Citations

Abstract Introduction: The myeloproliferative neoplasms (MPNs) including polycythaemia vera (PV), essential thrombocythaemia (ET) and primary myelofibrosis (PMF) are rare diseases which contribute to significant morbidity. Symptom management is a prime objective in MPN treatment but current symptom assessment tools have not been validated compared to the general population. Materials and Methods: The MPN Symptom Assessment Form (MPN-SAF) is a reliable and validated clinical tool used to assess MPN symptom burden. The MPN-SAF was administered to MPN patients (n=106) and, for the first time, General Practice and non-blood relative/family controls (n=124) as part of a UK pilot case-control study. Mean scores for individual MPN-SAF items and for the Total Symptom Score were previously compared between cases and controls adjusting for potential confounding variables (Anderson LA, et al. Am J Hematol. 2015). The current analysis employed linear discriminant analysis (a multivariate technique) to compare MPN-10 symptom profiles between controls and cases, and between controls and patient groups by MPN diagnosis (ET n=55, PV n=37, PMF n=14). Results: MPN patients as a single group had significantly different MPN-10 symptom profiles compared to controls (multivariate analysis of variance [MANOVA] p<0.001). Discriminant loadings which represent correlations between each individual MPN-10 item and the single significant canonical variable were >0.30 for all MPN-10 items, and >0.50 for weight loss, fatigue, night sweats, bone pain, abdominal discomfort, inactivity, concentration problems, and itching. This suggests that all MPN-10 items contribute to distinguishing between patients and controls. The linear discriminate function correctly categorized 72% of all subjects. When considering patients by diagnosis, MPN-10 symptom profiles significantly differed across patients with ET, PV, and PMF and controls (MANOVA p<0.001). Three canonical variables were significant, with discriminant loadings of the first canonical variable being >0.50 for the same MPN-10 items as the previous analysis; of the second canonical variable for fever; and of the third canonical variable for bone pain. This suggests that MPN-10 items are broadly useful in differentiating between patients and controls, with particular symptoms (e.g., fever and bone pain) contributing to differentiating between patients with different diagnoses. The linear discriminate function correctly categorized 58% of all subjects. Conclusions: MPN patients experience significant morbidity when compared to the general population highlighting the need to manage symptoms effectively. Symptom profiles can not only distinguish MPN patients from general population participants, but also distinguish among patients with ET, PV, and PMF. The results further validate the use of the MPN-SAF as a discriminatory tool to assess MPN symptomatic disease burden. The MOSAICC Study team acknowledges the support of the National Institute for Health Research, through the Northern Ireland Cancer Research Network (NICRN) and for Southampton the Central South Coast Cancer Network (CSCCN). Disclosures Mesa: Novartis. Research- incyte, Gilead, cti, Genentech, promedior, NS Pharma: Consultancy.

Abstract The existence of stereotyped B cell receptor immunoglobulins (BcR IG) in chronic lymphocytic leukemia (CLL) strongly implicated antigen selection in disease ontogeny. We have previously shown that the stereotyped fraction encompasses ~30% of all CLL and includes multiple subsets with distinct BcR IG configuration and variable size. Eventually, certain major subsets emerged as distinct clinical entities, exemplified by subset #2 (IGHV3-21/IGLV3-21, ~2.5-3% of all CLL, mixed somatic hypermutation (SHM) status) of a particularly aggressive clinical course, thus, sharply contrasting subset #4 (IGHV4-34/IGKV2-30, ~1% of all CLL, mutated IGHV genes, M-CLL), a prototype for indolent disease. Here, taking advantage of a multi-institutional cohort of 21,123 CLL IG rearrangements, almost three times the size of the largest previous study, and the availability of validated, purpose-built immunoinformatics methods, we reappraised BcR IG stereotypy especially focusing on major subsets and the degree of their sequence similarity to related minor subsets. Stereotypy discovery was performed with ARResT/Teiresias, while stereotypy assignment to existing subsets previously deemed as major was performed with ARResT/AssignSubsets (http://bat.infspire.org/arrest/). In the present study, a subset was characterized as major if representing > 0.2% of the cohort (i.e. at least 50 cases). Minor subsets closely related to major ones (termed satellite) were identified applying the following criteria: (i) usage of IGHV genes from the same phylogenetic clan; (ii) VH CDR3 length difference ranging from -2 to +2 compared to the respective major subset; (iii) shared VH CDR3 sequence motif; and, (iv) -2 to +2 difference in the offset of the VH CDR3 motif compared to the respective major subset. In