Clinical Prognosis Research Articles

Analysis of methylation-driven genes for predicting the prognosis of patients with oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is a highly aggressive malignancy that is characterized by early distant metastasis and poor prognosis. DNA methylation plays an important role in the etiology and pathogenesis of OSCC. This study aimed to identify methylation-driven genes through bioinformatics analysis as potential biomarkers for early diagnosis and prognostic assessment of OSCC. Methylation data, RNA sequencing (RNA-seq) data and clinical prognosis information of OSCC patients were retrieved from The Cancer Genome Atlas (TCGA) database. The R packages MethylMix were employed to analyze the correlation between methylation status and corresponding gene expression in tumor and normal tissues to obtain methylation-driven genes. Univariate Cox regression analysis was developed to further screen methylation-driven genes associated with the prognosis of OSCC patients. Subsequently, multivariate Cox regression analysis was utilized to construct a linear prognostic risk prediction model. Furthermore, a combined survival analysis integrating methylation and gene expression was performed to investigate the prognostic value. A total of 374 differentially expressed methylation-driven genes were identified. Seven methylation-driven genes (BST2, KRT15, ZNF134, NT5E, GSTA7P, NAPRT, and GOLPH3L) were found to be significantly associated with patient prognosis. Additionally, four methylation-driven genes (BST2, KRT15, ZNF134 and NAPRT) were used to construct a linear prognostic risk prediction model for OSCC patients. Furthermore, a combined Kaplan-Meier survival analysis revealed that three methylation-driven genes (ZKSCAN7, MFF, ZNF134) alone can be used as independent prognostic markers or drug targets. Our findings facilitate a better understanding of molecular mechanisms of OSCC and provide potential biomarkers of early diagnosis, precision treatment and prognosis evaluation.

A machine learning clinic scoring system for hepatocellular carcinoma based on the Surveillance, Epidemiology, and End Results database.

Hepatocellular carcinoma (HCC) poses a global threat to life; however, numerical tools to predict the clinical prognosis of these patients remain scarce. The primary objective of this study is to establish a clinical scoring system for evaluating the overall survival (OS) rate and cancer-specific survival (CSS) rate in HCC patients. From the Surveillance, Epidemiology, and End Results (SEER) Program, we identified 45,827 primary HCC patients. These cases were randomly allocated to a training cohort (22,914 patients) and a validation cohort (22,913 patients). Univariate and multivariate Cox regression analyses, coupled with Kaplan-Meier methods, were employed to evaluate prognosis-related clinical and demographic features. Factors demonstrating prognostic significance were used to construct the model. The model's stability and accuracy were assessed through C-index, receiver operating characteristic (ROC) curves, calibration curves, and clinical decision curve analysis (DCA), while comparisons were made with the American Joint Committee on Cancer (AJCC) staging. Ultimately, machine learning (ML) quantified the variables in the model to establish a clinical scoring system. Univariate and multivariate Cox regression analyses identified 11 demographic and clinical-pathological features as independent prognostic indicators for both CSS and OS using. Two models, each incorporating the 11 features, were developed, both of which demonstrated significant prognostic relevance. The C-index for predicting CSS and OS surpassed that of the AJCC staging system. The area under the curve (AUC) in time-dependent ROC consistently exceeded 0.74 in both the training and validation sets. Furthermore, internal and external calibration plots indicated that the model predictions aligned closely with observed outcomes. Additionally, DCA demonstrated the superiority of the model over the AJCC staging system, yielding greater clinical net benefit. Ultimately, the quantified clinical scoring system could efficiently discriminate between high and low-risk patients. A ML clinical scoring system trained on a large-scale dataset exhibits good predictive and risk stratification performance in the cohorts. Such a clinical scoring system is readily integrable into clinical practice and will be valuable in enhancing the accuracy and efficiency of HCC management.

Mendelian randomization based on genome-wide association studies and expression quantitative trait loci, predicting gene targets for the complexity of osteoarthritis as well as the clinical prognosis of the condition.

Osteoarthritis (OA) entails a prevalent chronic ailment, marked by the widespread involvement of entire joints. Prolonged low-grade synovial inflammation serves as the key instigator for a cascade of pathological alterations in the joints. The study seeks to explore potential therapeutic targets for OA and investigate the associated mechanistic pathways. Summary-level data for OA were downloaded from the genome-wide association studies (GWAS) database, expression quantitative trait loci (eQTL) data were acquired from the eQTLGen consortium, and synovial chip data for OA were obtained from the GEO database. Following the integration of data and subsequent Mendelian randomization analysis, differential analysis, and weighted gene co-expression network analysis (WGCNA) analysis, core genes that exhibit a significant causal relationship with OA traits were pinpointed. Subsequently, by employing three machine learning algorithms, additional identification of gene targets for the complexity of OA was achieved. Additionally, corresponding ROC curves and nomogram models were established for the assessment of clinical prognosis in patients. Finally, western blotting analysis and ELISA methodology were employed for the initial validation of marker genes and their linked pathways. Twenty-two core genes with a significant causal relationship to OA traits were obtained. Through the application of distinct machine learning algorithms, MAT2A and RBM6 emerged as diagnostic marker genes. ROC curves and nomogram models were utilized for evaluating both the effectiveness of the two identified marker genes associated with OA in diagnosis. MAT2A governs the synthesis of SAM within synovial cells, thereby thwarting synovial fibrosis induced by the TGF-β1-activated Smad3/4 signaling pathway. The first evidence that MAT2A and RBM6 serve as robust diagnostic for OA is presented in this study. MAT2A, through its involvement in regulating the synthesis of SAM, inhibits the activation of the TGF-β1-induced Smad3/4 signaling pathway, thereby effectively averting the possibility of synovial fibrosis. Concurrently, the development of a prognostic risk model facilitates early OA diagnosis, functional recovery evaluation, and offers direction for further therapy.

Mixed Gestational Trophoblastic Tumors-Challenging Clinicopathological Presentations.

Mixed gestational trophoblastic tumors are exceptionally rare and have variable clinicopathological presentations. We report 3 such tumors with different combinations of choriocarcinoma (CC), placental site trophoblastic tumor (PSTT), and epithelioid trophoblastic tumor (ETT). The patients' age ranged from 38 to 44 years. Mixed trophoblastic tumor was not considered at the initial diagnosis and all 3 tumors were proven of gestational origin by DNA genotyping. Patient #1 presented with serum human chorionic gonadotropin (hCG) of 97 mIU/mL and a 5.6-cm cervical mass that was initially interpreted as PSTT on biopsy. Hysterectomy revealed a mixed PSTT (60%) and ETT (40%) with extrauterine metastases of only the ETT component. The tumor recurred 15 months after a multiagent chemotherapy and was tested positive for programmed death-ligand 1. The patient received immune checkpoint inhibitor therapy and remained disease-free after 24 months. Patient #2 presented with vaginal bleeding and serum hCG of 46,458 mIU/mL. An endometrial biopsy was interpreted as CC. Recurrence developed in the uterus and lung after methotrexate-based chemotherapy. A mixed CC and ETT were eventually diagnosed upon consultation review. Patient #3 presented with a complete hydatidiform mole and serum hCG of 744,828 mIU/mL. Three months after methotrexate, followed by actinomycin D therapy, a uterine mass was found. Hysterectomy revealed a mixed CC and PSTT. In conclusion, the rarity, elusive presentation, and wide range of histology make the diagnosis of mixed trophoblastic tumors highly challenging. The clinical management and prognosis are dictated by each component of the tumor. CC component must be considered when the patient presents with a high serum hCG level.

Clinical characteristics of patients diagnosed with bilateral sudden sensorineural hearing loss.

This study investigated the etiology, clinical features, and prognosis of patients diagnosed with bilateral sudden sensorineural hearing loss (BSSNHL). The clinical data of 100 patients with bilateral sudden hearing loss as a chief complaint treated at Xiangya Second Hospital of Central South University between January 2010 and August 2022, including clinical characteristics, audiometric data, and prognosis, were retrospectively analyzed. These 100 cases accounted for 8.09% (100/1235) of all patients admitted for sudden sensorineural hearing loss (SSNHL) during the same period. Of these, 71 were simultaneous cases and 29 were sequential cases of BSSNHL. Among the 200 ears analyzed in this study, 13, 36, 57, and 94 had mild, moderate, severe, and profound sensorineural hearing loss, respectively. The overall effective rate after comprehensive treatment was 32%, with significant differences in efficacy and prognosis among different degrees of hearing loss (p < 0.05). Comorbidities of hypertension (24 cases), diabetes (14 cases), and coronary heart disease (9 cases) significantly impacted therapeutic efficacy and prognosis in patients with BSSNHL (p < 0.05). Compared to unilateral SSNHL, BSSNHL exhibits distinctive characteristics.

Predicting CD27 expression and clinical prognosis in serous ovarian cancer using CT-based radiomics

BackgroundThis study aimed to develop and evaluate radiomics models to predict CD27 expression and clinical prognosis before surgery in patients with serous ovarian cancer (SOC).MethodsWe used transcriptome sequencing data and contrast-enhanced computed tomography images of patients with SOC from The Cancer Genome Atlas (n = 339) and The Cancer Imaging Archive (n = 57) and evaluated the clinical significance and prognostic value of CD27 expression. Radiomics features were selected to create a recursive feature elimination-logistic regression (RFE-LR) model and a least absolute shrinkage and selection operator logistic regression (LASSO-LR) model for CD27 expression prediction.ResultsCD27 expression was upregulated in tumor samples, and a high expression level was determined to be an independent protective factor for survival. A set of three and six radiomics features were extracted to develop RFE-LR and LASSO-LR radiomics models, respectively. Both models demonstrated good calibration and clinical benefits, as determined by the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis. The LASSO-LR model performed better than the RFE-LR model, owing to the area under the curve (AUC) values of the ROC curves (0.829 vs. 0.736). Furthermore, the AUC value of the radiomics score that predicted the overall survival of patients with SOC diagnosed after 60 months was 0.788 using the LASSO-LR model.ConclusionThe radiomics models we developed are promising noninvasive tools for predicting CD27 expression status and SOC prognosis. The LASSO-LR model is highly recommended for evaluating the preoperative risk stratification for SOCs in clinical applications.

Status quo and factors of depression and anxiety in patients with non-muscle invasive bladder cancer after plasma electrocision.

Bladder cancer is a type of cancer with a high incidence in men. Plasma electrosurgery (PES) is often used in the treatment of bladder cancer. Postoperative complications often cause depression and anxiety in patients after surgery. To investigate the current state of depression and anxiety after PES in patients with non-muscle-invasive bladder cancer and analyze the factors affecting them. A retrospective study was conducted to compare the baseline data of patients by collecting their medical history and grouping them according to their mental status into negative and normal groups. Logistic regression analysis was used to explore the risk factors affecting the occurrence of anxiety and depression after surgery in patients with bladder cancer. Comparative analyses of baseline differences showed that the patients in the negative and normal groups differed in terms of their first surgery, economic status, educational level, and marital status. A logistic regression analysis showed that it affected the occurrence of anxiety in patients with bladder cancer, and the results showed that whether the risk factors were whether or not it was the first surgery, monthly income between 3000 and 3000-6000, secondary or junior high school education level, single, divorced, and widowed statuses. The risk factors affecting the onset of anxiety and depression in bladder cancer patients after PES are the number of surgeries, economic status, level of education, and marital status. This study provides a reference for the clinical treatment and prognosis of bladder cancer patients in the future.

Analysis of status and influencing factors of mental health in patients with systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disorder with varied clinical courses and prognoses, not only did the patients suffer from physical impairment, but also various physical and psychiatric comorbidities. Growing evidence have suggested that mental disorders in SLE patients, can lead to various adverse consequences. To explored the features and influencing factors of mental health in patients with SLE and clarifying the correlations between mental health and personality characteristics and perceived social support. The results would provide a basis for psychological intervention in patients with SLE. The clinical data of 168 patients with SLE admitted at the First Affiliated Hospital of Hainan Medical University between June 2020 and June 2022 were collected. Psychological assessment and correlation analysis were conducted using the Symptom Checklist-90 (SCL-90) and Perceived Social Support Scale, and the collected data were compared with the national norms in China. The relevant factors influencing mental health were identified by statistical analysis. A general information questionnaire, the Revised Life Orientation Test, and Short-Form 36-Item Health Survey were employed to assess optimism level and quality of life (QoL), respectively. Patients with SLE obtained higher scores for the somatization, depression, anxiety, and phobic anxiety subscales than national norms (P < 0.05). A correlation was identified between total social support and total SCL-90 score or each subscale (P < 0.05). The factors significantly affecting patients' mental health were hormone dosage and disease activity index (DAI) (P < 0.05). The average optimism score of patients with SLE was 14.36 ± 4.42, and 30 cases were in the middle and lower levels. A positive correlation was found between optimism level and QoL scores. Patients with SLE develop psychological disorders at varying degrees, which are significantly influenced by hormone dosage and DAI. Patients' mental health should be closely monitored during clinical diagnosis and treatment and provided adequate support in establishing positive, healthy thinking and behavior patterns and improving their optimism level and QoL.

Long non-coding RNA MSL3P1 regulates CUL3 mRNA cytoplasmic transport and stability and promotes lung adenocarcinoma metastasis.

Lung adenocarcinoma (LUAD) is the most prevalent histological type of lung cancer. Previous studies have reported that specific long non-coding RNAs (lncRNAs) are involved in cancer development and progression. The phenotype and mechanism of ENST00000440028, named MSL3P1, a lncRNA which we referring to a cancer-testis gene with potential roles in tumorigenesis and progression, have not been reported. We found that MSL3P1 is overexpressed in LUAD tumor tissues, which is significantly associated with clinical characteristics, metastasis, and poor clinical prognosis. MSL3P1 promotes the metastasis of LUAD in vitro and in vivo. The enhancer reprogramming in LUAD tumor tissue is the major driver of the aberrantly expression of MSL3P1. Mechanistically, due to the competitive binding to CUL3 mRNA with ZFC3H1 protein (a protein involved in targeting polyadenylated RNA to exosomes and promoting the degradation of target mRNA), MSL3P1 can prevent the ZFC3H1-mediated RNA degradation of CUL3 mRNA and transport it to the cytoplasm. This activates the downstream epithelial-to-mesenchymal transition signaling pathway, and promote tumor invasion and metastasis. Implications: This study indicates that lncRNA MSL3P1 regulates CUL3 mRNA stability and promotes the metastasis and holds potential as a prognostic biomarker and therapeutic target in LUAD.

Association between triglyceride glucose-body mass index and all-cause mortality in critically ill patients with acute myocardial infarction: retrospective analysis of the MIMIC-IV database.

Insulin resistance (IR) is closely related to the development of cardiovascular diseases. Triglyceride-glucose-body mass index (TyG-BMI) has been proven to be a reliable surrogate of IR, but the relationship between TyG-BMI and acute myocardial infarction (AMI) is unknown. The present study aims to determine the effects of TyG-BMI on the clinical prognosis of critically ill patients with AMI. The data of AMI patients were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. All patients were divided into four groups according to the TyG-BMI quartile. Outcomes were defined as 30-, 90-, 180-, and 365-day all-cause mortality. Kaplan-Meier (K-M) curve was used to compare survival rate between groups. Meanwhile, Cox regression analysis and restricted cubic splines (RCS) were used to explore the relationship between TyG-BMI index and outcome events. A total of 1,188 critically ill patients with AMI were included in this study. They were divided into four groups according to TyG-BMI quartiles, there were significant differences in 90-, 180-, and 365-day all-cause mortality while there was no difference in 30-day all-cause mortality. Interestingly, with the increase of TyG-BMI, the 90-, 180-, and 365-day survival rate increased first and then gradually decreased, but the survival rate after decreasing was still higher than that in the group with the lowest TyG-BMI. U-shaped relationships between TyG-BMI index and 90-, 180-, and 365-day all-cause mortality were identified using RCS curve and the inflection point was 311.1, 316.5, and 320.1, respectively, whereas the TyG-BMI index was not non-linearly associated with 30-day all-cause mortality. The results of Cox proportional hazard regression analysis are consistent with those of RCS analysis. U-shaped relationships are existed between the TyG-BMI index and 90-, 180-, and 365-day all-cause mortality in critically ill patients with AMI, but not 30-day all-cause mortality. The TyG-BMI index can be used as an effective index for early prevention of critically ill patients with AMI.

