Low Risk Score Research Articles

Identification of tumor-antigen signatures and immune subtypes for mRNA vaccine selection in muscle-invasive bladder cancer

BackgroundMuscle-invasive bladder cancer continues to lack reliable diagnostic and prognostic biomarkers. Recently, tumor vaccines targeting specific molecules have emerged as a promising treatment in inhibiting tumor progression, which was rekindled under the background of coronavirus disease-2019 pandemic. However, the application of mRNA vaccine targeting muscle-invasive bladder cancer–specific antigens remains limited, and there has been a lack of comprehensive studies or validations to identify suitable patient subgroups for vaccination. This study aims to explore novel muscle-invasive bladder cancer antigen signatures to identify patients most likely to benefit from vaccination. MethodsGene expression profiles of muscle-invasive bladder cancer samples, along with corresponding clinical data, were retrieved from the Cancer Genome Atlas Program. The least absolute shrinkage and selection operator model was applied to develop signatures for stratifying muscle-invasive bladder cancer patients. Prognostic accuracy of each factor was assessed using receiver operating characteristic analysis. Tumor Immune Estimation Resource was employed to visualize the relationship between the proportion of antigen-presenting cells and the expression of selected genes. The CIBERSORT and WGCNA R packages were used to identify differences in immune infiltration levels across muscle-invasive bladder cancer subgroups. Additionally, the STRING database and Cytoscape were used to construct the protein-protein interaction network. CCK-8 and colony formation assays were employed in invitro experiments. ResultsA total of 49 potential tumor antigens were identified. Using least absolute shrinkage and selection operator Cox regression, 14 tumor antigens were selected to develop a risk evaluation signature. The risk score signature can serve as a valuable tool for predicting the outcomes of muscle-invasive bladder cancer patients. Based on differential clinical, molecular, and immune-related gene profiles, muscle-invasive bladder cancer patients were classified into 2 subtypes: the immune “cold” subtype (immune score 1) and the immune “hot” subtype (immune score 2). The immune score signature, developed using a logistic score model, effectively distinguishes between patients more likely to belong to immune score 1 or 2. Notably, patients with a high risk score exhibited a higher proportion of immune score 2 compared to those with a low risk score. Additionally, the prognostic accuracy was significantly enhanced when the risk score and immune score were combined. Different tumor subtypes displayed distinct immune landscapes and signaling pathways. Moreover, novel tumor antigens associated with oxidative stress were identified. ConclusionThe risk score and immune score signatures based on tumor antigens have identified potential effective neo-antigens for the development of mRNA vaccines targeting muscle-invasive bladder cancer. Patients with low risk score and immune score 1 subtype are more likely to benefit from mRNA vaccination. Additionally, this study highlights the critical role of oxidative stress in modulating the efficacy of the mRNA vaccine.

Novel signature of ferroptosis-related long non-coding RNA to predict lower-grade glioma overall survival

BackgroundFerroptosis is a novel type of programmed cell death in various tumors; however, underlying mechanisms remain unclear. We aimed to develop ferroptosis-related long non-coding RNA (FRlncRNA) risk scores to predict lower-grade glioma (LGG) prognosis and to conduct functional analyses to explore potential mechanisms.MethodsLGG-related RNA sequencing data were extracted from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Pearson correlation analysis was used to identify the FRlncRNAs, univariate Cox regression analysis was for identify the prognostic FRlncRNAs, and then intersection FRlncRNAs were screened between TCGA and CGGA. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to develop a risk score to predict LGG prognosis.ResultsA total of nine FRlncRNAs were screened to construct the novel prognostic risk score of LGG, and high-risk score patients had a worse overall survival than low-risk score patients both in TCGA and CGGA datasets. The risk score was quite correlated with clinicopathological characteristics (age, WHO grade, status of MGMT Methtlation, IDH mutation, 1p/19q codeletion, and TMB), and could promote current molecular subtyping systems. Comprehensive analyses revealed that signaling pathways of B-cell receptor and T-cell receptor, immune cells of macrophage cell and CD4+ T cell, tumor microenvironment of stroma score and immune score, and immune checkpoints of PD-1, PD-L1, and CTLA4 were all enriched in the high-risk score group.ConclusionThe nine FRlncRNAs risk scores was a promising biomarker to predict the LGG’s prognosis and distinguish the characteristics of molecular and immune.

