The Heavy Burden of the State: Revisiting the History of Labor Law in the Interwar Period

This Article reflects on possible conclusions to be drawn from this symposium. The article concludes that individually, these authors have demonstrated the returns to be gained by pushing labor law history into new empirical and conceptual areas. Collectively, however, their achievement is somewhat different, for collectively they recommend that we revisit what is ostensibly familiar to us

The Heavy Burden of the State: Revisiting the History of Labor Law in the Interwar Period

This Article reflects on possible conclusions to be drawn from this symposium. The article concludes that individually, these authors have demonstrated the returns to be gained by pushing labor law history into new empirical and conceptual areas. Collectively, however, their achievement is somewhat different, for collectively they recommend that we revisit what is ostensibly familiar to us

Messina: A Novel Analysis Tool to Identify Biologically Relevant Molecules in Disease

BACKGROUND: Morphologically similar cancers display heterogeneous patterns of molecular aberrations and follow substantially different clinical courses. This diversity has become the basis for the definition of molecular phenotypes, with significant implications for therapy. Microarray or proteomic expression profiling is conventionally employed to identify disease-associated genes, however, traditional approaches for the analysis of profiling experiments may miss molecular aberrations which define biologically relevant subtypes. METHODOLOGY/PRINCIPAL FINDINGS: Here we present Messina, a method that can identify those genes that only sometimes show aberrant expression in cancer. We demonstrate with simulated data that Messina is highly sensitive and specific when used to identify genes which are aberrantly expressed in only a proportion of cancers, and compare Messina to contemporary analysis techniques. We illustrate Messina by using it to detect the aberrant expression of a gene that may play an important role in pancreatic cancer. CONCLUSIONS/SIGNIFICANCE: Messina allows the detection of genes with profiles typical of markers of molecular subtype, and complements existing methods to assist the identification of such markers. Messina is applicable to any global expression profiling data, and to allow its easy application has been packaged into a freely-available stand-alone software package

The MD Anderson prostate cancer patient-derived xenograft series (MDA PCa PDX) captures the molecular landscape of prostate cancer and facilitates marker-driven therapy development

BACKGROUND: Advances in prostate cancer (PCa) lag behind other tumor types partly due to the paucity of models reflecting key milestones in PCa progression. OBJECTIVE: To develop clinically relevant PCa models. DESIGN: Since 1996 we have generated clinically annotated patient-derived xenografts (PDXs) (the MDA PCa PDX series) linked to specific phenotypes reflecting all aspects of clinical PCa. RESULTS: We studied two cell line-derived xenografts and the first 80 PDXs derived from 47 human PCa donors. Of these, 47 PDXs derived from 22 donors are working models and can be expanded either as cell lines (MDA PCa 2a and 2b) or PDXs. The histopathologic, genomic, and molecular characteristics (AR, ERG, and PTEN loss) maintain fidelity with the human tumor and correlate with published findings. PDX growth response to mouse castration and targeted therapy illustrate their clinical utility. Comparative genomic hybridization and sequencing show significant differences in oncogenic pathways in pairs of PDXs derived from different areas of the same tumor. We also identified a recurrent focal deletion in an area that includes the SPOPL gene in PDXs derived from 7 human donors out of 28 studied (25%). SPOPL is a SPOP paralog, and SPOP mutations define a molecular subclass of PCa. SPOPL deletions are found in 7% of TCGA PCas, which suggests that our cohort is a reliable platform for targeted drug development. CONCLUSIONS: The MDA PCa PDX series is a dynamic resource that captures the molecular landscape of PCas progressing under novel treatments and enables optimization of PCa-specific, marker-driven therapy

Testing mutual exclusivity of ETS rearranged prostate cancer

Prostate cancer is a clinically heterogeneous and multifocal disease. More than 80% of patients with prostate cancer harbor multiple geographically discrete cancer foci at the time of diagnosis. Emerging data suggest that these foci are molecularly distinct consistent with the hypothesis that they arise as independent clones. One of the strongest arguments is the heterogeneity observed in the status of E26 transformation specific (ETS) rearrangements between discrete tumor foci. The clonal evolution of individual prostate cancer foci based on recent studies demonstrates intertumoral heterogeneity with intratumoral homogeneity. The issue of multifocality and interfocal heterogeneity is important and has not been fully elucidated due to lack of the systematic evaluation of ETS rearrangements in multiple tumor sites. The current study investigates the frequency of multiple gene rearrangements within the same focus and between different cancer foci. Fluorescence in situ hybridization (FISH) assays were designed to detect the four most common recurrent ETS gene rearrangements. In a cohort of 88 men with localized prostate cancer, we found ERG, ETV1, and ETV5 rearrangements in 51% (44/86), 6% (5/85), and 1% (1/86), respectively. None of the cases demonstrated ETV4 rearrangements. Mutual exclusiveness of ETS rearrangements was observed in the majority of cases; however, in six cases, we discovered multiple ETS or 5′ fusion partner rearrangements within the same tumor focus. In conclusion, we provide further evidence for prostate cancer tumor heterogeneity with the identification of multiple concurrent gene rearrangements

