The diagnosis of Graves’ orbitopathy is usually straightforward. However, orbital diseases that mimick some clinical signs of Graves’ orbitopathy may cause diagnostic confusion, particularly when associated to some form of thyroid dysfunction. This report describes the rare occurrence of localized inferior rectus muscle amyloidosis in a patient with autoimmune hypothyroidism, who was misdiagnosed as Graves’ orbitopathy. A 48-year-old man complained of painless progressive proptosis on the left side and intermittent vertical diplopia for 6 months. The diagnosis of Graves’ orbitopathy was entertained after magnetic resonance imaging revealing a markedly enlarged, tendon-sparing inferior rectus enlargement on the left side, and an autoimmune hypothyroidism was disclosed on systemic medical workup. After no clinical improvement with treatment, the patient was referred to an ophthalmologist and further investigation was performed. The presence of calcification in the inferior rectus muscle on computed tomography, associated with the clinical findings led to a diagnostic biopsy, which revealed amyloid deposition. This report emphasizes that a careful evaluation of atypical forms of Graves’ orbitopathy may be crucial and should include, yet with rare occurrence, amyloidosis in its differential diagnosis.
Flow cytometry adds to the results of morphologic and immunohistochemical studies, facilitating a rapid and accurate diagnosis of lymphoproliferative diseases.
Introduction: The development of next-generation sequencing has made it feasible to interrogate the entire genome or exome (coding genome) in a single experiment. Accordingly, our knowledge of the somatic mutations that cause cancer has increased exponentially in the last years. MPNs and MDS/MPD are chronic myeloid neoplasms characterized by an increased proliferation of one or more hematopoietic cell lineages, and an increased risk of transformation to acute myeloid leukemia (AML). MPNs and MDS/MPDs are heterogenous disorders, both in clinical presentation and in prognosis. We sought to determine the genetic landscape of Ph-negative MPNs and MDS/MPD through next-generation sequencing. Methods: Paired DNA (sorted CD66b-granulocytes/skin biopsy) from 102 patients with MPNs or MDS/MPD was subjected to whole exome sequencing on a Illumina HiSeq 2000 platform using Agilent SureSelect kit. Diagnosis included primary myelofibrosis (MF; N=42), essential thrombocythemia (ET; N=28), polycythemia vera (PV; N=12), chronic myelomonocytic leukemia (CMML; N=10), systemic mastocytosis (MS; N=6), MDS/MPD-Unclassified (N=2) and post-MPN AML (N=2). Tumor coverage was 150x and germline coverage was 60x. Somatic variants calls were generated by combining the output of Somatic Sniper (Washington University), Mutect (Broad Institute) and Pindel (Washington University). The combined output of these 3 tools was further filtered by in-house criteria in order to reduce false-positive calls (minimum coverage at both tumor/germline ≥8 reads; fraction of reads supporting alternate allele ≥10% in tumor and ≤10% in germline; ratio of allele fraction tumor:germline >2; excluding mutations seen in SNP databases). All JAK2 and CALR mutations were validated through Sanger sequencing. Validation of other somatic mutations is currently underway. Analysis of driver mutations was made with the Intogen web-based software, using the Oncodrive-FM and Oncodrive-cluster algorithms (www.intogen.org). Significantly mutated genes were considered as those with a q-value of <0.10. Results: We identified a total of 309 somatic mutations in all patients, with each patient having an average of 3 somatic abnormalities, fewer than most solid tumors that have been sequenced so far. Mutations occurred in 166 genes, and 40 of these were recurrently somatically mutated in Ph-negative MPNs. By the Oncodrive-FM algorithm, the following genes were identified as the most significantly mutated driver genes in Ph-negative MPNs and MDS/MPDs (in order of significance): CALR, ASXL1, JAK2, CBL, DNMT3A, U2AF1, TET2, TP53, RUNX1, EZH2, SH2B3 and KIT. By the Oncodrive-cluster algorithm, which considers clustering of mutations at a hotspot, the following genes were significantly mutated: KIT, JAK2, SRSF2 and U2AF1. Somatic mutations were seen in genes that are mutated at a low frequency in Ph-negative MPNs, including ATRX, BCL11A, BCORL1, BIRC5, BRCC3, CSF2RB, CUX1, IRF1, KDM2B, ROS1 and SUZ12. Consistent with the clinical phenotype, 96 patients (94%) had mutations that lead to increased cellular proliferation, either through activation of the JAK-STAT pathway (e.g. JAK2, CALR) or mutations that activated directly or indirectly signaling by receptor tyrosine kinases (e.g. FLT3, KIT, CBL). Besides biological pathways regulating cell proliferation, the most commonly implicated pathways included regulation of DNA methylation (e.g. DNMT3A, TET2), mRNA splicing (e.g. U2AF1, SRSF2) and histone modifications (e.g. ASXL1, EZH2), seen in 27%, 25% and 22% of patients, respectively. Abnormalities in these 3 pathways were more often seen in MF, MDS/MPD and CMML, as compared to PV and ET (65% vs. 20%; p<0.0001). Conclusions: Our study represents one of the largest series of patients with these neoplasms evaluated by whole exome sequencing, and together with the published data helps to delineate the genomic landscape of Ph-negative MPNs and MDS/MPDs. The majority of the most frequent mutations seen in Ph-negative MPNs have already been reported. Nevertheless, there are several low frequency mutations that need to be further studied and functionally validated in vitro and in vivo for a deeper knowledge of the pathophysiology of MPNs. Besides activation of cellular proliferation, abnormalities of DNA methylation, histone modification and mRNA splicing emerge as the most important biological pathways in these disorders. Disclosures No relevant conflicts of interest to declare.