High Fatty Acid-Binding Protein 4 Expression Associated with Favorable Clinical Characteristics and Prognosis in Papillary Thyroid Carcinoma.

Fatty acid-binding protein 4 (FABP4), a fatty acid transporter that coordinates lipid metabolism, is reported to exert a tumorigenic role in certain cancers. We investigated the effects of FABP4 in the carcinogenesis of thyroid cancer. Bioinformatics data about FABP4 in thyroid cancer were collected from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Sixteen paired papillary thyroid cancer (PTC) tissues from Taipei Medical University (TMU) were gathered, and commercial thyroid cancer complementary (c)DNA and tissue arrays were purchased to measure FABP4 messenger (m)RNA and protein levels. By analyzing data from the GEO and TCGA, we showed that FABP4 mRNA was reduced in PTC and follicular thyroid carcinoma (FTC). In addition, a lower FABP4 mRNA level in PTC was associated with poor clinical parameters and outcomes in the TCGA database. Moreover, FABP4 transcripts and proteins were downregulated in PTC and FTC, and its mRNA expression was associated with PTC staging in clinical specimens. In the TCGA database and TMU cohort, FABP4 mRNA levels were associated with thyroglobulin (r = 0.511 and r = 0.656, respectively), thyroid peroxidase (r = 0.612 and r = 0.909, respectively), and sodium iodide symporter (r = 0.485 and r = 0.637, respectively) transcripts. In conclusion, FABP4 mRNA and protein levels were reduced in PTC and FTC, and may be used as a potential indicator for thyroid cancer evolution in clinical settings. Further, well-designed research to dissect the molecular mechanism of FABP4 in modulating thyroid carcinogenesis is needed.

DNA Mutational and Copy Number Variation Profiling of Primary Craniofacial Osteosarcomas by Next-Generation Sequencing.

Craniofacial osteosarcomas (CFOS) are uncommon malignant neoplasms of the head and neck with different clinical presentation, biological behavior and prognosis from conventional osteosarcomas of long bones. Very limited genetic data have been published on CFOS. In the current study, we performed comprehensive genomic studies in 15 cases of high-grade CFOS by SNP array and targeted next generation sequencing. Our study shows high-grade CFOS demonstrate highly complex and heterogenous genomic alterations and harbor frequently mutated tumor suppressor genes TP53, CDKN2A/B, and PTEN, similar to conventional osteosarcomas. Potentially actionable gene amplifications involving CCNE1, AKT2, MET, NTRK1, PDGFRA, KDR, KIT, MAP3K14, FGFR1, and AURKA were seen in 43% of cases. GNAS hotspot activating mutations were also identified in a subset of CFOS cases, with one case representing malignant transformation from fibrous dysplasia, suggesting a role for GNAS mutation in the development of CFOS. High-grade CFOS demonstrate highly complex and heterogenous genomic alterations, with amplification involving receptor tyrosine kinase genes, and frequent mutations involving tumor suppressor genes.

Integrated analysis of single-cell RNA sequencing and bulk RNA data reveals gene regulatory networks and targets in dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a common cause of heart failure, thromboembolism, arrhythmias, and sudden cardiac death. The quality of life and long-term survival rates of patients with dilated DCM have greatly improved in recent decades. Nevertheless, the clinical prognosis for DCM patients remains unfavorable. The primary driving factors underlying the pathogenesis of DCM remain incompletely understood. The present study aimed to identify driving factors underlying the pathogenesis of DCM from the perspective of gene regulatory networks. Single-cell RNA sequencing data and bulk RNA data were obtained from the Gene Expression Omnibus (GEO) database. Differential gene analysis, single-cell genomics analysis, and functional enrichment analysis were conducted using R software. The construction of Gene Regulatory Networks was performed using Python. We used the pySCENIC method to analyze the single-cell data and identified 401 regulons. Through variance decomposition, we selected 19 regulons that showed significant responsiveness to DCM. Next, we employed the ssGSEA method to assess regulons in two bulk RNA datasets. Significant statistical differences were observed in 9 and 13 regulons in each dataset. By intersecting these differentiated regulons and identifying shared targets that appeared at least twice, we successfully pinpointed three differentially expressed targets across both datasets. In this study, we assessed and identified 19 gene regulatory networks that were responsive to the disease. Furthermore, we validated these networks using two bulk RNA datasets of DCM. The elucidation of dysregulated regulons and targets (CDKN1A, SAT1, ZFP36) enhances the molecular understanding of DCM, aiding in the development of tailored therapies for patients.

Three-dimensional environment sensitizes pancreatic cancer cells to the anti-proliferative effect of budesonide by reprogramming energy metabolism

BackgroundPancreatic ductal adenocarcinoma (PDAC) is the most lethal cancer with an aggressive metastatic phenotype and very poor clinical prognosis. Interestingly, a lower occurrence of PDAC has been described in individuals with severe and long-standing asthma. Here we explored the potential link between PDAC and the glucocorticoid (GC) budesonide, a first-line therapy to treat asthma.MethodsWe tested the effect of budesonide and the classical GCs on the morphology, proliferation, migration and invasiveness of patient-derived PDAC cells and pancreatic cancer cell lines, using 2D and 3D cultures in vitro. Furthermore, a xenograft model was used to investigate the effect of budesonide on PDAC tumor growth in vivo. Finally, we combined genome-wide transcriptome analysis with genetic and pharmacological approaches to explore the mechanisms underlying budesonide activities in the different environmental conditions.ResultsWe found that in 2D culture settings, high micromolar concentrations of budesonide reduced the mesenchymal invasive/migrating features of PDAC cells, without affecting proliferation or survival. This activity was specific and independent of the Glucocorticoid Receptor (GR). Conversely, in a more physiological 3D environment, low nanomolar concentrations of budesonide strongly reduced PDAC cell proliferation in a GR-dependent manner. Accordingly, we found that budesonide reduced PDAC tumor growth in vivo. Mechanistically, we demonstrated that the 3D environment drives the cells towards a general metabolic reprogramming involving protein, lipid, and energy metabolism (e.g., increased glycolysis dependency). This metabolic change sensitizes PDAC cells to the anti-proliferative effect of budesonide, which instead induces opposite changes (e.g., increased mitochondrial oxidative phosphorylation). Finally, we provide evidence that budesonide inhibits PDAC growth, at least in part, through the tumor suppressor CDKN1C/p57Kip2.ConclusionsCollectively, our study reveals that the microenvironment influences the susceptibility of PDAC cells to GCs and provides unprecedented evidence for the anti-proliferative activity of budesonide on PDAC cells in 3D conditions, in vitro and in vivo. Our findings may explain, at least in part, the reason for the lower occurrence of pancreatic cancer in asthmatic patients and suggest a potential suitability of budesonide for clinical trials as a therapeutic approach to fight pancreatic cancer.

After early mTICI 2b, stop or continue? Insights from the PERSIST Registry.

A higher reperfusion grade after endovascular thrombectomy (EVT) is associated with a good prognosis. However, the effect of the number of retrievals has not yet been investigated in vertebrobasilar occlusion (VBAO). Therefore, the aim of this study was to investigate whether to continue retrieval after early modified thrombolysis in cerebral infarction (mTICI) 2b to achieve a better reperfusion grade. We retrospectively analyzed the data of patients who underwent EVT caused by VBAO in a multicenter registry dataset. Patients who underwent successful reperfusion were included (mTICI 2b/3). Regression models were used to analyze the correlation of different reperfusion grades stratified by the number of retrieval attempts with clinical prognosis and hemorrhage transition. We included 432 patients: 34.5% (n = 149) had a final mTICI score of 2b and 65.5% (n = 283) had a final mTICI score of 3. Patients who obtained a mTICI of 3 after the first pass had significantly increased odds of having a good prognosis. As the number of passes increases, the chances of obtaining a good prognosis decreases. After three or more passes, the odds of achieving functional independence and favorable outcomes were comparable to those of the first mTICI 2b, regardless of the 90-day (OR 1.132 95% CI 0.367-3.487 p = 0.829; OR 1.070 95% CI 0.375-3.047 p = 0.900) or 1-year follow-up (OR 1.217 95% CI 0.407-3.637 p = 0.725; OR 1.068 95% CI 0.359-3.173 p = 0.906). Within two retrieval attempts, mTICI 3 was better than the first retrieval to mTICI 2b. After early mTICI 2b, each retrieval should be undertaken with caution to pursue a higher reperfusion grade.

