Biology subjects

Rubin, J. B.

Publications and source records attributed to Rubin, J. B..

At least 19 recordsLinked to original sources

bioRxiv2025

Platelets drive immune suppression and glioblastoma growth in a sex-dependent manner via PAR4 signaling

Sex differences in cancer outcome, including that of glioblastoma (GBM), are shaped by biological, hormonal, and immunological factors and impact disease progression, treatment responses, survival, and tumor microenvironment (TME) interactions. Platelets regulate the immune responses and tumor progression in many cancers, but it is not clear how they contribute to these sex-based differences by affecting the dynamics of the TME. Here, we show that GBM patients exhibit heightened platelet reactivity driven by PAR4 signaling. In murine GBM models, both pharmacological inhibition of PAR4 using BMS986120 and genetic deletion of PAR4 significantly prolong survival in females but not males. This survival advantage is estrogen dependent: it is preserved in chromosomal male-hormonal female mice within the four-core genotype model and is rescued in ovariectomized mice treated with estrogen. The survival benefit is TME specific and is mediated by platelet-driven enhancement of CD8 T cell infiltration into the tumor. Inhibition of platelet PAR4 signaling increases calcium signaling through an estrogen-dependent interaction between PAR4 and estrogen receptor {beta} (ER{beta})--a receptor interaction not previously described. PAR4-activated platelets within the TME suppress CD8 T cell function, and depletion of CD8 T cells abolishes both the tumor-induced platelet reactivity and the survival benefit conferred by PAR4 inhibition. These findings establish platelet-mediated PAR4 signaling as a critical driver of tumor progression and identify sex-specific immune responses as key to therapeutic efficacy.

cancer biology↗

bioRxiv2025

EGR1 drives sex-differences in glioblastoma tumorigenicity

Although progress has been made in treating glioblastoma (GBM), with fewer than 5% of patients surviving more than 5 years after diagnosis. For reasons that are not well understood, females are roughly 60% as likely as males to develop GBM, and female patients consistently respond better to treatment than do males. Understanding the molecular etiology of these sex differences in tumor progression and resiliency to treatment could reveal potent new therapeutic targets, ultimately improving survival of both male and female GBM patients. Here we show that the transcription factor Egr1 is a primary mediator of sex differences in multiple GBM tumorigenic phenotypes. In multivariate analysis, high levels of EGR1 expression are correlated with shortened survival for male GBM patients only. To investigate the molecular mechanisms underlying this sex difference, we performed a genomic analysis in our established ex vivo murine model of sex differences, which showed that the transcription factors Egr1 and Klf5 preferentially recruit the transcriptional activator Brd4 to enhancers in male cells relative to female cells, explaining a previously made observation that Brd4 inhibitors reverse sex differences in GBM. Next, using murine and human primary GBM cells, we demonstrated that the small molecule compound SR18662, which downregulates Egr1 and its downstream target Klf5, abrogates GBM growth, migration, invasion, clonogenicity, and response to radiation in a sex-biased fashion. Finally, we knocked down Egr1 and Klf5 via CRISPRi in both untreated and SR18662-treated GBM cells to reveal the sex-biased anti-tumorigenic effects of SR18662 were largely due to Egr1 downregulation, independent of Klf5 downregulation. This result was replicated in vivo. Our results strongly indicate that an Egr1 regulon is a key determinant of sex differences in GBM. As EGR1 is implicated in the cancer biology of many cancers that also display sex differences in incidence and treatment response, our results are likely to be broadly applicable in oncology.

cancer biology↗

bioRxiv2024

Daily glucocorticoids promote glioblastoma growth and circadian synchrony to the host

Glioblastoma (GBM) is the most common primary brain tumor in adults with a poor prognosis despite aggressive therapy. A recent, retrospective clinical study found that administering Temozolomide in the morning increased patient overall survival by 6 months compared to evening. Here, we tested the hypothesis that daily host signaling regulates tumor growth and synchronizes circadian rhythms in GBM. We found daily Dexamethasone promoted or suppressed GBM growth depending on time of day of administration and on the clock gene, Bmal1. Blocking circadian signals, like VIP or glucocorticoids, dramatically slowed GBM growth and disease progression. Finally, mouse and human GBM models have intrinsic circadian rhythms in clock gene expression in vitro and in vivo that entrain to the host through glucocorticoid signaling, regardless of tumor type or host immune status. We conclude that GBM entrains to the circadian circuit of the brain, which modulates its growth through clock-controlled cues, like glucocorticoids.

neuroscience↗

bioRxiv2022

Glioblastoma states are defined by cohabitating cellular populations with progression-, imaging- and sex-distinct patterns

Background: Magnetic Resonance Imaging (MRI) is the mainstay for neurosurgical oncology but not for informing us about glioma biology. An obstacle to developing MR-based glioma biomarkers is the absence of rigorous correlation between MRI features and glioma biology as assessed in multi-regional biopsies, within and across patients. Methods: We directly addressed this obstacle by collating a unique cohort of 202 MRI-localized biopsies from 58 patients. We define a low-dimensional transcriptional pseudotime continuum along which heterogeneous high-grade glioma (HGG) samples organize both within and across patients. Results: We observe three polarized transcriptional tissue states: infiltrated brain, immune/inflammatory, and proliferative associated with patterns of cohabitation of cellular subpopulations. The states and deconvolved populations show correlation with enhancement status on T1Gd MRI. Moreover, discrete MRI habitats, regions sharing common imaging features, defined as combinations of high or low signal intensity across multiparametric MRI revealed 14 MRI habitats. We order the MRI habitats according to the average pseudotime on the transcriptional continuum. We find that MRI habitats with low pseudotime (associated with early tumor development and diffusely invaded brain tissue) localized at the periphery of the tumor whilst high pseudotime either proliferative or immune/inflammatory states were towards the core of the lesion. We find that composition of MRI habitats is impacted by MGMT status. Conclusion: This suggests that ongoing aggregation of MRI-localized biopsies may augment our projection of biology onto MRI habitats to support the noninvasive identification of cellular ecologies within and across each patient's tumor.

cancer biology↗

bioRxiv2021

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), the most common type of lung cancer, 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 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.

cancer biology↗

bioRxiv2021

Sex Differences in Brain Tumor Glutamine Metabolism Reveal Sex-Specific Vulnerabilities to Treatment

Sex differences in normal metabolism are well described, but whether they persist in cancerous tissue is unknown. We assessed metabolite abundance in glioblastoma surgical specimens and found that male glioblastomas are enriched for amino acids, including glutamine. Using PET imaging, we found that gliomas in male patients exhibit significantly higher glutamine uptake. These sex differences were well-modeled in murine transformed astrocytes, in which male cells imported and metabolized more glutamine and were more sensitive to glutaminase 1 (GLS1) inhibition. The sensitivity to GLS1 inhibition in males was driven by their dependence on glutamine-derived glutamate for -ketoglutarate synthesis and TCA cycle replenishment. Females were resistant to GLS1 inhibition through greater pyruvate carboxylase-mediated TCA cycle replenishment. Thus, clinically important sex differences exist in targetable elements of metabolism. Recognition of sex-biased metabolism is an opportunity to improve treatments for all patients through further laboratory and clinical research.

cancer biology↗

bioRxiv2021

p53 mutations exhibit sex specific gain-of-function activity in gliomagenesis

The tumor suppressor TP53 is the most frequently mutated gene in cancer. Most TP53 mutations are missense mutations in the DNA-binding domain, which in addition to loss of canonical p53 activity, frequently confer gain-of-function (GOF) aberrant transcriptional activity through mutant p53 localization to non-canonical genes. GOF phenotypes differ by mutation and cell identity and are reported to include increased proliferation, migration, metabolic reprogramming, and therapy resistance. We found that several recurring p53 mutations exhibit a sex-bias in patients with glioblastoma (GBM). In vitro and in vivo analysis of three mutations, p53R172H, p53Y202C, and p53Y217C revealed sex differences in each mutations ability to transform primary mouse astrocytes. p53R172H exhibited a far greater ability to transform female astrocytes than males, p53Y202C transformed both male and female astrocytes with a small male bias, and p53Y217C only exhibited GOF transformation effects in male astrocytes. These phenotypic differences reflect an interaction between sex and GOF mutation to drive unique gene expression patterns in cancer pathways. We found that mutant p53 exhibits sex and mutation specific aberrant genomic localization to the transcriptional start sites of upregulated genes, whose promoter regions were enriched for different sets of transcription factor DNA-binding motifs. Together, our data establish a novel paradigm for sex specific mutant p53 GOF activity in GBM with implications for all cancer.

cancer biology↗

bioRxiv2021

Gonadal sex patterns p21-induced cellular senescence in mouse and human glioblastoma

Males exhibit higher incidence and worse prognosis for the majority of cancers, including glioblastoma (GBM). Disparate survival may be related to sex-biased responses to treatment, including radiation. Using a mouse model of GBM, we show that female cells are more sensitive to radiation, and that senescence represents a major component of the radiation therapeutic response in both sexes. Correlation analyses revealed that the CDK inhibitor p21 and irradiation induced senescence were differentially regulated between male and female cells. Indeed, female cellular senescence was more sensitive to changes in p21 levels, a finding that was observed in both wildtype and transformed murine astrocytes and patient-derived GBM cell lines. Using a novel Four Core Genotypes model of GBM, we further show that sex differences in p21-induced senescence are patterned by gonadal sex. These data suggest that sex differences in p21 induced senescence contribute to the female survival advantage in GBM.

cancer biology↗

bioRxiv2020

Integrative omics data analysis uncovers biomarker genes and potential candidate drugs for G3 medulloblastoma

Medulloblastoma (MB) is the most common malignant brain tumor in infants and children. Four molecular subtypes of MB are recognized: WNT, SHH, Group 3 (G3), and Group 4 (G4). Compared with WNT and SHH subtypes, G3 MBs exhibit significantly worse outcomes and higher metastatic rates, and there is no effective treatment yet. Moreover, G3 and G4 MBs are much more common in boys than girls, i.e., sex bias, which also plays important roles in cancer prognosis and drug response. However, the molecular mechanism of G3 remains unclear, and there are no well-identified biomarker genes associated with these phenotypes, i.e., worse survival rate, higher metastasis rate, and sex bias. In this exploratory study, we aim to identify potential biomarkers associated with the three phenotypes using integrative analysis of gene expression, methylation and copy number variation datasets. In the results, we identified a set of biomarker genes and linked them into a network signature. The network signature showed better performance in the separation of G3 MB patients into subtypes with a significant difference in terms of the three phenotypes. To identify potentially effective drugs for G3 MBs, a set of drugs with diverse targets were prioritized, which can potentially inhibit the network signature. These drugs or combinations thereof might be effective for G3 treatment.

bioinformatics↗

bioRxiv2020

Cognitive Deficits and Altered Functional Brain Network Organization in Pediatric Brain Tumor Patients

Pediatric brain tumor survivors experience significant cognitive sequelae from their diagnosis and treatment. The exact mechanisms of cognitive injury are poorly understood, and validated predictors of long-term cognitive outcome are lacking. Large-scale, distributed brain systems provide a window into brain organization and function that may yield insight into these mechanisms and outcomes. Here, we evaluated functional network architecture, cognitive performance, and brain-behavior relationships in pediatric brain tumor patients. Patients ages 4-18 years old with diagnosis of a brain tumor underwent awake resting state fMRI during regularly scheduled clinical visits and were tested with the NIH Toolbox Cognition Battery. We observed that functional network organization was significantly altered in patients compared to age- and sex-matched healthy controls, with the integrity of the dorsal attention network particularly affected. Moreover, patients demonstrated significant impairments in multiple domains of cognitive performance, including attention. Finally, a significant amount of variance of age-adjusted total composite scores from the Toolbox was explained by changes in segregation between the dorsal attention and default mode networks. Our results suggest that changes in functional network organization may provide insight into long-term changes in cognitive function in pediatric brain tumor patients.

neuroscience↗

bioRxiv2020

Diffusion Basis Spectrum Imaging with Deep Neural Network Differentiates Distinct Histology in Pediatric Brain Tumors

High-grade pediatric brain tumors constitute the highest mortality of cancer-death in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumor clinically, accurate neuroimaging detection and differentiation of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in the clinical management of pediatric brain tumor. We employed a novel Diffusion Histology Imaging (DHI) approach that incorporates diffusion basis spectrum imaging (DBSI) and deep neural network. DHI aims to detect, differentiate, and quantify heterogenous areas in pediatric high-grade brain tumors, which include normal white matter (WM), densely cellular tumor (DC tumor), less densely cellular tumor (LDC tumor), infiltrating edge, necrosis, and hemorrhage. Distinct diffusion metric combination would thus indicate the unique distributions of each distinct tumor histology features. DHI, by incorporating DBSI metrics and the deep neural network algorithm, classified pediatric tumor histology with an overall accuracy of 83.3%. Receiver operating analysis (ROC) analysis suggested DHIs great capability in distinguishing individual tumor histology with AUC values (95%CI) of 0.983 (0.985-0.989), 0.961 (0.957-0.964), 0.993 (0.992-0.994), 0.953 (0.947-0.958), 0.974 (0.970-0.978) and 0.980 (0.977-0.983) for normal WM, DC tumor, LDC tumor, infiltrating edge, necrosis and hemorrhage, respectively. Our results suggest that DBSI-DNN, or DHI, accurately characterized and classified multiple tumor histologic features in pediatric high-grade brain tumors. If further validated in patients, the novel DHI might emerge as a favorable alternative to the current neuroimaging techniques to better guide biopsy and resection as well as monitor therapeutic response in patients with high-grade brain tumors.

neuroscience↗

bioRxiv2019

JAM-A functions as a female microglial tumor suppressor in glioblastoma

Glioblastoma (GBM) remains refractory to treatment. In addition to its cellular and molecular heterogeneity, epidemiological studies indicate the presence of additional complexity associated with biological sex. GBM is more prevalent and aggressive in male compared to female patients, suggesting the existence of sex-specific growth, invasion, and therapeutic resistance mechanisms. While sex-specific molecular mechanisms have been reported at a tumor cell-intrinsic level, sex-specific differences in the tumor microenvironment have not been investigated. Using transgenic mouse models, we demonstrate that deficiency of junctional adhesion molecule-A (JAM-A) in female mice enhances microglia activation, GBM cell proliferation, and tumor growth. Mechanistically, JAM-A suppresses anti-inflammatory/pro-tumorigenic gene activation via interferon-activated gene 202b (Ifi202b) and found in inflammatory zone (Fizz1) in female microglia. Our findings suggest that cell adhesion mechanisms function to suppress pathogenic microglial activation in the female tumor microenvironment, which highlights an emerging role for sex differences in the GBM microenvironment and suggests that sex differences extend beyond previously reported tumor cell intrinsic differences.\n\nSummaryTuraga et al. demonstrate that female microglia drive a more aggressive glioblastoma phenotype in the context of JAM-A deficiency. These findings highlight a sex-specific role for JAM-A and represent the first evidence of sexual dimorphism in the glioblastoma microenvironment.

