Clinical Prognostic Risk Research Articles

The clinical prognostic risk stratification system for HIV infected hepatocellular carcinoma

BackgroundPatients with human immunodeficiency virus (HIV) are more susceptible to liver cancer because of their compromised immune system. There is no specific prognostic model for HIV-infected hepatocellular carcinoma (HCC) patients. MethodsClinical data of 85 patients with HIV-infected HCC was divided into a 7:3 ratio for training and internal validation sets, while the data of 23 patients with HIV-infected HCC was served as the external validation set. Data of 275 HIV-negative HCC patients was considered as external HIV-negative validation set. Variables associated with overall survival (OS) in the training set were used to develop the HIV-infected HCC prognosis (HIHP) model. The model was tested in the internal and external validation sets. The predictive accuracy of the model was assessed with conventional HIV-negative HCC prognostic scoring systems. ResultsIn the training set, variables independently associated with OS in multivariable analysis were organ involvement and tumor number. The HIHP model demonstrated a significant association with OS in the training set, with a median OS of 13 months for low risk, 7 months for medium risk, and 3 months for high risk (p < 0.001). The HIHP model showed a significant association with OS, and exhibited greater discriminative abilities compared to conventional HIV-negative HCC prognostic models both in the internal and external validation sets. In the external HIV-negative validation set, the HIHP model did not show better discrimination than conventional HIV-negative HCC scores. ConclusionThe new model presented in the work provided a more accurate prognostic prediction of OS in HIV-infected HCC patients. However, the model is not applicable to patients with HIV-negative HCC.

Pulmonary function test-related prognostic models in non-small cell lung cancer patients receiving neoadjuvant chemoimmunotherapy.

This study aimed to establish a comprehensive clinical prognostic risk model based on pulmonary function tests. This model was intended to guide the evaluation and predictive management of patients with resectable stage I-III non-small cell lung cancer (NSCLC) receiving neoadjuvant chemoimmunotherapy. Clinical pathological characteristics and prognostic survival data for 175 patients were collected. Univariate and multivariate Cox regression analyses, and least absolute shrinkage and selection operator (LASSO) regression analysis were employed to identify variables and construct corresponding models. These variables were integrated to develop a ridge regression model. The models' discrimination and calibration were evaluated, and the optimal model was chosen following internal validation. Comparative analyses between the risk scores or groups of the optimal model and clinical factors were conducted to explore the potential clinical application value. Univariate regression analysis identified smoking, complete pathologic response (CPR), and major pathologic response (MPR) as protective factors. Conversely, T staging, D-dimer/white blood cell ratio (DWBCR), D-dimer/fibrinogen ratio (DFR), and D-dimer/minute ventilation volume actual ratio (DMVAR) emerged as risk factors. Evaluation of the models confirmed their capability to accurately predict patient prognosis, exhibiting ideal discrimination and calibration, with the ridge regression model being optimal. Survival analysis demonstrated that the disease-free survival (DFS) in the high-risk group (HRG) was significantly shorter than in the low-risk group (LRG) (P=2.57×10-13). The time-dependent receiver operating characteristic (ROC) curve indicated that the area under the curve (AUC) values at 1 year, 2 years, and 3 years were 0.74, 0.81, and 0.79, respectively. Clinical correlation analysis revealed that men with lung squamous cell carcinoma or comorbid chronic obstructive pulmonary disease (COPD) were predominantly in the LRG, suggesting a better prognosis and potentially identifying a beneficiary population for this treatment combination. The prognostic model developed in this study effectively predicts the prognosis of patients with NSCLC receiving neoadjuvant chemoimmunotherapy. It offers valuable predictive insights for clinicians, aiding in developing treatment plans and monitoring disease progression.

High Serum ST2 Level Predicts Progression and Poor Prognosis of Denovomyelodysplastic Syndrome