Clinical outcome, radiological findings, and genetic features of IDH-mutant brainstem glioma in adults.

With the recent advent of genetic testing, IDH-mutant glioma has been found among adult brainstem gliomas. However, the clinical outcome and prognosis of IDH-mutant brainstem gliomas in adults have not been elucidated. This study aimed to investigate the clinical outcome, radiological findings, and genetic features of adult patients with IDH-mutant diffuse brainstem gliomas. Data from adult patients with brainstem glioma at Hokkaido University Hospital between 2006 and 2022 were retrospectively analyzed. Patient characteristics, treatment methods, genetic features, and prognosis were evaluated. Of 12 patients with brainstem glioma with proven histopathology, 4 were identified with IDH mutation. All patients underwent local radiotherapy with 54 Gray in 27 fractions combined with chemotherapy with temozolomide. Three patients had IDH1 R132H mutation and one had IDH2 R172G mutation. The median progression-free survival and overall survival were 68.4months and 85.2months, respectively, longer than that for IDH-wildtype gliomas (5.6months and 12.0months, respectively). At the time of initial onset, contrast-enhanced lesions were observed in two of the four cases in magnetic resonance imaging. As some adult brainstem gliomas have IDH mutations, and a clearly different prognosis from those with IDH-wildtype, biopsies are proactively considered to confirm the genotype.

Diffusion Tensor Imaging Identifies Cervical Spondylosis, Myelitis, and Spinal Cord Tumors.

Diffusion tensor imaging (DTI) has been increasingly recognized for its capability to study microstructural changes in the neuropathology of brain diseases. However, the optimal DTI metric and its diagnostic utility for a variety of spinal cord diseases are still under investigation. To evaluate the diagnostic efficacy of DTI metrics for differentiating between cervical spondylosis, myelitis, and spinal tumors. This retrospective study analyzed DTI scans from 68 patients (22 with cervical spondylosis, 23 with myelitis, and 23 with spinal tumors). DTI indicators, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD), were calculated. The Kruskal-Wallis test was used to compare these indicators, followed by Receiver Operating Characteristic (ROC) curve analysis, to evaluate the diagnostic efficacy of each indicator across disease pairs. Additionally, we explored the correlations of DTI indicators with specific clinical measurements. FA values were significantly lower in tumor patients compared to those with cervical spondylosis (p < 0.0001) and myelitis (p < 0.05). Additionally, tumor patients exhibited significantly elevated MD and RD values relative to the spondylosis and myelitis groups. ROC curve analysis underscored FA's superior discriminative performance, with an area under the curve (AUC) of 0.902 for differentiating tumors from cervical spondylosis, and an AUC of 0.748 for distinguishing cervical myelitis from spondylosis. Furthermore, a significant negative correlation was observed between FA values and Expanded Disability Status Scores (EDSSs) in myelitis patients (r = -0.62, p = 0.002), as well as between FA values and Ki-67 scores in tumor patients (r = -0.71, p = 0.0002). DTI indicators, especially FA, have the potential in distinguishing spondylosis, myelitis, and spinal cord tumors. The significant correlation between FA values and clinical indicators highlights the value of FA in the clinical assessment and prognosis of spinal diseases and may be applied in diagnostic protocols in the future.

Clinical characteristics and risk factors for ZF2001 fully vaccinated inpatients with COVID-19: A retrospective cohort study

