Citations

Inhibiting the E3 ubiquitin ligase Idol in a mouse model of Alzheimer’s-like pathology ameliorates disease severity by promoting clearance of Aβ peptides by microglia.

Purpose Autologous hematopoietic cell transplantation, or autotransplantation, is effective in light-chain amyloidosis (AL), but it is associated with a high risk of early mortality (EM). In a multicenter randomized comparison against oral chemotherapy, autotransplantation was associated with 24% EM. We analyzed trends in outcomes after autologous hematopoietic cell transplantation for AL in North America. Patients and Methods Between 1995 and 2012, 1,536 patients with AL who underwent autotransplantation at 134 centers were identified in the Center for International Blood and Marrow Transplant Research database. EM and overall survival (OS) were analyzed in three time cohorts: 1995 to 2000 (n = 140), 2001 to 2006 (n = 596), and 2007 to 2012 (n = 800). Hematologic and renal responses and factors associated with EM, relapse and/or progression, progression-free survival and OS were analyzed in more recent subgroups from 2001 to 2006 (n = 197) and from 2007 to 2012 (n = 157). Results Mortality at 30 and 100 days progressively declined over successive time periods from 11% and 20%, respectively, in 1995 to 2000 to 5% and 11%, respectively, in 2001 to 2006, and to 3% and 5%, respectively, in 2007 to 2012. Correspondingly, 5-year OS improved from 55% in 1995 to 2000 to 61% in 2001 to 2006 and to 77% in 2007 to 2012. Hematologic response to transplantation improved in the latest cohort. Renal response rate was 32%. Centers performing more than four AL transplantations per year had superior survival outcomes. In the multivariable analysis, cardiac AL was associated with high EM and inferior progression-free survival and OS. Autotransplantation in 2007 to 2012 and use of higher dosages of melphalan were associated with a lowered relapse risk. A Karnofsky score less than 80 and creatinine levels 2 mg/m2 or greater were associated with worsened OS. Conclusion Post-transplantation survival in AL has improved, with a dramatic reduction in early post-transplantation mortality and excellent 5-year survival. The risk-benefit ratio for autotransplantation has changed, and randomized comparison with nontransplantation approaches is again warranted.

AbstractBackground Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM).Methods A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms.Results We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility.Conclusion A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages.

Extracellular RNAs (exRNAs) have been identified in all tested biofluids and have been associated with a variety of extracellular vesicles, ribonucleoprotein complexes and lipoprotein complexes. Much of the interest in exRNAs lies in the fact that they may serve as signalling molecules between cells, their potential to serve as biomarkers for prediction and diagnosis of disease and the possibility that exRNAs or the extracellular particles that carry them might be used for therapeutic purposes. Among the most significant bottlenecks to progress in this field is the lack of robust and standardized methods for collection and processing of biofluids, separation of different types of exRNA‐containing particles and isolation and analysis of exRNAs. The Sample and Assay Standards Working Group of the Extracellular RNA Communication Consortium is a group of laboratories funded by the U.S. National Institutes of Health to develop such methods. In our first joint endeavour, we held a series of conference calls and in‐person meetings to survey the methods used among our members, placed them in the context of the current literature and used our findings to identify areas in which the identification of robust methodologies would promote rapid advancements in the exRNA field.

