STRING: a database of predicted functional associations between proteins

Integrative metabolomic and transcriptomic analyses reveals the accumulation patterns of key metabolites associated with flavonoids and terpenoids of Gynostemma pentaphyllum (Thunb.) Makino

Gynostemma pentaphyllum (Thunb.) Makino (G. pentaphyllum) is a medicinal and edible plant with multiple functions of liver protection, anti-tumor, anti-inflammation, balancing blood sugar and blood lipids. The nutritional value of the G. pentaphyllum plant is mainly due to its rich variety of biologically active substances, such as flavonoids, terpenes and polysaccharides. In this study, we performed a comprehensive analysis combining metabolomics and root, stem and leaf transcriptomic data of G. pentaphyllum. We used transcriptomics and metabolomics data to construct a dynamic regulatory network diagram of G. pentaphyllum flavonoids and terpenoids, and screened the transcription factors involved in flavonoids and terpenoids, including basic helix-loop-helix (bHLH), myb-related, WRKY, AP2/ERF. Transcriptome analysis results showed that among the DEGs related to the synthesis of flavonoids and terpenoids, dihydroflavonol 4-reductase (DFR) and geranylgeranyl diphosphate synthases (GGPPS) were core genes. This study presents a dynamic image of gene expression in different tissues of G. pentaphyllum, elucidating the key genes and metabolites of flavonoids and terpenoids. This study is beneficial to a deeper understanding of the medicinal plants of G. pentaphyllum, and also provides a scientific basis for further regulatory mechanisms of plant natural product synthesis pathways and drug development.

Bioinformatics analysis revealed underlying molecular mechanisms associated with asthma severity and identified GABAergic related pathway as a potential therapy for Th2-high endotype asthma

Background

Asthma, a principally T helper 2 (Th2) cell mediated immunological disease, is categorized into Th2-high and Th2-low endotypes. The influence of these endotypes on clinical characteristics and treatment responsiveness in asthma is yet to be completely understood. This study delves into the underlying molecular mechanisms of Th2 endotypes on asthma.

Methods

Transcriptomics data of airway epithelial and corresponding clinical information were sourced from the GEO. The co-expression modules were established by WGCNA. Cytoscape was applied to construct PPI networks, and hub genes were determined via the Cytohubba plugin. Additionally, a functional enrichment analysis was conducted on the co-expressed genes from the relevant modules. The relative abundances levels of 22 different types of immune cells in asthma patients were evaluated by CIBERSORT algorithm.

Results

There were 471 genes in the pink module significantly correlated with Th2 endotype. Overall, 151 DEGs were identified in the various Th2 endotypes, and 66 were obtained through intersection with the pink module. In the PPI network, the ten most important genes that regulate Th2 endotypes were selected as hub genes. In Th2-high endotype asthma, the hub genes were significantly related to γ-aminobutyric acid (GABA) pathways, indicating that hub genes can mainly regulate Th2-high endotype asthma through GABAergic system.

Conclusions

The severity of asthma is influenced by different Th2 endotypes. GABAergic related hub genes may provide innovative insights for the treatment of Th2-high asthma.

Unraveling the anti-breast cancer activity of Cimicifugae rhizoma using biological network pathways and molecular dynamics simulation

Cimicifugae is a commonly used treatment for breast cancer, but the specific molecular mechanisms underlying its effectiveness remain unclear. In this research, we employ a combination of network pharmacology, molecular docking, and molecular dynamics simulations to uncover the most potent phytochemical within Cimicifugae rhizoma in order to delve into its interaction with the target protein in breast cancer treatment. We identified 18 active compounds and 89 associated targets, primarily associated to various biological processes such as lipid metabolism, the signaling pathway in diabetes, viral infections, and cancer-related pathways. Molecular docking analysis revealed that the two most active compounds, Formononetin and Cimigenol, exhibit strong binding to the target protein AKT1. Through molecular dynamics simulations, we found that the Cimigenol-AKT1 complex exhibits greater structural stability and lower interaction energy compared to the stigmasterol-AKT1 complex. Our study demonstrates that Cimicifugae rhizoma exerts its effects in breast cancer treatment through a multi-component, multi-target synergistic approach. Furthermore, we propose that Cimigenol, targeting AKT-1, represents the most effective compound, offering valuable insights into the molecular mechanisms underpinning its role in breast cancer therapy.

From desert flora to cancer therapy: systematic exploration of multi-pathway mechanisms using network pharmacology and molecular modeling approaches

Ovarian cancer, often labeled a "silent killer," remains one of the most compelling and challenging areas of cancer research. In 2019 alone, a staggering 222,240 new cases of ovarian cancer were reported, with nearly 14,170 lives tragically lost to this relentless disease. The absence of effective diagnostic methods, increased resistance to chemotherapy, and the heterogeneous nature of ovarian cancer collectively contribute to the unfavorable prognosis observed in the majority of cases. Thus, there is a pressing need to explore therapeutic interventions that offer superior efficacy and safety, thereby enhancing the survival prospects for ovarian cancer patients. Recognizing this potential, our research synergizes bioinformatics with a network pharmacology approach to investigate the underlying molecular interactions of Saudi Arabian flora (Onopordum heteracanthum, Acacia ehrenbergiana, Osteospermum vaillantii, Cyperus rotundus, Carissa carandas, Carissa spinarum, and Camellia sinensis) in ovarian cancer treatment. At first, phytoconstituents of indigenous flora and their associated gene targets, particularly those pertinent to ovarian cancer, were obtained from open-access databases. Later, the shared targets of plants and diseases were compared to identify common targets. A protein-protein interaction (PPI) network of predicted targets was then constructed for the identification of key genes having the highest degree of connectivity among networks. Following that, a compound-target protein-pathway network was constructed, which uncovered that, namely, hispidulin, stigmasterol, ascorbic acid, octopamine, cyperene, kaempferol, pungenin, citric acid, d-tartaric acid, beta-sitosterol, (-)-epicatechin gallate, and (+)-catechin demonstrably influence cell proliferation and growth by impacting the AKT1 and VEGFA proteins. Molecular docking, complemented by a 20-ns molecular dynamic (MD) simulation, was used, and the binding affinity of the compound was further validated. Molecular docking, complemented by a 20-ns MD simulation, confirmed the binding affinity of these compounds. Specifically, for AKT1, ascorbic acid showed a docking score of -11.1227 kcal/mol, interacting with residues Ser A:240, Leu A:239, Arg A:243, Arg C:2, and Glu A:341. For VEGFA, hispidulin exhibited a docking score of -17.3714 kcal/mol, interacting with Asn A:158, Val A:190, Gln B:160, Ser A:179, and Ser B:176. To sum up, both a theoretical and empirical framework were established by this study, directing more comprehensive research and laying out a roadmap for the potential utilization of active compounds in the formulation of anti-cancer treatments.

A Cuproptosis-Related gene Signature as a Prognostic Biomarker in Thyroid Cancer Based on Transcriptomics

Thyroid cancer (THCA) is the most prevalent endocrine tumor, and its incidence continues to increase every year. However, the processes underlying the aggressive progression of thyroid cancer are unknown. We concentrated on the prognostic and biological importance of thyroid cancer cuproptosis-related genes in this investigation. Genomic and clinical data were obtained from the UCSC XENA website, and cuproptosis-related genes were obtained from the FerrDb website. We performed differential expression analysis and Cox regression analysis to identify possible predictive targets associated with thyroid cancer prognosis. To assess the role of CDKN2A in thyroid cancer and the ability to predict prognosis on the basis of the CDKN2A expression level, we performed immunohistochemical staining, survival analysis, immunological analysis, functional analysis, and clinical analysis with respect to CDKN2A gene expression. CDKN2A expression levels were found to be inversely correlated with thyroid cancer prognosis. Higher levels of CDKN2A expression were associated with higher T, N, and clinicopathological stage and more residual tumor cells. Through univariate and multivariate Cox regression analyses, the CDKN2A expression level was shown to be linked with thyroid cancer patients' overall survival (OS). Moreover, we discovered that CDKN2A expression was linked to a dysfunctional tumor immune microenvironment. The study shows that CDKN2A, a cuproptosis-related gene, can be used as a prognostic marker for thyroid cancer.

Pan-cancer analysis of Sushi domain-containing protein 4 (SUSD4) and validated in colorectal cancer

Sushi domain-containing protein 4 (SUSD4) is a complement regulatory protein whose primary function is to inhibit the complement system, and it is involved in immune regulation. The role of SUSD4 in cancer progression has largely remained elusive. SUSD4 was studied across a variety of cancer types in this study. According to the results, there is an association between the expression level of SUSD4 and prognosis in multiple types of cancer. Further analysis demonstrated that SUSD4 expression level was related to immune cell infiltration, immune-related genes, tumor heterogeneity, and multiple cancer pathways. Additionally, we validated the function of SUSD4 in colorectal cancer cell lines and found that knockdown of SUSD4 inhibited cell growth and impacted the JAK/STAT pathway. By characterizing drug sensitivity in organoids, we found that the expression of SUSD4 showed a positive correlation trend with IC50 of Selumetinib, YK-4-279, and Piperlongumine. In conclusion, SUSD4 is a valuable prognostic indicator for diverse types of cancer, and it has the potential to be a target for cancer therapy.

Transcriptomics of Marburg virus-infected primary proximal tubular cells reveals negative correlation of immune response and energy metabolism

Marburg virus, a member of the Filoviridae, is the causative agent of Marburg virus disease (MVD), a hemorrhagic fever with a case fatality rate of up to 90 %. Acute kidney injury is common in MVD and is associated with increased mortality, but its pathogenesis in MVD remains poorly understood. Interestingly, autopsies show the presence of viral proteins in different parts of the nephron, particularly in proximal tubular cells (PTC). These findings suggest a potential role for the virus in the development of MVD-related kidney injury. To shed light on this effect, we infected primary human PTC with Lake Victoria Marburg virus and conducted transcriptomic analysis at multiple time points. Unexpectedly, infection did not induce marked cytopathic effects in primary tubular cells at 20 and 40 h post infection. However, gene expression analysis revealed robust renal viral replication and dysregulation of genes essential for different cellular functions. The gene sets mainly downregulated in PTC were associated with the targets of the transcription factors MYC and E2F, DNA repair, the G2M checkpoint, as well as oxidative phosphorylation. Importantly, the downregulated factors comprise PGC-1α, a well-known factor in acute and chronic kidney injury. By contrast, the most highly upregulated gene sets were those related to the inflammatory response and cholesterol homeostasis. In conclusion, Marburg virus infects and replicates in human primary PTC and induces downregulation of processes known to be relevant for acute kidney injury as well as a strong inflammatory response.