total, 7378/21123 (34.9%) IG sequences were grouped into subsets with stereotyped VH CDR3, with the previously characterized 19 major subsets accounting collectively for 2594 sequences (12.3%) of the cohort: of these, 12 included cases with unmutated IGHV genes (U-CLL), 6 concerned M-CLL and 1 (subset #2) included cases with mixed SHM status. Four additional subsets exceeded 50 cases, and, thus, were also considered as 'major'. These results reinforce the notion that not all CLL will end up being stereotyped but rather that a plateau for stereotypy exists at ~1/3 of the cohort. Subset #2 was the largest subset (n=572, 2.7%), while subset #1 (IGHV clan I (IGHV1,5,7 subgroups)/IGKV1(D)-39) was the most frequent subset within U-CLL (n=515, 2.4%) and subset #4 the most common M-CLL subset (n=192, 0.9%), hence displaying remarkable consistency regarding their frequency in all cohorts published since the pioneering studies. Altogether, Teiresias and AssignSubsets gave concordant results for previously identified major subsets, illustrating the validity of our approach. Satellite subsets were sought for individually for each major subset. In general, few satellite subsets were identified, most of which concerned U-CLL major subsets. That notwithstanding, notable cases of satellite subsets were exemplified by major subset #1 and its satellite subset #99 from which it differed only in VH CDR3 length (13 aminoacids in subset #1 versus 14 in subset #99); interestingly, both subsets displayed equally aggressive clinical course. Another example concerned subset #8 (IGHV4-39/IGKV1(D)-39, U-CLL), an aggressive subset with very high risk for Richter's transformation, that, except for a one-aminoacid difference in VH CDR3 length, was otherwise identical to satellite subset #215, also displaying clinical aggressiveness. Overall, our results confirm that major subsets can be robustly identified and are consistent in relative size, hence representing distinct disease subgroups amenable to compartmentalized research with the potential of overcoming the pronounced heterogeneity of CLL. Most major subsets display unique sequence motifs, however satellite subsets exist, especially within U-CLL. Considering ever-increasing evidence that major stereotyped subsets may represent distinct disease subgroups, the existence of satellite subsets reveals a novel aspect of repertoire restriction and has implications for refined molecular classification of CLL. Disclosures Shanafelt: Genentech: Research Funding; GlaxoSmithkKine: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Pharmacyclics: Research Funding; Cephalon: Research Funding; Hospira: Research Funding. Gaidano:Roche: Consultancy, Honoraria, Speakers Bureau; Karyopharm: Consultancy, Honoraria; Morphosys: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau. Niemann:Janssen: Consultancy; Abbvie: Consultancy; Roche: Consultancy; Gilead: Consultancy. Langerak:F. Hofmann-LaRoche, Genentech: Research Funding; InVivoScribe Technologies: Patents & Royalties: Royalties are provided to European Network (EuroClonality). Jaeger:Roche: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Kater:Celgene: Research Funding; Gilead: Research Funding; Janssen: Consultancy, Research Funding; Roche: Consultancy, Research Funding; Abbvie: Consultancy, Research Funding. Stilgenbauer:Amgen: Consultancy, Honoraria, Other: Travel grants, Research Funding; Gilead: Consultancy, Honoraria, Other: Travel grants , Research Funding; Genentech: Consultancy, Honoraria, Other: Travel grants , Research Funding; Celgene: Consultancy, Honoraria, Other: Travel grants , Research Funding; Boehringer Ingelheim: Consultancy, Honoraria, Other: Travel grants , Research Funding; Genzyme: Consultancy, Honoraria, Other: Travel grants , Research Funding; AbbVie: Consultancy, Honoraria, Other: Travel grants, Research Funding; GSK: Consultancy, Honoraria, Other: Travel grants , Research Funding; Janssen: Consultancy, Honoraria, Other: Travel grants , Research Funding; Mundipharma: Consultancy, Honoraria, Other: Travel grants , Research Funding; Novartis: Consultancy, Honoraria, Other: Travel grants , Research Funding; Pharmacyclics: Consultancy, Honoraria, Other: Travel grants , Research Funding; Hoffmann-La Roche: Consultancy, Honoraria, Other: Travel grants , Research Funding; Sanofi: Consultancy, Honoraria, Other: Travel grants , Research Funding. Hallek:Gilead: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; F. Hoffmann-LaRoche: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Mundipharma: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Other: travel support, Research Funding, Speakers Bureau. Rosenquist:Gilead Sciences: Speakers Bureau. Ghia:Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Roche: Honoraria, Research Funding; Adaptive: Consultancy; Abbvie: Consultancy, Honoraria. Stamatopoulos:Novartis: Honoraria, Research Funding; Abbvie: Honoraria, Other: Travel expenses; Janssen: Honoraria, Other: Travel expenses, Research Funding; Gilead: Consultancy, Honoraria, Research Funding.