Introduction: Primary Myelofibrosis (PMF) and Essential Thrombocythemia (ET) are myeloproliferative neoplasms with similar genetic backgrounds. Both diseases are characterized, at the molecular level, by mutations in the genes JAK2, MPL and CALR. In addition recurring mutations is several other genes have been described in myeloid malignancies in general. Although the differential diagnosis between PMF and ET may be straight forward in most cases, there is a significant clinical and pathologic overlap between these two conditions, making the differential diagnosis difficult sometimes, mostly between early PMF and ET. With the goal of utilizing genomic information to better differentiate ET from PMF we decided to identify and compare all genomic alterations present in patients with ET and PMF, through whole exome / genome sequencing of paired granulocytes and skin. Methods: A total of 84 patients with either PMF (N=48) or ET (N=36) were analyzed. DNA was extracted from CD66b+ magnetic bead selected granulocytes (EasySep, Stem Cell Technologies) and matched skin biopsies with QiaAmp DNA Mini kit (Qiagen). Whole-exome targeted capture was carried out on 3 μg of genomic DNA, using the SureSelect Human Exome Kit 51Mb version 4 (Agilent Technologies, Inc., Santa Clara, CA, USA). The exome library was sequenced with 100 bp paired-end reads on an Illumina HiSeq2000. Somatic variants calls were generated by combining the output of Somatic Sniper (Washington University), Mutect (Broad Institute) and Pindel (Washington University). Tumor coverage was 150x and germline was 60x. The combined output of these 3 softwares was further filtered by in-house criteria in order to reduce false-positive calls (minimum coverage at both tumor/germline ≥8 reads; fraction of reads supporting alternate allele ≥5% in tumor and ≤10% in germline; ratio of allele fraction tumor:germline >2). All JAK2 and CALR mutations were validated through Sanger sequencing. Validations of other somatic mutations are under way at this point. For this work, other myeloid driver mutations were defined as mutations occurring recurrently in myeloid malignancies in the medical literature, and in this cohort of patients these mutations were present in the following genes: ASXL1, ATM, CALR, CBL, CUX1, DNMT3A, EZH2, GATA2, GNAS, IDH1, IDH2, JAK2, MPL, NRAS, SH2B3, SF3B1, STAG2, TET2, NFE2, SMC3, SUZ12, PRPF8, SRSF2, U2AF1, TP53. Fisherxs exact test was used for statistical comparisons. Results: The most common mutated genes after JAK2 and CALR were ASXL1 (n=16), TET2 (n=9) and DNMT3A (n=9). After data analysis, the patients could be divided in 7 groups based on the genomic profile: A – JAK2 mutation as the single genetic abnormality (JAK2_Single) (N=24), B – JAK2 plus other myeloid driver mutations (JAK2_Plus) (N=25), C - CALR mutation as the single genetic abnormality (CALR_Single) (N=11), D – CALR plus other myeloid driver mutations (CALR_Plus) (N=9), E – MPL mutation (N=1), F – Triple negative without other myeloid driver mutations (TN_Single) (N=8), G – No JAK2, CALR or MPL (triple negative) but with other myeloid driver mutations (TN_plus) (N=6) 1 – The presence of 3 or more total myeloid driver mutations was strongly associated with a diagnosis of PMF Table 1mut<3mut>2TE282PMF2521 P= 0.0002 2 – The presence of ASXL1 mutations was strongly associated with a diagnosis of PMF Table 2ASXL1+ASXL1-TE135PMF1533 P=0.0007 In order to validate our findings in an independent cohort of patients, we performed the same analysis using data from 2 published studies that evaluated myeloid multi-gene panels in ET and PMF (Nangalia J, NEJM 2013) (Lundberg P, Blood, 2014). We pooled together all patients with ET (N=117) and PMF (N=56) from both studies and repeated the two previous analyses, that confirmed the previous results: Table 3mut<3mut>2TE1106PMF4214P=0.0005ASXL1+ASXL1-TE4113PMF1442P=3.9E-05 Conclusions: We have demonstrated that ASXL1 mutations as well as a number of myeloid driver mutations higher than two is strongly associated with PMF. This information may be useful in the near future to improve the differential diagnosis between ET and PMF. Disclosures No relevant conflicts of interest to declare.
