The disability housing market: opportunity for community development finance as the Americans with Disabilities Act turns 20

Community development

Gene-expression data integration to squamous cell lung cancer subtypes reveals drug sensitivity

Background: Squamous cell lung cancer (SqCC) is the second most common type of lung cancer in the United States. Previous studies have used gene-expression data to classify SqCC samples into four subtypes, including the primitive, classical, secretory and basal subtypes. These subtypes have different survival outcomes, although it is unknown whether these molecular subtypes predict response to therapy. Methods: Here, we analysed RNAseq data of 178 SqCC tumour samples and characterised the features of the different SqCC subtypes to define signature genes and pathway alterations specific to each subtype. Further, we compared the gene-expression features of each molecular subtype to specific time points in models of airway development. We also classified SqCC-derived cell lines and their reported therapeutic vulnerabilities. Results: We found that the primitive subtype may come from a later stage of differentiation, whereas the basal subtype may be from an early time. Most SqCC cell lines responded to one of five anticancer drugs (Panobinostat, 17-AAG, Irinotecan, Topotecan and Paclitaxel), whereas the basal-type cell line EBC-1 was sensitive to three other drugs (PF2341066, AZD6244 and PD-0325901). Conclusion: Compared with the other three subtypes of cell lines, the secretory-type cell lines were significantly less sensitive to the five most effective drugs, possibly because of their low proliferation activity. We provide a bioinformatics framework to explore drug repurposing for cancer subtypes based on the available genomic profiles of tumour samples, normal cell types, cancer cell lines and data of drug sensitivity in cell lines

The fractional shortening-velocity ratio: Validation of a new echocardiographic doppler method for identifying patients with significant aortic stenosis

AbstractPrevious studies have shown that Doppler echographic methods based on the continuity equation can accurately determine aortic valve area in patients with clinically significant aortic stenosis; nonetheless, methods based on the continuity equation are time-consuming and may not be technically possible in all subsets of patients. Thee purpose of this study was to develop and prospectively evaluate a simpler new noninvasive method for determining aortic valve area. With this new method, aortic valve area is obtained by dividing the percent fractional anteroposterior shortening at the midventriclevel by 4V2, where V is the peak instantaneous Doppler-derived How velocity across the aortic valve.In the fast part of the study, the fractional shortening-velocity ratio was used to examine a group of 25 patients evaluated retrospectively. There was a highly significant linear relation between the fractional shortening-velocity ratio (FSVR) and the aortic valve area (AVA) determined by the Gorlin formula at cardiac catheterization: FSVR = 1.1(AVA) − 0.1 (r = 0.88; significance of slope p < 0.001). Furthermore, a fractional shortening-velocity ratio <1.1 reliably identified all patients with clinically significant aortic stenosis (aortic valve area <1 cm2), whereas a fractional shortening-velocity ratio <0.8 reliably identified all patients with critical aortic stenosis (aortic valve area <0.7 cm2).This new method was then validated by prospectively applying the fractignal shortening-velocity ratio to a group of 44 patients from two separate institutions. This prospective study showed that a fractional shortening-velocity ratio <l.l had a seRR-Jitivity of 90% to 96% and a positive predictive accuracy of 90% to 92% for identifying patients with significant aortic stenosis, whereas a fractional shortening-velocity ratio <0.8 had a sensitivity of 100% and a predictive accuracy of 74% to % for identifying patients with critical aortic stenosis.In summary, the fractional shortening-velocity ratio is a new Doppler echocardiographic method that reliably identifies patients with clinically significant aortic stenosis. The simplicity of this new noninvasive method readily lends itself to routine clinical use

Author Correction: LKB1 loss links serine metabolism to DNA methylation and tumorigenesis

Erratum for: LKB1 loss links serine metabolism to DNA methylation and tumorigenesis. [Nature. 2016

Therapeutic Insights from Genomic Studies of Head and Neck Squamous Cell Carcinomas

Large and comprehensive genomic surveys of head and neck squamous cell carcinomas are now greatly increasing our understanding of the diversity of this disease and the key genomic changes, which drive these tumors. The results from these studies are beginning to inform the introduction of novel therapies for patients with head and neck squamous cell cancers. Here, we review some of the key findings from recent genomic studies of head and neck cancers including the most comprehensive study to date from The Cancer Genome Atlas Network

Splanchnic metabolism of nutrients and hormones in steers fed alfalfa under conditions of increased absorption of ammonia and L-arginine supply across the portal-drained viscera

