Objective-A literature review was conducted to ascertain whether or not EEG spectral abnormalities are consistent enough to warrant additional effort towards developing them into a clinical diagnostic test for schizophrenia.Methods-Fifty three papers met criteria for inclusion into the review and 15 were included in a meta-analysis of the degree of significance of EEG deviations as compared to healthy controls. Studies were classified based on a 4-step approach based on guidelines for evaluating the clinical usefulness of a diagnostic test.Results-Our review and meta-analysis revealed that most of the abnormalities are replicated in the expected directions with the most consistent results related to the increased preponderance of slow rhythms in schizophrenia patients. This effect remained consistent in un-medicated patients. Only a small number of studies provided data on the sensitivity and specificity of the findings in differentiating among the psychiatric disorders that frequently appear on the same differential diagnostic list as schizophrenia (step 3 studies). No multicenter studies using standardized assessment criteria were found (step 4 studies).
Conclusions-AdditionalStep 3 and Step 4 studies are needed to draw conclusions on the usefulness of EEG spectral abnormalities as a diagnostic test for schizophrenia
The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we perform an integrative multi-omics analysis of patients diagnosed with NMIBC (n = 834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations are significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration is associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirms the higher infiltration of class 2b tumors and demonstrates an association between higher immune cell infiltration and lower recurrence rates. Finally, the independent prognostic value of the transcriptomic classes is documented in 1228 validation samples using a single sample classification tool. The classifier provides a framework for biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials.
Discrete bladder cancer molecular subtypes exhibit differential clinical aggressiveness and therapeutic response, which may have significant implications for identifying novel treatments for this common malignancy. However, research is hindered by the lack of suitable models to study each subtype. To address this limitation, we classified bladder cancer cell lines into molecular subtypes using publically available data in the Cancer Cell Line Encyclopedia (CCLE), guided by genomic characterization of bladder cancer by The Cancer Genome Atlas (TCGA). This identified a panel of bladder cancer cell lines which exhibit genetic alterations and gene expression patterns consistent with luminal and basal molecular subtypes of human disease. A subset of bladder cancer cell lines exhibit in vivo histomorphologic patterns consistent with luminal and basal subtypes, including papillary architecture and squamous differentiation. Using the molecular subtype assignments, and our own RNA-seq analysis, we found overexpression of GATA3 and FOXA1 cooperate with PPARɣ activation to drive transdifferentiation of a basal bladder cancer cells to a luminial phenotype. In summary, our analysis identified a set of human cell lines suitable for the study of molecular subtypes in bladder cancer, and furthermore indicates a cooperative regulatory network consisting of GATA3, FOXA1, and PPARɣ drive luminal cell fate.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.