Abstract Introduction: Pulmonary carcinoid tumors account for up to 5% of all lung malignancies in adults, and comprise 30% of all carcinoid malignancies. They are defined histologically as typical carcinoid (TC) and atypical carcinoid (AC) tumors, and are characterized by neuroendocrine differentiation and the potential to metastasize. Method: We characterized genomic alterations in pulmonary carcinoid tumors using whole genome and exome sequencing in addition to mRNA expression and SNP genotyping from specimens of normal lung, typical and atypical carcinoid, and SCLC. Results: Analysis of the sequencing data identified novel mutations in the pulmonary neuroendocrine tumor spectrum, including KRAS, ABCA9, GALNT10, HSFX1, PTHLH, RANBP2, BRIP1, FXR1, BACE2, NCOR2, DGKI, HERC1, HERC5 and GLI3. Pathway analysis found 45% of the cases to harbor a mutation in genes that are involved in protein-protein interaction with ubiquitin c (UBC) and may therefore play a role in ubiquitin protein degradation pathway. We also identified genes differentially expressed in corresponding regions of copy number variation, 52 of which were linked to ubiquitination pathways in 88% of the samples genotyped. Genes amplified in 15 to 23% of the cases included ITM2A, MAOA, EGR2, HAGH, TSC22D3, NBEA, TCEAL2, and TSPYL2 whereas deleted regions in 15% of the cases implicated CFD, GDI1, IFITM1 and IFITM2. Conclusion: These results suggest that in addition to previously identified pathways, dysregulation of the ubiquitin pathway may contribute to lung carcinoid tumorigenesis and could be exploited for therapeutic purposes. Citation Format: Michael K. Asiedu, Charles L. Thomas, Jie Dong, Prasidda Khadka, Zhifu Sun, Farhad Kosari, Jin Jen, Julian Molina, George Vasmatzis, Marie Christine Aubry, Ping Yang, Dennis Wigle. Genomic alterations modify ubiquitination pathways in pulmonary carcinoid tumors. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3895. doi:10.1158/1538-7445.AM2015-3895

Abstract Objective To review and evaluate available software tools for electronic health record–driven phenotype authoring in order to identify gaps and needs for future development. Materials and Methods Candidate phenotype authoring tools were identified through (1) literature search in four publication databases (PubMed, Embase, Web of Science, and Scopus) and (2) a web search. A collection of tools was compiled and reviewed after the searches. A survey was designed and distributed to the developers of the reviewed tools to discover their functionalities and features. Results Twenty-four different phenotype authoring tools were identified and reviewed. Developers of 16 of these identified tools completed the evaluation survey (67% response rate). The surveyed tools showed commonalities but also varied in their capabilities in algorithm representation, logic functions, data support and software extensibility, search functions, user interface, and data outputs. Discussion Positive trends identified in the evaluation included: algorithms can be represented in both computable and human readable formats; and most tools offer a web interface for easy access. However, issues were also identified: many tools were lacking advanced logic functions for authoring complex algorithms; the ability to construct queries that leveraged un-structured data was not widely implemented; and many tools had limited support for plug-ins or external analytic software. Conclusions Existing phenotype authoring tools could enable clinical researchers to work with electronic health record data more efficiently, but gaps still exist in terms of the functionalities of such tools. The present work can serve as a reference point for the future development of similar tools.

A mouse model for ALS A G4C2 repeat expansion in C9ORF72 is known to be the major genetic cause of frontotemporal dementia and amyotrophic lateral sclerosis (c9FTD/ALS). However, a lack of animal models recapitulating key disease features has hindered efforts to understand and prevent c9FTD/ALS-related neurodegeneration. Until now. Chew et al. describe a mouse model that mimics both neuropathological and clinical phenotypes of c9FTD/ALS. Science , this issue p. 1151

Abstract Background: The AAA-ATPase p97/VCP facilitates the extraction and degradation of ubiquitinated proteins by converting chemical energy into mechanical force. p97 is closely involved in several facets of protein homeostasis, including ubiquitin-dependent protein degradation, endoplasmic reticulum-associated degradation (ERAD) and autophagy. p97 has been increasingly linked to cancer: it showed elevated protein expression in tumors, it can mediate the degradation of proteins in cancer-relevant pathways and is required for orchestrating the ubiquitin-governed DNA-damage response. In this context, p97 inhibitors may have an advantage versus other protein homeostasis inhibitors and may be active in solid tumors where 26S proteasome inhibitors, bortezomib and carfilzomib, have shown poor efficacy. We report here p97 inhibition as a novel approach to exploit cancer cell addiction to protein homeostatic mechanisms. Results: We have discovered novel small molecule inhibitors of p97 ATPase activity with nanomolar enzymatic and cellular potency. In cellular models, treatment of cancer cells with our lead compound CB-5083 causes disruptions in specific p97 functions, including ubiquitin-dependent protein degradation, ERAD, endocytosis and autophagy. In mouse models, CB-5083 is orally bio-available and causes rapid and sustained accumulation of poly-ubiquitin in tumor xenografts after a single administration. Concurrent with increases in polyubiquitin levels, activation of ER stress response pathways and induction of apoptosis markers are also observed. Sub-chronic oral administration of CB-5083 is generally well-tolerated with <10% body weight loss and results in potent tumor growth inhibition in several solid tumor xenograft models. This result is in marked contrast to proteasome inhibitors that are inactive in the same solid tumor models. In the Vk*MYC transgenic mouse model of multiple myeloma, CB-5083 treatment resulted in >50% reduction in M-spike. Additional efforts are focused on the development of translational assays to monitor p97 target engagement and antitumor efficacy in upcoming clinical trials of CB-5083. Conclusion: These data demonstrate that CB-5083 is a potent inhibitor of p97 that translates to tumor growth inhibition in multiple rodent models of human cancer. Furthermore, CB-5083 appears to exhibit greater potency over current proteasome inhibitors that further validate targeting p97 and protein homeostasis in the treatment of cancer. Citation Format: Ronan Le Moigne, Steve Wong, Ferdie Soriano, Eduardo Valle, Daniel J. Anderson, Stevan Djakovic, Mary-Kamala Menon, Bing Yao, Julie Rice, Jinhai Wang, Szerenke Kiss Von Soly, Brajesh Kumar, Marta Chesi, P. Leif Bergsagel, Han-Jie Zhou, David Wustrow, Mark Rolfe, F. Michael Yakes. CB-5083 is a novel first in class p97 inhibitor that disrupts cellular protein homeostasis and demonstrates anti-tumor activity in solid and hematological models. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 951. doi:10.1158/1538-7445.AM2014-951

Abstract It is widely appreciated that early detection is the key to making inroads in the fight against cancers. Despite the availability of endoscopic screening, compliance is poor. The diagnosis of CRC is often made in advanced stages, and the consequence is a dismal 50% five year survival across all CRC. There is urgent need for biomarkers with performance that can meet the need of early diagnosis. Like most cancers, colorectal cancers (CRCs) express tumor antigens that can induce humoral immune response. The identification of the autoantibodies against tumor antigens may facilitate early diagnosis of CRC. The goal for this pilot project was to demonstrate the feasibility of discovering autoantibody biomarkers for colorectal cancer using Nucleic Acid Programmable Protein Arrays (NAPPA). Autoantibodies in serum samples collected from 40 patients with DNA mismatch repair proficient colorectal cancer who had died of their cancer within 18 months of their blood draw and from 40 age-gender matched healthy controls were profiled on NAPPA arrays with randomly selected 2000 human protein. The fact that p53, a tumor antigen that has been previously reported to be related to various cancers including CRC, was one of the top candidates based on the statistical analysis demonstrates the validity of our discovery platform. Besides p53, thirty-one candidate antigens were identified to have sensitivity greater than or equal to 25% at 95% specificity and fifty-one candidate antigens had an area under the ROC curve (AUC) equal to or greater than 0.6. Validation of the combined 83 unique genes selected based on these two different data analysis methods in an independent sample set in a blind fashion is on-going. This pilot study using late stage cancer samples demonstrates the feasibility and power of an immunoproteomics study using protein arrays. This approach may rapidly lead to identification of markers that could have relevance in monitoring disease progression as well as in early cancer detection. Citation Format: Gokhan Demirkan, Leah Soderberg, Garrick Wallstrom, Emily Szeto, Kristi Barker, Jie Wang, Joshua LaBaer, Noralane M. Lindor, Ji Qiu. Proteome scale identification of autoantibody biomarkers in colorectal cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 887. doi:10.1158/1538-7445.AM2014-887