Relationship between circulating inflammatory factors and glioma risk and prognosis: A meta-analysis

The role of IL-17 in the pathogenesis and treatment of glioblastoma-an update on the state of the art and future perspectives

Glioblastoma (GBM) is the most common malignant brain tumor, which, despite significant progress made in the last years in the field of neuro-oncology, remains an incurable disease. GBM has a poor prognosis with a median survival of 12-15 months, and its aggressive clinical course is related to rapid growth, extensive infiltration of adjacent tissues, resistance to chemotherapy, radiotherapy and immunotherapy, and frequent relapse. Currently, several molecular biomarkers are used in clinical practice to predict patient prognosis and response to treatment. However, due to the overall unsatisfactory efficacy of standard multimodal treatment and the remaining poor prognosis, there is an urgent need for new biomarkers and therapeutic strategies for GBM. Recent evidence suggests that GBM tumorigenesis is associated with crosstalk between cancer, immune and stromal cells mediated by various cytokines. One of the key factors involved in this process appears to be interleukin-17 (IL-17), a pro-inflammatory cytokine that is significantly upregulated in the serum and tissue of GBM patients. IL-17 plays a key role in tumorigenesis, angiogenesis, and recurrence of GBM by activating pro-oncogenic signaling pathways and promoting cell survival, proliferation, and invasion. IL-17 facilitates the immunomodulation of the tumor microenvironment by promoting immune cells infiltration and cytokine secretion. In this article we review the latest scientific reports to provide an update on the role of IL-17 role in tumorigenesis, tumor microenvironment, diagnosis, prognosis, and treatment of GBM.

Causal relationship between inflammatory proteins and glioblastoma: a two-sample bi‑directional mendelian randomization study

Background: Observational studies have indicated a potential correlation between glioblastoma and circulating inflammatory proteins. Further investigation is required to establish a causal relationship between these two factors. Methods: We performed a Mendelian randomization (MR) analysis using genome-wide association study (GWAS) summary of 91 circulating inflammation-related proteins (N = 14,824) to assess their causal impact on glioblastoma. The GWAS summary data for glioblastoma included 243 cases and 287,137 controls. The inverse variance weighted (IVW) method was used as the primary analytical method to assess causality. Four additional MR methods [simple mode, MR-Egger, weighted median, and weighted mode] were used to supplement the IVW results. Furthermore, several sensitivity analyses were performed to assess heterogeneity, horizontal pleiotropy, and stability. Reverse MR analysis was also performed. glioblastoma transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to validate the findings obtained through MR, while pathway and functional enrichment analyses were conducted to predict the potential underlying mechanisms. Results: Our findings from employing the inverse variance weighted method in our forward MR analysis provide robust evidence supporting a potential association between glioblastoma and elevated levels of Cystatin D, as well as decreased levels of fibroblast growth factor 21 (FGF21) in the circulation. Moreover, our reverse MR analysis revealed that glioblastoma may contribute to increased concentrations of C-X-C motif chemokine 9 (CXCL9) and Interleukin-33 (IL-33) in the bloodstream. Transcriptomic analysis showed that FGF21 expression was inversely associated with the risk of developing glioblastoma, whereas an increased risk was linked to elevated levels of CXCL9 and IL-33. Pathway and functional enrichment analyses suggested that Cystatin D might exert its effects on glioblastoma through intracellular protein transport, whereas FGF21 might affect glioblastoma via glucose response mechanisms. Conclusion: These results indicate that FGF21 is a significant factor in glioblastoma susceptibility. Glioblastoma also affects the expression of inflammatory proteins such as C-X-C motif chemokine 9 and Interleukin-33, providing new insights into the mechanisms of glioblastoma genesis and clinical research.

Chronic stress as an emerging risk factor for the development and progression of glioma

ABSTRACT

Gliomas tend to have a poor prognosis and are the most common primary malignant tumors of the central nervous system. Compared with patients with other cancers, glioma patients often suffer from increased levels of psychological stress, such as anxiety and fear. Chronic stress (CS) is thought to impact glioma profoundly. However, because of the complex mechanisms underlying CS and variability in individual tolerance, the role of CS in glioma remains unclear. This review suggests a new proposal to redivide the stress system into two parts. Neuronal activity is dominant upstream. Stress-signaling molecules produced by the neuroendocrine system are dominant downstream. We discuss the underlying molecular mechanisms by which CS impacts glioma. Potential pharmacological treatments are also summarized from the therapeutic perspective of CS.

Unveiling the landscape of cytokine research in glioma immunotherapy: a scientometrics analysis

Background: Cytokines modulate the glioma tumor microenvironment, influencing occurrence, progression, and treatment response. Strategic cytokine application may improve glioma immunotherapy outcomes. Gliomas remain refractory to standard therapeutic modalities, but immunotherapy shows promise given the integral immunomodulatory roles of cytokines. However, systematic evaluation of cytokine glioma immunotherapy research is absent. Bibliometric mapping of the research landscape, recognition of impactful contributions, and elucidation of evolutive trajectories and hot topics has yet to occur, potentially guiding future efforts. Here, we analyzed the structure, evolution, trends, and hotspots of the cytokine glioma immunotherapy research field, subsequently focusing on avenues for future investigation. Methods: This investigation conducted comprehensive bibliometric analyses on a corpus of 1529 English-language publications, from 1 January 2000, to 4 October 2023, extracted from the Web of Science database. The study employed tools including Microsoft Excel, Origin, VOSviewer, CiteSpace, and the Bibliometrix R package, to systematically assess trends in publication, contributions from various countries, institutions, authors, and journals, as well as to examine literature co-citation and keyword distributions within the domain of cytokines for glioma immunotherapy. The application of these methodologies facilitated a detailed exploration of the hotspots, the underlying knowledge structure, and the developments in the field of cytokines for glioma immunotherapy. Results: This bibliometric analysis revealed an exponential growth in annual publications, with the United States, China, and Germany as top contributors. Reviews constituted 17% and research articles 83% of total publications. Analysis of keywords like "interleukin-13," "TGF-beta," and "dendritic cells" indicated progression from foundational cytokine therapies to sophisticated understanding of the tumor microenvironment and immune dynamics. Key research avenues encompassed the tumor microenvironment, epidermal growth factor receptor, clinical trials, and interleukin pathways. This comprehensive quantitative mapping of the glioma immunotherapy cytokine literature provides valuable insights to advance future research and therapeutic development. Conclusion: This study has identified remaining knowledge gaps regarding the role of cytokines in glioma immunotherapy. Future research will likely focus on the tumor microenvironment, cancer vaccines, epidermal growth factor receptor, and interleukin-13 receptor alpha 2. Glioma immunotherapy development will continue through investigations into resistance mechanisms, microglia and macrophage biology, and interactions within the complex tumor microenvironment.

Gastrodin Attenuates Colitis and Prevents Tumorigenesis in Mice by Interrupting TLR4/MD2/NF-κB Signaling Transduction

INTRODUCTION

Chronic inflammation is one of the causative factors for tumorigenesis. Gastrodin is a main active ingredient isolated from Gastrodia elata Blume, a famous medicinal herb with a long edible history.

AIM

This study aimed to explore the effects of gastrodin on colitis-associated carcinogenesis (CRC) in mice and to elucidate its potential molecular mechanisms.

METHODS

Balb/c mice were induced with azoxymethane (AOM) and dextran sulfate sodium (DSS) for 12 weeks. Gastrodin (50 mg/kg) was administered via oral gavage three times per week until the end of the experiment. Disease indexes, including body weight, bloody diarrhea, colon length, histopathological score, and tumor size, were measured. Tumor cell proliferation was evaluated by BrdU incorporation assay and tumor cell cytotoxicity was assessed by cell counting kit (CCK-8). The expression levels of toll-like receptor 4 (TLR4)/nuclear factor kappa-B (NF-κB) signaling molecules, NF-κB luciferase, and pro-inflammatory cytokines were determined by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR), immunoblotting, immunohistochemistry (IHC), enzyme-linked immunosorbent assay (ELISA), or reporter gene assays. The binding affinity between gastrodin and myeloid differentiation protein-2 (MD2) was analyzed by molecular docking and cellular thermal shift assay (CETSA).

RESULTS

Gastrodin administration was demonstrated to mitigate various CRC-related symptoms in mice, including weight loss, diarrhea, and tissue abnormalities. Notably, gastrodin suppressed tumor cell growth during colitis- associated tumorigenesis, resulting in fewer and smaller adenomas in the colon. Unlike irinotecan, a broadspectrum antitumor drug, gastrodin did not exhibit apparent cytotoxicity in various colorectal adenocarcinoma cell lines. Additionally, gastrodin downregulated TLR4/NF-κB signaling molecules and pro-inflammatory mediators in mice and macrophages. Molecular docking and CETSA experiments suggested that gastrodin binds to the MD2 protein, potentially interfering with the recognition of lipopolysaccharide (LPS) by TLR4, leading to NF-κB pathway inhibition.

CONCLUSION

This study provides evidence for the first time that gastrodin attenuated colitis and prevented colitisrelated carcinogenesis in mice, at least partially, by diminishing tumor-promoting cytokines through the interruption of TLR4/MD2/NF-κB signaling transduction.

Cytokine Profile in Development of Glioblastoma in Relation to Healthy Individuals

Cytokines play an essential role in the control of tumor cell development and multiplication. However, the available literature provides ambiguous data on the involvement of these proteins in the formation and progression of glioblastoma (GBM). This study was designed to evaluate the inflammatory profile and to investigate its potential for the identification of molecular signatures specific to GBM. Fifty patients aged 66.0 ± 10.56 years with newly diagnosed high-grade gliomas and 40 healthy individuals aged 71.7 ± 4.9 years were included in the study. White blood cells were found to fall within the referential ranges and were significantly higher in GBM than in healthy controls. Among immune cells, neutrophils showed the greatest changes, resulting in elevated neutrophil-to-lymphocyte ratio (NLR). The neutrophil count inversely correlated with survival time expressed by Spearman's coefficient rs = -0.359 (p = 0.010). The optimal threshold values corresponded to 2.630 × 103/µL for NLR (the area under the ROC curve AUC = 0.831, specificity 90%, sensitivity 76%, the relative risk RR = 7.875, the confidence intervals 95%CI 3.333-20.148). The most considerable changes were recorded in pro-inflammatory cytokines interleukin IL-1β, IL-6, and IL-8, which were approx. 1.5-2-fold higher, whereas tumor necrosis factor α (TNFα) and high mobility group B1 (HMGB1) were lower in GBM than healthy control (p < 0.001). The results of the ROC, AUC, and RR analysis of IL-1β, IL-6, IL-8, and IL-10 indicate their high diagnostics potential for clinical prognosis. The highest average RR was observed for IL-6 (RR = 2.923) and IL-8 (RR = 3.151), which means there is an approx. three-fold higher probability of GBM development after exceeding the cut-off values of 19.83 pg/mL for IL-6 and 10.86 pg/mL for IL-8. The high values of AUC obtained for the models NLR + IL-1β (AUC = 0.907), NLR + IL-6 (AUC = 0.908), NLR + IL-8 (AUC = 0.896), and NLR + IL-10 (AUC = 0.887) prove excellent discrimination of GBM patients from healthy individuals and may represent GBM-specific molecular signatures.

