Sex-Specific Differences in Glioblastoma

Contribution of the Testosterone Androgen Receptor–PARD3B Signaling Axis to Tumorigenesis and Malignance of Glioblastoma Multiforme through Stimulating Cell Proliferation and Colony Formation

Background: Glioblastoma multiforme (GBM) is the most common and malignant brain tumor with very poor prognoses. After surgical resection of the primary tumor, rapid proliferation of residual glioblastoma cells is a critical cause explaining tumor malignance and recurrence. In this study, we evaluated de novo roles of the testosterone androgen receptor (AR)–PARD3B signaling axis in the tumorigenesis and malignance of human GBM and the possible related mechanisms. Methods: AR and PARD3B gene expressions and their correlations were mined from The Cancer Genome Atlas (TCGA) database and analyzed using the UALCAN system. Analyses using a real-time PCR, cell proliferation, and colony formation and a loss-of-function strategy by suppressing AR activity with its specific inhibitor, enzalutamide, were then carried out to determine roles of the testosterone AR–PARD3B signaling axis in tumor malignance. Results: Expressions of AR, PARD3B mRNA, and proteins in human GBM tissues were upregulated compared to normal human brain tissues. In contrast, levels of AR and PARD3B mRNA in most TCGA pan-cancer types were downregulated compared to their respective normal tissues. Interestingly, a highly positive correlation between AR and PARD3B gene expressions in human GBM was identified. The results of a bioinformatics search further showed that there were five AR-specific DNA-binding elements predicted in the 5′ promoter of the PARD3B gene. Regarding the mechanisms, exposure of human glioblastoma cells to testosterone induced AR and PARD3B gene expressions and successively stimulated cell proliferation and colony formation. Suppressing AR activity concurrently resulted in significant attenuations of testosterone-induced PARD3B gene expression, cell proliferation, and colony formation in human glioblastoma cells. Conclusions: This study showed the contribution of the testosterone AR–PARD3B signaling axis to the tumorigenesis and malignance of human GBM through stimulating cell proliferation and colony formation. Therefore, the AR-PARD3B signaling axis could be targeted for potential therapy for human GBM.

Metal-Based Nanostructured Therapeutic Strategies for Glioblastoma Treatment-An Update

Glioblastoma (GBM) is the most commonly diagnosed and most lethal primary malignant brain tumor in adults. Standard treatments are ineffective, and despite promising results obtained in early phases of experimental clinical trials, the prognosis of GBM remains unfavorable. Therefore, there is need for exploration and development of innovative methods that aim to establish new therapies or increase the effectiveness of existing therapies. One of the most exciting new strategies enabling combinatory treatment is the usage of nanocarriers loaded with chemotherapeutics and/or other anticancer compounds. Nanocarriers exhibit unique properties in antitumor therapy, as they allow highly efficient drug transport into cells and sustained intracellular accumulation of the delivered cargo. They can be infused into and are retained by GBM tumors, and potentially can bypass the blood-brain barrier. One of the most promising and extensively studied groups of nanostructured therapeutics are metal-based nanoparticles. These theranostic nanocarriers demonstrate relatively low toxicity, thus they might be applied for both diagnosis and therapy. In this article, we provide an update on metal-based nanostructured constructs in the treatment of GBM. We focus on the interaction of metal nanoparticles with various forms of electromagnetic radiation for use in photothermal, photodynamic, magnetic hyperthermia and ionizing radiation sensitization applications.

Small Molecule Inhibitors in Adult High-Grade Glioma: From the Past to the Future

Glioblastoma is the most common primary malignant tumor in the brain and has a dismal prognosis despite patients accepting standard therapies. Alternation of genes and deregulation of proteins, such as receptor tyrosine kinase, PI3K/Akt, PKC, Ras/Raf/MEK, histone deacetylases, poly (ADP-ribose) polymerase (PARP), CDK4/6, branched-chain amino acid transaminase 1 (BCAT1), and Isocitrate dehydrogenase (IDH), play pivotal roles in the pathogenesis and progression of glioma. Simultaneously, the abnormalities change the cellular biological behavior and microenvironment of tumor cells. The differences between tumor cells and normal tissue become the vulnerability of tumor, which can be taken advantage of using targeted therapies. Small molecule inhibitors, as an important part of modern treatment for cancers, have shown significant efficacy in hematologic cancers and some solid tumors. To date, in glioblastoma, there have been more than 200 clinical trials completed or ongoing in which trial designers used small molecules as monotherapy or combination regimens to correct the abnormalities. In this review, we summarize the dysfunctional molecular mechanisms and highlight the outcomes of relevant clinical trials associated with small-molecule targeted therapies. Based on the outcomes, the main findings were that small-molecule inhibitors did not bring more benefit to newly diagnosed glioblastoma, but the clinical studies involving progressive glioblastoma usually claimed “noninferiority” compared with historical results. However, as to the clinical inferiority trial, similar dosing regimens should be avoided in future clinical trials.