Colorectal Cancer Incidence and Mortality After Negative Colonoscopy Screening Results

The current recommendation for a 10-year rescreening interval after a negative colonoscopy screening (NCS) result has been questioned, with some studies showing a persistently lower risk of colorectal cancer (CRC) after NCS results. To examine long-term CRC incidence and mortality after NCS results (ie, no presence of CRC or polyps) and according to a risk score based on major demographic and lifestyle risk factors. In this cohort study, 3 prospective US population-based cohorts from the Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-up Study were followed up from 1988 and 1991 to 2020. Data from the National Health and Nutrition Examination Survey (NHANES) from the January 1, 2017, to December 31, 2018, cycle were used to compare the risk profile distribution with that of the general US population. Data analysis was performed from October 2023 to August 2024. Time-varying status of NCS results and risk score. Cox proportional hazards regression was used to calculate hazard ratios (HRs) and 95% CIs for incidence and mortality of CRC. A total of 195 453 participants (median [IQR] age, 44 [37-56] years at baseline; 81% female) were followed up for a median (IQR) of 12 (6-20) years. Among 81 151 individuals with NCS results and 114 302 without endoscopy, 394 and 2229 CRC cases and 167 and 637 CRC deaths, respectively, were documented. Negative colonoscopy screening results were consistently associated with lower CRC incidence (HR, 0.51; 95% CI, 0.44-0.58) and mortality (HR, 0.56; 95% CI, 0.46-0.70) for 20 years. Among individuals with NCS results, those with an intermediate risk (scores, 6-7) and low risk (scores, 0-5) did not reach the 10-year cumulative incidence of CRC (0.78%) of the high-risk individuals (scores, 8-12) until 16 and 25 years after initial screening, respectively. These findings provide evidence for shared decision-making between patients and physicians to consider extending the rescreening intervals after an NCS result beyond the currently recommended 10 years, particularly for individuals with a low-risk profile. These results showed, as a proof of concepts, the importance of considering known CRC risk factors when making decisions for colonoscopy rescreening.

Single-cell transcriptome analysis identifies subclusters and signature with N-glycosylation in endometrial cancer.

Endometrial cancer (EC) is a prevalent gynecologic cancer, with worldwide increasing incidence and disease-associated mortality. N-glycosylation, a critical post-translational modification, has been implicated in cancer progression and immune response modulation. We aimed to elucidate the role of N-glycosylation-related genes on EC cell heterogeneity, prognosis, and immunotherapy response. Data from single-cell RNA sequencing (scRNA) of five patients with EC were acquired from the Gene Expression Omnibus (GEO) database. Nonnegative matrix factorization (NMF) was used to identify cell subtypes related to N-glycosylation from a scRNA matrix. Subsequently, a consensus prognostic signature by integrating 101 combinations of 10 machine learning algorithms. The response to immunotherapy in EC was further examined by multiple algorithms. Our findings identified 11,020 differentially expressed genes (DEGs), of which 34 N-glycosylation-related DEGs were remarkably associated with overall survival (OS) in EC. Single-cell RNA sequencing analysis revealed 30,233 cells divided into eight clusters, with T cells and epithelial cells showing distinct functional characteristics. NMF clustering further classified malignant cells into four subtypes: N-glycosylation-C0, Glycosphingolipid-C1, O-GalNAc-C2, and Elongation-C3. The O-GalNAc-C2 subtype exhibited the highest metabolic pathway activity and activation of transcription factors SOX4, JUND, and FOS. Additionally, cell-cell interaction networks highlighted the MK signaling pathway as a critical mediator of intercellular communication. An integrated machine learning framework generated a prognostic model comprising eight DEGs (LAMC2, KRT7, IL32, KRT18, SERPINA1, PGR, AKAP12, EDN2), achieving an average C-index of 0.712 in training and validation cohorts. A low-risk score implies more significant immune cell infiltration and better response to immunotherapy. Our study underscores the role of N-glycosylation-related genes in EC prognosis and immunotherapy response prediction, and may provide a basis for the development of targeted therapies and personalized treatment strategies.

A novel necroptosis-related genes signature to predict prognosis and treatment response in bladder cancer

BackgroundNecroptosis, a form of programmed inflammatory cell death, plays a crucial role in tumor development, necrosis, metastasis, and immune response. This study aimed to explore the role of necroptosis in BLCA and construct a new prognostic model to guide clinical treatment and predict individualized treatment response.MethodsThe transcriptome profiling and the corresponding clinical data of BLCA patients were obtained from the Cancer Genome Atlas database (TCGA) and GEO databases. Univariate, multivariate and LASSO Cox regression analyses were used to identify and construct prognostic features associated with necroptosis. We constructed and validated a prognostic model associated with the patient’s overall survival (OS). A nomogram was established to predict the survival rates of BLCA patients. Finally, the correlation between risk scores and tumor immune microenvironment, somatic mutations, immunotherapy, and chemotherapy was comprehensively analyzed.ResultsThe study found two distinct NRG clusters and three gene subtypes, with significant differences in pathway enrichment and immune cell infiltration associated with different NRG clusters in the TME. In addition, we screened out six necroptosis prognosis-related genes (including PPP2R3A; CERCAM; PIK3IP1; CNTN1; CES1 and CD96) to construct a risk score prognostic model. Significant differences in overall survival rate, immune cell infiltration status, and somatic mutations existed between the high and low-risk scores in BLCA patients. Finally, drug sensitivity analysis showed that high-risk patients benefited more from immunotherapy and chemotherapy drugs.ConclusionThis study explores the importance of necroptosis in the prognosis of patients with BLCA, and the prognostic features associated with necroptosis that we identified can serve as new biomarkers to help develop more precise treatment strategies.

