Biomarker For Prognosis Research Articles

Early prognosis biomarkers of severe fever with thrombocytopenia syndrome

AbstractSevere fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that results from SFTS bunyavirus (SFTSV) infection. Infection with SFTSV can activate the immune system, producing a series of inflammatory factors. Some patients, particularly those with pre‐existing conditions or at an advanced age, may experience an excessive inflammatory response, triggering systemic multi‐organ failure progressing to severe disease and, potentially, death. In recent years, extensive research has been conducted on the mechanism of SFTSV infection and its interaction with host immune responses. Additionally, a range of biomarkers with significant prognostic value for SFTS have been identified. This review provides a comprehensive summary of the latest advancements in understanding the interplay between SFTSV and host immune responses, and elucidates the role of these biomarkers in the early detection of severe cases and fatal outcomes. The insights presented aim to inform strategies for early intervention, clinical treatment, and prognostic assessment of patients with SFTS.

Study the Relationship of IFN-γ (+874A/ T) Polymorphism, and Some Cytokines with Breast Cancer in a Population from Baghdad City, Iraq

Background: Breast cancer is still a complicated and common health issue that affects millions of people globally. Aim: the current investigation aimed to study the relationship of IFN-γ (+874 A/T) genetic polymorphism, and some cytokines to breast cancer women in a population from Baghdad city/ Iraq. Materials and Methods: In this study, (80) females with an age of (20-60) years were employed; they were attending Oncology Teaching Hospital, Medical City, Baghdad. All these females were notified regarding the purpose of these investigations and agreed to its protocol. 80 healthy women were taken into the current study for comparison purposes. Results: The findings demonstrated that C3 levels showed a significant (P≤0.05) elevation in patients compared to healthy females. C4 levels demonstrated significantly (P≤0.05) elevation in patients that compared to healthy females. IL-6 levels significantly (P <0.05) increased in patients compared with control group (4.15±0.65 pg/ml). IL-17 concentration in serum of patients showed a significant (P <0.05) increased in patients compared with healthy ones. T and A alleles of IFN-γ T / A +874 locus had distinct results when repeated distribution was used to compare women who had breast cancer to healthy individuals. In the patient BC sample, the T allele was 42.4%, while the allele T in the control group was 71.4%. While the allele A in the sample of BC patients, which is 57.6%, compared to the allele A in control group, which was 28.6%. Conclusions: This study suggests that elevated IL-6 and IL-17 levels, along with specific IFN-γ gene polymorphisms, could serve as potential biomarkers for breast cancer risk and prognosis.

Identification of Biomarkers for Diagnosis and Prognosis of Head and Neck Cancer: Bioinformatics Approach

Head and neck cancer (HNC) is the seventh most commonly diagnosed malignancy worldwide, and its incidence is expected to increase in coming years. Current diagnostic methods for HNC are often limited by suboptimal accuracy and speed, which can negatively impact therapeutic decision-making and patient outcomes. To address the shortcomings of conventional diagnostics, biomarker detection has attracted increasing clinical interest as a promising alternative. However, a major challenge is the identification of biomarkers with sufficient accuracy and sensitivity for HNC. The integration of bioinformatics tools with omics data analysis has proven to be a robust approach for biomarker discovery. In this study, we outline a bioinformatics protocol aimed at identifying differentially expressed genes (DEGs) in HNC and evaluating the diagnostic and prognostic relevance of specific genes, including FN1, LGALS3, MMP9, TIMP1, MMP2, and TIMP2, in this pathology. In addition, we performed an enrichment analysis for the genes of interest. The prognostic significance of the selected genes was evaluated in relation to patient survival. This study contributes to the growing body of knowledge by identifying potential biomarkers with diagnostic and prognostic utility in this malignancy.

Leptin Levels in Acute and Recovered Eating Disorders: An Arm-Based Network Meta-Analysis.

