Potential Predictive Ability Research Articles

Exploring a specialized programmed-cell death patterns to predict the prognosis and sensitivity of immunotherapy in cutaneous melanoma via machine learning.

The mortality and therapeutic failure in cutaneous melanoma (CM) are mainly caused by wide metastasis and chemotherapy resistance. Meanwhile, immunotherapy is considered a crucial therapy strategy for CM patients. However, the efficiency of currently available methods and biomarkers in predicting the response of immunotherapy and prognosis of CM is limited. Programmed cell death (PCD) plays a significant role in the occurrence, development, and therapy of various malignant tumors. In this research, we integrated fourteen types of PCD, multi-omics data from TCGA-SKCM and other cohorts in GEO, and clinical CM patients to develop our analysis. Based on significant PCD patterns, two PCD-related CM clusters with different prognosis, tumor microenvironment (TME), and response to immunotherapy were identified. Subsequently, seven PCD-related features, especially CD28, CYP1B1, JAK3, LAMP3, SFN, STAT4, and TRAF1, were utilized to establish the prognostic signature, namely cell death index (CDI). CDI accurately predicted the response to immunotherapy in both CM and other cancers. A nomogram with potential superior predictive ability was constructed, and potential drugs targeting CM patients with specific CDI have also been identified. Given all the above, a novel CDI gene signature was indicated to predict the prognosis and exploit precision therapeutic strategies of CM patients, providing unique opportunities for clinical intelligence and new management methods for the therapy of CM.

Baseline Circulating Blood Cell Counts and Ratios and Changes Therein for Predicting Immune-Related Adverse Events during Immune Checkpoint Inhibitor Therapy: A Multicenter, Prospective, Observational, Pan-Cancer Cohort Study with a Gender Perspective.

Several factors have been associated with the occurrence of immune-related adverse events (irAEs) induced by immune checkpoint inhibitor (ICI) therapy. Despite their availability, the predictive value of circulating blood cell parameters remains underexplored. Our aim was to investigate whether baseline values of and early changes in absolute neutrophil count (ANC), absolute lymphocyte count (ALC), other blood cell counts, and lymphocyte-related ratios can predict irAEs and whether sex may differentially influence this potential predictive ability. Of the 145 patients included, 52 patients (35.8%) experienced at least one irAE, with a 1-year cumulative incidence of 41.6%. Using Fine and Gray competing risk models, we identified female sex (hazard ratio (HR) = 2.17, 95% confidence interval (CI) = 1.20-3.85), high ALC before ICI initiation (HR = 1.63, 95% CI = 1.09-2.45), and low ANC after ICI initiation (HR = 0.81, 95% CI = 0.69-0.96) as predictors of irAEs. However, ALC and ANC may only have an impact on the risk of irAEs in women (stratified for female sex, ALC-related HR = 2.61, 95% CI = 1.40-4.86 and ANC-related HR = 0.57, 95% CI = 0.41-0.81). Priority should be given to developing models to predict ICI-related toxicity and their validation in various settings, and such models should assess the impact of patient sex on the risk of toxicity.

Maternal Iron Status Is Dynamic Throughout Pregnancy and Might Predict Birth Outcomes in a Sex Dependent Manner: Results from the Alberta Pregnancy Outcomes and Nutrition (APrON) Cohort Study