C-Reactive Protein: Pathophysiology, Diagnosis, False Test Results and a Novel Diagnostic Algorithm for Clinicians

The current literature provides a body of evidence on C-Reactive Protein (CRP) and its potential role in inflammation. However, most pieces of evidence are sparse and controversial. This critical state-of-the-art monography provides all the crucial data on the potential biochemical properties of the protein, along with further evidence on its potential pathobiology, both for its pentameric and monomeric forms, including information for its ligands as well as the possible function of autoantibodies against the protein. Furthermore, the current evidence on its potential utility as a biomarker of various diseases is presented, of all cardiovascular, respiratory, hepatobiliary, gastrointestinal, pancreatic, renal, gynecological, andrological, dental, oral, otorhinolaryngological, ophthalmological, dermatological, musculoskeletal, neurological, mental, splenic, thyroid conditions, as well as infections, autoimmune-supposed conditions and neoplasms, including other possible factors that have been linked with elevated concentrations of that protein. Moreover, data on molecular diagnostics on CRP are discussed, and possible etiologies of false test results are highlighted. Additionally, this review evaluates all current pieces of evidence on CRP and systemic inflammation, and highlights future goals. Finally, a novel diagnostic algorithm to carefully assess the CRP level for a precise diagnosis of a medical condition is illustrated.

Identification of a novel defined inflammation-related long noncoding RNA signature contributes to predicting prognosis and distinction between the cold and hot tumors in bladder cancer

Purpose

Bladder cancer (BLCA) is one of the most frequently diagnosed urological malignancies and is the 4th most common cancer in men worldwide. Molecular targets expressed in bladder cancer (BLCA) are usually used for developing targeted drug treatments. However, poor prognosis and poor immunotherapy efficacy remain major challenges for BLCA. Numerous studies have shown that long non-coding RNAs (LncRNAs) play an important role in the development of cancer. However, the role of lncRNAs related to inflammation in BLCA and their prognostic value remain unclear. Therefore, this study is aimed to explore new potential biomarkers that can predict cancer prognosis.

Methods

We downloaded BLCA-related RNA sequencing data from The Cancer Genome Atlas (TCGA) and searched for inflammation-related prognostic long non-coding RNAs (lncRNAs) by univariate Cox (uniCox) regression and co-expression analysis. We used the least absolute shrinkage and selection operator (LASSO) analysis to construct an inflammation-related lncRNA prognosis risk model. Samples were divided into high-risk score (HRS) group and low-risk score (LRS) group based on the median value of risk scores. The independent variable factors were identified by univariate Cox (uni-Cox) and multivariate Cox (multi-Cox) regression analyses, and receiver operating characteristic (ROC) curves were used to compare the role of different factors in predicting outcomes. Nomogram and Calibration Plot were generated by the R package rms to analyze whether the prediction results are correct and show good consistency. Correlation coefficients were calculated by Pearson analysis. The Kaplan-Meier method was used to assess the prognostic value. The expression of 7 lncRNAs related with inflammation was also confirmed by qRT-PCR in BLCA cell lines. Kyoto Encyclopedia of Gene and Genome (KEGG) pathways that were significantly enriched (P &lt; 0.05) in each risk group were identified by the GSEA software. The R package pRRophetic was used to predict the IC50 of common chemotherapeutic agents. TIMER, XCELL, QUANTISEQ, MCPCOUNTER, EPIC and CIBERSORT were applied to quantify the relative proportions of infiltrating immune cells. We also used package ggpubr to evaluate TME scores and immune checkpoint activation in LRS and HRS populations. R package GSEABase was used to analyze the activity of immune cells or immune function. Different clusters of principal component analysis (PCA), t-distribution random neighborhood embedding (t-SNE), and Kaplan-Meier survival were analyzed using R package Rtsne’s. The R package ConsensesClusterPlus was used to class the inflammation-related lncRNAs.

Results

In this study, a model containing 7 inflammation-related lncRNAs was constructed. The calibration plot of the model was consistent with the prognosis prediction outcomes. The 1-, 3-, and 5-year ROC curve (AUC) were 0.699, 0.689, and 0.699, respectively. High-risk patients were enriched in lncRNAs related with tumor invasion and immunity, and had higher levels of immune cell infiltration and immune checkpoint activation. Hot tumors and cold tumors were effectively distinguished by clusters 2 and 3 and cluster 1, respectively, which indicated that hot tumors are more susceptible to immunotherapy.

Conclusion

Our study showed that inflammation-related LncRNAs are closely related with BLCA, and inflammation-related lncRNA can accurately predict patient prognosis and effectively differentiate between hot and cold tumors, thus improving individualized immunotherapy for BLCA patients. Therefore, this study provides an effective predictive model and a new therapeutic target for the prognosis and clinical treatment of BLCA, thus facilitating the development of individualized tumor therapy.

Plasma nanoDSF Denaturation Profile at Baseline Is Predictive of Glioblastoma EGFR Status

Glioblastoma (GBM) is the most frequent and aggressive primary brain tumor in adults. Recently, we demonstrated that plasma denaturation profiles of glioblastoma patients obtained using Differential Scanning Fluorimetry can be automatically distinguished from healthy controls with the help of Artificial Intelligence (AI). Here, we used a set of machine-learning algorithms to automatically classify plasma denaturation profiles of glioblastoma patients according to their EGFR status. We found that Adaboost AI is able to discriminate EGFR alterations in GBM with an 81.5% accuracy. Our study shows that the use of these plasma denaturation profiles could answer the unmet neuro-oncology need for diagnostic predictive biomarker in combination with brain MRI and clinical data, in order to allow for a rapid orientation of patients for a definitive pathological diagnosis and then treatment. We complete this study by showing that discriminating another mutation, MGMT, seems harder, and that post-surgery monitoring using our approach is not conclusive in the 48 h that follow the surgery.

Predictive models and survival analysis of postoperative mental health disturbances in adult glioma patients

Background and Objectives

Patients with primary malignant brain tumors may experience mental health disturbances that can significantly affect their daily life. This study aims to identify risk factors and generate predictive models for postoperative mental health disturbances (PMHDs) in adult glioma patients in accordance with different clinical periods; additionally, survival analyses will be performed.

Methods

This longitudinal cohort study included 2,243 adult patients (age at diagnosis ≥ 18 years) with nonrecurrent glioma who were pathologically diagnosed and had undergone initial surgical resection. Six indicators of distress, sadness, fear, irritability, mood and enjoyment of life, ranging from 0-10, were selected to assess PMHDs in glioma patients in the third month after surgery, mainly referring to the M.D. Anderson Symptom Inventory Brain Tumor Module (MDASI-BT). Factor analysis (FA) was applied on these indicators to divide participants into PMHD and control groups based on composite factor scores. Survival analyses were performed, and separate logistic regression models were formulated for preoperative and postoperative factors predicting PMHDs.