Time-series blood cytokine profiles correlate with treatment responses in triple-negative breast cancer patients

BACKGROUND

Triple-negative breast cancer (TNBC) is the most heterogeneous breast cancer subtype. Partly due to its heterogeneity, it is currently challenging to stratify TNBC patients and predict treatment outcomes.

METHODS

In this study, we examined blood cytokine profiles of TNBC patients throughout treatments (pre-treatment, during chemotherapy, pre-surgery, and 1 year after the surgery in a total of 294 samples). We analyzed the obtained cytokine datasets using weighted correlation network analyses, protein-protein interaction analyses, and logistic regression analyses.

RESULTS

We identified five cytokines that correlate with good clinical outcomes: interleukin (IL)-1α, TNF-related apoptosis-inducing ligand (TRAIL), Stem Cell Factor (SCF), Chemokine ligand 5 (CCL5 also known as RANTES), and IL-16. The expression of these cytokines was decreased during chemotherapy and then restored after the treatment. Importantly, patients with good clinical outcomes had constitutively high expression of these cytokines during treatments. Protein-protein interaction analyses implicated that these five cytokines promote an immune response. Logistic regression analyses revealed that IL-1α and TRAIL expression levels at pre-treatment could predict treatment outcomes in our cohort.

CONCLUSION

We concluded that time-series cytokine profiles in breast cancer patients may be useful for understanding immune cell activity during treatment and for predicting treatment outcomes, supporting precision medicine.

TRIAL REGISTRATION

The study has been registered with the University Hospital Medical Information Network Clinical Trials Registry ( http://www.umin.ac.jp/ctr/index-j.htm ) with the unique trial number UMIN000023162. The association Japan Breast Cancer Research Group trial number is JBCRG-22. The clinical outcome of the JBCRG-22 study was published in Breast Cancer Research and Treatment on 25 March 2021. https://doi.org/10.1007/s10549-021-06184-w .

TBX15 and SDHB expression changes in colorectal cancer serve as potential prognostic biomarkers

Alterations in the expression of certain genes could be associated with both patient mortality rates and drug resistance. This study aimed to identify genes in colorectal cancer (CRC) that potentially serve as hub genes influencing patient survival rates. RNA-Seq data were downloaded from the cancer genome atlas database, and differential expression analysis was performed between tumors and healthy controls. Through the utilization of univariate and multivariate Cox regression analyses, in combination with the MCODE clustering module, the genes whose expression changes were related to survival rate and the hub genes related to them were identified. The mortality risk model was computed using the hub genes. CRC samples and the RT-qPCR method were utilized to confirm the outcomes. PharmacoGx data were employed to link the expression of potential genes to medication resistance and sensitivity. The results revealed the discovery of seven hub genes, which emerged as independent prognostic markers. These included HOXC6, HOXC13, HOXC8, and TBX15, which were associated with poor prognosis and overexpression, as well as SDHB, COX5A, and UQCRC1, linked to favorable prognosis and downregulation. Applying the risk model developed with the mentioned genes revealed a markedly higher incidence of deceased patients in the high-risk group compared to the low-risk group. RT-qPCR results indicated a decrease in SDHB expression and an elevation in TBX15 levels in cancer samples relative to adjacent healthy tissue. Also, PharmacoGx data indicated that the expression level of SDHB was correlated with drug sensitivity to Crizotinib and Dovitinib. Our findings highlight the potential association between alterations in the expression of genes such as HOXC6, HOXC13, HOXC8, TBX15, SDHB, COX5A, and UQCRC1 and increased mortality rates in CRC patients. As revealed by the PPI network, these genes exhibited the most connections with other genes linked to survival.

4-octyl itaconate alleviates cisplatin-induced ferroptosis possibly via activating the NRF2/HO-1 signalling pathway

Ferroptosis, characterized by iron-dependent lipid reactive oxygen species (ROS) accumulation, plays a pivotal role in cisplatin-induced ototoxicity. Existing research has suggested that in cisplatin-mediated damage to auditory cells and hearing loss, ferroptosis is partially implicated. 4-Octyl itaconate (4-OI), derived from itaconic acid, effectively permeates cell membranes, showcasing potent anti-inflammatory as well as antioxidant effects in several disease models. Our study aimed to investigate the effect of 4-OI on cisplatin-induced ferroptosis and the underlying molecular mechanisms. The survival rates of HEI-OC1 cells and mice cochlea hair cells were measured by CCK8 and immunofluorescence, respectively. The auditory brainstem response (ABR) audiometry was used to detect changes in hearing thresholds in mice before and after treatment. Levels of ROS were evaluated by DCFH-DA. Real-time PCR quantified inflammatory cytokines TNF-α, IL-6 and IL-1β. Network Pharmacology and RNA sequencing (RNA-seq) analysis of the potential mechanism of 4-OI resistance to cisplatin-induced ferroptosis. The expressions of ferroptosis-related factors (GPX4, SLC7A11 and PTGS2) and important antioxidant factors (NRF2, HO-1, GCLC and NQO1) were tested by real-time PCR, Western blot and immunofluorescence. Results demonstrated cisplatin-induced significant ROS and inflammatory factor release, reduced NRF2 expression, hindered nuclear translocation and activated ferroptosis. Pretreatment with 4-OI exhibited anti-inflammatory and antioxidant effects, along with resistance to ferroptosis, ultimately mitigating cisplatin-induced cell loss. In the present study, we show that 4-OI inhibits cisplatin-induced ferroptosis possibly through activation of the NRF2/HO-1 signalling pathway, thereby exerting a protective effect against cisplatin-induced damage to auditory cells, and providing a new therapeutic strategy for cisplatin-induced hearing loss.

Efficacy and potential mechanism of atherosclerosis prevention by the active components of leech based on network pharmacology combined with animal experiments

Introduction

Leeches are flesh-eating and bloodsucking parasitic worms. They are being used as a traditional Chinese medicine for centuries in activating blood and dissolving statis, dreging the meridims and tick. Hirudin, an active peptide product present in leech, has blood anticoagulant property and can assist in the treatment of thrombosis and diseases related to blood circulation. The efficacy and potential mechanism of action of leeches in such diseases should be further explored.

Materials and methods

First, network pharmacology was used to screen the predicted potential targets of the active constituents of leech and AS. The common targets of the active constituents of leech and AS were obtained using Venn diagram. Further, the drug-active-constituent-target network diagram, protein-protein interaction, and GO and KEGG pathway enrichment analyses were used to construct the active-constituent-AS target-pathway network diagram. Subsequently, the protein-drug molecule docking model was drawn. Finally, the results of network pharmacology were validated using a mouse model of AS.

Results

In total, 34 active constituents of leech and 1172 AS-related gene targets were selected, took the drug action targets and potential disease targets to get the common targets, and took the top 10 of degree value as the main active constituents for the treatment of atherosclerosis. There were 89 common targets and 12 core targets. The main targets included MAPK, EGFR, PIK3CB, etc. Potential regulatory pathways included cancer pathways, EGFR tyrosine kinase inhibitor resistance, Rap1 signaling pathway, PPAR signaling pathway, PI3K-Akt signaling pathway, C-type lectin receptor signaling pathway, and AGE-RAGE signaling pathway in diabetic complications. Animal experiments using mouse model of AS confirmed that AS plaques were smaller after treatment with leeches. SRC level was measured using western blotting. Expression of SRC in myocardial tissue was remarkably lower in the mice treated with leech than in the mice from model group fed on high-fat chow.

Conclusions

To the best of our knowledge, this is the first study to explore the mechanism of action of the active components of leech in AS prevention. The active components of leeches play a coordinated role in preventing AS through multicomponent, multitarget, and multichannel mechanism of action related to inflammatory response, oxidative stress, and lipid metabolism. This study provided a reference for subsequent cellular and animal experiments.

Machine Learning-based Development and Validation of a Cell Senescence Predictive and Prognostic Signature in Intrahepatic Cholangiocarcinoma

Background: Previous studies have shown that cellular senescence is strongly associated with tumorigenesis and the tumor microenvironment. Accordingly, we developed a novel prognostic signature for intrahepatic cholangiocarcinoma (ICCA) based on senescence-associated long non-coding RNAs (SR-lncRNAs) and identified a lncRNA-miRNA-mRNA axis involving in ICCA. Methods: Based on the 197 senescence-associated genes (SRGs) from Genacards and their expression in Fu-ICCA cohort, we identified 20 lncRNAs as senescence-associated lncRNAs (SR-lncRNAs) through co-expression and cox-regression analysis. According to 20 SR-lncRNAs, patients with ICCA were classified into 2 molecular subtypes using unsupervised clustering machine learning approach and to explore the prognostic and functional heterogeneity between these two subtypes. Subsequently, we integrated 113 machine learning algorithms to develop senescence-related lncRNA signature, ultimately identifying 11 lncRNAs and constructing prognostic models and risk stratification. The correlation between the signature and the immune landscape, immunotherapy response as well as drug sensitivity are explored too. Results: We developed a novel senescence related signature. The predictive model and risk score calculated by the signature exhibited favorable prognostic predictive performance, which is a suitable independent risk factor for the prognosis of patients with ICCA based on Kaplan-Meier plotter, nomogram and receiving operating characteristic (ROC) curves. The results were validated using external datasets. Estimate, ssGSEA (single sample gene set enrichment analysis), IPS (immunophenotype score) and TIDE (tumor immune dysfunction and exclusion) algorithms revealed higher immune infiltration, higher immune scores, lower immune escape potential and better response to immunotherapy in the high-risk group. In addition, signature identifies eight chemotherapeutic agents, including cisplatin for patients with different risk levels, providing guidance for clinical treatment. Finally, we identified a set of lncRNA-miRNA-mRNA axes involved in ICCA through regulation of senescence. Conclusion: SR-lncRNAs signature can favorably predict the prognosis, risk stratification, immune landscape and immunotherapy response of patients with ICCA and consequently guide individualized treatment.