ABSTRACT The ZF2001 vaccine has demonstrated high efficacy in preventing coronavirus disease 2019 (COVID-19). However, the clinical characteristics of breakthrough infections in vaccinated individuals and the risk factors for adverse outcomes in COVID-19 patients remain unclear. We conducted a retrospective single-center cohort study at Xiangya Hospital of Central South University, including 210 fully vaccinated COVID-19 inpatients from December 5, 2022, to January 31, 2023. Data on clinical characteristics, laboratory findings, disease severity, treatment, and prognosis were collected and analyzed. Our findings revealed that COVID-19 inpatients still experienced common symptoms at the onset of illness, but most laboratory findings were within the normal range, except for white blood cell count (WBC), lymphocyte count, and lactate dehydrogenase (LDH) levels. Following standard treatment, 95.7% of patients were discharged from the hospital. We identified seven variables significantly associated with a higher risk of adverse outcomes, including age over 65, elevated WBC count, reduced lymphocyte count, higher levels of blood urea nitrogen (BUN), LDH, troponin, D-dimer, and procalcitonin. This study supports the substantial clinical benefits of the ZF2001 vaccine for COVID-19 patients. Additionally, age over 65, elevated WBC count, reduced lymphocyte count, and higher blood levels of BUN, LDH, D-dimer, and procalcitonin may be used as predictive factors for disease progression in fully vaccinated COVID-19 inpatients.

Clinicopathological and molecular characteristics of NTRK-rearranged spindle cell neoplasms in the gastrointestinal tract

Objective: To investigate the clinicopathological, immunophenotypic and molecular genetic characteristics, and differential diagnosis of NTRK-rearranged spindle cell neoplasms (NTRK-RSCNs) in the gastrointestinal tract. Methods: Two NTRK-RSCNs diagnosed at the Department of Pathology of the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China and one case diagnosed at Zhengzhou Central Hospital, Zhengzhou, China from 2019 to 2022 were collected. The clinical data, histopathology, immunophenotypes and prognosis were analyzed. Fluorescence in situ hybridization (FISH) and next-generation sequencing (NGS) were used to detect NTRK gene rearrangements, while relevant literature was also reviewed and discussed. Results: Two patients were male and one was female, with the age of 17, 47 and 62 years, respectively. The tumors were located in the duodenum, ascending colon and descending colon, respectively. The tumors were protuberant masses with gray and rubbery sections. Their maximum diameter was 2.5, 5.0 and 10.0 cm, respectively. Histologically, the tumors invaded mucosa, intrinsic muscle and serosal adipose tissue. Tumor cells consisted of spindle or oval shaped cells with monotonous morphology and arranged in bundles or stripes pattern. Spindle cells were mildly to moderately atypical, with slightly eosinophilic cytoplasm and inconspicuous nucleoli. Necrosis and mitotic figures were observed in one high-grade tumor. All tumors expressed CD34, S-100 and pan-TRK in varying degrees. FISH analysis showed that NTRK1 gene was break-apart in 1 case and NTRK2 gene break-apart in 2 cases. NGS technologies showed LMNA::NTRK1 fusion in one case, STRN::NTRK2 fusion in another case. All patients recovered well after the surgery without recurrence at the end of the follow-up. Conclusions: NTRK-RSCN is rarely diagnosed in the gastrointestinal tract and has significant variations in morphology. It overlaps with various other mesenchymal tumors which should be considered as differential diagnoses. Be familiar with the features of histological morphology in combination with immunophenotype and molecular genetic characteristics can not only help diagnose NTRK-RSCNs, but provide therapeutic targets for clinical treatment.

Identification of a unique stress response state of T cells-related gene signature in patients with gastric cancer.

Gastric cancer (GC), the third most lethal cancer worldwide, is often diagnosed at an advanced stage, leaving limited therapeutic options. Given the diverse outcomes among GC patients with similar AJCC/UICC-TNM characteristics, there is a pressing need for more reliable prognostic tools. Recent advances in targeted therapy and immunotherapy have underscored this necessity. In this context, our study focused on a novel stress response state of T cells, termed TSTR, identified across multiple cancers, which is associated with resistance to immunotherapy. We aimed to develop a predictive gene signature for the TSTR phenotype within the tumor microenvironment (TME) of GC patients. By categorizing GC patients into high and low TSTR groups based on the infiltration states of TME TSTR cells, we observed significant differences in clinical prognosis and characteristics between the groups. Through a multi-step bioinformatics approach, we established an eight-gene signature based on genes differentially expressed between these groups. We conducted functional validations for the signature gene PDGFRL in GC cells. This gene signature effectively stratifies GC patients into high and low-risk categories, demonstrating robustness in predicting clinical outcomes. Furthermore, these risk groups exhibited distinct immune profiles, somatic mutations, and drug susceptibilities, highlighting the potential of our gene signature to enhance personalized treatment strategies in clinical practice.