Results

A total of 2,243 adult glioma patients were included in this study. Based on factor analysis results, 300 glioma patients had PMHDs in the third postoperative month, and the remaining 1,943 were controls. Candidate predictors for PMHDs in the preoperative model were associated with age, clinical symptoms (intracranial space-occupying lesion, muscle weakness and memory deterioration), and tumor location (corpus callosum, basal ganglia and brainstem), whereas age, clinical symptoms (nausea and memory deterioration), tumor location (basal ganglia and brainstem), hospitalization days, WHO grade 4, postoperative chemotherapy or radiotherapy and postoperative Karnofsky Performance Scale (KPS) served as important factors in the postoperative model. In addition, the median overall survival (OS) time for glioma patients with PMHDs was 19 months, compared to 13 months for glioblastoma, IDH-wild type (GBM) patients with PMHDs.

Conclusion

The risk factors for PMHDs were identified. These findings may provide new insights into predicting the probability of PMHD occurrence in glioma patients in addition to aiding effective early intervention and improving prognosis based on different clinical stages.

Pretreatment Pan-Immune-Inflammation Value Efficiently Predicts Survival Outcomes in Glioblastoma Multiforme Patients Receiving Radiotherapy and Temozolomide

Objectives

The purpose of this study was to determine the predictive significance of pretreatment pan-immune-inflammation value (PIV) in patients with newly diagnosed glioblastoma multiforme (GBM) who received postsurgical radiation (RT) and concurrent plus adjuvant temozolomide (TMZ).

Methods

The outcomes of 204 newly diagnosed GBM patients were analyzed retrospectively. Each eligible patient's PIV was calculated using the findings of peripheral blood platelet (P), monocyte (M), neutrophil (N), and lymphocyte (L) counts obtained on the first day of therapy: PIV = P × M × N ÷ L. We used receiver operating characteristic (ROC) curve analysis to discover the ideal cutoff values for PIV concerning progression-free (PFS) and overall survival (OS) outcomes. The primary and secondary end-points were the OS and PFS divergences across the PIV groups.

Results

In ROC curve analysis, the optimal PIV cutoff was 385, which substantially interacted with PFS and OS results and categorized patients into low PIV (L-PIV; N = 75) and high PIV (H-PIV; N = 129) groups. Comparative survival analyses showed that the patients in the H-PIV group had significantly shorter median PFS (6.0 vs. 16.6 months; P < 0.001) and OS (11.1 vs. 22.9 months; P < 0.001) durations than those in the L-PIV group. The results of multivariate Cox regression analysis indicated an independent and significant connection between an H-PIV measure and shorter PFS and OS outcomes.

Conclusions

The novel PIV was able to independently stratify newly diagnosed GBM patients into two groups with fundamentally different PFS and OS outcomes following RT and concurrent plus adjuvant TMZ.

Oncolytic viruses as a promising therapeutic strategy against the detrimental health impacts of air pollution: The case of glioblastoma multiforme

Human livelihood highly depends on applying different sources of energy whose utilization is associated with air pollution. On the other hand, air pollution may be associated with glioblastoma multiforme (GBM) development. Unlike other environmental causes of cancer (e.g., irradiation), air pollution cannot efficiently be controlled by geographical borders, regulations, and policies. The unavoidable exposure to air pollution can modify cancer incidence and mortality. GBM treatment with chemotherapy or even its surgical removal has proven insufficient (100% recurrence rate; patient's survival mean of 15 months; 90% fatality within five years) due to glioma infiltrative and migratory capacities. Given the barrage of attention and research investments currently plowed into next-generation cancer therapy, oncolytic viruses are perhaps the most vigorously pursued. Provision of an insight into the current state of the research and future direction is essential for stimulating new ideas with the potentials of filling research gaps. This review manuscript aims to overview types of brain cancer, their burden, and different causative agents. It also describes why air pollution is becoming a concerning factor. The different opinions on the association of air pollution with brain cancer are reviewed. It tries to address the significant controversy in this field by hypothesizing the air-pollution-brain-cancer association via inflammation and atopic conditions. The last section of this review deals with the oncolytic viruses, which have been used in, or are still under clinical trials for GBM treatment. Engineered adenoviruses (i.e., DNX-2401, DNX-2440, CRAd8-S-pk7 loaded Neural stem cells), herpes simplex virus type 1 (i.e., HSV-1 C134, HSV-1 rQNestin34.5v.2, HSV-1 G207, HSV-1 M032), measles virus (i.e., MV-CEA), parvovirus (i.e., ParvOryx), poliovirus (i.e., Poliovirus PVSRIPO), reovirus (i.e., pelareorep), moloney murine leukemia virus (i.e., Toca 511 vector), and vaccinia virus (i.e., vaccinia virus TG6002) as possible life-changing alleviations for GBM have been discussed. To the best of our knowledge, this review is the first review that comprehensively discusses both (i) the negative/positive association of air pollution with GBM; and (ii) the application of oncolytic viruses for GBM, including the most recent advances and clinical trials. It is also the first review that addresses the controversies over air pollution and brain cancer association. We believe that the article will significantly appeal to a broad readership of virologists, oncologists, neurologists, environmentalists, and those who work in the field of (bio)energy. Policymakers may also use it to establish better health policies and regulations about air pollution and (bio)fuels exploration, production, and consumption.

The Mechanism Study of Common Flavonoids on Antiglioma Based on Network Pharmacology and Molecular Docking

BACKGROUND

Glioma is the most common primary intracranial tumor in adult patients. Among them, glioblastoma is a highly malignant one with a poor prognosis. Flavonoids are a class of phenolic compounds widely distributed in plants and have many biological functions, such as anti-inflammatory, antioxidant, antiaging, and anticancer. Nowadays, flavonoids have been applied to the therapy of glioma; however, the molecular mechanism underlying the therapeutic effects has not been fully elaborated. This study was carried out to explore the mechanism of selected active flavonoid compounds in treating glioma using network pharmacology and molecular docking approaches.

