Sex-Specific Differences in Low-Grade Glioma Presentation and Outcome

Tewari, Surabhi; Tom, Martin C.; Park, Deborah Y.J.; Wei, Wei; Chao, Samuel T.; Yu, Jennifer; Suh, John H.; Kilic, Sarah; Peereboom, David M.; Stevens, Glen; Lathia, Justin D.; Prayson, Richard A.; Barnett, Gene H.; Angelov, Lilyana; Mohammadi, Alireza; Ahluwalia, Manmeet; Murphy, Erin S.

doi:10.1016/j.ijrobp.2022.05.036

Cited by 5 publications

(1 citation statement)

References 41 publications

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“…However, the underlying mechanisms are poorly understood. Although sex hormones play obvious and significant roles in the pathogenesis of some tumors such as estrogen receptor-positive breast or androgen receptor-positive prostate cancers, they do not explain the clear sex bias seen in many other cancers, such as brain cancers [5][6][7] . Cellautonomous mechanisms such as epigenetic changes during organogenesis and aging, and X-chromosome-linked gene expression contribute to sexual dimorphism 8,9,10 .…”

Section: Introductionmentioning

confidence: 99%

Sex-biasedYap1oncogene function

Abdelfattah

Natarajan

Maldonado

et al. 2022

Preprint

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The incidence of many human cancers differs according to sex, but little is known about the interplay between oncogenic events and sex as a variable in tumorigenesis. Here we report that the oncogene Yap1 is sexually dimorphic in medulloblastoma progression and immune suppression. We show that Yap1 promotes stemness and blocks differentiation in sonic hedgehog (SHH)-subtype medulloblastoma by at least two distinct but complementary molecular mechanisms to regulate the RNA expression and protein functions of Sox2, Atoh1, NeuroD1, and Zic1/2. Yap1 also promotes an immune suppressive tumor microenvironment by directly regulating Csf1, Igf1, and Igfbp3 transcription and modulating IL6-JAK-STAT3, TNFR1, TGF-β, and CCL5 immune pathways. Notably, Yap1 function is more critical in males and this is evolutionarily conserved: genes downstream of YAP1 identified in mouse models stratify male but not female medulloblastoma patient survival. In summary, we demonstrate a sex-based function for an oncogene, underscoring the critical need to incorporate sex as a variable in cancer mechanism and clinical response studies, particularly those involving YAP1.

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Section: Introductionmentioning

confidence: 99%

Sex-biasedYap1oncogene function

Abdelfattah

Natarajan

Maldonado

et al. 2022

Preprint

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A single-institution retrospective analysis of pathologically determined malignant transformation in IDH mutant glioma patients

Liu

Wetzel

Eldred

et al. 2023

Neuro-Oncology Advances

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Background Lower-grade IDH mutant glioma patients frequently undergo malignant transformation (MT), with apparent worse prognosis. Many studies examine MT in mixed IDH status cohorts and define MT using imaging, not histopathology. Our study examines timing, predictors, and prognostic implications of pathologically determined MT in a large, exclusively IDH mutant cohort. Methods We identified 193 IDH mutant lower-grade glioma patients at UCLA who received multiple surgeries. We examined the outcomes of MT patients, determined by pathology review. Results Time to MT is longer in grade 2 oligodendroglioma (G2 Oligo) than grade 2 astrocytomas (G2 Astro) (HR = 0.46, p = 0.0007). The grade 3 astrocytoma (G3 Astro) to grade 4 astrocytoma (G4 Astro) interval is shorter in stepwise MT (G2 to G3 to G4 Astro) patients than in initial G3 Astro patients (p = 0.03). Novel contrast enhancement had 65% positive predictivity, 67% negative predictivity, 75% sensitivity, and 55% specificity in indicating pathologically defined MT. In G2 Astro, initial gross total resection delayed MT (HR = 0.50, p = 0.02) and predicted better OS (HR = 0.34, p = 0.009). In G2 Oligo, spontaneous MT occurred earlier than treated MT (HR = 11.43, p = 0.0002), but treatment did not predict improved OS (p = 0.8). MT patients (n = 126) exhibited worse OS than non-MT patients (n = 67) in All (HR = 2.54, p = 0.0009) and G2 Astro (HR = 4.26, p = 0.02). Conclusion Our study expands understanding of MT to improve IDH mutant lower-grade glioma management.

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The construction of a novel prognostic prediction model for glioma based on GWAS-identified prognostic-related risk loci

Wei,

Li,

Zhou

et al. 2024

Open Medicine

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Backgrounds Glioma is a highly malignant brain tumor with a grim prognosis. Genetic factors play a role in glioma development. While some susceptibility loci associated with glioma have been identified, the risk loci associated with prognosis have received less attention. This study aims to identify risk loci associated with glioma prognosis and establish a prognostic prediction model for glioma patients in the Chinese Han population. Methods A genome-wide association study (GWAS) was conducted to identify risk loci in 484 adult patients with glioma. Cox regression analysis was performed to assess the association between GWAS-risk loci and overall survival as well as progression-free survival in glioma. The prognostic model was constructed using LASSO Cox regression analysis and multivariate Cox regression analysis. The nomogram model was constructed based on the single nucleotide polymorphism (SNP) classifier and clinical indicators, enabling the prediction of survival rates at 1-year, 2-year, and 3-year intervals. Additionally, the receiver operator characteristic (ROC) curve was employed to evaluate the prediction value of the nomogram. Finally, functional enrichment and tumor-infiltrating immune analyses were conducted to examine the biological functions of the associated genes. Results Our study found suggestive evidence that a total of 57 SNPs were correlated with glioma prognosis (p < 5 × 10−5). Subsequently, we identified 25 SNPs with the most significant impact on glioma prognosis and developed a prognostic model based on these SNPs. The 25 SNP-based classifier and clinical factors (including age, gender, surgery, and chemotherapy) were identified as independent prognostic risk factors. Subsequently, we constructed a prognostic nomogram based on independent prognostic factors to predict individualized survival. ROC analyses further showed that the prediction accuracy of the nomogram (AUC = 0.956) comprising the 25 SNP-based classifier and clinical factors was significantly superior to that of each individual variable. Conclusion We identified a SNP classifier and clinical indicators that can predict the prognosis of glioma patients and established a prognostic prediction model in the Chinese Han population. This study offers valuable insights for clinical practice, enabling improved evaluation of patients’ prognosis and informing treatment options.

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Sex-Specific Differences in Low-Grade Glioma Presentation and Outcome

Cited by 5 publications

References 41 publications

Sex-biasedYap1oncogene function

Sex-biasedYap1oncogene function

A single-institution retrospective analysis of pathologically determined malignant transformation in IDH mutant glioma patients

The construction of a novel prognostic prediction model for glioma based on GWAS-identified prognostic-related risk loci

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