Pan-cancer Comprehensive Analysis Identified EGFR as a Potential Biomarker for Multiple Tumor Types.

The epidermal growth factor receptor (EGFR) has been extensively studied for its critical role in the development and progression of various malignancies. In this comprehensive pan-cancer analysis, we investigated the potential of EGFR as a biomarker across multiple tumor types; a comprehensive analysis of EGFR gene mutation and copy number variation was conducted using cBioPortal and other tools. Utilizing multi-omics datasets from The Cancer Genome Atlas (TCGA), we analyzed EGFR's expression patterns, prognostic implications, genetic mutations, and molecular interactions in different cancers. Our findings revealed frequent dysregulation of EGFR in several tumor types, including lung cancers and glioblastoma multiforme. High EGFR expression was consistently associated with poor clinical outcomes, such as reduced overall survival, disease-free survival, and progression-free survival. Genetic alteration analysis indicated a high frequency of EGFR mutations and copy number variations, particularly in glioblastoma multiforme. Additionally, our study suggests a complex relationship between EGFR expression and cancer-associated fibroblast infiltration, which may contribute to an immunosuppressive tumor microenvironment. These findings underscore the clinical relevance of EGFR as a prognostic biomarker and therapeutic target, emphasizing the need for further research and the development of targeted therapies to enhance patient outcomes in cancers with EGFR alterations. The co-expression network of EGFR with genes and proteins involved in cell cycle regulation and mitotic control provided insights into the molecular mechanisms of oncogenesis.

Prevalence of Drug Resistance Associated Substitutions in Persons With Chronic Hepatitis C Infection and Virological Failure Following Initial or Re-treatment With Pan-genotypic Direct-Acting Antivirals: A Systematic Review and Meta-analysis.

BACKGROUND: The advent of short-course, curative treatment with direct-acting antivirals (DAA) has given promise for the global elimination of hepatitis C virus (HCV) infections by 2030. Virological failure occurs in 2%-12% of persons receiving curative DAA treatment and may be presaged by pre-existing polymorphisms or result from selection of drug resistant variants during therapy. METHODS: We conducted a systematic review to assess the prevalence of HCV resistance associated substitutions (RAS) among individuals with chronic hepatitis C infection who had virological failure following initial or re-treatment with pan-genotypic DAA regimens. We included 34 and 22 studies assessing RAS in people with virological failure published between January 2014 and July 2023. Pooled RAS prevalence was estimated using random-effects meta-analysis. RESULTS: The pooled prevalence of RAS in people with virological failure following initial DAA treatment was 78.0% (95% confidence interval [CI]: 62.0-92.0) for sofosbuvir/velpatasvir, 81.0% (95% CI: 67.0-93.0) for sofosbuvir/daclatasvir, and 79.0% (95% CI: 70.0-87.0) for glecaprevir/pibrentasvir, with a high prevalence of resistance to the NS5A inhibitors. Among those with virological failure following re-treatment regimens, RAS were present in 93.0% (95% CI: 83.0-99.0) for sofosbuvir/velpatasvir/voxilepravir and in 100% (95% CI: 92.0-100) for glecaprevir/pibrentasvir, with resistance driven by RAS to NS5A inhibitors. DISCUSSION: At least 1 RAS is present in a high proportion of the few individuals with virological failure following initial or re-treatment with pan-genotypic DAA regimens. There is a need for ongoing surveillance for DAA-associated resistance, to assess risk factors for their development and clinical impact to inform best practice strategies for re-treatment.

Pan-cancer characterization of cellular senescence reveals its inter-tumor heterogeneity associated with the tumor microenvironment and prognosis.

Cellular senescence (CS) is characterized by the irreversible cell cycle arrest and plays a key role in aging and diseases, such as cancer. Recent years have witnessed the burgeoning exploration of the intricate relationship between CS and cancer, with CS recognized as either a suppressing or promoting factor and officially acknowledged as one of the 14 cancer hallmarks. However, a comprehensive characterization remains absent from elucidating the divergences of this relationship across different cancer types and its involvement in the multi-facets of tumor development. Here we systematically assessed the cellular senescence of over 10,000 tumor samples from 33 cancer types, starting by defining a set of cancer-associated CS signatures and deriving a quantitative metric representing the CS status, called CS score. We then investigated the CS heterogeneity and its intricate relationship with the prognosis, immune infiltration, and therapeutic responses across different cancers. As a result, cellular senescence demonstrated two distinct prognostic groups: the protective group with eleven cancers, such as LIHC, and the risky group with four cancers, including STAD. Subsequent in-depth investigations between these two groups unveiled the potential molecular and cellular mechanisms underlying the distinct effects of cellular senescence, involving the divergent activation of specific pathways and variances in immune cell infiltrations. These results were further supported by the disparate associations of CS status with the responses to immuno- and chemo-therapies observed between the two groups. Overall, our study offers a deeper understanding of inter-tumor heterogeneity of cellular senescence associated with the tumor microenvironment and cancer prognosis.

