The molecular signature and prognosis of glioma with preoperative intratumoral hemorrhage: a retrospective cohort analysis.

BACKGROUND: Intratumoral hemorrhage, though less common, could be the first clinical manifestation of glioma and is detectable via MRI; however, its exact impacts on patient outcomes remain unclear and controversial. The 2021 WHO CNS 5 classification emphasised genetic and molecular features, initiating the necessity to establish the correlation between hemorrhage and molecular alterations. This study aims to determine the prevalence of intratumoral hemorrhage in glioma subtypes and identify associated molecular and clinical characteristics to improve patient management. METHODS: Integrated clinical data and imaging studies of patients who underwent surgery at the Department of Neurosurgery at Peking Union Medical College Hospital from January 2011 to January 2022 with pathological confirmation of glioma were retrospectively reviewed. Patients were divided into hemorrhage and non-hemorrhage groups based on preoperative magnetic resonance imaging. A comparison and survival analysis were conducted with the two groups. In terms of subgroup analysis, we classified patients into astrocytoma, IDH-mutant; oligodendroglioma, IDH-mutant, 1p/19q-codeleted; glioblastoma, IDH-wildtype; pediatric-type gliomas; or circumscribed glioma using integrated histological and molecular characteristics, according to WHO CNS 5 classifications. RESULTS: 457 patients were enrolled in the analysis, including 67 (14.7%) patients with intratumoral hemorrhage. The hemorrhage group was significantly older and had worse preoperative Karnofsky performance scores. The hemorrhage group had a higher occurrence of neurological impairment and a higher Ki-67 index. Molecular analysis indicated that CDKN2B, KMT5B, and PIK3CA alteration occurred more in the hemorrhage group (CDKN2B, 84.4% vs. 62.2%, p = 0.029; KMT5B, 25.0% vs. 8.9%, p = 0.029; and PIK3CA, 81.3% vs. 58.5%, p = 0.029). Survival analysis showed significantly worse prognoses for the hemorrhage group (hemorrhage 18.4 months vs. non-hemorrhage 39.1 months, p = 0.01). In subgroup analysis, the multivariate analysis showed that intra-tumoral hemorrhage is an independent risk factor only in glioblastoma, IDH-wildtype (162 cases of 457 overall, HR = 1.72, p = 0.026), but not in other types of gliomas. The molecular alteration of CDK6 (hemorrhage group p = 0.004, non-hemorrhage group p < 0.001), EGFR (hemorrhage group p = 0.003, non-hemorrhage group p = 0.001), and FGFR2 (hemorrhage group p = 0.007, non-hemorrhage group p = 0.001) was associated with shorter overall survival time in both hemorrhage and non-hemorrhage groups. CONCLUSIONS: Glioma patients with preoperative intratumoral hemorrhage had unfavorable prognoses compared to their nonhemorrhage counterparts. CDKN2B, KMT5B, and PIK3CA alterations were associated with an increased occurrence of intratumoral hemorrhage, which might be future targets for further investigation of intratumoral hemorrhage.

Clinical application of intraoperative ultrasound superb microvascular imaging in brain tumors resections: contributing to the achievement of total tumoral resection.

BACKGROUND: To investigate whether the intraoperative superb microvascular imaging(SMI) technique helps evaluate lesion boundaries compared with conventional grayscale ultrasound in brain tumor surgery and to explore factors that may be associated with complete radiographic resection. METHODS: This study enrolled 57 consecutive brain tumor patients undergoing surgery. During the operation, B-mode and SMI ultrasound evaluated the boundaries of brain tumors. MRI before and within 48h after surgery was used as the gold standard to evaluate gross-total resection(GTR). The ultrasound findings and GTR results were analyzed to determine the imaging factors related to GTR. RESULTS: A total of 57 patients were enrolled in the study, including 32 males and 25 females, with an average age of 53.4 ± 14.1 years old(range 19 ~ 80). According to the assessment criteria of MRI, before and within 48 h after the operation, 37(63.9%) cases were classified as GTR, and 20(35.1%) cases were classified as GTR. In comparing tumor interface definition between B-mode and SMI mode, SMI improved HGG boundary recognition in 5 cases(P = 0.033). The results showed that the tumor size ≥ 5 cm and unclear ultrasonic boundary were independent risk factors for nGTR (OR>1, P<0.05). CONCLUSIONS: As an innovative intraoperative doppler technique in neurosurgery, SMI can effectively demarcate the tumor's boundary and help achieve GTR as much as possible.

Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients.

Glioblastoma (GBM) is the most malignant and lethal intracranial tumor, with extremely limited treatment options. Immunotherapy has been widely studied in GBM, but none can significantly prolong the overall survival (OS) of patients without selection. Considering that GBM cancer stem cells (CSCs) play a non-negligible role in tumorigenesis and chemoradiotherapy resistance, we proposed a novel stemness-based classification of GBM and screened out certain population more responsive to immunotherapy. The one-class logistic regression algorithm was used to calculate the stemness index (mRNAsi) of 518 GBM patients from The Cancer Genome Atlas (TCGA) database based on transcriptomics of GBM and pluripotent stem cells. Based on their stemness signature, GBM patients were divided into two subtypes via consensus clustering, and patients in Stemness Subtype I presented significantly better OS but poorer progression-free survival than Stemness Subtype II. Genomic variations revealed patients in Stemness Subtype I had higher somatic mutation loads and copy number alteration burdens. Additionally, two stemness subtypes had distinct tumor immune microenvironment patterns. Tumor Immune Dysfunction and Exclusion and subclass mapping analysis further demonstrated patients in Stemness Subtype I were more likely to respond to immunotherapy, especially anti-PD1 treatment. The pRRophetic algorithm also indicated patients in Stemness Subtype I were more resistant to temozolomide therapy. Finally, multiple machine learning algorithms were used to develop a 7-gene Stemness Subtype Predictor, which were further validated in two external independent GBM cohorts. This novel stemness-based classification could provide a promising prognostic predictor for GBM and may guide physicians in selecting potential responders for preferential use of immunotherapy.

Recent advances and future challenges of tumor vaccination therapy for recurrent glioblastoma.

Glioblastoma (GBM) is the most malignant CNS tumor with a highest incidence rate, and most patients would undergo a recurrence. Recurrent GBM (rGBM) shows an increasing resistance to chemotherapy and radiotherapy, leading to a significantly poorer prognosis and the urgent need for novel treatments. Immunotherapy, a rapidly developing anti-tumor therapy in recent years, has shown its potential value in rGBM. Recent studies on PD-1 immunotherapy and CAR-T therapy have shown some efficacy, but the outcome was not as expected. Tumor vaccination is the oldest approach of immunotherapies, which has returned to the research focus because of the failure of other strategies and subversive understanding of CNS. The isolation effect of blood brain barrier and the immunosuppressive cell infiltration could lead to resistance existing in all phases of the anti-tumor immune response, where novel tumor vaccines have been designed to overcome these problems through new tumor antigenic targets and regulatory of the systematic immune response. In this review, the immunological characteristics of CNS and GBM would be discussed and summarized, as well as the mechanism of each novel tumor vaccine for rGBM. And through the review of completed early-phase studies and ongoing large-scale phase III clinical trials, evaluation could be conducted for potential immune response, biosecurity and initial clinical outcome, which further draw a panorama of this vital research field and provide some deep thoughts for the prospective tendency of vaccination strategy. Video Abstract.

Effects of oncolytic viruses and viral vectors on immunity in glioblastoma.

Glioblastoma (GBM) is regarded as an incurable disease due to its poor prognosis and limited treatment options. Virotherapies were once utilized on cancers for their oncolytic effects. And they are being revived on GBM treatment, as accumulating evidence presents the immunogenic effects of virotherapies in remodeling immunosuppressive GBM microenvironment. In this review, we focus on the immune responses induced by oncolytic virotherapies and viral vectors in GBM. The current developments of GBM virotherapies are briefly summarized, followed by a detailed depiction of their immune response. Limitations and lessons inferred from earlier experiments and trials are discussed. Moreover, we highlight the importance of engaging the immune responses induced by virotherapies into the multidisciplinary management of GBM.