METHODS

Active ingredients and associated targets of flavonoids were acquired by using the Traditional Chinese Medicine Database and Analysis Platform (TCMSP) and Swiss TargetPrediction platform. Genes related to glioma were obtained from the GeneCards and DisGeNET databases. The intersection targets between flavonoid targets and glioma-related genes were used to construct protein-protein interaction (PPI) network via the STRING database, and the results were analyzed by Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed and displayed by utilizing the Metascape portal and clusterProfiler R package. Molecular docking was carried out by iGEMDOCK and SwissDock, and the results were visually displayed by UCSF Chimera software.

RESULTS

Eighty-four active flavonoid compounds and 258 targets overlapped between flavonoid targets and glioma-related genes were achieved. PPI network revealed potential therapeutic targets, such as AKT1, EGFR, VEGFA, MAPK3, and CASP3, based on their node degree. GO and KEGG analyses showed that core targets were mainly enriched in the PI3K-Akt signaling pathway. Molecular docking simulation indicated that potential glioma-related targets-MAPK1 and HSP90AA1 were bounded more firmly with epigallocatechin-3-gallate (EGCG) than with quercetin.

CONCLUSIONS

The findings of this study indicated that selected active flavonoid compounds might play therapeutic roles in glioma mainly through the PI3K-Akt signaling pathway. Moreover, EGCG had the potential antiglioma activity by targeting MAPK1 and HSP90AA1.

The Clinical Value of High-Quality Nursing in Concurrent Radiotherapy and Chemotherapy after Glioma Surgery and Its Influence on the Stress Indicators Cor, ACTH, and CRP

Objective

The purpose of this study is to explore the clinical value of high-quality nursing in concurrent radiotherapy and chemotherapy after glioma surgery and its influence on the stress indicators such as cortisol (Cor), adrenocorticotrophic hormone (ACTH), and C-reactive protein (CRP).

Methods

A total of 94 glioma patients diagnosed and treated in our hospital were randomly divided into a research group and a control group, with 47 cases in each group. Both groups of patients were given concurrent radiotherapy and chemotherapy. On this basis, patients in the control group were given basic care, while patients in the research group were given a combination of basic care and high-quality care. The nursing satisfaction and adverse reactions of the two groups were compared. The pain degree and the levels of stress indicators Cor, ACTH, and CRP at different time points were compared between the two groups. The sleep quality, bad mood, and quality of life before and after nursing were compared between the two groups.

Results

After nursing, the nursing satisfaction of the research group (95.74%) was higher than that of the control group (80.85%), and the difference between the two groups was statistically significant (X² = 11.678, P < 0.05). There was no significant difference between patients in the Visual Analogue Scale (VAS) score and the levels of stress indicators Cor, ACTH, and CRP at the T1 time point between the two groups (P > 0.05). With the passage of time, the levels of Cor and ACTH of the two groups showed an upward trend. At T4, the increased levels of Cor and ACTH in the research group were less than those in the control group, and the difference was statistically significant (P < 0.05). The VAS scores and CRP levels of the two groups showed an upward trend at T1 and T2 and a downward trend at T3 and T4. And, at T4, the decrease in CRP level of the research group was greater than that in the control group, and the difference was statistically significant (P < 0.05). Before nursing, there was no statistically significant difference between two groups of patients in the time to fall asleep, sleep time, number of awakenings, SAS score, self-rating depression scale (SDS) score, quality of life index scores, and total scores (P > 0.05). After nursing, the time to fall asleep and the number of awakenings in the two groups of patients showed an upward trend, and the increase in the control group was higher (P < 0.05). The sleep time of the two groups showed a downward trend, and the degree of decline in the control group was higher (P < 0.05). After nursing, the SAS score and SDS score of the two groups of patients decreased (^∗P < 0.05), and the decrease in the research group was more obvious (^#P < 0.05). After nursing, the scores of all indicators of the quality of life and the total score of the two groups increased and the score of the research group increased more significantly (P < 0.05). After nursing, the control group had 5 cases of gastrointestinal reactions, 7 cases of bone marrow suppression, 6 cases of leukopenia, 6 cases of thrombocytopenia, and 10 cases of dizziness and nausea. In the research group, there were 1 case of gastrointestinal reaction, 2 cases of bone marrow suppression, 1 case of leukopenia, 1 case of thrombocytopenia, and 2 cases of dizziness and nausea. The difference between the two groups was statistically significant (P < 0.05).

Conclusion

Glioma patients are given high-quality care during the course of concurrent radiotherapy and chemotherapy, which can reduce the pain and bad mood of the patient, reduce the stress response of the patient, and improve the quality of sleep and the quality of life of the patient, thereby improving nursing satisfaction and patients compliance, reducing adverse reactions, and having a good prognosis.

Prognostic value of hematological pre-albumin to fibrinogen ratio in patients with glioma

OBJECTIVE

Hematological biomarkers that reflect host nutritional and inflammation status have been identified to be independent prognostic factors in various malignancies. The aim of the present study was to determine the predictive value of preoperative albumin (ALB), fibrinogen (FIB), pre-albumin (pALB), Albumin to fibrinogen ratio (AFR) and pre-albumin to fibrinogen ratio (PFR) for the prognosis of patients with glioma.

METHOD

X-tile software was used to identify cut-off values of these parameters. Kaplan-Meier survival analysis, univariate and multivariate analyses based on Cox proportional hazards regression model were used to determine whether these markers were associated with the prognosis of patients with glioma. In addition, the Harrell concordance index with variables was used to evaluate the prognostic accuracy.

RESULTS

The results indicated that PFR (HR = 2.827, 95% CI: 1.353-6.122, p = 0.006) is the only independent prognostic factor in patients of glioma along with clinicopathological grade and age. C-index of predicted nomogram including PFR (0.719) for glioma patients was higher than that without PFR (0.699).