Exon expression arrays as a tool to identify new cancer genes

Background: Identification of genes that are causally implicated in oncogenesis is a major goal in cancer research. An estimated 10-20% of cancer-related gene mutations result in skipping of one or more exons in the encoded transcripts. Here we report on a strategy to screen in a global fashion for such exon-skipping events using PAttern based Correlation (PAC). The PAC algorithm has been used previously to identify differentially expressed splice variants between two predefined subgroups. As genetic changes in cancer are sample specific, we tested the ability of PAC to identify aberrantly expressed exons in single samples. Principal Findings: As a proof-of-principle, we tested the PAC strategy on human cancer samples of which the complete coding sequence of eight cancer genes had been screened for mutations. PAC detected all seven exon-skipping mutants among 12 cancer cell lines. PAC also identified exon-skipping mutants in clinical cancer specimens although detection was compromised due to heterogeneous (wild-type) transcript expression. PAC reduced the number candidate genes/exons for subsequent mutational analysis by two to three orders of magnitude and had a substantial true positive rate. Importantly, of 112 randomly selected outlier exons, sequence analysis identified two novel exon skipping events, two novel base changes and 21 previously reported base changes (SNPs). Conclusions: The ability of PAC to enrich for mutated transcripts and to identify known and novel genetic changes confirms its suitability as a strategy to identify candidate cancer genes

DNA-PKcs-Mediated Transcriptional Regulation Drives Prostate Cancer Progression and Metastasis.

Emerging evidence demonstrates that the DNA repair kinase DNA-PKcs exerts divergent roles in transcriptional regulation of unsolved consequence. Here, in vitro and in vivo interrogation demonstrate that DNA-PKcs functions as a selective modulator of transcriptional networks that induce cell migration, invasion, and metastasis. Accordingly, suppression of DNA-PKcs inhibits tumor metastases. Clinical assessment revealed that DNA-PKcs is significantly elevated in advanced disease and independently predicts for metastases, recurrence, and reduced overall survival. Further investigation demonstrated that DNA-PKcs in advanced tumors is highly activated, independent of DNA damage indicators. Combined, these findings reveal unexpected DNA-PKcs functions, identify DNA-PKcs as a potent driver of tumor progression and metastases, and nominate DNA-PKcs as a therapeutic target for advanced malignancies

Identification of Functional Networks of Estrogen- and c-Myc-Responsive Genes and Their Relationship to Response to Tamoxifen Therapy in Breast Cancer

BACKGROUND: Estrogen is a pivotal regulator of cell proliferation in the normal breast and breast cancer. Endocrine therapies targeting the estrogen receptor are effective in breast cancer, but their success is limited by intrinsic and acquired resistance. METHODOLOGY/PRINCIPAL FINDINGS: With the goal of gaining mechanistic insights into estrogen action and endocrine resistance, we classified estrogen-regulated genes by function, and determined the relationship between functionally-related genesets and the response to tamoxifen in breast cancer patients. Estrogen-responsive genes were identified by transcript profiling of MCF-7 breast cancer cells. Pathway analysis based on functional annotation of these estrogen-regulated genes identified gene signatures with known or predicted roles in cell cycle control, cell growth (i.e. ribosome biogenesis and protein synthesis), cell death/survival signaling and transcriptional regulation. Since inducible expression of c-Myc in antiestrogen-arrested cells can recapitulate many of the effects of estrogen on molecular endpoints related to cell cycle progression, the estrogen-regulated genes that were also targets of c-Myc were identified using cells inducibly expressing c-Myc. Selected genes classified as estrogen and c-Myc targets displayed similar levels of regulation by estrogen and c-Myc and were not estrogen-regulated in the presence of siMyc. Genes regulated by c-Myc accounted for 50% of all acutely estrogen-regulated genes but comprised 85% (110/129 genes) in the cell growth signature. siRNA-mediated inhibition of c-Myc induction impaired estrogen regulation of ribosome biogenesis and protein synthesis, consistent with the prediction that estrogen regulates cell growth principally via c-Myc. The 'cell cycle', 'cell growth' and 'cell death' gene signatures each identified patients with an attenuated response in a cohort of 246 tamoxifen-treated patients. In multivariate analysis the cell death signature was predictive independent of the cell cycle and cell growth signatures. CONCLUSIONS/SIGNIFICANCE: These functionally-based gene signatures can stratify patients treated with tamoxifen into groups with differing outcome, and potentially identify distinct mechanisms of tamoxifen resistance

Role of genetic testing for inherited prostate cancer risk: Philadelphia prostate cancer consensus conference 2017

Purpose: Guidelines are limited for genetic testing for prostate cancer (PCA). The goal of this conference was to develop an expert consensus-dri