The C-reactive protein/albumin ratio (CAR) has been shown to play a significant prognostic role in several cancers. We aimed to comprehensively explore the potential role of the CAR as a prognostic indicator in solid cancers. In this meta-analysis, we collected data from 10 studies that examined the association between serum CAR and overall survival in patients with cancer. This meta-analysis included 4592 tumor patients. The eligible studies were found through the PubMed and Web of Science databases updated on 6 Oct 2016. The pooled hazard ratio (2.01, 95% CI: 1.58-2.56, p < 0.001) indicated that high CAR yielded worse survival in different cancers. Subgroup analyses showed a significant association between CAR and prognosis, regardless of the cutoff value, cutoff value selection, treatment method, country, sample size, stage and cancer type. This meta-analysis suggests that CAR may be a potential prognostic marker in solid cancers. However, further large prospective studies should be conducted to explore the critical role of CAR in survival of cancer patients.

Tremendous efforts have been made to explore biomarkers for classification and grading on gliomas. The goal of this study was to identify more molecular features that are associated with clinical outcomes by comparing the genomic profiles of primary and recurrent gliomas and determine potential recurrence leading factors that are significantly enriched in relapse tumors. Hybrid capture based next generation sequencing (NGS) analysis was performed on 64 primary and 17 recurrent glioma biopsies. Copy number variation (CNV) was more frequent in recurrent tumors and CDKN2A/B loss was significantly enriched. In addition, overall mutations in cell cycle pathway are more common in relapse tumors. The patterns of gene sets, including IDH1/TERT and IDH1/TP53 exhibited significant difference between the groups. Survival analysis uncovered the worse disease-free survival (DFS) and overall survival (OS) associated with altered copy number and excessive activation of CELL CYCLE pathway. High Tumor Mutation Burden (TMB) was also a biomarker with great potential for poor prognosis. The assessment of genomic characteristics in primary versus recurrent gliomas aids the discovery of potential predictive biomarkers. The prognostic value of TMB in gliomas was raised for the first time.

Non-small lung cancer (NSCLC) is a common malignant disease with very poor outcome. Accurate prediction of prognosis can better guide patient risk stratification and treatment decision making, and could optimize the outcome. Utilizing clinical and methylation/expression data in The Cancer Genome Atlas (TCGA), we conducted comprehensive evaluation of early-stage NSCLC to identify a methylation signature for survival prediction. 349 qualified cases of NSCLC with curative surgery were included and further grouped into the training and validation cohorts. We identified 4000 methylation loci with prognostic influence on univariate and multivariate regression analysis in the training cohort. KEGG pathway analysis was conducted to identify the key pathway. Hierarchical clustering and WGCNA co-expression analysis was performed to classify the sample phenotype and molecular subtypes. Hub 5'-C-phosphate-G-3' (CpG) loci were identified by network analysis and then further applied for the construction of the prognostic signature. The predictive power of the prognostic model was further validated in the validation cohort. Based on clustering analysis, we identified 6 clinical molecular subtypes, which were associated with different clinical characteristics and overall survival; clusters 4 and 6 demonstrated the best and worst outcomes. We identified 17 hub CpG loci, and their weighted combination was used for the establishment of a prognostic model (RiskScore). The RiskScore significantly correlated with post-surgical outcome; patients with a higher RiskScore have worse overall survival in both the training and validation cohorts (P < 0.01). We developed a novel methylation signature that can reliably predict prognosis for patients with NSCLC.

Early identification of gastric cancer (GC) is associated with a superior survival rate compared to advanced GC. However, the poor specificity and sensitivity of traditional biomarkers suggest the importance of identifying more effective biomarkers. This study aimed to identify novel biomarkers for the prognosis of GC and construct a risk score (RS) signature based on these biomarkers, with to validation of its predictive performance. We used multi-omics data from The Cancer Genome Atlas to analyze the significance of differences in each omics data and combined the data using Fisher's method. Hub genes were subsequently subjected to univariate Cox and LASSO regression analyses and used to construct the RS signature. The RS of each patient was calculated, and the patients were divided into two subgroups according to the RS. The RS signature was validated in two independent datasets from the Gene Expression Omnibus and subsequent analyses were subsequently conducted. Five immune-related genes strongly linked to the prognosis of GC patients were obtained, namely CGB5, SLC10A2, THPO, PDGFRB, and APOD. The results revealed significant differences in overall survival between the two subgroups (p < 0.001) and indicated the high accuracy of the RS signature. When validated in two independent datasets, the results were consistent with those in the training dataset (p = 0.003 and p = 0.001). Subsequent analyses revealed that the RS signature is independent and has broad applicability among various GC subtypes. In conclusion, we used multi-omics data to obtain five immune-related genes comprising the RS signature, which can independently and effectively predict the prognosis of GC patients with high accuracy.

Clear cell renal cell carcinoma (ccRCC) is one of the most common primary malignancies of the urinary tract, highly heterogeneous, and increasing in incidence worldwide. Anoikis is a specific type of programmed cell death in which solid tumor cells or normal epithelial cells that do not have metastatic properties lose adhesion to the extracellular matrix or undergo inappropriate cell adhesion-induced apoptosis. Anoikis is thought to play a critical role in tumorigenesis, maintenance, and treatment, according to an increasing amount of research. However, there is still some uncertainty regarding the general impact of anoikis-related genes (ARGs) on the prognostic importance, tumor microenvironment characteristics, and treatment reaction of ccRCC patients. For this study, we used The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus datasets to access the RNA sequencing results and clinical information from ccRCC patients. 29 ARGs related to survival were found using differential analysis and univariate Cox regression analysis. The samples were then divided into two clusters that had different immune traits via unsupervised cluster analysis using 29 prognosis-associated differently expressed ARGs. Then, to build an ARGs signature, 7 genes (PLAU, EDA2R, AFP, PLG, TUBB3, APOBEC3G, and MALAT1) were found using Least Absolute Shrinkage and Selection Operator regression analysis. The new ARGs signature demonstrated outstanding prognostic capability for ccRCC patients' overall survival. In conclusion, for ccRCC patients, we created an ARGs signature that strongly connects to immunological traits and therapy response. Clinicians may find this ARGs signature helpful in developing more individualized and detailed treatment strategies for ccRCC patients.

The intricate involvement of Rho GTPases in a multitude of human malignancies and their diverse array of biological functions has garnered substantial attention within the scientific community. However, their expression pattern and potential role in gastric cancer (GC) remain unclear. In this study, we successfully identified two distinct subtypes associated with Rho GTPase-related gene (RGG) through consensus clustering analysis, which exhibited significant disparities in overall survival and the tumor microenvironment. Subsequently, an extensively validated risk model termed RGGscore was meticulously constructed to prognosticate the outcomes of GC patients. This model was further assessed and validated using an external cohort. Notably, the high RGGscore group was indicative of a poorer prognosis. Univariate and multivariate Cox regression analyses unveiled the RGGscore as an autonomous prognostic indicator for GC patients. Subsequent external validation, utilizing two cohorts of patients who underwent immunotherapy, demonstrated a significant correlation between a low RGGscore and improved response to immunotherapy. Additionally, the expression levels of three genes associated with RGGscore were examined using qRT-PCR. Taken together, a pioneering RGGscore model has been successfully established, showcasing its potential efficacy in offering valuable therapeutic guidance for GC.