High-Performance Pure Polymer Electrolytes with Enhanced Ionic Conductivity for Room-Temperature Applications.

All-solid-state lithium metal batteries (ASSLMBs) are renowned for their high energy density and safety, positioning them as leading candidates for next-generation energy storage solutions. In this study, pure polymer solid-state electrolytes are developed using the solution casting method, optimized for room temperature operation. The base material, poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP), is enhanced with succinonitrile (SN) and polyacrylonitrile (PAN) to improve its electrochemical performance at room temperature. The optimized electrolyte, PSP-0.05, demonstrated superior characteristics, including an ionic conductivity (σ) of 3.2 × 10-4 S cm-1 and a wide voltage window of up to 5 V. When integrated into full batteries, PSP-0.05 exhibited exceptional performance in multiplicative cycling tests at room temperature, achieving discharge specific capacities of 132 and 113 mAh g-1 at 3 and 5 C rates, respectively. Additionally, long-term cycling at 1 C rate resulted in an initial discharge-specific capacity of 145.2 mAh g-1 with over 94.9% capacity retention after 1000 cycles. Given the simplicity of the preparation process and its impressive electrochemical properties, the PSP-0.05 electrolyte holds significant potential for practical applications in safer ASSLMBs.

Pan-genome-scale metabolic modeling of Bacillus subtilis reveals functionally distinct groups.

Bacillus subtilis is an important industrial and environmental microorganism known to occupy many niches and produce many compounds of interest. Although it is one of the best-studied organisms, much of this focus including the reconstruction of genome-scale metabolic models has been placed on a few key laboratory strains. Here, we substantially expand these prior models to pan-genome-scale, representing 481 genomes of B. subtilis with 2,315 orthologous gene clusters, 1,874 metabolites, and 2,239 reactions. Furthermore, we incorporate data from carbon utilization experiments for eight strains to refine and validate its metabolic predictions. This comprehensive pan-genome model enables the assessment of strain-to-strain differences related to nutrient utilization, fermentation outputs, robustness, and other metabolic aspects. Using the model and phenotypic predictions, we divide B. subtilis strains into five groups with distinct patterns of behavior that correlate across these features. The pan-genome model offers deep insights into B. subtilis' metabolism as it varies across environments and provides an understanding as to how different strains have adapted to dynamic habitats. IMPORTANCE: As the volume of genomic data and computational power have increased, so has the number of genome-scale metabolic models. These models encapsulate the totality of metabolic functions for a given organism. Bacillus subtilis strain 168 is one of the first bacteria for which a metabolic network was reconstructed. Since then, several updated reconstructions have been generated for this model microorganism. Here, we expand the metabolic model for a single strain into a pan-genome-scale model, which consists of individual models for 481 B. subtilis strains. By evaluating differences between these strains, we identified five distinct groups of strains, allowing for the rapid classification of any particular strain. Furthermore, this classification into five groups aids the rapid identification of suitable strains for any application.

SNRPB2 in the pan-cancer landscape: A bioinformatics exploration and validation in hepatocellular carcinoma.

