The Role of Pharmacotherapy in Treatment of Meningioma: A Systematic Review

The safety and efficacy of various pharmacotherapeutic regimens on refractory meningiomas have been the focus of investigations. We present a comprehensive review of the previous efforts and the current state of ongoing clinical trials. A PRISMA-compliant review of the MEDLINE and ClinicalTrial.gov databases of the National Library of Medicine were performed. The primary outcomes of interest for included articles were radiographic response, overall survival, progression-free survival, six-month progression-free survival, and adverse events. Overall, 34 completed trials and 27 ongoing clinical trials were eligible. Six-month progression-free survival was reported in 6–100% of patients in the completed studies. Hematological disorders were the most common adverse events. Of the ongoing clinical trials identified, nine studies are phase I clinical trials, eleven are phase II trials, two are phase I and II trials, one is phase II and III, and two trials do not have a designated phase. Currently, there is no effective chemotherapy for refractory or recurrent meningiomas. Several promising targeted agents have been developed and are currently being investigated in the hope of identifying novel therapeutic strategies for the treatment of this pathology

Traumatic brain injury and subsequent brain tumor development: a systematic review of the literature.

The role of prior head trauma in stimulating brain tumor development has been previously described in the literature but continues to be debated. The goal of this study was to conduct a systematic review interrogating the contemporary literature to delineate any possible relationship between traumatic brain injury and brain tumor development. A systematic review exploring development of post-TBI brain tumor was conducted by searching electronic databases. Abstracts from articles were read and selected for full-text review according to criteria previously established in the scientific literature. Relevant full-text articles were divided into case reports and single-arm studies and epidemiological studies. Of 1070 resultant articles, 18 case reports and single-arm studies (level of evidence of IV and V) with 45 patients were included. The most common cause of TBI was traffic accidents. The average period between TBI and subsequent tumor diagnosis was 12.8 years. Meningiomas represented the largest share of tumors, followed by gliomas. Most post-TBI brain tumors developed in the frontal and temporal lobes. Fifteen epidemiological studies were also interrogated from a variety of countries (level of evidence of III). Case-control studies were more common than cohort studies. There were 9 of 15 studies proposed a possible relationship between history of head trauma and development of brain tumor. The relationship between head trauma and neoplastic growth continues to be heavily debated. There are certainly case reports and epidemiological studies in the literature that suggest a correlational relationship between the two. However, there is no concrete evidence of a causal relationship between TBI and brain tumors. More research is needed to definitively delineate the extent of any such relationship

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease