Comparing major burnout measures: an analysis of predictive and incremental validity

Burnout is an increasingly prominent topic both in industrial and organizational psychology and the public discourse. While the concept of burnout is well known, studies on its temporal relationships are rare and debate remains as to how to best measure it. Frequently used to assess burnout, the Maslach Burnout Inventory (MBI) has received criticism for its dimensions, item wording, and cost relative to other measures. In response, several burnout measures have been created, notably the Shirom-Melamed Burnout Measure (SMBM), the Copenhagen Burnout Inventory (CBI), and more recently the Burnout Assessment Tool (BAT). The proposed research would be the first to examine the incremental and predictive validity of these four major burnout measures regarding person- and job-related predictors and outcomes. On the person-related side, anxiety, depression, stress, and subjective well-being are prominent correlates to the burnout construct. This research will also investigate the role of personal resources such as resilience, self-efficacy, and optimism. On the job-related side, job performance, satisfaction, organizational commitment, and job engagement will be examined. In the proposed study, 300 full-time workers will be recruited via Prolific to take the MBI, SMBM, CBI, and BAT at three time points, along with the person- and job-related variables above. Using a cross-lagged panel design, regressions will be calculated to analyze the temporal relationships between the personal and job-related predictors and outcomes with each burnout measure. Multiple regressions will be conducted to examine the predictive and incremental validities of the four measures as regards the predictors and outcomes. Pilot data suggests that among the four measures, the BAT aligns best with the burnout construct. Therefore, it is expected to have the strongest relationships with the predictors and outcomes. This research will allow for a comparison among burnout measures regarding meaningful person- and job-related variables. A major contribution of the proposed research comes from its longitudinal design, which will allow for causal inferences. Additionally, this study can offer insight into the directionality of the burnout-strain relationship. For researchers, adding temporal data to existing knowledge of burnout’s nomological network will provide guidance regarding whether conservation of resources, effort recovery, or other theoretical models best fit the way burnout unfolds. For practitioners, burnout prevention and intervention efforts can be developed, implemented, and evaluated based on a more comprehensive understanding of burnout and can therefore be more targeted and effective

Genome-wide analysis of the RpoN regulon in Geobacter sulfurreducens

Background The role of the RNA polymerase sigma factor RpoN in regulation of gene expression in Geobacter sulfurreducens was investigated to better understand transcriptional regulatory networks as part of an effort to develop regulatory modules for genome-scale in silico models, which can predict the physiological responses of Geobacter species during groundwater bioremediation or electricity production. Results An rpoN deletion mutant could not be obtained under all conditions tested. In order to investigate the regulon of the G. sulfurreducens RpoN, an RpoN over-expression strain was made in which an extra copy of the rpoN gene was under the control of a taclac promoter. Combining both the microarray transcriptome analysis and the computational prediction revealed that the G. sulfurreducens RpoN controls genes involved in a wide range of cellular functions. Most importantly, RpoN controls the expression of the dcuB gene encoding the fumarate/succinate exchanger, which is essential for cell growth with fumarate as the terminal electron acceptor in G. sulfurreducens. RpoN also controls genes, which encode enzymes for both pathways of ammonia assimilation that is predicted to be essential under all growth conditions in G. sulfurreducens. Other genes that were identified as part of the RpoN regulon using either the computational prediction or the microarray transcriptome analysis included genes involved in flagella biosynthesis, pili biosynthesis and genes involved in central metabolism enzymes and cytochromes involved in extracellular electron transfer to Fe(III), which are known to be important for growth in subsurface environment or electricity production in microbial fuel cells. The consensus sequence for the predicted RpoN-regulated promoter elements is TTGGCACGGTTTTTGCT. Conclusion The G. sulfurreducens RpoN is an essential sigma factor and a global regulator involved in a complex transcriptional network controlling a variety of cellular processes

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

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 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

RNA Binding Protein CUGBP2/CELF2 Mediates Curcumin-Induced Mitotic Catastrophe of Pancreatic Cancer Cells

Curcumin inhibits the growth of pancreatic cancer tumor xenografts in nude mice; however, the mechanism of action is not well understood. It is becoming increasingly clear that RNA binding proteins regulate posttranscriptional gene expression and play a critical role in RNA stability and translation. Here, we have determined that curcumin modulates the expression of RNA binding protein CUGBP2 to inhibit pancreatic cancer growth.In this study, we show that curcumin treated tumor xenografts have a significant reduction in tumor volume and angiogenesis. Curcumin inhibited the proliferation, while inducing G2-M arrest and apoptosis resulting in mitotic catastrophe of various pancreatic cancer cells. This was further confirmed by increased phosphorylation of checkpoint kinase 2 (Chk2) protein coupled with higher levels of nuclear cyclin B1 and Cdc-2. Curcumin increased the expression of cyclooxygenase-2 (COX-2) and vascular endothelial growth factor (VEGF) mRNA, but protein levels were lower. Furthermore, curcumin increased the expression of RNA binding proteins CUGBP2/CELF2 and TIA-1. CUGBP2 binding to COX-2 and VEGF mRNA was also enhanced, thereby increasing mRNA stability, the half-life changing from 30 min to 8 h. On the other hand, silencer-mediated knockdown of CUGBP2 partially restored the expression of COX-2 and VEGF even with curcumin treatment. COX-2 and VEGF mRNA levels were reduced to control levels, while proteins levels were higher.Curcumin inhibits pancreatic tumor growth through mitotic catastrophe by increasing the expression of RNA binding protein CUGBP2, thereby inhibiting the translation of COX-2 and VEGF mRNA. These data suggest that translation inhibition is a novel mechanism of action for curcumin during the therapeutic intervention of pancreatic cancers

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy