Sex differences in brain tumor glutamine metabolism reveal sex-specific vulnerabilities to treatment

Metabolic Characteristics of Gut Microbiota and Insomnia: Evidence from a Mendelian Randomization Analysis

Insomnia is a common sleep disorder that significantly impacts individuals' sleep quality and daily life. Recent studies have suggested that gut microbiota may influence sleep through various metabolic pathways. This study aims to explore the causal relationships between the abundance of gut microbiota metabolic pathways and insomnia using Mendelian randomization (MR) analysis. This two-sample MR study used genetic data from the OpenGWAS database (205 gut bacterial pathway abundance) and the FinnGen database (insomnia-related data). We identified single nucleotide polymorphisms (SNPs) associated with gut bacterial pathway abundance as instrumental variables (IVs) and ensured their validity through stringent selection criteria and quality control measures. The primary analysis employed the inverse variance-weighted (IVW) method, supplemented by other MR methods, to estimate causal effects. The MR analysis revealed significant positive causal effects of specific carbohydrate, amino acid, and nucleotide metabolism pathways on insomnia. Key pathways, such as gluconeogenesis pathway (GLUCONEO.PWY) and TCA cycle VII acetate producers (PWY.7254), showed positive associations with insomnia (B > 0, p < 0.05). Conversely, pathways like hexitol fermentation to lactate, formate, ethanol and acetate pathway (P461.PWY) exhibited negative causal effects (B < 0, p < 0.05). Multivariable MR analysis confirmed the independent causal effects of these pathways (p < 0.05). Sensitivity analyses indicated no significant pleiotropy or heterogeneity, ensuring the robustness of the results. This study identifies specific gut microbiota metabolic pathways that play critical roles in the development of insomnia. These findings provide new insights into the biological mechanisms underlying insomnia and suggest potential targets for therapeutic interventions. Future research should further validate these causal relationships and explore how modulating gut microbiota or its metabolic products can effectively improve insomnia symptoms, leading to more personalized and precise treatment strategies.

Glutamine Metabolism and Prostate Cancer

Glutamine (Gln) is a non-essential amino acid that is involved in the development and progression of several malignancies, including prostate cancer (PCa). While Gln is non-essential for non-malignant prostate epithelial cells, PCa cells become highly dependent on an exogenous source of Gln. The Gln metabolism in PCa is tightly controlled by well-described oncogenes such as MYC, AR, and mTOR. These oncogenes contribute to therapy resistance and progression to the aggressive castration-resistant PCa. Inhibition of Gln catabolism impedes PCa growth, survival, and tumor-initiating potential while sensitizing the cells to radiotherapy. Therefore, given its significant role in tumor growth, targeting Gln metabolism is a promising approach for developing new therapeutic strategies. Ongoing clinical trials evaluate the safety and efficacy of Gln catabolism inhibitors in combination with conventional and targeted therapies in patients with various solid tumors, including PCa. Further understanding of how PCa cells metabolically interact with their microenvironment will facilitate the clinical translation of Gln inhibitors and help improve therapeutic outcomes. This review focuses on the role of Gln in PCa progression and therapy resistance and provides insights into current clinical trials.

Glutathione overproduction mediates lymphoma initiating cells survival and has a sex-dependent effect on lymphomagenesis

Lymphoid tumor patients often exhibit resistance to standard therapies or experience relapse post-remission. Relapse is driven by Tumor Initiating Cells (TICs), a subset of tumor cells capable of regrowing the tumor and highly resistant to therapy. Growing cells in 3D gels is a method to discern tumorigenic cells because it strongly correlates with tumorigenicity. The finding that TICs, rather than differentiated tumor cells, grow in 3D gels offers a unique opportunity to unveil TIC-specific signaling pathways and therapeutic targets common to various cancer types. Here, we show that culturing lymphoid cells in 3D gels triggers reactive oxygen species (ROS) production, leading to non-tumor lymphoid cell death while enabling the survival and proliferation of a subset of lymphoma/leukemia cells, TICs or TIC-like cells. Treatment with the antioxidant N-acetylcysteine inhibits this lethality and promotes the growth of primary non-tumor lymphoid cells in 3D gels. A subset of lymphoma cells, characterized by an increased abundance of the antioxidant glutathione, escape ROS-induced lethality, a response not seen in non-tumor cells. Reducing glutathione production in lymphoma cells, either through pharmacological inhibition of glutamate cysteine ligase (GCL), the enzyme catalyzing the rate-limiting step in glutathione biosynthesis, or via knockdown of GCLC, the GCL catalytic subunit, sharply decreased cell growth in 3D gels and xenografts. Tumor cells from B-cell lymphoma/leukemia patients and λ-MYC mice, a B-cell lymphoma mouse model, overproduce glutathione. Importantly, pharmacological GCL inhibition hindered lymphoma growth in female λ-MYC mice, suggesting that this treatment holds promise as a therapeutic strategy for female lymphoma/leukemia patients.