Aberrant splicing is a significant contributor to gene expression abnormalities in cancer. SNRPB2, a component of U2 small nuclear ribonucleoprotein particles (snRNPs), contributes to the assembly of the spliceosome, the molecular machinery responsible for splicing. To date, few studies have investigated the role of SNRPB2 in tumorigenesis. We examined data sourced from various public databases, such as The Cancer Genome Atlas(TCGA), the Clinical Proteomic Tumor Analysis Consortium(CPTAC), and Gene Expression Omnibus(GEO). Our investigation included gene expression, genomic and epigenomic scrutiny, gene set enrichment assessment(GSEA), and immune cell infiltration evaluation. Furthermore, we performed empirical validation to ascertain the impact of SNRPB2 suppression on the proliferation and migration of liver cancer cells. Analysis of gene expression revealed widespread upregulation of SNRPB2 across a spectrum of cancer types, with heightened levels of SNRPB2 expression in numerous tumors linked to unfavorable prognosis. Genomic and epigenomic assessments revealed connections between SNRPB2 expression and variations in SNRPB2 copy number, DNA methylation patterns, and RNA modifications. Through gene set enrichment analysis, the involvement of SNRPB2 in vital biological processes and pathways related to cancer was identified. Furthermore, scrutiny of immune cell infiltration suggested a potential relationship between SNRPB2 and the tumor microenvironment, which was reinforced by multiple single-cell sequencing profiles. Subsequent experimental validation revealed that silencing SNRPB2 effectively impeded the proliferation and migration of liver cancer cells. Taken together, these findings underscore the prospective utility of SNRPB2 as a prognostic biomarker and a promising candidate for immunotherapy in cancer. It is necessary to engage in additional exploration into its underlying mechanisms and clinical treatment potential.

The Predictive Role of Indices Indirectly Indicating Hyperlipidemia and Inflammation in Ascending Aortic Aneurysm.

Introduction Ascending aortic aneurysm (AAA) is an aortic disease that can progress with serious complications. The roles of hyperlipidemia and inflammation in its etiology are controversial. In this study, we aimed to investigate the predictive value of indices that can indirectly reflect hyperlipidemia and inflammation in patients with AAA. Methods This prospective study included 146 patients diagnosed with AAA and 88 controls. Demographic data, clinical history and laboratory results, including the atherogenic index of plasma (AIP), atherogenic coefficient (AC), pan-immune-inflammation value (PIV), and systemic immune-inflammation index (SII), were collected. Statistical analyses were performed to evaluate the relationships between these indices and the aortic diameter. Results Patients with AAA presented significantly higher PIV levels than controls did (p>0.05). However, no significant differences were observed in the AIP, AC, or SII between the patient and control groups. Furthermore, no significant correlation was found between the aortic diameter and the studied indices (p<0.05). PIV was the only significant parameter with a p-value of 0.026 (AUC: 0.587) according to the ROC analysis. Conclusion These findings suggest that while hyperlipidemia, as measured by the AIP and AC, may not play a direct role in AAA progression, inflammation indicated by PIV could be an important factor. Especially in resource-limited settings, these useful indicators can improve AAA management before the disease progresses to an advanced stage.

Comparative efficacy of THR-ß agonists, FGF-21 analogues, GLP-1R agonists, GLP-1-based polyagonists, and Pan-PPAR agonists for MASLD: A systematic review and network meta-analysis.

AIMS: To compare the efficacy of thyroid hormone receptor beta (THR-ß) agonists, fibroblast growth factor 21 (FGF-21) analogues, glucagon-like peptide-1 receptor agonists (GLP-1RAs), GLP-1-based polyagonists, and pan-peroxisome proliferator-activated receptor (Pan-PPAR) agonists in the treatment of metabolic dysfunction-associated steatotic liver disease (MASLD). METHODS: A database search for relevant randomized double-blind controlled trials published until July 11, 2024, was conducted. Primary outcomes were the relative change in hepatic fat fraction (HFF) and liver stiffness assessed non-invasively by magnetic resonance imaging proton density fat fraction and elastography. Secondary outcomes included histology, liver injury index, lipid profile, glucose metabolism, blood pressure, and body weight. RESULTS: Twenty-seven trials (5357 patients with MASLD) were identified. For HFF reduction, GLP-1-based polyagonists were most potentially effective (mean difference [MD] -51.47; 95 % confidence interval [CI]: -68.25 to -34.68; surface under the cumulative ranking curve [SUCRA] 84.9) vs. placebo, followed by FGF-21 analogues (MD -47.08; 95 % CI: -58.83 to -35.34; SUCRA 75.5), GLP-1R agonists (MD -37.36; 95 % CI: -69.52 to -5.21; SUCRA 52.3) and THR-ß agonists (MD -33.20; 95 % CI: -43.90 to -22.51; SUCRA 36.9). For liver stiffness, FGF-21 analogues were most potentially effective (MD -9.65; 95 % CI: -19.28 to -0.01; SUCRA 82.2) vs. placebo, followed by THR-ß agonists (MD -5.79; 95 % CI: -9.50 to -2.09; SUCRA 58.2), and GLP-1RAs (MD -5.58; 95 % CI: -15.02 to 3.86; SUCRA 54.7). For fibrosis improvement in histology, GLP-1-based polyagonists were most potentially effective, followed by FGF-21 analogues, THR-ß agonists, Pan-PPAR agonists, and GLP-1R agonists; For MASH resolution in histology, GLP-1-based polyagonists were most potentially effective, followed by THR-ß agonists, GLP-1R agonists, FGF-21 analogues, and Pan-PPAR agonists. THR-ß agonists are well-balanced in liver steatosis and fibrosis, and excel at improving lipid profiles; FGF-21 analogues are effective at improving steatosis and particularly exhibit strong antifibrotic abilities. GLP-1R agonists showed significant benefits in improving liver steatosis, glucose metabolism, and body weight. GLP-1-based polyagonists have demonstrated the most potential efficacy overall in terms of comprehensive curative effect. Pan-PPAR agonists showed distinct advantages in improving liver function and glucose metabolism. CONCLUSION: These results illustrate the relative superiority of the five classes of therapy in the treatment of MASLD and may serve as guidance for the development of combination therapies.