Molecular landscape of IDH-mutant astrocytoma and oligodendroglioma grade 2 indicate tumor purity as an underlying genomic factor.

BACKGROUND: IDH-mutant astrocytoma and oligodendroglioma have an indolent natural history and are recognized as distinct entities of neoplasms. There is little knowledge on the molecular differences between IDH-mutant astrocytoma and oligodendroglioma grade 2. Therefore, we investigated the multiomics and clinical data regarding these two types of tumors. METHOD: In silico analyses were performed around mRNA, somatic mutations, copy number alternations (CNAs), DNA methylation, microRNA (miRNA), epigenetics, immune microenvironment characterization and clinical features of the two types of gliomas. A diagnostic model incorporating tumor purity was further established using machine learning algorithms, and the predictive value was evaluated by receiver operative characteristic curves. RESULTS: Both types of gliomas shared chromosomal instability, and astrocytomas exhibited increased total CNAs compared to oligodendrogliomas. Oligodendrogliomas displayed distinct chromosome 4 (chr 4) loss, and subtyping of chr 7 gain/chr 4 loss (+ 7/- 4) presented the worst survival (P = 0.004) and progression-free interval (PFI) (P < 0.001). In DNA damage signatures, oligodendroglioma had a higher subclonal genome fraction (P < 0.001) and tumor purity (P = 0.001), and astrocytoma had a higher aneuploidy score (P < 0.001). Furthermore, astrocytomas exhibited inflamed immune cell infiltration, activated T cells and a potential response to immune checkpoint inhibitors (ICIs), while oligodendrogliomas were more homogeneous with increased tumor purity and decreased aggression. The tumor purity-involved diagnostic model exhibited great accuracy in identifying astrocytoma and oligodendroglioma. CONCLUSION: This study addresses the similarities and differences between IDH-mutant astrocytoma and oligodendroglioma grade 2 and facilitates a deeper understanding of their molecular features, immune microenvironment, tumor purity and prognosis. The diagnostic tool developed using machine learning may offer support for clinical decisions.

Systematic identification, development, and validation of prognostic biomarkers involving the tumor-immune microenvironment for glioblastoma.

Gliomas are infiltrative neoplasms with a highly invasive nature. Due to its distinct genomic, genetic and epigenetic features, the immune prognostic signature (IPS) and immune microenvironment of glioblastoma (GBM) merit further research. We aimed to explore prognosis-related immune genes and develop an IPS model for predicting prognosis in GBM. RNA-sequencing data, as well as clinical information, from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) public cohorts were analyzed. To develop the IPS, least absolute shrinkage and selection operator (LASSO) Cox analysis was performed for immune-related genes that were differentially expressed between GBM and normal tissues. Then, interaction effects of the IPS on the immune microenvironment were systematically analyzed; the precise prognostic model was developed based on the IPS and clinical data and was then further validated. A total of 21 immune prognostic genes were identified based on GBM microenvironment status. An 8-gene IPS was established, and the GBM patients were effectively stratified into low- and high-risk groups in the TCGA cohort as a training set. Univariate and multivariate Cox analyses revealed that IPS was an independent prognostic factor, and the prognostic performance of individual IPS genes was systematically illustrated. In addition, a comprehensive and novel nomogram model was initially established to estimate overall survival in TCGA-GBM patients, and high-risk patients had higher levels of dendritic cell and neutrophil infiltration. Furthermore, the nomogram model was developed and validated in the CGGA validation set. The low-risk IPS was linked to a stronger response to anti-PD-L1 immunotherapy and clinical advantages in the IMvigor210 cohort. This novel IPS with promising biomarkers classifies GBM patients into subgroups with distinct clinical outcomes and immunophenotypes. Our findings and this resource may help to characterize the immune microenvironment, inform cancer immunotherapy and facilitate the development of precision immuno-oncology.

A Bayesian network meta-analysis regarding the comparative efficacy of therapeutics for ALK-positive, brain metastatic non-small cell lung cancer.

More clinical evidence is needed regarding the ranking priority of interventions for ALK-positive, brain metastatic (BM) non-small cell lung cancer (NSCLC). Eligible randomized controlled trials (RCTs) were identified. Progression-free survival (PFS), objective response rate (ORR) and overall survival (OS) for the intended populations were analyzed with random effects, Bayesian network meta-analysis with the estimated hazard ratio (HR) and odds ratio (OR) with 95% credible interval (95% CrIs). We included 11 RCTs (2687 NSCLC and 991 BM patients) investigating 7 treatments and 5 medication classes. For PFS for BM patients, lorlatinib (hazard ratio (HR): 0.01, 95% CrI: 0.001-0.12), alectinib (HR: 0.05, 95% CrI: 0.01-0.21) and brigatinib (HR: 0.07, 95% CrI: 0.007-0.76) were top-ranking individual treatments; for ORR for BM patients, brigatinib, lorlatinib and alectinib were top-ranking treatments. For PFS for all NSCLC patients, the top-ranking individual treatments were lorlatinib (HR: 0.05, 95% CrI: 0.02-0.13), alectinib (HR: 0.09, 95% CrI: 0.05-0.18) and brigatinib (HR: 0.11, 95% CrI: 0.05-0.28). For OS for all NSCLC patients, we found that no individual treatments were superior to chemotherapy, whereas the following top-ranking interventions were alectinib (HR: 0.29, 95% CrI: 0.03-1.68), lorlatinib (HR: 0.41, 95% CrI: 0.04-4.13), and ceritinib (HR: 0.63, 95% CrI: 0.10-4.25). The results of individual treatments and medication classes were similar. Data were limited in regard to subgroup analyses and adverse events of BM patients. Lorlatinib has the most statistical superiority for BM patients, but ORR differences between third- and second-generation inhibitors are not obvious. All things considered, alectinib is recommended as first-line treatment, followed by lorlatinib, especially after developing drug resistance to alectinib.

Cloning and identification of a novel NhaD-type Na+/H+ antiporter from metagenomic DNA of the halophilic bacteria in soil samples around Daban Salt Lake.

In this study, metagenomic DNA was screened for the Na(+)/H(+) antiporter gene from the halophilic bacteria in Daban Salt Lake by selection in Escherichia coli KNabc lacking three major Na(+)/H(+) antiporters. One gene designated as Hb_nhaD encoding a novel NhaD-type Na(+)/H(+) antiporter was finally cloned. The presence of Hb_NhaD conferred tolerance of E. coli KNabc to up to 0.5 M NaCl and 0.2 M LiCl, and an alkaline pH. Hb_NhaD has the highest identity (70.6%) with a putative NhaD-type Na(+)/H(+) antiporter from an uncharacterized Clostridiaceae species, and also has lower identity with known NhaD-type Na(+)/H(+) antiporters from Halomonas elongata (20.8%), Alkalimonas amylolytica (19.0%), Vibrio parahaemolyticus (18.9%) and Vibrio cholerae (18.7 %). pH-dependent Na(+)(Li(+))/H(+) antiport activity was detected from everted membrane vesicles prepared from E. coli KNabc carrying Hb_nhaD. Hb_NhaD exhibited very high Na(+)(Li(+))/H(+) antiport activity over a wide pH range from 6.5 to 9.0 with the highest activity at pH 7.0 which is significantly different from those of the above known NhaD-type Na(+)/H(+) antiporters. Also, the apparent K m values of Hb_NhaD for Na(+) and Li(+) at pH 7.0 were determined to be 1.31 and 2.16, respectively. Based on the above results, we proposed that Hb_NhaD should be categorized as a novel NhaD-type Na(+)/H(+) antiporter.