Introduction: Mutations that activate the RAS-RAF-MEK-ERK pathway have long been known to occur in patients with solid tumors and hematological malignancies. The most common mutations occur in the Ras family of GTPases (HRAS, NRAS, KRAS) and the Raf family of serine-threonine kinases (ARAF, BRAF, CRAF). In myeloid malignancies, RAS mutations have mainly been described in patients with acute myeloid leukemia, chronic myelomonocytic leukemia (CMML) and myelodysplastic syndrome. There are few studies describing the incidence of mutations of the RAS-RAF-MEK-ERK pathway in patients with MPNs other than CMML. Objective: To describe the incidence, clinical features and prognostic impact of Ras and Raf mutations in patients with Ph-negative MPNs and MPN/MDS-U Methods: Paired DNA (sorted CD66b-granulocytes/skin biopsy) from patients with MPNs or MPN/MDS was subjected to whole exome sequencing on a Illumina HiSeq 2000 platform using Agilent SureSelect kit (see our abstract “Whole Exome Sequencing of Myeloproliferative Neoplasms and Myelodysplastic/Myeloproliferative Disorders”). Tumor coverage was 150x and germline coverage was 60x. Somatic variants calls were generated by combining the output of Somatic Sniper (Washington University), Mutect (Broad Institute) and Pindel (Washington University), followed by in-house filters to reduce false positive calls. Statistical calculations were done in Stata, v11.0. Results: We found clonal activating mutations of the RAS-RAF-MEK-ERK pathway in 8 patients (6.7% of cases). Diagnosis included primary myelofibrosis (PMF; N=5), MDS/MPD-U (N=2) and essential thrombocythemia (ET; N=1). Their clinical features are summarized in Table 1 (three of these patients [UPIs #11, #13, #99] are also described in the abstract “Genomic Profile of Patients with Triple Negative (JAK2, CALR and MPL) Essential Thrombocythemia and Primary Myelofibrosis”). There were 7 NRAS mutations and 1 BRAF mutation. In 5 cases the variant allele fraction (VAF) of reads in the tumor sample indicated that the mutation was present in a subclone at the time of sequencing. We next compared the clinical features of these 8 patients with 79 patients (MF=43, ET=35, MDS/MPD=1) who did not harbor these mutations. Patients with NRAS/BRAF mutations had lower hemoglobin (8.3 vs. 11.8 g/dL, p=0.001), higher white blood cell counts (28.37 vs. 7.7 x109/L, p=0.008) and had higher lactate dehydrogenase (1041 vs. 685 IU/L, p=0.02). They also had worse overall survival compared to unmutated cases (Hazard ratio [HR]=11.57; p=0.001). Most patients with NRAS/BRAF mutations had a high number of concomitant driver mutatons (median 5 vs. 1; p<0.0001). When the number of driver mutations was analyzed together with NRAS/BRAF mutations in a Cox model, NRAS/BRAF mutations were no longer independent predictors of survival (HR=1.48; p=0.61). Conclusions: Activating mutations of the RAS-RAF-MEK-ERK pathway occur in 6-7% of patients with Ph-negative MPNs, and they tend to co-occur with a high number of concomitant driver mutations. In most cases the mutation was present in a subclone, suggesting that they are late occurring. Patients with NRAS/BRAF mutations had a trend for worse outcome, but that was mainly dependent on the total number of driver mutations. The activity of MEK and BRAF inhibitors needs to be explored in patients with Ph-negative MPNs who harbor activating mutations of the RAS-RAF-MEK-ERK pathway. Table 1. Clinical features of patients with NRAS/BRAF mutations UPI Diagnosis Mutation VAF Concomitant driver genes and Chromosomal abnormalities Outcomes 7 MF NRAS p.G12S 47% ASXL1, CALR, STAG2, U2AF1 Died from disease progression 11 MF NRAS p.G12R 5% ASXL1, CBL, CUX1 (double mutant), EZH2 Died from disease progression 13 MF NRAS p.G12D 48% ASXL1, DNMT3A, ETV6 (double mutant) JARID2, U2AF1 Died from disease progression 18 MF NRAS p.G13D 25% JAK2, Del(5q) Underwent allogeneic transplantation; disease relapsed day+80; alive 29 MDS/MPD-U BRAF p.D594G 25% JAK2, Del(5q) Transformed to AML; entered CR with induction chemotherapy; underwent allogeneic transplantation; disease relapsed day+35; alive 99 ET NRAS p.G12D 43% ASXL1, CSF3R, STAG2 Alive 109 MF NRAS p.Q61R 19% CALR, DNMT3A, ZRSR2 Alive 122 MDS/MPD-U NRAS p.G12S 7% ASXL1, EZH2 (double mutant), PTPN11, TET2 (double mutant) Transformed to AML; underwent allogeneic transplantation; died on day+58 Disclosures No relevant conflicts of interest to declare.