The prognostic and immune significance of Rab11A in pan-cancer and its function and mechanism underlying estrogen receptor targeting in breast cancer.

OBJECTIVE: Rab11A is an important molecule for recycling endosomes and is closely related to the proliferation, invasion, and metastasis of tumors. This study investigated the prognostic and immune significance of Rab11A and validated its potential function and mechanism in breast cancer (BRCA). METHODS: RNA sequencing data for 33 tumors were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression databases. Correlation analysis was used to evaluate the relationship between Rab11A expression and immune characteristics. Potential pathways were identified using the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analysis. Immunohistochemical analysis, colony formation assay, bromodeoxyuridine incorporation assay, immunofluorescence, and Western blot were used to explore potential function and mechanism. RESULTS: Analysis of the TCGA database showed significant upregulation of Rab11A expression in a variety of cancers. Rab11A was up-regulated in 82.4% of BRCA. High Rab11A expression is associated with poor survival in cancer patients and is a predictor of poor prognosis. CIBERSORT analysis showed that Rab11A was negatively associated with almost all immune cycle activity scores pan-cancer. The results of the TCGA-BRCA cohort were further confirmed by using pathological samples from clinical BRCA patients. The results showed that Rab11A expression was correlated with estrogen receptor (ER) and progesterone receptor expression in BRCA (p < 0.05). Knockdown and overexpression of Rab11A affected the proliferation of BRCA cells. Further mechanistic studies revealed that down-regulation of ER alpha (ERα) and up-regulation of ER beta (ERß) mediated Rab11A-induced inhibition of BRCA cell proliferation. CONCLUSION: Rab11A expression in pan-cancer is associated with poor prognosis and immune profile. In particular, in BRCA, Rab11A expression regulates cell proliferation by targeting ERα and ERß. High Rab11A expression is tightly associated with immune characteristics, tumor microenvironment, and genetic mutations. These results provide a reference for exploring the role of Rab11A in pan-cancer and provide a new perspective for revealing potential therapeutic targets in BRCA.

Organic carbon and mercury exports from pan-Arctic rivers in a thawing permafrost context - A review.

Climate change affects more than elsewhere the northern circumpolar permafrost region. This zone comprises large rivers flowing mainly to the Arctic Ocean, delivering about 10 % of the global riverine water flux. These pan-Arctic Rivers drive the dynamics of northern organic carbon (OC) and mercury (Hg) cycling. Permafrost degradation may release substantial amounts of OC and Hg, with potential regional and global impacts. In this review, we summarise the main findings in the last three decades about the role of the pan-Arctic Rivers in OC and Hg cycling and the effect of climate change on these dynamics. Total DOC and POC fluxes delivered by the pan-Arctic rivers presently reach 34.4 ±â€¯1.2 TgC·yr-1 and 7.9 ±â€¯0.5 TgC·yr-1, while the export of Hg reaches 38.9 ±â€¯1.7 Mg·yr-1. This review highlights future challenges for the scientific community in evaluating spatial and temporal dynamics of the processes involved in OC and Hg cycling in permafrost-affected areas. Permafrost thawing could lead to greater fluxes of OC and Hg with ill-known resulting risks for food chains. Within this context, efforts should be made to study OC effects on Hg methylation. Moreover, assessing the spatial variability of OC and Hg mobilisation and transport within the pan-Arctic watersheds may help understand the future OC and Hg cycling dynamics in the northern circumpolar permafrost region.

Characterization of meningitis-causing bacteria, with focus on genomic and pangenomic study of multi-drug resistant Streptococcus pneumoniae from cerebrospinal fluid.

Streptococcus pneumoniae is a major cause of meningitis in under developed countries with low vaccination rates and high antibiotic resistance. This study aimed to analyze 83 suspected meningitis patients in Karachi for the detection of S. pneumoniae followed by its whole genome sequencing and Pan Genome analysis. Out of the 83 samples collected, 33 samples with altered physical (turbidity), cytological (white blood cell count) and biochemical (total protein and total glucose concentrations) parameters indicated potential meningitis cases, while these parameters were within normal healthy ranges in remaining 50 samples. Latex particle agglutination (LPA) was performed on the 33 samples, revealing 20 positive cases of bacterial meningitis. The PCR and culturing methods revealed 5 S. pneumoniae isolates. Antibiotic susceptibility tests showed that one S. pneumoniae strain was resistant to erythromycin, levofloxacin, and tetracycline. Whole-genome sequencing of this resistant strain was performed and S. pneumoniae was confirmed with MLST analysis, while it had > 2.3 Mb genome and a single repUS43 plasmid. In CARD analysis, the strain had tet(M), ermB, RlmA(II), patB, pmrA, and patA ARGs, which could provide resistance against tetracycline, macrolide, fluoroquinolone, and glycopeptide antibiotics. Phylogenetic analysis revealed that the isolate was closely related to strains from Hungary and the USA. Pan-genome analysis with 144 genome assemblies from NCBI database showed that 1101 non-redundant core genes were shared between all strains. This study gives valuable understanding into the prevalence and characterization of meningitis-causing bacteria in Karachi, Pakistan  with prime focus on multi-drug resistant S. pneumoniae.

STARD7 could be an immunological and prognostic biomarker: from pan-cancer analysis to hepatocellular carcinoma validation.

BACKGROUND: As the emergence of technologies such as sequencing and gene mapping, significant advancements have been made in understanding the landscape of tumors. However, the effective treatment of tumors continues to pose a tremendous challenge in clinical practice, which highlights the importance of predicting tumor markers and studying drug resistance mechanisms. The prognosis and differential expression of STARD7 in human pan-cancer were investigated by bioinformatic methods and experimental verification. METHODS: The expression, diagnostic, and prognostic significance of the STARD7 gene were comprehensive analyzed using bioinformatics techniques. Furthermore, we validated our projected outcomes in liver cancer through experimental methodologies, including the use of qRT-PCR, CCK8 and transwell assays. RESULTS: The STARD7 gene exhibits differential expression in 25 tumors, with high expression observed in 22 tumors. These distinct expression patterns within different tumor types are closely associated with poor prognosis and diagnosis. Furthermore, the STARD7 gene plays a role in regulating the tumor immune microenvironment. Methylation levels of STARD7 vary among 20 types of tumors and are correlated with survival outcomes. Furthermore, the experiment results demonstrated that STARD7 is highly expressed in hepatocellular carcinoma cells. Suppression of STARD7 significantly impedes the proliferation, migration, and invasion of HepG-2 and SMMC-7721 cells. CONCLUSIONS: STARD7 has the potential to function as a crucial prognostic biomarker and exhibit correlation with tumor immunity in various types of human cancers. The implications of our findings extend to informing cancer immune-therapy and promoting the advancement of precision immune-oncology.

Modeling of mRNA deadenylation rates reveal a complex relationship between mRNA deadenylation and decay.

Complete cytoplasmic polyadenosine tail (polyA-tail) deadenylation is thought to be essential for initiating mRNA decapping and subsequent degradation. To investigate this prevalent model, we conducted direct RNA sequencing of S. cerevisiae mRNAs derived from chase experiments under steady-state and stress condition. Subsequently, we developed a numerical model based on a modified gamma distribution function, which estimated the transcriptomic deadenylation rate at 10 A/min. A simplified independent method, based on the delineation of quantile polyA-tail values, showed a correlation between the decay and deadenylation rates of individual mRNAs, which appeared consistent within functional transcript groups and associated with codon optimality. Notably, these rates varied during the stress response. Detailed analysis of ribosomal protein-coding mRNAs (RPG mRNAs), constituting 40% of the transcriptome, singled out this transcript group. While deadenylation and decay of RPG mRNAs accelerated under heat stress, their degradation could proceed even when deadenylation was blocked, depending entirely on ongoing nuclear export. Our findings support the general primary function of deadenylation in dictating the onset of decapping, while also demonstrating complex relations between these processes.

The Evolution of Extreme Genetic Variability in a Parasite-Resistance Complex.

Genomic regions that play a role in parasite defense are often found to be highly variable, with the MHC serving as an iconic example. Single nucleotide polymorphisms may represent only a small portion of this variability, with Indel polymorphisms and copy number variation further contributing. In extreme cases, haplotypes may no longer be recognized as orthologous. Understanding the evolution of such highly divergent regions is challenging because the most extreme variation is not visible using reference-assisted genomic approaches. Here we analyze the case of the Pasteuria Resistance Complex (PRC) in the crustacean Daphnia magna, a defense complex in the host against the common and virulent bacterium Pasteuria ramosa. Two haplotypes of this region have been previously described, with parts of it being non-homologous, and the region has been shown to be under balancing selection. Using pan-genome analysis and tree reconciliation methods to explore the evolution of the PRC and its characteristics within and between species of Daphnia and other Cladoceran species, our analysis revealed a remarkable diversity in this region even among host species, with many non-homologous hyper-divergent-haplotypes. The PRC is characterized by extensive duplication and losses of Fucosyltransferase (FuT) and Galactosyltransferase (GalT) genes that are believed to play a role in parasite defense. The PRC region can be traced back to common ancestors over 250 million years. The unique combination of an ancient resistance complex and a dynamic, hyper-divergent genomic environment presents a fascinating opportunity to investigate the role of such regions in the evolution and long-term maintenance of resistance polymorphisms. Our findings offer valuable insights into the evolutionary forces shaping disease resistance and adaptation, not only in the genus Daphnia, but potentially across the entire Cladocera class.

Comprehensive pan-cancer analysis and experiments revealed R3HDM1 as a novel predictive biomarker for prognosis and immune therapy response.

Background: R3HDM1, an RNA binding protein with one R3H domain, remains uncharacterized in terms of its association with tumor progression, malignant cell regulation, and the tumor immune microenvironment. This paper aims to fill this gap by analyzing the potential of R3HDM1 in diagnosis, prognosis, chemotherapy, and immune function across various cancers. Methods: Data was collected from the Firehost database (http://gdac.broadinstitute.org) to obtain the TCGA pan-cancer queue containing tumor and normal samples. Additional data on miRNA, TCPA, mutations, and clinical information were gathered from the UCSC Xena database (https://xenabrowser.net/datapages/). The mutation frequency and locus of R3HDM1 in the TCGA database were examined using the cBioPortal. External validation through GEO data was conducted to assess the differential expression of R3HDM1 in different cancers. Protein expression levels were evaluated using the Clinical Proteomics Tumor Analysis Alliance (CPTAC). The differential expression of R3HDM1 was verified in lung adenocarcinoma cell lines and normal lung glandular epithelial cells via RT-qPCR. Cell migration and proliferation experiments were conducted by knocking down the expression of R3HDM1 in two lung adenocarcinoma cell lines using small interfering RNA. The biological role of R3HDM1 in pan-cancer was explored using the GSEA method. Multiple immune infiltration algorithms from the TIMER2.0 database was employed to investigate the correlation between R3HDM1 expression and the tumor immune microenvironment. Validation of transcriptome immune infiltration was based on 140 single-cell datasets from the TISCH database. The study also characterized a pan-cancer survival profile and analyzed the differential expression of R3HDM1 in different molecular subtypes. The relationship between R3HDM1 and drug resistance was investigated using four chemotherapy data sources: CellMiner, GDSC, CTRP and PRISM. The impact of chemicals on the expression of R3HDM1 was explored through the CTD database. Result: The study revealed differential expression of R3HDM1 in various tumors, indicating its potential as an early diagnostic marker. Changes in somatic copy number (SCNA) and DNA methylation were identified as factors contributing to abnormal expression levels. Additionally, the study found that R3HDM1 expression is associated with clinical features, metabolic pathways, and important pathways related to metastasis and the immune system. High expression of R3HDM1 was linked to poor prognosis across different tumors and altered drug sensitivity. Furthermore, the expression of R3HDM1 showed significant correlations with immune modulatory molecules and biomarkers of lymphocyte subpopulation infiltration. Finally, the study highlighted four chemicals that could influence the expression of R3HDM1. Conclusion: Overall, this study proposes that R3HDM1 expression is a promising biomarker for predicting the prognosis of cancer, especially lung adenocarcinoma, and the efficacy of immunotherapy, demonstrating the rationale for further exploration in the development of anti-tumor therapies.

