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MiT family translocation renal cell carcinoma (MiT-RCC) harbors translocations involving the TFE3 or TFEB genes. RCC with TFEB amplification is also identified and is associated with a more aggressive clinical course. Accurate diagnosis of MiT-RCC is crucial for patient management. In this study, we evaluated the performance of the Archer FusionPlex assay for detection of MiT-RCC with TFE3 or TFEB translocations and TFEB amplifications. RNA was extracted from 49 RCC FFPE tissue samples with known TFE3/TFEB status (26 TFE3 FISH positive, 12 TFEB FISH positive, 4 TFEB amplified (1 case both split and amplified), and 8 FISH negative) using the Covaris extraction kit. Target enriched cDNA libraries were prepared using the Archer FusionPlex kit and sequenced on the Illumina NextSeq 550. We demonstrate that the age of the specimen, quality of RNA, and sequencing metrics are important for fusion detection. Fusions were identified in 20 of 21 cases less than 2 years old, and TFE3/TFEB rearrangements were detected in all cases with Fusion QC ≥ 100. The assay identified intrachromosomal inversions in two cases (TFE3-RBM10 and NONO-TFE3), usually difficult to identify by FISH assays. TFEB mRNA expression and the TFEB/TFE3 mRNA expression ratio were significantly higher in RCCs with TFEB fusion and TFEB gene amplification compared to tumors without TFEB fusion or amplification. A cutoff TFEB/TFE3 ratio of 0.5 resulted in 97.3% concordance to FISH results with no false negatives. Our study demonstrates that the FusionPlex assay successfully identifies TFE3 and TFEB fusions including intrachromosomal inversions. Age of the specimen and certain sequencing metrics are important for successful fusion detection. Furthermore, mRNA expression levels may be used for predicting cases harboring TFEB amplification, thereby streamlining testing. This assay enables accurate molecular detection of multiple subtypes of MiT-RCCs in a convenient workflow.

Context.— Detection of variants in hematologic malignancies is increasingly important because of a growing number of variants impacting diagnosis, prognosis, and treatment response, and as potential therapeutic targets. The use of next-generation sequencing technologies to detect variants in hematologic malignancies in a clinical diagnostic laboratory setting allows for efficient identification of routinely tested markers in multiple genes simultaneously, as well as the identification of novel and rare variants in other clinically relevant genes. Objective.— To apply a systematic approach to evaluate and validate a commercially available next-generation sequencing panel (TruSight Myeloid Sequencing Panel, Illumina, San Diego, California) targeting 54 genes. In this manuscript, we focused on the parameters that were used to evaluate assay performance characteristics. Data Sources.— Analytical validation was performed using samples containing known variants that had been identified previously. Cases were selected from different disease types, with variants in a range of genes. Panel performance characteristics were assessed and genomic regions requiring additional analysis or wet-bench approaches identified. Conclusions.— We validated the performance characteristics of a myeloid next-generation sequencing panel for detection of variants. The TruSight Myeloid Sequencing Panel covers more than 95% of target regions with depth greater than 500×. However, because of unique variant types such as large insertions or deletions or genomic regions of high GC content, variants in CEBPA, FLT3, and CALR required supplementation with non–next-generation sequencing assays or with informatics approaches to address deficiencies in performance. The use of multiple bioinformatics approaches (2 variant callers and informatics scripts) allows for maximizing calling of true positives, while identifying limitations in using either method alone.

The universe of prion and prion-like phenomena has expanded significantly in the past several years. Here, we overview the challenges in classifying this data informatically, given that terms such as "prion-like", "prion-related" or "prion-forming" do not have a stable meaning in the scientific literature. We examine the spectrum of proteins that have been described in the literature as forming prions, and discuss how "prion" can have a range of meaning, with a strict definition being for demonstration of infection with in vitro-derived recombinant prions. We suggest that although prion/prion-like phenomena can largely be apportioned into a small number of broad groups dependent on the type of transmissibility evidence for them, as new phenomena are discovered in the coming years, a detailed ontological approach might be necessary that allows for subtle definition of different "flavors" of prion / prion-like phenomena.