cancer biology↗

bioRxiv2019

Sex differences in seizure at presentation in glioma population

Seizures are common presenting symptoms of primary brain tumors. Mechanisms of epileptogenesis are still unknown and are believed to be multifactorial. Previous studies have indicated correlation of seizure with tumor location. Recent investigations of our group have shown image-based parameters have sex-specific implications for patient outcome. In this retrospective study, we examined the association of tumor location with the probability and risk of seizure in male and female glioma patients.

cancer biology↗

bioRxiv2019

Sex Differences in Predictors of Seizure in Contrast-Enhancing Gliomas at Clinical Presentation: A Network Approach

BackgroundBrain tumor related epilepsy (BTE) is a major co-morbidity related to the management of patients with brain cancer. Despite published practice guidelines recommending against anti-epileptic drug (AED) utilization in patients with gliomas, there is heterogeneity in prescription practices of AEDs in these patients. In an attempt to impact BTE management, we statistically analyzed clinically relevant attributes (sex, age, tumor size, tumor growth kinetics, and tumor location) pertaining to seizure at presentation and used them to build a computational machine learning model to predict the probability of a seizure (at presentation).\n\nMethodsFrom our clinical data repository, we identified 223 patients (females, n=86; males, n=137) with pathologically-determined glioma and known seizure status at clinical presentation. Non-parametric and Fishers Exact tests were used to identify statistical differences in clinical characteristics. We utilized a random forest machine learning method for generating our predictive models by entire cohort and separated by male and female.\n\nFindingsPatients were divided into those that presented with seizure (SP, n=96, 43%; F, n= 28; M, n= 68) and those that presented without seizure (nSP, n=127, 57%, F n=58, M n=69). Females presented with seizures significantly less often than males (x2=6{middle dot}28, p=0{middle dot}01). SP patients had significantly smaller T1Gd radius compared to nSP (SP 11{middle dot}30mm, nSP 18.66mm, p<0{middle dot}0001). Tumor size and patient age were significant negative predictors for SP; patients with larger tumors, older age and less tumor diffusivity (p/D) were at lower risk for SP.\n\nInterpretationDespite heterogeneity across our patient cohort, there is strong evidence of a role for patient sex, tumor size, tumor invasion, and patient age in predicting the incidence of seizures at diagnosis. Future studies, with prospectively detailed data collection, may provide clearer insights into the incidence of seizures through a patients treatment course.

cancer biology↗

bioRxiv2018

Connecting Patterns of Tumor Growth with Sex Differences in Extreme Survivorship for Primary Glioblastoma Patients

BackgroundSex is recognized as a significant determinant of outcome among glioblastoma patients, but the relative prognostic importance of glioblastoma features has not been thoroughly explored for sex differences.\n\nMethodsCombining multi-modal MR images, biomathematical models, and patient clinical information, this investigation assesses which pretreatment variables have a sex-specific impact on the survival of glioblastoma patients. Pretreatment MR images of 494 glioblastoma patients (299 males and 195 females) were segmented to quantify tumor volumes. Cox proportional hazard (CPH) models and Students t-tests were used to assess which variables were associated with survival outcomes.\n\nResultsAmong males, tumor (T1Gd) radius was a predictor of overall survival (HR=1.027, p=0.044). Among females, higher tumor cell net invasion rate was a significant detriment to overall survival (HR=1.011, p<0.001). Female extreme survivors had significantly smaller tumors (T1Gd) (p=0.010 t-test), but tumor size was not correlated with female overall survival (p=0.955 CPH). Both male and female extreme survivors had significantly lower tumor cell net proliferation rates than other patients (M p=0.004, F p=0.001, t-test). Additionally, extent of resection, tumor laterality, and IDH1 mutation status were also found to have sex-specific effects on overall survival.\n\nConclusionDespite similar distributions of the MR imaging parameters between males and females, there was a sex-specific difference in how these parameters related to outcomes, which emphasizes the importance of considering sex as a biological factor when determining patient prognosis and treatment approach.

cancer biology↗

bioRxiv2017

Sex-specific genome-wide association study in glioma identifies new risk locus at 3p21.31 in females, and finds sex-differences in risk at 8q24.21

