Faculty Bibliography

The dynamic and reversible N⁶-methyladenosine (m⁶A) RNA modification installed and erased by N⁶-methyltransferases and demethylases regulates gene expression and cell fate. We show that the m⁶A demethylase ALKBH5 is highly expressed in glioblastoma stem-like cells (GSCs). Silencing ALKBH5 suppresses the proliferation of patient-derived GSCs. Integrated transcriptome and m⁶A-seq analyses revealed altered expression of certain ALKBH5 target genes, including the transcription factor FOXM1. ALKBH5 demethylates FOXM1 nascent transcripts, leading to enhanced FOXM1 expression. Furthermore, a long non-coding RNA antisense to FOXM1 (FOXM1-AS) promotes the interaction of ALKBH5 with FOXM1 nascent transcripts. Depleting ALKBH5 and FOXM1-AS disrupted GSC tumorigenesis through the FOXM1 axis. Our work uncovers a critical function for ALKBH5 and provides insight into critical roles of m⁶A methylation in glioblastoma.

Glioblastoma (GBM) is an ideal candidate disease for signal transduction targeted therapy because the majority of these tumors harbor genetic alterations that result in aberrant activation of growth factor signaling pathways. Loss of heterozygosity of chromosome 10, mutations in the tumor suppressor gene PTEN, and PI3K mutations are molecular hallmarks of GBM and indicate poor prognostic outcomes in many cancers. Consequently, inhibiting the PI3K pathway may provide therapeutic benefit in these cancers. PI3K inhibitors generally block proliferation rather than induce apoptosis. To restore the sensitivity of GBM to apoptosis induction, targeted agents have been combined with conventional therapy. However, the molecular heterogeneity and infiltrative nature of GBM make it resistant to traditional single agent therapy. Our objectives were to test a dual PI3K/mTOR inhibitor that may cross the blood-brain barrier (BBB) and provide the rationale for using this inhibitor in combination regimens to chemotherapy-induced synergism in GBM. Here we report the preclinical potential of a novel, orally bioavailable PI3K/mTOR dual inhibitor, DS7423 (hereafter DS), in in-vitro and in-vivo studies. DS was tested in mice, and DS plasma and brain concentrations were determined. DS crossed the BBB and led to potent suppression of PI3K pathway biomarkers in the brain. The physiologically relevant concentration of DS was tested in 9 glioma cell lines and 22 glioma-initiating cell (GIC) lines. DS inhibited the growth of glioma tumor cell lines and GICs at mean 50% inhibitory concentration values of less than 250 nmol/L. We found that PI3K mutations and PTEN alterations were associated with cellular response to DS treatment; with preferential inhibition of cell growth in PI3KCA-mutant and PTEN altered cell lines. DS showed efficacy and survival benefit in the U87 and GSC11 orthotopic models of GBM. Furthermore, administration of DS enhanced the antitumor efficacy of temozolomide against GBM in U87 glioma models, which shows that PI3K/mTOR inhibitors may enhance alkylating agent-mediated cytotoxicity, providing a novel regimen for the treatment of GBM. Our present findings establish that DS can specifically be used in patients who have PI3K pathway activation and/or loss of PTEN function. Further studies are warranted to determine the potential of DS for glioma treatment.

The classification of brain tumors has traditionally depended on microscopic examination of hematoxylin and eosin-stained tissue sections. The increased understanding of clinically relevant genetic alterations has led to the incorporation of molecular signatures as part of the diagnosis of brain malignancies. Advances in sequencing technologies have facilitated the use of next-generation sequencing (NGS) assays in clinical laboratories. We performed a retrospective analysis of sequencing results for 381 brain tumors tested by NGS at our institution using a validated, commercially available panel. The results of the NGS assay were analyzed in conjunction with the results of immunohistochemical stains. A genetic alteration was detected in approximately two thirds of the cases. The most commonly mutated genes were TP53 (37.2%), IDH1 (29.4%), PIK3CA (8%), PTEN (8%), and EGFR (7.5%). BRAF mutations were detected in ∼3% of the cases, including 50% of gangliogliomas and ∼20% of gliosarcomas. No mutations were detected in 6 medulloblastomas. PIK3CA and CTNNB1 mutations were detected in 1 rosette-forming glioneuronal tumor and 1 adamantinomatous craniopharyngioma, respectively. Approximately 23% of cases showed amplification of 1 or more of the genes included in the NGS panel. This analysis demonstrates the utility of NGS for detecting genetic alterations in brain tumors in the clinical setting.