BackgroundDevelopmental responses to nutrient deprivation may differ by fetal sex. Despite this, relationships between maternal prenatal iron biomarkers and birth outcomes when stratifying by offspring sex are poorly described, especially in healthy cohorts. ObjectivesThis study aimed to determine associations between maternal iron biomarkers and birth weights (BWs) and birth head circumferences (BHCs) among female and male newborns to assess whether the potential predictive ability of iron biomarkers on birth outcomes differs by offspring sex. MethodsThe Alberta Pregnancy Outcomes and Nutrition (APrON) cohort study recruited 2189 pregnant individuals from Calgary and Edmonton, Canada. Maternal blood was drawn at each trimester and 3 mo postpartum. Maternal serum ferritin (SF) concentrations were measured using chemiluminescent immunoassays and erythropoietin (EPO), hepcidin, and soluble transferrin receptor (sTfR) using enzyme-linked immunosorbent assays. Ratios of sTfR:SF and hepcidin:EPO were calculated and birth outcomes accessed through delivery records. Directed acyclic graphs informed multivariate regression models. ResultsThe risk of maternal iron deficiency increased throughout pregnancy because ∼61% showed depleted iron stores (SF < 15 μg/L) by the third trimester. Maternal hepcidin, SF, sTfR, and sTfR:SF concentrations changed across time (P < 0.01), and participants carrying female fetuses consistently (across 6 biomarkers) showed a lower iron status during the third trimester compared with those with male fetuses (P < 0.05). Higher maternal SF and hepcidin:EPO during the third trimester was associated with lower BWs in males (P = 0.006 for SF; P = 0.03 for hepcidin:EPO) and females (P = 0.02 for SF; P = 0.02 for hepcidin:EPO). There were additional inverse associations between BWs and third trimester maternal hepcidin (P = 0.03) and hemoglobin (P = 0.004) and between BHCs and maternal SF (second trimester; P < 0.05) and Hb (third trimester P = 0.02) but only in males. ConclusionsRelationships between maternal iron biomarkers and BWs and BHCs may depend on the timing of pregnancy and offpsring sex. There was a high risk of third trimester iron storage depletion among generally healthy pregnant individuals.

Peripheral blood mononuclear cell- transcriptome signatures of atopic dermatitis and prediction for the efficacy of dupilumab

BackgroundFew studies have explored transcriptome of the peripheral blood mononuclear cells (PBMCs) of atopic dermatitis (AD). Parameters for prediction of the efficacy of dupilumab in AD remain obscure. ObjectiveTo explore transcriptome signature of the PBMCs from Chinese AD patients and the usage in predication for the efficacy of dupilumab. MethodsA total of 56 moderate-to-severe adult AD patients were enrolled and followed up for 16 week-dupilumab treatment. PBMCs samples were collected at baseline and 16 weeks after dupilumab treatment. Thirty-five patients were subjected to RNA-sequencing. Weighted gene co-expression network analysis (WGCNA) was used to find genes for prediction of dupilumab efficacy, which was validated in the rest 21 AD patients. Another 30 healthy individuals were enrolled and subjected to RNA-sequencing as healthy controls. ResultsUpregulation of the T helper (Th) 2/Th22 pathway, Th17 antimicrobial genes, and natural T-regulatory cell abundance in the PBMCs of AD cases was observed, whereas TGF-β signaling and NK-cell signaling were decreased. Dupilumab treatment reversed the increase in the expression of Th2 cytokine receptors. WGCNA identified two immune-related modules that were correlated significantly with the efficacy of dupilumab. Hub gene MAP2K3 and UBE2L3 of these two modules demonstrated potential predictive ability for efficacy in the RNA-sequencing group by Spearman correlation, ROC analysis, and regression analysis, which was further validated in additional 21 AD cases. ConclusionWe firstly revealed the molecular phenotype of PBMCs in Chinese patients with AD, and uncovered two molecules that might be useful for prediction of the efficacy of dupilumab.

A pilot study investigating early postmortem interval of rats based on ambient temperature and postmortem interval-related metabolites in blood.

Estimation of the postmortem interval (PMI), especially the early PMI, plays a key role in forensic practice. Although several studies based on metabolomics approaches have presented significant findings for PMI estimation, most did not examine the effects of ambient temperature. In this study, gas chromatography-mass spectrometry (GC‒MS)‒based metabolomics was adopted to explore the changes in metabolites in the cardiac blood of suffocated rats at various ambient temperatures (5°C, 15°C, 25°C, and 35°C) from 0 to 24h after death. Isoleucine, alanine, proline, valine, glycerol, glycerol phosphate, xanthine, and hypoxanthine were found to contribute to PMI in all temperature groups. Hypoxanthine and isoleucine were chosen to establish estimation models (equations) with an interpolation function using PMI as the dependent variable (f(x, y)), relative intensity as the independent variable x, and temperature as the independent variable y. Thereafter, these two models were validated with predictive samples and shown to have potential predictive ability. The findings indicate that isoleucine, alanine, proline, valine, glycerol, glycerol phosphate, xanthine, and hypoxanthine may be significant for PMI estimation at various ambient temperatures. Furthermore, a method to determine PMI based on ambient temperature and PMI-related metabolites was explored, which may provide a basis for future studies and practical applications.

