a lower P value, involving the most genes. Conclusions: Urine is a better sample for RIF exo-miRNA detection than blood. Urinary exosomal hsa-miR-143-3p_R+1, hsa-miR-183-5p, hsa-miR-126-3p, mmu-miR-5106_R-4_1ss1AG, hsa-miR-126-5p, and hsa-miR-199b-3p_R-1 are novel liquid biopsy markers for RIF. These DEexo-miRNA may be associated with the occurrence and development of RIF and may participate in specific biological processes by regulating the expression of their target mRNA. Further research may require exploring the specific functions and mechanisms of these miRNAs in RIF, as well as whether they can serve as diagnostic or therapeutic targets for RIF.