Influenza A virus replicates productively in primary human kidney cells and induces factors and mechanisms related to regulated cell death and renal pathology observed in virus-infected patients

Introduction

Influenza A virus (IAV) infection can cause the often-lethal acute respiratory distress syndrome (ARDS) of the lung. Concomitantly, acute kidney injury (AKI) is frequently noticed during IAV infection, correlating with an increased mortality. The aim of this study was to elucidate the interaction of IAV with human kidney cells and, thereby, to assess the mechanisms underlying IAV-mediated AKI.

Methods

To investigate IAV effects on nephron cells we performed infectivity assays with human IAV, as well as with human isolates of either low or highly pathogenic avian IAV. Also, transcriptome and proteome analysis of IAV-infected primary human distal tubular kidney cells (DTC) was performed. Furthermore, the DTC transcriptome was compared to existing transcriptomic data from IAV-infected lung and trachea cells.

Results

We demonstrate productive replication of all tested IAV strains on primary and immortalized nephron cells. Comparison of our transcriptome and proteome analysis of H1N1-type IAV-infected human primary distal tubular cells (DTC) with existing data from H1N1-type IAV-infected lung and primary trachea cells revealed enrichment of specific factors responsible for regulated cell death in primary DTC, which could be targeted by specific inhibitors.

Discussion

IAV not only infects, but also productively replicates on different human nephron cells. Importantly, multi-omics analysis revealed regulated cell death as potential contributing factor for the clinically observed kidney pathology in influenza.

Securin acetylation prevents precocious separase activation and premature sister chromatid separation

Lysine acetylation of non-histone proteins plays crucial roles in many cellular processes. In this study, we examine the role of lysine acetylation during sister chromatid separation in mitosis. We investigate the acetylation of securin at K21 by cell-cycle-dependent acetylome analysis and uncover its role in separase-triggered chromosome segregation during mitosis. Prior to the onset of anaphase, the acetylated securin via TIP60 prevents its degradation by the APC/CCDC20-mediated ubiquitin-proteasome system. This, in turn, restrains precocious activation of separase and premature separation of sister chromatids. Additionally, the acetylation-dependent stability of securin is also enhanced by its dephosphorylation. As anaphase approaches, HDAC1-mediated deacetylation of securin promotes its degradation, allowing released separase to cleave centromeric cohesin. Blocking securin deacetylation leads to longer anaphase duration and errors in chromosome segregation. Thus, this study illustrates the emerging role of securin acetylation dynamics in mitotic progression and genetic stability.

Identification of potential cell death-related biomarkers for diagnosis and treatment of osteoporosis

BACKGROUND

This study aimed to identify potential biomarkers for the diagnosis and treatment of osteoporosis (OP).

METHODS

Data sets were downloaded from the Gene Expression Omnibus database, and differentially programmed cell death-related genes were screened. Functional analyses were performed to predict the biological processes associated with these genes. Least absolute shrinkage and selection operator (LASSO), support vector machine (SVM), and random forest (RF) machine learning algorithms were used to screen for characteristic genes, and receiver operating characteristics were used to evaluate the diagnosis of disease characteristic gene values. Gene set enrichment analysis (GSEA) and single-sample GSEA were conducted to analyze the correlation between characteristic genes and immune infiltrates. Cytoscape and the Drug Gene Interaction Database (DGIdb) were used to construct the mitochondrial RNA-mRNA-transcription factor network and explore small-molecule drugs. Reverse transcription real-time quantitative PCR (RT-qPCR) analysis was performed to evaluate the expression of biomarker genes in clinical samples.

RESULTS

In total, 25 differential cell death genes were identified. Among these, two genes were screened using the LASSO, SVM, and RF algorithms as characteristic genes, including BRSK2 and VPS35. In GSE56815, the area under the receiver operating characteristic curve of BRSK2 was 0.761 and that of VPS35 was 0.789. In addition, immune cell infiltration analysis showed that BRSK2 positively correlated with CD56dim natural killer cells and negatively correlated with central memory CD4 + T cells. Based on the data from DGIdb, hesperadin was associated with BRSK2, and melagatran was associated with VPS35. BRSK2 and VPS35 were expectably upregulated in OP group compared with controls (all p < 0.05).

CONCLUSIONS

BRSK2 and VPS35 may be important diagnostic biomarkers of OP.

Network Pharmacology and Experimental Verification Reveal the Regulatory Mechanism of Chuanbeimu in Treating Chronic Obstructive Pulmonary Disease

Background

Chronic obstructive pulmonary disease (COPD) is a common respiratory disorder in pulmonology. Chuanbeimu (CBM) is a traditional Chinese medicinal herb for treating COPD and has been widely utilized in clinical practice. However, the mechanism of CBM in the treatment of COPD remains incompletely understood. This study aims to investigate the underlying therapeutic mechanism of CBM for COPD using network pharmacology and experimental approaches.

Methods

Active ingredients and their targets were obtained from the Traditional Chinese Medicine Systems Pharmacology database. COPD-associated targets were retrieved from the GeneCards database. The common targets for CBM and COPD were identified through Venn diagram analysis. Protein-protein interaction (PPI) networks and disease-herb-ingredient-target networks were constructed. Subsequently, the results of the network pharmacology were validated by molecular docking and in vitro experiments.

Results

Seven active ingredients and 32 potential targets for CBM were identified as closely associated with COPD. The results of the disease-herb-ingredient-target network and PPI network showed that peimisine emerged as the core ingredient, and SRC, ADRB2, MMP2, and NOS3 were the potential targets for CBM in treating COPD. Molecular docking analysis confirmed that peimisine exhibited high binding affinity with SRC, ADRB2, MMP2, and NOS3. In vitro experiments demonstrated that peimisine significantly upregulated the expression of ADRB2 and NOS3 and downregulated the expression of SRC and MMP2.

Conclusion

These findings indicate that CBM may modulate the expression of SRC, ADRB2, MMP2, and NOS3, thereby exerting a protective effect against COPD.

Mining Heat-Resistant Key Genes of Peony Based on Weighted Gene Co-Expression Network Analysis

The RNA-Seq and gene expression data of mature leaves under high temperature stress of Paeonia suffruticosa 'Hu Hong' were used to explore the key genes of heat tolerance of peony. The weighted gene co-expression network analysis (WGCNA) method was used to construct the network, and the main modules and core genes of co-expression were screened according to the results of gene expression and module function enrichment analysis. According to the correlation of gene expression, the network was divided into 19 modules. By analyzing the expression patterns of each module gene, Blue, Salmon and Yellow were identified as the key modules of peony heat response related functions. GO and KEGG functional enrichment analysis was performed on the genes in the three modules and a network diagram was constructed. Based on this, two key genes PsWRKY53 (TRINITY_DN60998_c1_g2, TRINITY_DN71537_c0_g1) and PsHsfB2b (TRINITY_DN56794_c0_g1) were excavated, which may play a key role in the heat shock response of peony. The three co-expression modules and two key genes were helpful to further elucidate the heat resistance mechanism of P. suffruticosa 'Hu Hong'.

Identifying and validating MMP family members (MMP2, MMP9, MMP12, and MMP16) as therapeutic targets and biomarkers in kidney renal clear cell carcinoma (KIRC)

Kidney Renal Clear Cell Carcinoma (KIRC) is a malignant tumor that carries a substantial risk of morbidity and mortality. The MMP family assumes a crucial role in tumor invasion and metastasis. This study aimed to uncover the mechanistic relevance of the MMP gene family as a therapeutic target and diagnostic biomarker in Kidney Renal Clear Cell Carcinoma (KIRC) through a comprehensive approach encompassing both computational and molecular analyses. STRING, Cytoscape, UALCAN, GEPIA, OncoDB, HPA, cBioPortal, GSEA, TIMER, ENCORI, DrugBank, targeted bisulfite sequencing (bisulfite-seq), conventional PCR, Sanger sequencing, and RT-qPCR based analyses were used in the present study to analyze MMP gene family members to accurately determine a few hub genes that can be utilized as both therapeutic targets and diagnostic biomarkers for KIRC. By performing STRING and Cytohubba analyses of the 24 MMP gene family members, MMP2 (matrix metallopeptidase 2), MMP9 (matrix metallopeptidase 9), MMP12 (matrix metallopeptidase 12), and MMP16 (matrix metallopeptidase 16) genes were denoted as hub genes having highest degree scores. After analyzing MMP2, MMP9, MMP12, and MMP16 via various TCGA databases and RT-qPCR technique across clinical samples and KIRC cell lines, interestingly, all these hub genes were found significantly overexpressed at mRNA and protein levels in KIRC samples relative to controls. The notable effect of the up-regulated MMP2, MMP9, MMP12, and MMP16 was also documented on the overall survival (OS) of the KIRC patients. Moreover, targeted bisulfite-sequencing (bisulfite-seq) analysis revealed that promoter hypomethylation pattern was associated with up-regulation of hub genes (MMP2, MMP9, MMP12, and MMP16). In addition to this, hub genes were involved in various diverse oncogenic pathways. The MMP gene family members (MMP2, MMP9, MMP12, and MMP16) may serve as therapeutic targets and prognostic biomarkers in KIRC.