This study aimed to provide a BMI-adjusted meta-analytical calculation of blood leptin levels across different eating disorders (EDs) including anorexia nervosa (AN), bulimia nervosa (BN), binge eating disorder (BED), recovered EDs, and healthy controls (HCs). The goal was to understand BMI-independent leptin alterations and their potential as biomarkers. PubMed and ClinicalTrials.gov were searched for studies reporting serum leptin in AN, BN, BED, or recovered EDs. A multilevel network meta-analysis using a linear mixed-effects meta-regression model, adjusting for BMI, sex, and assay type, was performed on 146 studies (5048 patients, 3525 controls). Significant differences in leptin levels were found across EDs. AN patients exhibited the lowest leptin levels, while BED patients had the highest. BN and recovered AN patients had leptin levels similar to AN, significantly lower than HCs. BMI, sex, and assay type were significant covariates. The model accounted for heterogeneity due to diagnostic criteria, assay types, and study-level differences. Leptin levels in EDs are significantly altered beyond BMI effects, suggesting disease-specific factors. These findings support leptin's potential as a biomarker for ED staging and prognosis. Further research is needed to explore leptin's role in ED pathogenesis and trajectory, to identify subpopulations and improve clinical interventions.

Taurine Synthesis by 2-Aminoethanethiol Dioxygenase as a Vulnerable Metabolic Alteration in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) exhibits an altered metabolic profile compared to normal pancreatic tissue. However, studies on actual pancreatic tissues are limited. Untargeted metabolomics analysis was conducted on 54 pairs of tumor and matched normal tissues. Taurine levels were validated via immunohistochemistry (IHC) on separate PDAC and normal tissues. Bioinformatics analysis of transcriptomics and proteomics data evaluated genes associated with taurine metabolism. Identified taurine-associated gene was validated through gene modulation. Clinical implications were evaluated using patient data. Metabolomics analysis showed a 2.51-fold increase in taurine in PDAC compared to normal tissues (n=54). IHC confirmed this in independent samples (n=99 PDAC, 19 normal). Bioinformatics identified 2-aminoethanethiol dioxygenase (ADO) as a key gene modulating taurine metabolism. IHC on a tissue microarray (39 PDAC, 10 normal) confirmed elevated ADO in PDAC. The ADOTaurine axis correlated with PDAC recurrence and disease-free survival. ADO knockdown reduced cancer cell proliferation and tumor growth in a mouse xenograft model. The MEK-related signaling pathway is suggested to be modulated by ADO-Taurine metabolism. Our multi-omics investigation revealed elevated taurine synthesis mediated by ADO upregulation in PDAC. The ADOTaurine axis may serve as a biomarker for PDAC prognosis and a therapeutic target.

Unveiling KLHL23 as a key immune regulator in hepatocellular carcinoma through integrated analysis.

Age-related cancers are characterized by impaired protein homeostasis, where Kelch protein superfamily members have showed accumulating clues as critical regulators. In this paper, the cancerous role of Kelch-like family member 23 (KLHL23) was comprehensively analyzed with TCGA and single cell GEO database across overall 33 cancer types. By multi-omics analysis upon the transcriptomic, genomic, and methylation data, the current study explored the association of KLHL23 with patient survival, gene ontology, tumor-infiltrating lymphocytes, and drug responses. The correlation of copy number variations and methylation with dysregulated expression of KLHL23 were also addressed. Notably, KLHL23 levels correlated with survival in cancers such as hepatocellular carcinoma and low-grade glioma. The study also highlighted how reduced KLHL23 expression is linked to increased immune activity and sensitivity to chemotherapy, suggesting its potential as a biomarker for cancer prognosis and treatment responsiveness.