Preoperative frailty assessment could be a predictive factor for the prognosis of elderly patients undergoing coronary artery bypass grafting: a retrospective case-control study

BackgroundFrailty has been considered to be associated with major mortality and increased length of stay after cardiac surgery. This study aimed to explore the predictive potential of frailty assessment in the prognosis of elderly patients undergoing bypass surgery.MethodsThis study assessed the preoperative frailty according to the Fried’s frailty phenotype, and included 150 frail and 150 non-frail elderly patients (≥ 65 y) who underwent bypass surgery. The present study evaluated the prognosis of elderly patients based on sequential organ failure assessment (SOFA) score, and collected clinical indicators to construct logistic regression models with the prognosis as the dependent variable, to explore the potential predictive ability of preoperative frailty. Moreover, this study focused on the complications and analyzed the relationship between preoperative frailty and postoperative complications.ResultsIn the present study, 244 patients were divided into the favorable prognosis group and 56 patients were divided into the unfavorable prognosis group. Logistic regression analysis showed that increased myoglobin and high cardiac function classification were independent risk factors for unfavorable prognosis in elderly patients undergoing bypass surgery. The discrimination of the clinical prediction model was determined by the receiver operating characteristic (ROC) curve, and the area under curve (AUC) was 0.928. After adding preoperative frailty assessment, the AUC was improved to 0.939. This study found a significant correlation between preoperative frailty and postoperative complications, mainly in the circulatory system.ConclusionPreoperative frailty assessment could be a predictive factor for the prognosis of elderly patients undergoing coronary artery bypass grafting. According to our study, frailty assessment and appropriate intervention before bypass surgery may be beneficial to the enhanced recovery after cardiac surgery.Trial registrationThe clinical study was approved by the Medical Ethics Committee of The First Affiliated Hospital of Nanjing Medical University (2021-SR-393). All patients signed an informed consent form.

Association of cerebrospinal fluid CD4+/CD8+Ratio with 60-day functional outcome after intracerebral hemorrhage.

Background: The immune inflammatory reaction has vital function in pathologic mechanism of critical intracerebral hemorrhage. It recently has been reported that CD4/CD8 ratio may represent a novel composite immune inflammatory marker to predict prognosis of critical intracerebral hemorrhage (ICH). Nevertheless, as for considering the effects of surgical evacuation upon initiation of immune inflammatory reactions, the association between cerebrospinal fluid (CSF) CD4/CD8 ratio and 60-day functional outcome of patients with critical ICH after surgery has not been investigated. Present study aimed to evaluate the predictive value concerning postoperative complement system and immunoglobulin, paired cerebrospinal fluid and peripheral blood lymphocyte subsets, as well as inflammation index before and after the operations upon the 60-day prognosis of patients with ICH.Methods: In total, 69 patients with acute critical ICH admitted in First Central Hospital of Baoding City from January to July in 2022 were prospectively enrolled. We recorded and analyzed the relevant clinical data. Laboratory parameters included postoperative lymphocyte subsets in paired cerebrospinal fluid and peripheral blood, inflammation index before and after operation. The associations between 60-day outcome and laboratory biomarkers were assessed by multivariable logistic regression analysis. Comparisons of predictive value regarding independent predictors was evaluated by receiver operating characteristic (ROC) curves.Results: In total, 51 patients with critical ICH exhibited poor outcomes at 60days, which was associated with fever after surgery, hernia before surgery, SAH and lower Glasgow Coma Scale (GCS) at admission and large hematoma volume, greater CD3T%CSF, greater CD4T%CSF, and greater CD4/CD8 ratioCSF. CD4/CD8ratio CSF showcased significant predictive power by comparing with other laboratorial variables (AUC = 0.6808; cut-off = 1.61; sensitivity = 80.39%; specificity = 61.11%; 95% CI: 0.5232-0.8385; p = .0233), which was found to correlated linearly with postoperative fever, first CSF test time, CD3T% CSF, CD4T% CSF, CD8T% CSF, NKCSF, CD3T%PB, CD8T%PB, CD4/CD8 ratioPB, and glucoseCSF. Poor outcome at 60days linearly correlated with CD4/CD8ratioCSF after adjustments. In 3-5days after surgery tested CSF lymphocyte subsets, CD4/CD8ratioCSF ≥1.61 was associated with a higher risk for 60-day poor outcome comparing with corresponding subgroups.Conclusions: In association of critical ICH patient prognosis, CSF CD4/CD8 ratio, especially in 3-5days after surgery, exhibited potential independent predictive ability for 60-day functional outcomes of patients with critical ICH.

