Unsupervised machine learning models reveal predictive clinical markers of glioblastoma patient survival using white blood cell counts prior to initiating chemoradiation.

Background: Glioblastoma is a malignant brain tumor requiring careful clinical monitoring even after primary management. Personalized medicine has suggested the use of various molecular biomarkers as predictors of patient prognosis or factors utilized for clinical decision-making. However, the accessibility of such molecular testing poses a constraint for various institutes requiring identification of low-cost predictive biomarkers to ensure equitable care. Methods: We collected retrospective data from patients seen at Ohio State University, University of Mississippi, Barretos Cancer Hospital (Brazil), and FLENI (Argentina) who were managed for glioblastoma-amounting to 581 patient records documented using REDCap. Patients were evaluated using an unsupervised machine learning approach comprised of dimensionality reduction and eigenvector analysis to visualize the inter-relationship of collected clinical features. Results: We discovered that the serum white blood cell (WBC) count of a patient during baseline planning for treatment was predictive of overall survival with an over 6-month median survival difference between the upper and lower quartiles of WBC count. By utilizing an objective PD-L1 immunohistochemistry quantification algorithm, we were further able to identify an increase in PD-L1 expression in glioblastoma patients with high serum WBC counts. Conclusions: These findings suggest that in a subset of glioblastoma patients the incorporation of WBC count and PD-L1 expression in the brain tumor biopsy as simple biomarkers predicting glioblastoma patient survival. Moreover, machine learning models allow the distillation of complex clinical data sets to uncover novel and meaningful clinical relationships.

Glioblastoma pseudoprogression and true progression reveal spatially variable transcriptional differences.

Post-resection radiologic monitoring to identify areas of new or progressive enhancement concerning for cancer recurrence is critical during patients with glioblastoma follow-up. However, treatment-related pseudoprogression presents with similar imaging features but requires different clinical management. While pathologic diagnosis is the gold standard to differentiate true progression and pseudoprogression, the lack of objective clinical standards and admixed histologic presentation creates the needs to (1) validate the accuracy of current approaches and (2) characterize differences between these entities to objectively differentiate true disease. We demonstrated using an online RNAseq repository of recurrent glioblastoma samples that cancer-immune cell activity levels correlate with heterogenous clinical outcomes in patients. Furthermore, nCounter RNA expression analysis of 48 clinical samples taken from second neurosurgical resection supports that pseudoprogression gene expression pathways are dominated with immune activation, whereas progression is predominated with cell cycle activity. Automated image processing and spatial expression analysis however highlight a failure to apply these broad expressional differences in a subset of cases with clinically challenging admixed histology. Encouragingly, applying unsupervised clustering approaches over our segmented histologic images provides novel understanding of morphologically derived differences between progression and pseudoprogression. Spatially derived data further highlighted polarization of myeloid populations that may underscore the tumorgenicity of novel lesions. These findings not only help provide further clarity of potential targets for pathologists to better assist stratification of progression and pseudoprogression, but also highlight the evolution of tumor-immune microenvironment changes which promote tumor recurrence.

Unsupervised machine learning models reveal predictive markers of glioblastoma patient survival using white blood cell counts prior to initiating chemoradiation.

Purpose: Glioblastoma is a malignant brain tumor requiring careful clinical monitoring even after primary management. Personalized medicine has suggested use of various molecular biomarkers as predictors of patient prognosis or factors utilized for clinical decision making. However, the accessibility of such molecular testing poses a constraint for various institutes requiring identification of low-cost predictive biomarkers to ensure equitable care. Methods: We collected retrospective data from patients seen at Ohio State University, University of Mississippi, Barretos Cancer Hospital (Brazil), and FLENI (Argentina) who were managed for glioblastoma-amounting to nearly 600 patient records documented using REDCap. Patients were evaluated using an unsupervised machine learning approach comprised of dimensionality reduction and eigenvector analysis to visualize the inter-relationship of collected clinical features. Results: We discovered that white blood cell count of a patient during baseline planning for treatment was predictive of overall survival with an over 6-month median survival difference between the upper and lower quartiles of white blood cell count. By utilizing an objective PDL-1 immunohistochemistry quantification algorithm, we were further able to identify an increase in PDL-1 expression in glioblastoma patients with high white blood cell counts. Conclusion: These findings suggest that in a subset of glioblastoma patients the incorporation of white blood cell count and PDL-1 expression in the brain tumor biopsy as simple biomarkers predicting glioblastoma patient survival. Moreover, use of machine learning models allows us to visualize complex clinical datasets to uncover novel clinical relationships.

Disruption of DNA Repair and Survival Pathways through Heat Shock Protein Inhibition by Onalespib to Sensitize Malignant Gliomas to Chemoradiation Therapy.