Endoplasmic reticulum stress-related signatures: a game-changer in prognostic stratification for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) has limited therapeutic options and a poor prognosis. The endoplasmic reticulum (ER) plays a crucial role in tumor progression and response to stress, making it a promising target for HCC stratification. This study aimed to develop a risk stratification model using ER stress-related signatures. We utilized transcriptome data from The Cancer Genome Atlas and Gene Expression Omnibus, which encompass whole-genome expression profiles and clinical annotations. Machine learning algorithms, including the least absolute shrinkage and selection operator, random forest, and support vector machine recursive feature elimination, were applied to the key genes associated with HCC prognosis. A prognostic system was developed using univariate Cox hazard analysis and least absolute shrinkage and selection operator Cox regression, followed by validation using Kaplan-Meier analysis and receiver operating characteristic curves. Tumor immune dysfunction and exclusion tools were used to predict immunotherapy responsiveness. Two distinct clusters associated with ER stress were identified in HCC, each exhibiting unique clinical and biological features. Using a computational approach, a prognostic risk model, namely the ER stress-related signature, was formulated, demonstrating enhanced predictive accuracy compared with that of existing prognostic models. An effective clinical nomogram was established by integrating the risk model with clinicopathological factors. Patients with lower risk scores exhibited improved responsiveness to various chemotherapeutic, targeted, and immunotherapeutic agents. The critical role of ER stress in HCC is highlighted. The ER stress-related signature developed in this study is a powerful tool to assess the risk and clinical treatment of HCC.

Primary prevention of cardiovascular diseases among women in a South Asian population: a descriptive study of modifiable risk factors

ObjectiveThe aim of this study was the assessment of modifiable risk factors of cardiovascular diseases (CVD) among women versus men at a newly developed preventive cardiology clinic of a large...

Genetic determinants of pancreatitis risk in hypertriglyceridemia.

In recent years, studies have shed light on the concept of risk heterogeneity among patients with severe hypertriglyceridemia (HTG). Several clinical risk factors for acute pancreatitis have been identified in this population, but the importance of different genetic factors above and beyond triglyceride concentration remains unclear. This review endeavours to summarize recent developments in this field. Recent studies suggest that the molecular basis of severe HTG (polygenic susceptibility vs. rare pathogenic variants) can modulate the risk of acute pancreatitis independently of triglyceride level. Furthermore, a pancreatitis polygenic risk score has been developed and validated using data from the largest GWAS meta-analysis of acute pancreatitis published to date. In patients with severe HTG, a high polygenic susceptibility for pancreatitis was associated with a three-fold increased risk of acute pancreatitis compared with those with a lower polygenic risk score. In the past months, there have been substantial advances in understanding the prediction of acute pancreatitis in patients with severe HTG. However, further efforts at developing risk-stratification strategies and predictive models may help identifying the patients who would benefit most from early and effective interventions to reduce the risk of pancreatitis, including treatment with APOC3 inhibitors.

The Demographic and Clinical Characteristics, Prognostic Factors, and Survival Outcomes of Head and Neck Carcinosarcoma: A SEER Database Analysis.