Molecular analysis to identify novel potential biomarkers as drug targets in colorectal cancer therapy: an integrated bioinformatics analysis

Colorectal cancer (CRC) is a heterogeneous disease that requires new diagnostic and prognostic markers. Integrated bioinformatics approach to identify novel therapeutic targets associated with CRC. Using GEO2R identified DEGs in CRC, and Funrich software facilitated the visualization of DEGs through Venn diagrams. From a total of 114 enhanced DEGs, potential hub genes were further filtered based on their nodal strength and edges using STRING database. To gain insights into the functional roles of these hub genes, gene ontology and pathway enrichment were conducted thorough g: profiler web server. Subsequently, overall survival plots from GEPIA and oncogenic predictive functions like mRNA expressions for stages and nodal metastasis were employed to identify hub genes in CRC patient samples. Additionally, the cBioPortal and HPA databases also revealed genetic alterations and expression levels in these hub genes in CRC patients, further supporting their involvement in colorectal cancer. Gene expression by RT-PCR shows upregulation of hub genes in HT-29 cells. Finally, our integrated bioinformatic analysis revealed that ABCE1, AURKA, HSPD1, PHKA1, CDK4, and YWHAE as hub genes with potential oncogenic roles in CRC. These genes hold promise as diagnostic and prognostic markers for colorectal tumorigenesis, providing insights into targeted therapies for improved patient outcomes.

Protocol for differential multi-omic analyses of distinct cell types in the mouse cerebral cortex

Here, we present a protocol for differential multi-omic analyses of distinct cell types in the developing mouse cerebral cortex. We describe steps for in utero electroporation, subsequent flow-cytometry-based isolation of developing mouse cortical cells, bulk RNA sequencing or quantitative liquid chromatography-tandem mass spectrometry, and bioinformatic analyses. This protocol can be applied to compare the proteomes and transcriptomes of developing mouse cortical cell populations after various manipulations (e.g., epigenetic). For complete details on the use and execution of this protocol, please refer to Meka et al. (2022).1.

Identification of key lncRNAs in age-related macular degeneration through integrated bioinformatics and experimental validation

This study aimed to identify key long noncoding RNAs (lncRNAs) in age-related macular degeneration (AMD) patients and to identify relevant pathological mechanisms of AMD development. We identified 407 differentially expressed mRNAs and 429 differentially expressed lncRNAs in retinal pigment epithelium (RPE) and retina in the macular region of AMD patients versus controls (P < 0.05 and |log2FC| > 0.585) from GSE135092. A total of 14 key differentially expressed mRNAs were obtained through external data validation from GSE115828. A miRNA-mRNA and miRNA-lncRNA network containing 52 lncRNA nodes, 49 miRNA nodes, 14 mRNA nodes and 351 edges was constructed via integrated analysis of these components. Finally, the LINC00276-miR-619-5p-IFIT3 axis was identified via protein-protein network analysis. In the t-BH-induced ARPE-19 senescent cell model, LINC00276 and IFIT3 were downregulated. Overexpression of LINC00276 could accelerate cell migration in combination with IFIT3 upregulation. This compelling finding suggests that LINC00276 plays an influential role in the progression of AMD, potentially through modulating senescence processes, thereby setting a foundation for future investigative efforts to verify this relationship.

Prognostic model revealing pyroptosis-related signatures in oral squamous cell carcinoma based on bioinformatics analysis

One of the most common oral carcinomas is oral squamous cell carcinoma (OSCC), bringing a heavy burden to global health. Although progresses have been made in the intervention of OSCC, 5 years survival of patients suffering from OSCC is poor like before regarding to the high invasiveness of OSCC, which causes metastasis and recurrence of the tumor. The relationship between pyroptosis and OSCC remains to be further investigated as pyroptosis in carcinomas has gained much attention. Herein, the key pyroptosis-related genes were identified according to The Cancer Genome Atlas (TCGA) dataset. Additionally, a prognostic model was constructed based upon three key genes (CTLA4, CD5, and IL12RB2) through least absolute shrinkage and selection operator (LASSO) analyses, as well as univariate and multivariate COX regression in OSCC. It was discovered that the high expression of these three genes was associated with the low-risk group. We also identified LAIR2 as a hub gene, whose expression negatively correlated with the risk score and the different immune cell infiltration. Finally, we proved that these three genes were independent prognostic factors linked to overall survival (OS), and reliable consequences could be predicted by this model. Our study revealed the relationship between pyroptosis and OSCC, providing insights into new treatment targets for preventing and treating OSCC.

Surface Topography, Microbial Adhesion, and Immune Responses in Silicone Mammary Implant-Associated Capsular Fibrosis

Breast cancer is the most common cancer in women globally, often necessitating mastectomy and subsequent breast reconstruction. Silicone mammary implants (SMIs) play a pivotal role in breast reconstruction, yet their interaction with the host immune system and microbiome remains poorly understood. This study investigates the impact of SMI surface topography on host antimicrobial responses, wound proteome dynamics, and microbial colonization. Biological samples were collected from ten human patients undergoing breast reconstruction with SMIs. Mass spectrometry profiles were analyzed for acute and chronic wound proteomes, revealing a nuanced interplay between topography and antimicrobial response proteins. 16S rRNA sequencing assessed microbiome dynamics, unveiling topography-specific variations in microbial composition. Surface topography alterations influenced wound proteome composition. Microbiome analysis revealed heightened diversity around rougher SMIs, emphasizing topography-dependent microbial invasion. In vitro experiments confirmed staphylococcal adhesion, growth, and biofilm formation on SMI surfaces, with increased texture correlating positively with bacterial colonization. This comprehensive investigation highlights the intricate interplay between SMI topography, wound proteome dynamics, and microbial transmission. The findings contribute to understanding host-microbe interactions on SMI surfaces, essential for optimizing clinical applications and minimizing complications in breast reconstruction.

EM-transcriptomic signature predicts drug response in advanced stages of high-grade serous ovarian carcinoma based on ascites-derived primary cultures

Introduction: High-grade serous ovarian carcinoma (HGSOC) remains a medical challenge despite considerable improvements in the treatment. Unfortunately, over 75% of patients have already metastasized at the time of diagnosis. Advances in understanding the mechanisms underlying how ascites cause chemoresistance are urgently needed to derive novel therapeutic strategies. This study aimed to identify the molecular markers involved in drug sensitivity and highlight the use of ascites as a potential model to investigate HGSOC treatment options. Methods: After conducting an in silico analysis, eight epithelial-mesenchymal (EM)-associated genes related to chemoresistance were identified. To evaluate differences in EM-associated genes in HGSOC samples, we analyzed ascites-derived HGSOC primary cell culture (AS), tumor (T), and peritoneal nodule (NP) samples. Moreover, in vitro experiments were employed to measure tumor cell proliferation and cell migration in AS, following treatment with doxorubicin (DOX) and cisplatin (CIS) and expression of these markers. Results: Our results showed that AS exhibits a mesenchymal phenotype compared to tumor and peritoneal nodule samples. Moreover, DOX and CIS treatment leads to an invasive-intermediate epithelial-to-mesenchymal transition (EMT) state of the AS by different EM-associated marker expression. For instance, the treatment of AS showed that CDH1 and GATA6 decreased after CIS exposure and increased after DOX treatment. On the contrary, the expression of KRT18 has an opposite pattern. Conclusion: Taken together, our study reports a comprehensive investigation of the EM-associated genes after drug exposure of AS. Exploring ascites and their associated cellular and soluble components is promising for understanding the HGSOC progression and treatment response at a personalized level.

Prodromal Parkinson disease signs are predicted by a whole-blood inflammatory transcriptional signature in young Pink1-/- rats

BACKGROUND

Parkinson disease (PD) is the fastest growing neurodegenerative disease. The molecular pathology of PD in the prodromal phase is poorly understood; as such, there are no specific prognostic or diagnostic tests. A validated Pink1 genetic knockout rat was used to model early-onset and progressive PD. Male Pink1-/- rats exhibit progressive declines in ultrasonic vocalizations as well as hindlimb and forelimb motor deficits by mid-to-late adulthood. Previous RNA-sequencing work identified upregulation of genes involved in disease pathways and inflammation within the brainstem and vocal fold muscle. The purpose of this study was to identify gene pathways within the whole blood of young Pink1-/- rats (3 months of age) and to link gene expression to early acoustical changes. To accomplish this, limb motor testing (open field and cylinder tests) and ultrasonic vocalization data were collected, immediately followed by the collection of whole blood and RNA extraction. Illumina® Total RNA-Seq TruSeq platform was used to profile differential expression of genes. Statistically significant genes were identified and Weighted Gene Co-expression Network Analysis was used to construct co-expression networks and modules from the whole blood gene expression dataset as well as the open field, cylinder, and USV acoustical dataset. ENRICHR was used to identify the top up-regulated biological pathways.

RESULTS

The data suggest that inflammation and interferon signaling upregulation in the whole blood is present during early PD. We also identified genes involved in the dysregulation of ribosomal protein and RNA processing gene expression as well as prion protein gene expression.

CONCLUSIONS

These data identified several potential blood biomarkers and pathways that may be linked to anxiety and vocalization acoustic parameters and are key candidates for future drug-repurposing work and comparison to human datasets.

Diel Cycle Proteomics: Illuminating Molecular Dynamics in Purple Bacteria for Optimized Biotechnological Applications

Circadian rhythms, characterized by approximately 24 h cycles, play a pivotal role in enabling various organisms to synchronize their biological activities with daily variations. While ubiquitous in Eukaryotes, circadian clocks remain exclusively characterized in Cyanobacteria among Prokaryotes. These rhythms are regulated by a core oscillator, which is controlled by a cluster of three genes: kaiA, kaiB, and kaiC. Interestingly, recent studies revealed rhythmic activities, potentially tied to a circadian clock, in other Prokaryotes, including purple bacteria such as Rhodospirillum rubrum, known for its applications in fuel and plastic bioproduction. However, the pivotal question of how light and dark cycles influence protein dynamics and the expression of putative circadian clock genes remains unexplored in purple non-sulfur bacteria. Unraveling the regulation of these molecular clocks holds the key to unlocking optimal conditions for harnessing the biotechnological potential of R. rubrum. Understanding how its proteome responds to different light regimes-whether under continuous light or alternating light and dark cycles-could pave the way for precisely fine-tuning bioproduction processes. Here, we report for the first time the expressed proteome of R. rubrum grown under continuous light versus light and dark cycle conditions using a shotgun proteomic analysis. In addition, we measured the impact of light regimes on the expression of four putative circadian clock genes (kaiB1, kaiB2, kaiC1, kaiC2) at the transcriptional and translational levels using RT-qPCR and targeted proteomic (MRM-MS), respectively. The data revealed significant effects of light conditions on the overall differential regulation of the proteome, particularly during the early growth stages. Notably, several proteins were found to be differentially regulated during the light or dark period, thus impacting crucial biological processes such as energy conversion pathways and the general stress response. Furthermore, our study unveiled distinct regulation of the four kai genes at both the mRNA and protein levels in response to varying light conditions. Deciphering the impact of the diel cycle on purple bacteria not only enhances our understanding of their ecology but also holds promise for optimizing their applications in biotechnology, providing valuable insights into the origin and evolution of prokaryotic clock mechanisms.