Artificial neural network identified a 20-gene panel in predicting immunotherapy response and survival benefits after anti-PD1/PD-L1 treatment in glioblastoma patients.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are a promising immunotherapy approach, but glioblastoma clinical trials have not yielded satisfactory results. OBJECTIVE: To screen glioblastoma patients who may benefit from immunotherapy. METHODS: Eighty-one patients receiving anti-PD1/PD-L1 treatment from a large-scale clinical trial and 364 patients without immunotherapy from The Cancer Genome Atlas (TCGA) were included. Patients in the ICI-treated cohort were divided into responders and nonresponders according to overall survival (OS), and the most critical responder-relevant features were screened using random forest (RF). We constructed an artificial neural network (ANN) model and verified its predictive value with immunotherapy response and OS. RESULTS: We defined two groups of ICI-treated glioblastoma patients with large differences in survival benefits as nonresponders (OS ≤6 months, n = 18) and responders (OS ≥17 months, n = 8). No differentially mutated genes were observed between responders and nonresponders. We performed RF analysis to select the most critical responder-relevant features and developed an ANN with 20 input variables, five hidden neurons and one output neuron. Receiver operating characteristic analysis and the DeLong test demonstrated that the ANN had the best performance in predicting responders, with an AUC of 0.97. Survival analysis indicated that ANN-predicted responders had significantly better OS rates than nonresponders. CONCLUSION: The 20-gene panel developed by the ANN could be a promising biomarker for predicting immunotherapy response and prognostic benefits in ICI-treated GBM patients and may guide oncologists to accurately select potential responders for the preferential use of ICIs.

Clinical roles of EGFR amplification in diffuse gliomas: a real-world study using the 2021 WHO classification of CNS tumors.

Background: The 2021 World Health Organization Classification of Central Nervous System Tumors updates glioma subtyping and grading system, and incorporates EGFR amplification (Amp) as one of diagnostic markers for glioblastoma (GBM). Purpose: This study aimed to describe the frequency, clinical value and molecular correlation of EGFR Amp in diffuse gliomas based on the latest classification. Methods: We reviewed glioma patients between 2011 and 2022 at our hospital, and included 187 adult glioma patients with available tumor tissue for detection of EGFR Amp and other 59 molecular markers of interest. Clinical, radiological and pathological data was analyzed based on the status of EGFR Amp in different glioma subtypes. Results: 163 gliomas were classified as adult-type diffuse gliomas, and the number of astrocytoma, oligodendroglioma and GBM was 41, 46, and 76. EGFR Amp was more common in IDH-wildtype diffuse gliomas (66.0%) and GBM (85.5%) than IDH-mutant diffuse gliomas (32.2%) and its subtypes (astrocytoma, 29.3%; oligodendroglioma, 34.8%). EGFR Amp did not stratify overall survival (OS) in IDH-mutant diffuse gliomas and astrocytoma, while was significantly associated with poorer OS in IDH-wildtype diffuse gliomas, histologic grade 2 and 3 IDH-wildtype diffuse astrocytic gliomas and GBM. Conclusion: Our study validated EGFR Amp as a diagnostic marker for GBM and still a useful predictor for shortened OS in this group.

A prognostic model for overall survival in recurrent glioma patients treated with bevacizumab-containing therapy.

