ALBERT

Description: At this time, pretransplant viral screening of donors and recipients is based on serological status and limited to certain viruses. After transplantation, patient follow-up is based on a monitoring strategy using ELISA or PCR. Such approaches exclude other emerging viruses that can affect the transplant outcome. Recently, a multiplex unbiased array, VirScan, was developed. This tool allows the detection of antibodies against viruses, using a synthetic human virome, with minimal serum and cost. We decided to test the value of VirScan in the follow-up of a cohort of transplant recipients. We enrolled 45 kidney transplant recipients and performed virus serological profiling at day 0 and day +365, using VirScan. We compared the results obtained with ELISA/PCR assays. We detected antibody responses to 39 of the 206 species of virus present in the VirScan library, with an average of 12 species of virus per sample. VirScan gave similar results to PCR/ELISA screening tests. Using VirScan, we found that anti-viral antibody responses were largely conserved in patients during the first year after transplantation, regardless of immunosuppressive treatment. Our study suggests VirScan offers an unprecedented opportunity to screen and monitor posttransplant virus infection in a cost-effective, easy, and unbiased manner.

Description: Abstract 193FN2 INTRODUCTION: aHUS is a genetic, systemic disease with a devastating prognosis caused by chronic uncontrolled complement activation leading to thrombotic microangiopathy (TMA), progressive organ damage and premature mortality. In a 26-wk phase II trial, pts receiving ECU, a terminal complement inhibitor, had a highly significant increase in platelet count (a measure of TMA improvement) (primary endpoint: 73×109/L increase; p=0.0001). 13/15 pts with low platelet count at baseline (BL) (ITT) had platelet normalization at Wk 26. 15/17 pts (88%) achieved TMA event-free status (≥12 wks of stable platelet count, no PE/PI and no new dialysis). 13/13 pts treated with ECU for 26 wks had platelet normalization at Wk 26 and 15/15 treated with ECU for 26 wks achieved TMA event-free status. Median TMA intervention rate was 0 (no. of PE/PI and new dialysis events/pt/day). Importantly, 4/5 pts on dialysis with PE/PI discontinued dialysis with ECU. ECU was well tolerated (Legendre. ASN 2010). We report longer follow-up data from the extension phase of this ongoing trial. METHODS: Pts ≥12 yrs with aHUS and persistent TMA despite ≥4 PE/PI sessions 1 wk before screening were enrolled in a 26-wk, controlled, open-label, single-arm phase II trial and continued into an extension trial. ECU dosage: 900mg/wk for 4 wks, 1200mg at Wk 5, 1200mg q2 wks. All pts received a meningococcal vaccine and prophylactic antibiotics ≥14 days after vaccination. Efficacy analyses were based on ITT population. RESULTS: 17 pts enrolled (2 discontinued at Wks 1 and 6; systemic lupus erythematosus [protocol violation] and an adverse event unrelated to ECU, respectively). Median time from diagnosis to screening=10mo (0.3–236). Median duration from overt clinical manifestations of aHUS to screening=0.75mo (0.2–4). Median number of PE/PI sessions per pt during aHUS current clinical presentation=17 (2–37). 5 patients (29%) required dialysis at baseline. Median age=28 yrs. 4 pts (24%) had no identified complement regulatory factor mutations (CRFM). ECU mean (SD) duration=58 (29) wks at data cut-off. Mean change (SD) in platelet count from BL was maintained (97×109/L [81] at Wk 26 vs 98×109/L [60] at 1 yr). All 13 pts who had platelet normalization at Wk 26 continued to maintain normal levels at data cut-off. The same 15/17 (88%) pts achieved TMA event-free status at data cut-off. All pts receiving sustained ECU treatment throughout the study achieved TMA event-free status at data cut-off. Renal function was maintained and continued to further improve in pts with ongoing ECU: improvement ≥1 CKD stage from BL: from 10 (59%) pts at Wk 26 to 11 (65%) pts at data cut-off and ≥25% decrease in creatinine from BL: from 11 (65%) pts at Wk 26 to 13 (77%) pts at data cut-off. With sustained ECU therapy, only 1 of the 5 pts at baseline continued on to require dialysis and no patient newly required dialysis (as of data cut off). Long-term chronic ECU was similarly effective in pts with/without identified CRFM. ECU was generally well tolerated; adverse events deemed related to ECU were reported in 12 pts (mostly mild to moderate, 1 severe). The extension trial continues. CONCLUSIONS: In aHUS, despite PE/PI, 〉50% of pts either die, require dialysis, or have permanent renal damage within the first year of diagnosis. In contrast, all pts treated with ECU for a mean duration of 〉1 yr remain alive, 4 out of 5 pts became dialysis free, and no pt newly required dialysis. This demonstrates that continued ECU treatment significantly transformed the clinical course of aHUS in this pt population. In addition, long-term ECU therapy suppressed TMA and dramatically improved renal function. These long-term follow-up data further strengthen the evidence for ECU as the new standard of care for aHUS. Disclosures: Greenbaum: Alexion: Consultancy, Honoraria, Research Funding, Speakers Bureau. Off Label Use: Eculizumab for the treatment of atypical hemolytic syndrome as part of clinical trials. Babu:Alexion: Research Funding. Furman:Alexion: Research Funding. Sheerin:Alexion: Research Funding. Cohen:Alexion: Research Funding. Gaber:Alexion: Research Funding. Delmas:Alexion: Research Funding. Loirat:Alexion: Research Funding. Bedrosian:Alexion: Employment. Legendre:Alexion: Research Funding.