Introduction Graft-versus-host disease (GvHD) causes morbidity and mortality in recipients of allogeneic hematopoietic stem cell transplantation (ASCT). This study assessed the distribution of GvHD in gastrointestinal (GI) biopsies from the upper and lower GI tract in all patients who had undergone ASCT in our institution between 2005 to 2013 and evaluated the correlation between biopsy of upper and lower GI, possible relation with CMV Infection in GI biopsy and Blood sample, GvHD GI grade and extra-intestinal manifestations of GvHD Methods We performed a retrospective pathology records review for all patients diagnosed with positive GI GvHD biopsy, who underwent both upper and lower endoscopy. We also reviewed pathology and clinical reports to determine which biopsy sites were diagnostic of GvHD and to evaluate for the possible presence of extra-intestinal manifestations GvHD at the time of biopsy, CMV Status on the biopsy findings and blood sample. Results One hundred eighty nine patients (78 children and 111 adults) received ASCT transplant between 2005 to 2013. Twenty eight patients ( 14,8%) had undergone both upper and lower positive biopsy for acute GvHD diagnosis. Seventeen ( 60,7%) were male. The median age was 28 (1.50- 63.6) years old. Eleven patients had AML (39%), 6 had benign diseases (21.4%); five had ALL (17.9%); 2 lymphomas; 02 (7.1%) CML and 01 (3.1%) MDS. Main stem cell source was bone marrow 14 (50%), followed by PSCB in 7 (25%) and SCUP in 7 (25%). ATG was used in 16 (57, 1%) patients. Extra- intestinal manifestation of GVHD was: skin in 19 (67, 9%); liver in 6 (21,4%) patients. Five (17,9%) had the 3 organ involvement. The GI GvHD grade was: grade I in 7 ( 25%) , grade II in 4 ( 14,3%), grade III in 9 ( 32.1% ) and grade IV in 8 ( 28,6%). Regarding the concordance between the biopsy findings, there is agreement only between Ileum Biopsy Negative plus ileum and Rectum, because both have a higher percentage of positive GvHD. The stomach has a higher percentage of negative GvHD, and therefore there is no agreement with Colon plus ileum and Rectum. The frequency and correlation between involvement of different parts of GI-GVHD are presented in Tables 1,2 and 3. Just 2 ( 11.1%) patients had negative rectal biopsy and positive colon + ileum. Nine (32, 1%) had blood CMV detected. Five ( 17.9%) had positive Biopsy for CMV ( one in stomach, 3 in Colum and on in rectum), and just one patients had both positive. There is no association between clinical grade of GI-GVHD and the presence of CMV in biopsy and blood (CMV positive X GvHD grade, p=0.885; and biopsy CMV positive X GvHD grade, p= 0.859). It has no association between clinical grade of GI- GVHD and conditioning (p= 0.070) and use of ATG (p=0.867). HLA disparity was related with higher grades of GI-GVHD (p=0.029). All patients with Grade I are Fullmatch, whereas patients with Grade III and IV had highest percentage of mismatch [grade III= 5 (55.6%); and grade IV= 4 (57.15%) patients]. The median follow up was 7.2 (1.8-90.6) month. Overall survival (OS) was 40% in 60 month and patients with grade IV GVHD had worst OS ( P= 0.004). Conclusion Use of sigmoid biopsy for GvHD diagnosis is effective, safe, and less expensive compared to other endoscopic interventions, because it was most frequent site of lower GI-GVHD and only 11% of biopsies were discordant. CMV infection may be underdiagnosted with this approach, where colonocospy study should be considered as most of CMV positivity in biopsy was in Colum. Disclosures: No relevant conflicts of interest to declare.
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