Predictive markers and prognostic models are useful for the individualization of cancer treatment. In this study, we sought to identify clinical and molecular factors to predict overall survival in recurrent glioma patients receiving bevacizumab-containing regimens. A cohort of 102 patients was retrospectively collected from June 2011 to January 2022 at our institution. A nomogram was generated by Cox regression and feature selection algorithms based on 19 clinicopathological and 60 molecular variables. The model's performance was internally evaluated by bootstrapping in terms of discrimination and calibration. The median overall survival from the initiation of bevacizumab administration to death or last follow-up was 11.6 months (95% CI: 9.2-13.8 months) for all 102 patients, 10.2 months (95% CI: 6.4-13.3 months) for 66 patients with grade 4 tumors, and 13.8 months (lower limit of 95% CI: 11.5 months) for 36 patients with tumors of grade lower or not available. In the final model, a lower WHO 2021 grade (Grade lower or not available vs. Grade 4, HR: 0.398, 95% CI: 0.223-0.708, p = 0.00172), having received adjuvant radiochemotherapy (Yes vs. No, HR: 0.488, 95% CI: 0.268-0.888, p = 0.0189), and wildtype EGFR (Wildtype vs. Altered, HR: 0.193, 95% CI: 0.0506-0.733, p = 0.0157; Not available vs. Altered, HR: 0.386, 95% CI: 0.184-0.810, p = 0.0118) were significantly associated with longer overall survival in multivariate Cox regression. The overall concordance index was 0.652 (95% CI: 0.566-0.714), and the areas under the time-dependent curves for 6-, 12-, and 18-month overall survival were 0.677 (95% CI: 0.516-0.816), 0.654 (95% CI: 0.470-0.823), and 0.675 (95% CI: 0.491-0.860), respectively. A prognostic model for overall survival in recurrent glioma patients treated with bevacizumab-based therapy was established and internally validated. It could serve as a reference tool for clinicians to assess the extent the patients may benefit from bevacizumab and stratify their treatment response.

Clinical features, MRI, molecular alternations, and prognosis of astrocytoma based on WHO 2021 classification of central nervous system tumors: A single-center retrospective study.

BACKGROUND: The diagnosis of glioma has advanced since the release of the WHO 2021 classification with more molecular alterations involved in the integrated diagnostic pathways. Our study aimed to present our experience with the clinical features and management of astrocytoma, IDH mutant based on the latest WHO classification. METHODS: Patients diagnosed with astrocytoma, IDH-mutant based on the WHO 5th edition classification of CNS tumors at our center from January 2009 to January 2022 were included. Patients were divided into WHO 2-3 grade group and WHO 4 grade group. Integrate diagnoses were retrospectively confirmed according to WHO 2016 and 2021 classification. Clinical and MRI characteristics were reviewed, and survival analysis was performed. RESULTS: A total of 60 patients were enrolled. 21.67% (13/60) of all patients changed tumor grade from WHO 4th edition classification to WHO 5th edition. Of these, 21.43% (6/28) of grade II astrocytoma and 58.33% (7/12) of grade III astrocytoma according to WHO 4th edition classification changed to grade 4 according to WHO 5th edition classification. Sex (p = 0.042), recurrent glioma (p = 0.006), and Ki-67 index (p < 0.001) of pathological examination were statistically different in the WHO grade 2-3 group (n = 27) and WHO grade 4 group (n = 33). CDK6 (p = 0.004), FGFR2 (p = 0.003), and MYC (p = 0.004) alterations showed an enrichment in the WHO grade 4 group. Patients with higher grade showed shorter mOS (mOS = 75.9 m, 53.6 m, 26.4 m for grade 2, 3, and 4, respectively, p = 0.01). CONCLUSIONS: Patients diagnosed as WHO grade 4 according to the 5th edition WHO classification based on molecular alterations are more likely to have poorer prognosis. Therefore, treatment should be tailored to their individual needs. Further research is needed for the management of IDH-mutant astrocytoma is needed in the future.

Molecular Determinants of Neurocognitive Deficits in Glioma: Based on 2021 WHO Classification.

Cognitive impairment is a common feature among patients with diffuse glioma. The objective of the study is to investigate the relationship between preoperative cognitive function and clinical as well as molecular factors, firstly based on the new 2021 World Health Organization's updated classification of central nervous system tumors. A total of 110 diffuse glioma patients enrolled underwent preoperative cognitive assessments using the Mini-Mental State Examination and Montreal Cognitive Assessment. Clinical information was collected from medical records, and gene sequencing was performed to analyze the 18 most influenced genes. The differences in cognitive function between patients with and without glioblastoma were compared under both the 2016 and 2021 WHO classification of tumors of the central nervous system to assess their effect of differentiation on cognition. The study found that age, tumor location, and glioblastoma had significant differences in cognitive function. Several genetic alterations were significantly correlated with cognition. Especially, IDH, CIC, and ATRX are positively correlated with several cognitive domains, while most other genes are negatively correlated. For most focused genes, patients with a low number of genetic alterations tended to have better cognitive function. Our study suggested that, in addition to clinical characteristics such as age, histological type, and tumor location, molecular characteristics play a crucial role in cognitive function. Further research into the mechanisms by which tumors affect brain function is expected to enhance the quality of life for glioma patients. This study highlights the importance of considering both clinical and molecular factors in the management of glioma patients to improve cognitive outcomes.