Integrated gene co-expression network analysis and experimental validation revealed potential targets of human urine extract CDA-II in treating chronic myeloid leukemia

BACKGROUND

Cell differentiation agent II (CDA-II) exhibits potent anti-proliferative and apoptosis-inducing properties against a variety of cancer cells. However, its mechanism of action in chronic myeloid leukemia (CML) remains unclear.

METHODS

Cell counting Kit 8 (CCK-8) and flow cytometry were used to investigate the effects of CDA-II on the biological characteristics of K562 cells. Gene (mRNA and lncRNA) expression profiles were analyzed by bioinformatics to screen differentially expressed genes and to perform enrichment analysis. The Pearson correlation coefficients of lncRNAs and mRNAs were calculated using gene expression values, and a lncRNA/mRNA co-expression network was constructed. The MCODE and cytoHubba plugins were used to analyze the co-expression network.

RESULTS

The Results, derived from CCK-8 and flow cytometry, indicated that CDA-II exerts dual effects on K562 cells: it inhibits their proliferation and induces apoptosis. From bioinformatics analysis, we identified 316 mRNAs and 32 lncRNAs. These mRNAs were predominantly related to the meiotic cell cycle, DNA methylation, transporter complex and peptidase regulator activity, complement and coagulation cascades, protein digestion and absorption, and cell adhesion molecule signaling pathways. The co-expression network comprised of 163 lncRNA/mRNA interaction pairs. Notably, our analysis results implicated clustered histone gene families and five lncRNAs in the biological effects of CDA-II on K562 cells.

CONCLUSION

This study highlights the hub gene and lncRNA/mRNA co-expression network as crucial elements in the context of CDA-II treatment of CML. This insight not only enriches our understanding of CDA-II's mechanism of action but also might provide valuable clues for subsequent experimental studies of CDA-II, and potentially contribute to the discovery of new therapeutic targets for CML.

Oral squamous cell carcinoma gene patterns connected with RNA methylation for prognostic prediction

OBJECTIVES

To determine whether m6A/m1A/m5C/m7G/m6Am/Ψ-related genes influence the prognosis of a patient with oral squamous cell carcinoma.

MATERIALS AND METHODS

We investigated the changes in regulatory genes using publicly available data from The Cancer Genome Atlas. Consensus clustering by RNA methylation-related regulators was used to describe oral squamous cell carcinomas (OSCCs). Then, we developed the prediction model. The tumor microenvironment was investigated using ESTIMATE. Gene set enrichment analysis was used to determine whether pathways or cell types were enriched in different groups. The association between the model and immune-related risk scores was investigated using correlation analysis.

RESULTS

We found 22 gene signatures in this analysis and then developed a predictive model that reveals the genes that are highly connected to the overall survival of OSCC patients. The survival and death rates were substantially different in the two groups (high and low risk) classified by the risk scores. The validation cohort verified the phenotypic diversity and prognostic effects of these genes.

CONCLUSION

Our data reveal that immune cell infiltration, genetic mutation, and survival potential in OSCC patients are linked to m6A/m1A/m5C/m7G/m6Am/Ψ-related genes, and we constructed a dependable prognostic model for OSCC patients.

Interleukin-4 induced 1-mediated resistance to an immune checkpoint inhibitor through suppression of CD8+ T cell infiltration in melanoma

Cancer cells adopt multiple strategies to escape tumor surveillance by the host immune system and aberrant amino acid metabolism in the tumor microenvironment suppresses the immune system. Among the amino acid-metabolizing enzymes is an L-amino-acid oxidase called interleukin-4 induced 1 (IL4I1), which depletes essential amino acids in immune cells and is associated with a poor prognosis in various cancer types. Although IL4I1 is involved in immune metabolism abnormalities, its effect on the therapeutic efficacy of immune checkpoint inhibitors is unknown. In this study, we established murine melanoma cells overexpressing IL4I1 and investigated their effects on the intratumor immune microenvironment and the antitumor efficacy of anti-programmed death-ligand 1 (PD-L1) antibodies (Abs) in a syngeneic mouse model. As a result, we found that IL4I1-overexpressing B16-F10-derived tumors showed resistance to anti-PD-L1 Ab therapy. Transcriptome analysis revealed that immunosuppressive genes were globally upregulated in the IL4I1-overexpressing tumors. Consistently, we showed that IL4I1-overexpressing tumors exhibited an altered subset of lymphoid cells and particularly significant suppression of cytotoxic T cell infiltration compared to mock-infected B16-F10-derived tumors. After treatment with anti-PD-L1 Abs, we also found a more prominent elevation of tumor-associated macrophage (TAM) marker, CD68, in the IL4I1-overexpressing tumors than in the mock tumors. Consistently, we confirmed an enhanced TAM infiltration in the IL4I1-overexpressing tumors and a functional involvement of TAMs in the tumor growth. These observations indicate that IL4I1 reprograms the tumor microenvironment into an immunosuppressive state and thereby confers resistance to anti-PD-L1 Abs.

Proteomic profiling of interferon-responsive reactive astrocytes in rodent and human

Astrocytes are a heterogeneous population of central nervous system glial cells that respond to pathological insults and injury by undergoing a transformation called "reactivity." Reactive astrocytes exhibit distinct and context-dependent cellular, molecular, and functional state changes that can either support or disturb tissue homeostasis. We recently identified a reactive astrocyte sub-state defined by interferon-responsive genes like Igtp, Ifit3, Mx1, and others, called interferon-responsive reactive astrocytes (IRRAs). To further this transcriptomic definition of IRRAs, we wanted to define the proteomic changes that occur in this reactive sub-state. We induced IRRAs in immunopanned rodent astrocytes and human iPSC-differentiated astrocytes using TNF, IL1α, C1Q, and IFNβ and characterized their proteomic profile (both cellular and secreted) using unbiased quantitative proteomics. We identified 2335 unique cellular proteins, including IFIT2/3, IFITM3, OASL1/2, MX1/2/3, and STAT1. We also report that rodent and human IRRAs secrete PAI1, a serine protease inhibitor which may influence reactive states and functions of nearby cells. Finally, we evaluated how IRRAs are distinct from neurotoxic reactive astrocytes (NRAs). While NRAs are described by expression of the complement protein C3, it was not upregulated in IRRAs. Instead, we found ~90 proteins unique to IRRAs not identified in NRAs, including OAS1A, IFIT3, and MX1. Interferon signaling in astrocytes is critical for the antiviral immune response and for regulating synaptic plasticity and glutamate transport mechanisms. How IRRAs contribute to these functions is unknown. This study provides the basis for future experiments to define the functional roles of IRRAs in the context of neurodegenerative disorders.

Perinatal exposure to PFOS and sustained high-fat diet promote neurodevelopmental disorders via genomic reprogramming of pathways associated with neuromotor development

Perfluorooctanesulfonic acid (PFOS) is a neurotoxic widespread organic contaminant which affects several brain functions including memory, motor coordination and social activity. PFOS has the ability to traverse the placenta and the blood brain barrier (BBB) and cause weight gain in female mice. It's also known that obesity and consumption of a high fat diet have negative effects on the brain, impairs cognition and increases the risk for the development of dementia. The combination effect of developmental exposure to PFOS and the intake of a high-fat diet (HFD) has not been explored. This study investigates the effect of PFOS and /or HFD on weight gain, behavior and transcriptomic and proteomic analysis of adult brain mice. We found that female mice exposed to PFOS alone showed an increase in weight, while HFD expectedly increased body weight. The combination of HFD and PFOS exacerbated generalized behavior such as time spent in the center and rearing, while PFOS alone impacted the distance travelled. These results suggest that PFOS exposure may promote hyperactivity. The combination of PFOS and HFD alter social behavior such as rearing and withdrawal. Although HFD interfered with memory retrieval, biomarkers of dementia did not change except for total Tau and phosphorylated Tau. Tau was impacted by either or both PFOS exposure and HFD. Consistent with behavioral observations, global cerebral transcriptomic analysis showed that PFOS exposure affects calcium signaling, MAPK pathways, ion transmembrane transport, and developmental processes. The combination of HFD with PFOS enhances the effect of PFOS in the brain and affects pathways related to ER stress, axon guidance and extension, and neural migration. Proteomic analysis showed that HFD enhances the impact of PFOS on inflammatory pathways, regulation of cell migration and proliferation, and MAPK signaling pathways. Overall, these data show that PFOS combined with HFD may reprogram the genome and modulate neuromotor development and may promote symptoms linked to attention deficit-hyperactivity disorders (ADHD) and autism spectrum disorders (ASD). Future work will be needed to confirm these connections.

ADAMTS12, a novel prognostic predictor, promotes cell proliferation, migration, and invasion in head and neck squamous cell carcinoma

OBJECTIVES

The prognostic significance and potential carcinogenic mechanism of ADAM metallopeptidase with thrombospondin type 1 motif 12 (ADAMTS12) in head and neck squamous cell carcinoma (HNSC) remain unclear.

