Search

Despite social class being a burgeoning area of research in the higher education literature, there is no single comprehensive measure of social class in university student populations. Most previous research has included objective single-item measures (e.g., parent education or occupation) to assess social class and then sorted students into distinct social class categories using these items. Such approaches do not adequately capture the complexity and nuance of class, and they ignore the subjective and social components involved. The present paper reports the development and validation of an 11-item Comprehensive Social Class Scale (CSCS) that uses a mix of objective and subjective items to assess multiple aspects of social class, including education level, occupational prestige, family affluence, social class identity and subjective social status. Across 12 samples (N = 4926), we provide evidence for a single factor structure of the CSCS and demonstrate aspects of its reliability and validity. We conclude by discussing some limitations and suggestions for use of the CSCS in higher education populations.

PI5P4Ks are a class of phosphoinositide kinases that phosphorylate PI-5-P to PI-4,5-P2. Distinct localization of phosphoinositides is fundamental for a multitude of cellular functions. Here, we identify a role for peroxisomal PI-4,5-P2 generated by the PI5P4Ks in maintaining energy balance. We demonstrate that PI-4,5-P2 regulates peroxisomal fatty acid oxidation by mediating trafficking of lipid droplets to peroxisomes, which is essential for sustaining mitochondrial metabolism. Using fluorescent-tagged lipids and metabolite tracing, we show that loss of the PI5P4Ks significantly impairs lipid uptake and β-oxidation in the mitochondria. Further, loss of PI5P4Ks results in dramatic alterations in mitochondrial structural and functional integrity, which under nutrient deprivation is further exacerbated, causing cell death. Notably, inhibition of the PI5P4Ks in cancer cells and mouse tumor models leads to decreased cell viability and tumor growth, respectively. Together, these studies reveal an unexplored role for PI5P4Ks in preserving metabolic homeostasis, which is necessary for tumorigenesis.

BackgroundInnovations in treatments, imaging, and molecular characterisation in advanced prostate cancer have improved outcomes, but there are still many aspects of management that lack high-level evidence to inform clinical practice. The Advanced Prostate Cancer Consensus Conference (APCCC) 2019 addressed some of these topics to supplement guidelines that are based on level 1 evidence.ObjectiveTo present the results from the APCCC 2019.Design, setting, and participantsSimilar to prior conferences, experts identified 10 important areas of controversy regarding the management of advanced prostate cancer: locally advanced disease, biochemical recurrence after local therapy, treating the primary tumour in the metastatic setting, metastatic hormone-sensitive/naïve prostate cancer, nonmetastatic castration-resistant prostate cancer, metastatic castration-resistant prostate cancer, bone health and bone metastases, molecular characterisation of tissue and blood, inter- and intrapatient heterogeneity, and adverse effects of hormonal therapy and their management. A panel of 72 international prostate cancer experts developed the programme and the consensus questions.Outcome measurements and statistical analysisThe panel voted publicly but anonymously on 123 predefined questions, which were developed by both voting and nonvoting panel members prior to the conference following a modified Delphi process.Results and limitationsPanellists voted based on their opinions rather than a standard literature review or formal meta-analysis. The answer options for the consensus questions had varying degrees of support by the panel, as reflected in this article and the detailed voting results reported in the Supplementary material.ConclusionsThese voting results from a panel of prostate cancer experts can help clinicians and patients navigate controversial areas of advanced prostate management for which high-level evidence is sparse. However, diagnostic and treatment decisions should always be individualised based on patient-specific factors, such as disease extent and location, prior lines of therapy, comorbidities, and treatment preferences, together with current and emerging clinical evidence and logistic and economic constraints. Clinical trial enrolment for men with advanced prostate cancer should be strongly encouraged. Importantly, APCCC 2019 once again identified important questions that merit assessment in specifically designed trials.Patient summaryThe Advanced Prostate Cancer Consensus Conference provides a forum to discuss and debate current diagnostic and treatment options for patients with advanced prostate cancer. The conference, which has been held three times since 2015, aims to share the knowledge of world experts in prostate cancer management with health care providers worldwide. At the end of the conference, an expert panel discusses and votes on predefined consensus questions that target the most clinically relevant areas of advanced prostate cancer treatment. The results of the voting provide a practical guide to help clinicians discuss therapeutic options with patients as part of shared and multidisciplinary decision making.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.

