A critical evaluation of visual proportion of Gleason 4 and maximum cancer core length quantified by histopathologists.

Gleason score 7 prostate cancer with a higher proportion of pattern 4 (G4) has been linked to genomic heterogeneity and poorer patient outcome. The current assessment of G4 proportion uses estimation by a pathologist, with a higher proportion of G4 more likely to trigger additional imaging and treatment over active surveillance. This estimation method has been shown to have inter-observer variability. Fifteen patients with Prostate Grade Group (GG) 2 (Gleason 3 + 4) and fifteen patients with GG3 (Gleason 4 + 3) disease were selected from the PROMIS study with 192 haematoxylin and eosin-stained slides scanned. Two experienced uropathologists assessed the maximum cancer core length (MCCL) and G4 proportion using the current standard method (visual estimation) followed by detailed digital manual annotation of each G4 area and measurement of MCCL (planimetric estimation) using freely available software by the same two experts. We aimed to compare visual estimation of G4 and MCCL to a pathologist-driven digital measurement. We show that the visual and digital MCCL measurement differs up to 2 mm in 76.6% (23/30) with a high degree of agreement between the two measurements; Visual gave a median MCCL of 10 ± 2.70 mm (IQR 4, range 5-15 mm) compared to digital of 9.88 ± 3.09 mm (IQR 3.82, range 5.01-15.7 mm) (p = 0.64) The visual method for assessing G4 proportion over-estimates in all patients, compared to digital measurements [median 11.2% (IQR 38.75, range 4.7-17.9%) vs 30.4% (IQR 18.37, range 12.9-50.76%)]. The discordance was higher as the amount of G4 increased (Bias 18.71, CI 33.87-48.75, r 0.7, p < 0.0001). Further work on assessing actual G4 burden calibrated to clinical outcomes might lead to the use of differing G4 thresholds of significance if the visual estimation is used or by incorporating semi-automated methods for G4 burden measurement.

Cerebrovascular disease in patients with COVID-19: neuroimaging, histological and clinical description.

Since the appearance of the first case of coronavirus disease 2019 (COVID-19) a pandemic has emerged affecting millions of individuals worldwide. Although the main clinical manifestations are respiratory, an increase in neurological conditions, specifically acute cerebrovascular disease, has been detected. We present cerebrovascular disease case incidence in hospitalized patients with SARS-CoV-2 infection. Patients were confirmed by microbiological/serological testing, or on chest CT semiology. Available data on co-morbidity, laboratory parameters, treatment administered, neuroimaging, neuropathological studies and clinical evolution during hospitalization, measured by the modified Rankin scale, were analysed. A bivariate study was also designed to identify differences between ischaemic and haemorrhagic subtypes. A statistical model of binary logistic regression and sensitivity analysis was designed to study the influence of independent variables over prognosis. In our centre, there were 1683 admissions of patients with COVID-19 over 50 days, of which 23 (1.4%) developed cerebrovascular disease. Within this group of patients, cerebral and chest CT scans were performed in all cases, and MRI in six (26.1%). Histological samples were obtained in 6/23 cases (two brain biopsies, and four arterial thrombi). Seventeen patients were classified as cerebral ischaemia (73.9%, with two arterial dissections), five as intracerebral haemorrhage (21.7%), and one leukoencephalopathy of posterior reversible encephalopathy type. Haemorrhagic patients had higher ferritin levels at the time of stroke (1554.3 versus 519.2, P = 0.004). Ischaemic strokes were unexpectedly frequent in the vertebrobasilar territory (6/17, 35.3%). In the haemorrhagic group, a characteristic radiological pattern was identified showing subarachnoid haemorrhage, parieto-occipital leukoencephalopathy, microbleeds and single or multiple focal haematomas. Brain biopsies performed showed signs of thrombotic microangiopathy and endothelial injury, with no evidence of vasculitis or necrotizing encephalitis. The functional prognosis during the hospital period was unfavourable in 73.9% (17/23 modified Rankin scale 4-6), and age was the main predictive variable (odds ratio = 1.5; 95% confidence interval 1.012-2.225; P = 0.043). Our series shows cerebrovascular disease incidence of 1.4% in patients with COVID-19 with high morbidity and mortality. We describe pathological and radiological data consistent with thrombotic microangiopathy caused by endotheliopathy with a haemorrhagic predisposition.

Intraoperative Ultrasonographic Elastography: A Semi-Quantitative Analysis of Brain Tumor Elasticity Patterns and Peritumoral Region.

