Citations

Abstract Objectives The lack of uniform terminology and abbreviations for anti-synthetase syndrome has led to significant challenges in research and clinical practice. This study aimed to establish an international consensus on a standardized nomenclature and abbreviation among a diverse group of global myositis experts and patient representatives. Methods This qualitative project was approved by the International Myositis Assessment and Clinical Studies Group (IMACS). Based on the outcomes of a literature review and preliminary survey, list of terms for nomenclature and abbreviations was finalized. Subsequently, two rounds of the Delphi survey were conducted among myositis experts and patient participants to ascertain current practices and preferences. Using Nominal Group Technique (NGT), the project steering committee developed a consensus nomenclature and abbreviation. Results A total of 241 and 132 myositis experts from six continents, 35 countries and 9 specialities participated in round 1 and round 2 of the Delphi survey, respectively. The results indicated a preference for the terms anti-synthetase syndrome, antisynthetase syndrome and anti-tRNA synthetase syndrome. The abbreviations ASS, ASyS and ASSD were most used, though ASS received notable disapproval. The steering committee, including twenty-five myositis experts and three patient representatives from diverse backgrounds and geographical locations, reached a consensus on ‘anti-synthetase syndrome’ as the preferred nomenclature and ASyS as the preferred abbreviation, with 100% and 93.1% votes, respectively. Conclusion The terms anti-synthetase syndrome and ASyS should be adopted as the standard nomenclature and abbreviation in both research and clinical practice. This standardization is expected to increase consistency within the literature.

Abstract Objectives To compare clinical characteristics, including the frequency of cutaneous, extramuscular manifestations and malignancy, between adults with anti-synthetase syndrome (ASyS) and DM. Methods Using data regarding adults from the MYONET registry, a cohort of DM patients with anti-Mi2/-TIF1γ/-NXP2/-SAE/-MDA5 autoantibodies, and a cohort of ASyS patients with anti-tRNA synthetase autoantibodies (anti-Jo1/-PL7/-PL12/-OJ/-EJ/-Zo/-KS) were identified. Patients with DM sine dermatitis or with discordant dual autoantibody specificities were excluded. Sub-cohorts of patients with ASyS with or without skin involvement were defined based on presence of DM-type rashes (heliotrope rash, Gottron’s papules/sign, violaceous rash, shawl sign, V-sign, erythroderma, and/or periorbital rash). Results In total 1054 patients were included (DM, n = 405; ASyS, n = 649). In the ASyS cohort, 31% (n = 203) had DM-type skin involvement (ASyS-DMskin). A higher frequency of extramuscular manifestations, including Mechanic’s hands, Raynaud’s phenomenon, arthritis, interstitial lung disease and cardiac involvement differentiated ASyS-DMskin from DM (all P < 0.001), whereas higher frequency of any of four DM-type rashes—heliotrope rash (n = 248, 61% vs n = 90, 44%), violaceous rash (n = 166, 41% vs n = 57, 9%), V-sign (n = 124, 31% vs n = 28, 4%), and shawl sign (n = 133, 33% vs n = 18, 3%)—differentiated DM from ASyS-DMskin (all P < 0.005). Cancer-associated myositis (CAM) was more frequent in DM (n = 67, 17%) compared with ASyS (n = 21, 3%) and ASyS-DMskin (n = 7, 3%) cohorts (both P < 0.001). Conclusion DM-type rashes are frequent in patients with ASyS; however, distinct clinical manifestations differentiate these patients from classical DM. Skin involvement in ASyS does not necessitate increased malignancy surveillance. These findings will inform future ASyS classification criteria and patient management.

SummaryBackgroundColitis is a significant complication of immune checkpoint inhibitors (ICI). Currently, clinical and endoscopic severity are used to guide therapy.AimsTo investigate associations between clinical, endoscopic, and histological features with outcomesMethodsWe identified 149 patients from seven institutions with biopsy‐proven ICI colitis. Biopsies were evaluated for histological features including the Geboes score, and the Robarts histopathological index (RHI) was calculated. Clinical, endoscopic, and histological data were tested for associations with biological use and adverse colitis outcomes (biological‐refractory colitis, colectomy or death from colitis).ResultsThree mutually exclusive histological patterns were identified: acute colitis, chronic active colitis and microscopic colitis. Microscopic colitis was associated with older age (68.5 vs 61 years for acute colitis pattern, P = 0.02) and longer time to colitis (5.5 vs 3 months for the other patterns, P = 0.05). Biological use was associated with earlier time to colitis (2 vs 3 months, P = 0.04) and higher RHI (18 vs 12, P = 0.007). On multivariate analysis, RHI ≥14 was associated with biological use with an odds ratio of 4.5 (95% CI 1.4‐13.8; P = 0.01). Adverse colitis outcomes were associated with shorter time to colitis (2 vs 3 months, P = 0.008) and higher RHI (24 vs 14, P = 0.001). On multivariate analysis, RHI ≥24 was associated with adverse colitis outcomes with an odds ratio 9.5 (95% CI 2.1‐42.3 P = 0.003).ConclusionHistological activity as measured by RHI is the only factor independently associated with biological use and adverse colitis outcomes. Prospective studies are needed to validate these findings to determine if histological activity should be incorporated into therapeutic algorithms.