PURPOSE: Proficient DNA repair by homologous recombination (HR) facilitates resistance to chemoradiation in glioma stem cells (GSC). We evaluated whether compromising HR by targeting HSP90, a molecular chaperone required for the function of key HR proteins, using onalespib, a long-acting, brain-penetrant HSP90 inhibitor, would sensitize high-grade gliomas to chemoradiation in vitro and in vivo. EXPERIMENTAL DESIGN: The ability of onalespib to deplete HR client proteins, impair HR repair capacity, and sensitize glioblastoma (GBM) to chemoradiation was evaluated in vitro in GSCs, and in vivo using zebrafish and mouse intracranial glioma xenograft models. The effects of HSP90 inhibition on the transcriptome and cytoplasmic proteins was assessed in GSCs and in ex vivo organotypic human glioma slice cultures. RESULTS: Treatment with onalespib depleted CHK1 and RAD51, two key proteins of the HR pathway, and attenuated HR repair, sensitizing GSCs to the combination of radiation and temozolomide (TMZ). HSP90 inhibition reprogrammed the transcriptome of GSCs and broadly altered expression of cytoplasmic proteins including known and novel client proteins relevant to GSCs. The combination of onalespib with radiation and TMZ extended survival in a zebrafish and a mouse xenograft model of GBM compared with the standard of care (radiation and TMZ) or onalespib with radiation. CONCLUSIONS: The results of this study demonstrate that targeting HR by HSP90 inhibition sensitizes GSCs to radiation and chemotherapy and extends survival in zebrafish and mouse intracranial models of GBM. These results provide a preclinical rationale for assessment of HSP90 inhibitors in combination with chemoradiation in patients with GBM.

Inhibition of nicotinamide phosphoribosyltransferase (NAMPT), the rate-limiting enzyme of the nicotinamide adenine dinucleotide (NAD) salvage pathway, to target glioma heterogeneity through mitochondrial oxidative stress.

BACKGROUND: Tumor-specific metabolic processes essential for cell survival are promising targets to potentially circumvent intratumoral heterogeneity, a major resistance factor in gliomas. Tumor cells preferentially using nicotinamide phosphoribosyltransferase (NAMPT), the rate-limiting enzyme in the salvage pathway for synthesis of NAD, a critical cofactor for diverse biological processes including cellular redox reactions, energy metabolism, and biosynthesis. NAMPT is overexpressed in most malignancies, including gliomas, and can serve as a tumor-specific target. METHODS: Effects of pharmacological inhibition of NAMPT on cellular oxygen consumption rate, extracellular acidification, mitochondrial respiration, cell proliferation, invasion, and survival were assessed through in vitro and ex vivo studies on genetically heterogeneous glioma cell lines, glioma stem-like cells (GSCs), and mouse and human ex vivo organotypic glioma slice culture models. RESULTS: Pharmacological inhibition of the NAD salvage biosynthesis pathway using a highly specific inhibitor, KPT-9274, resulted in the reduction of NAD levels and related downstream metabolites, inhibited proliferation, and induced apoptosis in vitro in cell lines and ex vivo in human glioma tissue. These effects were mediated by mitochondrial dysfunction, DNA damage, and increased oxidative stress leading to apoptosis in GSCs independent of genotype, IDH status, or MGMT promoter methylation status. Conversely, NAMPT inhibition had minimal in vitro effects on normal human astrocytes (NHA) and no apparent in vivo toxicity in non-tumor-bearing mice. CONCLUSIONS: Pharmacological NAMPT inhibition by KPT9274 potently targeted genetically heterogeneous gliomas by activating mitochondrial dysfunction. Our preclinical results provide a rationale for targeting the NAMPT-dependent alternative NAD biosynthesis pathway as a novel clinical strategy against gliomas.

Clinical and Radiologic Outcomes After Fenestration and Partial Wall Excision of Idiopathic Intradural Spinal Arachnoid Cysts Presenting with Myelopathy.

BACKGROUND: Intradural spinal arachnoid cysts (ISACs) with associated neurologic deficits are encountered infrequently. Various management strategies have been proposed with minimal data on comparative outcomes. OBJECTIVE: We describe the clinical and radiologic presentation as well as the outcomes of 14 surgically managed patients who presented with an ISAC and associated myelopathy. METHODS: We retrospectively reviewed the clinical course of consecutive patients presenting with neurologic deficits associated with idiopathic ISACs at our institution. The diagnoses were based on preoperative magnetic resonance imaging studies followed by intraoperative and histopathological confirmation. RESULTS: A total of 14 consecutive patients with ISACs (1 cervicothoracic, 12 thoracic, and 1 thoracolumbar) and associated myelopathy were identified. Syringomyelia was noted in 8 patients. All ISACs were treated with cyst fenestration and partial wall resection through a posterior approach. Preoperative neurologic symptoms were noted to be stable or improved in all patients starting at 6-week postoperative follow-up. The median (interquartile range) preoperative mJOA score was 13 (12.0-14.8), whereas the postoperative median score at a mean follow-up of 22 months (range 6-50 months) was 16 (14.0-17.0), which represents a median improvement (ΔmJOA) of 2.0 (1.3-3.0) (P < 0.001). Comparison of ΔmJOA scores between cases without and with associated syrinxes did not reveal a significant difference (P = 0.23). Postoperative magnetic resonance imaging scans revealed spinal cord re-expansion at the level of the ISAC in all cases and either complete or partial syrinx resolution in 7 of 8 cases. CONCLUSIONS: Early treatment with fenestration and partial wall resection allows for cord decompression, syrinx resolution, and gradual resolution of myelopathic symptoms in most cases.