CONCLUSIONS

Our findings demonstrated that circulating preoperative PFR might be a potential negative independent prognostic biomarker for glioma individuals.

A Hypoxia-Related Long Non-Coding RNAs Signature Associated With Prognosis in Lower-Grade Glioma

Accumulating evidence suggests that hypoxia microenvironment and long non-coding lncRNAs (lncRNAs) exert critical roles in tumor development. Herein, we aim to develop a hypoxia-related lncRNA (HRL) model to predict the survival outcomes of patient with lower-grade glioma (LGG). The RNA-sequencing data of 505 LGG samples were acquired from The Cancer Genome Atlas (TCGA). Using consensus clustering based on the expression of hypoxia-related mRNAs, these samples were divided into three subsets that exhibit distinct hypoxia content, clinicopathologic features, and survival status. The differentially expressed lncRNAs across the subgroups were documented as candidate HRLs. With LASSO regression analysis, eight informative lncRNAs were selected for constructing the prognostic HRL model. This signature had a good performance in predicting LGG patients’ overall survival in the TCGA cohort, and similar results could be achieved in two validation cohorts from the Chinese Glioma Genome Atlas. The HRL model also showed correlations with important clinicopathologic characteristics such as patients’ age, tumor grade, IDH mutation, 1p/19q codeletion, MGMT methylation, and tumor progression risk. Functional enrichment analysis indicated that the HLR signature was mainly involved in regulation of inflammatory response, complement, hypoxia, Kras signaling, and apical junction. More importantly, the signature was related to immune cell infiltration, estimated immune score, tumor mutation burden, neoantigen load, and expressions of immune checkpoints and immunosuppressive cytokines. Finally, a nomogram was developed by integrating the HRL signature and clinicopathologic features, with a concordance index of 0.852 to estimate the survival probability of LGG patients. In conclusion, our study established an effective HRL model for prognosis assessment of LGG patients, which may provide insights for future research and facilitate the designing of individualized treatment.

A prospective study of inflammatory biomarkers and growth factors and risk of glioma in the UK Biobank

PURPOSE

The role of growth factors and inflammation in the onset of glioma is poorly understood, and conflicting reports of associations of circulating IGF-1 and inflammatory biomarkers with glioma risk exist in the literature. We examined associations between C-reactive protein (CRP), white blood cell count (WBC), neutrophil-to-lymphocyte ratio (NLR), and insulin-like growth factor-1 (IGF-1) and glioma risk in the UK Biobank cohort.

METHODS

Hazard ratios (HR) and 95% confidence intervals (CI) for glioma according to circulating biomarkers concentrations were calculated using Cox proportional hazards regression, adjusted for age, sex, race, and education. Analyses were conducted separately for glioma overall and by glioma subtype.

RESULTS

We identified 417 incident glioma cases among 428,537 participants with 3,255,815 person-years of follow up. Weak, non-significant associations were observed with increasing levels of these biomarkers for risk of glioma overall or by glioma subtype. Among women only, IGF-1 in the highest quartile was positively associated with glioma risk compared to the lowest quartile (HR=1.64, 95%CI: 1.03-2.60, p-trend=0.08), as was NLR (HR=1.54, 95%CI: 1.00-2.39, p-trend=0.05).

CONCLUSION

In this prospective cohort, we found no significant associations between the inflammatory biomarkers CRP and WBC and the development of glioma. NLR and IGF-1 were associated with risk in women, but not men. When considered with previous studies, further investigation of NLR and IGF-1 as markers of glioma risk appears warranted, particularly in women.

Development and Validation of an Mesenchymal-Related Long Non-Coding RNA Prognostic Model in Glioma

Glioma is well known as the most aggressive and prevalent primary malignant tumor in the central nervous system. Molecular subtypes and prognosis biomarkers remain a promising research area of gliomas. Notably, the aberrant expression of mesenchymal (MES) subtype related long non-coding RNAs (lncRNAs) is significantly associated with the prognosis of glioma patients. In this study, MES-related genes were obtained from The Cancer Genome Atlas (TCGA) and the Ivy Glioblastoma Atlas Project (Ivy GAP) data sets of glioma, and MES-related lncRNAs were acquired by performing co-expression analysis of these genes. Next, Cox regression analysis was used to establish a prognostic model, that integrated ten MES-related lncRNAs. Glioma patients in TCGA were divided into high-risk and low-risk groups based on the median risk score; compared with the low-risk groups, patients in the high-risk group had shorter survival times. Additionally, we measured the specificity and sensitivity of our model with the ROC curve. Univariate and multivariate Cox analyses showed that the prognostic model was an independent prognostic factor for glioma. To verify the predictive power of these candidate lncRNAs, the corresponding RNA-seq data were downloaded from the Chinese Glioma Genome Atlas (CGGA), and similar results were obtained. Next, we performed the immune cell infiltration profile of patients between two risk groups, and gene set enrichment analysis (GSEA) was performed to detect functional annotation. Finally, the protective factors DGCR10 and HAR1B, and risk factor SNHG18 were selected for functional verification. Knockdown of DGCR10 and HAR1B promoted, whereas knockdown of SNHG18 inhibited the migration and invasion of gliomas. Collectively, we successfully constructed a prognostic model based on a ten MES-related lncRNAs signature, which provides a novel target for predicting the prognosis for glioma patients.