Abstract 5-azacitidine (5-AZA) is standard of care in the first-line setting for higher-risk patients with Myelodysplastic Syndrome (MDS). However, 40-50% of patients are refractory to 5-AZA and most responders ultimately demonstrate disease progression within 2 years, often progressing to AML. For patients refractory to 5-AZA, 2-year survival probability is low (15%). Thus, there is a need for more effective initial and second-line therapies for patients with higher-risk MDS. The Inhibitors of Apoptosis (IAP) Proteins are a family of molecules that suppress apoptotic cell death. Expression of IAPs is dysregulated in MDS, suggesting a potential path for therapeutic intervention. SMAC (second mitochondrial activator of caspases) is an IAP antagonist, resulting in caspase activation, inhibition of NF-kB and increased apoptosis. Birinapant is a potent bivalent SMAC mimetic with improved tolerability and therapeutic index compared to other SMAC mimetics. This Phase Ib/2a study was designed primarily to determine the MTD and recommended Phase 2 dose and schedule of birinapant in combination with 5-AZA in patients with higher-risk MDS who are naïve or have relapsed or are refractory to 5-AZA. To date, 11 patients have been enrolled in the Phase 1b portion of the study, including 7 with IPSS classification high-risk MDS (5 male, 2 female; median age 75, range 64-82) and 4 with intermediate-risk MDS (2 male, 2 female; median age 72.5, range 65-84). All patients received standard 5-AZA, administered via either intravenous (IV) or subcutaneous (SC) routes, at 75 mg/m2 for 7 days of a 28-day cycle in combination with birinapant. Birinapant was administered IV twice weekly (Days 1 and 4) for either 3 of 4 weeks or 4 of 4 weeks per 28-day cycle at a dose of 13 mg/m2. No cycle 1 dose-limiting toxicities have been observed. Adverse events ≥ Grade 2 observed in two or more patients and judged to be related to treatment were rash/pruritis (Grade 2, 2 patients), thrombocytopenia (Grade 4, 2 patients) and neutropenia (Grade 4, 1 patient; Grade 3, 1 patient). Two SAEs, Grade 3 abdominal soft tissue necrosis with abdominal pain in the area of subcutaneous injections of 5-AZA, and Grade 3 cellulitis were judged to be related to treatment. These local injection site reactions/cellulitis were more severe than usually expected with SC 5-AZA, suggesting an on target pharmacodynamic (TNF mediated) localized synergistic effect in skin, but were not observed with IV administration. Both occurred after cycle 1 and were not considered DLTs. Data showing inhibition of NF-kB, a downstream pro-survival molecule activated by IAPs, in circulating blast cells from patients treated with birinapant at a dose of 13 mg/m2 twice weekly for 3 weeks out of 4, suggests that birinapant is pharmacologically active at this dosing schedule. Based on these and other pharmacodynamic data, despite not determining the formal MTD, the Phase 2 dosing regimen has been established as birinapant administered at 13 mg/m2 IV twice weekly for 3 weeks of a 28-day cycle in combination with 5-AZA at 75 mg/m2 by IV infusion for 7 days of a 28-day cycle. Although not a primary endpoint, evidence of clinical activity in 5-AZA resistant/refractory patients was observed in 2 of 11 patients to date, with an additional good clinical response in a 5-AZA naive high-risk MDS/CMML patient. One patient with prior 5-AZA-refractory MDS (cytogenetics: hypodiploid and +11q) showed bone marrow (BM) blast count reduction from 25% to 2% after 1 cycle of 5-AZA/birinapant treatment. Another patient with MDS (cytogenetics: +X; +19; +21) refractory to single-agent 5-AZA showed BM blast count reduction from 21% to 7% after 2 cycles. A third patient with treatment-naïve MDS/CMML-2 (cytogenetics: 46, XY, inv(6)(p11.2q15), t(6;21)(q21;q22) ) who had received prior hydroxyurea demonstrated BM blast count reduction from 17% to 2% after 3 cycles and underwent hematopoietic stem cell transplant. Several patients remain on study and are in active follow-up. This Phase 1b trial provide data for an acceptable safety profile of the first combination of a SMAC mimetic (birinapant) administered with IV 5-AZA. Early signs of clinical activity including in 5-AZA naïve and refractory patients were observed. These results provide rationale for a randomized Phase 2 study comparing birinapant in combination with 5-AZA against 5-AZA alone in the first-line setting for patients with higher-risk MDS. Disclosures Borthakur: Tetralogic Pharmaceuticals: Research Funding. Foran:TetraLogic Pharmaceuticals: Research Funding. Wang:Tetralogic Pharmaceuticals: Research Funding. Rakkar:Tetralogic Pharmaceuticals: Research Funding. Hager:Tetralogic Pharmaceuticals: Research Funding. Frey:Tetralogic Pharmaceuticals: Research Funding. Andreeff:TetraLogic Pharmaceuticals: Research Funding. Carter:Tetralogic Pharmaceuticals: Research Funding. Minderman:Tetralogic Pharmaceuticals: Research Funding. Russell:Tetralogic Pharmaceuticals: Employment. Tibes:Tetralogic Pharmaceuticals: Research Funding.

Abstract In chronic lymphocytic leukemia (CLL), the molecular features of the clonotypic B-cell receptor immunoglobulins (BcR IG) are set from the birth of the clone and in contrast to genetic aberrations, remain stable overtime, rendering the BcR IG a reference biomarker that is usually not significantly affected by clonal evolution. Approximately 30% of CLL cases carry quasi-identical BcR IGs and can be assigned to distinct stereotyped subsets. While preliminary evidence alludes to BcR IG stereotypy being relevant from a clinical viewpoint, this aspect has never been explored systematically or in a cohort of adequate size to enable meaningful conclusions. In order to assess the clinical implications of BcR IG stereotypy, we evaluated clinicobiological data from 8593 CLL patients, particularly focusing on 14 major stereotyped subsets of cases with unmutated (U-CLL) or mutated IGHV genes (M-CLL). The largest subset was #2 (n=254, 3%), within which 156 and 98 cases were M-CLL and U-CLL, respectively, followed by U-CLL subsets #1 (n=173, 2%) and #7 (n=123, 1.4%). Amongst M-CLL, the largest subsets were #4 (n=94, 1.1%) and #148 (n=92, 1%). Stereotyped subsets, even of the same mutational category i.e. U-CLL or M-CLL, exhibited significant clinicobiological differences regarding: age at diagnosis (median age ranging from 53-68 years, p<0.001); gender distribution (male/female ratios ranging from 0.85-4.4, p<0.001); the frequency of advanced stage disease (Binet C) at diagnosis (ranging from 9-21%, p<0.001); CD38 positivity (median percentage of positive cells ranging from 2-73%, p<0.05). Moving to cytogenetic findings, we detected subset-biased spectra of FISH-detected aberrations which can be summarized as follows: (i) isolated del(13q) varied from 10% in subset #8 (U-CLL), to 29% in subsets #59 (U-CLL) and #16 (M-CLL), and >75% in M-CLL subsets #77 and #148 (p<0.001); (ii) trisomy 12 was absent in subsets #31 (U-CLL) and #77 (M-CLL), in 20% of subset #201 (M-CLL) and, 60% in subset #8 (U-CLL) (p<0.001); (iii) del(11q) ranged from 69% in subset #31 (U-CLL) to 12% in subset #8 (U-CLL) and 0% in M-CLL subsets #16 and #201 (p<0.001); (iv) del(17p): absent from all M-CLL subsets except #148 (7.5%); absent from U-CLL subsets #5 and #59, and present in 19% and 17% of stereotyped subset #8 and #6 cases, respectively (p<0.05). We considered subset #2 separately since it included both M-CLL and U-CLL and identified a distinctive clinicobiological profile characterized by a constellation of features, including high incidence of Binet stage C disease (21%), CD38 positivity (41%) and certain cytogenetic abnormalities i.e. del(13q) (56%) and del(11q) (23%) and, in contrast, low frequency of del(17p) (4.5%). Notably, no differences were found between U-CLL versus M-CLL subset #2 cases regarding the incidence of these parameters. Survival analysis for time-to-first-treatment (TTFT) revealed that each stereotyped subset exhibited a distinct clinical course, different from that of other subsets even with similar IGHV gene mutational status and/or expressing the same IGHV gene. Interestingly, subsets #1 and #2 demonstrated a similar TTFT to that of del(17p) positive cases, while within subset #2 the clinical outcome was independent of IGHV mutational status. By integrating BcR IG stereotypy into the Döhner cytogenetic prognostication model, we found that subsets #1, #2 and #4, collectively accounting for ~7% of our series, and representing both U-CLL and M-CLL, constituted distinct clinical entities, with the latter exhibiting a particularly indolent disease even when compared to isolated del(13q) cases or cases with no cytogenetic aberrations. Finally, in multivariate analysis for TTFT, assignment to subset #2 emerged as a new independent unfavorable factor (p=0.002); furthermore, when restricting the analysis to Binet A cases, subset #2 exhibited the second highest hazard ratio after U-CLL. In conclusion, the molecular classification of CLL based on BcR IG stereotypy refines prognostication beyond IG mutational status and improves the Döhner hierarchical model. Hence, we suggest that a compartmentalized approach focusing on and comparing different subsets sheds light on CLL clinical behavior and biology and that BcR IG stereotypy represents a companion molecular diagnostic for personalized medicine in CLL. Disclosures Montillo: Janssen: Honoraria.

Abstract The human IGHV4-34 gene encodes antibodies which are intrinsically autoreactive when the VH domain is unmutated. Therefore, B cells expressing IGHV4-34 B-cell receptor immunoglobulins (BcR IG) are normally under close scrutiny in order to avoid unwanted autoreactivity, especially against DNA. The IGHV4-34 gene is frequently utilized in chronic lymphocytic leukemia (CLL), where, typically, it shows a high load of somatic hypermutation (SHM). We have previously reported distinctive SHM patterns amongst IGHV4-34 CLL, especially for subsets with stereotyped BcR IG. However, although a large number of cases (~2000) was previously studied, since even the largest subsets account for only ~3% of CLL, meaningful conclusions could not be reached for smaller subsets. Here we revisit this issue in a series of 16,528 CLL cases and focus on IGHV4-34 expressing subsets: #4 (IGHV4-34/IGHD5-18/IGHJ6 | 156 cases, 0.9%); #11 (IGHV4-34/IGHD3-10/IGHJ4 | 16 cases, 0.1%); #16 (IGHV4-34/IGHD2-15/IGHJ6 | 41 cases, 0.25%); #29 (IGHV4-34/IGHD: unassignable/IGHJ3 | 39 cases, 0.24%); and #201 (IGHV4-34/IGHD: unassignable/IGHJ3 | 43 cases 0.26%). Focusing on codons 27-104 within the VH domain (from CDR1-IMGT to FR3-IMGT), we calculated the sequence distance between subsets and the corresponding IGHV4-34 germline sequence based on a pairwise qualitative and quantitative comparison of the respective amino acid composition. The minimum distance calculated, and hence the greatest identity, was observed between subsets #4 and #16, both concerning IgG-switched cases (IgG-CLL), which is notable given the overall rarity of IgG-CLL. In contrast, the maximum distance, implying the least identity, was between subsets #16 and #201, the latter concerning IgM/D-CLL. Extreme variations between subsets were noted in codons spanning the entire VH domain. This result is consistent with our finding of a subset-biased distribution of mutations over the VH domain. More specifically, while subsets #11, #16, #29 and #201 had a lower frequency of mutations within VH CDR1 compared to VH CDR2, the exact opposite was seen in subset #4, with 40% of mutations in VH CDR1 versus 27% in VH CDR2. In addition, subsets #4, #11, #16 and #29 had a similar distribution of mutations in VH FR2 and VH FR3, in contrast to subset #201 that showed a preference for VH FR3 over VH FR2. Consequently, we noted that certain positions were targeted in a subset-specific manner e.g. codon 28 in VH CDR1 was heavily targeted in subsets #4 (68.6%) and #16 (87.8%), with most cases carrying an acidic amino acid (AA) introduced by SHM, glycine to glutamic acid, G>E: 51.3% for subset #4 and 78% for subset #16. The high prevalence of acidic AA introduced by SHM in these subsets is notable considering the electropositive nature of their VH CDR3 (especially of subset #4), strongly recalling edited anti-DNA antibodies. Interestingly, the G>E change was identified at a much lower frequency in other IGHV4-34 subsets: 18.75% for subset #11; 2.6% for subset #29; 7% for subset #201, all of which carried electronegative VH CDR3. Further, we noted that certain positions were heavily targeted in all subsets e.g. 56-86% targeting for SHM at codon 92 in VH FR3 where serine is encoded by the agc triplet, the ”hottest of hotspots”. This result could be viewed as sequence- rather than subset-dependent and linked to the molecular features of this codon, which is supported by the low targeting of codon 93 (0-6%), also encoding serine by the tct triplet. Other positions were targeted in all subsets but at vastly different frequencies e.g. codon 64 was targeted in 37.8% in subset #4 rising to 100% in subset #29. Finally, positions heavily targeted by SHM in certain subsets were unmutated in other subsets e.g. codon 36 in VH CDR1 remained unmutated in subset #16, in contrast 76.9% of subset #29 were mutated at this position resulting in an AA change. In conclusion, we document different spectra of SHM and AA changes between stereotyped IGHV4-34 CLL subsets. The finding of subset-biased, recurrent AA changes at certain codons indicates that the respective progenitor cells may have responded in a specific manner to the selecting antigen(s), despite expressing the same IGHV gene, indicating a functional purpose for these modifications. This is exemplified by the molecular characteristics of the recurrent AA changes in subset #4, thereby offering interesting pathogenetic hints. Disclosures No relevant conflicts of interest to declare.