Risk Factors of Sudden Cardiac Arrest during the Postoperative Period in Patient Undergoing Heart Valve Surgery

Sudden cardiac arrest (SCA) is the sudden cessation of normal cardiac activity with hemodynamic collapse. This usually leads to sudden cardiac death (SCD) when cardiopulmonary resuscitation is not undertaken. In patients undergoing heart valve surgery, postoperative SCA is a complication with a high risk of death, cerebral hypoxia and multiple organ dysfunction syndrome (MODS). Therefore, knowledge of the predictors of postoperative SCA is extremely important as it enables the identification of patients at risk of this complication and the application of the special surveillance and therapeutic management in this group of patients. The aim of the study was to evaluate the usefulness of selected biomarkers in predicting postoperative SCA in patients undergoing heart valve surgery. This prospective study was conducted on a group of 616 consecutive patients with significant valvular heart disease that underwent elective valve surgery with or without coronary artery bypass surgery. The primary end-point at the intra-hospital follow-up was postoperative SCA. The secondary end-point was death from all causes in patients with postoperative SCA. Patients were observed until discharge from the hospital or until death. Logistic regression was used to assess the relationships between variables. The postoperative SCA occurred in 14 patients. At multivariate analysis, only NT-proBNP (odds ratio (OR) 1.022, 95% confidence interval (CI) 1.012-1.044; p = 0.03) remained independent predictors of the primary end-point. Age and NT-proBNP were associated with an increased risk of death in patients with postoperative SCA. The results of the presented study indicate that SCA in the early postoperative period in patients undergoing heart valve surgery is an unpredictable event with high mortality. The potential predictive ability of the preoperative NT-proBNP level for the occurrence of postoperative SCA and death in patients after SCA demonstrated in the study may indicate that the overloaded and damaged myocardium in patients undergoing heart valve surgery is particularly sensitive to non-physiological conditions prevailing in the perioperative period, which may cause serious hemodynamic disturbances in the postoperative period and lead to death.

Ophthalmic artery changes in type 2 diabetes with and without acute coronary syndrome

BackgroundOcular blood flow provides a new perspective for studying the effects of diabetes and ischemic heart disease on systemic blood flow, pathological mechanisms, and prognosis. Previous studies have analyzed the hemodynamic changes of the ophthalmic artery (OA) in patients with diabetes and ischemic heart disease, but the results remain controversial due to limited observation methods. We aimed to explore the morphological and hemodynamic features in the OA in patients with type 2 diabetes (T2D) with and without acute coronary syndrome (ACS).MethodsIn total, 134 participants, including 30 control participants, 34 with ACS only, 34 with T2D only, and 36 with both ACS and T2D, undergoing computed tomography angiography were enrolled. Three-dimensional OA models were reconstructed, and morphological parameters of the OA were measured. In addition, numerical simulations using computational fluid dynamics were used to acquire hemodynamic parameters of the OA.ResultsIn this study, 134 OA models were reconstructed. Morphological measurements revealed a smaller initial OA diameter in the T2D group than in the other two ACS groups. A hemodynamic simulation showed a significantly lower OA blood velocity in patients with ACS and T2D than that in controls (P < 0.001). The mass flow ratios in all disease groups were lower than those in the control group (P < 0.001, P = 0.020, and P < 0.001, respectively). The ACS and T2D groups had higher OA pressure levels than those of the control group (P = 0.013). The OA blood velocity and mass flow ratio were correlated with several clinical parameters.ConclusionsThis study revealed morphological and hemodynamic differences in the OA between patients with T2D with and without ACS. Furthermore, the hemodynamic characteristics of the OA correlated with clinical prognostic biomarkers, suggesting the potential predictive ability of the OA.

Do Routine Laboratory Parameters have Predictive Ability to Differentiate Subjects with Fibromyalgia from Healthy Subjects?