MATERIALS AND METHODS

Immunohistochemistry was used to analyze the correlation between ADAMTS12 protein expression and clinicopathological factors in tumor samples from 195 patients with HNSC. Based on clinicopathological data of patients, Cox regression and Kaplan-Meier analysis were used to identify the prognostic significance of the ADAMTS12 expression. The carcinogenicity of the ADAMTS12 in HNSC cells was analyzed by CCK-8 assay, the wound-healing assay, and transwell assays after transfection of ADAMTS12 overexpression or knock-down vector.

RESULTS

The expression of ADAMTS12 was up-regulated in HNSC compared with normal tissue, related to pathology grade and lymph node metastasis of patients with HNSC, which was an independent prognostic factor. ADAMTS12 overexpression facilitated cell viability, invasion, and migration of HNSC cells, while ADAMTS12 knock-down had inverse results. Moreover, enrichment analysis, ADAMTS12 overexpression assay, and ADAMTS12 knock-down assay confirmed that ADAMTS12 mediated the activation of P13K/Akt pathway in HNSC.

CONCLUSIONS

Our studies indicated that ADAMTS12 was a novel prognostic biomarker and potentially therapeutic target in HNSC.

Biomarker screening using integrated bioinformatics for the development of "normal-impaired glucose intolerance-type 2 diabetes mellitus"

Type 2 diabetes mellitus (T2DM) is a progressive disease. We utilized bioinformatics analysis and experimental research to identify biomarkers indicative of the progression of T2DM, aiming for early detection of the disease and timely clinical intervention. Integrating Mfuzz analysis with differential expression analysis, we identified 76 genes associated with the progression of T2DM, which were primarily enriched in signaling pathways such as apoptosis, p53 signaling, and necroptosis. Subsequently, using various analytical methods, including machine learning, we further narrowed down the hub genes to STK17A and CCT5. Based on the hub genes, we calculated the risk score for samples and interestingly found that the score correlated with multiple programmed cell death (PCD) pathways. Animal experiments revealed that the diabetes model exhibited higher levels of MDA and LDH, with lower expression of SOD, accompanied by islet cell apoptosis. In conclusion, our study suggests that during the progression of diabetes, STK17A and CCT5 may contribute to the advancement of the disease by regulating oxidative stress, programmed cell death pathways, and critical signaling pathways such as p53 and MAPK, thereby promoting the death of islet cells. This provides substantial evidence in support of further disease prevention and treatment strategies.

High-throughput drug target discovery using a fully automated proteomics sample preparation platform

Drug development is plagued by inefficiency and high costs due to issues such as inadequate drug efficacy and unexpected toxicity. Mass spectrometry (MS)-based proteomics, particularly isobaric quantitative proteomics, offers a solution to unveil resistance mechanisms and unforeseen side effects related to off-targeting pathways. Thermal proteome profiling (TPP) has gained popularity for drug target identification at the proteome scale. However, it involves experiments with multiple temperature points, resulting in numerous samples and considerable variability in large-scale TPP analysis. We propose a high-throughput drug target discovery workflow that integrates single-temperature TPP, a fully automated proteomics sample preparation platform (autoSISPROT), and data independent acquisition (DIA) quantification. The autoSISPROT platform enables the simultaneous processing of 96 samples in less than 2.5 hours, achieving protein digestion, desalting, and optional TMT labeling (requires an additional 1 hour) with 96-channel all-in-tip operations. The results demonstrated excellent sample preparation performance with >94% digestion efficiency, >98% TMT labeling efficiency, and >0.9 intra- and inter-batch Pearson correlation coefficients. By automatically processing 87 samples, we identified both known targets and potential off-targets of 20 kinase inhibitors, affording over a 10-fold improvement in throughput compared to classical TPP. This fully automated workflow offers a high-throughput solution for proteomics sample preparation and drug target/off-target identification.

KAT8-catalyzed lactylation promotes eEF1A2-mediated protein synthesis and colorectal carcinogenesis

Aberrant lysine lactylation (Kla) is associated with various diseases which are caused by excessive glycolysis metabolism. However, the regulatory molecules and downstream protein targets of Kla remain largely unclear. Here, we observed a global Kla abundance profile in colorectal cancer (CRC) that negatively correlates with prognosis. Among lactylated proteins detected in CRC, lactylation of eEF1A2K408 resulted in boosted translation elongation and enhanced protein synthesis which contributed to tumorigenesis. By screening eEF1A2 interacting proteins, we identified that KAT8, a lysine acetyltransferase that acted as a pan-Kla writer, was responsible for installing Kla on many protein substrates involving in diverse biological processes. Deletion of KAT8 inhibited CRC tumor growth, especially in a high-lactic tumor microenvironment. Therefore, the KAT8-eEF1A2 Kla axis is utilized to meet increased translational requirements for oncogenic adaptation. As a lactyltransferase, KAT8 may represent a potential therapeutic target for CRC.

Integrating network pharmacology, molecular docking and simulation approaches with machine learning reveals the multi-target pharmacological mechanism of Berberis integerrima against diabetic nephropathy

Diabetic nephropathy (DN) is one of the most feared complications of diabetes and key cause of end-stage renal disease (ESRD). Berberis integerrima has been widely used to treat diabetic complications, but exact molecular mechanism is yet to be discovered. Data on active ingredients of B. integerrima and target genes of both diabetic nephropathy and B.integerrima were obtained from public databases. Common results between B. integerrima and DN targets were used to create protein-protein interaction (PPI) network using STRING database and exported to Cytoscape software for the selection of hub genes based on degree of connectivity. Future, PPI network between constituents and overlapping targets was created using Cytoscape to investigate the network pharmacological effects of B. integerrima on DN. KEGG pathway analysis of core genes exposed their involvement in excess glucose-activated signaling pathway. Then, expression of core genes was validated through machine learning classifiers. Finally, PyRx and AMBER18 software was used for molecular docking and simulation. We found that Armepavine, Berberine, Glaucine, Magnoflorine, Reticuline, Quercetin inhibits the growth of diabetic nephropathy by affecting ICAM1, PRKCB, IKBKB, KDR, ALOX5, VCAM1, SYK, TBXA2R, LCK, and F3 genes. Machine learning revealed SYK and PRKCB as potential genes that could use as diagnostic biomarkers against DN. Furthermore, docking and simulation analysis showed the binding affinity and stability of the active compound with target genes. Our study revealed that B. integerrima has preventive effect on DN by acting on glucose-activated signaling pathways. However, experimental studies are needed to reveal biosafety profiles of B. integerrima in DN.Communicated by Ramaswamy H. Sarma.

Targets and Effects of Common Biocompounds of Hibiscus sabdariffa (Delphinidin-3-Sambubiosid, Quercetin, and Hibiscus Acid) in Different Pathways of Human Cells According to a Bioinformatic Assay

The utilization of food as a therapeutic measure for various ailments has been a prevalent practice throughout history and across different cultures. This is exemplified in societies where substances like Hibiscus sabdariffa have been employed to manage health conditions like hypertension and elevated blood glucose levels. The inherent bioactive compounds found in this plant, namely, delphinidin-3-sambubioside (DS3), quercetin (QRC), and hibiscus acid (HA), have been linked to various health benefits. Despite receiving individual attention, the specific molecular targets for these compounds remain unclear. In this study, computational analysis was conducted using bioinformatics tools such as Swiss Target Prediction, ShinnyGo 0.77, KEGG, and Stringdb to identify the molecular targets, pathways, and hub genes. Supplementary results were obtained through a thorough literature search in PubMed. DS3 analysis revealed potential genetic alterations related to the metabolism of nitrogen and glucose, inflammation, angiogenesis, and cell proliferation, particularly impacting the PI3K-AKT signaling pathway. QRC analysis demonstrated interconnected targets spanning multiple pathways, with some overlap with DS3 analysis and a particular focus on pathways related to cancer. HA analysis revealed distinct targets, especially those associated with pathways related to the nervous system. These findings emphasize the necessity for focused research on the molecular effects of DS3, QRC, and HA, thereby providing valuable insights into potential therapeutic pathways.

Proteomic characterization identifies clinically relevant subgroups of soft tissue sarcoma

Soft tissue sarcoma is a broad family of mesenchymal malignancies exhibiting remarkable histological diversity. We portray the proteomic landscape of 272 soft tissue sarcomas representing 12 major subtypes. Hierarchical classification finds the similarity of proteomic features between angiosarcoma and epithelial sarcoma, and elevated expression of SHC1 in AS and ES is correlated with poor prognosis. Moreover, proteomic clustering classifies patients of soft tissue sarcoma into 3 proteomic clusters with diverse driven pathways and clinical outcomes. In the proteomic cluster featured with the high cell proliferation rate, APEX1 and NPM1 are found to promote cell proliferation and drive the progression of cancer cells. The classification based on immune signatures defines three immune subtypes with distinctive tumor microenvironments. Further analysis illustrates the potential association between immune evasion markers (PD-L1 and CD80) and tumor metastasis in soft tissue sarcoma. Overall, this analysis uncovers sarcoma-type-specific changes in proteins, providing insights about relationships of soft tissue sarcoma.

Bone morphogenetic protein 1: a prognostic indicator and potential biomarker in three cancer types

BACKGROUND

Bone morphogenetic protein 1 (BMP1) is a metalloprotease that plays a role in activating both transforming growth factor-β (TGF-β) and BMP signaling pathways. TGF-β has been identified as a factor initiating and facilitating cancer development. Consequently, we propose the hypothesis that dysregulation of BMP1 could potentially contribute to the onset and advancement of human cancers.

METHODS

In this research, we aimed to analyze BMP1 expression level and the associated clinical outcomes across various cancers using online cancer OMICS databases, advanced Bioinformatics tools, and molecular analyses.