INTRODUCTION: High-resolution manometry using the Chicago Classification is standard in the evaluation of esophageal motility. When the relaxation of the esophagogastric junction is impaired and achalasia excluded, esophagogastric junction outflow obstruction (EGJ-OO) is diagnosed and the esophageal body is essentially ignored. We sought to characterize the function of the esophageal body in consecutive patients with EGJ-OO. METHODS: Retrospective review of the esophageal manometry findings in consecutive patients where there was computer recognition of EGJ-OO collected over a 2-month period. In each case, the esophageal body was reviewed manually and results reported independent of the suggested computer diagnosis. RESULTS: 116 patients underwent manometry over a 2-month period and 30 (26%) were identified as having EGJ-OO. The indications for testing included chronic cough (n = 5), GERD (n = 8), dysphagia (n = 9) and esophageal evaluation associated with severe lung disease or transplantation (n = 8). The mean IRP was 20.8 (range 16-33.6) and did not vary depending on indication ( P = 0.381). Computer interpretation was EGJ-OO in all patients without mention of the esophageal body. After review, 11 (37%) had an additional esophageal diagnosis. In effective esophageal motility (IEM) was the most prevalent among them (IEM-8, achalasia-2, jackhammer esophagus-1; P = 0.020). The frequency of an additional esophageal diagnosis was significantly different between GERD (0%) and dysphagia (66%; P = 0.004), but not between other groups (i.e. 40% in cough and 37.5% in transplant group). An esophageal body diagnosis was significantly more likely in patients with IRP > 25 (80%) compared with those with IRP < 25 (28%; P = 0.028). CONCLUSION: 1-EGJ-OO is common in patients referred for esophageal manometry. 2-An additional esophageal body diagnosis is common in those with EGJ-OO.3-Esophageal diagnoses are more common in patients with dysphagia and in those with a very high IRP. The body of the esophagus is important in cases of EGJ-OO and should be reported independent of the computer-generated interpretation of the Chicago Classification.

Objective Discrepancies in ELISA measurements of human corticosteroid-binding globulin (CBG) using detection monoclonal antibodies that recognize an epitope (9G12) within its reactive center loop (RCL), versus an epitope (12G2) in a different location, have suggested that CBG with a proteolytically cleaved RCL exists in blood samples. We have previously been unable to verify this biochemically, and sought to determine if N -glycosylation differences account for discrepancies in ELISA measurements of CBG. Methods and subjects Molecular biological, biochemical and glycopeptide analyses were used to examine how N -glycosylation at specific sites, including at N347 within the RCL, affect CBG ELISA or steroid-binding capacity assay (BCA) measurements. Plasma from patients with congenital disorders of glycosylation (CDG) was also examined in these assays as examples of N -glycosylation defects. Results We demonstrate that an N -glycan at N347 within the CBG RCL limits the 9G12 antibody from recognizing its epitope, whereas the 12G2 antibody reactivity is unaffected, thereby contributing to discrepancies in ELISA measurements using these two antibodies. Qualitative differences in N -glycosylation at N238 also negatively affect the steroid-binding of CBG in the absence of an N -glycan at N347 caused by a T349A substitution. Desialylation increased both ELISA measurements relative to BCA values. Similarly, plasma CBG levels in both ELISAs were much higher than BCA values in several CDG patients. Conclusions Plasma CBG measurements are influenced by variations in N -glycosylation. This is important given the increasing number of CDG defects identified recently and because N -glycosylation abnormalities are common in patients with metabolic and liver diseases.