Prions are transmissible, propagating alternative states of proteins. Prions in budding yeast propagate heritable phenotypes and can function in large-scale gene regulation, or in some cases occur as diseases of yeast. Other 'prionogenic' proteins are likely prions that have been determined experimentally to form amyloid in vivo, and to have prion-like domains that are able to propagate heritable states. Furthermore, there are over 300 additional 'prion-like' yeast proteins that have similar amino-acid composition to prions (primarily a bias for asparagines and glutamines). Here, we examine the protein functional and interaction networks that involve prion, prionogenic and prion-like proteins. Set against a marked overall preference for N/Q-rich prion-like proteins not to interact with each other, we observe a significant tendency of prion/prionogenic proteins to interact with other, N/Q-rich prion-like proteins. This tendency is mostly due to a small number of networks involving the proteins NUP100p, LSM4p and PUB1p. In general, different data analyses of functional and interaction networks converge to indicate a strong linkage of prionogenic and prion-like proteins, to stress-granule assembly and related biological processes. These results further elucidate how prions may impact gene regulation, and reveal a broader horizon for the functional relevance of N/Q-rich prion-like domains.

Introduction. Recent genome profiling studies have increased our understanding of the mutation landscapes of myeloid malignancies. Molecular testing of AMLs (NPM1, FLT3-ITD, KIT) and MPNs (JAK2, CALR) constitute current diagnostic standard-of-care. Evidence for the diagnostic, prognostic and/or therapeutic impact of a growing set of genes and variants in myeloid malignancies allows for more accurate patient stratification and enhanced patient management. This has led to consideration of next-generation sequencing (NGS) approaches to simultaneously detect multiple variants in myeloid malignancies for use in the clinical diagnostic setting, to supplant single-gene molecular assays. We designed the Princess Margaret Advanced Genomics in Leukemia (AGILE) trial to prospectively assess the utility of NGS molecular profiling in the management of patients with myeloid malignancies. Methods. Patients for the AGILE trial are consented at the time of diagnosis using an REB approved written consent. Bone marrow or peripheral blood samples are collected at consent, accessioned within CoPath, and DNA extracted for NGS testing. NGS molecular profiling was performed using the TruSight Myeloid Sequencing Panel (TMSP; Illumina) on the MiSeq benchtop genome sequencer (Illumina) by the University Health Network Advanced Molecular Diagnostics Laboratory. The TMSP enables profiling of 54 genes (39 hotspot region; 15 complete coding region coverage) using amplicon-based library preparation and sequencing by synthesis. The TMSP detects the CALR 52 base pair deletion relevant to myelofibrosis, but not FLT3 internal tandem duplications greater than 30 base pair in size. Data were analyzed by NextGENe (v.2.3.1, SoftGenetics) and MiSeq Reporter v2.4.60. A specific script enabling alignment and calling of CALR deletions was added to the analysis to ensure there were no false negative calls. Additional testing and verification of CEBPA variants was performed by Sanger sequencing. Variants were interpreted according to Sukhai et al (Genetics in Medicine, 2015), reviewed by lab directors and reported in the Electronic Patient Record. Impact on patient care was defined as: potential for post-consolidation clinical trials; changes to frequency of monitoring; and, changes to transplant management. Cases were discussed in an interdisciplinary Genomic Tumor Board setting, at which NGS profiling data were reviewed in the context of all other diagnostic information for the patient, to determine impact on patient care. Results. Between February 11 and July 24, 2015, 162 patients were consented for AGILE; 148/162 were profiled by NGS, and to date 124/148 have been reviewed and interpreted. 62/124 (50%) of interpreted cases had a diagnosis of acute myeloid leukemia (AML); 21/124 (20%) with myeloproliferative neoplasms (MPNs); 13/124 (10%) with myelodysplastic syndromes (MDS); 6/124 (5%) with MDS/MPN; and, 15% with other hematologic malignancies. 90% of all cases profiled were informative for at least one variant (range 1-9 variants, average 3.1 variants/case). AML, MDS and MDS/MPN cases exhibited slightly more variants (3.4-4.4 variants/case) than did MPN cases (2.6 variants/case). Overall, 69% of variants were potentially actionable (Sukhai et al, 2015: 23% class 1; 8% class 2; 38% class 3), with a large fraction of cases (90/124, 72.6%) demonstrating at least one class 1 or class 3 variant. Additionally, 73/124 (58.9%) of patients exhibited actionable, class 1, variants not currently being identified by routine molecular diagnostics. In AMLs and MPNs, 88-90% of cases exhibited at least one potentially actionable variant; NGS profiling was more informative in AMLs (62% of cases exhibiting potentially actionable variants not profiled in standard of care testing, compared to 12% of MPN cases). Conclusions. We report the results of a prospective analysis of integrated NGS profiling in the context of diagnosis and management of patients with myeloid malignancies. Using a targeted NGS panel, molecular profiling of patients yielded significant information benefit over current standard approaches in 58.9% of cases analyzed, enabling potential impact on patient management. These data highlight the utility of NGS profiling to complement the initial diagnostic evaluation of myeloid malignancies. Disclosures Gupta: Incyte: Honoraria, Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Prions are units of propagation of an altered state of a protein or proteins. Prions can propagate from cell to cell, and from organism to organism, through cooption of other protein copies. Prions contain no necessary nucleic acids, and are important both as both pathogenic agents, and as a potential force in epigenetic phenomena. The original prions were derived from a misfolded form of the mammalian Prion Protein PrP. Infection by these prions causes neurodegenerative diseases. Other prions cause non-Mendelian inheritance in budding yeast, and sometimes act as diseases of yeast. We have compiled a database of >2000 prion-related sequences, called the PrionOme. The database comprises seven PrionOme classification categories: prionogenic sequences (i.e., sequences that can make prions), ‘prionoids’ (i.e., phenomena that have some prion characteristics), orthologs, paralogs, pseudogenes, prion interactors, and prion-like molecules. Database entries list: supporting information for PrionOme classifications, prion-determinant areas (where relevant), and disordered and compositionally-biased regions. Also included are original references for the PrionOme classifications, transcripts and genomic coordinates, and structural data (including comparative models). We provide database usage examples for both vertebrate and fungal prion contexts. As development of this resource is on-going, we will be very happy to receive and act on any constructive comments from peer scientists in the areas of prion biology and protein misfolding, either by email or using the feedback form provided on the PrionOme website. We hope that this database will be a valuable experimental aid and reference resource. It is freely available at: http://libaio.biol.mcgill.ca/prion.