Sexual-biased necroinflammation is revealed as a predictor of bevacizumab benefit in glioblastoma

BACKGROUND

Glioblastoma (GBM) is a highly malignant brain tumor that affects men more often than women. In addition, the former shows a poorer survival prognosis. To date, the reason for this sex-specific aggressiveness remains unclear. Therefore, the aim of this study is to investigate tumor processes that explain these sex differences.

METHODS

This was a retrospective study of GBM patients which was stratified according to sex. A cohort with 73 tumors was analyzed with immunohistochemistry, RNA-seq and RT-qPCR to characterize differences in vascular and immunological profiles. Transcriptomic profiling, gene set enrichment analysis, and pathway enrichment analysis were used for discovering molecular pathways predominant in each group. We further investigated the therapeutic effect of bevacizumab (vascular endothelial growth factor A (VEGFA) blocking antibody) in a retrospective GBM cohort (36 tumors) based on sex differences.

RESULTS

We found that under hypoxic tumor conditions, 2 distinct tumor immuno-angiogenic ecosystems develop linked to sex differences and ESR1 expression is generated. One of these subgroups, which includes male patients with low ESR1 expression, is characterized by vascular fragility associated with the appearance of regions of necrosis and high inflammation (called necroinflamed tumors). This male-specific tumor subtype shows high inflammation related to myeloid-derived suppressor cells infiltration. Using this stratification, we identified a possible group of patients who could respond to bevacizumab (BVZ) and revealed a genetic signature that may find clinical applications as a predictor of those who may benefit most from this treatment.

CONCLUSIONS

This study provides a stratification based on the sexual differences in GBM, which associates the poor prognosis with the presence of immunosuppressive myeloid cells in the necrotic areas. This new stratification could change the current prognosis of GBM and identifies those who respond to BVZ treatment.

miR-644a is a tumor cell-intrinsic mediator of sex bias in glioblastoma

Background

Biological sex is an important risk factor for glioblastoma (GBM), with males having a higher incidence and poorer prognosis. The mechanisms for this sex bias are thought to be both tumor intrinsic and tumor extrinsic. MicroRNAs (miRNAs), key post-transcriptional regulators of gene expression, have been previously linked to sex differences in various cell types and diseases, but their role in the sex bias of GBM remains unknown.

Methods

We leveraged previously published paired miRNA and mRNA sequencing of 39 GBM patients (22 male, 17 female) to identify sex-biased miRNAs. We further interrogated a separate single-cell RNA sequencing dataset of 110 GBM patients to examine whether differences in miRNA target gene expression were tumor cell intrinsic or tumor cell extrinsic. Results were validated in a panel of patient-derived cell models.

Results

We identified 10 sex-biased miRNAs (adjusted < 0.1), of which 3 were more highly expressed in males and 7 more highly expressed in females. Of these, miR-644a was higher in females, and increased expression of miR-644a target genes was significantly associated with decreased overall survival (HR 1.3, p = 0.02). Furthermore, analysis of an independent single-cell RNA sequencing dataset confirmed sex-specific expression of miR-644a target genes in tumor cells (p < 10-15). Among patient derived models, miR-644a was expressed a median of 4.8-fold higher in females compared to males.

Conclusions

Our findings implicate miR-644a as a candidate tumor cell-intrinsic regulator of sex-biased gene expression in GBM.

Sex-specific molecular differences in glioblastoma: assessing the clinical significance of genetic variants

Introduction

Glioblastoma multiforme (GBM) is one of the most aggressive types of brain cancer, and despite rigorous research, patient prognosis remains poor. The characterization of sex-specific differences in incidence and overall survival (OS) of these patients has led to an investigation of the molecular mechanisms that may underlie this dimorphism.

Methods

We reviewed the published literature describing the gender specific differences in GBM Biology reported in the last ten years and summarized the available information that may point towards a patient-tailored GBM therapy.