Researching the molecular mechanisms of Taohong Siwu Decoction in the treatment of varicocele-associated male infertility using network pharmacology and molecular docking: A review.

Taohong Siwu Decoction (THSWD) was widely used for the treatment of varicocele-associated male infertility. However, the pharmacological mechanism of action is not completely clear. Therefore, network pharmacology and molecular docking were performed to explore potential mechanism of THSWD in the treatment of varicocele-associated male infertility. The Traditional Chinese Medicine Systems Pharmacology (TCMSP), Swiss Target Prediction, and GeneCards were used to retrieve candidate compounds, action targets, and disease-related targets. The construction of the protein-protein interaction (PPI) network and the screening of core genes were completed by the STRING and Cytoscape 3.9.1, respectively. The DAVID was used to obtain results of gene ontology function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The Mcule analysis platform was used to perform molecular docking. There were a total of 53 candidate compounds and 782 relevant targets in THSWD. There were 45 common targets between THSWD, varicocele, and male infertility, and 23 core genes were found in the PPI network. Biological processes involved response to hypoxia, regulation of blood pressure, cellular response to hypoxia, and regulation of the nitric oxide biosynthetic process. Furthermore, the KEGG pathway enrichment analysis showed that the common targets mainly regulated the disease of varicocele-associated male infertility through the HIF-1 signaling pathway, PI3K-Akt signaling pathway, Relaxin signaling pathway, and TNF signaling pathway. Finally, the molecular docking showed that luteolin, quercetin, and kaempferol had good intercalation with major targets. As predicted by network pharmacology, THSWD regulated varicocele-associated male infertility through multiple compounds and targets, and its mechanism was closely related to inflammatory response, reactive oxygen species damage, and function of blood vessels.

Progress in phase III clinical trials of molecular targeted therapy and immunotherapy for glioblastoma.

Glioblastoma (GBM) is the most common primary central nervous system tumor, whose prognosis remains poor under the sequential standard of care, such as neurosurgery followed by concurrent temozolomide radiochemotherapy and adjuvant temozolomide chemotherapy in the presence or absence of tumor treating fields. Accordingly, the advent of molecular targeted therapy and immunotherapy has opened a new era of tumor management. A diverse range of targeted drugs have been tested in patients with GBM in phase III clinical trials. However, these drugs are ineffective for all patients, as evidenced by the fact that only a minority of patients in these trials showed prolonged survival. Furthermore, there are several published phase III clinical trials that involve immune checkpoint inhibitors, peptide vaccines, dendritic cell vaccines, and virotherapy. Accordingly, this review comprehensively overviews existing studies of targeted drugs and immunotherapy for glioma and discusses the challenge and perspective of targeted drugs and immunotherapy for glioma to clarify future directions.

Intraoperative shear-wave elastography and superb microvascular imaging contribute to the glioma grading.