Meningioma is the most common primary brain tumor and carries a substantial risk of local recurrence. Methylation profiles of meningioma and their clinical implications are not well understood. We hypothesized that aggressive meningiomas have unique DNA methylation patterns that could be used to better stratify patient management. Samples (n = 140) were profiled using the Illumina HumanMethylation450BeadChip. Unsupervised modeling on a training set (n = 89) identified 2 molecular methylation subgroups of meningioma (MM) with significantly different recurrence-free survival (RFS) times between the groups: a prognostically unfavorable subgroup (MM-UNFAV) and a prognostically favorable subgroup (MM-FAV). This finding was validated in the remaining 51 samples and led to a baseline meningioma methylation classifier (bMMC) defined by 283 CpG loci (283-bMMC). To further optimize a recurrence predictor, probes subsumed within the baseline classifier were subject to additional modeling using a similar training/validation approach, leading to a 64-CpG loci meningioma methylation predictor (64-MMP). After adjustment for relevant clinical variables [WHO grade, mitotic index, Simpson grade, sex, location, and copy number aberrations (CNAs)] multivariable analyses for RFS showed that the baseline methylation classifier was not significant (p = 0.0793). The methylation predictor, however, was significantly associated with tumor recurrence (p < 0.0001). CNAs were extracted from the 450k intensity profiles. Tumor samples in the MM-UNFAV subgroup showed an overall higher proportion of CNAs compared to the MM-FAV subgroup tumors and the CNAs were complex in nature. CNAs in the MM-UNFAV subgroup included recurrent losses of 1p, 6q, 14q and 18q, and gain of 1q, all of which were previously identified as indicators of poor outcome. In conclusion, our analyses demonstrate robust DNA methylation signatures in meningioma that correlate with CNAs and stratify patients by recurrence risk.

Purpose The American Society for Radiation Oncology (ASTRO) produced an evidence-based guideline on radiation therapy for glioblastoma. Because of its relevance to the ASCO membership, ASCO reviewed the guideline and applied a set of procedures and policies used to critically examine guidelines developed by other organizations. Methods The ASTRO guideline on radiation therapy for glioblastoma was reviewed for developmental rigor by methodologists. An ASCO endorsement panel updated the literature search and reviewed the content and recommendations. Results The ASCO endorsement panel determined that the recommendations from the ASTRO guideline, published in 2016, are clear, thorough, and based on current scientific evidence. ASCO endorsed the ASTRO guideline on radiation therapy for glioblastoma and added qualifying statements. Recommendations Partial-brain fractionated radiotherapy with concurrent and adjuvant temozolomide is the standard of care after biopsy or resection of newly diagnosed glioblastoma in patients up to 70 years of age. Hypofractionated radiotherapy for elderly patients with fair to good performance status is appropriate. The addition of concurrent and adjuvant temozolomide to hypofractionated radiotherapy seems to be safe and efficacious without impairing quality of life for elderly patients with good performance status. Reasonable options for patients with poor performance status include hypofractionated radiotherapy alone, temozolomide alone, or best supportive care. Focal reirradiation represents an option for select patients with recurrent glioblastoma, although this is not supported by prospective randomized evidence. Additional information is available at www.asco.org/glioblastoma-radiotherapy-endorsement and www.asco.org/guidelineswiki .

