A SAS-6-like protein suggests that the Toxoplasma conoid complex evolved from flagellar components

SAS-6 is required for centriole biogenesis in diverse eukaryotes. Here, we describe a novel family of SAS-6-like (SAS6L) proteins that share an N-terminal domain with SAS-6 but lack coiled-coil tails. SAS6L proteins are found in a subset of eukaryotes that contain SAS-6, including diverse protozoa and green algae. In the apicomplexan parasite Toxoplasma gondii, SAS-6 localizes to the centriole but SAS6L is found above the conoid, an enigmatic tubulin-containing structure found at the apex of a subset of alveolate organisms. Loss of SAS6L causes reduced fitness in Toxoplasma. The Trypanosoma brucei homolog of SAS6L localizes to the basal-plate region, the site in the axoneme where the central-pair microtubules are nucleated. When endogenous SAS6L is overexpressed in Toxoplasma tachyzoites or Trypanosoma trypomastigotes, it forms prominent filaments that extend through the cell cytoplasm, indicating that it retains a capacity to form higher-order structures despite lacking a coiled-coil domain. We conclude that although SAS6L proteins share a conserved domain with SAS-6, they are a functionally distinct family that predates the last common ancestor of eukaryotes. Moreover, the distinct localization of the SAS6L protein in Trypanosoma and Toxoplasma adds weight to the hypothesis that the conoid complex evolved from flagellar components

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

A survey and panel discussion of the effects of the COVID-19 pandemic on paediatric urological productivity, guideline adherence and provider stress

Introduction The COVID-19 pandemic has led to an unprecedented need to re-organise and re-align priorities for all surgical specialties. Despite the current declining numbers globally, the direct effects of the pandemic on institutional practices and on personal stress and coping mechanisms remains unknown. The aims of this study were to assess the effect of the pandemic on daily scheduling and work balances, its effects on stress, and to determine compliance with guidelines and to assess whether quarantining has led to other areas of increased productivity. Methods A trans-Atlantic convenience sample of paediatric urologists was created in which panellists (Zoom) discussed the direct effects of the COVID-19 pandemic on individual units, as well as creating a questionnaire using a mini-Delphi method to provide current semi-quantitative data regarding practice, and adherence levels to recently published risk stratification guidelines. They also filled out a Perceived Stress Scale (PSS) questionnaire to assess contemporary pandemic stress levels. Results There was an 86% response rate from paediatric urologists. The majority of respondents reported near complete disruption to planned operations (70%), and trainee education (70%). They were also worried about the effects of altered home-lives on productivity (<= 90%), as well as a lack of personal protective equipment (57%). The baseline stress rate was measured at a very high level (PSS) during the pandemic. Adherence to recent operative guidelines for urgent cases was 100%. Conclusion This study represents a panel discussion of a number of practical implications for paediatric urologists, and is one of the few papers to assess more pragmatic effects and combines opinions from both sides of the Atlantic. The impact of the pandemic has been very significant for paediatric urologists and includes a decrease in the number of patients seen and operated on, decreased salary, increased self-reported stress levels, substantially increased telemedicine usage, increased free time for various activities, and good compliance with guidelines and hospital management decisions

Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (, , ) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation