Citations

ObjectiveTo examine the association between macrophage migration inhibitory factor (MIF) promoter polymorphisms and granulomatosis with polyangiitis (GPA) in human subjects, and to assess the role of MIF in a murine model of granulomatous vasculitis.MethodsThe human study involved 1,077 patients with GPA and healthy controls whose serum was genotyped by capillary electrophoresis for the MIF −794 CATT5−8 promoter microsatellite (rs5844572). MIF promoter, CATT‐length–dependent gene expression in response to β‐glucan was assessed by gene reporter assays. In mouse studies, granulomatous disease was induced by injection of Candida albicans β‐glucan into wild‐type (WT) or Mif‐knockout (Mif‐KO) C57BL/6 mice and C57BL/6 mice transgenically overexpressing Mif in lung epithelium (Mif lung–Tg2.1). Mice were treated with a neutralizing anti‐MIF antibody and analyzed for the density of pulmonary granulomas, expression of inflammatory chemokines, and frequency of mortality.ResultsThe percentage of human subjects carrying >5 CATT repeats in each MIF allele (high genotypic MIF expressers) was 60.2% among patients with GPA and 53.9% among healthy controls (adjusted P = 0.049). In response to granulomatous stimulation, human MIF gene expression increased proportionally with CATT length. Mif lung–Tg2.1 mice exhibited more pulmonary granulomas than WT mice, which in turn showed more granulomas than Mif‐KO mice. A significantly higher percentage of Mif lung–Tg2.1 mice, compared to Mif‐KO or WT mice, died when injected with Candida albicans β‐glucan, and treatment of these mice with an anti‐MIF monoclonal antibody protected against a lethal outcome. Levels of MIF‐dependent neutrophil/macrophage chemokines were elevated in the bronchoalveolar lavage fluid or plasma of Mif lung–Tg2.1 mice.ConclusionPatients with GPA have an increased frequency of high MIF expression CATT alleles. Higher Mif expression increases the incidence of mortality and pulmonary granulomas in Mif lung–Tg2.1 mice, while anti‐MIF treatment protects these mice against death. Blockade of MIF in high genotypic MIF expressers may therefore offer a selective pharmacologic therapy for GPA.

Evidence of prior autoerotic asphyxia is often difficult to establish due to the decedent's efforts to hide the activity from others. In this case report, we suggest that a healed fracture of the thyroid cartilage is indicative of prior autoerotic asphyxia activity. The decedent was a 45-year-old man who was found unclothed on the floor of his bedroom with a belt ligature around the neck. A second rope ligature was loosely wrapped around the decedent's wrists, scrotum, and penis. A definitive escape mechanism was not identified, but a nearby towel and barbell weight may have comprised a possible escape mechanism. There was no known history of depression or prior autoerotic activity. Autopsy was notable for the presence of a healed fracture of the right superior horn of the thyroid cartilage. Three-dimensional (3D) surface scanning and 3D printing was utilized to preserve the anatomical findings prior to histologic sampling. To our knowledge, this is the first reported use of 3D surface scanning and 3D printing for the purpose of documenting a forensic finding prior to alteration of the anatomical specimen for histologic sampling. Acute fractures of the superior horns of the thyroid cartilage are not infrequently seen in ligature hanging. Therefore, the presence of a healed fracture in the setting of autoerotic asphyxia likely indicates prior activity. Histologic sampling of the laryngeal cartilages to detect occult healed fractures in autoerotic asphyxia may be useful. Three-dimensional scanning and printing may alleviate concerns for specimen alteration due to histology sampling.