RESULTS

The outcomes of our web server-based expression analysis indicated an up-regulation of BMP1 in a majority of the human cancers examined. External validation using clinical samples also showed higher expression of BMP1. Moreover, heightened BMP1 expression exhibited a noteworthy correlation with reduced overall survival (OS) duration in Bladder Cancer (BLCA), Kidney Renal Clear Cell Carcinoma (KIRC), and Lung Adenocarcinoma (LUAD) patients. This suggests a substantial involvement of the BMP1 gene in the development and progression of these three types of cancers. The major signaling pathways related with BMP1 enriched genes were "ECM-receptor interaction, Amoebiasis, Focal adhesion, Protein digestion and absorption, progesterone-mediated, PI3K-Akt signaling pathway, and platelet activation". Moreover, we also explored some interesting correlations among BMP1 expression and its DNA promoter methylation level, CD8+ T immune cells level, and genetic variations.

CONCLUSION

In conclusion, our study has provided some solid basis for BMP1 to be used as a reliable common biomarker for BLCA, KIRC, and LUAD patients.

Identification of diagnostic model in heart failure with myocardial fibrosis and conduction block by integrated gene co-expression network analysis

BACKGROUND

Despite the advancements in heart failure(HF) research, the early diagnosis of HF continues to be a challenging issue in clinical practice. This study aims to investigate the genes related to myocardial fibrosis and conduction block, with the goal of developing a diagnostic model for early treatment of HF in patients.

METHOD

The gene expression profiles of GSE57345, GSE16499, and GSE9128 were obtained from the Gene Expression Omnibus (GEO) database. After merging the expression profile data and adjusting for batch effects, differentially expressed genes (DEGs) associated with conduction block and myocardial fibrosis were identified. Gene Ontology (GO) resources, Kyoto Encyclopedia of Genes and Genomes (KEGG) resources, and gene set enrichment analysis (GSEA) were utilized for functional enrichment analysis. A protein-protein interaction network (PPI) was constructed using a string database. Potential key genes were selected based on the bioinformatics information mentioned above. SVM and LASSO were employed to identify hub genes and construct the module associated with HF. The mRNA levels of TAC mice and external datasets (GSE141910 and GSE59867) are utilized for validating the diagnostic model. Additionally, the study explores the relationship between the diagnostic model and immune cell infiltration.

RESULTS

A total of 395 genes exhibiting differential expression were identified. Functional enrichment analysis revealed that these specific genes primarily participate in biological processes and pathways associated with the constituents of the extracellular matrix (ECM), immune system processes, and inflammatory responses. We identified a diagnostic model consisting of 16 hub genes, and its predictive performance was validated using external data sets and a transverse aortic coarctation (TAC) mouse model. In addition, we observed significant differences in mRNA expression of 7 genes in the TAC mouse model. Interestingly, our study also unveiled a correlation between these model genes and immune cell infiltration.

CONCLUSIONS

We identified sixteen key genes associated with myocardial fibrosis and conduction block, as well as diagnostic models for heart failure. Our findings have significant implications for the intensive management of individuals with potential genetic variants associated with heart failure, especially in the context of advancing cell-targeted therapy for myocardial fibrosis.

Gene expression analysis reveals diabetes-related gene signatures

BACKGROUND

Diabetes is a spectrum of metabolic diseases affecting millions of people worldwide. The loss of pancreatic β-cell mass by either autoimmune destruction or apoptosis, in type 1-diabetes (T1D) and type 2-diabetes (T2D), respectively, represents a pathophysiological process leading to insulin deficiency. Therefore, therapeutic strategies focusing on restoring β-cell mass and β-cell insulin secretory capacity may impact disease management. This study took advantage of powerful integrative bioinformatic tools to scrutinize publicly available diabetes-associated gene expression data to unveil novel potential molecular targets associated with β-cell dysfunction.

METHODS

A comprehensive literature search for human studies on gene expression alterations in the pancreas associated with T1D and T2D was performed. A total of 6 studies were selected for data extraction and for bioinformatic analysis. Pathway enrichment analyses of differentially expressed genes (DEGs) were conducted, together with protein-protein interaction networks and the identification of potential transcription factors (TFs). For noncoding differentially expressed RNAs, microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), which exert regulatory activities associated with diabetes, identifying target genes and pathways regulated by these RNAs is fundamental for establishing a robust regulatory network.

RESULTS

Comparisons of DEGs among the 6 studies showed 59 genes in common among 4 or more studies. Besides alterations in mRNA, it was possible to identify differentially expressed miRNA and lncRNA. Among the top transcription factors (TFs), HIPK2, KLF5, STAT1 and STAT3 emerged as potential regulators of the altered gene expression. Integrated analysis of protein-coding genes, miRNAs, and lncRNAs pointed out several pathways involved in metabolism, cell signaling, the immune system, cell adhesion, and interactions. Interestingly, the GABAergic synapse pathway emerged as the only common pathway to all datasets.

CONCLUSIONS

This study demonstrated the power of bioinformatics tools in scrutinizing publicly available gene expression data, thereby revealing potential therapeutic targets like the GABAergic synapse pathway, which holds promise in modulating α-cells transdifferentiation into β-cells.

Landscape of protein-protein interactions during hepatitis C virus assembly and release

Assembly of infectious hepatitis C virus (HCV) particles requires multiple cellular proteins including for instance apolipoprotein E (ApoE). To describe these protein-protein interactions, we performed an affinity purification mass spectrometry screen of HCV-infected cells. We used functional viral constructs with epitope-tagged envelope protein 2 (E2), protein (p) 7, or nonstructural protein 4B (NS4B) as well as cells expressing a tagged variant of ApoE. We also evaluated assembly stage-dependent remodeling of protein complexes by using viral mutants carrying point mutations abrogating particle production at distinct steps of the HCV particle production cascade. Five ApoE binding proteins, 12 p7 binders, 7 primary E2 interactors, and 24 proteins interacting with NS4B were detected. Cell-derived PREB, STT3B, and SPCS2 as well as viral NS2 interacted with both p7 and E2. Only GTF3C3 interacted with E2 and NS4B, highlighting that HCV assembly and replication complexes exhibit largely distinct interactomes. An HCV core protein mutation, preventing core protein decoration of lipid droplets, profoundly altered the E2 interactome. In cells replicating this mutant, E2 interactions with HSPA5, STT3A/B, RAD23A/B, and ZNF860 were significantly enhanced, suggesting that E2 protein interactions partly depend on core protein functions. Bioinformatic and functional studies including STRING network analyses, RNA interference, and ectopic expression support a role of Rad23A and Rad23B in facilitating HCV infectious virus production. Both Rad23A and Rad23B are involved in the endoplasmic reticulum (ER)-associated protein degradation (ERAD). Collectively, our results provide a map of host proteins interacting with HCV assembly proteins, and they give evidence for the involvement of ER protein folding machineries and the ERAD pathway in the late stages of the HCV replication cycle.IMPORTANCEHepatitis C virus (HCV) establishes chronic infections in the majority of exposed individuals. This capacity likely depends on viral immune evasion strategies. One feature likely contributing to persistence is the formation of so-called lipo-viro particles. These peculiar virions consist of viral structural proteins and cellular lipids and lipoproteins, the latter of which aid in viral attachment and cell entry and likely antibody escape. To learn about how lipo-viro particles are coined, here, we provide a comprehensive overview of protein-protein interactions in virus-producing cells. We identify numerous novel and specific HCV E2, p7, and cellular apolipoprotein E-interacting proteins. Pathway analyses of these interactors show that proteins participating in processes such as endoplasmic reticulum (ER) protein folding, ER-associated protein degradation, and glycosylation are heavily engaged in virus production. Moreover, we find that the proteome of HCV replication sites is distinct from the assembly proteome, suggesting that transport process likely shuttles viral RNA to assembly sites.

Anoikis-related signature predicts prognosis and characterizes immune landscape of ovarian cancer

Ovarian cancer (OV) is the most lethal gynecological malignancy worldwide, with high recurrence rates. Anoikis, a newly-acknowledged form of programmed cell death, plays an essential role in cancer progression, though studies focused on prognostic patterns of anoikis in OV are still lacking. We filtered 32 potential anoikis-related genes (ARGs) among the 6406 differentially expressed genes (DEGs) between the 180 normal controls and 376 TCGA-OV samples. Through the LASSO-Cox analysis, a 2-gene prognostic signature, namely AKT2, and DAPK1, was finally distinguished. We then demonstrated the promising prognostic value of the signature through the K-M survival analysis and time-dependent ROC curves (p-value < 0.05). Moreover, based on the signature and clinical features, we constructed and validated a nomogram model for 1-year, 3-year, and 5-year overall survival, with reliable prognostic values in both TCGA-OV training cohort (p-value < 0.001) and ICGC-OV validation cohort (p-value = 0.030). We evaluated the tumor immune landscape through the CIBERSORT algorithm, which indicated the upregulation of resting Myeloid Dendritic Cells (DCs), memory B cells, and naïve B cells and high expression of key immune checkpoint molecules (CD274 and PDCD1LG2) in the high-risk group. Interestingly, the high-risk group exhibited better sensitivity toward immunotherapy and less sensitivity toward chemotherapies, including Cisplatin and Bleomycin. Especially, based on the IHC of tissue microarrays among 125 OV patients at our institution, we reported that aberrant upregulation of DAPK1 was related to poor prognosis. Conclusively, the anoikis-related signature was a promising tool to evaluate prognosis and predict therapy responses, thus assisting decision-making in the realm of OV precision medicine.

RAB27B-regulated exosomes mediate LSC maintenance via resistance to senescence and crosstalk with the microenvironment

The fate of leukaemia stem cells (LSCs) is determined by both their inherent mechanisms and crosstalk with their niches. Although LSCs were confirmed to be eradicated by restarting senescence, the specific key regulators of LSC resistance to senescence and remodelling of the niche to obtain a microenvironment suitable for stemness remain unknown. Here, we found that RAB27B, a gene regulating exosome secretion, was overexpressed in LSCs and associated with the poor prognosis of acute myeloid leukaemia (AML) patients. The increased RAB27B in LSCs prevented their senescence and maintained their stemness in vitro and in vivo. Mechanically, the increased RAB27B expression in LSCs selectively promoted the loading and release of exosomes rich in senescence-inducing proteins by direct combination. Furthermore, RAB27B-regulated LSC-derived exosomes remodelled the niche and induced senescence of mesenchymal stem cells (MSCs) with increased RAB27B expression ex vivo and in vivo. The increased RAB27B in the senescent MSCs conversely promoted LSC maintenance ex vivo and in vivo via selective excretion of exosomes rich in stemness-promoting proteins. Therefore, we identified the specifically increased RAB27B in LSCs and their educated senescent MSCs as a hub molecule for LSC resistance to senescence and maintenance through crosstalk with its niche via selective exosome excretion.