BACKGROUND: To explore the diagnostic value and feasibility of shear wave elastography and superb microvascular imaging in the grading diagnosis of glioma intraoperatively. MATERIALS AND METHODS: Forty-nine patients with glioma were included in this study. B-mode ultrasonography, Young's modulus in shear-wave elastography (SWE) and vascular architecture in superb microvascular imaging(SMI) of tumor tissue and peritumoral tissue were analyzed. Receiver operating characteristic(ROC) curve analysis was used to evaluate the diagnostic effect of SWE. Logistic regression model was used to calculate the prediction probability of HGG diagnosis. RESULTS: Compared with LGG, HGG was often characterized by peritumoral edema in B mode (P < 0.05). There was a significant difference in Young's modulus between HGG and LGG; the diagnostic threshold of HGG and LGG was 13.05 kPa, the sensitivity was 78.3%, and the specificity was 76.9%. The vascular architectures of the tumor tissue and peritumoral tissues of HGG and LGG were significantly different (P < 0.05). The vascular architectures of peritumoral tissue in HGG often characterized by distorted blood flow signals surrounding the tumor (14/26,53.8%); in the tumor tissue, HGG often presents as dilated and bent vessels(19/26,73.1%). The elasticity value of SWE and the tumor vascular architectures of SMI were correlated with the diagnosis of HGG. CONCLUSION: Intraoperative ultrasound (ioUS), especially SWE, and SMI are beneficial for the differentiation of HGG and LGG and may help optimize clinical surgical procedures.

Prognostic Prediction Model for Glioblastoma: A Ferroptosis-Related Gene Prediction Model and Independent External Validation.

Glioblastoma (GBM) is the most common primary malignant intracranial tumor with a poor prognosis. Ferroptosis is a newly discovered, iron-dependent, regulated cell death, and recent studies suggest its close correlation to GBM. The transcriptome and clinical data were obtained for patients diagnosed with GBM from TCGA, GEO, and CGGA. Ferroptosis-related genes were identified, and a risk score model was constructed using Lasso regression analyses. Survival was evaluated by univariate or multivariate Cox regressions and Kaplan-Meier analyses, and further analyses were performed between the high- and low-risk groups. There were 45 ferroptosis-related different expressed genes between GBM and normal brain tissues. The prognostic risk score model was based on four favorable genes, CRYAB, ZEB1, ATP5MC3, and NCOA4, and four unfavorable genes, ALOX5, CHAC1, STEAP3, and MT1G. A significant difference in OS between high- and low-risk groups was observed in both the training cohort (p < 0.001) and the validation cohorts (p = 0.029 and 0.037). Enrichment analysis of pathways and immune cells and functioning was conducted between the two risk groups. A novel prognostic model for GBM patients was developed based on eight ferroptosis-related genes, suggesting a potential prediction effect of the risk score model in GBM.

Single-cell transcriptomic analyses provide insights into the cellular origins and drivers of brain metastasis from lung adenocarcinoma.

BACKGROUND: Brain metastasis (BM) is the most common intracranial malignancy causing significant mortality, and lung cancer is the most common origin of BM. However, the cellular origins and drivers of BM from lung adenocarcinoma (LUAD) have yet to be defined. METHODS: The cellular constitutions were characterized by single-cell transcriptomic profiles of 11 LUAD primary tumor (PT) and 10 BM samples (GSE131907). Copy number variation (CNV) and clonality analysis were applied to illustrate the cellular origins of BM tumors. Brain metastasis-associated epithelial cells (BMAECs) were identified by pseudotime trajectory analysis. By using machine-learning algorithms, we developed the BM-index representing the relative abundance of BMAECs in the bulk RNA-seq data indicating a high risk of BM. Therapeutic drugs targeting BMAECs were predicted based on the drug sensitivity data of cancer cell lines. RESULTS: Differences in macrophages and T cells between PTs and BMs were investigated by single-cell RNA (scRNA) and immunohistochemistry and immunofluorescence data. CNV analysis demonstrated BM was derived from subclones of PT with a gain of chromosome 7. We then identified BMAECs and their biomarker, S100A9. Immunofluorescence indicated strong correlations of BMAECs with metastasis and prognosis evaluated by the paired PT and BM samples from Peking Union Medical College Hospital. We further evaluated the clinical significance of the BM-index and identified 7 drugs that potentially target BMAECs. CONCLUSIONS: This study clarified possible cellular origins and drivers of metastatic LUAD at the single-cell level and laid a foundation for early detection of LUAD patients with a high risk of BM.