A blood-based mRNA signature distinguishes people with Long COVID from recovered individuals

IntroductionLong COVID is a debilitating condition that lasts for more than three months post-infection by SARS–CoV–2. On average, one in ten individuals infected with SARS CoV- 2 develops Long COVID worldwide. A knowledge gap exists in our understanding of the mechanisms, genetic risk factors, and biomarkers that could be associated with Long COVID.MethodsIn this pilot study we used RNA-Seq to quantify the transcriptomes of peripheral blood mononuclear cells isolated from COVID-recovered individuals, seven with and seven without Long COVID symptoms (age- and sex-matched individuals), on average 6 months after infection.ResultsSeventy genes were identified as significantly up- or down-regulated in Long COVID samples, and the vast majority were downregulated. The most significantly up- or downregulated genes fell into two main categories, either associated with cell survival or with inflammation. This included genes such as ICOS (FDR p = 0.024) and S1PR1 (FDR p = 0.019) that were both up-regulated, indicating that a pro-inflammatory state is sustained in Long COVID PBMCs compared with COVID recovered PBMCs. Functional enrichment analysis identified that immune-related functions were expectedly predominant among the up- or down-regulated genes. The most frequently downregulated genes in significantly altered functional categories were two leukocyte immunoglobulin like receptors LILRB1 (FDR p = 0.005) and LILRB2 (FDR p = 0.027). PCA analysis demonstrated that LILRB1 and LILRB2 expression discriminated all of the Long COVID samples from COVID recovered samples.DiscussionDownregulation of these inhibitory receptors similarly indicates a sustained pro-inflammatory state in Long COVID PBMCs. LILRB1 and LILRB2 should be validated as prospective biomarkers of Long COVID in larger cohorts, over time and against clinically overlapping conditions.

CENPE is a Diagnostic and Prognostic Biomarker for Cervical Cancer

Cervical squamous cell carcinoma (CESC) is a common cancer in women. Despite advancements in early diagnosis through high-risk human papillomavirus (HPV) screening, challenges remain in predicting and treating the disease. Hence, the identification of novel biomarkers for prognosis and therapeutic targets is crucial.CENPE, a microtubule-end directed motor protein that accumulates during the G2 phase, is recognized for its involvement in promoting cancer growth and progression. However, its specific role in CESC remains unclear. This research investigated the expression of CENPE in CESC utilizing data from The Cancer Genome Atlas (TCGA), which was further validated through gene expression profiles, the Human Protein Atlas (HPA), and clinical data. The study utilized Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and immune infiltration analysis to elucidate the role of CENPE in CESC. Additionally, Protein-protein interaction (PPI) networks and competing endogenous RNA (CeRNA) networks involving CENPE and its differentially expressed genes were established. Furthermore, Kaplan-Meier survival analysis was conducted to evaluate the impact of CENPE on patient prognosis.Our study revealed an upregulation of CENPE expression in cervical cancer tissues, which promotes the progression of CESC through IL-6-mediated PI3K-Akt and MAPK signaling pathways. The significant associations with ACNG3, LY6H, and SLC6A7 suggest that CENPE may play a role in tumor growth and metastasis, potentially involving the nervous system. Moreover, the correlations with ARIH1, KDM1A, KDM5B, and NSD3 indicate that CENPE could be a promising target for drug development. Our analysis of the ROC curve demonstrated a high diagnostic accuracy of CENPE in CESC (AUC: 0.997, CI: 0.990-1.000). Subgroup analysis highlighted substantial effects in patients under 50 years old, those with a height under 160 cm, individuals in peri- and post-menopausal stages, and patients in clinical stages 1 and 4. Additionally, COX regression analysis indicated that older age, lower BMI, and higher CENPE expression are associated with decreased 1-year, 3-year, and 5-year survival rates.In conclusion, CENPE emerges as a crucial factor in the initiation and advancement of cervical cancer, showing potential as a novel target for therapeutic interventions.

Building a Risk Scoring Model for ARDS in Lung Adenocarcinoma Patients Using Machine Learning Algorithms.

Lung adenocarcinoma (LUAD), the predominant form of non-small-cell lung cancer, is frequently complicated by acute respiratory distress syndrome (ARDS), which increases mortality risks. Investigating the prognostic implications of ARDS-related genes in LUAD is crucial for improving clinical outcomes. Data from TCGA, GEO and GTEx were used to identify 276 ARDS-related genes in LUAD via differential expression analysis. Univariate Cox regression, consensus clustering and machine learning algorithms were used to develop a prognostic risk scoring model. Functional enrichment, immune infiltration analyses, copy number variations and mutational burdens were examined, and the results were validated at the single-cell level. ARDS-related genes significantly impact the prognosis of LUAD patients. A machine learning-based risk scoring model accurately predicted survival rates. Functional enrichment and immune infiltration analyses revealed that these genes are primarily involved in cell cycle regulation and immune cell infiltration. Single-cell expression data supported these findings, and the assessments of copy number variations and mutational burdens highlighted distinct genetic characteristics. This study establishes the prognostic relevance of ARDS-associated genes in LUAD and provides potential biomarkers for personalized therapy and prognosis. Future studies will validate these findings and explore their clinical applications.

WNT2 blockade augments antitumor immunity by attenuating myeloid‐derived suppressor cells in colorectal cancer

AbstractColorectal cancer (CRC) ranks as one of the most common malignancies worldwide. Myeloid‐derived suppressor cells (MDSCs) represent an immunosuppressive heterogeneous population of immature monocytes and granulocytes constituting a major obstacle for CRC therapy. Previous studies demonstrated that WNT2 is enriched in tumor microenvironment (TME), promoting CRC progression. However, the role of WNT2 in regulating MDSCs to facilitate CRC progression remains largely unexplored. Our analysis of The Cancer Genome Atlas (TCGA) database and blood samples from 50 primary and recurrent CRC patients revealed a positive correlation between WNT2 expression and MDSCs abundance. Treatment with recombinant WNT2 protein significantly enhanced the accumulation and immunosuppressive function of MDSCs in vitro. Conversely, anti‐WNT2 monoclonal antibody remarkably reduced the percentage and functional activity of MDSCs in CRC tumor‐bearing mice. Mechanistic analyses further demonstrated that WNT2 mediates MDSCs activities through the p38 MAPK/Akt pathway. Collectively, our findings not only highlight the pivotal role of WNT2 in CRC progression by enhancing MDSCs activities within the TME, but also provide evidence that WNT2 levels and MDSCs abundance in peripheral blood could serve as predictive biomarkers for early diagnosis and prognosis of CRC patients.

Identification and Validation of Serum Biomarkers to Improve Colorectal Cancer Diagnosis.

The pressing need for reliable biomarkers in colorectal cancer (CRC) diagnosis and prognosis is a major global health concern. Current diagnostic methods rely heavily on invasive procedures like colonoscopy, and existing biomarkers such as Carbohydrate Antigen 19-9 (CA19-9) and Carcinoembryonic Antigen (CEA) exhibit limitations in accuracy and specificity. This study aims to identify and validate novel biomarkers that can enhance the early detection and diagnostic precision of CRC while overcoming the shortcomings of conventional biomarkers. Leveraging advancements in genomic and proteomic technologies, gene expression datasets were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). We identified differentially expressed genes (DEGs) and conducted further analyses, including Gene Ontology (GO) enrichment and Protein-Protein Interaction (PPI) network construction. Five promising biomarkers-INHBA, MMP7, PSAT1, SLC7A5, and TGFBI-were selected based on their robust performance in Receiver Operating Characteristic (ROC) curve analysis. Serum concentrations of these biomarkers were measured in 200 CRC patients and 100 healthy controls. The study revealed significantly elevated expression levels of the selected biomarkers in CRC tissues compared to normal tissues. Additionally, serum concentrations of INHBA, MMP7, PSAT1, SLC7A5, and TGFBI were notably higher in CRC patients than in healthy individuals, with Area Under the Curve (AUC) values ranging from 0.8361 to 0.9869 indicating high diagnostic accuracy. Optimal cutoff values for diagnosis ranged from 38.9 pg/mL to 280.7 pg/mL, yielding sensitivity and specificity values between 74.5% and 92.9%. The findings underscore the potential of INHBA, MMP7, PSAT1, SLC7A5, and TGFBI as effective non-invasive biomarkers for CRC detection. Their elevated serum concentrations and robust discriminatory abilities highlight their promise in improving diagnostic accuracy and patient outcomes compared to traditional biomarkers. The identification and validation of these novel biomarkers represent a significant advancement in CRC diagnosis and management. Further studies are required to validate their clinical applicability in larger cohorts and to elucidate their functional roles in CRC pathogenesis, ultimately enhancing diagnostic strategies and personalized treatment approaches.