WGS Analysis of Staphylococcus warneri Outbreak in a Neonatal Intensive Care Unit.

Purpose: Staphylococcus warneri is an opportunistic pathogen responsible for hospital-acquired infections (HAIs). The aim of this study was to describe an outbreak caused by S. warneri infection in a neonatal intensive care unit (NICU) and provide investigation, prevention and control strategies for this outbreak. Methods: We conducted an epidemiological investigation of the NICU S. warneri outbreak, involving seven neonates, staff, and environmental screening, to identify the source of infection. WGS analyses were performed on S. warneri isolates, including species identification, core genome single-nucleotide polymorphism (cgSNP) analysis, pan-genome analysis, and genetic characterization assessment of the prevalence of specific antibiotic resistance and virulence genes. Results: Eight S. warneri strains were isolated from this outbreak, with seven from neonates and one from environment. Six clinical cases within three days in 2021 were linked to one strain isolated from environmental samples; isolates varied by 0-69 SNPs and were confirmed to be from an outbreak through WGS. Multiple infection prevention measures were implemented, including comprehensive environmental disinfection and stringent protocols, and all affected neonates were transferred to the isolation wards. Following these interventions, no further cases of S. warneri infections were observed. Furthermore, pan-genome analysis results suggested that in human S. warneri may exhibit host specificity. Conclusion: The investigation has revealed that the outbreak was linked to the milk preparation workbench by the WGS. It is recommended that there be a stronger focus on environmental disinfection management in order to raise awareness, improve identification, and prevention of healthcare-associated infections that are associated with the hospital environment.

Discovery of Tetrahydro Tanshinone I as a Naturally Occurring Covalent Pan-Inhibitor Against Gut Microbial Bile Salt Hydrolases.

Gut microbial bile salt hydrolases (gmBSHs), an important class of bacteria-produced cysteine hydrolases, play a crucial role in bile acid metabolism. Modulating the total gmBSH activity is a feasible way for ameliorating some metabolic diseases including colorectal cancer, type 2 diabetes, and obesity. This study reported the discovery and characterization of a botanical compound as a covalent pan-inhibitor of gmBSHs. Following the screening of more than 100 botanical compounds, tanshinones were found with strong time-dependent anti-EfBSH effects. After that, a total of 17 naturally occurring tanshinones were collected, and their anti-EfBSH potentials were tested. Among all tested tanshinones, tetrahydro tanshinone I (THTI) exhibited the most potent inhibitory effects against five gmBSHs (EfBSH, LsBSH, BtBSH, CpBSH, and BlBSH), showing the IC50 values ranging from 0.28 ± 0.05 µM to 1.62 ± 0.07 µM. Further investigations showed that THTI could covalently modify the conserved catalytic cysteine (Cys2) of all tested gmBSHs, while this agent could strongly inhibit the total gmBSHs activity in live microorganisms and murine gut luminal content. Collectively, THTI is identified as a naturally occurring covalent pan-inhibitor of gmBSHs, which offers a promising lead compound to develop more efficacious gmBSHs inhibitors for the management of bile acid metabolism and related metabolic disorders.

CISD3 is a prognostic biomarker and therapeutic target in pan-cancer.