Incidence of glioma is approximately 50% higher in males. Previous analyses have examined exposures related to sex hormones in women as potential protective factors for these tumors, with inconsistent results. Previous glioma genome-wide association studies (GWAS) have not stratified by sex. Potential sex-specific genetic effects were assessed in autosomal SNPs and sex chromosome variants for all glioma, GBM and non-GBM patients using data from four previous glioma GWAS. Datasets were analyzed using sex-stratified logistic regression models and combined using meta-analysis. There were 4,831 male cases, 5,216 male controls, 3,206 female cases and 5,470 female controls. A significant association was detected at rs11979158 (7p11.2) in males only. Association at rs55705857 (8q24.21) was stronger in females than in males. A large region on 3p21.31 was identified with significant association in females only. The identified differences in effect of risk variants do not fully explain the observed incidence difference in glioma by sex.

epidemiology↗

bioRxiv2017

Sex-specific gene and pathway modeling of inherited glioma risk

BackgroundGenome-wide association studies (GWAS) have identified 25 risk variants for glioma, which explain ~30% of heritable risk. Most glioma histologies occur with significantly higher incidence in males. A sex-stratified analysis ide7ntified sex-specific glioma risk variants, and further analyses using gene- and pathway-based approaches may further elucidate risk variation by sex.\n\nMethodsResults from the Glioma International Case-Control Study were used as a testing set, and results from three GWAS were combined via meta-analysis and used as a validation set. Using summary statistics for autosomal SNPs found to be nominally significant (p<0.01) in a previous meta-analysis and X chromosome SNPs with nominally significant association (p<0.01), three algorithms (Pascal, BimBam, and GATES) were used to generate gene-scores, and Pascal was used to generate pathway scores. Results were considered significant when p<3.3x10-6 in [2/3] algorithms.\n\nResults25 genes within five regions and 19 genes within six regions reached the set significance threshold in at least 2/3 algorithms in males and females, respectively. EGFR and RTEL1-TNFRSF6B were significantly associated with all glioma and glioblastoma in males only, and a female-specific association in TERT, all of which remained nominally significant after conditioning on known risk loci. There were nominal associations with the Telomeres, Telomerase, Cellular Aging, and Immortality pathway in both males and females.\n\nConclusionsThese results suggest that there may be biologically relevant significant differences by sex in genetic risk for glioma. Additional gene- and pathway-based analyses may further elucidate the biological processes through which this risk is conferred.

epidemiology↗

bioRxiv2017

Clinically Important sex differences in GBM biology revealed by analysis of male and female imaging, transcriptome and survival data

Sex differences in the incidence and outcome of human disease are broadly recognized but in most cases not adequately understood to enable sex-specific approaches to treatment. Glioblastoma (GBM), the most common malignant brain tumor, provides a case in point. Despite well-established differences in incidence, and emerging indications of differences in outcome, there are few insights that distinguish male and female GBM at the molecular level, or allow specific targeting of these biological differences. Here, using a quantitative imaging-based measure of response, we found that temozolomide chemotherapy is more effective in female compared to male GBM patients. We then applied a novel computational algorithm to linked GBM transcriptome and outcome data, and identified novel sex-specific molecular subtypes of GBM in which cell cycle and integrin signaling were identified as the critical determinants of survival for male and female patients, respectively. The clinical utility of cell cycle and integrin signaling pathway signatures was further established through correlations between gene expression and in vitro chemotherapy sensitivity in a panel of male and female patient-derived GBM cell lines. Together these results suggest that greater precision in GBM molecular subtyping can be achieved through sex-specific analyses, and that improved outcome for all patients might be accomplished via tailoring treatment to sex differences in molecular mechanisms.\n\nOne Sentence SummaryMale and female glioblastoma are biologically distinct and maximal chances for cure may require sex-specific approaches to treatment.

cancer biology↗