Description: Multiple Myeloma (MM) is a genetically heterogeneous disease of plasma cells that generally exhibits chromosomal abnormalities and distinct gene expression signatures. Previous studies have sought to identify gene expression indices using microarray technology to discern genes associated with survival outcomes to predict whether a newly diagnosed patient has an aggressive form of the disease. One such MM-specific index is the UAMS 70 gene index, which is composed of 51 over- and 19 under-expressed genes. This index was developed using Affymetrix U133Plus2.0 microarray data from 532 MM patients at diagnosis by computing log-rank test statistics on gene expression quartiles. Despite consistently achieving a high performance across a variety of MM datasets, issues arise when applying this index to RNAseq data. Here we address those issues, deriving an independent index based on the RNAseq data from the Multiple Myeloma Research Foundation (MMRF) CoMMpass Study (NCT01454297), and benchmark its performance to an implementation of the UAMS 70 gene index. UAMS index scores are computed by taking the difference between the average log2-scale expression of the 51 over- and 19 under-expressed genes. We applied this calculation to RNAseq data analyzed using Sailfish, Salmon v7.2, and HTseq counts collected from 41 Multiple Myeloma Genomics Initiative samples and compared the results to scores from matching GCRMA, MAS5, RMA, and PLIER16 Affymetrix U133Plus2.0 microarray data. Differences in the distribution of index values across data types led to nonconforming classification of high-risk individuals. Additionally, when applied to RNAseq data, several Affymetrix probesets did not uniquely match to gene annotations from Ensembl-v74. This reduced the number of genes upon which our UAMS score was calculated to 61 genes. Of the original 51 over-expressed probes, only 44 uniquely mapped genes remained after 7 multi-mapped probes are removed and similarly, out of the 19 under-expressed genes only 17 were uniquely mapped. Given the complication of probe-gene mismatch and inconsistencies identifying high-risk individuals when applied to RNAseq data, we developed an independent index using the baseline RNAseq data from the MMRF CoMMpass Study IA13 dataset. From a training set (n=375) of RNAseq data measuring 56430 genes, we performed univariate log-rank tests on expression quartiles associated with disease-related survival while controlling for an FDR of 2.5%, resulting in 23 under- and 332 over-expressed genes. Subsequent multivariate Cox regression analysis and backward stepwise selection culminated in the identification of the CoMMpass RNAseq index, which is based on the ratio of mean expression values of 87 genes (19 under- and 68 over-expressed) predictive of high risk (hazard ratio [HR] = 8.7341, 95% CI = 5.615-13.58, p 〈 0.001). Validation on the test set (n=251) yielded a HR of 5.612 (95% CI = 3.066-10.27, p 〈 0.001) as compared to a HR of 4.753 (95% CI = 2.688-8.403, p 〈 0.001) achieved with the adapted UAMS index. Adjusting for a patient's International Staging System (ISS) stage revises these hazard ratios to 6.236 (95% CI = 3.345-11.627, p 〈 0.001) and 3.6420 (95% CI = 1.9726-6.724, p 〈 0.001) for the CoMMpass RNAseq and the adapted UAMS indices, respectively. Furthermore, the distribution of CoMMpass RNAseq index values across the training and test set show no observable bias with respect to three main therapy arms, suggesting it is predictive of high risk independent of treatment. Our newly derived CoMMpass RNAseq index shares one gene in common with the UAMS 61 gene index (CENPW) and recovers two over-expressed genes (FABP5, TAGLN2), which were removed from the UAMS 70 gene index due to probe multimapping. When the recovered genes are added back to the UAMS index, the unadjusted and adjusted hazard ratios measured for the test set are 5.173 (CI = 2.926-9.146, p 〈 0.001) and 4.022 (CI = 2.1840-7.408, p 〈 0.001), respectively. Of the original 70 genes in the UAMS index, 21 (30%) map to chromosome 1, which frequently exhibits copy number gains in MM. Only 11 of the 87 (13%) genes in our proposed index map to chr1, which indicates that, given its performance, the newly derived list of genes may represent a more diverse index to predict, and provide novel insights into, high risk MM. Altogether, the CoMMpass RNAseq index identifies a high risk signature in 13% of MM patients and outperforms the UAMS index. Disclosures Lonial: Amgen: Research Funding.

Description: Multiple myeloma (MM) is a malignancy of the antibody producing plasma cell, which exhibits a high degree of genetic diversity between patients. As genetic analysis technologies have improved so has our understanding of the diverse genetic phenotypes underlying the disease. The MMRF CoMMpass study (NCT01454297) is using whole genome (WGS), exome (WES), and RNA (RNAseq) sequencing to provide a precise characterization of each patient before and after therapy. However, these advanced assays are not widely available to patients today limiting the utility of many observations to a small population of patients. To expand the utility of the data set to a broader patient population we focused on DNA copy number (CN) phenotypes that can be identified by the standard FISH assays widely used in the field. To discover potential underlying phenotypes of myeloma beyond the known dichotomy of hyperdiploid (HRD) and non-hyperdiploid (NHRD) karyotypes, unsupervised consensus clustering was performed on 871 patients with CN profiles from WGS. Given the limited dynamic range of CN values, a Monte Carlo reference-based consensus clustering algorithm, M3C, was used to limit potential overfitting issues. Three independent replicates of this procedure identified an optimal solution of eight subtypes with no more than 6 patients having different class assignments between replicates. The eight CN subtypes consisted of five HRD and three NHRD subtypes and were annotated based on common CN features. The HRD classic subtype had ubiquitous CN gains, trisomies, of classic HRD chromosomes, 3, 5, 7, 9, 11, 15, and 19. The remaining HRD subtypes were annotated based on deviations from the classic HRD phenotype. The HRD, ++15 subtype phenocopies classic HRD except tetrasomy, not trisomy, is observed on chr15. Two groups of HRD patients were identified lacking CN gains of chr7 which are split into two distinct subtypes: the HRD, diploid 7 subtype, which lacked gains of chr7; and the HRD diploid 3, 7 subtype lacking trisomies of both chr3 and chr7. This suggest some relationship between chromosomes 3 and 7 where trisomy 7 is not tolerated in the absence of trisomy 3. Finally, the HRD, +1q, diploid 11, -13 subtype had gains of the classic HRD chromosomes except chr11 with gains of chr1q and loss of chr13. This subtype suggests trisomy 11 is essential for an HRD phenotype but it can be phenocopied by the combination of 1q gains and 13 loss. Within the NHRD subtypes, the diploid subtype is almost devoid of CN abnormalities less a common gain of 11q initiating at the breakpoint the t(11;14) event, which is almost universally observed in this subtype. Unlike the diploid subtype, the remaining NHRD subtypes have more complex CN profiles with the -13 subtype defined by monosomy 13, and the +1q/-13 subtype defined by gains of 1q and monosomy 13. Outcome analyses of the CN subtypes identified in CoMMpass revealed that both HRD and NHRD patients with gains of chr1q and loss of chr13 exhibited poor PFS and OS outcomes as compared to patients in other CN subtypes. Interestingly, the PFS curves split into three groups with a good risk group defined by the HRD classic and HRD ++15 subtypes. a high-risk group defined by 1q gain and monosomy 13 regardless of ploidy phenotype, and an intermediate group with all other subtypes. The distribution of HRD patients into these three outcome groups highlights the danger of assuming all HRD myeloma patients will have similar outcomes. Patients in the HRD, +1q, diploid 11, -13 subtype exhibited poor OS outcomes (median = 56 months) as compared to patients in the HRD, ++15 (p