Bias and Class Imbalance in Oncologic Data-Towards Inclusive and Transferrable AI in Large Scale Oncology Data Sets

Recent technological developments have led to an increase in the size and types of data in the medical field derived from multiple platforms such as proteomic, genomic, imaging, and clinical data. Many machine learning models have been developed to support precision/personalized medicine initiatives such as computer-aided detection, diagnosis, prognosis, and treatment planning by using large-scale medical data. Bias and class imbalance represent two of the most pressing challenges for machine learning-based problems, particularly in medical (e.g., oncologic) data sets, due to the limitations in patient numbers, cost, privacy, and security of data sharing, and the complexity of generated data. Depending on the data set and the research question, the methods applied to address class imbalance problems can provide more effective, successful, and meaningful results. This review discusses the essential strategies for addressing and mitigating the class imbalance problems for different medical data types in the oncologic domain.

Allopregnanolone Promotes Migration and Invasion of Human Glioblastoma Cells through the Protein Tyrosine Kinase c-Src Activation

Glioblastomas (GBs) are the most aggressive and common primary malignant brain tumors. Steroid hormone progesterone (P4) and its neuroactive metabolites, such as allopregnanolone (3α-THP) are synthesized by neural, glial, and malignant GB cells. P4 promotes cellular proliferation, migration, and invasion of human GB cells at physiological concentrations. It has been reported that 3α-THP promotes GB cell proliferation. Here we investigated the effects of 3α-THP on GB cell migration and invasion, the participation of the enzymes involved in its metabolism (AKR1C1-4), and the role of the c-Src kinase in 3α-THP effects in GBs. 3α-THP 100 nM promoted migration and invasion of U251, U87, and LN229 human-derived GB cell lines. We observed that U251, LN229, and T98G cell lines exhibited a higher protein content of AKR1C1-4 than normal human astrocytes. AKR1C1-4 silencing did not modify 3α-THP effects on migration and invasion. 3α-THP activated c-Src protein at 10 min (U251 cells) and 15 min (U87 and LN229 cells). Interestingly, the pharmacological inhibition of c-Src decreases the promoting effects of 3α-THP on cell migration and invasion. Together, these data indicate that 3α-THP promotes GB migration and invasion through c-Src activation.

RNA Editing in Glioma as a Sexually Dimorphic Prognostic Factor That Affects mRNA Abundance in Fatty Acid Metabolism and Inflammation Pathways

RNA editing alters the nucleotide sequence and has been associated with cancer progression. However, little is known about its prognostic and regulatory roles in glioma, one of the most common types of primary brain tumors. We characterized and analyzed RNA editomes of glioblastoma and isocitrate dehydrogenase mutated (IDH-MUT) gliomas from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas (CGGA). We showed that editing change during glioma progression was another layer of molecular alterations and that editing profiles predicted the prognosis of glioblastoma and IDH-MUT gliomas in a sex-dependent manner. Hyper-editing was associated with poor survival in females but better survival in males. Moreover, noncoding editing events impacted mRNA abundance of the host genes. Genes associated with inflammatory response (e.g., EIF2AK2, a key mediator of innate immunity) and fatty acid oxidation (e.g., acyl-CoA oxidase 1, the rate-limiting enzyme in fatty acid β-oxidation) were editing-regulated and associated with glioma progression. The above findings were further validated in CGGA samples. Establishment of the prognostic and regulatory roles of RNA editing in glioma holds promise for developing editing-based therapeutic strategies against glioma progression. Furthermore, sexual dimorphism at the epitranscriptional level highlights the importance of developing sex-specific treatments for glioma.