CK2B is a Prognostic Biomarker and a Potential Drug Target for Hepatocellular Carcinoma.

Although casein kinase II subunit beta (CK2B) was previously reported to be involved in human cancers, such as hepatocellular carcinoma (HCC), there has been no systematic assessment of CK2B in HCC. To assess the potential function of CK2B as a prognostic biomarker and possible druggable target in HCC. The Cancer Genome Atlas database was accessed to investigate the potential oncogenic and prognostic roles of CK2B in HCC. Diverse analytical methods were used to obtain a fuller understanding of CK2B, including CIBERSORT, The Tumor Immune Estimation Resource (TIMER), gene set enrichment analyses (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene ontology (GO). Furthermore, the Comparative Toxicogenomic Database (CTD) was used to identify potential drugs to treat CK2B-overexpressing HCC. Patents for these drugs were reviewed using Patentscope® and Worldwide Espacenet®. Upregulated CK2B expression was markedly associated with more aggressive pathological features, including G3, G4 (vs. G1, G2), and T2, T3 (vs. T1). Kaplan-Meier survival curves indicated that patients with HCC with higher expression of CK2B had worse overall survival (P = 0.005), progression-free interval (P = 0.001), and disease-specific survival (P = 0.011). GO and KEGG analysis revealed that CK2B dysregulation affects mitotic chromosome condensation, protein stabilization and binding, regulation of signal transduction of p53 class mediator, and cancer-related pathways. GSEA identified six well-known pathways, including MAPK, WNT, Hedgehog, and TGFβ signaling pathways. Finally, CTD identified six compounds that might represent targeted drugs to treat HCC with CK2B overexpression. A review of patents indicated these compounds showed promising anticancer results; however, whether CK2B interacts with these drugs and improves drug outcomes for patients with HCC was not confirmed. CK2B is a biomarker for HCC prognosis and could be a potential new drug target. Moreover, the association between infiltrating immune cells and CK2B in the HCC tumor microenvironment might provide a solid basis for further investigation and a potent strategy for immunotherapy of HCC.

DUPAN-2 in pancreatic cancer: Systematic review and meta-analysis.

Pancreatic cancer (PC) is a highly aggressive malignancy with poor prognosis and high mortality rate. Identifying reliable biomarkers for the early diagnosis and treatment is urgently needed. This study aims to comprehensively evaluate the diagnostic and prognostic value of DUPAN-2 in PC through a meta-analysis. We systematically searched PubMed, Embase, and other databases for studies related to DUPAN-2 and its prognostic and diagnostic relevance in PC, covering publications up to August 2024. We used pooled hazard ratios (HRs) to evaluate the prognostic value of DUPAN-2 in PC, the summary receiver operating characteristic (SROC) curve and the area under the curve (AUC) to assess diagnostic performance, while pooled odds ratios (ORs) analyzed associations with clinicopathological features. A total of 22 studies involving 4765 patients were included in this meta-analysis, with 11 studies focusing on diagnostic analysis, 10 on prognostic analysis, and 3 on clinicopathological features. The diagnostic meta-analysis revealed a pooled sensitivity of 0.63 (95 % CI: 0.56-0.69), a pooled specificity of 0.98 (95 % CI: 0.95-0.99), and an AUC of 0.83 (95 % CI: 0.79-0.86). Subgroup analysis indicated that a DUPAN-2 threshold at 150 U/mL achieved the highest diagnostic performance. The prognostic meta-analysis demonstrated that elevated DUPAN-2 levels were associated with poorer OS (HR = 1.70, 95 % CI: 1.36-2.14) and PFS (HR = 1.33, 95 % CI: 1.14-1.56). Additionally, the clinicopathological features meta-analysis showed that elevated DUPAN-2 levels were associated with vascular invasion (OR = 3.48, 95 % CI: 1.26-9.59), while normalized DUPAN-2 levels were associated with higher resectability (OR = 0.57, 95 % CI: 0.36-0.90) and lower N-stage (OR = 0.39, 95 % CI: 0.24-0.63) CONCLUSION: Serum DUPAN-2 demonstrates significant potential as a biomarker for diagnosis and prognosis in patients with PC.