Radiotherapy benefits patients with advanced esophageal squamous cell carcinoma (ESCC) in terms of symptom relief and long-term survival. In contrast, a substantial proportion of ESCC patients have not benefited from radiotherapy. This study aimed to establish and validate an artificial neural network-based radiomics model for the pretreatment prediction of the radiotherapy response of advanced ESCC by using integrated data combined with feasible baseline characteristics of computed tomography. A total of 248 patients with advanced ESCC who underwent baseline CT and received radiotherapy were enrolled in this study and were analyzed by two types of radiomics models, machine learning and deep learning. As a result, the Att. Resnet50 pretrained network model indicated superior performance, with AUCs of 0.876, 0.802 and 0.732 in the training, internal validation, and external validation cohorts, respectively. Similarly, our Att. Resnet50 pretrained network model showed excellent calibration and significant clinical benefit according to the C index and decision curve analysis. Herein, a novel pretreatment radiomics model was established based on deep learning methods and could be used for radiotherapy response prediction in advanced ESCC patients, thus providing reliable evidence for therapeutic decision-making.

Persister cells constitute a small subpopulation of bacteria that display remarkably high antibiotic tolerance and for pathogens such as Staphylococcus aureus are suspected as culprits of chronic and recurrent infections. Persisters formed during exponential growth are characterized by low ATP levels but less is known of cells in stationary phase. By enrichment from a transposon mutant library in S. aureus we identified mutants that in this growth phase displayed enhanced persister cell formation. We found that inactivation of either sucA or sucB, encoding the subunits of the α-ketoglutarate dehydrogenase of the tricarboxylic acid cycle (TCA cycle), increased survival to lethal concentrations of ciprofloxacin by 10-100 fold as did inactivation of other TCA cycle genes or atpA encoding a subunit of the F1F0 ATPase. In S. aureus, TCA cycle activity and gene expression are de-repressed in stationary phase but single cells with low expression may be prone to form persisters. While ATP levels were not consistently affected in high persister mutants they commonly displayed reduced membrane potential, and persistence was enhanced by a protein motive force inhibitor. Our results show that persister cell formation in stationary phase does not correlate with ATP levels but is associated with low membrane potential.

N-myristoyltransferase-1 (NMT1) catalyzes protein myristoylation, a lipid modification that is elevated in cancer cells. NMT1 sustains proliferation and/or survival of cancer cells through mechanisms that are not completely understood. We used genetic and pharmacological inhibition of NMT1 to further dissect the role of this enzyme in cancer, and found an unexpected essential role for NMT1 at promoting lysosomal metabolic functions. Lysosomes mediate enzymatic degradation of vesicle cargo, and also serve as functional platforms for mTORC1 activation. We show that NMT1 is required for both lysosomal functions in cancer cells. Inhibition of NMT1 impaired lysosomal degradation leading to autophagy flux blockade, and simultaneously caused the dissociation of mTOR from the surface of lysosomes leading to decreased mTORC1 activation. The regulation of lysosomal metabolic functions by NMT1 was largely mediated through the lysosomal adaptor LAMTOR1. Accordingly, genetic targeting of LAMTOR1 recapitulated most of the lysosomal defects of targeting NMT1, including defective lysosomal degradation. Pharmacological inhibition of NMT1 reduced tumor growth, and tumors from treated animals had increased apoptosis and displayed markers of lysosomal dysfunction. Our findings suggest that compounds targeting NMT1 may have therapeutic benefit in cancer by preventing mTORC1 activation and simultaneously blocking lysosomal degradation, leading to cancer cell death.

