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Background Serum remnant cholesterol (RC) is associated with the onset of ischemic stroke (IS). However, studies on the correlation between RC levels and recurrent IS are limited, and the predictive value of RC in recurrent IS has not been analyzed. Objective To investigate the correlation between serum RC and the recurrence of IS, and to evaluate the predictive value of RC levels in recurrent IS by detecting serum RC levels in patients with IS. Methods Patients diagnosed as IS and hospitalized in the First Affiliated Hospital of Nanchang University, the Second Affiliated Hospital of Nanchang University, the Second Hospital of Nanchang, and the Third Hospital of Nanchang from March 2019 to March 2021 were included in the study. Relevant clinical information within 48 hours of admission was collected. All patients were followed up for 12 months to record the cases of recurrent IS. Cox regression and Restricted Cubic Spline (RCS) were performed to identify the correlation between RC levels and recurrent IS. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive value of RC levels in recurrent IS. Results A total of 1 023 eligible patients were included in the study, and 107 (10.46%) of them experienced IS recurrence within 1 year. Multivariable Cox regression analysis showed that high RC was an independent risk factor for recurrent IS (HR=2.709, 95%CI=1.150-6.382; P

Objective: Construction of a neuroblastoma (NB) prognostic predictive model based on pyroptosis-related genes (PRGs) to improve individualized management of NB patients. Methods: The NB cohort GSE49711 was obtained from the Gene Expression Omnibus (GEO) database, and a total of 498 patients were enrolled into the study, which were randomized into a training set and a test set at a ratio of 1:1, with 250 patients in the training set and 248 patients in the test set. A risk prediction model was constructed using the training set, and the GSE49711 cohort and test set were used as internal validation to verify the reliability of the model. Independent predictors associated with prognosis were screened using univariate and multivariate COX regression analyses, and risk score models were constructed. Single-cell gene set enrichment analysis (ssGSEA) was used to assess the relationship between PRGs and the tumor immune microenvironment. Nomograms were constructed to extend the clinical usability of the model and the reliability of the model was verified using ROC curves and calibration curves. Protein interaction networks of risk genes were mapped using the String database, and the expression of PRGs in NB cell lines was staged using the CCLE database. Results: A prognostic model was first developed with the training set: the risk score formula was (− 0.30 × GSDMB) + (− 0.46 × IL-18) + (− 0.21 × NLRP3) + (0.56 × AIM2). Patients were categorized into high- and low-risk groups based on the median risk score value. Survival analysis showed that NB patients in the high-risk group had a significantly lower survival rate than those in the low-risk group (P < 0.001). In both the GSE49711 overall cohort and the test cohort, survival analyses showed that patients in the high-risk group had significantly lower survival than those in the low-risk group (P < 0.001). Single-cell gene set enrichment analysis was used to assess the relationship between PRGs and the tumor immune microenvironment. Time-dependent ROC curves assessed the predictive performance of the nomogram in 5-, 7.5-, and 10-year survival with areas under the curve (AUC) of 0.843, 0.802 and 0.797, respectively. The calibration curves show good clinical predictive performance for nomograms. Conclusion: The results suggest that PRGs may serve as a novel prognostic marker for NB patients to provide new immunotherapeutic targets for the clinical treatment of NB patients. [ABSTRACT FROM AUTHOR]

Osteosarcoma remains a major health problem in teenagers. However, its pathogenesis mechanism remains not fully elucidated. This study aims to identify the prognostic biomarkers for osteosarcoma. In this study, we selected genes with a median absolute deviation (MAD) value of the top 5000 in the GSE32981 dataset for subsequent analysis. Weighted correlation network analysis (WGCNA) was used to construct a coexpression network. WGCNA showed that the tan module and midnight blue module were highly correlated with origin and metastases of osteosarcoma, respectively. Enrichment analysis was conducted using genes in the tan module and midnight blue module. A gene coexpression network was constructed by calculating the Spearman correlation coefficients. Four key genes (LTF, C10orf107, HIST1H2AK, and NEXN) were identified to be correlated with the prognosis of osteosarcoma patients. LTF has the highest AUC value, and its effect on osteosarcoma cells was then evaluated. The effect of LTF overexpression on proliferation, migration, and invasion of MG63 and 143B cells was detected by the CCK-8 assay, transwell cell migration assay, and transwell invasion assay, respectively. The overexpression of LTF promoted the proliferation, migration, and invasion of MG63 and 143B cells. In conclusion, LTF may serve as a prognostic biomarker for osteosarcoma. [ABSTRACT FROM AUTHOR]

