Significance of Ribonucleoside-diphosphate Reductase Subunit M2 in Lung Adenocarcinoma.

INTRODUCTION: The Ribonucleoside-diphosphate Reductase subunit M2 (RRM2) is known to be overexpressed in various cancers, though its specific functional implications remain unclear. This aims to elucidate the role of RRM2 in the progression of Lung Adenocarcinoma (LUAD) by exploring its involvement and potential impact. METHODS: RRM2 data were sourced from multiple databases to assess its diagnostic and prognostic significance in LUAD. We evaluated the association between RRM2 expression and immune cell infiltration, analyzed its function, and explored the effects of modulating RRM2 expression on LUAD cell characteristics through laboratory experiments. RESULTS: RRM2 was significantly upregulated in LUAD tissues and cells compared to normal counterparts (p<0.05), with rare genetic alterations noted (approximately 2%). This overexpression clearly distinguished LUAD from normal tissue (area under the curve (AUC): 0.963, 95% confidence intervals (CI): 0.946-0.981). Elevated RRM2 expression was significantly associated with adverse clinicopathological characteristics and poor prognosis in LUAD patients. Furthermore, a positive association was observed between RRM2 expression and immune cell infiltration. Pathway analysis revealed a critical connection between RRM2 and the cell cycle signaling pathway within LUAD. Targeting RRM2 inhibition effectively suppressed LUAD cell proliferation, migration, and invasion while promoting apoptosis. This intervention also modified the expression of several crucial proteins, including the downregulation of CDC25A, CDC25C, RAD1, Bcl-2, and PPM1D and the upregulation of TP53 and Bax (p < 0.05). CONCLUSION: Our findings highlight the potential utility of RRM2 expression as a biomarker for diagnosing and predicting prognosis in LUAD, shedding new light on the role of RRM2 in this malignancy.

Proteomic Landscape Associated with Cognitive Impairment in Individuals with Long-term Methamphetamine Dependence.

BACKGROUND: Methamphetamine (METH) is a highly addictive drug that directly affects the central nervous system. METH use not only harms the user's health but also poses risks and costs to society. Prolonged METH dependence has been shown to impair cognition, which may be the primary factor in impulsive drug-seeking behaviors and high relapse rates. However, the molecular mechanisms underlying METH addiction and METH-induced cognitive decline remain poorly understood. METHODS: To illuminate the potential molecular mechanisms underpinning METH addiction, we compared serum protein expression levels between 12 long-term METH users and 12 healthy controls using label-free quantitative proteomics. Bioinformatic analyses were conducted to determine functional networks and protein-protein interactions. RESULTS: In total, 23 differentially expressed proteins were identified between the two groups. The differentially expressed proteins were related to cognitive dysfunction, neuroinflammation, immune impairment, metabolic disturbances, and calcium binding and regulation. CONCLUSIONS: These 23 proteins may underpin the multi-system damage induced by chronic METH exposure. Our findings provide novel insights into the molecular basis of METH addiction and inform potential prevention and treatment strategies for individuals with METH dependence.

Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review.

In recent years, the role of bioinformatics and computational biology together with omics techniques and transcriptomics has gained tremendous importance in biomedicine and healthcare, particularly for the identification of biomarkers for precision medicine and drug discovery. Differential gene expression (DGE) analysis is one of the most used techniques for RNA-sequencing (RNA-seq) data analysis. This tool, which is typically used in various RNA-seq data processing applications, allows the identification of differentially expressed genes across two or more sample sets. Functional enrichment analyses can then be performed to annotate and contextualize the resulting gene lists. These studies provide valuable information about disease-causing biological processes and can help in identifying molecular targets for novel therapies. This review focuses on differential gene expression (DGE) analysis pipelines and bioinformatic techniques commonly used to identify specific biomarkers and discuss the advantages and disadvantages of these techniques.

OralExplorer: a web server for exploring the mechanisms of oral inflammatory diseases.

