Person:

Claus, Elizabeth

Vitamin D deficiency (≤20 ng/mL) is associated with an increased incidence and worse prognosis of various types of cancer including melanoma. A retrospective, single-center study of individuals diagnosed with melanoma from January 2007 through June 2013 who had a vitamin D (25(OH)D3) level measured within one year of diagnosis was performed to determine whether vitamin D deficiency and repletion are associated with melanoma outcome. A total of 409 individuals diagnosed with histopathology-confirmed melanoma who had an ever measured serum 25(OH)D3 level were identified. 252 individuals with a 25(OH)D3 level recorded within one year after diagnosis were included in the study and the individual and melanoma characteristics such as age, sex, Breslow thickness, ulceration, stage, mitotic rate, and LDH were obtained from the medical record. A worse melanoma prognosis was associated with vitamin D deficiency (P=0.012), higher stage (P<0.001), ulceration (P=0.001), and higher mitotic rate (P=0.001) (HR 1.93, 95% CI 1.15-3.22). In patients with stage IV metastatic melanoma, vitamin D deficiency was associated with significantly worse melanoma-specific mortality (adjusted HR 2.06, 95% CI 1.10-3.87). Patients with metastatic melanoma who were initially vitamin D deficient and subsequently had a decrease or ≤20 ng/mL increase in their 25(OH)D3 concentration had significantly worse outcomes (HR 4.68, 95% CI 1.05-20.88) compared to non-deficient patients who had a >20 ng/mL increase. Our results suggest that initial vitamin D deficiency and insufficient repletion is associated with a worse prognosis in patients with metastatic melanoma.

Brain metastases represent the greatest clinical challenge in treating HER2-positive breast cancer. We report the development of orthotopic patient-derived xenografts (PDXs) of HER2-expressing breast cancer brain metastases (BCBM), and their use for the identification of targeted combination therapies. Combined inhibition of PI3K and mTOR resulted in durable tumor regressions in three of five PDXs, and therapeutic response correlated with reduction of 4EBP1 phosphorylation. The two non-responding PDXs showed hypermutated genomes with enrichment of mutations in DNA repair genes, suggesting an association of genomic instability with therapeutic resistance. These findings suggest that a biomarker-driven clinical trial of PI3K inhibitor plus an mTOR inhibitor should be conducted for patients with HER2-positive BCBM.

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.

BACKGROUND Meningioma is the most common primary brain tumor and has a variable risk of local recurrence. While World Health Organization (WHO) grade generally correlates with recurrence, there is substantial within-grade variation of recurrence risk. Current risk stratification does not accurately predict which patients are likely to benefit from adjuvant radiation therapy (RT). We hypothesized that tumors at risk for recurrence have unique gene expression profiles (GEP) that could better select patients for adjuvant RT. METHODS We developed a recurrence predictor by machine learning modeling using a training/validation approach. RESULTS Three publicly available AffymetrixU133 gene expression datasets (GSE9438, GSE16581, GSE43290) combining 127 primary, non-treated meningiomas of all grades served as the training set. Unsupervised variable selection was used to identify an 18-gene GEP model (18-GEP) that separated recurrences. This model was validated on 62 primary, non-treated cases with similar grade and clinical variable distribution as the training set. When applied to the validation set, 18-GEP separated recurrences with a misclassification error rate of 0.25 (log-rank p=0.0003). 18-GEP was predictive for tumor recurrence [p=0.0008, HR=4.61, 95%CI=1.89-11.23)] and was predictive after adjustment for WHO grade, mitotic index, sex, tumor location, and Simpson grade [p=0.0311, HR=9.28, 95%CI=(1.22-70.29)]. The expression signature included genes encoding proteins involved in normal embryonic development, cell proliferation, tumor growth and invasion (FGF9, SEMA3C, EDNRA), angiogenesis (angiopoietin-2), cell cycle regulation (CDKN1A), membrane signaling (tetraspanin-7, caveolin-2), WNT-pathway inhibitors (DKK3), complement system (C1QA) and neurotransmitter regulation (SLC1A3, Secretogranin-II). CONCLUSIONS 18-GEP accurately stratifies patients with meningioma by recurrence risk having the potential to guide the use of adjuvant RT.