The aim of this study was to evaluate laboratory parameters for investigating their potential predictive ability to differentiate patients with fibromyalgia (FM) from healthy subjects. We carried out a case-control study with 79 FM patients and 20 controls to analyze complete blood count, serum chemistry profile, glycosylated hemoglobin (HbA1c), and erythrocyte sedimentation rate (ESR). The predictive value of these parameters was determined by receiver operating characteristic (ROC) analysis. We also examined the relationships with clinical parameters (functional capacity, pain, and physical and mental health status). Results showed significant differences in red blood cell count, hematocrit, mean corpuscular hemoglobin concentration, platelet count, creatinine, HbA1c, and ESR between groups. According to ROC analysis, all these parameters may assist in making FM diagnosis. Hematocrit and ESR values were correlated with FM clinical parameters. The determination of these routine laboratory parameters may be an uncomplicated means of facilitating FM diagnosis, together with the clinical data of the patient.

EP16.01-022 A Signature of B Cells-Related Gene Pairs Predicts Oncologic Outcomes and Response to Immunotherapy in NSCLC Patients

Tumor-infiltrating B cells accompanying several widely used B cell-related biomarkers, such as CD19 and CD20, have inconsistent clinical prognostic values in non-small-cell lung cancer (NSCLC) patients. Considering only one B cell-related biomarker could not distinguish the anti-tumor and pro-tumor B cell subsets in tumor, we aimed to construct a more accurate B-cells related gene pairs (BRGPs) prognostic model and evaluate its potential predictive ability to immunotherapy in NSCLC patients.

Validation and derivation of short-term prognostic risk score in acute decompensated heart failure in China

BackgroundFew prognostic risk scores (PRSs) have been routinely used in acute decompensated heart failure (ADHF). We, therefore, externally validated three published PRSs (3A3B, AHEAD, and OPTIME-CHF) and derived a new PRS to predict the short-term prognosis in ADHF.MethodsA total of 4550 patients from the Heb-ADHF registry in China were randomly divided into the derivation and validation cohorts (3:2). Discrimination of each PRS was assessed by the area under the receiver operating characteristic curve (AUROC). Logistic regression was exploited to select the predictors and create the new PRS. The Hosmer–Lemeshow goodness-of-fit test was used to assess the calibration of the new PRS.ResultsThe AUROCs of the 3A3B, AHEAD, and OPTIME-CHF score in the derivation cohort were 0.55 (95% CI 0.53–0.57), 0.54 (95% CI 0.53–0.56), and 0.56 (95% CI 0.54–0.57), respectively. After logistic regression analysis, the new PRS computed as 1 × (diastolic blood pressure < 80 mmHg) + 2 × (lymphocyte > 1.11 × 109/L) + 1 × (creatinine > 80 μmol/L) + 2 × (blood urea nitrogen > 21 mg/dL) + 1 × [BNP 500 to < 1500 pg/mL (NT-proBNP 2500 to < 7500 pg/mL)] or 3 × [BNP ≥ 1500 (NT-proBNP ≥ 7500) pg/mL] + 3 × (QRS fraction of electrocardiogram < 55%) + 4 × (ACEI/ARB not used) + 1 × (rhBNP used), with a better AUROC of 0.67 (95% CI 0.64–0.70) and a good calibration (Hosmer–Lemeshow χ2 = 3.366, P = 0.186). The results in validation cohort verified these findings.ConclusionsThe short-term prognostic values of 3A3B, AHEAD, and OPTIME-CHF score in ADHF patients were all poor, while the new PRS exhibited potential predictive ability. We demonstrated the QRS fraction of electrocardiogram as a novel predictor for the short-term outcomes of ADHF for the first time. Our findings might help to recognize high-risk ADHF patients.

