The cDNA-mediated Annealing, extension, Selection and Ligation (DASL) assay has become a suitable gene expression profiling system for degraded RNA from paraffin-embedded tissue. We examined assay characteristics and the performance of the DASL 502-gene Cancer Panel v1 (1.5K) and 24,526-gene panel (24K) platforms at differentiating nine human epidermal growth factor receptor 2- positive (HER2+) and 11 HER2-negative (HER2-) paraffin-embedded breast tumors.

MicroRNAs (miRNAs) are a class of approximately 22 nucleotide long, widely expressed RNA molecules that play important regulatory roles in eukaryotes. To investigate miRNA function, it is essential that methods to quantify their expression levels be available.

The association between duration of pancreatitis and pancreatic cancer has not been well characterized in large population-based studies. We conducted detailed analyses to determine the association between pancreatitis onset and pancreatic cancer risk.

Genome-wide association studies (GWASs) have identified thousands of single nucleotide polymorphisms (SNPs) robustly associated with hundreds of complex human diseases including cancers. However, the large number of GWAS-identified genetic loci only explains a small proportion of the disease heritability. This "missing heritability" problem has been partly attributed to the yet-to-be-identified gene-gene (G × G) and gene-environment (G × E) interactions. In spite of the important roles of G × G and G × E interactions in understanding disease mechanisms and filling in the missing heritability, straightforward GWAS scanning for such interactions has very limited statistical power, leading to few successes. Here we propose a two-step statistical approach to test G × G/G × E interactions: the first step is to perform principal component analysis (PCA) on the multiple SNPs within a gene region, and the second step is to perform Tukey's one degree-of-freedom (1-df) test on the leading PCs. We derive a score test that is computationally fast and numerically stable for the proposed Tukey's 1-df interaction test. Using extensive simulations we show that the proposed approach, which combines the two parsimonious models, namely, the PCA and Tukey's 1-df form of interaction, outperforms other state-of-the-art methods. We also demonstrate the utility and efficiency gains of the proposed method with applications to testing G × G interactions for Crohn's disease using the Wellcome Trust Case Control Consortium (WTCCC) GWAS data and testing G × E interaction using data from a case-control study of pancreatic cancer.

Mammalian target of rapamycin (mTOR) represents a key downstream intermediate for a myriad of oncogenic receptor tyrosine kinases. In the case of the insulin-like growth factor (IGF) pathway, the mTOR complex (mTORC1) mediates IGF-1 receptor (IGF-1R)-induced estrogen receptor alpha (ERα) phosphorylation/activation and leads to increased proliferation and growth in breast cancer cells. As a result, the prevalence of mTOR inhibitors combined with hormonal therapy has increased in recent years. Conversely, activated mTORC1 provides negative feedback regulation of IGF signaling via insulin receptor substrate (IRS)-1/2 serine phosphorylation and subsequent proteasomal degradation. Thus, the IGF pathway may provide escape (e.g. de novo or acquired resistance) from mTORC1 inhibitors. It is therefore plausible that combined inhibition of mTORC1 and IGF-1R for select subsets of ER-positive breast cancer patients presents as a viable therapeutic option.

Recent heritability analyses have indicated that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS), a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner's-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs) in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied our methods to GWAS summary-level data of 14 complex diseases. Across all diseases, a simple winner's curse correction uniformly led to enhancement of performance of the models, whereas incorporation of functional SNPs was beneficial only for selected diseases. Compared to the standard PRS algorithm, the proposed methods in combination led to notable gain in efficiency (25-50% increase in the prediction R2) for 5 of 14 diseases. As an example, for GWAS of type 2 diabetes, winner's curse correction improved prediction R2 from 2.29% based on the standard PRS to 3.10% (P = 0.0017) and incorporating functional annotation data further improved R2 to 3.53% (P = 2×10-5). Our simulation studies illustrate why differential treatment of certain categories of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction because of non-uniform linkage disequilibrium structure.

Urinary exosome-like vesicles (ELVs) are a heterogenous mixture (diameter 40-200 nm) containing vesicles shed from all segments of the nephron including glomerular podocytes. Contamination with Tamm-Horsfall protein (THP) oligomers has hampered their isolation and proteomic analysis. Here we improved ELV isolation protocols employing density centrifugation to remove THP and albumin, and isolated a glomerular membranous vesicle (GMV)-enriched subfraction from 7 individuals identifying 1830 proteins and in 3 patients with glomerular disease identifying 5657 unique proteins. The GMV fraction was composed of podocin/podocalyxin-positive irregularly shaped membranous vesicles and podocin/podocalyxin-negative classical exosomes. Ingenuity pathway analysis identified integrin, actin cytoskeleton, and Rho GDI signaling in the top three canonical represented signaling pathways and 19 other proteins associated with inherited glomerular diseases. The GMVs are of podocyte origin and the density gradient technique allowed isolation in a reproducible manner. We show many nephrotic syndrome proteins, proteases, and complement proteins involved in glomerular disease are in GMVs and some were only shed in the disease state (nephrin, TRPC6, INF2 and phospholipase A2 receptor). We calculated sample sizes required to identify new glomerular disease biomarkers, expand the ELV proteome, and provide a reference proteome in a database that may prove useful in the search for biomarkers of glomerular disease.

Ovarian cancer represents the most lethal tumor type among malignancies of the female reproductive system. Overall survival rates remain low. In this study, we identify the serine protease inhibitor Kazal type 1 (SPINK1) as a potential therapeutic target for a subset of ovarian cancers. We show that SPINK1 drives ovarian cancer cell proliferation through activation of epidermal growth factor receptor (EGFR) signaling, and that SPINK1 promotes resistance to anoikis through a distinct mechanism involving protease inhibition. In analyses of ovarian tumor specimens from a Mayo Clinic cohort of 490 patients, we further find that SPINK1 immunostaining represents an independent prognostic factor for poor survival, with the strongest association in patients with nonserous histological tumor subtypes (endometrioid, clear cell, and mucinous). This study provides novel insight into the fundamental processes underlying ovarian cancer progression, and also suggests new avenues for development of molecularly targeted therapies.

TAIR (The Arabidopsis Information Resource) is the model organism database (MOD) for Arabidopsis thaliana, a model plant with a literature corpus of about 39 000 articles in PubMed, with over 4300 new articles added in 2011. We have developed a literature curation workflow incorporating both automated and manual elements to cope with this flood of new research articles. The current workflow can be divided into two phases: article selection and curation. Structured controlled vocabularies, such as the Gene Ontology and Plant Ontology are used to capture free text information in the literature as succinct ontology-based annotations suitable for the application of computational analysis methods. We also describe our curation platform and the use of text mining tools in our workflow. Database URL: www.arabidopsis.org

Growing evidence suggests a major role for Src-homology-2-domain-containing phosphatase 2 (SHP2/PTPN11) in MYCN-driven high-risk neuroblastoma, although biologic confirmation and a plausible mechanism for this contribution are lacking. Using a zebrafish model of MYCN-overexpressing neuroblastoma, we demonstrate that mutant ptpn11 expression in the adrenal gland analog of MYCN transgenic fish promotes the proliferation of hyperplastic neuroblasts, accelerates neuroblastomagenesis, and increases tumor penetrance. We identify a similar mechanism in tumors with wild-type ptpn11 and dysregulated Gab2, which encodes a Shp2 activator that is overexpressed in human neuroblastomas. In MYCN transgenic fish, Gab2 overexpression activated the Shp2-Ras-Erk pathway, enhanced neuroblastoma induction, and increased tumor penetrance. We conclude that MYCN cooperates with either GAB2-activated or mutant SHP2 in human neuroblastomagenesis. Our findings further suggest that combined inhibition of MYCN and the SHP2-RAS-ERK pathway could provide effective targeted therapy for high-risk neuroblastoma patients with MYCN amplification and aberrant SHP2 activation.

Therapy with demethylating agent 5-azacitidine and histone deacetylase inhibitor entinostat shows synergistic re-expression of tumor-suppressor genes and growth inhibition in colorectal (CRC) cell lines and in vivo studies.

Although 70-80% of newly diagnosed ovarian cancer patients respond to first-line therapy, almost all relapse and five-year survival remains below 50%. One strategy to increase five-year survival is prolonging time to relapse by improving first-line therapy response. However, no biomarker today can accurately predict individual response to therapy. In this study, we present analytical and prospective clinical validation of a new test that utilizes primary patient tissue in 3D cell culture to make patient-specific response predictions prior to initiation of treatment in the clinic. Test results were generated within seven days of tissue receipt from newly diagnosed ovarian cancer patients obtained at standard surgical debulking or laparoscopic biopsy. Patients were followed for clinical response to chemotherapy. In a study population of 44, the 32 test-predicted Responders had a clinical response rate of 100% across both adjuvant and neoadjuvant treated populations with an overall prediction accuracy of 89% (39 of 44, p < 0.0001). The test also functioned as a prognostic readout with test-predicted Responders having a significantly increased progression-free survival compared to test-predicted Non-Responders, p = 0.01. This correlative accuracy establishes the test's potential to benefit ovarian cancer patients through accurate prediction of patient-specific response before treatment.

Germline copy number variants (CNVs) increase risk for many diseases, yet detection of CNVs and quantifying their contribution to disease risk in large-scale studies is challenging due to biological and technical sources of heterogeneity that vary across the genome within and between samples.

Interest in preclinical drug development for ovarian cancer has stimulated development of patient-derived xenograft (PDX) or tumorgraft models. However, the unintended formation of human lymphoma in severe combined immunodeficiency (SCID) mice from Epstein-Barr virus (EBV)-infected human lymphocytes can be problematic. In this study, we have characterized ovarian cancer PDXs which developed human lymphomas and explore methods to suppress lymphoproliferative growth. Fresh human ovarian tumors from 568 patients were transplanted intraperitoneally in SCID mice. A subset of PDX models demonstrated atypical patterns of dissemination with mediastinal masses, hepatosplenomegaly, and CD45-positive lymphoblastic atypia without ovarian tumor engraftment. Expression of human CD20 but not CD3 supported a B-cell lineage, and EBV genomes were detected in all lymphoproliferative tumors. Immunophenotyping confirmed monoclonal gene rearrangements consistent with B-cell lymphoma, and global gene expression patterns correlated well with other human lymphomas. The ability of rituximab, an anti-CD20 antibody, to suppress human lymphoproliferation from a patient's ovarian tumor in SCID mice and prevent growth of an established lymphoma led to a practice change with a goal to reduce the incidence of lymphomas. A single dose of rituximab during the primary tumor heterotransplantation process reduced the incidence of CD45-positive cells in subsequent PDX lines from 86.3% (n = 117 without rituximab) to 5.6% (n = 160 with rituximab), and the lymphoma rate declined from 11.1% to 1.88%. Taken together, investigators utilizing PDX models for research should routinely monitor for lymphoproliferative tumors and consider implementing methods to suppress their growth.

Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance.

SARS-CoV-2 infection activates coagulation and stimulates innate immune system. Little is known about coagulopathy and response of inflammation and infection in ICU patients with COVID-19. Derangement of coagulation and markers of infection and inflammation induced by SARS-CoV-2 infection, as well as their correlations were elucidated.

The known epithelial ovarian cancer (EOC) susceptibility genes account for less than 50% of the heritable risk of ovarian cancer suggesting that other susceptibility genes exist. The aim of this study was to evaluate the contribution to ovarian cancer susceptibility of rare deleterious germline variants in a set of candidate genes.

Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10-8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82-0.93; former smokers 1.00, 95% CI, 0.91-1.07; current smokers 1.25, 95% CI 1.12-1.40, P interaction = 3.08 × 10-9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r 2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. SIGNIFICANCE: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.

The COVID-19 pandemic has revealed the pronounced vulnerability of the elderly and chronically ill to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced morbidity and mortality. Cellular senescence contributes to inflammation, multiple chronic diseases, and age-related dysfunction, but effects on responses to viral infection are unclear. Here, we demonstrate that senescent cells (SnCs) become hyper-inflammatory in response to pathogen-associated molecular patterns (PAMPs), including SARS-CoV-2 spike protein-1, increasing expression of viral entry proteins and reducing antiviral gene expression in non-SnCs through a paracrine mechanism. Old mice acutely infected with pathogens that included a SARS-CoV-2-related mouse β-coronavirus experienced increased senescence and inflammation, with nearly 100% mortality. Targeting SnCs by using senolytic drugs before or after pathogen exposure significantly reduced mortality, cellular senescence, and inflammatory markers and increased antiviral antibodies. Thus, reducing the SnC burden in diseased or aged individuals should enhance resilience and reduce mortality after viral infection, including that of SARS-CoV-2.

Of clinically node-negative (cN0) cutaneous melanoma patients with sentinel lymph node (SLN) metastasis, between 10% and 30% harbor additional metastases in non-sentinel lymph nodes (NSLNs). Approximately 80% of SLN-positive patients have a single positive SLN.