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Glioblastoma is an aggressive form of brain cancer with well-established patterns of intra-tumoral heterogeneity implicated in treatment resistance and progression. While regional and single cell transcriptomic variations of glioblastoma have been recently resolved, downstream phenotype-level proteomic programs have yet to be assigned across glioblastoma’s hallmark histomorphologic niches. Here, we leverage mass spectrometry to spatially align abundance levels of 4,794 proteins to distinct histologic patterns across 20 patients and propose diverse molecular programs operational within these regional tumor compartments. Using machine learning, we overlay concordant transcriptional information, and define two distinct proteogenomic programs, MYC- and KRAS-axis hereon, that cooperate with hypoxia to produce a tri-dimensional model of intra-tumoral heterogeneity. Moreover, we highlight differential drug sensitivities and relative chemoresistance in glioblastoma cell lines with enhanced KRAS programs. Importantly, these pharmacological differences are less pronounced in transcriptional glioblastoma subgroups suggesting that this model may provide insights for targeting heterogeneity and overcoming therapy resistance. Gioblastoma tumours consist of different niches defined by histology. Here, the authors use proteomics and machine learning to assign protein expression programs to these niches, and reveal that KRAS and hypoxia are associated with drug resistance.

Advancements in computer vision and artificial intelligence (AI) carry the potential to make significant contributions to health care, particularly in diagnostic specialties such as radiology and pathology. The impact of these technologies on physician stakeholders is the subject of significant speculation. There is however a dearth of information regarding the opinions, enthusiasm, and concerns of the pathology community at large. Here, we report results from a survey of 487 pathologist-respondents practicing in 54 countries, conducted to examine perspectives on AI implementation in clinical practice. Despite limitations, including difficulty with quantifying response bias and verifying identity of respondents to this anonymous and voluntary survey, several interesting findings were uncovered. Overall, respondents carried generally positive attitudes towards AI, with nearly 75% reporting interest or excitement in AI as a diagnostic tool to facilitate improvements in workflow efficiency and quality assurance in pathology. Importantly, even within the more optimistic cohort, a significant number of respondents endorsed concerns about AI, including the potential for job displacement and replacement. Overall, around 80% of respondents predicted the introduction of AI technology in the pathology laboratory within the coming decade. Attempts to identify statistically significant demographic characteristics (e.g., age, sex, type/place of practice) predictive of attitudes towards AI using Kolmogorov–Smirnov (KS) testing revealed several associations. Important themes which were commented on by respondents included the need for increasing efforts towards physician training and resolving medical-legal implications prior to the generalized implementation of AI in pathology.

Clinical samples are vital for understanding diseases, but their scarcity requires refined research methods. Emerging single-cell technologies offer detailed views of tissue heterogeneity but need sufficient fully characterized tissues. We developed an optimized single-nuclei RNA sequencing (snRNA-seq) protocol to extract nuclei from just 15 mg of cryopreserved human tissue. Applied to four cancer tissues (brain, bladder, lung, prostate), it profiled 1550–7468 nuclei per tissue, revealing heterogeneity comparable to public single-cell atlases. This method enhances the use and sharing of rare, cryopreserved biospecimens, supporting research where sample quantity is limited and full tissue characterization is needed.

Background Chronic subdural hematoma (CSDH) is one of the most frequent reason for cranial neurosurgical consultation. There is no widely accepted medical treatment for this condition. Herein, we present the protocol for the Tranexamic Acid (TXA) in Chronic Subdural Hematomas (TRACS) trial aiming at determining whether TXA can increase the rate of CSDH resolution following conservative management, lower the number of required surgical procedures and decrease the rate of CSDH recurrence following surgical evacuation. Methods TRACS is a multicenter, double-blind, randomized, parallel-design, placebo-controlled, phase IIB study designed to provide preliminary efficacy data as well as feasibility, safety and incidence data required to plan a larger definitive phase III trial. Consecutive patients presenting with a diagnosis of chronic subdural hematoma will be screened for eligibility. Exclusion criteria include: specific risk factors for thromboembolic disease, anticoagulant use or contraindication to TXA. A total of 130 patients will be randomized to receive either 750 mg of TXA daily or placebo until complete radiological resolution of the CSDH or for a maximum of 20 weeks. CSDH volume will be measured on serial computed tomography (CT) scanning. Cognitive function tests, quality of life questionnaires as well as functional autonomy assessments will be performed at enrollment, at 10 weeks following randomization and at 3 months following treatment cessation. During the treatment period, patients will undergo standard CSDH management with surgery being performed at the discretion of the treating physician. If surgery is performed, the CSDH and its outer membrane will be sampled for in vitro analysis. The primary outcome is the rate of CSDH resolution by 20 weeks without intervening unplanned surgical procedure. Secondary outcomes include: CSDH volume, incidence of surgical evacuation procedures, CSDH recurrence, cognitive functions, functional autonomy, quality of life, incidence of complications and length of hospital stay. Planned subgroup analyses will be performed for conservatively versus surgically managed subjects and highly versus poorly vascularized CSDH. Discussion CSDH is a frequent morbidity for which an effective medical treatment has yet to be discovered. The TRACS trial will be the first prospective study of TXA for CSDH. Trial registration NCT ID: NCT02568124 .