Objective: To compare the long-term prognosis effects of non-esophagectomy and esophagectomy on patients with T1 stage esophageal cancer. Methods: All esophageal cancer patients in the study were included from the National Surveillance Epidemiology and End Results (SEER) database between 2005-2015. These patients were classified into non-esophagectomy group and esophagectomy group according to therapy methods and were compared in terms of esophagus cancer specific survival (ECSS) and overall survival (OS) rates. Results: A total of 591 patients with T1 stage esophageal cancer were enrolled in this study, including 212 non-esophagectomy patients and 111 esophagectomy patients in the T1a subgroup and 37 non-esophagectomy patients and 140 esophagectomy patients in the T1b subgroup. In all T1 stage esophageal cancer patients, there was no difference in the effect of non-esophagectomy and esophagectomy on postoperative OS, but postoperative ECSS in patients treated with non-esophagectomy was significantly better than those treated with esophagectomy. Cox proportional hazards regression model analysis showed that the risk factors affecting ECSS included race, primary site, tumor size, grade, and AJCC stage but factors affecting OS only include tumor size, grade, and AJCC stage in T1 stage patients. In the subgroup analysis, there was no difference in either ECSS or OS between the non-esophagectomy group and the esophagectomy group in T1a patients. However, in T1b patients, the OS after esophagectomy was considerably better than that of non-esophagectomy. Conclusions: Non-esophagectomy, including a variety of non-invasive procedures, is a safe and available option for patients with T1a stage esophageal cancer. For some T1b esophageal cancer patients, esophagectomy cannot be replaced at present due to its diagnostic and therapeutic effect on lymph node metastasis. [ABSTRACT FROM AUTHOR]

Background: As one of the most common malignancy, lung adenocarcinoma (LUAD) is characterized by low 5-year survival rate. This research aimed to investigate the effects of ribonucleotide reductase regulatory subunit M2 (RRM2) on malignant biological behaviors and activation of cGAS/STING pathway. We also explored the synergistic sensitization mechanisms of RRM2 and radiotherapy. Methods: Bioinformatic tools were used to evaluate the clinical significance of RRM2 in LUAD patients. The roles of RRM2 in malignant phenotype and DNA damage in LUAD cells were investigated with cell proliferation, colony formation, immunofluorescence, modified Boyden chamber and comet assays. The mouse models were used to evaluate the biological significance of RRM2 in vivo. Cytotoxic T cell infiltration was evaluated via flow cytometric analysis and immunohistochemistry staining in C57BL/6 mice. We also explored the synergistic effects of RRM2 silencing and radiation on LUAD cells with apoptosis assay and immunoblotting in vitro. Results: Bioinformatic analysis revealed that RRM2 had diagnostic values for LUAD patients. Higher levels of RRM2 predicted worse prognosis. RRM2 silencing inhibited LUAD cell proliferation, invasion and migration. RRM2 knockdown induced S phase arrest and DNA damage. RRM2 silencing induced cyclic GMP-AMP synthase (cGAS)/stimulator of interferon genes (STING) pathway, and the downstream targets were regulated in a STING-dependent manner. Knockdown of RRM2 suppressed tumor growth in the xenograft tumor models. RRM2 deficiency increased CD8 + T cells in the tumor tissues and spleens. Furthermore, RRM2 silencing had synergistic effects with radiation on inhibiting cell proliferation and promoting apoptosis. Meanwhile, this combination promoted the activation of cGAS/STING signaling pathway synergistically, and simultaneously increased expression of IFNβ, CCL5 and CXCL10. Conclusion: Our results demonstrated that RRM2 silencing had anti-tumor values and activated the cGAS/STING signaling pathway. RRM2 silencing increased CD8 + T cells infiltration. RRM2 silencing cooperated with radiation to inhibit LUAD cell proliferation, promote apoptosis and enhance the activation of cGAS/STING signaling pathway. RRM2 could be a promising target for tumor regression through cancer immunotherapy in LUAD. [ABSTRACT FROM AUTHOR]