Abstract Colorectal cancer (CRC) is estimated to be the third most common cancer in both men and women in the US in 2012, accounting for over 50,000 deaths. Familial CRC accounts for approximately 30% of all CRC, yet only 5% of familial CRCs can be attributed to mutations in known hereditary colon cancer (HCC) genes. Many families with a strong family history of CRC do not have mutations in known CRC genes. Finding the genes underpinning CRC in these families may improve screening for disease and allow the development of more targeted therapeutics. We completed targeted sequencing of over 2,000 genes and miRNAs in 1,500 cases of CRC from the Colon Cancer Family Registry (CCFR) in an effort to identify rare variants associated with CRC risk and to identify mutations in known CRC genes missed by conventional sequencing. Several categories of genes were included: 18 known HCC genes; 18 candidate HCC genes; 185 genes in previously reported CRC linkage peaks; 1,423 miRNAs; and 363 genes identified through whole exome sequencing of 40 affected cases in 16 families with hereditary CRC (n=2,007 total genes sequenced). Genomic DNA samples were indexed, then libraries were made using Agilent's SureSelect Targeted Enrichment kit. Samples were pooled (96 samples/pool), then each pool of samples was run on five lanes on an Illumina HiSeq2000 (average of 19.2 samples/lane). GenomeGPS, an in-house developed workflow, was used for read alignment, variant calling, and annotation. In early analyses of the first 161 cases, the mean number of mapped reads exceeded 20 million per sample and over 90% of the target region exceeded 40x coverage. A total of 26,484 SNPs were identified and passed quality filtering. Sequencing identified known mutations in MMR genes in positive control cases as well as mutations in HCC genes in previously untested cases. Analysis is currently on-going on the remaining samples and we will report results on the full set of 1500 cases at the meeting. Citation Format: Melissa S. DeRycke, Shanaka R. Gunawardena, Sumit Middha, Shannon K. McDonnell, Shaun M. Riska, Zachary C. Fogarty, Bruce W. Eckloff, Daniel J. Schaid, Ellen L. Goode, Stephen N. Thibodeau. Targeted sequencing to identify rare variants in colorectal cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2548. doi:10.1158/1538-7445.AM2013-2548

Abstract Background: Colorectal cancer (CRC) in densely affected families without Lynch Syndrome may be due to mutations in undiscovered genetic loci. Familial linkage analyses have yielded disparate results; the use of exome sequencing in coding regions may identify novel segregating variants. Methods: We completed exome sequencing on 40 affected cases from 16 multicase pedigrees to identify novel loci. Variants shared among all sequenced cases within each family were identified and filtered to exclude common variants and single-nucleotide variants (SNV) predicted to be benign. Results: We identified 32 nonsense or splice-site SNVs, 375 missense SNVs, 1,394 synonymous or noncoding SNVs, and 50 indels in the 16 families. Of particular interest are two validated and replicated missense variants in CENPE and KIF23, which are both located within previously reported CRC linkage regions, on chromosomes 1 and 15, respectively. Conclusions: Whole-exome sequencing identified DNA variants in multiple genes. Additional sequencing of these genes in additional samples will further elucidate the role of variants in these regions in CRC susceptibility. Impact: Exome sequencing of familial CRC cases can identify novel rare variants that may influence disease risk. Cancer Epidemiol Biomarkers Prev; 22(7); 1239–51. ©2013 AACR.

Abstract Several platforms for genome sequencing and methods for exon enrichment are now available and continue to evolve quickly. In this study, we compared the performance of whole exome sequencing using two instruments, Illumina's GAIIx and HiSeq 2000, comparing single versus duplicate runs. Eight runs of eight samples each were performed with genomic DNA derived from whole blood and sample libraries prepared with the Agilent SureSelect capture array. One run was conducted in duplicate on the GAIIx, and, for some analyses, the combined data were used. We used TREAT (Targeted RE-sequencing and Annotation Tool), developed in-house for data analysis, including sequence alignment (MAQ, BWA), local re-alignment (GATK), variant calling (utilizing MAQ), annotation (SIFT and Seattle Seq), and visualization. Overall, duplicate runs on the GAIIx platform (compared to a single run) increased the number of total reads by approximately two-fold: from ∼66 M to ∼130 M. For both single and duplicate runs, ∼90% of reads mapped to the reference sequence, and ∼55% of reads mapped on-target. Of importance, the percent coverage of the target region increased substantially with duplicate runs; ∼72% of the target region was covered at 40-fold or more when run in duplicate compared to only ∼52% when run once. At 30x, 20x, and 10x, there was a 1.3- (62% v. 78%), 1.2- (72% v. 84%), and 1.1-fold (84% v. 91%) increase respectively, in the percent coverage of the target region for samples run twice. A similar number of filtered, on-target SNPs per sample (∼24 K) was found for both single and duplicate run analyses. However, a 1.3-fold increase in the number of on-target indels was seen in the duplicate run (∼1,200) compared to the single run (∼900). When the combined data for samples run twice on a GAIIx were compared to the samples run using a HiSeq, the total number of reads were similar (∼130 M), although several of the samples had substantially more reads on the HiSeq platform. Samples run on a HiSeq had an increase in the percent coverage of the target region at 40x (72% v. 81%), 30x (78% v. 86%), 20x (84% v. 91%) and 10x (91% v. 95%) compared to the two-run approach on a GAIIx. A similar number of filtered on-target SNPs (∼24 K/sample) and indels (∼1200) was found with the HiSeq compared to two runs on a GAIIx. In summary, our results demonstrate increases in the total number of reads and in overall coverage with the HiSeq 2000 instrument. The total number of SNPs and indel that mapped on target for the version 1 Agilent SureSelect capture array is ∼25 K and 1,200 per sample, respectively. As capture is of variable efficiency for individual runs, higher average coverage of the target region is necessary for sufficient coverage of poorly captured regions. Additional analyses comparing Agilent SureSelect versions 1 and 2 arrays are underway. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2742. doi:10.1158/1538-7445.AM2011-2742