There has been much effort to prioritize genomic variants with respect to their impact on function. However, function is often not precisely defined: sometimes it is the disease association of a variant; on other occasions, it reflects a molecular effect on transcription or epigenetics. Here, we coupled multiple genomic predictors to build GRAM, a GeneRAlized Model, to predict a well-defined experimental target: the expression-modulating effect of a non-coding variant on its associated gene, in a transferable, cell-specific manner. Firstly, we performed feature engineering: using LASSO, a regularized linear model, we found transcription factor (TF) binding most predictive, especially for TFs that are hubs in the regulatory network; in contrast, evolutionary conservation, a popular feature in many other variant-impact predictors, has almost no contribution. Moreover, TF binding inferred from in vitro SELEX is as effective as that from in vivo ChIP-Seq. Second, we implemented GRAM integrating only SELEX features and expression profiles; thus, the program combines a universal regulatory score with an easily obtainable modifier reflecting the particular cell type. We benchmarked GRAM on large-scale MPRA datasets, achieving AUROC scores of 0.72 in GM12878 and 0.66 in a multi-cell line dataset. We then evaluated the performance of GRAM on targeted regions using luciferase assays in the MCF7 and K562 cell lines. We noted that changing the insertion position of the construct relative to the reporter gene gave very different results, highlighting the importance of carefully defining the exact prediction target of the model. Finally, we illustrated the utility of GRAM in fine-mapping causal variants and developed a practical software pipeline to carry this out. In particular, we demonstrated in specific examples how the pipeline could pinpoint variants that directly modulate gene expression within a larger linkage-disequilibrium block associated with a phenotype of interest (e.g., for an eQTL).

The benefits of positive intergroup contact for intergroup attitudes are well‐established. Yet individual and group self‐segregation practices demonstrate that opportunities for intergroup contact are not sufficient for contact uptake; and persistent institutionalized segregation reinforces and compounds this problem. Hence, we need to understand what drives people towards and away from intergroup contact and what consequences the capacity to deliberately engage or avoid contact has for individuals, groups, and communities. This paper formally introduces the concept of intergroup contact volition: our perceived personal control over intergroup contact engagement and avoidance. We demonstrate this concept's theoretical, political, and practical significance by highlighting its embeddedness in both old and recent literature. We document debates around volition in early intergroup contact research and note a prolonged neglect since. After discussing reasons for that neglect, we present a detailed analysis of the concept, outlining how the idea of volition itself is contested and political, as well as the ways it intersects with broader societal power and status dynamics. We then outline pathways for future research, including investigations of when taking volition away (making contact mandated) might be helpful, intersections between psychological and human geography perspectives on volition, and connections between volition and system justification. We argue that contact volition is intimately and ultimately linked to issues of social change: support of, versus resistance to, policies promoting intergroup integration. As a result, an enhanced understanding of volition is critical to developing intergroup contact research and practice into outcomes that maximize social justice. [ABSTRACT FROM AUTHOR]