Effects of increased ammonia and/or arginine absorption on net splanchnic (portal-drained viscera [PDV] plus liver) metabolism of nonnitrogenous nutrients and hormones in cattle were examined. Six Hereford × Angus steers (501 ± 1 kg BW) prepared with vascular catheters for measurements of net flux across the splanchnic bed were fed a 75% alfalfa:25% (as-fed basis) corn and soybean meal diet (0.523 MJ of ME/[kg BW0.75.d]) every 2 h without (27.0 g of N/kg of DM) and with 20 g of urea/kg of DM (35.7 g of N/kg of DM) in a split-plot design. Net flux measurements were made immediately before and after a 72-h mesenteric vein infusion of L-arginine (15 mmol/h). There were no treatment effects onPDVor hepaticO2 consumption. Dietary urea had no effect on splanchnic metabolism of glucose or L-lactate, but arginine infusion decreased net hepatic removal of L-lactate when urea was fed (P < 0.01). Net PDV appearance of n-butyrate was increased by arginine infusion (P < 0.07), and both dietary urea (P < 0.09) and arginine infusion (P < 0.05) increased net hepatic removal of n-butyrate. Dietary urea also increased total splanchnic acetate output (P < 0.06), tended to increase arterial glucagon concentration (P < 0.11), and decreased arterial ST concentration (P < 0.03). Arginine infusion increased arterial concentration (P < 0.07) and net PDV release (P < 0.10) and tended to increase hepatic removal (P < 0.11) of insulin, as well as arterial concentration (P < 0.01) and total splanchnic output (P < 0.01) of glucagon. Despite changes in splanchnic N metabolism, increased ammonia and arginine absorption had little measurable effect on splanchnic metabolism of glucose and other nonnitrogenous components of splanchnic energy metabolism

Frequent mutation of receptor protein tyrosine phosphatases provides a mechanism for STAT3 hyperactivation in head and neck cancer

The underpinnings of STAT3 hyperphosphorylation resulting in enhanced signaling and cancer progression are incompletely understood. Loss-of-function mutations of enzymes that dephosphorylate STAT3, such as receptor protein tyrosine phosphatases, which are encoded by the PTPR gene family, represent a plausible mechanism of STAT3 hyperactivation. We analyzed whole exome sequencing (n = 374) and reverse-phase protein array data (n = 212) from head and neck squamous cell carcinomas (HNSCCs). PTPR mutations are most common and are associated with significantly increased phospho-STAT3 expression in HNSCC tumors. Expression of receptor-like protein tyrosine phosphatase T (PTPRT) mutant proteins induces STAT3 phosphorylation and cell survival, consistent with a “driver” phenotype. Computational modeling reveals functional consequences of PTPRT mutations on phospho-tyrosine–substrate interactions. A high mutation rate (30%) of PTPRs was found in HNSCC and 14 other solid tumors, suggesting that PTPR alterations, in particular PTPRT mutations, may define a subset of patients where STAT3 pathway inhibitors hold particular promise as effective therapeutic agents.Fil: Lui, Vivian Wai Yan. University of Pittsburgh; Estados UnidosFil: Peyser, Noah D.. University of Pittsburgh; Estados UnidosFil: Ng, Patrick Kwok-Shing. University Of Texas Md Anderson Cancer Center;Fil: Hritz, Jozef. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados Unidos. Masaryk University; República ChecaFil: Zeng, Yan. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Lu, Yiling. University Of Texas Md Anderson Cancer Center;Fil: Li, Hua. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Wang, Lin. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Gilbert, Breean R.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: General, Ignacio. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Bahar, Ivet. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Ju, Zhenlin. University Of Texas Md Anderson Cancer Center;Fil: Wang, Zhenghe. Case Western Reserve University; Estados UnidosFil: Pendleton, Kelsey P.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Xiao, Xiao. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Du, Yu. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Vries, John K.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Hammerman, Peter S.. Harvard Medical School; Estados UnidosFil: Garraway, Levi A.. Harvard Medical School; Estados UnidosFil: Mills, Gordon B.. University Of Texas Md Anderson Cancer Center;Fil: Johnson, Daniel E.. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Grandis, Jennifer R.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados Unido

Integrated RNA and DNA sequencing improves mutation detection in low purity tumors

Identifying somatic mutations is critical for cancer genome characterization and for prioritizing patient treatment. DNA whole exome sequencing (DNA-WES) is currently the most popular technology; however, this yields low sensitivity in low purity tumors. RNA sequencing (RNA-seq) covers the expressed exome with depth proportional to expression. We hypothesized that integrating DNA-WES and RNA-seq would enable superior mutation detection versus DNA-WES alone. We developed a first-of-its-kind method, called UNCeqR, that detects somatic mutations by integrating patient-matched RNA-seq and DNA-WES. In simulation, the integrated DNA and RNA model outperformed the DNA-WES only model. Validation by patient-matched whole genome sequencing demonstrated superior performance of the integrated model over DNA-WES only models, including a published method and published mutation profiles. Genome-wide mutational analysis of breast and lung cancer cohorts (n = 871) revealed remarkable tumor genomics properties. Low purity tumors experienced the largest gains in mutation detection by integrating RNA-seq and DNA-WES. RNA provided greater mutation signal than DNA in expressed mutations. Compared to earlier studies on this cohort, UNCeqR increased mutation rates of driver and therapeutically targeted genes (e.g. PIK3CA, ERBB2 and FGFR2). In summary, integrating RNA-seq with DNA-WES increases mutation detection performance, especially for low purity tumors