Recent studies indicate that CISD3 is crucial in mitochondrial function and tumorigenesis. Using various databases, we systematically analyzed its expression, prognostic value, and immune activity. Our findings show CISD3 is mainly expressed in tumor cells across cancers, with higher mRNA but lower protein levels, degraded post-translationally via the lysosomal pathway. In certain cancers, CISD3 expression is positively correlated with tumor-infiltrating immune cells. Prognostic analysis suggests dual roles as both protective and risk factors, notably an independent prognostic predictor in renal cell carcinoma (RCC). CISD3 copy number variations are linked to homologous recombination defects and tumor-specific neoantigens, negatively correlated with methylation levels. Pathway analysis reveals CISD3 involvement in oncogenic processes, such as proliferation inhibition and epithelial-mesenchymal transition. Protein interactions underline its role in mitochondrial metabolism and redox balance. Experiments confirm low CISD3 expression in cancers, with overexpression reducing proliferation, migration, invasion, and tumor growth in mice. Mechanistic studies indicate CISD3 overexpression disrupts mitochondrial function, increases ROS levels, decreases GSH/GSSG ratios and mitochondrial membrane potential, inhibiting antioxidant activity and promoting cell damage and ferroptosis, thus impeding cancer progression. This study highlights CISD3's potential as a prognostic biomarker and therapeutic target.

Neutrophil chemotaxis score and chemotaxis-related genes have the potential for clinical application to prognosticate the survival of patients with tumours.

As frontline cells, the precise recruitment of neutrophils is crucial for resolving inflammation and maintaining the homeostasis of the organism. Increasing evidence suggests the pivotal role of neutrophil chemotaxis in cancer progression and metastasis. Here, we collected clinical data and peripheral blood samples from patients with tumours to examine the alterations in the neutrophil quantity and chemotactic function using the Cell Chemotaxis Analysis Platform (CCAP). Transcriptome sequencing data of pan-cancer were obtained from The Cancer Genome Atlas (TCGA). Using the least absolute shrinkage and selection operator (LASSO) Cox regression model, we selected a total of 29 genes from 155 neutrophil- and chemotaxis-related genes to construct the ChemoScore model. Meanwhile, nomogram-based comprehensive model was established for clinical application. Furthermore, immunofluorescence (IF) staining was employed to assess the relationship between the neutrophils infiltrating and the survival outcomes of tumours. In this observational study, the chemotactic function of neutrophils was notably diminished in patients. The establishment and validation of ChemoScore suggested neutrophil chemotaxis to be a risk factor in most tumours, whereby higher scores were associated with poorer survival outcomes and were correlated with various immune cells and malignant biological processes. Moreover, IF staining of tumour tissue substantiated the adverse correlation between neutrophil infiltration and the survival of patients with lung adenocarcinoma (P = 0.0002) and colon adenocarcinoma (P = 0.0472). Taken together, patients with tumours demonstrated a decrease in chemotactic function. ChemoScore potentially prognosticates the survival of patients with tumours. Neutrophil chemotaxis provides novel directions and theoretical foundations for anti-tumour treatment.

Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types.

BACKGROUND: Homologous recombination deficiency (HRD) is recognized as a pan-cancer predictive biomarker that potentially indicates who could benefit from treatment with PARP inhibitors (PARPi). Despite its clinical significance, HRD testing is highly complex. Here, we investigated in a proof-of-concept study whether Deep Learning (DL) can predict HRD status solely based on routine hematoxylin & eosin (H&E) histology images across nine different cancer types. METHODS: We developed a deep learning pipeline with attention-weighted multiple instance learning (attMIL) to predict HRD status from histology images. As part of our approach, we calculated a genomic scar HRD score by combining loss of heterozygosity (LOH), telomeric allelic imbalance (TAI), and large-scale state transitions (LST) from whole genome sequencing (WGS) data of n = 5209 patients across two independent cohorts. The model's effectiveness was evaluated using the area under the receiver operating characteristic curve (AUROC), focusing on its accuracy in predicting genomic HRD against a clinically recognized cutoff value. RESULTS: Our study demonstrated the predictability of genomic HRD status in endometrial, pancreatic, and lung cancers reaching cross-validated AUROCs of 0.79, 0.58, and 0.66, respectively. These predictions generalized well to an external cohort, with AUROCs of 0.93, 0.81, and 0.73. Moreover, a breast cancer-trained image-based HRD classifier yielded an AUROC of 0.78 in the internal validation cohort and was able to predict HRD in endometrial, prostate, and pancreatic cancer with AUROCs of 0.87, 0.84, and 0.67, indicating that a shared HRD-like phenotype occurs across these tumor entities. CONCLUSIONS: This study establishes that HRD can be directly predicted from H&E slides using attMIL, demonstrating its applicability across nine different tumor types.