Background: Myelodysplastic syndromes (MDS) are heterogeneous hematological stem cell malignancies with a complex pathophysiology involving immune, genetic, and epigenetic changes induced by aging, oxidative stress, and genotoxicity. Dysregulated immune responses and aberrant inflammatory signaling have been identified as critical drivers of MDS development. Recent research has highlighted the significant association of the IL-33/ST2 signaling axis with tumorigenicity and tumor immunity in various cancers. Soluble ST2 (sST2), a transmembrane-free receptor induced by IL-33, negatively regulates the IL-33/ST2 signaling pathway, and elevated levels of sST2 have been reported to correlate with poor prognosis in malignant tumors. However, the specific level of soluble ST2 and the precise role of the IL-33/ST2 signaling axis in the context of MDS remain uncertain and require further investigation. Method: This prospective study enrolled 89 newly diagnosed, untreated outpatient individuals with MDS to assess their clinical prognostic risk using the International Prognostic Scoring System-Revised (IPSS-R) and the International Prognostic Scoring System-Molecular (IPSS-M). A control group of 45 healthy donors (HD) was also included. The levels of various cytokines (sST2, IL-33, IL-2Rα, IL-6, IL-15) were measured using ELISA. Result: Our study revealed that sST2 levels in MDS patients were significantly higher compared to HD (22.18 vs. 12.43 ng/ml, p = 0.0313), with no significant difference between low and high-risk groups. The Receiver Operating Characteristic (ROC) curve analysis showed an Area Under the Curve (AUC) of 0.6140 for sST2 (p = 0.0315, 95%CI 0.5199-0.7081). Using the maximum Youden index, the optimal cut-off value for sST2 (&amp;gt;14.71 ng/ml) was determined with a sensitivity and specificity of 51.69% and 73.33%, respectively. Progressive events include conversion to leukemia(n=8), transfusion-dependent occurrence(n=1) and death (n=29). Patients with higher sST2 levels in both high and low-risk groups demonstrated poorer Event-Free Survival (EFS) (p = 0.0193) and Overall Survival (OS) (p = 0.0130) (Figure 1). Further, multivariate analysis identified cytokine sST2(HR = 0.337, 95%CI 0.163-0.696, P=0.003), blast percentage(HR = 0.472, 95%CI 0.237-0.940, P = 0.033), and transfusion dependence(HR = 0.367, 95%CI 0.179-0.753, P = 0.006) as independent risk factors, indicating sST2's potential in predicting prognosis and adverse event risk in MDS patients. Furthermore, sST2 exhibited a significant correlation with other inflammatory cytokines (IL-2Rα, r = 0.4152, p = 0.0005; IL-6, r = 0.4897, p = 0.0013; IL-15, r = 0.3535, p = 0.0253). This suggests that sST2 plays an active role in immune system activation and chronic inflammation. Multiple attempts to detect IL-33 expression in the serum of MDS patients were unsuccessful, indicating the need for a more sensitive and specific assay. In our study, no statistically significant difference was observed in the level of sST2 between bone marrow and peripheral blood (P=0.2197), as well as before treatment and after chemotherapy (P=0.3965). These findings indicate that sST2 is an easily detectable and relatively stable indicator. Conclusions: sST2 emerges as a significant, independent negative prognostic factor at the time of MDS diagnosis, offering valuable predictive insights into disease progression and a poor prognosis.

Preventing secondary screw perforation following proximal humerus fracture after locking plate fixation: a new clinical prognostic risk stratification model.

After locking plate (LP) fixation, secondary screw perforation (SSP) is the most common complication in proximal humerus fracture (PHF). SSP is the main cause of glenoid destruction and always leads to reoperation. This study aimed to identify independent risk parameters for SSP and establish an individualized risk prognostic model to facilitate its clinical management. We retrospectively reviewed the medical information of patients with PHF who underwent open reduction and internal LP fixation at one medical center (n = 289) between June 2013 and June 2021. Uni- and multivariate regression analyses identified the independent risk factors. A novel nomogram was formulated based on the final independent risk factors for predicting the risk of SSP. We performed internal validation through concordance indices (C-index) and calibration curves. To implement the clinical use of the model, we performed decision curve analyses (DCA) and risk stratification according to the optimal cutoff value. A total of 232 patients who met the inclusion criteria were enrolled. The incidence of SSP was 21.98% at the last follow-up. We found that fracture type (odds ratio [OR], 3.111; 95% confidence interval [CI], 1.223-7.914; P = 0.017), postoperative neck-shaft angle (OR, 4.270; 95% CI 1.622-11.239; P = 0.003), the absence of calcar screws (OR, 3.962; 95% CI 1.753-8.955; P = 0.003), and non-medial metaphyseal support (OR,7.066; 95% CI 2.747-18.174; P = 0.000) were independent predictors of SSP. Based on these variables, we developed a nomogram that showed good discrimination (C-index = 0.815). The predicted values of the new model were in good agreement with the actual values demonstrated by the calibration curve. Furthermore, the model's DCA and risk stratification (cutoff = 140 points) showed significantly higher clinical benefits. We developed and validated a visual and personalized nomogram that could predict the individual risk of SSP and provide a decision basis for surgeons to create the most optional management plan. However, future prospective and externally validated design studies are warranted to verify our model's efficacy.

A radiomics nomogram prediction for survival of patients with “driver gene-negative” lung adenocarcinomas (LUAD)

BackgroundTo study the role of computed tomography (CT)-derived radiomics features and clinical characteristics on the prognosis of “driver gene-negative” lung adenocarcinoma (LUAD) and to explore the potential molecular biological which may be helpful for patients’ individual postoperative care.MethodsA total of 180 patients with stage I-III “driver gene-negative” LUAD in the First Affiliated Hospital of Sun Yat-Sen University from September 2003 to June 2015 were retrospectively collected. The Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression model was used to screen radiomics features and calculated the Rad-score. The prediction performance of the nomogram model based on radiomics features and clinical characteristics was validated and then assessed with respect to calibration. Gene set enrichment analysis (GSEA) was used to explore the relevant biological pathways.ResultsThe radiomics and the clinicopathological characteristics were combined to construct a nomogram resulted in better performance for the estimation of OS (C-index: 0.815; 95% confidence interval [CI]: 0.756–0.874) than the clinicopathological nomogram (C-index: 0.765; 95% CI: 0.692–0.837). Decision curve analysis demonstrated that in terms of clinical usefulness, the radiomics nomogram outperformed the traditional staging system and the clinicopathological nomogram. The clinical prognostic risk score of each patient was calculated based on the radiomics nomogram and divided by X-tile into high-risk (> 65.28) and low-risk (≤ 65.28) groups. GSEA results showed that the low-risk score group was directly related to amino acid metabolism, and the high-risk score group was related to immune and metabolism pathways.ConclusionsThe radiomics nomogram was promising to predict the prognosis of patients with “driver gene-negative” LUAD. The metabolism and immune-related pathways may provide new treatment orientation for this genetically unique subset of patients, which may serve as a potential tool to guide individual postoperative care for those patients.

Bioinformatics analysis and experimental validation of a novel autophagy-related signature relevant to immune infiltration for recurrence prediction after curative hepatectomy

Hepatocellular carcinoma (HCC) remains imposing an enormous economic and healthcare burden worldwide. In this present study, we constructed and validated a novel autophagy-related gene signature to predict the recurrence of HCC patients. A total of 29 autophagy-related differentially expressed genes were identified. A five-gene signature (CLN3, HGF, TRIM22, SNRPD1, and SNRPE) was constructed for HCC recurrence prediction. Patients in high-risk groups exhibited a significantly poor prognosis compared with low-risk patients both in the training set (GSE14520 dataset) and the validation set (TCGA and GSE76427 dataset). Multivariate cox regression analysis demonstrated that the 5-gene signature was an independent risk factor for recurrence-free survival (RFS) in HCC patients. The nomograms incorporating 5-gene signature and clinical prognostic risk factors were able to effectively predict RFS. KEGG and GSEA analysis revealed that the high-risk group was enriched with multiple oncology characteristics and invasive-related pathways. Besides, the high-risk group had a higher level of immune cells and higher levels of immune checkpoint-related gene expression in the tumor microenvironment, suggesting that they might be more likely to benefit from immunotherapy. Finally, the immunohistochemistry and cell experiments confirmed the role of SNRPE, the most significant gene in the gene signature. SNRPE was significantly overexpressed in HCC. After SNRPE knockdown, the proliferation, migration and invasion ability of the HepG2 cell line were significantly inhibited. Our study established a novel five-gene signature and nomogram to predict RFS of HCC, which may help in clinical decision-making for individual treatment.

Analysis on echocardiographic data of fetal heart defects at high altitude in Yunnan province and surrounding high altitude areas