BACKGROUND: Oral inflammatory diseases are localized infectious diseases primarily caused by oral pathogens with the potential for serious systemic complications. However, publicly available datasets for these diseases are underutilized. To address this issue, a web tool called OralExplorer was developed. This tool integrates the available data and provides comprehensive online bioinformatic analysis. METHODS: Human oral inflammatory disease-related datasets were obtained from the GEO database and normalized using a standardized process. Transcriptome data were then subjected to differential gene expression analysis, immune infiltration analysis, correlation analysis, pathway enrichment analysis, and visualization. The single-cell sequencing data was visualized as cluster plot, feature plot, and heatmaps. The web platform was primarily built using Shiny. The biomarkers identified in OralExplorer were validated using local clinical samples through qPCR and IHC. RESULTS: A total of 35 human oral inflammatory disease-related datasets, covering 6 main disease types and 901 samples, were included in the study to identify potential molecular signatures of the mechanisms of oral diseases. OralExplorer consists of 5 main analysis modules (differential gene expression analysis, immune infiltration analysis, correlation analysis, pathway enrichment analysis and single-cell analysis), with multiple visualization options. The platform offers a simple and intuitive interface, high-quality images for visualization, and detailed analysis results tables for easy access by users. Six markers (IL1ß, SRGN, CXCR1, FGR, ARHGEF2, and PTAFR) were identified by OralExplorer. qPCR- and IHC-based experimental validation showed significantly higher levels of these genes in the periodontitis group. CONCLUSIONS: OralExplorer is a comprehensive analytical platform for oral inflammatory diseases. It allows users to interactively explore the molecular mechanisms underlying the action and regression of these diseases. It also aids dental researchers in unlocking the potential value of transcriptomics data related to oral diseases. OralExplorer can be accessed at https://smuonco.shinyapps.io/OralExplorer/  (Alternate URL: http://robinl-lab.com/OralExplorer ).

Linc-ROR inhibits NK cell-killing activity by promoting RXRA ubiquitination and reducing MICB expression in gastric cancer patients.

Linc-ROR plays an important role in gastric cancer (GC) development and progression. This study sought to determine how the aberrant expression of Linc-ROR impacts GC progression and immune evasion, and to identify new targets for GC therapy. GC cells overexpressing Linc-ROR and GSAGS cells were cocultured with NK-92 cells, respectively, and Linc-ROR expression was determined using reverse transcription polymerase chain reaction. Linc-ROR overexpression experiments were used to measure the expression of MICB, a tumor protein that is recognized by natural killer (NK) cells. Bioinformatics analysis identified retinoid X receptor α (RXRA) and YY1 as MICB-specific transcription factors. Cotransfection and ubiquitinated drug experiments found that Linc-ROR promoted the ubiquitination and degradation of RXRA. Linc-ROR was upregulated in GC tissue and high expression was associated with tumor escape from NK-92 cell-mediated immunity. Linc-ROR overexpression inhibited the expression of MICB on the cell surface by degrading RXRA. These findings indicate that Linc-ROR promotes the binding of RXRA and E3 ligase UBE4B, reducing RXRA and MICB expression, and limiting NK cell-killing activity. Linc-ROR is a critical long noncoding RNA with a tumor-promoting function in GC and thus may serve as a potential therapeutic target.

Genome-Wide Identification of lncRNA and mRNA for Diagnosing Type 2 Diabetes in Saudi Arabia.

Purpose: According to the World Health Organization, Saudi Arabia ranks seventh worldwide in the number of patients with diabetes mellitus. To our knowledge, no research has addressed the potential of noncoding RNA as a diagnostic and/or management biomarker for patients with type 2 diabetes mellitus (T2DM) living in high-altitude areas. This study aimed to identify molecular biomarkers influencing patients with T2DM living in high-altitude areas by analyzing lncRNA and mRNA. Patients and Methods: RNA sequencing and bioinformatics analyses were used to identify significantly expressed lncRNAs and mRNAs in T2DM and healthy control groups. Coding potential was analyzed using coding-noncoding indices, the coding potential calculator, and PFAM, and the lncRNA function was predicted using Pearson's correlation. Differentially expressed transcripts between the groups were identified, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to identify the biological functions of both lncRNAs and mRNAs. Results: We assembled 1766 lncRNAs in the T2DM group, of which 582 were novel. This study identified three lncRNA target genes (KLF2, CREBBP, and REL) and seven mRNAs (PIK3CD, PIK3R5, IL6R, TYK2, ZAP70, LAMTOR4, and SSH2) significantly enriched in important pathways, playing a role in the progression of T2DM. Conclusion: To the best of our knowledge, this comprehensive study is the first to explore the applicability of certain lncRNAs as diagnostic or management biomarkers for T2DM in females in Taif City, Saudi Arabia through the genome-wide identification of lncRNA and mRNA profiling using RNA seq and bioinformatics analysis. Our findings could help in the early diagnosis of T2DM and in designing effective therapeutic targets.