Background: Osteosarcoma (OTS) is aggressive bone malignancy without well-recognized prognosis biomarker. Tumor mutational burden (TMB) has been proved as effective biomarker in predicting clinical outcomes in several cancer types. However, its prognostic value in OTS remains unknown. In this study, we aim to evaluate the implication of TMB in OTS patients. Methods: To depict the landscape of somatic mutations in OTS, we performed Whole-Exome Sequencing (WES) on 31 OTS tissue samples and corresponding White Blood Cells (WBCs) as matched control. TMB was calculated as the total number of somatic alterations in coding regions normalized to the per sequenced genomic megabase (~30.4Mb in WES). The prognostic values of TMB were evaluated by Kaplan-Meier methods and Cox regression models. Results: The median age was 16.0 years at diagnosis, and 54.8% of patients were male. The most common genetic alterations were mainly involved in cell cycle and DNA damage response and repair, including H3F3A, TP53, MYC, and CDKN2A/B. The median progression-free survival (PFS) was 775.5 days in TMB-High (defined as third quartile of TMB value, <2.565) versus 351 days in TMB-Low (<2.565). All patients with TMB-High are PFS-Long (>400 days), while 36.4% of all patients with TMB-Low were PFS-Long (P =0.003). TMB were significantly greater in PFS-Long than in PFS-Short (<400 days) (P =0.002). Moreover, the median overall survival (OS) was 1,307 days in TMB-High versus 672.5 days in TMB-Low. Furthermore, TMB-High group had significantly improved PFS (P =0.04) and OS (P =0.03). Conclusions: TMB-High can be used as prognostic marker for OTS. Our findings demonstrate that TMB may be helpful in combination with traditionally clinicopathologic risk factors to optimize risk stratification and guide treatment decisions. [ABSTRACT FROM AUTHOR]

Background and Purpose: Head and neck squamous carcinoma (HNSCC), characterized by immunosuppression, is a group of highly heterogeneous cancers. Although immunotherapy exerts a promising influence on HNSCC, the response rate remains low and varies in assorted primary sites. Immunological mechanisms underlying HNSCC pathogenesis and treatment response are not fully understood. This study aimed to develop a differentially expressed genes (DEGs)–based risk model to predict immunotherapy efficacy and stratify prognosis of HNSCC patients. Materials and Methods: The expression profiles of HNSCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The tumor microenvironment and immune response were estimated by cell type identification via estimating relative subset of known RNA transcripts (CIBERSORT) and immunophenoscore (IPS). The differential expression pattern based on human papillomavirus status was identified. A DEGs-based prognostic risk model was developed and validated. All statistical analyses were performed with R software (version 3.6.3). Results: By using the TCGA database, we identified DKK1 , HBEGF , RNASE7 , TNFRSF12A , INHBA , and IPIK3R3 as DEGs that were associated with patients' overall survival (OS). Patients were stratified into the high- and low-risk subgroups according to a DEGs-based prognostic risk model. Significant difference in OS was found between the high- and low-risk patients (1.64 vs. 2.18 years, P = 0.0017). In multivariate Cox analysis, the risk model was an independent prognostic factor for OS (hazard radio = 1.06, 95% confidence interval [1.02–1.10], P = 0.004). More CD8+ T cells and regulatory T cells were observed in the low-risk group and associated with a favorable prognosis. The IPS analysis suggested that the low-risk patients possessed a higher IPS score and a higher immunoreactivity phenotype, which were correlated with better immunotherapy response. Conclusion: Collectively, we established a reliable DEGs-based risk model with potential prognostic value and capacity to predict the immunophenotype of HNSCC patients. [ABSTRACT FROM AUTHOR]