Clinical Utility of Molecular Profiling in Recurrent Glioblastoma Multiforme

Introduction: Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor found in adults. GBM has limited therapeutic options. Initial tumor sampling establishes the histopathologic diagnosis, identifies prognostic and therapeutic biomarkers, and provides an opportunity for molecular profiling. By contrast, the utility of repeat tumor sampling and molecular profiling in recurrent GBM is not well established. Clinical Findings: We present a 69-year-old woman with GBM whose tumor recurred after standard treatment with temozolomide (TMZ) and concurrent radiation, followed by adjuvant TMZ. This patient had a methylated O6-methylguanine-DNA methyltransferase (MGMT) promoter, which ordinarily predicts a favorable response to TMZ. Main Diagnosis, Therapeutic Interventions, and Outcomes: Our patient’s recurrent tumor was rechallenged with TMZ based on persistent methylation of the MGMT promoter. However, her tumor was refractory to TMZ, and she floridly progressed through multiple treatments. We performed retrospective molecular profiling using next-generation sequencing (NGS) on her recurrent tumor. The NGS results showed a TMZ hypermutation signature that confers resistance to TMZ. This signature impacted our patient’s treatment plan in real time and prompted an immediate discontinuation of TMZ. Conclusions: Advances in NGS provide further insight into the molecular landscape of GBM. As NGS becomes more timely and cost-effective, molecular profiling of recurrent tumors could impact treatment decisions through either avoiding a particular treatment paradigm or identifying a potential targetable mutation. For this reason, we suggest that clinical practice routinely consider repeat biopsy and molecular profiling for recurrent GBM

Epistemic Beliefs: Relationship to Future Expectancies and Quality of Life in Cancer Patients.

CONTEXT: Expectations about the future (future expectancies) are important determinants of psychological well-being among cancer patients, but the strategies patients use to maintain positive and cope with negative expectancies are incompletely understood. OBJECTIVES: To obtain preliminary evidence on the potential role of one strategy for managing future expectancies: the adoption of epistemic beliefs in fundamental limits to medical knowledge. METHODS: A sample of 1307 primarily advanced-stage cancer patients participating in a genomic tumor testing study in community oncology practices completed measures of epistemic beliefs, positive future expectancies, and mental and physical health-related quality of life (HRQOL). Descriptive and linear regression analyses were conducted to assess the relationships between these factors and test two hypotheses: 1) epistemic beliefs affirming fundamental limits to medical knowledge ( fallibilistic epistemic beliefs ) are associated with positive future expectancies and mental HRQOL, and 2) positive future expectancies mediate this association. RESULTS: Participants reported relatively high beliefs in limits to medical knowledge (M = 2.94, s.d.=.67) and positive future expectancies (M = 3.01, s.d.=.62) (range 0-4), and relatively low mental and physical HRQOL. Consistent with hypotheses, fallibilistic epistemic beliefs were associated with positive future expectancies (b = 0.11, SE=.03, P\u3c 0.001) and greater mental HRQOL (b = 0.99, SE=.34, P = 0.004); positive expectancies also mediated the association between epistemic beliefs and mental HRQOL (Sobel Z=4.27, P\u3c0.001). CONCLUSIONS: Epistemic beliefs in limits to medical knowledge are associated with positive future expectancies and greater mental HRQOL; positive expectancies mediate the association between epistemic beliefs and HRQOL. More research is needed to confirm these relationships and elucidate their causal mechanisms

Physician-patient communication about genomic tumor testing: perceptions of oncology providers

Background: • Genomic tumor testing (GTT) is a new technology and a cornerstone of the “precision medicine” movement in cancer care. • GTT uses next-generation genome sequencing technology to identify somatic variants in tumor cells. • By identifying somatic variants that predict responses to cancer therapies, GTT can help tailor therapy to individual patients, making them more effective. • However, due to the fact that GTT also detects many variants of uncertain significance, its clinical value is currently unproven. • When using GTT, physicians counsel patients about both its benefits and its limitations, but the ideal goals and content of these physician-patient discussions have not been clearly defined

Community oncology clinicians’ knowledge, beliefs, and attitudes regarding genomic tumor testing

Introduction: Genomic tumor testing (GTT) is a new technology that promises to make cancer treatment more precise. However, little is known about clinicians’ knowledge, beliefs, and attitudes regarding GTT, particularly in community oncology settings

Genomic Profiling of Two Histologically Distinct Rare Urothelial Cancers in a Clinical Setting to Identify Potential Therapeutic Options for Treatment and Management of Disease.

Molecular profiling of urothelial cancers for therapeutic and prognostic potential has been very limited due to the absence of cancer-specific targeted therapies. We describe here 2 clinical cases with a histological diagnosis of an invasive sarcomatoid and a poorly differentiated carcinoma favoring urothelial with some neuroendocrine differentiation, two of the rarer types of urothelial cancers, which were evaluated for mutations in 212 genes for single-nucleotide variants and copy-number variants and 53 genes for fusions associated with solid tumors. In both cases, we identified variants in 2 genes, Case Rep Oncol 2018 Mar 27; 11(1):196-205

Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer.

Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of \u3e530 PKs have been targeted by FDA-approved medications, and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machine learning to investigate the relations between PKs and cancers, predicting PKs whose inhibition would be efficacious to treat a certain cancer. Our approach represents PKs and cancers as semantically meaningful 100-dimensional vectors based on word and concept neighborhoods in PubMed abstracts. We use information about phase I-IV trials in ClinicalTrials.gov to construct a training set for random forest classification. Our results with historical data show that associations between PKs and specific cancers can be predicted years in advance with good accuracy. Our tool can be used to predict the relevance of inhibiting PKs for specific cancers and to support the design of well-focused clinical trials to discover novel PKIs for cancer therapy

Community oncologists\u27 perceptions and utilization of large-panel genomic tumor testing.

PURPOSE: Large-panel genomic tumor testing (GTT) is an emerging technology with great promise but uncertain clinical value. Previous research has documented variability in academic oncologists\u27 perceptions and use of GTT, but little is known about community oncologists\u27 perceptions of GTT and how perceptions relate to clinicians\u27 intentions to use GTT. METHODS: Community oncology physicians (N = 58) participating in a statewide initiative aimed at improving access to large-panel GTT completed surveys assessing their confidence in using GTT, attitudes regarding the value of GTT, perceptions of barriers to GTT implementation, and future intentions to use GTTs. Descriptive and multivariable regression analyses were conducted to characterize these perceptions and to explore the relationships between them. RESULTS: There was substantial variability in clinicians\u27 perceptions of GTT. Clinicians generally had moderate confidence in their ability to use GTT, but lower confidence in patients\u27 ability to understand test results and access targeted treatment. Clinicians had positive attitudes regarding the value of GTT. Clinicians\u27 future intentions to use GTT were associated with greater confidence in using GTT and greater perceived barriers to implementing GTT, but not with attitudes about the value of GTT. CONCLUSIONS: Community oncologists\u27 perceptions of large-panel genomic tumor testing are variable, and their future intentions to use GTT are associated with both their confidence in and perceived barriers to its use, but not with their attitudes towards GTT. More research is needed to understand other factors that determine how oncologists perceive and use GTT in clinical practice

Lessons from non-canonical splicing

Recent improvements in experimental and computational techniques that are used to study the transcriptome have enabled an unprecedented view of RNA processing, revealing many previously unknown non-canonical splicing events. This includes cryptic events located far from the currently annotated exons and unconventional splicing mechanisms that have important roles in regulating gene expression. These non-canonical splicing events are a major source of newly emerging transcripts during evolution, especially when they involve sequences derived from transposable elements. They are therefore under precise regulation and quality control, which minimizes their potential to disrupt gene expression. We explain how non-canonical splicing can lead to aberrant transcripts that cause many diseases, and also how it can be exploited for new therapeutic strategies

The clinical significance of molecular subtyping in glioblastoma

Background: Glioblastoma (GBM) is the most aggressive primary brain tumor in adults. Three molecular subtypes (Proneural; Classical; Mesenchymal) have been described based on gene expression, but the clinical significance remains unclear. Methods: We studied 26 adult patients with GBM diagnosed between 2014 and 2019 at a single tertiary institution, for whom next generation sequencing and overall survival (OS) data were available. Genes were identified using a CLIA/CAP certified tumor panel. Results: Among 26 patients, the median age was 67 years and 16 (62%) were male. 23 (88%) initial tumors were IDH wildtype and 10 (38%) were MGMT methylated. At diagnosis, 22 (85%) initiated standardized temozolomide chemoradiation and 15 (58%) received bevacizumab, Optune, or an experimental agent. We stratified patients into shorter (OS \u3c 12 months, n=10) and longer (OS \u3e12 months, n=16) survival groups. Patients with longer survival tended to be younger, with higher KPS, and more extensive surgical resection. PTEN variants were more frequent among patients with shorter survival (3/10, 30% versus 0/16, 0%, p = 0.046), as were CDKN2A deletions (5/10, 50% versus 1/16, 6%, p = 0.018); CDK4 amplifications were not informative. TP53 variants were more frequent among longer survivors (9/16, 56% versus 2/10, 20%, p = 0.11), as were PDGFRA variants (2/16, 12.5% versus 0/10, 0%, p = 0.51). Overall, there was no association between EGFR variants and OS (3/10, 30% versus 4/16, 25%, p=1.0), although EGFR vIII was only observed among longer survivors (3/16, 19% versus 0/10, 0% p = 0.26). NF1 mutations were infrequent, with 1 per survival group. Conclusion: The Proneural subtype is associated with longer OS, mutations in TP53 and PDGFRA, and absent PTEN mutations. Our clinical data, although not always significant, were consistent with this. The Classical subtype is characterized by improved treatment sensitivity, EGFR variants, and CDKN2A deletions. Our data were not consistent with this. CDKN2A deletions were associated with shorter OS; EGFR vIII had potentially longer survival, and other EGFR variants had no relationship to OS. The Mesenchymal subtype (associated with NF1) could not be assessed due to low numbers