Comprehensive analyses reveal the prognosis and biological function roles of chromatin regulators in lung adenocarcinoma.

The present study explored the prognosis and biological function roles of chromatin regulators (CRs) in patients with lung adenocarcinoma (LUAD). Using transcriptome profile and clinical follow-up data of LUAD dataset, we explored the molecular classification, developed, and validated a CR prognostic model, built an individual risk scoring system in LUAD, and compared the clinical and molecular characteristics between different subtypes and risk stratifications. We investigated the chemotherapy sensitivity and predicted potential immunotherapy response. Lastly, we collected the clinical samples and validated the prognosis and potential function role of NAPS2. Our study indicated that LUAD patients could be classified into two subtypes that had obviously different clinical background and molecular features. We constructed a prognostic model with eight CR genes, which was well validated in several other population cohort. We built high- and low-risk stratifications for LUAD patients. Patients from high-risk group were totally different from low-risk groups in clinical, biological function, gene mutation, microenvironment, and immune infiltration levels. We idented several potential molecular compounds for high-risk group treatment. We predicted that high-risk group may have poor immunotherapy response. We finally found that Neuronal PAS Domain Protein 2 (NPAS2) involved in the progression of LUAD via regulating cell adhesion. Our study indicated that CR involved in the progression of LUAD and affect their prognosis. Different therapeutic strategies should be developed for different molecular subtypes and risk stratifications. Our comprehensive analyses uncover specific determinants of CRs in LUAD and provides implications for investigating disease-associated CRs.

Genome-Wide Identification and Bioinformatics Analyses of Host Defense Peptides Snakin/GASA in Mangrove Plants.

Host defense peptides (HDPs) are components of plant defensive barriers that resist microbial infection. Members of the Snakin/GASA protein family in plants have functions of regulating plant growth, defense, and bacteriostasis. Most mangrove plants grow in coastal zones. In order to survive in harsh environments, mangrove plants have evolved complex adaptations against microbes. In this study, Snakin/GASA family members were identified and analyzed in the genomes of three mangrove species. Twenty-seven, thirteen, and nine candidate Snakin/GASA family members were found in Avicennia marina, Kandelia obovata, and Aegiceras corniculatum, respectively. These Snakin/GASA family members were identified and categorized into three subfamilies via phylogenetic analysis. The genes coding for the Snakin/GASA family members were unevenly distributed on chromosomes. Collinearity and conservative motif analyses showed that the Snakin/GASA family members in K. obovata and A. corniculatum underwent multiple gene duplication events. Snakin/GASA family member expression in normal leaves and leaves infected with pathogenic microorganisms of the three mangrove species was verified using real-time quantitative polymerase chain reaction. The expression of KoGASA3 and 4, AcGASA5 and 10, and AmGASA1, 4, 5, 15, 18, and 23 increased after microbial infection. This study provides a research basis for the verification of HDPs from mangrove plants and suggests directions for the development and utilization of marine biological antimicrobial peptides.

A multiplex PCR assay for the differentiation of Mycobacterium tuberculosis complex reveals high rates of mixed-lineage tuberculosis infections among patients in Ghana.

