Insights about circadian clock in glioma: From molecular pathways to therapeutic drugs

Circadian rhythm related genes signature in glioma for drug resistance prediction: a comprehensive analysis integrating transcriptomics and machine learning

BACKGROUND

Gliomas, 24% of all primary brain tumors, have diverse histology and poor survival rates, with about 70% recurring due to acquired or de novo resistance. Insomnia in patients is correlated strongly with circadian rhythm disruptions. The correlation between circadian rhythm disorders and drug resistance of some tumors has been proved. However, the precise mechanism underlying the relationship between glioma and circadian rhythm disorders has not been elucidated.

METHODS

Circadian rhythm-related genes (CRRGs) were identified using the least absolute shrinkage and selection operator (LASSO) regression, and stochastic gradient descent (SGD) was performed to form a circadian rhythm-related score (CRRS) model. The studies of immune cell infiltration, genetic variations, differential gene expression pattern, and single cell analysis were performed for exploring the mechanisms of chemotherapy resistance in glioma. The relationship between CRRGs and chemosensitivity was also confirmed by IC 50 (half maximal inhibitory concentration) analysis.

RESULT

Signatures of 16 CRRGs were screened out and identified. Based on the CRRS model, an optimal comprehensive nomogram was created, exhibiting a favorable potential for predicting drug resistance in samples. Immune infiltration, cell-cell communication, and single cell analysis all indicated that high CRRS group was closely related to innate immune cells. IC50 analysis showed that CRRG knockdown enhanced the chemosensitivity of glioma.

CONCLUSION

A significant correlation between CRRGs, drug resistance of glioma, and innate immune cells was found, which might hold a significant role in the drug resistance of glioma.

Green synthesis of metal nanocarriers: A perspective for targeting glioblastoma

Glioblastoma, the most aggressive brain cancer, is challenging to treat owing to the difficulty of crossing the blood-brain barrier, high recurrence rates and significant mortality. This review highlights the potential of green synthesis methods in developing metal nanoparticles (MNPs) as a sustainable solution for drug delivery systems targeting glioblastoma. We explore the unique properties and modes of action of MNPs synthesised through eco-friendly processes by focusing on their bioavailability and precision in brain targeting, and discuss the potential of MNPs to target glioblastoma at the molecular level. Integrating green synthesis into cancer therapeutics represents a novel paradigm shift towards treatments with higher efficacy and lower environmental impact, offering hope in the fight against glioblastoma.

Development and validation of a nomogram to predict overall survival in patients with glioma: a population-based study

AIM

The objective is to investigate the prognostic factors associated with gliomas and to develop and assess a predictive nomogram model connected to survival that may serve as an additional resource for the clinical management of glioma patients.

METHOD

From 2010 to 2015, participants included in the study were chosen from the Surveillance Epidemiology and End Results (SEER) database. Gliomas were definitively diagnosed in each of them. They were divided into the training group and the validation cohort at random (7/3 ratio) using a random number table. To identify the independent predictive markers for overall survival (OS), Cox regression analysis was utilized. Subsequently, the training cohort's survival-related nomogram predictive model for OS was created by incorporating the fundamental patient attributes. Following that, the training cohort's model underwent internal validation. The nomogram model's authenticity and reliability were assessed through the computation of receiver operating characteristic (ROC) curves and concordance index (C-index). To evaluate the degree of agreement between the observed and predicted values in the training and validation cohorts, calibration plots were created.

RESULT

Age, primary site, histological type, surgery, chemotherapy, marital status, and grade were the independent predictive factors for OS in the training cohort, according to Cox regression analysis. Moreover, the nomogram model for predicting 1-year, 3-year, and 5-year OS was built using these variables. The C-indexes of OS for glioma patients in the training cohort and internal validation cohort were found to be 0.779 (95% CI=0.769-0.789) and 0.776 (95% CI=0.760-0.792), respectively, according to the results. The ROC curves also demonstrated good discrimination. Additionally, calibration plots demonstrated a fair amount of agreement.

CONCLUSIONS

In summary, the nomogram prediction model of OS demonstrated a moderate level of reliability in its predictive performance, offering valuable reference data to enable doctors to quickly and easily determine the survival likelihood of patients with gliomas.

Radiotherapy of high-grade gliomas: dealing with a stalemate

This article discusses the studies on radiotherapy of high-grade gliomas published between January 1, 2022, and June 30, 2022, with special reference to their molecular biology basis. The focus was on advances in radioresistance, radiosensitization and the toxicity of radiotherapy treatments. In the first half of 2022, several important advances have been made in understanding resistance mechanisms in high-grade gliomas. Furthermore, the development of several radiosensitization procedures for these deadly tumors, including studies with small molecule radiosensitizers, new fractionation protocols, and new immunostimulatory agents, has progressed in both the preclinical and clinical settings, reflecting the frantic research effort in the field. However, since 2005 our research efforts fail to produce significant improvements to treatment guidelines for high-grade gliomas. Possible reasons for this stalemate and measures to overcome it are discussed.

Gut microbiota in brain tumors: An emerging crucial player

In recent decades, various roles of the gut microbiota in physiological and pathological conditions have been uncovered. Among the many interacting pathways between the host and gut flora, the gut-brain axis has drawn increasing attention and is generally considered a promising way to understand and treat brain tumors, one of the most lethal neoplasms. In this narrative review, we aimed to unveil and dissect the sophisticated mechanisms by which the gut-brain axis exerts its influence on brain tumors. Furthermore, we summarized the latest research regarding the gastrointestinal microbial landscape and the effect of gut-brain axis malfunction on different brain tumors. Finally, we outlined the ongoing developing approaches of microbial manipulation and their corresponding research related to neuro-malignancies. Collectively, we recapitulated the advances in gut microbial alterations along with their potential interactive mechanisms in brain tumors and encouraged increased efforts in this area.

Overview on Common Genes Involved in the Onset of Glioma and on the Role of Migraine as Risk Factor: Predictive Biomarkers or Therapeutic Targets?

Gliomas are relatively rare but fatal cancers, and there has been insufficient research to specifically evaluate the role of headache as a risk factor. Nowadays, gliomas are difficult to cure due to the infiltrative nature and the absence of specific adjuvant therapies. Until now, mutations in hundreds of genes have been identified in gliomas and most relevant discoveries showed specific genes alterations related to migraine as potential risk factors for brain tumor onset. Prognostic biomarkers are required at the time of diagnosis to better adapt therapies for cancer patients. In this review, we aimed to highlight the significant modulation of CLOCK, BMLA1 and NOTCH genes in glioma onset and development, praising these genes to be good as potentially attractive therapeutic markers for brain tumors. A improved knowledge regarding the role of these genes in triggering or modulating glioma maybe the key to early diagnosing brain tumor onset in patients affected by a simple headache. In addition, investigating on these genes we can suggest potential therapeutic targets for treating brain tumors. These considerations open up the possibility of personalized treatments that can target each brain tumor's specific genetic abnormality.