Four Strategies for Driving a University Pre-College Computing Outreach Program

A public university’s computing outreach program focused on four key strategies for increasing the depth and breadth of science, technology, engineering, and mathematics (STEM) education. This paper describes the development and implementation of a project management hands-on learning laboratory activity within the context of the university’s outreach strategies. The first two strategies, establishing relationships with the primary and secondary (K–12) level partner schools and implementing whole-grade participation, have led to repeat visits by students over several years. The third strategy, hands-on learning laboratory activities, has successfully engaged K–12 students, as indicated by the assessment results that provide evidence of successful student learning. The fourth strategy, producer–consumer collaborations, has facilitated the efficient matching of faculty expertise with K–12 teacher needs. The results include the evidence that outreach strategies can have a positive influence on student engagement in STEM education at multiple points in the K–12 education experience

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

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

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

Evaluation of Population-Level Changes Associated With the 2021 US Preventive Services Task Force Lung Cancer Screening Recommendations in Community-Based Health Care Systems

Importance: The US Preventive Services Task Force (USPSTF) released updated lung cancer screening recommendations in 2021, lowering the screening age from 55 to 50 years and smoking history from 30 to 20 pack-years. These changes are expected to expand screening access to women and racial and ethnic minority groups. Objective: To estimate the population-level changes associated with the 2021 USPSTF expansion of lung cancer screening eligibility by sex, race and ethnicity, sociodemographic factors, and comorbidities in 5 community-based health care systems. Design, Setting, and Participants: This cohort study analyzed data of patients who received care from any of 5 community-based health care systems (which are members of the Population-based Research to Optimize the Screening Process Lung Consortium, a collaboration that conducts research to better understand how to improve the cancer screening processes in community health care settings) from January 1, 2010, through September 30, 2019. Individuals who had complete smoking history and were engaged with the health care system for 12 or more continuous months were included. Those who had never smoked or who had unknown smoking history were excluded. Exposures: Electronic health record-derived age, sex, race and ethnicity, socioeconomic status (SES), comorbidities, and smoking history. Main Outcomes and Measures: Differences in the proportion of the newly eligible population by age, sex, race and ethnicity, Charlson Comorbidity Index, chronic obstructive pulmonary disease diagnosis, and SES as well as lung cancer diagnoses under the 2013 recommendations vs the expected cases under the 2021 recommendations were evaluated using χ2 tests. Results: As of September 2019, there were 341 163 individuals aged 50 to 80 years who currently or previously smoked. Among these, 34 528 had electronic health record data that captured pack-year and quit-date information and were eligible for lung cancer screening according to the 2013 USPSTF recommendations. The 2021 USPSTF recommendations expanded screening eligibility to 18 533 individuals, representing a 53.7% increase. Compared with the 2013 cohort, the newly eligible 2021 population included 5833 individuals (31.5%) aged 50 to 54 years, a larger proportion of women (52.0% [n = 9631]), and more racial or ethnic minority groups. The relative increases in the proportion of newly eligible individuals were 60.6% for Asian, Native Hawaiian, or Pacific Islander; 67.4% for Hispanic; 69.7% for non-Hispanic Black; and 49.0% for non-Hispanic White groups. The relative increase for women was 13.8% higher than for men (61.2% vs 47.4%), and those with a lower comorbidity burden and lower SES had higher relative increases (eg, 68.7% for a Charlson Comorbidity Index score of 0; 61.1% for lowest SES). The 2021 recommendations were associated with an estimated 30% increase in incident lung cancer diagnoses compared with the 2013 recommendations. Conclusions and Relevance: This cohort study suggests that, in diverse health care systems, adopting the 2021 USPSTF recommendations will increase the number of women, racial and ethnic minority groups, and individuals with lower SES who are eligible for lung cancer screening, thus helping to minimize the barriers to screening access for individuals with high risk for lung cancer

Recombinational exchange of M-fibril and T-pilus genes generates extensive cell surface diversity in the global group A streptococcus population

Among genes present in all group A streptococci (GAS), those encoding M-fibril and T-pilus proteins display the highest levels of sequence diversity, giving rise to the two primary serological typing schemes historically used to define strain. A new genotyping scheme for the pilin adhesin and backbone genes is developed and, when combined with emm typing, provides an account of the global GAS strain population. Cluster analysis based on nucleotide sequence similarity assigns most T-serotypes to discrete pilin backbone sequence clusters, yet the established T-types correspond to only half the clusters. The major pilin adhesin and backbone sequence clusters yield 98 unique combinations, defined as “pilin types.” Numerous horizontal transfer events that involve pilin or emm genes generate extensive antigenic and functional diversity on the bacterial cell surface and lead to the emergence of new strains. Inferred pilin genotypes applied to a meta-analysis of global population-based collections of pharyngitis and impetigo isolates reveal highly significant associations between pilin genotypes and GAS infection at distinct ecological niches, consistent with a role for pilin gene products in adaptive evolution. Integration of emm and pilin typing into open-access online tools (pubmlst.org) ensures broad utility for end-users wanting to determine the architecture of M-fibril and T-pilus genes from genome assemblies. IMPORTANCE Precision in defining the variant forms of infectious agents is critical to understanding their population biology and the epidemiology of associated diseases. Group A Streptococcus (GAS) is a global pathogen that causes a wide range of diseases and displays a highly diverse cell surface due to the antigenic heterogeneity of M-fibril and T-pilus proteins which also act as virulence factors of varied functions. emm genotyping is well-established and highly utilized, but there is no counterpart for pilin genes. A global GAS collection provides the basis for a comprehensive pilin typing scheme, and online tools for determining emm and pilin genotypes are developed. Application of these tools reveals the expansion of structural-functional diversity among GAS via horizontal gene transfer, as evidenced by unique combinations of surface protein genes. Pilin and emm genotype correlations with superficial throat vs skin infection provide new insights on the molecular determinants underlying key ecological and epidemiological trends

Towards resolving the transcription factor network controlling myelin gene expression

In the central nervous system (CNS), myelin is produced from spirally-wrapped oligodendrocyte plasma membrane and, as exemplified by the debilitating effects of inherited or acquired myelin abnormalities in diseases such as multiple sclerosis, it plays a critical role in nervous system function. Myelin sheath production coincides with rapid up-regulation of numerous genes. The complexity of their subsequent expression patterns, along with recently recognized heterogeneity within the oligodendrocyte lineage, suggest that the regulatory networks controlling such genes drive multiple context-specific transcriptional programs. Conferring this nuanced level of control likely involves a large repertoire of interacting transcription factors (TFs). Here, we combined novel strategies of computational sequence analyses with in vivo functional analysis to establish a TF network model of coordinate myelin-associated gene transcription. Notably, the network model captures regulatory DNA elements and TFs known to regulate oligodendrocyte myelin gene transcription and/or oligodendrocyte development, thereby validating our approach. Further, it links to numerous TFs with previously unsuspected roles in CNS myelination and suggests collaborative relationships amongst both known and novel TFs, thus providing deeper insight into the myelin gene transcriptional network