Natural killer cell-based signature: Prognostic analysis in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSC) is a challenging cancer with significant clinical implications. Natural killer (NK) cells have emerged as important players in tumor immunosurveillance, yet their role and potential as prognostic biomarkers in HNSC remain unclear.

METHODS

Quantitative analysis using multiple algorithms identified FCRL1, KIR3DL2 and ZNF541 as molecules significantly associated with local NK cell infiltration and patient survival. A prognostic model based on these molecules demonstrated robust predictive performance.

RESULTS

Analysis of high- and low-risk patient groups revealed distinct differences in the tumor microenvironment, indicating an inhibitory immune microenvironment in high-risk patients. Notably, low-risk patients exhibited potential sensitivity to immunotherapy and showed favorable responses to specific drugs such as axitinib, methotrexate, rapamycin and vorinostat. NK cells, important effectors of the innate immune response, were found to play a crucial role in HNSC immunity. The present study provides valuable insights into the correlation between FCRL1, KIR3DL2, ZNF541 and NK cell infiltration, paving the way for future investigations into their roles in HNSC. Activation of NOTCH signaling, MYC targets, DNA repair, E2F targets, epithelial-mesenchymal transition, G2M checkpoint and mitotic spindle pathways in high-risk patients suggests their involvement in disease progression and poor prognosis.

CONCLUSIONS

The present study reveals the significance of NK cells in HNSC and their potential as prognostic biomarkers. The CFKZ score offers a promising approach for predicting patient outcomes and guiding personalized treatment decisions in HNSC. These findings contribute to our understanding of HNSC immunobiology and hold implications for precision medicine in HNSC management.

Sfrp2 promotes renal dysfunction of diabetic kidney disease via modulating Fzd5-induced cytosolic calcium ion concentration and CaMKII/Mek/Erk pathway in mesangial cells

OBJECTIVE

Mesangial cells (MCs) in the kidney play central role in maintaining glomerular integrity, and their abnormal proliferation leads to major glomerular diseases including diabetic kidney disease (DKD). Although high blood glucose elicits MCs impairment, the underlying molecular mechanism is poorly understood. The present study aimed to investigate the effect of secreted frizzled-related protein 2 (Sfrp2) from single-nucleus RNA profiling on MC proliferation of DKD in vitro and in vivo and explored the specific mechanisms.

RESULTS

By snRNA-seq analysis of isolated renal cells from leptin receptor-deficient db/db mice and control db/m mice, we found that Sfrp2 was increased in the MCs of DKD in comparison to other intrinsic renal cells, which was further verified in vitro and in vivo. We also found that the expression of Sfrp2 was significantly upregulated in DKD patients and correlated with renal function, demonstrating that Sfrp2 might serve as an independent biomarker for DKD patients. Functionally, we showed the loss and acquisition of Sfrp2 affected cytosolic Ca2+ concentration, cell proliferation and fibrosis of MC, albuminuria and kidney injury in vitro and in vivo. Mechanistically, we identify c-Jun as a transcription factor of Sfrp2 promoting its transcription, and the Ca2+ signaling related protein frizzled receptor 5 (Fzd5) as the binding protein of Sfrp2. And we further found Sfrp2 promoted Fzd5-induced cytosolic Ca2+ concentration and the downstream CaMKII/Mek/Erk pathway activation, leading to MC proliferation and fibrosis in DKD.

CONCLUSION

Our study revealed a novel involvement for Sfrp2 in the regulation of MC function and the effect of Sfrp2 on cell proliferation and fibrosis of MC via the Fzd5/Ca2+/CaMKII/Mek/Erk pathway, implying that Sfrp2 may be a possible biomarker and therapeutic target for DKD.

Identification of potential biomarkers for melanoma cancer (black tumor) using bioinformatics strategy: a study based on GEO and SRA datasets

Melanoma, a highly invasive type of skin cancer that penetrates the entire dermis layer, is associated with increased mortality rates. Excessive exposure of the skin to sunlight, specifically ultraviolet radiation, is the underlying cause of this malignant condition. The appearance of unique skin moles represents a visible clue, referred to as the "ugly duckling" sign, indicating the presence of melanoma and its association with cellular DNA damage. This research aims to explore potential biomarkers derived from microarray data, employing bioinformatics techniques and methodologies, for a thorough investigation of melanoma skin cancer. The microarray dataset for melanoma skin cancer was obtained from the GEO database, and thorough data analysis and quality control measures were performed to identify differentially expressed genes (DEGs). The top 14 highly expressed DEGs were identified, and their gene information and protein sequences were retrieved from the NCBI gene and protein database. These proteins were further analyzed for domain identification and network analysis. Gene expression analysis was conducted to visualize the upregulated and downregulated genes. Additionally, gene metabolite network analysis was carried out to understand the interactions between highly interconnected genes and regulatory transcripts. Molecular docking was employed to investigate the ligand-binding sites and visualize the three-dimensional structure of proteins. Our research unveiled a collection of genes with varying expression levels, some elevated and others reduced, which could function as promising biomarkers closely linked to the development and advancement of melanoma skin cancer. Through molecular docking analysis of the GINS2 protein, we identified two natural compounds (PubChem-156021169 and PubChem-60700) with potential as inhibitors against melanoma. This research has implications for early detection, treatment, and understanding the molecular basis of melanoma.

Identification of multiomics map and key biomarkers in uveal melanoma with chromosome 3 loss

Purpose

Chromosome 3 loss is an independent risk factor for uveal melanoma (UM), but its exact molecular mechanisms remain unclear. This study was designed to investigate the relationship between chromosome 3 loss and molecular alterations at multiple levels to construct a prognostic model.

Methods

Forty-four UM cases with chromosome 3 loss (chr3 del group) and 36 UM cases without copy number variation on chromosome 3 (chr3 wt group) were collected from the Cancer Genome Atlas (TCGA). The TCGA dataset was subjected to a univariate Cox regression analysis to identify different expressed genes, and a subsequent random forest algorithm analysis revealed significant changes in different expressed genes, which were used to develop key biomarkers for UM. Following that, the immune cell infiltration analysis and drug sensitivity analyses were carried out. The UM cell line was then utilized to investigate the potential functions of the key biomarker via cell apoptosis, proliferation, cycle assays, WB, and RT-qPCR.

Results

By analyzing the 80 cases data in TCGA, the authors unveiled molecular changes relevant to loss of chromosome 3 in UM as well as their poor survival. In addition, machine learning analysis identified three hub genes (GRIN2A, ACAN, and MMP9) as potential therapeutic targets. The differentially enriched pathways between the two groups were mainly about immune-system activity, and hub genes expression was also highly correlated with immune infiltration levels.

Conclusion

Chromosome 3 loss has considerable clinical significance for UM, and GRIN2A may be useful in diagnosing, treating, and prognosticating the condition.

The mixed effect of Endocrine-Disrupting chemicals on biological age Acceleration: Unveiling the mechanism and potential intervention target

INTRODUCTION

Although previous studies investigated the potential adverse effects of endocrine-disrupting chemicals (EDCs) on biological age acceleration and aging-related diseases, the mixed effect of multiple types of EDCs on biological age acceleration, including its potential underlying mechanism, remains unclear.

METHODS

Data from the National Health and Nutrition Examination Survey (NHANES) were used to analyze biological age measures, including Klemera-Doubal method biological age (KDM-BA), phenotypic age, and homeostatic dysregulation (HD). Weight quantile sum (WQS) regression was performed to screen biological age-related EDCs (BA-EDCs) and assess the mixed effect of BA-EDCs on biological age acceleration and aging-related disease. Targets of BA-EDCs were obtained from three databases, while heart aging-related genes were obtained from the Aging Anno database. Protein-protein interaction (PPI) network and MCODE algorithm were applied to identify potential interactions between BA-EDC targets and heart aging-related genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to identify related pathways.

RESULTS

This cross-sectional study included 1,439 participants. A decile increase in BA-EDCs co-exposure was associated with 0.31 years and 0.17 years of KDM-BA and phenotypic age acceleration, respectively. The mixed effect of BA-EDCs was associated with an increased prevalence of atherosclerotic cardiovascular disease (ASCVD). Vitamins C and E demonstrated a significant interaction effect on the association between BA-EDCs and KDM-BA acceleration. PPI network and functional enrichment analysis indicated that the AGE-RAGE signaling pathway in diabetic complications was significantly enriched.

CONCLUSION

Our results showed that the co-exposure effect of BA-EDCs was associated with biological age acceleration and ASCVD, with the AGE-RAGE signaling pathway being the underlying mechanism. Vitamins C and E may also be an actionable target for preventing EDC-induced biological aging.

Significance of chitinase-3-like protein 1 in the pathogenesis of inflammatory diseases and cancer

Chitinase-3-like protein 1 (CHI3L1) is a secreted glycoprotein that mediates inflammation, macrophage polarization, apoptosis, and carcinogenesis. The expression of CHI3L1 is strongly upregulated by various inflammatory and immunological diseases, including several cancers, Alzheimer's disease, and atherosclerosis. Several studies have shown that CHI3L1 can be considered as a marker of disease diagnosis, prognosis, disease activity, and severity. In addition, the proinflammatory action of CHI3L1 may be mediated via responses to various proinflammatory cytokines, including tumor necrosis factor-α, interleukin-1β, interleukin-6, and interferon-γ. Therefore, CHI3L1 may contribute to a vast array of inflammatory diseases. However, its pathophysiological and pharmacological roles in the development of inflammatory diseases remain unclear. In this article, we review recent findings regarding the roles of CHI3L1 in the development of inflammatory diseases and suggest therapeutic approaches that target CHI3L1.