Head and neck carcinosarcoma (HNCS) is a rare and highly aggressive malignancy with limited research, resulting in an incomplete understanding of disease progression and a lack of reliable prognostic tools. This study aimed to retrospectively analyze the clinical characteristics and outcomes of HNCS patients using data from the Surveillance, Epidemiology, and End Results (SEER) database and to develop a nomogram to predict overall survival (OS) and cancer-specific survival (CSS). Patients diagnosed with HNCS from 1975 to 2020 were identified in the SEER database. Univariate and multivariate Cox regression analyses were conducted to identify independent prognostic indicators, with the optimal model selected using the minimal Akaike Information Criterion (AIC). The identified prognostic factors were incorporated into nomograms to predict OS and CSS. Model performance was assessed using the concordance index (C-index), area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Survival curves were generated using Kaplan-Meier analysis and compared via the log-rank test. A total of 152 HNCS patients were included, with 108 assigned to the training cohort and 44 to the validation cohort in a 7:3 ratio. Prognostic factors including age, primary tumor site, marital status, radiotherapy, chemotherapy, tumor size, pathological grade, and tumor stage were incorporated into the nomogram models. The models demonstrated strong predictive performance, with C-index values for OS and CSS of 0.757 and 0.779 in the training group, and 0.777 and 0.776 in the validation group, respectively. AUC values for predicting 3-, 5-, and 10-year OS were 0.662, 0.713, and 0.761, and for CSS the values were 0.726, 0.703, and 0.693. Kaplan-Meier analysis indicated significantly improved survival for patients with lower risk scores. The 3-, 5-, and 10-year OS rates for the entire cohort were 54.1%, 45.6%, and 35.1%, respectively, and the CSS rates were 62.9%, 57.5%, and 52.2%, respectively. This study provides validated nomograms for predicting OS and CSS in HNCS patients, offering a reliable tool to support clinical decision-making for this challenging malignancy. These nomograms enhance the ability to predict patient prognosis and personalize treatment strategies.

Metabolomic Profiling of Open-Angle Glaucoma Etiologic Endotypes: Tohoku Multi-Omics Glaucoma Study.

The purpose of this study was to investigate biologically meaningful endotypes of open-angle glaucoma (OAG) by applying unsupervised machine learning to plasma metabolites. This retrospective longitudinal cohort study enrolled consecutive patients aged ≥20 years with OAG at Tohoku University Hospital from January 2017 to January 2020. OAG was confirmed based on comprehensive ophthalmic examinations. Among the 523 patients with OAG with available clinical metabolomic data, 173 patients were longitudinally followed up for ≥2 years, with available data from ≥5 reliable visual field (VF) tests without glaucoma surgery. We collected fasting blood samples and clinical data at enrollment and nuclear magnetic resonance spectroscopy to profile 45 plasma metabolites in a targeted approach. After computing a distance matrix of preprocessed metabolites with Pearson distance, gap statistics determined the optimal number of OAG endotypes. Its risk factors, clinical presentations, metabolomic profiles, and progression rate of sector-based VF loss were compared across endotypes. Five distinct OAG endotypes were identified. The highest-risk endotype (endotype B) showed a significant faster progression of central VF loss (P = 0.007). Compared with patients with other endotypes, those with endotype B were more likely to have a high prevalence of dyslipidemia, cold extremities, oxidative stress, and low OAG genetic risk scores. Pathway analysis of metabolomic profiles implicated altered fatty acid and ketone body metabolism in this endotype, with 34 differentially enriched pathways (false discovery rate [FDR] < 0.05). Integrated metabolomic profiles identified five distinct etiologic endotypes of OAG, suggesting pathological mechanisms related with a high-risk group of central vision loss progression in the Japanese population.

Waist circumference and waist-to-height ratio: Exploring the associations for high blood pressure risk in school-age adolescents

BackgroundChildhood and adolescent obesity present a global health concern, notably due to its association with adverse outcomes such as high blood pressure (HBP). Waist circumference (WC) and waist-to-height ratio (WHtR) are promising indicators for assessing HBP risk in school-age adolescents. However, their association with Stavnsbo-recommended WC cutoff points and high BP prevalence necessitates further investigation, holding potential implications for early intervention and prevention strategies. ObjectiveInvestigate the association between high blood pressure (HBP) and WC cutoff points advised by Stavnsbo, along with WHtR, in adolescents from privileged socioeconomic backgrounds in Brazil. MethodsThis cross-sectional study in 2022 involved 216 students aged 9 to 16 from a private school in Londrina, Paraná, Brazil. Data, collected through an internal project monitoring anthropometric and social indicators, included validated blood pressure assessments. Statistical analyses, employing t-tests, chi-square tests, and logistic regression, explored relationships between WC, WHtR, and blood pressure, adjusting for covariates. ResultsFemale participants had a lower prevalence of obesity (2.9% vs 5.3%) but a higher prevalence of overweight (27.5% vs 17.5%) compared to males. The overall excess weight prevalence was 26.4%, with females showing lower absolute risk scores for WC (25.5% vs 34.2%), WHtR (19.6% vs 23.7%), and HBP (21.5% vs. 40.3%). Significant associations were observed between HBP and WC (X2 = 9.759, P = 0.002) as well as WHtR (X2 = 6.335, P = 0.012) among males, with those in the “Risk” category exhibiting higher HBP prevalence. Overall, both WC and WHtR demonstrated significant associations with HBP (X2 = 12.428, P < 0.001, and X2 = 9.550, P = 0.002, respectively). Logistic regression indicated higher odds for HBP in males with risk values for WC (OR 3.876 [1.714–8.765 CI], P = 0.001) or WHtR (OR 3.684 [1.457–9.315 CI], P = 0.006). In the overall analysis, participants with risk values for WC had 3.2 (1.688–6.080 CI, P < 0.001) times higher odds, and for WHtR, 3.4 (1.679–6.934 CI, P = 0.001) times higher odds of HBP. ConclusionThis study highlights the associations between WC, WHtR, and HBP in adolescent schoolchildren. The results underscore the significance of gender-specific assessments and emphasize the potential of these anthropometric measures as valuable tools for identifying and managing HBP risk in adolescents. Further research and clinical applications are imperative to deepen understanding and address the health needs of this vulnerable population.