GD-Net: An Integrated Multimodal Information Model Based on Deep Learning for Cancer Outcome Prediction and Informative Feature Selection.

Multimodal information provides valuable resources for cancer prognosis and survival prediction. However, the computational integration of this heterogeneous data information poses significant challenges due to the complex interactions between molecules from different biological modalities and the limited sample size. Here, we introduce GD-Net, a Graph Deep learning algorithm to enhance the accuracy of survival prediction with an average accuracy of 72% by early fusing of multimodal information, which includes an interpretable and lightweight XGBoost module to efficiently extract informative features. First, we applied GD-Net to eight cancer datasets and achieved superior performance compared to benchmarking methods, with an average 7.9% higher C-index value. The ablation experiments strongly supported that multi-modal integration could significantly improve accuracy over the single-modality model. In the deep case study of liver cancer, 319 differential genes, 15 differential miRNAs and 155 methylated differential genes based on the predicted risk subgroups are identified as the informative features, and then we have statistically and biologically validated the efficacy of these key molecules in internal and external test datasets. The comprehensive independent validations demonstrated that GD-Net is accurate and competitive in predicting different cancer outcomes in real-time, and it is an effective tool for identifying new multimodal prognosis biomarkers.

Total alkaloids of Aconitum carmichaelii Debx alleviate cisplatin-induced acute renal injury by inhibiting inflammation and oxidative stress related to gut microbiota metabolism

BackgroundCisplatin-induced acute kidney injury (AKI) is a complex and serious clinical issue, representing a major cause of hospital-acquired AKI. Alkaloids are the main active constituents of Aconitum carmichaelii Debx, which exhibit protective effects in several kidney disease models and against other acute organ injuries. However, its activity and mechanism of action in AKI treatment remain unclear. PurposeThis study aimed to elucidate the effect of Aconitum carmichaelii Debx (ACA) in a model of cisplain-induced AKI and comprehensively investigate its underlying mechanisms. MethodsThe major alkaloids in ACA were analyzed using high-performance liquid chromatography. Blood urea nitrogen (BUN) and serum creatine levels were measured using automated biochemical instruments. 16S rRNA sequencing, short-chain fatty acid (SCFA) analysis, fecal microbiota transplantation (FMT), non-targeted metabolomics, and transcriptomics were performed to systematically identify prospective biomarkers after ACA treatment. Anti-inflammatory and anti-oxidative stress activities were monitored using ELISA and western blotting. ResultsFour main compounds (fuziline, neoline, talatisamine, and songorine) were identified in ACA. ACA significantly alleviated cisplatin-induced AKI by reducing (BUN) and serum creatine levels and improving histopathological scores. Moreover, ACA balanced cisplatin-mediated confoundments in microbial composition and function, including decreasing the levels of Escherichia-Shigella, Clostridium, and Ruminococcus, as well as increasing Ligilactobacillus, Anaerotruncus, Bacteroides and Desulfovibrio levels, accompanied by uremic toxin reduction, and augmenting serum SCFAs. The FMT experiments further confirmed that ACA exerts anti-AKI effects by affecting gut microbiota. A multi-omics study has shown that ACA regulates glutathione and tryptophan metabolism and mediates pathways that trigger inflammatory responses. Finally, ACA reduced serum levels of inflammatory factors (IL-1β, IL-6, and TNF-α), restored enzymes of the antioxidative system (SOD and CAT) and GSH values, and decreased monoester diterpene alkaloid levels in the kidney by inhibiting the expression of NF-κB pathway-related proteins and increasing Nrf2/HO-1 pathway-related protein expression. ConclusionACA protects against cisplatin-induced AKI through its anti-inflammatory and antioxidant functions, which may be associated with the restoration of gut microbiota metabolism. ACA is a potential drug for AKI and other forms of organ damage related to the disruption of the gut microbiota.