Abstract The Hippo pathway effector, Yes-associated protein (YAP), is a transcriptional coactivator implicated in cholangiocarcinoma (CCA) pathogenesis. YAP is known to be regulated by a serine/threonine kinase relay module (MST1/2–LATS1/2) culminating in phosphorylation of YAP at Serine 127 and cytoplasmic sequestration. However, YAP also undergoes tyrosine phosphorylation, and the role of tyrosine phosphorylation in YAP regulation remains unclear. Herein, YAP regulation by tyrosine phosphorylation was examined in human and mouse CCA cells, as well as patient-derived xenograft (PDX) models. YAP was phosphorylated on tyrosine 357 (Y357) in CCA cell lines and PDX models. SRC family kinase (SFK) inhibition with dasatinib resulted in loss of YAPY357 phosphorylation, promoted its translocation from the nucleus to the cytoplasm, and reduced YAP target gene expression, including cell lines expressing a LATS1/2-resistant YAP mutant in which all serine residues were mutated to alanine. Consistent with these observations, precluding YAPY357 phosphorylation by site-directed mutagenesis (YAPY357F) excluded YAP from the nucleus. Targeted siRNA experiments identified LCK as the SFK that most potently mediated YAPY357 phosphorylation. Likewise, inducible CRISPR/Cas9-targeted LCK deletion decreased YAPY357 phosphorylation and its nuclear localization. The importance of LCK in CCA biology was demonstrated by clinical observations suggesting LCK expression levels were associated with early tumor recurrence following resection of CCA. Finally, dasatinib displayed therapeutic efficacy in PDX models. Mol Cancer Res; 16(10); 1556–67. ©2018 AACR.

AbstractMotivationThe use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP–SNP interactions.ResultsWe tested two candidate approaches: the ‘Five-Full’ and ‘AA9int’ method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP–SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP–SNP interactions in large-scale studies.Availability and implementationThe ‘AA9int’ and ‘parAA9int’ functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/.Supplementary informationSupplementary data are available at Bioinformatics online.

Purpose Pancreatic cancer has a poor prognosis and limited treatment options. Approximately 9% of pancreatic cancers harbor a germline or somatic BRCA1 or BRCA2 ( BRCA1/2) mutation. Because poly (ADP-ribose) polymerase inhibitors have significant activity in BRCA1/2-mutant ovarian and breast cancers, RUCAPANC investigated the efficacy and safety of rucaparib in BRCA1/2-mutant pancreatic cancer. Patients and Methods RUCAPANC enrolled patients with measurable locally advanced/metastatic pancreatic cancer who had received one to two prior chemotherapy regimens. Patients received oral rucaparib (600 mg twice daily) until disease progression. The primary end point was objective response rate. Results Nineteen patients were enrolled. Sixteen of 19 BRCA1/2 mutations were germline; three were somatic. Patients had received a median of two prior chemotherapy regimens. Four patients achieved a response; two partial responses and one complete response (CR) were confirmed (objective response rate, 15.8%; 3 of 19), with an additional CR unconfirmed. The disease control rate (CR, partial response, or stable disease for ≥ 12 weeks) was 31.6% (6 of 19) in all patients and 44.4% (4 of 9) in those who had received one prior chemotherapy regimen. As prespecified in the protocol, enrollment was stopped because of an insufficient response rate among the first 15 patients. Treatment-emergent adverse events included nausea (63.2%) and anemia (47.4%). Grade ≥ 3 adverse events included anemia (31.6%), fatigue (15.8%), and ascites (15.8%). Secondary resistance mutations were detected in circulating free tumor DNA in two patients with a germline BRCA2 mutation. These mutations are predicted to lead to the reversion of a somatic—not germline—mutation. Conclusion Rucaparib provided clinical benefit to patients with advanced pancreatic cancer and a BRCA1/2 mutation, and demonstrated an acceptable safety profile. Additional trials of rucaparib in this population are warranted.

Background: Heart involvement is the most important prognostic determinant in AL amyloidosis patients. Echocardiography is a cornerstone for the diagnosis and provides important prognostic information. Methods and Results: We studied 754 patients with AL amyloidosis who underwent echocardiographic assessment at the Mayo Clinic, including a Doppler-derived measurement of stroke volume (SV) within 30 days of their diagnosis to explore the prognostic role of echocardiographic variables in the context of a well-established soluble cardiac biomarker staging system. Reproducibility of SV, myocardial contraction fraction, and left ventricular strain was assessed in a separate, yet comparable, study cohort of 150 patients from the Pavia Amyloidosis Center. The echocardiographic measures most predictive for overall survival were SV index <33 mL/min, myocardial contraction fraction <34%, and cardiac index <2.4 L/min/m 2 with respective hazard ratios (95% confidence intervals) of 2.95 (2.37–3.66), 2.36 (1.96–2.85), and 2.32 (1.91–2.80). For the subset that had left ventricular strain performed, the prognostic cut point was −14% (hazard ratios, 2.70; 95% confidence intervals, 1.84–3.96). Each parameter was independent of systolic blood pressure, Mayo staging system (NT-proBNP [N-terminal pro-B-type natriuretic peptide] and troponin), and ejection fraction on multivariable analysis. Simple predictive models for survival, including biomarker staging along with SV index or left ventricular strain, were generated. Conclusions: SV index prognostic performance was similar to left ventricular strain in predicting survival in AL amyloidosis, independently of biomarker staging. Because SV index is routinely calculated and widely available, it could serve as the preferred echocardiographic measure to predict outcomes in AL amyloidosis patients.

Abstract Background Treatment-induced neuroendocrine prostate cancer (tNEPC) is an aggressive variant of late-stage metastatic castrate-resistant prostate cancer that commonly arises through neuroendocrine transdifferentiation (NEtD). Treatment options are limited, ineffective, and, for most patients, result in death in less than a year. We previously developed a first-in-field patient-derived xenograft (PDX) model of NEtD. Longitudinal deep transcriptome profiling of this model enabled monitoring of dynamic transcriptional changes during NEtD and in the context of androgen deprivation. Long non-coding RNA (lncRNA) are implicated in cancer where they can control gene regulation. Until now, the expression of lncRNAs during NEtD and their clinical associations were unexplored. Results We implemented a next-generation sequence analysis pipeline that can detect transcripts at low expression levels and built a genome-wide catalogue (n = 37,749) of lncRNAs. We applied this pipeline to 927 clinical samples and our high-fidelity NEtD model LTL331 and identified 821 lncRNAs in NEPC. Among these are 122 lncRNAs that robustly distinguish NEPC from prostate adenocarcinoma (AD) patient tumours. The highest expressed lncRNAs within this signature are H19, LINC00617, and SSTR5-AS1. Another 742 are associated with the NEtD process and fall into four distinct patterns of expression (NEtD lncRNA Class I, II, III, and IV) in our PDX model and clinical samples. Each class has significant (z-scores &gt;2) and unique enrichment for transcription factor binding site (TFBS) motifs in their sequences. Enriched TFBS include (1) TP53 and BRN1 in Class I, (2) ELF5, SPIC, and HOXD1 in Class II, (3) SPDEF in Class III, (4) HSF1 and FOXA1 in Class IV, and (5) TWIST1 when merging Class III with IV. Common TFBS in all NEtD lncRNA were also identified and include E2F, REST, PAX5, PAX9, and STAF. Interrogation of the top deregulated candidates (n = 100) in radical prostatectomy adenocarcinoma samples with long-term follow-up (median 18 years) revealed significant clinicopathological associations. Specifically, we identified 25 that are associated with rapid metastasis following androgen deprivation therapy (ADT). Two of these lncRNAs (SSTR5-AS1 and LINC00514) stratified patients undergoing ADT based on patient outcome. Discussion To date, a comprehensive characterization of the dynamic landscape of lncRNAs during the NEtD process has not been performed. A temporal analysis of the PDX-based NEtD model has for the first time provided this dynamic landscape. TFBS analysis identified NEPC-related TF motifs present within the NEtD lncRNA sequences, suggesting functional roles for these lncRNAs in NEPC pathogenesis. Furthermore, select NEtD lncRNAs appear to be associated with metastasis and patients receiving ADT. Treatment-related metastasis is a clinical consequence of NEPC tumours. Top candidate lncRNAs FENDRR, H19, LINC00514, LINC00617, and SSTR5-AS1 identified in this study are implicated in the development of NEPC. We present here for the first time a genome-wide catalogue of NEtD lncRNAs that characterize the transdifferentiation process and a robust NEPC lncRNA patient expression signature. To accomplish this, we carried out the largest integrative study that applied a PDX NEtD model to clinical samples. These NEtD and NEPC lncRNAs are strong candidates for clinical biomarkers and therapeutic targets and warrant further investigation.