Outdoor worker knowledge of ticks and Lyme disease in Québec.

Lyme disease is a well-known occupational risk across North America caused by exposure to Borrelia burgdorferi via blacklegged ticks (Ixodes scapularis). As the geographic range of B. burgdorferi advances with the increasing distribution of blacklegged ticks, more outdoor workers are at risk of contracting Lyme disease. In this study, we examined the demography and personal perceptions of outdoor workers within one framework to better determine the overall risk for those working outdoors. We analysed outdoor worker knowledge of ticks and of behaviours that can prevent tick bites and Lyme disease. We then compared these risk perceptions of individuals across age, sex, education, and industry, as well as time spent outdoors. We tested the hypothesis that the risk perception of an individual and their knowledge of Lyme disease transmission was dependent on their demographics, experience in their job, and the region in which they spend time outdoors. We estimated a knowledge-based risk score based on individuals' answers to a questionnaire on risk perception given to voluntary participants who work outdoors. Those who had higher risk scores were more at risk. We found that knowledge-based risk scores were correlated with geographic risk levels and with the number of hours per day spent outdoors. Those who work longer hours and who work in areas with mid-level risk had higher risk scores. Those who spend more time outdoors recreationally had lower risk scores. Further examination and acknowledgment of the reasoning behind why these factors are affecting workers' risks must be considered to recognize that it is not necessarily demographics or geographically high-risk areas that affect an individual's risk. Workers' knowledge of these risks is affected by several variables that should be taken into consideration when implementing safety measures and awareness programs.

General Practice Sleep Scale – the “GPSS” – A proposed new tool for use in General Practice for risk assessment of Obstructive Sleep Apnoea

BackgroundThis pilot study investigated a new simplified OSA screening tool that could be used in primary care/GP settings – the “GPSS” tool – “General Practice Sleep Scale” and compared against common existing OSA screening tools. MethodsA convenience sample of patients attending the respiratory and sleep clinic in the Northern Territory of Australia were included if they completed the GPSS prior to undergoing a diagnostic polysomnography. The GPSS contained 9 questions to provide information on: sex, age, body mass index, neck circumference, snoring, witnessed apnoeas, morning tiredness, daytime sleepiness and presence of hypertension/diabetes/heart disease/depression. Presence of OSA was defined as an apnoea-hypopnoea index of ≥15/hour. The GPSS scoring was developed via log odds of regression predictions for each GPSS question upon OSA. Results159 patients (65 % male, median age 45 years) were enrolled. A minimum score of 1 was assigned to GPSS questions, up to 5 for the strongest predictor (neck circumference). The median total GPSS score was 13 (IQR 9, 16) (maximum 22) and correlated strongly with OSA (AUC 0.812 (95 % CI 0.744, 0.881)). Categorised into low (0–7), moderate (8–13) or high risk (>13), a moderate or severe score had sensitivity 100, specificity 34.9 %. The GPSS significantly outperformed the Epworth Sleepiness Scale, Berlin questionnaire and OSA-50, and was comparable but slightly improved against the STOP-Bang. ConclusionsThe proposed GPSS tool could be of use in general practice settings. Further prospective research is warranted to test the applicability and adaptability of the GPSS tool in wider population settings.

Understanding long-term risk in Percutaneous Coronary Intervention (PCI) in the Australian contemporary era with a focus on defining Complex Revascularisation in High-Risk Indicated Patients (CHIP)