In low-resource settings with high tuberculosis (TB) burdens, lack of rapid diagnostic methods for detection and differentiation of Mycobacterium tuberculosis complex (MTBC) is a major challenge affecting TB management. This study utilized comparative genomic analyses of MTBC lineages; M. tuberculosis, M. africanum Lineages 5/6 and M. bovis to identify lineage-specific genes. Primers were designed for the development of a Multiplex PCR assay which was successful in differentiating the MTBC lineages. There was no cross-reaction with other respiratory pathogens tested. Validation of the assay using clinical samples was performed with sputum DNA extracts from 341 clinically confirmed active TB patients. It was observed that 24.9% of cases were caused by M. tuberculosis, while M. africanum L5 & L6 reported 9.0% and 14.4%, respectively. M. bovis infection was the least frequently detected lineage with 1.8%. Also, 27.0% and 17.0% of the cases were PCR negative and unspeciated, respectively. However, mixed-lineage TB infections were recorded at a surprising 5.9%. This multiplex PCR assay will allow speciation of MTBC lineages in low-resource regions, providing rapid differentiation of TB infections to select appropriate medication at the earliest possible time point. It will also be useful in epidemiological surveillance studies providing reliable information on the prevalence of TB lineages as well as identifying difficult to treat cases of mixed-lineage tuberculosis infections.

In Silico Methodologies to Improve Antioxidants' Characterization from Marine Organisms.

Marine organisms have been reported to be valuable sources of bioactive molecules that have found applications in different industrial fields. From organism sampling to the identification and bioactivity characterization of a specific compound, different steps are necessary, which are time- and cost-consuming. Thanks to the advent of the -omic era, numerous genome, metagenome, transcriptome, metatranscriptome, proteome and microbiome data have been reported and deposited in public databases. These advancements have been fundamental for the development of in silico strategies for basic and applied research. In silico studies represent a convenient and efficient approach to the bioactivity prediction of known and newly identified marine molecules, reducing the time and costs of "wet-lab" experiments. This review focuses on in silico approaches applied to bioactive molecule discoveries from marine organisms. When available, validation studies reporting a bioactivity assay to confirm the presence of an antioxidant molecule or enzyme are reported, as well. Overall, this review suggests that in silico approaches can offer a valuable alternative to most expensive approaches and proposes them as a little explored field in which to invest.

Comprehensive analyses of A 12-metabolism-associated gene signature and its connection with tumor metastases in clear cell renal cell carcinoma.

BACKGROUND: The outcomes of patients with clear cell renal cell carcinoma (ccRCC) were dreadful due to lethal local recurrence and distant metastases. Accumulating evidence suggested that ccRCC was considered a metabolic disease and metabolism-associated genes (MAGs) exerted essential functions in tumor metastases. Thus, this study intends to seek whether the dysregulated metabolism promotes ccRCC metastases and explores underlying mechanisms. METHOD: Weighted gene co-expression network analysis (WGCNA) was employed based on 2131 MAGs to select genes mostly associated with ccRCC metastases for subsequent univariate Cox regression. On this basis, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression were employed to create a prognostic signature based on the cancer genome atlas kidney renal clear cell carcinoma (TCGA-KIRC) cohort. The prognostic signature was confirmed using E-MTAB-1980 and GSE22541 cohorts. Kaplan-Meier, receiver operating characteristic (ROC) curve, and univariate and multivariate Cox regression were applied to detect the predictability and independence of the signature in ccRCC patients. Functional enrichment analyses, immune cell infiltration examinations, and somatic variant investigations were employed to detect the biological roles of the signature. RESULT: A 12-gene-metabolism-associated prognostic signature, termed the MAPS by our team, was constructed. According to the MAPS, patients were divided into low- and high-risk subgroups and high-risk patients displayed inferior outcomes. The MAPS was validated as an independent and reliable biomarker in ccRCC patients for forecasting the prognosis and progression of ccRCC patients. Functionally, the MAPS was closely associated with metabolism dysregulation, tumor metastases, and immune responses in which the high-risk tumors were in an immunosuppressive status. Besides, high-risk patients benefited more from immunotherapy and held a higher tumor mutation burden (TMB) than low-risk patients. CONCLUSION: The 12-gene MAPS with prominent biological roles could independently and reliably forecast the outcomes of ccRCC patients, and provide clues to uncover the latent mechanism in which dysregulated metabolism controlled ccRCC metastases.

