Search Results (5)

The glioblastoma (GBM) tumor microenvironment consists of a heterogeneous mixture of neoplastic and non-neoplastic cells, including immune cells. Tumor recurrence following standard-of-care therapy results in a rich landscape of inflammatory cells throughout the glioma-infiltrated cortex. Immune cells consisting of glioma-associated macrophages and microglia (GAMMs) overwhelmingly constitute the bulk of the recurrent glioblastoma (rGBM) microenvironment, in comparison to the highly cellular and proliferative tumor microenvironment characteristic of primary GBM. These immune cells dynamically interact within the tumor microenvironment and can contribute to disease progression and therapy resistance while also providing novel targets for emerging immunotherapies. Within these varying contexts, histological-based assessments of immune cells in rGBM, including immunohistochemistry (IHC) and immunofluorescence (IF), offer a critical way to visualize and examine the inflammatory landscape. Here, we exhaustively review the available body of literature on the inflammatory landscape in rGBM as identified through histological-based assessments. We highlight the heterogeneity of immune cells throughout the glioma-infiltrated cortex with a focus on microglia and macrophages, drawing insights from canonical and novel immune-cell histological markers to estimate cell phenotypes and function. Lastly, we discuss opportunities for immunomodulatory treatments aiming to harness the inflammatory landscape in rGBM. Full article

Indeterminate thyroid nodules (ITN) represent 20–30% of biopsied nodules, with a 10–60% risk of malignancy. Molecular testing can stratify the risk of malignancy among ITNs, and subsequently reduce the need for unnecessary diagnostic surgery. We aimed to assess the performance of these molecular tests at a single institution. Patients with Bethesda III, IV, and V nodules with Afirma and Interpace Diagnostics genetic testing data from November 2013 to November 2021 were included. Three cohorts were formed, including GSC + XA, ThyGeNEXT + ThyraMIR, and GSC + GEC. Statistical analysis determined the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), diagnostic odds ratio (DOR), and accuracy of each type of testing. The PPV of nodules undergoing genetic testing by ThyGeNEXT + ThyraMIR (45.00%, 95%CI: 28.28–62.93%, p = 0.032) and GSC + XA (57.14%, 95%CI: 29.32–81.08%, p < 0.001) were superior to that of GEC + GSC (30.72%, 95%CI: 26.83–34.90%). The NPV was above 85% in all cohorts, suggesting overall suitable rule-out tests. The Afirma platform (GSC + XA) had the highest NPV at 96.97%. The overall accuracy for nodules undergoing ThyGeNEXT + ThyraMIR was 81.42% (95%CI: 73.01–88.11%, p < 0.001). A total of 230 patients underwent thyroidectomy, including less than 60% of each of the ThyGeNEXT + ThyraMIR and GSC + XA cohorts. Specifically, only 25% of patients in the GSC + XA cohort underwent surgery, considerably decreasing the rate of unnecessary surgical intervention. Sub-group analysis, including only patients with surgical pathology, found that PPV tended to be higher in the GSC + XA cohort, at 66.67% (95%CI: 37.28–87.06%), as compared to the ThyGeNEXT + ThyraMIR cohort, at 52.94% (95%CI: 35.25–69.92%). The Afirma genetic testing platform GSC + XA outperformed the other platforms with regards to both PPV and NPV and decreased the rate of surgery in patients with ITNs by 75%, significantly preventing unnecessary surgical intervention. Full article

