The Lantern Vol. 27, No. 2, Spring 1959

• The Case for a Stratified Society • Education Courses • Some Thoughts for God\u27s Thinking Creatures • Sawdust to the Oats? • To Change the Things I Can... • Vignette • I Meet Goliath • Reverie and Reminiscence • On Flight • In Defense of Jazz • A Description • Line of Retreat • Alan Lomax and the American Folk Song • Dawn Stillness • Seasons • Two Poems • Despair • Too Late • Education • For All Practical Purposes He Was Bald • Contrast • I Belong to the Sea • Waves • Love • The Glory and the Dreamhttps://digitalcommons.ursinus.edu/lantern/1077/thumbnail.jp

4th Biennial Employment Law Institute

Materials from the 4th Biennial Employment Law Institute held by UK/CLE in June 1994

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

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

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

Examining multi-session brief intervention for substance use in primary care: research methods of a randomized controlled trial

BACKGROUND: Brief interventions such as Screening, a single session of Brief Intervention, and Referral to Treatment (SBIRT) have shown mixed effectiveness in primary care. However, there are indications that multi-session brief interventions may demonstrate more consistently positive outcomes, and perhaps a more intensive approach would be of benefit in addressing substance use in primary care. This study compared the effectiveness of SBIRT with a single BI session (BI/RT) to a multi-session brief-treatment intervention (BI/RT+) in primary care. We also developed easy-to-use, evidence-based materials to assist clinicians in delivering these interventions. METHODS/DESIGN: This study was conducted in three Federally Qualified Healthcare Centers (FQHCs). A total of 10,935 patients were screened, and 600 individuals were recruited. The sample was primarily Black/African American (82 %) with a mean age of 40. Patients who attended a healthcare appointment were screened for substance use via the AUDIT and DAST. Patients were eligible for the study if they scored 8 or higher on the AUDIT, were using only marijuana and scored 2 or higher on the DAST, or were using other illicit drugs and scored 1 or higher on the DAST. Participants were randomly assigned to receive one-session BI/RT, or two to six sessions of brief intervention that incorporated elements of motivational enhancement therapy and cognitive-behavioral therapy (BI/RT+). Both interventions were delivered by behavioral health consultants at the FQHCs. Participants completed follow-up assessments every 3 months for 1 year. Primary outcome variables included substance use treatment sessions attended and days of substance use. Secondary outcomes included measures of health, employment, legal, and psychiatric functioning and HIV risk behaviors. Additionally, we will conduct an economic evaluation examining cost-effectiveness and will analyze outcomes from a process evaluation examining patient and provider experiences. DISCUSSION: The ability of brief interventions to impact substance use has great potential, but research findings have been mixed. By conducting a large-scale randomized controlled trial in real-world health centers, this study will answer important questions about the effectiveness of expanded BIs for patients who screen positive for risky substance use in primary care. Trial registration NCT01751672

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