Considerations and challenges for sex-aware drug repurposing

Sex differences are essential factors in disease etiology and manifestation in many diseases such as cardiovascular disease, cancer, and neurodegeneration [33]. The biological influence of sex differences (including genomic, epigenetic, hormonal, immunological, and metabolic differences between males and females) and the lack of biomedical studies considering sex differences in their study design has led to several policies. For example, the National Institute of Health's (NIH) sex as a biological variable (SABV) and Sex and Gender Equity in Research (SAGER) policies to motivate researchers to consider sex differences [204]. However, drug repurposing, a promising alternative to traditional drug discovery by identifying novel uses for FDA-approved drugs, lacks sex-aware methods that can improve the identification of drugs that have sex-specific responses [7, 11, 14, 33]. Sex-aware drug repurposing methods either select drug candidates that are more efficacious in one sex or deprioritize drug candidates based on if they are predicted to cause a sex-bias adverse event (SBAE), unintended therapeutic effects that are more likely to occur in one sex. Computational drug repurposing methods are encouraging approaches to develop for sex-aware drug repurposing because they can prioritize sex-specific drug candidates or SBAEs at lower cost and time than traditional drug discovery. Sex-aware methods currently exist for clinical, genomic, and transcriptomic information [1, 7, 155]. They have not expanded to other data types, such as DNA variation, which has been beneficial in other drug repurposing methods that do not consider sex [114]. Additionally, some sex-aware methods suffer from poorer performance because a disproportionate number of male and female samples are available to train computational methods [7]. However, there is development potential for several different categories (i.e., data mining, ligand binding predictions, molecular associations, and networks). Low-dimensional representations of molecular association and network approaches are also especially promising candidates for future sex-aware drug repurposing methodologies because they reduce the multiple hypothesis testing burden and capture sex-specific variation better than the other methods [151, 159]. Here we review how sex influences drug response, the current state of drug repurposing including with respect to sex-bias drug response, and how model organism study design choices influence drug repurposing validation.

Discrimination of glioma patient-derived cells from healthy astrocytes by exploiting Raman spectroscopy

Glioblastoma multiforme (GBM) is one of the most common and aggressive brain tumors. It presents a very bad prognosis with a patients' overall survival of 12-15 months; treatment failure is mainly ascribable to tumor recurrence. The development of new tools, that could help the precise detection of the tumor border, is thus an urgent need. During the last decades, different vibrational spectroscopy techniques have been developed to distinguish cancer tissue from heathy tissue; in the present work, we compared GBM cells deriving from four patients with healthy human astrocytes using Raman spectroscopy. We have shown that the region between 1000 and 1300 cm^-1 is enough informative for this discrimination, indeed highlighting that peaks related to DNA/RNA and cytochrome c are increased in cancer cells. Finally, our model has been able to discriminate cancer cells from healthy cells with an average accuracy of 92.5%. We believe that this study might help to further understand which are the essential Raman peaks exploitable in the detection of cancer cells, with important perspectives under a diagnostic point of view.

From GWAS to drug screening: repurposing antipsychotics for glioblastoma

BACKGROUND

Glioblastoma is currently an incurable cancer. Genome-wide association studies have demonstrated that 41 genetic variants are associated with glioblastoma and may provide an option for drug development.

METHODS

We investigated FDA-approved antipsychotics for their potential treatment of glioblastoma based on genome-wide association studies data using a 'pathway/gene-set analysis' approach.

RESULTS

The in-silico screening led to the discovery of 12 candidate drugs. DepMap portal revealed that 42 glioma cell lines show higher sensitivities to 12 candidate drugs than to Temozolomide, the current standard treatment for glioblastoma.

CONCLUSION

In particular, cell lines showed significantly higher sensitivities to Norcyclobenzaprine and Protriptyline which were predicted to bind targets to disrupt a certain molecular function such as DNA repair, response to hormones, or DNA-templated transcription, and may lead to an effect on survival-related pathways including cell cycle arrest, response to ER stress, glucose transport, and regulation of autophagy. However, it is recommended that their mechanism of action and efficacy are further determined.

MAPK Activated Protein Kinase 3 Is a Prognostic-Related Biomarker and Associated With Immune Infiltrates in Glioma

Glioma is the most common primary brain tumor that causes significant morbidity and mortality. MAPK activated protein kinase 3 (MAPKAPK3/MK3) is a serine/threonine protein kinase regulating various cellular responses and gene expression. However, the role of MK3 in tumor progress, prognosis, and immunity for glioma remains unclear. Here, we determined the expression and prognostic values of MK3. We further analyzed the correlation of MK3 expression with immune infiltrations by using the biochemical methods and bioinformatic approaches with available databases. We find that MK3 is aberrantly upregulated in glioma. In addition, the higher MK3 expression is closely linked to the poor clinicopathologic features of glioma patients. Importantly, MK3 expression is negatively correlated with the prognosis of patients with glioma. Mechanistically, we demonstrated that the correlated genes of MK3 were mainly enriched in pathways that regulate tumor immune responses. The MK3 level was significantly associated with tumor-infiltrating immune cells and positively correlated with the majority of tumor immunoinhibitors, chemokines, and chemokine receptors in glioma. Thus, these findings suggest the novel prognostic roles of MK3 and define MK3 as a promising target for glioma immunotherapy.