Hashimoto’s thyroiditis (HT) (autoimmune thyroiditis) is a clinicopathological entity associated with chronic lymphocytic infiltration resulting in hypothyroidism. HT is a double-edged sword that increases the risk of papillary thyroid cancer (PTC), yet it serves as a protective factor for PTC progression. BRAF mutation in PTCs is associated with rapid cell growth, aggressive tumor characteristics, and higher mortality rates. Here, we aimed to analyze the influence of HT in patients with PTCs and its effect on lymph node metastasis (LNM) in BRAF mutant tumors. Adults diagnosed with PTC between 2008 and January 2021 were retrospectively included. A total of 427 patients, 128 of whom had underlying HT, were included. The HT group had significantly higher rates of microcarcinoma (49.2% vs. 37.5%, p = 0.025) and less lateral LNM (8.6% vs. 17.1%, p = 0.024). Interestingly, BRAF-mutated PTCs were found to have significantly less overall LNM (20.9% vs. 51%, p = 0.001), central LNM (25.6% vs. 45.1%, p = 0.040) and lateral LNM (9.3% vs. 29.4%, p = 0.010) in patients with HT when compared to those without underlying HT. HT was found to be an independent protective predictor of overall and lateral LNM. Altogether, HT was able to neutralize the effect of BRAF mutation and was determined to be an independent protective factor against LNM. Specifically, our work may influence treatment-aggressiveness decision making for endocrinologists, oncologists and surgeons alike. Full article

Background: Advanced breast cancer (abc) represents a substantial burden for patients and caregivers. In the present study, we aimed to estimate quality of life (qol), utility, productivity loss, pain, health care resource utilization, and costs for patients with abc, and qol, utility, and productivity loss for their caregivers. Methods: This multicentre prospective non-interventional study was conducted in Canada. Eligible participants were postmenopausal women with estrogen receptor–positive, her2-negative unresectable abc and their caregivers. Validated questionnaires were used to measure qol, utility, productivity loss, and pain. Patients and caregivers were classified into 4 health states typically used in oncology economic modelling: first-line progression-free (1l-pf), first-line progressive disease (1l-pd), second- or subsequent-line progression-free (≥2l-pf), and second- or subsequent-line progressive disease (≥2l-pd). Results: Most patients and caregivers accepted to participate, with total recruitment of 202 patients and 78 caregivers. Compared with patients in pf, patients in pd had lower mean qol scores (52.9 ± 29.9 for 1l-pd vs. 68.2 ± 23.2 for 1l-pf, and 54.0 ± 23.6 for ≥2l-pd vs. 66.0 ± 22.1 for ≥2l-pf), lower mean utility values (0.64 ± 0.22 for 1l-pd vs. 0.73 ± 0.20 for 1l-pf, and 0.65 ± 0.25 for ≥2l-pd vs. 0.74 ± 0.18 for ≥2l-pf), and greater productivity loss (39.4 ± 27.7 for 1l-pd vs. 27.5 ± 30.1 for 1l-pf, and 37.6 ± 29.2 for ≥2l-pd vs. 32.0 ± 29.0 for ≥2l-pf). Compared with caregivers of patients in pf, caregivers of patients in pd had lower qol scores and utility values, and greater productivity loss. Conclusions: Study results indicate that, for patients and caregivers, pd health states are associated with a deterioration of qol and utility and a decrease in productivity in both 1l and ≥2l. Full article

High-resolution drone aerial surveys combined with object-based image analysis are transforming our capacity to monitor and manage aquatic vegetation in an era of invasive species. To better exploit the potential of these technologies, there is a need to develop more efficient and accessible analysis workflows and focus more efforts on the distinct challenge of mapping submerged vegetation. We present a straightforward workflow developed to monitor emergent and submerged invasive water soldier (Stratiotes aloides) in shallow waters of the Trent-Severn Waterway in Ontario, Canada. The main elements of the workflow are: (1) collection of radiometrically calibrated multispectral imagery including a near-infrared band; (2) multistage segmentation of the imagery involving an initial separation of above-water from submerged features; and (3) automated classification of features with a supervised machine-learning classifier. The approach yielded excellent classification accuracy for emergent features (overall accuracy = 92%; kappa = 88%; water soldier producer’s accuracy = 92%; user’s accuracy = 91%) and good accuracy for submerged features (overall accuracy = 84%; kappa = 75%; water soldier producer’s accuracy = 71%; user’s accuracy = 84%). The workflow employs off-the-shelf graphical software tools requiring no programming or coding, and could therefore be used by anyone with basic GIS and image analysis skills for a potentially wide variety of aquatic vegetation monitoring operations. Full article