Biological correlates before esophageal cancer screening and after diagnosis

Almost 50% of the world's esophageal cancer (EC) cases occur in China, and the impact of cancer screening has long been a controversial topic. The study was designed to evaluate the biological correlates of EC screening and subsequent diagnosis in China. Based on the national cohort of esophageal cancer program, a prospective multicenter study in high-risk regions was conducted from 2017 to 2019. 61 participants received twice esophageal endoscopy screening and pathological biopsy successively (with a mean follow-up of 14.03 months). Box-Cox-power transformation and two-way repeated measures ANOVA were used to evaluate hormone cortisol and immunoglobulin (IgA, IgG, IgM) levels in plasma, reflecting their stress, immune function, and biological correlates before screening and after knowing the diagnosis. The median of cortisol, IgA, IgG, and IgM in pre-screening was 15.46 ug/dL, 1.86 g/L, 12.14 g/L, and 0.91 g/L, corresponding value at post-diagnosis was 15.30 ug/dL, 2.00 g/L, 12.79 g/L, and 0.94 g/L, respectively. No significant differences in biological indicators were found between normal and esophagitis and low-grade intraepithelial neoplasia before screening and after diagnosis. After normality transformation, cortisol, IgA, IgG and IgM levels were (0.25 ± 0.04) U/mL, (0.72 ± 0.13) (g/L), (2.44 ± 0.22) (g/L) and (0.98 ± 0.25) (g/L) before screening, (0.25 ± 0.05) U/mL, (0.70 ± 0.13) (g/L), (2.48 ± 0.21) (g/L) and (1.00 ± 0.25) (g/L) after diagnosis, respectively. Repeated Measures ANOVA showed that the main effects were significant on IgA levels between pre-screening and post-diagnosis (P = 0.019). No interaction effects on biological levels between pre-post screening and esophageal pathology, anxiety states (all P > 0.05). Little biological correlates were found both before screening and after diagnosis. Cortisol and IgA dropped less significantly, while IgM and IgA were increased slightly after diagnosis. Further multi-round longitudinal studies are needed to validate these results.

A Novel Inflammatory lncRNAs Prognostic Signature for Predicting the Prognosis of Low-Grade Glioma Patients

Background

As immunotherapy has received attention as new treatments for brain cancer, the role of inflammation in the process of glioma is of particular importance. Increasing studies have further shown that long non-coding RNAs (lncRNAs) are important factors that promote the development of glioma. However, the relationship between inflammation-related lncRNAs and the prognosis of glioma patients remains unclear. The purpose of this study is to construct and validate an inflammation-related lncRNA prognostic signature to predict the prognosis of low-grade glioma patients.

Methods

By downloading and analyzing the gene expression data and clinical information of the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) patients with low-grade gliomas, we could screen for inflammatory gene-related lncRNAs. Furthermore, through Cox and the Least Absolute Shrinkage and Selection Operator regression analyses, we established a risk model and divided patients into high- and low-risk groups based on the median value of the risk score to analyze the prognosis. In addition, we analyzed the tumor mutation burden (TMB) between the two groups based on somatic mutation data, and explored the difference in copy number variations (CNVs) based on the GISTIC algorithm. Finally, we used the MCPCounter algorithm to study the relationship between the risk model and immune cell infiltration, and used gene set enrichment analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to explore the enrichment pathways and biological processes of differentially expressed genes between the high- and low-risk groups.

Results

A novel prognostic signature was constructed including 11 inflammatory lncRNAs. This risk model could be an independent prognostic predictor. The patients in the high-risk group had a poor prognosis. There were significant differences in TMB and CNVs for patients in the high- and low-risk groups. In the high-risk group, the immune system was activated more significantly, and the expression of immune checkpoint-related genes was also higher. The GSEA, GO, and KEGG analyses showed that highly expressed genes in the high-risk group were enriched in immune-related processes, while lowly expressed genes were enriched in neuromodulation processes.

Conclusion

The risk model of 11 inflammation-related lncRNAs can serve as a promising prognostic biomarker for low-grade gliomas patients.

Cytokine Profiling in Plasma from Patients with Brain Tumors Versus Healthy Individuals using 2 Different Multiplex Immunoassay Platforms

We compared the performance of two 96-well multiplex immunoassay platforms in assessing plasma cytokine concentrations in patients with glioblastoma (GBM; n = 27), individuals with melanoma, breast or lung cancer metastases to the brain (n = 17), and healthy volunteers (n = 11). Assays included a bead-based fluorescence MILLIPLEX^® assay/Luminex (LMX) platform and 4 planar electrochemiluminescence kits from Meso Scale Discovery (MSD). The LMX kit evaluated 21 cytokines and the 3 MSD kits evaluated 20 cytokines in total, with 19 overlapping human cytokines between platforms (GM-CSF, IFNγ, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, IL-17A, IL-21, IL-23, MIP-1α, MIP-1β, MIP-3α, TNFα). The MSD platform had lower LLoQs (lower limits of quantification) than LMX for 17/19 cytokines, and higher LLoQs for IFN-γ and IL-21. The ULoQs were higher in LMX versus MSD assays for 17/19 shared analytes, but lower than MSD for IL-17A and IL-21. With LMX, all 19 shared analytes were quantifiable in each of 55 samples. Although MSD recombinant protein standard curves indicated lower LLoQs than LMX for most cytokines, MSD detected 7/19 (37%) native analytes in <75% of samples, including 0% detection for IL-21 and 8% for IL-23. The LMX platform categorized identical samples at greater concentrations than the MSD system for most analytes (MIP-1β the sole exception), sometimes by orders of magnitude. This mismatched quantification paradigm was supported by Bland-Altman analysis. LMX identified significantly elevated levels of 10 of 19 circulating cytokines in GBM: GM-CSF, IFN-γ, IL-1β, IL-5, IL-10, IL-17A, IL-21, IL-23, MIP-1α, and MIP-3α, consistent with prior findings and confirming the utility of applying appropriate multiplex immunoassay technologies toward developing a cytokine signature profile for GBM.

Baseline Serum C-Reactive Protein and Plasma Fibrinogen-Based Score in the Prediction of Survival in Glioblastoma

Objective: The present study investigates a score based on baseline C-reactive protein (CRP) and fibrinogen values (FC score) in 173 consecutive glioblastoma (GBM) patients.

Methods: The optimal cut-off value for fibrinogen and CRP was defined as 3.5 g/dl and 3.0 mg/L, respectively, according to previous reports. Patients with elevated CRP and fibrinogen were classified with a score of 2, those with an elevation of only one of these parameters were allocated a score of 1, and those without any abnormalities were assigned a score of 0.