BackgroundComplex Revascularisation in High-Risk Indicated Patients (CHIP) is emerging in Percutaneous Coronary Intervention (PCI). We document the frequency and outcomes following CHIP PCI in the Australian population, to understand risk and guide clinical decision-making. We propose a scoring system to define CHIP procedures. MethodsPatients undergoing PCI from Melbourne Intervention Group registry between 2005 and 2018 were analysed. Patients were stratified based on the number of high-risk features defined as 1)presence of ≥3 patient factors including age > 75yo, COPD, diabetes, renal impairment (eGFR<60 mL/min/1.73 m2), PVD, and 2)LVEF<30 %, and/or 3)having one complex coronary anatomical feature such as LMCA PCI, ACC/AHA B2/C lesion PCI, presence of multi-vessel disease or CTO PCI. National Death Index linkage was performed for long-term mortality analysis. Outcomes were analysed according to 4 risk categories – low risk(score 0), intermediate risk(score 1), high-risk(score 2), and very high-risk(score 3). Results20,973patients were analysed. Majority of patients underwent intermediate-risk procedures(71.7 %), with low rates of high-risk(6.6 %), and very high-risk(0.2 %). Lesion success inversely correlates with risk; low-risk(99.4 %), intermediate-risk(95.1 %), high-risk(94.3 %), very high-risk(92.5 %),p < 0.001. In-hospital and 30-day death correlates with risk; low-risk(0.0 %/0.1 %), intermediate-risk(0.3 %/0.5 %), high-risk(1.5 %/2.9 %), very high-risk(2.4 %/7.1 %),p < 0.001. Long-term mortality correlates with risk; low-risk(12.3 %), intermediate-risk(15.8 %), high-risk(49.3 %), very high-risk(76.2 %),p < 0.001. On multivariate analysis, increasing risk correlates with long-term mortality; intermediate-risk(HR1.41), high-risk(HR6.42), and very high-risk(14.05). ConclusionIn the Australian practice, proportion of patients undergoing high and very high-risk PCI procedures are low. Despite good procedural success and in-hospital outcomes, long-term mortality is poor. Further research into appropriate patient selection, and direct comparison of CHIP PCI to those treated medically and surgically should be considered.

Risk assessment models and survival in pulmonary arterial hypertension: a SPAHR analysis

BackgroundMulticomponent improvement (MCI) is a novel endpoint for predicting survival in patients with pulmonary arterial hypertension (PAH), included in the sotatercept clinical program. For the first time, we investigated the prognostic value of MCI, ESC/ERS 4-strata risk (4SR) assessment, and the non-invasive French risk stratification score (FRS), for predicting survival in PAH patients in Sweden. All risk prediction models are based on three parameters: WHO-FC (World Health Organization Functional Class), NT-proBNP, and 6MWD (6-minute walk distance). MethodsData from the Swedish PAH & CTEPH Registry (SPAHR) collected 2008-2021 were used for the analyses. The association of MCI achievement, 4SR, and FRS calculated at 6 months (6M), with transplant-free (TF) survival was investigated in the whole cohort, as well as categorized by age (<65 and ≥65 years). All risk prediction models are based on three parameters: WHO-FC (World Health Organization Function Class), NT-proBNP, and 6MWD (6-minute walk distance). Kaplan-Meier estimate/Log-Rank test and Cox proportional model were used for survival analyses. ResultsThe study included 411 patients (70% women) with a median [IQR] age of 66y.21 At 6M, the mean (SD) NT-proBNP decrease was 808 (603) and the mean 6MWD increase was 44 (11) meters. Median survival/follow-up time was 3.5y [1.7, 5.4]. After adjustment for sex and comorbidities, achievement of MCI independently predicted TF-survival; one MCI-criterion met (HR 0.65; CI 0.46-0.92, p=0.015); two MCI-criteria met (HR 0.45; CI 0.31-0.66, p<0.001); all three MCI-criteria met (HR 0.32; CI 0.21-0.52, p<0.001). Likewise, 4SR and FRS demonstrated a strong association with TF-survival with patients achieving lower risk scores exhibiting longer survival compared to those with higher risk scores. Patients ≥65Y more often had connective tissue disease-associated PAH, lower DLCO, more pronounced comorbidity burden, higher risk at baseline, less improvement during follow-up, and worse TF-survival then patients <65Y. ConclusionAll models were found to have prognostic relevance for TF-survival. Risk prediction was incremental with the number of low-risk criteria met, while improvements in only one of 6MWD, NT-proBNP, or FC showed a modest association with survival. The risk assessment tools predicted outcome in patients across both age categories.

LAMP5, One of Four Genes Related to Oxidative Stress That Predict Biochemical Recurrence-Free Survival, Promotes Proliferation and Invasion in Prostate Cancer.