Xanthones from Gentianella acuta (Michx.) Hulten Ameliorate Colorectal Carcinoma via the PI3K/Akt/mTOR Signaling Pathway.

Colorectal carcinoma (CRC) is a kind of malignant tumor closely related to ulcerative colitis. Xanthone derivatives are one of the most promising therapeutic drugs which have been used in phase I/II clinical trials for cancer therapy. Our previous study indicated that the aerial parts of Gentianella acuta Michx. Hulten (GA) was rich in xanthones and showed a good therapeutic effect on ulcerative colitis in mice, suggesting that GA xanthones might have some therapeutic or ameliorative effects on CRC. However, no relevant study has been reported. This study aims to find the effective substances of GA inhibiting CRC and clarify their mechanism. Solvent extraction, column chromatographic separation, and LC-MS analysis were used to characterize the 70% EtOH extract of GA and track xanthones abundant fraction XF. MTT assay was carried out to clarify the activity of GA fractions; the result showed XF to be the main active fraction. LC-MS analysis was executed to characterize XF, 38 xanthones were identified. Network pharmacology prediction, in vitro activity screening, and molecular docking assay were combined to predict the potential mechanism; the PI3K/Akt/mTOR signaling pathway was found to be most important. Western blot assay on the main active xanthones 1,3,5-trihydroxyxanthone (16), 1,3,5,8-tetrahydroxyxanthone (17), 1,5,8-trihydroxy-3-methoxyxanthone (18), and 1,7-dihydroxy-3,8-dimethoxyxanthone (19) was used to verify the above prediction; these xanthones were found to inhibit the PI3K/Akt/mTOR signaling pathway, and 17 played a significant role among them through Western blot assay using PI3K/AKT/mTOR agonist IGF-1. In conclusion, this study demonstrated that GA xanthones were effective compounds of GA inhibiting CRC by regulating PI3K/Akt/mTOR signaling pathway transduction, at least. Importantly, 1,3,5,8-tetrahydroxyxanthone (17), the most abundant active xanthone in GA, might be a candidate drug for CRC.

Study on Molecular Anti-tumor Mechanism of 2-Thiohydantoin Derivative based on Molecular Docking and Bioinformatic Analyses.

OBJECTIVE: Several methods for synthesizing 2-thiohydantoin derivatives have been devised and exploited, and they have found widespread application as antioxidants, antimicrobials, antivirals, and anticancer agents. As a result, we tried to understand the underlying processes of the 2- thiohydantoin derivative's anti-LIHC activity. METHODS: We predicted the anticancer mechanism of N-(4-oxo-5-(2-oxo-2-(p-tolylamino)ethyl)-3- phenyl-2-thioxoimidazolidin-1-yl)benzamide as a derivative of 2-thiohydantoin by utilizing molecular docking and molecular dynamic simulation. Furthermore, based on the results of molecular dynamic modelling, we employed bioinformatics to anticipate the immunotherapy of this molecule in the tumor microenvironment (TME) of Liver Hepatocellular Carcinoma (LIHC) patients. Next, we examined how this derivative affected proliferation, cell cycle progression, reactive oxygen species production, and apoptosis in HepG2 cancer cells. RESULTS: Substantially, our investigation revealed that the IC50 value was 2.448 µM and that it arrested the cell cycle of HepG2 in the S phase. Furthermore, molecular docking and dynamics studies revealed a worthy interaction of this compound with AKT1 and CDK2 proteins. Considerably, AKT1 and CDK2 have negative affinity energies of -10.4 kcal/mol and -9.6 kcal/mol, respectively. Several bioinformatic tools were used in this investigation to provide insight into the future clinical application of this derivative as a novel candidate to target immune cells such as macrophages, neutrophils, eosinophils, and CD8+ T cells. CONCLUSION: The relevance of this 2-thiohydantoin derivative was demonstrated by our experimental tests, docking studies, and bioinformatics analysis, and it may be investigated as a lead molecule for anticancer medicines, notably as AKT1 and CKD2 inhibitors.

Comparative transcription profiling of mRNA and lncRNA in pulmonary arterial hypertension after C75 treatment.