Objective: To explore the current situation of fetal heart defects in Yunnan Province and surrounding high altitude areas and the social factors affecting pregnancy outcome. Methods: This is a retrospective study. Pregnant woman who underwent fetal echocardiography and diagnosed as fetal cardiac defects in Yunnan Fuwai Cardiovascular Hospital from June 2017 to January 2021 were included. According to the clinical prognostic risk scoring system and grading criteria of fetal cardiac birth defects, the cases were divided into grade Ⅰ to Ⅳ. The disease distribution and proportion of each prognostic grade, pregnancy outcomes were analyzed and compared. The cases were divided into continued pregnancy group and terminated pregnancy group according to pregnancy outcome. The social factors that may affect the selection of pregnancy outcomes were analyzed by multivariate logistic regression analysis. Results: A total of 4 929 fetal echocardiography examination data were collected, and 4 464 cases (90.57%) were from Yunnan Province and surrounding high altitude areas. 2 166 cases of heart defects were finally analyzed, including 998 cases of congenital heart disease (CHD), 93 cases of cardiac tumors, cardiomyopathy and arrhythmia, 1 075 cases of foramen ovale, ductus arteriosus abnormalities and normal variations. The pregnant women were (29.2±5.0) years old with (25.6±3.8) gestational weeks. The number of cases with prognostic grade from Ⅰ to Ⅳ was 1 037 (47.88%), 620 (28.62%), 314 (14.50%), and 44 (2.03%), respectively. And 151 cases (6.97%) were not classified. The cases of normal variation and thin aortic arch development accounted for 42.66% (924/2 166), 5.22% (113/2 166), respectively. The top 3 diseases of grade Ⅱ were ventricular septal defect, coarctation of aorta and mild-moderate pulmonary stenosis, respectively, and their distribution was 11.63% (252/2 166), 3.92% (85/2 166) and 2.35% (51/2 166) respectively in all cases of heart defects, and 25.25% (252/998), 8.52% (85/998) and 5.11% (51/998) respectively in cases of CHD. Among the cases rated as grade Ⅲ and Ⅳ, most of them were complicated congenital heart disease, and the disease types are scattered. The more common cases in grade Ⅲ were complete transposition of great arteries (accounting for 2.40% (52/2 166) of all cases with heart defects, 5.21% (52/998) of all cases with CHD) and pulmonary artery occlusion (type Ⅰ to Ⅲ) with ventricular septal defect (accounting for 2.17% (47/2 166) of all cases with heart defects, and 4.71% (47/998) of all cases with CHD). In grade Ⅳ, single ventricle (0.74% (16/2 166) of all cases with heart defects, 1.60% (16/998) of all cases with CHD) and left ventricular dysplasia syndrome (0.65% (14/2 166) of all cases with heart defects, 1.40% (14/998) of all cases with CHD) are more common. A total of 1 084 cases were successfully followed up, and 675 cases were born, 392 cases were terminated, spontaneous abortion occurred in 17 cases. The proportion of terminated pregnancy cases was significantly increased from grade Ⅰ to Ⅳ, accounting for 5.24% (21/401), 27.78% (70/252), 89.54% (214/239) and 95.56% (43/45), respectively. Among the terminated pregnancy cases, those with grade Ⅲ accounted for the highest proportion (54.59% (214/392)). The distribution of terminated pregnancy cases was mainly complex congenital malformations or diseases with very poor prognosis (pregnancy outcome grade Ⅲ and Ⅳ), and proportion of terminated pregnancy with pregnancy outcome grade Ⅰ and Ⅱ cases (normal variation or good prognosis) accounted for 5.36% (21/392) and 17.86% (70/392), respectively. The results of multivariate logistic regression analysis showed that pregnant women with low education (high school and below: OR=2.73, 95%CI 1.26-5.93, P<0.001; illiteracy: OR=3.27, 95%CI 1.29-7.10, P<0.001) and low family income (Annual income<100 000 yuan: OR=2.47, 95%CI 1.69-5.12, P<0.001) were more likely to choose termination of pregnancy in case of fetal heart defect. Conclusion: In Yunnan province and the surrounding high altitude areas, the disease distribution of fetal heart defect is mainly simple or low-risk disease, but the complex malformation, especially the disease with poor pregnancy outcome, accounts for a relative high proportion. Pregnancy termination also occurs in some cases with good pregnancy outcome. The education level and family income of pregnant women may affect their choice of pregnancy outcome in case of fetal heart defect.

Clinical prognostic risk analysis and progression factor exploration of primary breast lymphoma

ABSTRACT Purpose : A primary breast lymphomais a rare form of extranodal lymphoma type. We aimed to analyze prognosticriskfactors and explore relapse factors in primary breast diffuse large B cell lymphoma (PB-DLBCL). Methods : From November 2003 to September 2020, sixty-three patients from two medical centers newly diagnosed with PB-DLBCL patients were analyzed retrospectively. Results : The median age was 52, and >50% of patients were post-menopausal. The international prognostics index (IPI) (0–1) was mainlyin the low-risk group (84%), and there were four patients with stage IV (6%) who had bilateral breast involvement. With a median follow-up time of 4.92 years (3.17–8.00), five-year overall survival (OS) and progression-free survival (PFS) were 78.9% and 67.1%, respectively. Univariate and multivariate analyses showed that elevated erythrocyte sedimentation rate (ESR) and B symptoms were independent adverse prognostic risk factors for OS, whereas bilateral breast involvement was unfavorable for PFS. Disease recurrence and relapse occurred in 40% (25/63) patients, mainly in the breast, followed by the central nervous system (CNS) and skin/soft tissue. Conclusion : This is the first study to explore the prognostic risk factors and relapse factorsof PB-DLBCL in a relatively large Chinese PBL cohort. Local breast and CNS recurrence after standard R-CHOP treatment were the main issues we are facing now.

Soluble PD-L1 Predict Poor Outcome and Disease Progression in Patients with De Novo Myelodysplastic Syndrome

Background: Myelodysplastic syndromes (MDS) are a group of myeloid neoplasms characterized by clonal proliferation of hematopoietic stem cells, recurrent genetic abnormalities, myelodysplasia, ineffective hematopoiesis, peripheral-blood cytopenia, and a high risk of evolution to acute myeloid leukemia (AML). Mounting evidence indicates that dysregulating immune checkpoint pathways are implicated in the pathogenesis of MDS, which thus promoting a number of trials employing immune checkpoints inhibitors (ICIs) in different settings. Soluble ICs (sICs) are soluble forms of ICs, which can be measured from circulation. In solid tumors, sICs have been identified with roles in predicting prognosis and mediating resistance to ICIs. However, in MDS, it is still unclear whether sICs levels are dysregulating in this disease and already has a prognostic influence at the time of diagnosis. Method: Seventy-nine adult patients with untreated de novo MDS were enrolled in this prospective study and managed upon clinical prognostic risk assessment by Revised International Prognostic Scoring System (IPSS-R), 10 healthy donors (HD) were enrolled as control. Profile of sICs (sPD-1, sPD-L1, sCTLA-4, sLAG-3, sTIM-3, sGITR, sOX40, s4-1BB, sST-2) and cytokines (IFN-γ, IFN-α2, IL-2, IL-2α, IL-6, IL-7, IL-10, IL-15, IL-17, TNF-α) were tested by ELISA, and the expression levels of PD-1 on T cells (CD3+, CD4+, CD8+, DPT, DNT）were measured using flow cytometry (FCM). Follow-up time ended on June 21, 2022. Result: MDS patients showed significant higher levels of sPD-1 and sPD-L1 (P＜0.01). Patients with high pretreatment sPD-L1 (>73.79 pg/mL) and high percent of PD-1+CD8+T cells (>7.3%) had worse OS (P < 0.05). Using a multivariate cox regression model adjusting established prognostic factors, including IPSS-R and transfusion dependency, high pretreatment sPD-L1 level was retained as a negative independent prognostic factor for OS (HR 3.151, 95%CI 1.061-9.364, P = 0.039). Moreover, to explore the roles of the PD-1/PD-L1 pathway in the pathogenesis of MDS, we examined the correlations between sPD-1, sPD-L1 and percent of PD-1+CD8+T cells and parameters associating with disease progression (Table. 1). Among clinico-pathological features, male patients showed higher levels of sPD-L1 and percent of PD-1+CD8+T cells, lower hemoglobin (＜80 g/L) significantly correlated to high sPD-L1 levels. In addition, in low- and very low- risk group according to IPSS-R, levels of sPD-L1 were significantly lower than intermediate-, high- and very high- risk group. Furthermore, in previous studies, it was reported that mPD-1/mPD-L1 can be induced by multiple inflammatory cytokines in cancer, including IFN-γ, IFN-α2, IL-2, IL-2α, IL-6, IL-7, IL-10, IL-15, IL-17, TNF-α, and we further tested them in our study. Correlation analysis showed that significant correlations were observed among different sICs as well as cytokines (Figure. 1). In addition, a positive correlation was found between TNF-α and sICs, including sPD-1, sPD-L1 and sST2 (P < 0.05). Conclusions: In conclusion, sPD-L1 was a negative independent prognostic factor for MDS patients at the time of diagnosis. High levels of sPD-L1 were presented in patients with lower hemoglobin and higher risk group, associating with disease progressing. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Stemness analysis in hepatocellular carcinoma identifies an extracellular matrix gene-related signature associated with prognosis and therapy response.

Background: Tumor stemness is the stem-like phenotype of cancer cells, as a hallmark for multiple processes in the development of hepatocellular carcinoma (HCC). However, comprehensive functions of the regulators of tumor cell’s stemness in HCC remain unclear. Methods: Gene expression data and clinical information of HCC samples were downloaded from The Cancer Genome Atlas (TCGA) dataset as the training set, and three validation datasets were derived from Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC). Patients were dichotomized according to median mRNA expression–based stemness index (mRNAsi) scores, and differentially expressed genes were further screened out. Functional enrichment analysis of these DEGs was performed to identify candidate extracellular matrix (ECM)–related genes in key pathways. A prognostic signature was constructed by applying least absolute shrinkage and selection operator (LASSO) to the candidate ECM genes. The Kaplan–Meier curve and receiver operating characteristic (ROC) curve were used to evaluate the prognostic value of the signature. Correlations between signatures and genomic profiles, tumor immune microenvironment, and treatment response were also explored using multiple bioinformatic methods. Results: A prognostic prediction signature was established based on 10 ECM genes, including TRAPPC4, RSU1, ILK, LAMA1, LAMB1, FLNC, ITGAV, AGRN, ARHGEF6, and LIMS2, which could effectively distinguish patients with different outcomes in the training and validation sets, showing a good prognostic prediction ability. Across different clinicopathological parameter stratifications, the ECMs signature still retains its robust efficacy in discriminating patient with different outcomes. Based on the risk score, vascular invasion, α-fetoprotein (AFP), T stage, and N stage, we further constructed a nomogram (C-index = 0.70; AUCs at 1-, 3-, and 5-year survival = 0.71, 0.75, and 0.78), which is more practical for clinical prognostic risk stratification. The infiltration abundance of macrophages M0, mast cells, and Treg cells was significantly higher in the high-risk group, which also had upregulated levels of immune checkpoints PD-1 and CTLA-4. More importantly, the ECMs signature was able to distinguish patients with superior responses to immunotherapy, transarterial chemoembolization, and sorafenib. Conclusion: In this study, we constructed an ECM signature, which is an independent prognostic biomarker for HCC patients and has a potential guiding role in treatment selection.

Advances in clinical prediction scores for prognosis of coronavirus disease-2019

Coronavirus Disease-2019 (COVID-19) has been a major public health issue all over the world, placing a significant burden on available healthcare resources. The most common types of COVID-19 are the mild and common forms. Although the proportion of the severe-critical types is smaller, the rate of death is significantly higher and the medical resources required tend to be greater. Thus, a variety of scores based on other disease and COVID-19 were used to assess the risk of poor prognosis on the COVID-19, including the common scores for community-acquired pneumonia, sepsis and viral pneumonia. Unfortunately, the above scores often lacked an adequate description of the applicable population or were at high risk of bias with unknown applicability. Therefore, the article summarized the existing scores, aiming to provide a reference for clinical prognostic risk assessment.

The Role of Post-treatment FDG-PET/CT Scanning after the First-line Chemotherapy in Predicting Prognosis in Patients with Hodgkin Disease and High-grade Non-Hodgkin Lymphoma: A Comparative Study with Clinical Prognostic Risk Scoring Data

The Role of Post-treatment FDG-PET/CT Scanning after the First-line Chemotherapy in Predicting Prognosis in Patients with Hodgkin Disease and High-grade Non-Hodgkin Lymphoma: A Comparative Study with Clinical Prognostic Risk Scoring Data

Role of m5 C RNA methylation regulators in colorectal cancer prognosis and immune microenvironment.

BackgroundRNA modification has become one of the hot topics of research as it can be used for tumor prognosis. However, its role in various biological processes is still poorly understood. The aim of this study was to investigate the role of m5C and m1A regulators on colorectal cancer prognosis using bioinformatics tools. The association between these regulators and differences in patient survival as well as the clinicopathological characteristics and tumor immune microenvironment in colorectal cancer tissues were assessed.MethodsWe selected publicly available colorectal cancer data sets from The Cancer Genome Atlas and used the “limma” package in R to identify differentially expressed genes. The least absolute shrinkage and selection operator regression model was used to calculate the prognostic risk, and a risk prediction model was constructed, to help assess the prognostic values of the differentially expressed genes. Finally, using TISCH and TIMER, we assessed the extent of cellular infiltration in colorectal cancer.ResultsWe explored NSUN6 and DNMT3A expression using UALCAN and HPA and found that their expression is significantly increased in colorectal cancer tissues and correlated with sex and TP53 mutation status. Moreover, we found NSUN6 and DNMT3A were related to the infiltration of six major immune cells, with DNMT3A being closely related to dendritic cells, CD4+ T cells, and B cells, whereas NSUN6 to B cells and CD8+ T cells.ConclusionOur findings suggest that m5C regulators can predict the clinical prognostic risk and regulate the tumor immune microenvironment in colorectal cancer.

Paired-Box 5 Positivity Related to High MIPI Score Predicts Shorter Overall Survival in Mantle Cell Lymphoma Patients

Introduction: Mantle cell lymphoma (MCL) is a sub-type of B-cell non-Hodgkin Lymphomas (NHL) that characterized by a heterogenous clinical course and poor prognosis. The transcription factor paired-box 5 (PAX5) is associated with B cell normal differentiation and development. Herein, we aim to explore both the prognostic factors and the role of PAX5 expression in MCL patients from single-center, which can provide theoretical guidance for clinical practice.Methods: The data of 80 MCL patients admitted to Shandong Provincial Hospital from October 2006 to April 2020 were collected to be analyzed. Kaplan-Meier method and univariate and multivariate cox analysis was used to analyze the correlation between overall survival and prognostic factors. Chi-square test, Pearson and Fisher correlation analysis were performed for statistical analysis of clinical features and experimental indicators. *p value<0.05 indicated that the difference was statistically significant. Immunohistochemistry (IHC) was used to label the protein expression. Gene expression profiles were applied to analyze the discrepancy of PAX5 mRNA expression in some lymphoma types.Results: Clinical characteristics of all MCL patients were analyzed. PAX5 expression was identified by IHC in this study: the positive expression rate of PAX5 in all MCL patients was 60% (Figure 1A). The mRNA expression level of PAX5 was obviously elevated in MCL specimens than in normal group compared with other groups (p= 0.034) (Figure 1B). Besides, CD5, CD19, CD22, CD38, CD79α, CD79β and SOX11 were shown co-expressed with PAX5 by string database analysis (Figure 1C). PAX5-related genes were found mainly enriched in lymphocyte activation, B cell proliferation and NOTCH1 signaling pathway (Figure 1D). As is shown in Figure 1E-I, MIPI score (≥6), median to high risk group, high β2-MG level (≥2.65 mg/L), ECOG score (≥2), and splenomegaly were associated with adverse survival (p= 0.006, 0.030, 0.001, 0.019 and 0.001 respectively). The positive expression of PAX5 indicated a shorter overall survival in MCL patients (p= 0.024, Figure 1G). Positive PAX5 expression was associated with international prognostic index (MIPI) score (p= 0.038), high risk stratification (p= 0.006), WBC count (p= 0.024), and increased β2-microglobulin level (p= 0.008). MCL patients with PAX5-positive expression, high level of β2-MG level (≥2.65 mg/L), splenomegaly correlated with a poorer OS (p=0.002, and 0.004 respectively, Figure 1K, L). In patients with PAX5-negative expression, splenomegaly also indicated poor prognosis (p= 0.030, Figure 1M). Furthermore, among patients with high MIPI scores, PAX5-positive MCL patients had a shorter overall survival than PAX5-negative patients (p= 0.016, Figure N, O). Multivariate analysis showed that positive PAX was an independent prognostic factor for poor survival of MCL (p= 0.035).Conclusions: The positive expression of PAX5 in immunohistochemistry may be a factor contributing to the poor prognosis of MCL patients, which is correlated with clinical characteristics and laboratory indicators to a certain extent. Our results the role of PAX5 positivity in MCL and provide clinical guidance for clinical prognostic risk assessment and treatment strategy selection.Keywords: Mantle cell lymphoma; Paired-box 5; Prognosis; Immunohistochemistry [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Development and Validation of a Clinical Prognostic Risk Score to Predict Early Neonatal Mortality, Ethiopia: A Receiver Operating Characteristic Curve Analysis.

BackgroundEarly neonatal death is the death of a live-born baby within the first seven days of life, which is 73% of all postnatal deaths in the globe. This study aimed to develop and validate a prognostic clinical risk tool for the prediction of early neonatal death.MethodsA prospective follow-up study was conducted among 393 neonates at Debre Tabor Referral hospital, Northwest Ethiopia. Multivariable logistic regression model was employed to identify potential prognostic determinants for early neonatal mortality. Area under receiver operating characteristics curve (AUROC) was used to check the model discrimination probability using ‘pROC’ R-package. Model calibration plot was checked using ‘givitiR’ R-package. Finally, a risk score prediction tool was developed for ease of applicability. Decision curve analysis was done for cost-benefit analysis and to check the clinical impact of the model.ResultsOverall, 15.27% (95% CI: 12.03–19.18) of neonates had the event of death during the follow-up period. Maternal undernutrition, antenatal follow-up less than four times, birth asphyxia, low birth weight, and not exclusive breastfeeding were the prognostic predictors of early neonatal mortality. The AUROC for the reduced model was 88.7% (95% CI: 83.8–93.6%), which had good discriminative probability. The AUROC of the simplified risk score algorithm was 87.8% (95% CI, 82.7–92.9%). The sensitivity and specificity of the risk score tool was 70% and 89%, respectively. The true prediction accuracy of the risk score tool to predict early neonatal mortality was 86%, and the false prediction probability was 13%.ConclusionWe developed an early neonatal death prediction tool using easily available maternal and neonatal characteristics for resource-limited settings. This risk prediction using risk score is an easily applicable tool to identify neonates at a higher risk of having early neonatal mortality. This risk score tool would offer an opportunity to reduce early neonatal mortality, thus improving the overall early neonatal death in a resource-limited setting.

Prognostic Significance and Tumor Immune Microenvironment Heterogenicity of m5C RNA Methylation Regulators in Triple-Negative Breast Cancer.

PurposeThe m5C RNA methylation regulators are closely related to tumor proliferation, occurrence, and metastasis. This study aimed to investigate the gene expression, clinicopathological characteristics, and prognostic value of m5C regulators in triple-negative breast cancer (TNBC) and their correlation with the tumor immune microenvironment (TIM).MethodsThe TNBC data, Luminal BC data and HER2 positive BC data set were obtained from The Cancer Genome Atlas and Gene Expression Omnibus, and 11 m5C RNA methylation regulators were analyzed. Univariate Cox regression and the least absolute shrinkage and selection operator regression models were used to develop a prognostic risk signature. The UALCAN and cBioportal databases were used to analyze the gene characteristics and gene alteration frequency of prognosis-related m5C RNA methylation regulators. Gene set enrichment analysis was used to analyze cellular pathways enriched by prognostic factors. The Tumor Immune Single Cell Hub (TISCH) and Timer online databases were used to explore the relationship between prognosis-related genes and the TIM.ResultsMost of the 11 m5C RNA methylation regulators were differentially expressed in TNBC and normal samples. The prognostic risk signature showed good reliability and an independent prognostic value. Prognosis-related gene mutations were mainly amplified. Concurrently, the NOP2/Sun domain family member 2 (NSUN2) upregulation was closely related to spliceosome, RNA degradation, cell cycle signaling pathways, and RNA polymerase. Meanwhile, NSUN6 downregulation was related to extracellular matrix receptor interaction, metabolism, and cell adhesion. Analysis of the TISCH and Timer databases showed that prognosis-related genes affected the TIM, and the subtypes of immune-infiltrating cells differed between NSUN2 and NSUN6.ConclusionRegulatory factors of m5C RNA methylation can predict the clinical prognostic risk of TNBC patients and affect tumor development and the TIM. Thus, they have the potential to be a novel prognostic marker of TNBC, providing clues for understanding the RNA epigenetic modification of TNBC.