Prostate cancer (PCa) development largely depends on increased levels of oxidative stress (OS) and a deficient anti-oxidative system. Identifying genes associated with oxidative stress is critical in order to direct PCa therapy and future research. The TCGA and GTEx databases provided the bulk RNA-seq data, andthe GEO database provided the single-celldata GSE141445. Utilizing reactive oxygen species (ROS) markers, single-cell analysis and cluster identification related to oxidative stress were conducted using the R packages "Seurat" and "AUCell". The differentially expressed genes (DEGs) in normal and PCa samples were identified with the "limma" R package. LASSO regression analysis was used to build a recurrence score (RS) model. The R packages "maftools" and the CIBERSORT method were employed to explore genetic mutation and the infiltrating immune cell, respectively. LAMP5 was chosen for further investigation after random forest analysis was performed. The RS model for PCa was found to be an independent predictor. The tumor immune microenvironment and the frequency of gene mutationsdiffered significantly between the high-and low-risk score groups. Further investigation revealed that downregulation of LAMP5 in PC-3 and DU145 cell lines suppressed cell proliferation and invasion, as demonstrated by the results of in vitro experiments. We successfully created a robust RS model. The result of the study indicates that LAMP5 could contribute to cell proliferation and invasion in PCa.

10-Year Atherosclerotic Cardiovascular Disease (ASCVD) Risk Score Calculation in Out-Patient Department

Objective: To calculate 10-year Atherosclerotic Cardiovascular Disease risk score in outdoor department of a tertiary care hospital and identify individuals at high risk of cardiovascular disease. Study Design: Cross-sectional study. Place and Duration of Study: Combined Military Hospital, Malir, Pakistan, from Oct 2020 to Mar 2021. Methodology: 116 patients presenting to Out-Patient Department of General Medicine of CMH, Malir, Pakistan, without previous evidence of cardiovascular disease were included. Previous history of diabetes, smoking, use of anti-hypertensives, Aspirin and statins was recorded. Systolic and diastolic blood pressures, waist circumference, HbA1c, fasting blood sugar, fasting LDL, HDL and total cholesterol were tested for each patient. 10-year ASCVD risk score was calculated using online ASCVD Risk Estimator calculator. Results: Mean age of the patients was 58.6±9.92 years with 62.1% being males and 37.9% being females. Mean 10-year ASCVD risk score was 13.37±7.1, of which 21 patients (18.1%) had Very High, 66(56.9%) had Intermediate and 29(25%) had Low 10-year ASCVD risk score. Among Very High cases, 80.9% were males, all were in age group 50-79 years, 61.9% were diabetic, 33.3% were smokers and 66.7% were obese. Conclusion: A very high percentage of study group had Intermediate or Very High 10-year ASCVD risk score. Identifying those individuals at high risk early and controlling the modifiable risk factors can help lessen the morbidity and mortality associated with cardiovascular diseases.

Development of a prognostic model for early-stage gastric cancer-related DNA methylation-driven genes and analysis of immune landscape.

This study aimed to develop a prognostic model based on DNA methylation-driven genes for patients with early-stage gastric cancer and to examine immune infiltration and function across varying risk levels. We analyzed data from stage I/II gastric cancer patients in The Cancer Genome Atlas which included clinical details, mRNA expression profiles, and level 3 DNA methylation array data. Using the empirical Bayes method of the limma package, we identified differentially expressed genes (DEGs), and the MethylMix package facilitated the identification of DNA methylation-driven genes (DMGs). Univariate Cox regression and LASSO (least absolute shrinkage and selector operation) analyses were utilized to pinpoint critical genes. A risk score prediction model was formulated using two genes that demonstrated the most significant hazard ratios (HRs). Model performance was evaluated within the initial cohort and verified in the GSE84437 cohort; a nomogram was also constructed based on these genes. We further examined 50 methylation sites associated with three CpG islands in C1orf35 and 14 methylation sites linked to one CpG island in FAAH. The CIBERSORT package was employed to identify immune cell clusters in the prediction model. A total of 176 DNA methylation-driven genes were refined down to a four-gene signature (ZC3H12A was hypermethylated; GATA3, C1orf35, and FAAH were hypomethylated), which exhibited a significant correlation with overall survival (OS), as evidenced by p-values below 0.05 following univariate Cox regression and LASSO analysis. Specifically, for the risk score prediction model, C1orf35, which had the highest hazard ratio (HR = 2.035, p = 0.028), and FAAH, with the lowest hazard ratio (HR = 0.656, p = 0.012), were selected. The Kaplan-Meier analysis demonstrated distinct survival outcomes between the high-risk and low-risk score groups. The model's predictive accuracy was confirmed with an area under the curve (AUC) of 0.611 for 3-year survival and 0.564 for 5-year survival. Notably, the hypomethylation of the three CpG islands in C1orf35 and the single CpG island in FAAH was significantly different in stage I/II gastric cancer patients compared to normal tissues. Additionally, the high-risk score group showed a notable association with resting CD4 memory T cells. Promoter hypomethylation of C1orf35 and FAAH in early-stage gastric cancer underscores their potential as biomarkers for accurate diagnosis and treatment. The developed predictive model employing genes affected by DNA methylation serves as a crucial independent prognostic factor in early-stage gastric cancer.