Deep learning has proven capable of automating key aspects of histopathologic analysis. However, its context-specific nature and continued reliance on large expert-annotated training datasets hinders the development of a critical mass of applications to garner widespread adoption in clinical/research workflows. Here, we present an online collaborative platform that streamlines tissue image annotation to promote the development and sharing of custom computer vision models for PHenotyping And Regional Analysis Of Histology (PHARAOH; https://www.pathologyreports.ai/ ). Specifically, PHARAOH uses a weakly supervised, human-in-the-loop learning framework whereby patch-level image features are leveraged to organize large swaths of tissue into morphologically-uniform clusters for batched annotation by human experts. By providing cluster-level labels on only a handful of cases, we show how custom PHARAOH models can be developed efficiently and used to guide the quantification of cellular features that correlate with molecular, pathologic and patient outcome data. Moreover, by using our PHARAOH pipeline, we showcase how correlation of cohort-level cytoarchitectural features with accompanying biological and outcome data can help systematically devise interpretable morphometric models of disease. Both the custom model design and feature extraction pipelines are amenable to crowdsourcing, positioning PHARAOH to become a fully scalable, systems-level solution for the expansion, generalization and cataloging of computational pathology applications. Faust, Chen, and colleagues present PHARAOH, a collaborative computational pathology platform that allows histologists to quickly develop custom labelled image datasets to train and catalogue a variety of machine learning models for histopathological analysis.

Background Gliomas are among the most malignant tumors, with a very poor prognosis. Early diagnosis is highly desirable since it can help implement more effective treatments for smaller tumors, which have not yet extensively metastasized. Improving early diagnosis may facilitate access of patients to clinical trials and prepare them for the future availability of new disease-modifying treatments. Methods We analyzed retrospective samples collected at diagnosis (before therapy initiation), with PEA (Olink Proteomics), quantifying about 3000 proteins. We utilized 30 plasmas from gliomas (20 glioblastomas, 5 anaplastic astrocytomas, 5 anaplastic oligodendrogliomas) and 20 meningiomas (as controls). We then analyzed the data to identify proteins which either alone, or in combination, could discriminate gliomas from meningiomas, or correlate with clinical and molecular alterations. Results We identified 8 plasma proteins which were increased in gliomas vs. meningiomas (GFAP, NEFL, EDDM3B, PROK1, MMP3, CTRL, GP2, SPINT3) and 4 proteins which were decreased in gliomas vs. meningiomas (FABP4, ALDH3A1, IL-12B and OXT). Partition algorithms and logistic regression algorithms with two biomarkers (GFAP and FABP4) achieved sensitivity of 83% and 93% at 100% and 90% specificity, respectively. The strongest single marker was GFAP with an area under the ROC curve (AUC) of 0.86. The AUC for the GFAP-FABP4 combination was 0.98. Conclusion PEA is a powerful new proteomic technology for biomarker discovery. GFAP and a handful of other plasma biomarkers may be useful for early glioma detection and probably, prognosis. Statement Detecting gliomas as early as possible is highly desirable since it can significantly improve the chances of effective treatments. Reliable glioma biomarkers can timely inform glioma patients about the efficacy of their prescribed treatment. Our results reveal some novel putative glioma markers that may prove valuable, when used alone or in combination, towards improved clinical care of gliomas. In order to better appreciate the potential usefulness of these markers, their performance needs to be further validated in a larger cohort of samples.

Background Effectiveness of chemotherapy for treating glioblastoma (GBM) brain tumors is hampered by the blood–brain barrier which limits the entry into the brain of most drugs from the blood. To bypass this barrier, convection-enhanced delivery (CED) was proposed to directly inject drugs in tumor. However, the benefit of CED may be hampered when drugs diffuse outside the tumor to then induce neurotoxicity. Encapsulation of drugs into liposome aims at increasing tumor cells specificity and reduces neurotoxicity. However, the most appropriate liposomal formulation to inject drugs into brain tumor by CED still remains to be determined. In this study, four liposomal carboplatin formulations were prepared and tested in vitro on F98 glioma cells and in Fischer rats carrying F98 tumor implanted in the brain. Impact of pegylation on liposomal surface and relevance of positive or negative charge were assessed. Results The cationic non-pegylated (L1) and pegylated (L2) liposomes greatly improved the toxicity of carboplatin in vitro compared to free carboplatin, whereas only a modest improvement and even a reduction of efficiency were measured with the anionic non-pegylated (L3) and the pegylated (L4) liposomes. Conversely, only the L4 liposome significantly increased the median survival time of Fisher rats implanted with the F98 tumor, compared to free carboplatin. Neurotoxicity assays performed with the empty L4′ liposome showed that the lipid components of L4 were not toxic. These results suggest that the positive charge on liposomes L1 and L2, which is known to promote binding to cell membrane, facilitates carboplatin accumulation in cancer cells explaining their higher efficacy in vitro. Conversely, negatively charged and pegylated liposome (L4) seems to diffuse over a larger distance in the tumor, and consequently significantly increased the median survival time of the animals. Conclusions Selection of the best liposomal formulation based on in vitro studies or animal model can result in contradictory conclusions. The negatively charged and pegylated liposome (L4) which was the less efficient formulation in vitro showed the best therapeutic effect in animal model of GBM. These results support that relevant animal model of GBM must be considered to determine the optimal physicochemical properties of liposomal formulations.