Results: No significant differences in age, gender, tumor area, molecular pathology, physical status, or extent of resection were identified among the three groups defined by this score. Univariate survival analysis demonstrated that a high baseline FC score (≥1) is significantly associated with a shortened overall survival (OS) (HR: 1.52, 95% CI: 1.05–2.20, p = 0.027). A multivariate Cox regression analysis considering age (>65/≤65), extent of resection (GTR/STR), MGMT promoter status (hypermethylated/non-hypermethylated), and FC score (0/≥1) confirmed that an elevated FC score (≥1) is an independent predictor of shortened OS (HR: 1.71, 95% CI: 1.16–2.51, p = 0.006).

Conclusions: The baseline fibrinogen and CRP score thus serves as an independent predictor of OS in GBM. Further investigations of the role of inflammation in the prediction of a prognosis are needed.

High expression of microRNA 221 is a poor predictor for glioma

BACKGROUND

MicroRNA 221 has been found to be a good marker for several cancers. Some studies also focused on the relationship between microRNA 221 and glioma. However, the results are controversial. We aimed to systematically evaluate the prognostic role of microRNA 221 in glioma through performing a meta-analysis.

METHODS

The articles which were included in our study were searched on the Web of Science, EMBASE, PubMed, Cochrane Library and China National Knowledge Infrastructure. The basic characteristics and relevant data were extracted. Hazard ratios (HRs) with 95% confidence intervals (CIs) were pooled to evaluate the prognostic role of microRNA 221 in glioma.

RESULTS

Eight studies with 1069 patients were included. We systematically evaluated the role of microRNA 221 for overall survival (OS) and disease free survival (DFS) in glioma patients (HR for OS = 1.66, 95% CI, 1.34-2.04; HR for DFS = 1.14, 95% CI, 1.02-1.26). Subgroup analyses were performed according to the nation of the studies, the origin of the samples, the stage of the tumors, the cut-off value, and the method for detecting the microRNA 221. No significant publication bias was found (P = .133).

CONCLUSION

In conclusion, high expression of microRNA 221 was related to poor prognosis of glioma. These findings may assist future exploration on microRNA 221 and help predict the prognosis of glioma. However, due to the significant heterogeneity of these studies, more studies are warranted.

The Value of Laboratory Parameters for Anemia, Renal Function, Systemic Inflammation and Nutritional Status as Predictors for Outcome in Elderly Patients with Head-and-Neck Cancers

The purpose of this study was to evaluate the value of routine blood markers regarding their predictive potential for treatment outcomes of elderly head-and-neck squamous cell carcinoma (HNSCC) patients. In total, 246 elderly HNSCC patients (≥65 years) undergoing (chemo)radiotherapy from 2010 to 2018 were analyzed for treatment outcomes, depending on their hemoglobin, glomerular filtration rate (GFR), C-reactive protein (CRP) and albumin values, representing anemia, kidney function, inflammation and nutrition status, respectively. Local/locoregional control, progression-free and overall survival (OS) were calculated using the Kaplan–Meier method. Cox analyses were performed to examine the influence of blood parameters on oncological outcomes. In the univariate Cox regression analysis, hemoglobin ≤ 12 g/dL (HR = 1.536, p < 0.05), a GFR ≤ 60 mL/min/1.73 m² (HR = 1.537, p < 0.05), a CRP concentration > 5 mg/L (HR = 1.991, p < 0.001) and albumin levels ≤ 4.2 g/dL (HR = 2.916, p < 0.001) were significant risk factors for OS. In the multivariate analysis including clinical risk factors, only performance status (HR = 2.460, p < 0.05) and baseline albumin (HR = 2.305, p < 0.05) remained significant prognosticators. Additionally, baseline anemia correlated with the prevalence of higher-grade chronic toxicities. We could show for the first time that laboratory parameters for anemia (and at least partly, tumor oxygenation), decreased renal function, inflammation and reduced nutrition status are associated with impaired survival in elderly HNSCC patients undergoing (chemo)radiotherapy.

Relationship between circulating inflammatory factors and glioma risk and prognosis: A meta-analysis

BACKGROUND

Inflammatory factors have been considered a significant factor contributing to the development and progression of glioma. However, the relationship between circulating inflammatory factors and glioma risk as well as their prognostic values in glioma patients is still inconclusive. Here, we performed a meta-analysis to address this issue.

METHODS

Relevant articles were identified through PubMed, EMBASE, the Cochrane Library, Web of Science, Wanfang database, and China National Knowledge Infrastructure (CNKI) from inception to February 2019. The weighted mean differences (WMDs) or standard mean differences (SMDs) with 95% confidence intervals (CIs) were used to describe the predictive ability of the levels of circulating inflammatory factors on glioma risk. To evaluate the prognostic values of the circulating inflammatory factors in glioma, hazard ratios (HRs) with 95% CIs were used.

RESULTS

Thirty-one studies comprising 2587 patients were included. The overall analysis showed that increased circulating interleukin-6 (IL-6) [SMD 0.81 (95% CI: 0.21-1.40; P = .008)], interleukin-8 (IL-8) [SMD 1.01 (95% CI: 0.17-1.84; P = .018)], interleukin-17 (IL-17) [SMD 1.12 (95% CI: 0.26-1.98; P = .011)], tumor necrosis factor-α (TNF-α) [SMD 1.80 (95% CI: 1.03-2.56; P = .000)], transforming growth factor-β (TGF-β) [SMD 10.55 (95% CI: 5.59-15.51; P = .000)], and C-reactive protein (CRP) [SMD 0.95 (95% CI: 0.75-1.15; P = .000)] levels were significantly associated with glioma risk. On the other hand, our results showed that circulating IL-6 [HR 1.10 (95% CI: 1.05-1.16; P = .000)] and CRP [HR 2.02 (95% CI: 1.52-2.68; P = .000)] levels were highly correlated with a poor overall survival (OS) rate in glioma patients.

CONCLUSION

Our results indicate that increased circulating IL-6, IL-8, IL-17, TNF-α, TGF-β, and CRP levels are significantly associated with increased glioma risk. Moreover, our meta-analysis suggests that circulating IL-6 and CRP may serve as powerful biomarkers for a poor prognosis in glioma patients.