SLC12A9 is an immunological and prognostic biomarker for glioma

BackgroundGlioma is one of the most common malignant brain tumors. It has a high rate of progression and a poor prognosis, and effective biomarkers still need to be identified. The solute carrier family 12 (SLC12) family has been reported to be involved in various physiological and pathological processes, but their functional roles in glioma remain unclear. MethodsUsing public datasets, we studied the mutation and expression level of SLC12 family genes in glioma and identified the significantly differentially expressed member solute carrier family 12 member 9 (SLC12A9). We further predicted the prognostic role of SLC12A9 in glioma by using the Kaplan–Meier method and Cox regression analysis. Then, we performed biological functional enrichment analysis. We focused on the relationships between SLC12A9 expression and immune infiltration in glioma. Meanwhile, we conducted in vitro experiments to evaluate the effect of SLC12A9 expression on glioma cells. ResultsAmong the members of the SLC12 family, SLC12A9 had the highest mutation rate in glioma, with gene amplification as the major mutation type, and its expression was significantly upregulated in glioma. Higher SLC12A9 expression was significantly associated with older age, higher grade, wild-type isocitrate dehydrogenase (IDH), and a worse prognosis. The functional enrichment analysis indicated that SLC12A9 is mainly related to ion channel annotation. Gene set enrichment analysis (GSEA) revealed that SLC12A9 was mainly related to the DNA replication pathway. Furthermore, we found that SLC12A9 correlated with tumor-infiltrating immune cells and immune checkpoints. Thus, SLC12A9 may be involved in regulating the immune response of glioma. Finally, our in vitro experiments revealed that silencing SLC12A9 dramatically inhibited glioma cell growth and migration. ConclusionsWe showed that SLC12A9 may be a new predictive biomarker for glioma diagnosis, prognosis, and immunotherapy response, offering helpful guidelines to advance glioma treatment.

Atherogenic low-density lipoprotein and cardiovascular risk.

Despite reductions in low-density lipoprotein (LDL) cholesterol (LDLc), residual cardiovascular risk remains due to factors beyond lipoprotein levels, such as LDL particle count, size, electronegativity and modifications. Technological advances allow detailed profiling of LDL particles, offering potential biomarkers for diagnosis, prognosis, and treatment of cardiovascular disease (CVD). The aim of this review is to provide an updated overview of the state of knowledge in the field of LDL atherosclerotic role, which is evolving rapidly due to technological advances in biomarker measurement and applications. While small dense LDL has been linked to increased CVD risk, current approaches favor a comprehensive evaluation of all lipoprotein subtypes, as this is a more feasible and standardized method. The atherogenic potential of circulating oxidized LDL (oxLDL) may be the key factor in the onset and progression of atherosclerosis. Thus, elevated oxLDL levels are recognized as a marker of increased CVD risk in both general and high-risk populations, although further research is needed to clarify some conflicting findings. The oxidized LDL receptor 1 (LOX-1) has emerged as a promising target for immunotherapy and innovative drug delivery strategies to modulate atherosclerosis. A panel of biomarkers related to LDL atherogenicity may help predict future ischemic events. An atheroprotective diet and increased physical activity could improve LDL oxidation. OxLDL has become a target for immunomodulatory antiatherosclerosis therapy and delivering LDL-based nanocarriers holds promise for both imaging and therapeutics.

Blood-based microRNAs as the potential biomarkers for Alzheimer's disease: evidence from a systematic review.