Purpose The prevalence and features of treatment-emergent small-cell neuroendocrine prostate cancer (t-SCNC) are not well characterized in the era of modern androgen receptor (AR)-targeting therapy. We sought to characterize the clinical and genomic features of t-SCNC in a multi-institutional prospective study. Methods Patients with progressive, metastatic castration-resistant prostate cancer (mCRPC) underwent metastatic tumor biopsy and were followed for survival. Metastatic biopsy specimens underwent independent, blinded pathology review along with RNA/DNA sequencing. Results A total of 202 consecutive patients were enrolled. One hundred forty-eight (73%) had prior disease progression on abiraterone and/or enzalutamide. The biopsy evaluable rate was 79%. The overall incidence of t-SCNC detection was 17%. AR amplification and protein expression were present in 67% and 75%, respectively, of t-SCNC biopsy specimens. t-SCNC was detected at similar proportions in bone, node, and visceral organ biopsy specimens. Genomic alterations in the DNA repair pathway were nearly mutually exclusive with t-SCNC differentiation ( P = .035). Detection of t-SCNC was associated with shortened overall survival among patients with prior AR-targeting therapy for mCRPC (hazard ratio, 2.02; 95% CI, 1.07 to 3.82). Unsupervised hierarchical clustering of the transcriptome identified a small-cell-like cluster that further enriched for adverse survival outcomes (hazard ratio, 3.00; 95% CI, 1.25 to 7.19). A t-SCNC transcriptional signature was developed and validated in multiple external data sets with > 90% accuracy. Multiple transcriptional regulators of t-SCNC were identified, including the pancreatic neuroendocrine marker PDX1. Conclusion t-SCNC is present in nearly one fifth of patients with mCRPC and is associated with shortened survival. The near-mutual exclusivity with DNA repair alterations suggests t-SCNC may be a distinct subset of mCRPC. Transcriptional profiling facilitates the identification of t-SCNC and novel therapeutic targets.

BackgroundIn advanced prostate cancer (APC), successful drug development as well as advances in imaging and molecular characterisation have resulted in multiple areas where there is lack of evidence or low level of evidence. The Advanced Prostate Cancer Consensus Conference (APCCC) 2017 addressed some of these topics.ObjectiveTo present the report of APCCC 2017.Design, setting, and participantsTen important areas of controversy in APC management were identified: high-risk localised and locally advanced prostate cancer; "oligometastatic" prostate cancer; castration-naïve and castration-resistant prostate cancer; the role of imaging in APC; osteoclast-targeted therapy; molecular characterisation of blood and tissue; genetic counselling/testing; side effects of systemic treatment(s); global access to prostate cancer drugs. A panel of 60 international prostate cancer experts developed the program and the consensus questions.Outcome measurements and statistical analysisThe panel voted publicly but anonymously on 150 predefined questions, which have been developed following a modified Delphi process.Results and limitationsVoting is based on panellist opinion, and thus is not based on a standard literature review or meta-analysis. The outcomes of the voting had varying degrees of support, as reflected in the wording of this article, as well as in the detailed voting results recorded in Supplementary data.ConclusionsThe presented expert voting results can be used for support in areas of management of men with APC where there is no high-level evidence, but individualised treatment decisions should as always be based on all of the data available, including disease extent and location, prior therapies regardless of type, host factors including comorbidities, as well as patient preferences, current and emerging evidence, and logistical and economic constraints. Inclusion of men with APC in clinical trials should be strongly encouraged. Importantly, APCCC 2017 again identified important areas in need of trials specifically designed to address them.Patient summaryThe second Advanced Prostate Cancer Consensus Conference APCCC 2017 did provide a forum for discussion and debates on current treatment options for men with advanced prostate cancer. The aim of the conference is to bring the expertise of world experts to care givers around the world who see less patients with prostate cancer. The conference concluded with a discussion and voting of the expert panel on predefined consensus questions, targeting areas of primary clinical relevance. The results of these expert opinion votes are embedded in the clinical context of current treatment of men with advanced prostate cancer and provide a practical guide to clinicians to assist in the discussions with men with prostate cancer as part of a shared and multidisciplinary decision-making process.

We report a novel computational method, RegNetDriver, to identify tumorigenic drivers using the combined effects of coding and non-coding single nucleotide variants, structural variants, and DNA methylation changes in the DNase I hypersensitivity based regulatory network. Integration of multi-omics data from 521 prostate tumor samples indicated a stronger regulatory impact of structural variants, as they affect more transcription factor hubs in the tissue-specific network. Moreover, crosstalk between transcription factor hub expression modulated by structural variants and methylation levels likely leads to the differential expression of target genes. We report known prostate tumor regulatory drivers and nominate novel transcription factors (ERF, CREB3L1, and POU2F2), which are supported by functional validation.