OBJECTIVES: To investigate mRNA and long non-coding RNA (lncRNA) expression profiles in monocrotaline (MCT)- mice. MATERIALS AND METHODS: Lung tissues (Control-Vehicle, MCT-Vehicle, and MCT-C75) were examined by high-throughput sequencing (HTS). Aberrantly expressed mRNAs and lncRNAs were analyzed by bioinformatics. Cell proliferation and cell cycle analysis were performed to detect the potential protective effects of C75, an inhibitor of fatty acid synthase. The signaling pathways associated with inflammatory responses were verified by real time-PCR. RESULTS: RNA sequencing data reveals 285 differentially expressed genes (DEGs) and 147 lncRNAs in the MCT-Vehicle group compared to the control. After five-week of C75 treatment, 514 DEGs and 84 lncRNAs are aberrant compared to the MCT-Vehicle group. Analysis of DEGs and lncRNA target genes reveals that they were enriched in pathways related to cell cycle, cell division, and vascular smooth muscle contraction that contributes to the PAH pathological process. Subsequently, the expression of eight DEGs and three lncRNAs is verified using RT-PCR. Differentially expressed lncRNAs (ENSMUSG00000110393.2, Gm38850, ENSMUSG00000100465.1, ENSMUSG00000110399.1) may associate in PAH pathogenesis as suggested by co-expression network analysis. C75 can protect against MCT-induced PAH through its anti-inflammatory and anti-proliferation. CONCLUSIONS: These DEGs and lncRNAs can be considered as novel candidate regulators of PAH pathogenesis. We propose that C75 treatment can partially reverse PAH pathogenesis through modulating cell cycle, cell proliferation, and anti-inflammatory.

Bioinformatic identification and validation of autophagy-related genes in rheumatoid arthritis.

OBJECTIVES: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disorder characterized by progressive synovial inflammation and joint destruction, with a largely unknown etiology. Studies have suggested that autophagy and its expression may be involved in the pathogenesis of RA; however, autophagy-related genes in RA are still largely unidentified. Therefore, in this study, we aimed to identify and validate autophagy-related genes in RA. METHODS: We identified differentially expressed autophagy-related genes between patients with RA and healthy individuals using gene expression profiles in the GSE55235 dataset and R software. Subsequently, correlation analysis, protein-protein interaction, gene ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were carried out using these differentially expressed autophagy-related genes. Finally, our results were validated by examining the expression of differentially expressed autophagy-related hub genes in clinical samples using qRT-PCR. RESULTS: We identified 52 potential autophagy-related genes in RA based on bioinformatic analyses. Ten hub genes, CASP8, CTSB, TNFSF10, FADD, BAX, MYC, FOS, CDKN1A, GABARAPL1, and BNIP3, were validated to be differentially expressed and may serve as valuable prognostic markers and new potential therapeutic targets for RA via the regulation of autophagy. CONCLUSIONS: Our results may help improve the understanding of RA pathogenesis. Autophagy-related genes in RA could be valuable biomarkers for diagnosis and prognosis and they might be exploited clinically as therapeutic targets in the future.

Interaction of RARRES1 with ICAM1 modulates macrophages to suppress the progression of kidney renal clear cell carcinoma.

Background: RARRES1 is a tumor suppressor protein, and its expression is suppressed in various tumor cells. However, whether it participates in the immune response in kidney renal clear cell carcinoma (KIRC) is unknown, and the defined mechanism is not clear. Therefore, the mechanism of RARRES1 in KIRC is worthy of investigation. Methods: We analysed the expression and function of RARRES1 with The Cancer Genome Atlas (TCGA) database. The Kaplan-Meier curve was adopted to estimate survival. RARRES1-correlated genes were obtained from the UALCAN database and subjected to Gene Ontology (GO) enrichment and protein-protein interaction (PPI) network analyses. The correlation analysis between tumor-infiltrating immune cells and selected genes were performed with TIMER database. We also investigated the possible function of RARRES1 in KIRC by coculturing Caki-1 cells with THP-1 cells. Immunofluorescence assay was performed to study the RARRES1 expression in difference grade KIRC tissues. Results: The expression of RARRES1 was negatively correlated with survival in KIRC patients. The GO biological process term most significantly enriched with the RARRES1-correlated genes was regulation of cell adhesion. ICAM1, which exhibited a relatively highest correlation with RARRES1, is positively correlated with the infiltration level of macrophages. RARRES1 could enhance the expression of ICAM1 in Caki-1 cells and then induce the activation of M1 THP-1 cells to decrease the viability and induce the apoptosis of Caki-1 cells. Conclusion: RARRES1 plays an antitumor role by promoting ICAM1 expression and inducing the activation of M1 macrophages. We offer insights into the molecular mechanism of KIRC and reveal a potential therapeutic target.