Association between CHA2DS2-VASc score and left atrial function by speckle tracking echocardiography in patients with sinus rhythm

Abstract Background The CHA2DS2-VASc score is a scoring system that was first used for the risk assessment of cerebrovascular or thromboembolic events in patients with atrial fibrillation (AF). The factors that constitute the CHA2DS2-VASc scoring system can all individually have an impact on LA function. The application of this scoring system can also be applied to patients without AF. The LA structural remodeling and/or functional impairment play a part in the pathogenesis and development of AF and independent of rhythm, may result in atrial hemostasis and confer a prothrombotic diathesis, resulting in thromboembolic stroke. Speckle- tracking echocardiography (STE) makes it possible to measure LA function with relatively high accuracy and at the very early stage even in the absence of LA enlargement. Purpose The aim of our study was to assess the left atrial function in patients with sinus rhythm with different CHA2DS2-VASc scores (low, moderate and high) by speckle tracking echocardiography and to identify the association between them. Methods This study was conducted using prospectively collected data (1st May, 2022 to 30th October 2022) from patients with sinus rhythm and different CHA2DS2-VASc scores (50 Low risk score patients (1 for females and 0 for males), 50 moderate risk score patients (2 for females and 1 for males) and 50 high risk score patients (≥3 for females and ≥2 for males) After obtaining an informed consent, all volunteers underwent thorough history taking, 12 lead ECG and conventional transthoracic echocardiography and speckle-tracking echocardiography. Results LA strain during the reservoir (LASr) and conduit phases (LAScd) were statistically significantly lower in the high-risk score group (33.2 ± 7.1 and 20.3 ± 5.7) than the moderate-risk score group (36.9 ± 6.1 and 23.5 ± 4.8, p = 0.005 and 0.003 respectively) and low -risk score group (40.6 ± 5.6 and 26.9 ± 3.9, p &amp;lt; 0.001). In addition, LASr and LAScd were statistically significantly lower in moderate- risk score group (36.9 ± 6.1 and 23.5 ± 4.8) than the low -risk score group (40.6 ± 5.6 and 26.9 ± 3.9 ,p=0.007 and 0.001 respectively). Conclusion Higher CHA2DS2-VASc scores were associated with decreased LA strain during the reservoir and conduit phases as markers of LA function with relatively high accuracy and at the very early stage even in the absence of LA enlargement.

High ABCD2-score after transient ischemic attack is associated with a two-fold higher stroke-rate during long-term follow-up

Abstract Background The ABCD2-score is a validated risk score used to estimate the short-term risk of stroke after transient ischemic attack (TIA). However, "real-world" contemporary data on the long-term risk of stroke after TIA according to ABCD2-score are needed in order to guide preventive strategies. Purpose To determine the long-term risk of stroke after TIA according to modified ABCD2-score (high-risk (≥4 points) versus low-risk (&amp;lt;4 points)). Methods Patients aged ≥18 years with first-time TIA were included from the Danish Stroke Registry (2014-2020). The study population was stratified in high-risk (≥4 points) and low-risk (&amp;lt;4 points) ABCD2-score group. We utilized a modified ABCD2-score consisting of the following parameters: age ≥60 years, hypertension, clinical features, and diabetes. The 3-year risk of ischemic stroke and all-cause mortality was compared between the high-risk and low-risk group using the Aalen-Johansen and Kaplan-Meier estimator. A cox regression model was also conducted. Results In total, 21,433 patients with first-time TIA were included; 1,281 (6.0%) in the high-risk and 20,152 (94.0%) in the low-risk group. Patients in the high-risk group were older (77.5 years [interquartile range [IQR] 70.8-84.1] versus 70.3 years [IQR 60.1-78.2]), more often females (52.2% versus 46.6%) (p &amp;lt;0.001), more comorbid and received more medication compared with the low-risk group at baseline. The 3-year cumulative incidence of stroke was 6.0% [95% CI: 4.6-7.5] in the high-risk group and 4.2% [95% CI: 3.9-4.5] in the low-risk group, and the unadjusted hazard ratio (HR) was 1.6 (95% CI 1.2 – 2.0) (Figure 1). The cumulative incidence of all-cause mortality within three-years after TIA was 28.9% [95% CI: 26.1-31.7] in the high-risk group and 10.3% [95% CI: 9.9-10.8] in the low-risk group. The unadjusted HR was 3.2 (95% CI 2.8 – 3.6). Conclusions Patients with high-risk ABCD2-scores had an almost two-fold higher associated long-term stroke-rate compared to those with low-risk scores. Trials focusing on preventive measures, including evidence-based antithrombotic strategies, especially for the high-risk group are warranted.