Ceramide Pathway Regulators Predict Clinical Prognostic Risk and Affect the Tumor Immune Microenvironment in Lung Adenocarcinoma.

PurposeThe ceramide pathway is strongly associated with the regulation of tumor proliferation, differentiation, senescence, and apoptosis. This study aimed to explore the gene signatures, prognostic value, and immune-related effects of ceramide-regulated genes in lung adenocarcinoma (LUAD).MethodsPublic datasets of LUAD from The Cancer Genome Atlas and Gene Expression Omnibus were selected. Consensus clustering was adopted to classify LUAD patients, and a least absolute shrinkage and selection operator (LASSO) regression model was employed to develop a prognostic risk signature. CIBERSORT algorithm was used to estimate the association between the risk signature and the tumor immune microenvironment.ResultsMost of the 22 ceramide-regulated genes were differentially expressed between LUAD and normal samples. LUAD patients were classified into two subgroups (cluster 1 and 2) and cluster 2 was associated with a poor prognosis. Furthermore, a prognostic risk signature was developed based on the three ceramide-regulated genes, Cytochrome C (CYCS), V-rel reticuloendotheliosis viral oncogene homolog A (RELA) and Fas-associated via death domain (FADD). LUAD patients with low- and high-risk scores differed concerning the subtypes of tumor−infiltrating immune cells. A moderate to weak correlation was observed between the risk score and tumor−infiltrating immune cells.ConclusionsCeramide-regulated genes could predict clinical prognostic risk and affect the tumor immune microenvironment in LUAD.

Diabetes increases the mortality of patients with COVID-19: a meta-analysis.

AimsNowadays, the ongoing pandemic of COVID-19 caused by the novel coronavirus Syndrome-Coronavirus-2 (SARS-CoV-2) is an emerging, rapidly evolving situation. Complications such as hypertension, diabetes, COPD, cardiovascular disease, and cerebrovascular disease are major risk factors for patients with COVID-19.MethodsNo meta-analysis has explored if or not diabetes related to mortality of patients with COVID-19. Therefore, this meta-analysis first aims to explore the possible clinical mortality between diabetes and COVID-19, analyze if diabetes patients infected with SARS-CoV-2 are exposed to the worst clinical prognostic risk, and to evaluate the reliability of the evidence.ResultsOur results showed a close relationship between diabetes and mortality of COVID-19, with a pooled OR of 1.75 (95% CI 1.31–2.36; P = 0.0002). The pooled data were calculated with the fixed effects model (FEM) as no heterogeneity appeared in the studies. Sensitivity analysis showed that after omitting any single study or converting a random effect model to FEM, the main results still held.ConclusionsOur meta-analysis showed that diabetes increases the mortality of patients with COVID-19. These results indicated the disturbance of blood glucose in the COVID-19 patients. More importantly, this meta-analysis grades the reliability of evidence for further basic and clinical research into the diabetes dysfunction in COVID-19 patients.

Diabetes Increase the Mortality of Patients with COVID-19: A Meta-Analysis

Aims: Nowadays, the ongoing pandemic of COVID-19 caused by the novel coronavirus Syndrome-Coronavirus-2 (SARS-CoV-2) is an emerging, rapidly evolving situation. Complications such as hypertension, diabetes, COPD, cardiovascular disease, and cerebrovascular disease are major risk factors for patients with COVID-19. Method: No meta-analysis has explored if or not diabetes related to mortality of patients with COVID-19. Therefore, this meta-analysis first aims to explored the possible clinical mortality between diabetes and COVID-19, and analysis if diabetes patients infected with SARS-CoV-2 are particularly likely to have the worst clinical prognostic risk and to evaluate the strength of the evidence. Results: Our results found a significant relationship between diabetes and mortality COVID-19, with a pooled OR of 1.70 (95% CI: 1.16-2.48; P=0.006). The pooled data was calculated with the fixed effects model (FEM) as a low heterogeneity within the studies. Sensitivity analysis showed that after omitting any single study or converting a random effect model (REM) to FEM, the main results still held. Conclusions: Our meta-analysis showed that diabetes increases the mortality of patients with COVID-19. More importantly, this meta-analysis grades the strength of evidence for further basic and clinical research into the diabetes dysfunction in COVID-19 patients.

Prostate pathological evaluation after radical prostatectomy

The article presents information about the prostate's zonal structure, prostate preparation after radical prostatectomy, cancer incidence in different prostate areas. This provides an overview of the WHO classification (2016) of prostate tumors, the changes are noted, approaches to the diagnosis of cancer variants, Gleason score assessment, gradation determination, clinical prognostic risk groups for prostate cancer, primary tumor assessment according to the international classification of prostate cancer according to the TNM system (AjCC 8th ed.), which was supplemented and revised in 2017. Prognostic factors for acinar carcinoma and the role of immunohistochemical diagnosis in the morphological material were determined. In conclusion, the main significant parameters are indicated, which should be reflected in the Protocol of in vivo pathoanatomical study of the prostate samples after radical prostatectomy.