Comprehensive bioinformatics analysis of ribonucleoside diphosphate reductase subunit M2(RRM2) gene correlates with prognosis and tumor immunotherapy in pan-cancer.

Ribonucleotide reductase (RNR) small subunit M2 (RRM2) levels are known to regulate the activity of RNR, a rate-limiting enzyme in the synthesis of deoxyribonucleotide triphosphates (dNTPs) and essential for both DNA replication and repair. The high expression of RRM2 enhances the proliferation of cancer cells, thereby implicating its role as an anti-cancer agent. However, little research has been performed on its role in the prognosis of different types of cancers. This pan-cancer study aimed to evaluate the effect of high expression of RRM2 the tumor prognosis based on clinical information collected from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) databases. We found RRM2 gene was highly expressed in 30 types of cancers. And we performed a pan-cancer analysis of the genetic alteration status and methylation of RRM2. Results indicated that RRM2 existed hypermethylation, associated with m6A, m1A, and m5C related genes. Subsequently, we explored the microRNAs (miRNA), long non-coding RNAs (lncRNA), and the transcription factors responsible for the high expression of RRM2 in cancer cells. Results indicated that has-miR-125b-5p and has-miR-30a-5p regulated the expression of RRM2 along with transcription factors, such as CBFB, E2F1, and FOXM. Besides, we established the competing endogenous RNA (ceRNA) diagram of lncRNAs-miRNAs-circular RNAs (circRNA) involved in the regulation of RRM2 expression. Meanwhile, our study demonstrated that high-RRM2 levels correlated with patients' worse prognosis survival and immunotherapy effects through the consensus clustering and risk scores analysis. Finally, we found RRM2 regulated the resistance of immune checkpoint inhibitors through the PI3K-AKT single pathways. Collectively, our findings elucidated that high expression of RRM2 correlates with prognosis and tumor immunotherapy in pan-cancer. Moreover, these findings may provide insights for further investigation of the RRM2 gene as a biomarker in predicting immunotherapy's response and therapeutic target.

Identification and characterization of aging/senescence-induced genes in osteosarcoma and predicting clinical prognosis.

Background: Aging is an influential risk factor for progression of both degenerative and oncological diseases of the bone. Osteosarcoma, considered the most common primary mesenchymal tumor of the bone, is a worldwide disease with poor 5-year survival. This study investigated the role of aging-/senescence-induced genes (ASIGs) in contributing to osteosarcoma diagnosis, prognosis, and therapeutic agent prediction. Methods: Therapeutically Applicable Research to Generate Effective Treatments (TARGET), Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA) were used to collect relevant gene expression and clinical data of osteosarcoma and paracancerous tissues. Patients were clustered by consensus using prognosis-related ASIGs. ssGSEA, ESTIMATE, and TIMER were used to determine the tumor immune microenvironment (TIME) of subgroups. Functional analysis of differentially expressed genes between subgroups, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set variation analyses (GSVAs), was performed to clarify functional status. Prognostic risk models were constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. SCISSOR was used to identify relevant cells in osteosarcoma single-cell data for different risk groups. The effect of immunotherapy was predicted based on TIDE scores and chemotherapy drug sensitivity using CTRP and PRISM. Results: Three molecular subgroups were identified based on prognostic differentially expressed ASIGs. Immunological infiltration levels of the three groups differed significantly. Based on GO and KEGG analyses, differentially expressed genes between the three subgroups mainly relate to immune and aging regulation pathways; GSVA showed substantial variations in multiple Hallmark pathways among the subgroups. The ASIG risk score built based on differentially expressed genes can predict patient survival and immune status. We also developed a nomogram graph to accurately predict prognosis in combination with clinical characteristics. The correlation between the immune activation profile of patients and the risk score is discussed. Through single-cell analysis of the tumor microenvironment, we identified distinct risk-group-associated cells with significant differences in immune signaling pathways. Immunotherapeutic efficacy and chemotherapeutic agent screening were evaluated based on risk score. Conclusion: Aging-related prognostic genes can distinguish osteosarcoma molecular subgroups. Our novel aging-associated gene signature risk score can be used to predict the osteosarcoma immune landscape and prognosis. Moreover, the risk score correlates with the TIME and provides a reference for immunotherapy and chemotherapy in terms of osteosarcoma.

Effect of Pyroptosis-Related Genes on the Prognosis of Breast Cancer.

Backgrounds: Pyroptosis, a newly pattern of specific programmed cell death, has been reported to participate in several cancers. However, the value of pyroptosis in breast cancer (BRCA) is still not clear. Methods: Herein, we analyzed the data of BRCA from both The Cancer Genome Atlas (TCGA) and GSEA MSigDB database. Based on the obtained pyroptosis-related genes (PRGs), we searched the interactions by STRING. After that, we performed clustering analysis by ConsensusClusterPlus. The PRGs with significant prognostic value were then screened through univariate cox regression and further evaluate by constructing a risk model by least absolute shrinkage and selection operator (LASSO) Cox regression. The immune and sensitivity to drugs were also predicted by comprehensive algorithms. Finally, real-time quantitative PCR (qPCR) was performed on two of the screened signature PRGs. Results: A total of 49 PRGs were obtained from public database and 35 of them were significantly differentially expressed genes (DEGs). Cluster analysis was then performed to explore the relationship between DEGs with overall survival. After that, 6 optimal PRGs (GSDMC, IL-18, CHMP3, TP63, GZMB and CHMP6) were screened out to construct a prognostic signature, which divide BRCA patients into two risk groups. Risk scores were then confirmed to be independent prognostic factors in BRCA. Functional enrichment analyses showed that the signature were obviously associated with tumor-related and immune-associated pathways. 79 microenvironmental cells and 11 immune checkpoint genes were found disparate in two groups. Besides, tumor immune dysfunction and exclusion (TIDE) scores revealed that patients with higher risk scores are more sensitive to immune checkpoint blockade treatment. Patients in the low-risk group were more sensitive to Cytarabine, Docetaxel, Gefitinib, Paclitaxel, and Vinblastine. Inversely, patients in the high-risk group were more sensitive to Lapatinib. Finally, we found that, CHMP3 were down-regulated in both BRCA tissues and cell lines, while IL-18 were up-regulated. Conclusion: PRGs play important roles in BRCA. Our study fills the gaps of 6 selected PRGs in BRCA, which were worthy for the further study as predict potential biomarkers and therapeutic targets.

CLN8 Gene Compound Heterozygous Variants: A New Case and Protein Bioinformatics Analyses.

The CLN8 disease type refers to one of the neuronal ceroid lipofuscinoses (NCLs) which are the most common group of neurodegenerative diseases in childhood. The clinical phenotypes of this disease are progressive neurological deterioration that could lead to seizures, dementia, ataxia, visual failure, and various forms of abnormal movement. In the current study, we describe two patients who presented with atypical phenotypic manifestation and protracted clinical course of CLN8 carrying a novel compound heterozygous variant at the CLN8 gene. Our patients developed a mild phenotype of CLN8 disease: as they presented mild epilepsy, cognitive decline, mild learning disability, attention-deficit/hyperactivity disorder (ADHD), they developed a markedly protracted course of motor decline. Bioinformatic analyses of the compound heterozygous CLN8 gene variants were carried out. Most of the variants seem likely to act by compromising the structural integrity of regions within the protein. This in turn is expected to reduce the overall stability of the protein and render the protein less active to various degrees. The cases in our study confirmed and expanded the effect of compound heterozygous variants in CLN8 disease.