Abstract Cerebrovascular disease (CVD) has been associated with cognitive impairment. Yet, our understanding of vascular contribution to cognitive decline has been limited by heterogeneity of definitions and assessment, as well as its occurrence in cognitively healthy aging. Therefore, we aimed to establish the natural progression of CVD associated with aging. We conducted a retrospective observational study of 63 cognitively healthy participants aged 19–84 years selected through the histological archives of the CHU de Québec. Assessment of CVD lesions was performed independently by 3 observers blinded to clinical data using the Vascular Cognitive Impairment Neuropathology Guidelines (VCING). We found moderate to almost perfect interobserver agreement for most regional CVD scores. Atherosclerosis (ρ = 0.758) and arteriolosclerosis (ρ = 0.708) showed the greatest significant association with age, followed by perivascular hemosiderin deposits (ρ = 0.432) and cerebral amyloid angiopathy (CAA; ρ = 0.392). Amyloid and tau pathologies were both associated with higher CVD load, but only CAA remained significantly associated with amyloid plaques after controlling for age. Altogether, these findings support the presence of multiple CVD lesions in the brains of cognitively healthy adults, the burden of which increases with age and can be quantified in a reproducible manner using standardized histological scales such as the VCING.

Childhood brain tumors have suspected prenatal origins. To identify vulnerable developmental states, we generated a single-cell transcriptome atlas of >65,000 cells from embryonal pons and forebrain, two major tumor locations. We derived signatures for 191 distinct cell populations and defined the regional cellular diversity and differentiation dynamics. Projection of bulk tumor transcriptomes onto this dataset shows that WNT medulloblastomas match the rhombic lip-derived mossy fiber neuronal lineage and embryonal tumors with multilayered rosettes fully recapitulate a neuronal lineage, while group 2a/b atypical teratoid/rhabdoid tumors may originate outside the neuroectoderm. Importantly, single-cell tumor profiles reveal highly defined cell hierarchies that mirror transcriptional programs of the corresponding normal lineages. Our findings identify impaired differentiation of specific neural progenitors as a common mechanism underlying these pediatric cancers and provide a rational framework for future modeling and therapeutic interventions. A single-cell transcriptomic atlas from embryonal pons and forebrain provides insights into the developmental origins of pediatric brain tumors. The study identifies impaired differentiation of specific neural progenitors as a common mechanism underlying these cancers.

PurposeThe present report of two fatal awake malignant hyperthermia (MH) episodes in an MH susceptible (MHS) family is intended to raise awareness among medical personnel and MHS individuals to the possibility of life-threatening non-anesthesia-triggered MH episodes and to provide a strong incentive for development of effective preventive measures.Clinical featuresTwo young athletic males (28 and 16 yr old), members of the same extended family with a history of anesthesia-related MH episodes and deaths, succumbed ten years apart on two different continents, with symptoms unrelated to anesthesia but strikingly similar to typical anesthetic-induced MH. Both suffered an abrupt surge in body temperature, tachycardia, tachypnea, muscle rigidity, hyperkalemia, and respiratory and metabolic acidosis. Despite aggressive resuscitation attempts, both developed cardiac arrest and died shortly upon arrival to hospital emergency departments. Autopsy analyses were negative for drugs, alcohol, or bacterial infection. Individual and familial genetic analyses revealed a novel, potentially pathogenic RYR1 variant (p.Gly159Arg) that co-segregates with the MHS phenotype in the family. Both fatal awake MH episodes are hypothesized to have been triggered by physical exertion compounded with a febrile illness that in one case was due to influenza type A.ConclusionsLife-threatening awake MH episodes may develop in some MHS individuals in the absence of anesthetic triggers. Potential triggers can be physical exertion in combination with a febrile illness. Malignant hyperthermia susceptible patients are recommended to be vaccinated against flu and restrict physical activities when febrile, wear an MH alert bracelet, and inform medical personnel of their MH history. Oral dantrolene is suggested to be available to MHS patients for administration with the early signs of awake MH.