Results

Radiomics analyses have revealed that imaging parameters predict OS and treatment response of GBM patients in a sex-specific manner. Moreover, gender-based analysis of the transcriptome GBM tumors has found differential expression of various genes, potentially impacting the OS survival of patients in a sex-dependent manner. In addition to gene expression differences, the timing (subclonal or clonal) of the acquisition of common GBM-driver mutations, metabolism requirements, and immune landscape of these tumors has also been shown to be sex-specific, leading to a differential therapeutic response by sex. In male patients, transformed astrocytes are more sensitive to glutaminase 1 (GLS1) inhibition due to increased requirements for glutamine uptake. In female patients, GBM is more sensitive to anti-IL1β due to an increased population of circulating granulocytic myeloid-derived suppressor cells (gMDSC).

Conclusion

Moving forward, continued elucidation of GBM sexual dimorphism will be critical in improving the OS of GBM patients by ensuring that treatment plans are structured to exploit these sex-specific, molecular vulnerabilities in GBM tumors.

'Slicing' glioblastoma drivers with the Swiss cheese model

The Swiss cheese model is used to assess risks and explain accidents in a variety of industries. This model can be applied to dissect the homeostatic mechanisms whose cumulative dysregulation contributes to disease states, including cancer. Using glioblastoma (GBM) as an exemplar, we discuss how specific protumorigenic mechanisms collectively drive disease by affecting genomic integrity, epigenetic regulation, metabolic homeostasis, and antitumor immunity. We further highlight how host factors, such as hormonal differences and aging, impact this process, and the interplay between these 'system failures' that enable tumor progression and foster therapeutic resistance. Finally, we examine therapies that consider the interactions between these elements, which may comprise more effective approaches given the multifaceted protumorigenic mechanisms that drive GBM.

Accounting for sex differences as a continuous variable in cancer treatments

The significant sex differences that exist in cancer mechanisms, incidence, and survival, have yet to impact clinical practice. We propose that one barrier to translation is that sex differences in cancer phenotypes resemble sex differences in height: highly overlapping, but distinct, male and female population distributions that vary continuously between female- and male- skewed extremes. A consequence of this variance is that sex-specific treatments are rendered unrealistic, and our translational goal should be adaptation of treatment to the variable sex-effect on targetable pathways. To develop a tool that could advance this goal, we applied a Bayesian Nearest Neighbor (BNN) analysis to 8370 cancer transcriptomes from 26 different adult and 4 different pediatric cancer types to establish patient-specific Transcriptomic Indices (TI). TI precisely positions a patient's whole transcriptome on axes of mechanistic phenotypes like cell cycle signaling and immunity that exhibit skewing in the cancer population relative to sex-identified extremes (poles). Importantly, the TI approach reveals that even when TI values are identical, underlying mechanisms in male and female individuals can differ in identifiable ways. Thus, cancer type, patient sex, and TI value provides a novel and patient- specific mechanistic identifier that can be used for precision cancer treatment planning.

Accounting for sex differences variability in the design of sex-adapted cancer treatments

The significant sex differences that exist in cancer mechanisms, incidence, and survival, have yet to impact clinical practice. We hypothesized that one barrier to translation is that sex differences in cancer phenotypes resemble sex differences in height: highly overlapping, but distinct, male and female population distributions that vary continuously between female- and male- biased extremes. A consequence of this variance is that sex-specific treatments are rendered unrealistic, and our translational goal should be adaptation of treatment to the unique mix of sex-biased mechanisms that are present in each patient. To develop a tool that could advance this goal, we applied a Bayesian Nearest Neighbor (BNN) analysis to 8370 cancer transcriptomes from 26 different adult and 4 different pediatric cancer types to establish patient-specific Transcriptomic Sex Indices (TSI). TSI precisely partitions an individual patient's whole transcriptome into female- and male- biased components such that cancer type, patient sex, and transcriptomics, provide a novel and patient-specific mechanistic identifier that can be used for sex-adapted, precision cancer treatment planning.

De novo serine biosynthesis from glucose predicts sex-specific response to antifolates in non-small cell lung cancer cell lines

Lung cancer is the leading cause of cancer-related death. Intriguingly, males with non-small cell lung cancer (NSCLC) have a higher mortality rate than females. Here, we investigated the role of serine metabolism as a predictive marker for sensitivity to the antifolate pemetrexed in male and female NSCLC cell lines. Using [13C6] glucose tracing in NSCLC cell lines, we found that a subset of male cells generated significantly more serine from glucose than female cells. Higher serine biosynthesis was further correlated with increased sensitivity to pemetrexed in male cells only. Concordant sex differences in metabolic gene expression were evident in NSCLC and pan-cancer transcriptome datasets, suggesting a potential mechanism with wide-reaching applicability. These data were further validated by integrating antifolate drug cytotoxicity and metabolic pathway transcriptome data from pan-cancer cell lines. Together, these findings highlight the importance of considering sex differences in cancer metabolism to improve treatment for all patients.