BACKGROUND:Dexamethasone is reported to induce both tumor-suppressive and tumor-promoting effects. The purpose of this study was to identify the genomic impact of dexamethasone in glioblastoma stem cell (GSC) lines and its prognostic value; furthermore, to identify drugs that can counter these side effects of dexamethasone exposure. METHODS:We utilized 3 independent GSC lines with tumorigenic potential for this study. Whole-genome expression profiling and pathway analyses were done with dexamethasone-exposed and control cells. GSCs were also co-exposed to dexamethasone and temozolomide. Risk scores were calculated for most affected genes, and their associations with survival in The Cancer Genome Atlas and Repository of Molecular Brain Neoplasia Data databases. In silico Connectivity Map analysis identified camptothecin as antagonist to dexamethasone-induced negative effects. RESULTS:Pathway analyses predicted an activation of dexamethasone network (z-score: 2.908). Top activated canonical pathways included "role of breast cancer 1 in DNA damage response" (P=1.07E-04). GSCs were protected against temozolomide-induced apoptosis when coincubated with dexamethasone. Altered cellular functions included cell movement, cell survival, and apoptosis with z-scores of 2.815, 5.137, and -3.122, respectively. CCAAT/enhancer binding protein beta (CEBPB) was activated in a dose dependent manner specifically in slow-dividing "stem-like" cells. CEBPB was activated in dexamethasone-treated orthotopic tumors. Patients with high risk scores had significantly shorter survival. Camptothecin was validated as potential partial neutralizer of dexamethasone-induced oncogenic effects. CONCLUSIONS:Dexamethasone exposure induces a genetic program and CEBPB expression in GSCs that adversely affects key cellular functions and response to therapeutics. High risk scores associated with these genes have negative prognostic value in patients. Our findings further suggest camptothecin as a potential neutralizer of adverse dexamethasone-mediated effects.

BACKGROUND:Glioma, the most common primary brain neoplasm, describes a heterogeneous tumor of multiple histologic subtypes and cellular origins. At clinical presentation, gliomas are graded according to the World Health Organization guidelines (WHO), which reflect the malignant characteristics of the tumor based on histopathological and molecular features. Lower grade diffuse gliomas (LGGs) (WHO Grade II-III) have fewer malignant characteristics than high-grade gliomas (WHO Grade IV), and a better clinical prognosis, however, accurate discrimination of overall survival (OS) remains a challenge. In this study, we aimed to identify tissue-derived image features using a machine learning approach to predict OS in a mixed histology and grade cohort of lower grade glioma patients. To achieve this aim, we used H and E stained slides from the public LGG cohort of The Cancer Genome Atlas (TCGA) to create a machine learned dictionary of "image-derived visual words" associated with OS. We then evaluated the combined efficacy of using these visual words in predicting short versus long OS by training a generalized machine learning model. Finally, we mapped these predictive visual words back to molecular signaling cascades to infer potential drivers of the machine learned survival-associated phenotypes. METHODS:We analyzed digitized histological sections downloaded from the LGG cohort of TCGA using a bag-of-words approach. This method identified a diverse set of histological patterns that were further correlated with OS, histology, and molecular signaling activity using Cox regression, analysis of variance, and Spearman correlation, respectively. A support vector machine (SVM) model was constructed to discriminate patients into short and long OS groups dichotomized at 24-month. RESULTS:This method identified disease-relevant phenotypes associated with OS, some of which are correlated with disease-associated molecular pathways. From these image-derived phenotypes, a generalized SVM model which could discriminate 24-month OS (area under the curve, 0.76) was obtained. CONCLUSION/CONCLUSIONS:Here, we demonstrated one potential strategy to incorporate image features derived from H and E stained slides into predictive models of OS. In addition, we showed how these image-derived phenotypic characteristics correlate with molecular signaling activity underlying the etiology or behavior of LGG.