Cardio-renal fibrosis plays key roles in heart failure and chronic kidney disease. We sought to determine the effects of renal denervation (RDN) on cardiac and renal fibrosis in rats with isoproterenol induced cardiomyopathy. Sixty male Sprague Dawley rats were randomly assigned to Control (n = 10) and isoproterenol (ISO)-induced cardiomyopathy group (n = 50). At week 5, 31 survival ISO-induced cardiomyopathy rats were randomized to RDN (n = 15) and Sham group (n = 16). Compared with Control group, ejection fraction was decreased, diastolic interventricular septal thickness and left atrial dimension were increased in ISO-induced cardiomyopathy group at 5 week. After 10 weeks, cardio-renal pathophysiologic results demonstrated that the collagen volume fraction of left atrio-ventricular and kidney tissues reduced significantly in RDN group compared with Sham group. Moreover the pro-fibrosis factors (TGF-β1, MMP2 and Collagen I), inflammatory cytokines (CRP and TNF-α), and collagen synthesis biomarkers (PICP, PINP and PIIINP) concentration significantly decreased in RDN group. Compared with Sham group, RDN group showed that release of noradrenaline and aldosterone were reduced, angiotensin-converting enzyme (ACE)/angiotensin II (Ang II)/angiotensin II type-1 receptor (AT1R) axis was downregulated. Meanwhile, angiotensin-converting enzyme 2 (ACE2)/angiotensin-1-7 (Ang-(1-7))/mas receptor (Mas-R) axis was upregulated. RDN inhibits cardio-renal fibrogenesis through multiple pathways, including reducing SNS over-activity, rebalancing RAAS axis.

The purpose of this study was to investigate the association of Epstein-Barr virus (EBV) with peripheral blood immune cell counts and clinical outcomes in advanced nasopharyngeal carcinoma (NPC) patients. In a retrospective design, 146 patients with NPC at stage IV were enrolled in this study. The association of EBV status with peripheral blood immune cell counts, distant metastases, and long-term survival in patients with advanced NPC were determined. Eighty-seven (59.6%) of all patients were positive for EBV. Compared with patients with normal NK cell count, patients with lower NK cell count showed a significantly lower EBV viral load (median: 614.0 vs. 2190.0 copies/mL, P = 0.024). EBV-positive patients showed a significantly higher incidence of liver metastasis than EBV-negative patients (32.6% vs. 23.7%, P = 0.021). Multi-variant regression analysis showed that EBV infection was independently associated with liver metastasis (OR: 2.33, P = 0.043). EBV positive patients showed a significantly worse PFS (P = 0.001) and OS (P = 0.001) than EBV negative patients. Multivariate Cox regression analysis revealed that EBV infection was independently associated with a worse PFS (HR: 1.94, P = 0.003), and OS (HR: 2.12, P = 0.014) in advanced NPC. In conclusion, EBV infection is associated with a high risk of liver metastasis and is also an independent negative predictor for PFS and OS in patients with advanced NPC. EBV infection is associated with lower CD8% and higher NK%, while lower NK cell count is associated with lower EBV viral load.

Auditory dysfunction is the most prevalent injury associated with blast overpressure exposure (BOP) in Warfighters and civilians, yet little is known about the underlying pathophysiological mechanisms. To gain insights into these injuries, an advanced blast simulator was used to expose rats to BOP and assessments were made to identify structural and molecular changes in the middle/inner ears utilizing otoscopy, RNA sequencing (RNA-seq), and histopathological analysis. Deficits persisting up to 1 month after blast exposure were observed in the distortion product otoacoustic emissions (DPOAEs) and the auditory brainstem responses (ABRs) across the entire range of tested frequencies (4-40 kHz). During the recovery phase at sub-acute time points, low frequency (e.g. 4-8 kHz) hearing improved relatively earlier than for high frequency (e.g. 32-40 kHz). Perforation of tympanic membranes and middle ear hemorrhage were observed at 1 and 7 days, and were restored by day 28 post-blast. A total of 1,158 differentially expressed genes (DEGs) were significantly altered in the cochlea on day 1 (40% up-regulated and 60% down-regulated), whereas only 49 DEGs were identified on day 28 (63% up-regulated and 37% down-regulated). Seven common DEGs were identified at both days 1 and 28 following blast, and are associated with inner ear mechanotransduction, cytoskeletal reorganization, myelin development and axon survival. Further studies on altered gene expression in the blast-injured rat cochlea may provide insights into new therapeutic targets and approaches to prevent or treat similar cases of blast-induced auditory damage in human subjects.