BACKGROUND: Ultrasonographic elastography imaging visualizes the elastic properties of tissues to distinguish pathologic and healthy areas. Real-time elastography measures relative tissue hardness by evaluating changes in local strain in response to external forces. OBJECTIVE: We aimed to determine the elastographic patterns of different brain tumor types and establish differences between their peritumoral regions. METHODS: We prospectively enrolled patients undergoing craniotomy along with intraoperative ultrasonographic elastography for supratentorial brain tumors in March 2018-May 2019. The elastograms were semi-quantitatively analyzed offline based on the mean tissue elasticity of the tumors, peritumoral regions, and healthy parenchyma. RESULTS: We examined 37 lesions in 36 patients. The pathologic diagnoses comprised 11 meningiomas (29.7%), 4 low-grade gliomas (LGGs; 10.8%), 16 high-grade gliomas (HGGs; 43.2%), and 6 metastases (16.2%). The median MTE values observed after manual segmentation of the whole tumor were as follows: meningiomas, 119.9 (36.6); HGGs, 77.9 (18.9); LGGs, 91 (19.5); metastases, 103.9 (35.6); tumor types significantly differed (H = 18.2; P < 0.001). The peritumoral MTE values were as follows: meningiomas, 120.1 (36.3); HGGs, 86.3 (20.9); LGGs, 94.8 (7.38); and metastases, 116.3 (22). The intergroup differences were significant (H = 17.43; P < 0.001). Using receiver operating characteristic curves, we obtained an optimal cutoff point of 92.22 (whole tumors) and 109.6 (peritumoral regions). Values below these cutoff points were correlated with a high probability of being a glioma. CONCLUSIONS: We objectively describe the elastographic patterns of different types of brain tumors (i.e., gliomas, metastases, and meningiomas). We have identified differences in both the tumors and the peritumoral areas of these histologic types.

mTOR inhibition decreases SOX2-SOX9 mediated glioma stem cell activity and temozolomide resistance.

BACKGROUND: SOX2 and SOX9 are commonly overexpressed in glioblastoma, and regulate the activity of glioma stem cells (GSCs). Their specific and overlapping roles in GSCs and glioma treatment remain unclear. METHODS: SOX2 and SOX9 levels were examined in human biopsies. Gain and loss of function determined the impact of altering SOX2 and SOX9 on cell proliferation, senescence, stem cell activity, tumorigenesis and chemoresistance. RESULTS: SOX2 and SOX9 expression correlates positively in glioma cells and glioblastoma biopsies. High levels of SOX2 bypass cellular senescence and promote resistance to temozolomide. Mechanistic investigations revealed that SOX2 acts upstream of SOX9. mTOR genetic and pharmacologic (rapamycin) inhibition decreased SOX2 and SOX9 expression, and reversed chemoresistance. CONCLUSIONS: Our findings reveal SOX2-SOX9 as an oncogenic axis that regulates stem cell properties and chemoresistance. We identify that rapamycin abrogate SOX protein expression and provide evidence that a combination of rapamycin and temozolomide inhibits tumor growth in cells with high SOX2/SOX9.

A small noncoding RNA signature found in exosomes of GBM patient serum as a diagnostic tool.

BACKGROUND: Glioblastoma multiforme (GBM) is the most frequent malignant brain tumor in adults, and its prognosis remains dismal despite intensive research and therapeutic advances. Diagnostic biomarkers would be clinically meaningful to allow for early detection of the tumor and for those cases in which surgery is contraindicated or biopsy results are inconclusive. Recent findings show that GBM cells release microvesicles that contain a select subset of cellular proteins and RNA. The aim of this hypothesis-generating study was to assess the diagnostic potential of miRNAs found in microvesicles isolated from the serum of GBM patients. METHODS: To control disease heterogeneity, we used patients with newly diagnosed GBM. In the discovery stage, PCR-based TaqMan Low Density Arrays followed by individual quantitative reverse transcriptase polymerase chain reaction were used to test the differences in the miRNA expression levels of serum microvesicles among 25 GBM patients and healthy controls paired by age and sex. The detected noncoding RNAs were then validated in another 50 GBM patients. RESULTS: We found that the expression levels of 1 small noncoding RNA (RNU6-1) and 2 microRNAs (miR-320 and miR-574-3p) were significantly associated with a GBM diagnosis. In addition, RNU6-1 was consistently an independent predictor of a GBM diagnosis. CONCLUSIONS: Altogether our results uncovered a small noncoding RNA signature in microvesicles isolated from GBM patient serum that could be used as a fast and reliable differential diagnostic biomarker.

Therapeutic strategies targeting glioblastoma stem cells.

Glioblastoma is the most common, aggressive and lethal brain tumor in adults. However, current therapeutic protocols have low success rates and average overall survival is less than 15 months. The resistance to therapy is largely a result of the remarkable cellular and phenotypical heterogeneity that characterizes this type of tumor. The discovery of a subpopulation of cells exhibiting stem cell properties within the tumor bulk has profound implications for therapy as increasing evidence indicates that these cells, glioblastoma stem cells (GSCs), are responsible for the origin, maintenance and recurrence of the glioblastomas. These findings highlight the need to characterize GSCs in order to find novel treatments directly targeted specifically against them. In this review, we summarize the current knowledge regarding this issue, including some recent and relevant patents.