Alzheimer's disease (AD) is a neurodegenerative disorder that progresses over time and is identified by the development of neurofibrillary tangles and amyloid deposits in the brain. Mounting evidence has revealed that microRNAs (miRNAs) are significantly involved in AD progression, and may be used as promising biomarkers for diagnosis and prognosis. Nevertheless, the existing body of data regarding dysregulated circulating miRNAs in AD and their therapeutic applications are characterized by a lack of consistency. A comprehensive search was performed across various databases (PubMed, EMBASE, Web of Science, Scopus, Google Scholar, Cochrane, and ProQuest), starting from its inception and ending in January 2023. The criteria for inclusion consisted of original research studies written in English, which utilized Real-Time PCR to analyze miRNA expression in the blood, serum, or plasma of AD patients and healthy controls. The extracted data included the miRNA(s) investigated, dysregulation status, study type, human sample(s), and major findings. The search produced 608 records, which after careful examination, resulted in 48 suitable articles for data extraction. The research revealed a wide range of sample types used, with whole blood (39.59%) and serum (27.09%, including serum-exosome at 4.17%) emerging as the most prominent. The compiled dataset featured 4001 AD patients and 3886 healthy controls, revealing intricate regulatory patterns among 83 up-regulated (35.78%), 66 down-regulated (28.44%), and 83 not significantly altered (35.78%) miRNAs. Our results demonstrated that specific circulating miRNAs are consistently dysregulated in AD and could serve as non-intrusive biomarkers for the identification, prognosis, and prediction of cognitive decline. Further large-scale prospective studies are required to validate their clinical applications.

Role of long non-coding RNAs in neurofibromatosis and Schwannomatosis: pathogenesis and therapeutic potential.

Neurofibromatosis (NF) is identified as genetic disorder characterized by multiple tumors on nerve tissues. NF1 is the most prevalent form, identified by neurofibromas and skin changes. NF1 is the most prevalent neurofibromatosis disorder, distinct from the rarer NF2 and schwannomatosis (SWN) conditions. NF2, including NF2-related SWN (NF2-SWN), predominantly involves schwannoma formation and differs from NF1 in its genetic basis and clinical presentation. Despite the established genetic basis of NF, effective treatments remain scarce. Long non-coding RNAs (lncRNAs) have emerged as important regulators of gene expression, impacting pathways vital to tumor biology. This review explores the lncRNAs role in NF pathogenesis along with their potential as therapeutic targets. LncRNAs such as ANRIL and H19 show dysregulated expression in NF, influencing signaling pathways like Ras/MAPK and JAK/STAT, thereby contributing to tumor development. Understanding these interactions sheds light on the molecular mechanisms underlying NF and highlights lncRNAs as potential biomarkers of diagnosis and prognosis of NF. Additionally, therapeutic strategies targeting lncRNAs with antisense oligonucleotides (ASOs) or CRISPR-Cas9 offer promising treatment options. The present review emphasizes crucial role of lncRNAs in NF pathogenesis and their promise to create innovative treatments, aiming to improve patient outcomes and meet the urgent need for effective NF therapies.

Pan-cancer TCGA analysis reveals the potential involvement of B-type lamins in dysregulating chromosome segregation in human cancer.

Lamins play a crucial role in maintaining nuclear structure and function. Our study investigates the expression patterns and clinical implications of B-type lamins with a special focus on lamin B2 across various cancer types using comprehensive RNA sequencing datasets. We found that high expression levels of lamin B1 and lamin B2 are associated with decreased overall and disease-free survival in cancer. This association is further pronounced when both lamins are co-expressed, indicating a compounded negative impact on patient prognosis. Additionally, we highlighted the relationship between B-type lamins and the tumor microenvironment. Lamin B1 mRNA expression shows a strong positive correlation with activated CD4+ T-cells and type 2 T-helper cells (Th2), suggesting its role in immune cell infiltration and response within tumors. Lamin B2 expression also correlates moderately with these immune cells, indicating a potential but lesser role in modulating the immune landscape. Notably, the epigenetic state of lamin B1 significantly affects the tumor microenvironment, suggesting a dual role in structural integrity and immune modulation. We have identified 9 lamin B2 interacting proteins that are co-expressed with B-type lamins in cancerous conditions and modulate cytokinesis and cell division pathways during tumorigenesis. Furthermore, we have identified specific molecular targets of B-type lamins that co-express with them in a range of human cancers and are potentially involved in dysregulating chromosome segregation and mRNA binding. Overexpression of these targets alongside B-type lamins correlates with poor prognosis in multiple cancers. These findings underscore the potential of B-type lamins as biomarkers for poor prognosis and as targets for cancer therapies.