Utility of China-PAR stroke equations for predicting 10-year stroke risk in the rural Inner Mongolian population in China

ABSTRACT Background The aim of this study is to investigate the capability using the China-PAR stroke equations for predicting 10-year risk of stroke among the Inner Mongolian population in China. Methods A prospective cohort study was conducted among 2535 rural Inner Mongolian residents from June 2002 to July 2012. Participants were categorized into four subgroups according to their 10-year predicted stroke risks calculated using the China-PAR stroke equations: <5%, 5–9.9%, 10–19.9%, and ≥20%. Results The C-statistic of the China-PAR stroke equations for 10-year stroke was 0.58, and the result from Hosmer–Lemeshow ‘goodness-of-fit’ test showed that the China-PAR stroke equations fitted the Inner Mongolian women well (χ2 = 11.18, P = 0.192). The adjusted hazard ratios of stroke were 3.86 (95% CI: 1.12–13.29) for 5–9.9% category, 10.37 (95% CI: 2.70–39.84) for 10–19.9% category, and 17.00 (95% CI: 3.54–81.63) for ≥20% category among Inner Mongolian women using the <5% category as reference (P for trend <0.001). However, the China-PAR stroke equations underestimated the 10-year stroke risk in Inner Mongolian men, and the calibration was unsatisfactory (χ 2 = 15.82, P = 0.045). Conclusion The China-PAR stroke equations have potential predictive ability for 10-year stroke risk in the rural Inner Mongolian women, while it might not suit the rural Inner Mongolian men well. The performance of China-PAR stroke equations in other ethnic groups in China will need to be further evaluated.

Signature based on B cells-related gene pairs could predict prognosis and immunotherapeutic response in NSCLC.

e21051 Background: Tumor-infiltrating B cells accompanying several widely used B cell-related biomarkers, such as CD19 and CD20, have inconsistent clinical prognostic values in non-small-cell lung cancer (NSCLC) patients. Considering only one B cell-related biomarker could not distinguish the anti-tumor and pro-tumor B cell subsets in tumor, we aimed to construct a more accurate B-cells related gene pairs (BRGPs) prognostic model and evaluate its potential predictive ability to immunotherapy in NSCLC patients. Methods: Using public single-cell RNA sequencing data, the B cells-related genes (BRGs) in NSCLC samples were identified. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were utilized to construct the BRGPs model which was not affected by the technical bias of different platforms. With no dependence upon specific gene expression levels, a novel signature based on BRGPs was established in this study. In addition, the prognostic value and immunotherapeutic response for this signature with regard to the TME components and potential molecular mechanism were explored. Results: Based on the TCGA database, we built a novel prognostic signature of 23 BRGPs comprising 28 unique BRGs. This risk model showed significant power in distinguishing good or poor prognosis and could serve as an independent prognostic factor for NSCLC patients in the TCGA cohort. The prognostic accuracy of the model was further verified in the GSE31210 dataset from the GEO database. Likewise, the prognostic value of the risk score for the BRGPs model was demonstrated in the GEO cohorts by the univariate and multivariate cox regression analysis. In addition, the risk model was significantly associated with sex, TNM stage, immune score, tumor purity and various tumor-infiltrating immune cells. GSEA analysis indicated that low-risk group enriched with several immune-related pathways, such as activation of immune response, antigen receptor mediated signaling pathway, B cell activation and B cell mediated immunity, whereas several proliferation-related pathways, such as nuclear chromosome segregation, sister chromatid segregation and mitotic sister chromatid segregation were most enriched in high-risk group. Besides, the tumor mutational burden (TMB) score rather than CD274(PD-L1 mRNA) expression was positively correlated with the risk score (P＜0.001; P = 0.94, respectively). NSCLC patients with high-risk exhibited significantly higher TMB score compared with low-risk patients (P &lt; 0.001). Correspondingly, we demonstrated that immune checkpoint blockade therapy may be more efficacious in high-risk group NSCLC patients according to TIDE method (P＜0.01). Conclusions: This novel BRGPs model can assess the prognosis of patients with NSCLC, and may be helpful to guide immune checkpoint inhibitors treatment in our clinical practice.

Integrated Bioinformatics Algorithms and Experimental Validation to Explore Robust Biomarkers and Landscape of Immune Cell Infiltration in Dilated Cardiomyopathy.

BackgroundThe etiology of dilated cardiomyopathy (DCM) is unclear. Bioinformatics algorithms may help to explore the underlying mechanisms. Therefore, we aimed to screen diagnostic biomarkers and identify the landscape of immune infiltration in DCM.MethodsFirst, the CIBERSORT algorithm was used to excavate the proportion of immune-infiltration cells in DCM and normal myocardial tissues. Meanwhile, the Pearson analysis and principal component analysis (PCA) were used to identify immune heterogeneity in different tissues. The Wilcoxon test, LASSO regression, and machine learning method were conducted to identify the hub immune cells. In addition, the differentially expressed genes (DEGs) were screened by the limma package, and DEGs were analyzed for functional enrichment. In the protein–protein interaction (PPI) network, multiple algorithms were used to calculate the score of each DEG for screening the hub genes. Subsequently, external datasets were used to further validate the expression of hub genes, and the receiver operating characteristic (ROC) curve was used to analyze the diagnostic efficacy. Finally, we examined the expression of hub biomarkers in animal models.ResultsA total of 108 DEGs were screened, and these genes may be related to biological processes such as cytolysis, positive regulation of cytokine secretion, etc. Two types of hub immune cells [activated natural killer (NK) cells and eosinophils] and four hub genes (ASPN, CD163, IL10, and LUM) were identified in DCM myocardial tissues. CD163 was verified to have the capability to diagnose DCM with the most excellent specificity and sensitivity. It is worth mentioning that the combined CD163 and eosinophils may have better diagnostic efficacy. Moreover, the correlation analysis showed CD163 was negatively correlated with activated NK cells. Finally, the results of the mice model also indicated that CD163 might be involved in the occurrence of DCM.ConclusionASPN, CD163, IL10, and LUM may have a potential predictive ability for DCM, and especially CD163 showed the most robust efficacy. Furthermore, activated NK cells and eosinophils may relate to the occurrence of DCM.

Health Technology Assessment to assess value of biomarkers in the decision-making process.

Clinical practice guidelines (CPGs) on screening, surveillance, and treatment of several diseases recommend the selective use of biomarkers with central role in clinical decision-making and move towards including patients in this process. To this aim we will clarify the multidisciplinary interactions required to properly measure the cost-effectiveness of biomarkers with regard to the risk-benefit of the patients and how Health Technology Assessment (HTA) approach may assess value of biomarkers integrated within the decision-making process. HTA through the interaction of different skills provides high-quality research information on the effectiveness, costs, and impact of health technologies, including biomarkers. The biostatistical methodology is relevant to HTA but only meta-analysis is covered in depth, whereas proper approaches are needed to estimate the benefit-risk balance ratio. Several biomarkers underwent HTA evaluation and the final reports have pragmatically addressed: 1) a redesign of the screening based on biomarker; 2) a de-implementation/replacement of the test in clinical practice; 3) a selection of biomarkers with potential predictive ability and prognostic value; and 4) a stronger monitoring of the appropriateness of test request. The COVID-19 pandemic has disclosed the need to create a robust and sustainable system to urgently deal with global health concerns and the HTA methodology enables rapid cost-effective implementation of diagnostic tests allowing healthcare providers to make critical patient-management decisions.

Prediction of immunotherapy efficacy and immunomodulatory role of hypoxia in colorectal cancer.

Immunotherapy has been used in the clinical treatment of colorectal cancer (CRC); however, most patients fail to achieve satisfactory survival benefits. Biomarkers with high specificity and sensitivity are being increasingly developed to predict the efficacy of CRC immunotherapy. In addition to DNA alteration markers, such as microsatellite instability/mismatch repair and tumor mutational burden, immune cell infiltration and immune checkpoints (ICs), epigenetic changes and no-coding RNA, and gut microbiomes all show potential predictive ability. Recently, the hypoxic tumor microenvironment (TME) has been identified as a key factor mediating CRC immune evasion and resistance to treatment. Hypoxia-inducible factor-1α is the central transcription factor in the hypoxia response that drives the expression of a vast number of survival genes by binding to the hypoxia response element in cancer and immune cells in the TME. Hypoxia regulates angiogenesis, immune cell infiltration and activation, expression of ICs, and secretion of various immune molecules in the TME and is closely associated with the immunotherapeutic efficacy of CRC. Currently, various agents targeting hypoxia have been found to improve the TME and enhance the efficacy of immunotherapy. We reviewed current markers commonly used in CRC to predict therapeutic efficacy and the mechanisms underlying hypoxia-induced angiogenesis and tumor immune evasion. Exploring the mechanisms by which hypoxia affects the TME will assist the discovery of new immunotherapeutic predictive biomarkers and development of more effective combinations of agents targeting hypoxia and immunotherapy.

The Impact of m1A Methylation Modification Patterns on Tumor Immune Microenvironment and Prognosis in Oral Squamous Cell Carcinoma.

N1-methyladenosine (m1A) modification widely participates in the occurrence and progression of numerous diseases. Nevertheless, the potential roles of m1A in the tumor immune microenvironment (TIME) are still not fully understood. Based on 10 m1A methylation regulators, we comprehensively explored the m1A modification patterns in 502 patients with oral squamous cell carcinoma (OSCC). The m1A modification patterns were correlated with TIME characteristics and the m1A score was established to evaluate the effect of the m1A modification patterns on individual OSCC patients. The TIME characteristics and survival outcomes under the three m1A modification patterns were significantly distinct. OSCC patients in the high m1A score group were characterized by poorer prognosis, lower immune infiltration, lower ssGSEA score, lower expression levels of immune checkpoint molecules, and higher tumor mutation loads. The present study revealed that m1A modification might be associated with the TIME in OSCC, and has potential predictive ability for the prognosis of OSCC.

An IMERG-Based Optimal Extended Probabilistic Climatology (EPC) as a Benchmark Ensemble Forecast for Precipitation in the Tropics and Subtropics

AbstractCurrent numerical weather prediction models show limited skill in predicting low-latitude precipitation. To aid future improvements, be it with better dynamical or statistical models, we propose a well-defined benchmark forecast. We use the arguably best currently high-resolution, gauge-calibrated, gridded precipitation product, the Integrated Multi-Satellite Retrievals for GPM (Global Precipitation Measurement) (IMERG) “final run” in a ± 15-day window around the date of interest to build an empirical climatological ensemble forecast. This window size is an optimal compromise between statistical robustness and flexibility to represent seasonal changes. We refer to this benchmark as Extended Probabilistic Climatology (EPC) and compute it on a 0.1°×0.1° grid for 40°S–40°N and the period 2001–2019. In order to reduce and standardize information, a mixed Bernoulli-Gamma distribution is fitted to the empirical EPC, which hardly affects predictive performance. The EPC is then compared to 1-day ensemble predictions from the European Centre for Medium-Range Weather Forecasts (ECMWF) using standard verification scores. With respect to rainfall amount, ECMWF performs only slightly better than EPS over most of the low latitudes and worse over high-mountain and dry oceanic areas as well as over tropical Africa, where the lack of skill is also evident in independent station data. For rainfall occurrence, EPC is superior over most oceanic, coastal, and mountain regions, although the better potential predictive ability of ECMWF indicates that this is mostly due to calibration problems. To encourage the use of the new benchmark, we provide the data, scripts, and an interactive webtool to the scientific community.

Dysregulation of miR-637 serves as a diagnostic biomarker in patients with carotid artery stenosis and predicts the occurrence of the cerebral ischemic event

ABSTRACT The present research aims to explore the relationship between circulating microRNA and carotid artery stenosis (CAS). To evaluate the diagnostic significance of miR-637 in CAS patients and its potential predictive value for cerebral ischemia events through clinical studies. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to verify the differences in serum miR-637 between enrolled 97 CAS patients and 90 healthy individuals. Logistic regression analysis of the correlation between the level of miR-637 and the degree of carotid artery stenosis. The receiver operating characteristic (ROC) curve evaluated the diagnostic significance of miR-637 in identifying CAS patients from healthy individuals. Kaplan-Meier survival and Cox regression were used to evaluate the potential predictive ability of serum miR-637 levels during follow-up for cerebral ischemia events. Serum miR-637 of CAS patients was significantly reduced which was a good indicator of severe carotid stenosis (P < 0.001). Reduced miR-637 can identify CAS patients from healthy individuals, demonstrating strong diagnostic capabilities. Furthermore, Kaplan-Meier analysis confirmed that the lower miR-637 levels in CAS, the more cerebral ischemia events (log-rank, P = 0.035), and the Multivariate Cox regressions confirmed that miR-637 was an independent predictor of CAS patients (HR = 0.073, 95%CI = 0.017–0.313, P < 0.001). We confirmed that serum miR-637 in CAS patients was significantly reduced. And reduced miR-637 was not only a potentially reliable biomarker for the diagnosis of CAS but also a useful indicator for predicting future cerebral ischemic events.