Recent cancer genome profiling studies have increased our understanding of the somatic mutation landscape of myeloid malignancies. A number of genes and variants are known to have prognostic/predictive utility in several myeloid malignancies, allowing for more accurate stratification, and enhanced patient management. This has led to consideration of NGS for detection of somatic mutations in myeloid malignancies in the clinical diagnostic setting, to supplant single-gene molecular testing assays in current use. Building on our prior work establishing a novel mass spectrometry-based high throughput mutation detection assay for hematologic malignancies, we investigated the application of NGS to myeloid malignancy diagnostics. To do this, we validated the Illumina TruSight Myeloid Sequencing Panel (54 genes, 568 amplicons) on 71 acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasm (MPN) patient samples, alongside relevant controls. NGS Libraries were prepared using standard protocols, and sequencing performed on the Illumina MiSeq platform. Concordance among NGS calls, single gene tests, and Sanger verification was tested as part of the clinical validation process. Analysis of 41 cases tested in our previously developed mass spectrometry assay indicated 100% concordance (70/70) for reportable variants mutually covered in both assays. Single nucleotide variations detectable in lab-standard single gene assays were all found by NGS (100% concordance). 58/71 (82%) cases had at least one additional potentially clinically relevant variant that would not have been identified in the existing assay (mean 1.95 additional variants/case; range 1-9). Additionally, we determined that AMLs carrying IDH1, IDH2 or TET2 mutations had a higher mutation burden (mean 4.6 mutations/case, range 2-7), compared to AMLs wild-type for these three genes (mean 3.1 mutations/case, range 2-4; p = 0.008). Clinically relevant insertions (up to 33 bp) and deletions (up to 52 bp) associated with AML and MPN, including FLT3 ITD and CALR deletions, were detected in known positive cases. In these cases, our analysis was supplemented with a custom bioinformatics algorithm allowing for alignment against an artificial reference sequence to detect larger indels. Due to low coverage of the clinically actionable CEBPA, we supplemented the NGS assay with Sanger sequencing for this locus. Therefore, we report the validation of an NGS panel for high throughput detection of mutations in myeloid malignancies, and the development of a wet-bench and informatics workflow enabling maximal information benefit in the diagnostic setting. This pipeline allows the detection of variants that impact diagnosis and patient management, with significantly improved information benefit over current tests. Citation Format: Mariam Thomas, Mahadeo Sukhai, Tong Zhang, Djamel Harbi, Justin De Souza, Katherine MacDonald, Trevor Pugh, Mark Minden, Andre Schuh, Tracy L. Stockley, Suzanne Kamel-Reid. Clinical testing and implementation of the TruSight Myeloid Next Generation Sequencing (NGS) panel for identification of clinically relevant variants in hematological malignancies. [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 4260. doi:10.1158/1538-7445.AM2015-4260