Description: Introduction: Multiple Myeloma (MM) is a complex malignancy of plasma cells well-described hyperdyploidy, and immunoglobulin gene rearrangements. To promote rapid advances in the field, Multiple Myeloma Research Foundation (MMRF) initiative is an intensive and comprehensive longitudinal study (CoMMpass) designed to create a rich discovery ecosystem to through in-depth clinical and molecular profiling to understand the molecular perturbations of the disease in the context of therapy. The large study population empowered us to stratify mutational landscapes among different ethnicities to influence on broader disparities in tumor dynamics. Methods: Clinical data, tumor/normal sample collection, and mutational landscape analysis described in this abstract are derived from MMRF CoMMpass IA7 release that is composed of self-identified 93 African American (AA) and 377 European American (EA). The post-processing and primary analysis was done on baseline samples only. Whole exome sequencing was analyzed for the detection of somatic events. Secondary analysis was performed using MutSigCV (Mutation Significance) algorithm and GISTIC (The Genomic Identification of Significant Targets in Cancer) to determine the significance of coding mutations and copy number events. Results: Our preliminary comparison analysis of CoMMpass IA7 data demonstrated that overall there was no statistical difference (p=0.5973) in nonsilent mutation burden between the two stratified groups, AA (μ=63.9 mutations/patient) vs EA (μ=73.7 mutations/patient). However, we have observed several notable differences. The most notable population difference (p

Description: Abstract 3303 INTRODUCTION: Chronic uncontrolled complement activation drives systemic thrombotic microangiopathy (TMA) and life-threatening complications in aHUS. In the initial 26-wk, phase II trial of eculizumab, (ECU) a terminal complement inhibitor, in pts with aHUS requiring chronic PE/PI for an extended period of time, a statistically significant and sustained suppression of TMA was observed. In addition, no pt required PE/PI, no new dialysis was required and all pts either maintained/improved renal function in the absence of PE/PI (Licht ASN 2011). We report longer follow-up data from this trial. METHODS: Pts ≥12 yrs with aHUS, receiving chronic PE/PI on an unchanged regimen were enrolled in a controlled, open-label, single-arm, phase II trial. After an 8-week observation period, pts discontinued PE/PI and started ECU (900mg/week for 4 wks, 1200mg at wk 5, then 1200mg q2 wks). Pts received a meningococcal vaccine. Primary endpoint: TMA event-free status defined as ≥12 consecutive wks of stable platelet count, no PE/PI and no new dialysis. Secondary endpoints included TMA intervention rate (no. of PE/PI and new dialysis events/pt/day), renal function, and safety. Pts continued into an extension trial. RESULTS: Of 20 pts (median age=28 yrs) who received ECU through Wk 26 of the initial trial, 19 pts continued ECU treatment into the extension trial. Mean (SD) duration of ECU treatment was 60 (12) wks at data cut-off. Median time from diagnosis to screening=48 mo (0.66–286). Median time from overt clinical symptoms of aHUS to screening=8.6 mo (1.2–45). Median no. of PE/PI sessions per pt during current clinical presentation=62 (20–230). Median duration of eGFR ≤60 mL/min/1.73m2=180 days (23–485). Six pts had no complement regulatory factor mutation (CRFM) identified. Ongoing treatment with long-term ECU was associated with continued improvements in TMA intervention rate and TMA event-free status and further improvement in renal function (Table). Long-term ECU treatment showed a highly significant time-dependent improvement in eGFR (p1 year are still alive and none progressed to ESRD or required new dialysis with sustained ECU treatment. Importantly, compared with historical outcomes with chronic PE/PI, initiation of sustained, long-term ECU therapy, without PE/PI, was associated with a highly significant time-dependent improvement in eGFR. Switching to chronic ECU therapy significantly changed the course of the disease in severe and prolonged renal insufficiency pts, resulting in sustained suppression of TMA. These data further demonstrate ECU to be the new standard of care for aHUS. Disclosures: Licht: Alexion: Honoraria, Research Funding. Off Label Use: Eculizumab but as part of clinical controlled trials. Muus:Alexion: Membership on an entity's Board of Directors or advisory committees, Research Funding. Legendre:Alexion: Research Funding. Douglas:Alexion: Genzyme, but not relevant to current submission, Research Funding. Hourmant:Alexion: Research Funding. Delmas:Alexion: Research Funding. Herthelius:Alexion: Research Funding. Trivelli:Alexion: Research Funding. Goodship:Alexion: Honoraria, Research Funding. Bedrosian:Alexion: Employment. Loirat:Alexion: Honoraria, Research Funding.