Citations

Abstract Background Cancer rehabilitation research has accelerated over the last decade. However, closer examination of the published literature reveals that the majority of this work has focused on psychological interventions and cognitive and behavioral therapies. Recent initiatives have aggregated expert consensus around research priorities, highlighting a dearth in research regarding measurement of and interventions for physical function. Increasingly loud calls for the need to address the myriad of physical functional impairments that develop in people living with and beyond cancer have been published in the literature. A detailed survey of the landscape of published research has not been reported to our knowledge. Purpose This scoping review systematically identified literature published between 2008 and 2018 related to the screening, assessment, and interventions associated with physical function in people living with and beyond cancer. Data Sources PubMed and CINAHL were searched up to September 2018. Study Selection Study selection included articles of all levels of evidence on any disease stage and population. A total of 11,483 articles were screened for eligibility, 2507 full-text articles were reviewed, and 1055 articles were selected for final inclusion and extraction. Data Extraction Seven reviewers recorded type of cancer, disease stage, age of participants, phase of treatment, time since diagnosis, application to physical function, study design, impairments related to physical function, and measurement instruments used. Data Synthesis Approximately one-third of the articles included patients with various cancer diagnoses (30.3%), whereas the rest focused on a single cancer, most commonly breast (24.8%). Most articles (77%) measured physical function following the completion of active cancer treatment with 64% representing the assessment domain. The most commonly used measures of physical function were the Medical Outcomes Study 36-Item Health Survey Questionnaire (29%) and the European Organization for Research and Treatment of cancer Quality of Life Questionnaire-Cancer 30 (21.5%). Limitations Studies not written in English, study protocols, conference abstracts, and unpublished data were excluded. Conclusions This review elucidated significant inconsistencies in the literature regarding language used to define physical function, measurement tools used to characterize function, and the use of those tools across the cancer treatment and survivorship trajectory. The findings suggested that physical function in cancer research is predominantly measured using general health-related quality-of-life tools rather than more precise functional assessment tools. Interdisciplinary and clinician-researcher collaborative efforts should be directed toward a unified definition and assessment of physical function.

Background The American Registry for Migraine Research (ARMR) is a multicenter, prospective, longitudinal patient registry, biorepository, and neuroimaging repository that collects clinical data, electronic health record (EHR) data, blood samples, and brain imaging data from individuals with migraine or other headache types. In this manuscript, we outline ARMR research methods and report baseline data describing an initial cohort of ARMR participants. Methods Adults with any International Classification of Headache Disorders (ICHD) diagnosis were prospectively enrolled from one of the 8 participating headache specialty centers. At baseline, ARMR participants complete web‐based questionnaires, clinicians enter the participant’s ICHD diagnoses, an optional blood specimen is collected, and neuroimaging data are uploaded to the ARMR neuroimaging repository. Participants maintain the ARMR daily headache diary longitudinally and follow‐up questionnaires are completed by participants every 3 months. EHR data are integrated into the ARMR database from a subset of ARMR sites. Herein, we describe the ARMR methodology and report the summary data from ARMR participants who had, from February 2016 to May 2019, completed at least 1 baseline questionnaire from which data are reported in this manuscript. Descriptive statistics are used to provide an overview of patient’s sociodemographics, headache diagnoses, headache characteristics, most bothersome symptoms other than headache, headache‐related disability, comorbidities, and treatments. Results Data were available from 996 ARMR participants, enrolled from Mayo Clinic Arizona, Dartmouth‐Hitchcock Medical Center, University of Utah, University of Colorado, Thomas Jefferson University, University of Texas Health Science Center at Houston, Georgetown University Medical Center, and DENT Neurological Institute. Among ARMR participants, 86.7% (n = 864) were female and the mean age at the time of enrollment was 48.6 years (±13.9; range 18‐84). The most common provider‐reported diagnosis was chronic migraine (n = 622), followed by migraine without aura (n = 327), migraine with aura (n = 196), and medication overuse headache (n = 65). Average headache frequency was 19.1 ± 9.2 days per month (n = 751), with 68% reporting at least 15 headache days per month. Sensitivity to light was the most frequent (n = 222) most bothersome symptom overall, other than headache, but when present, cognitive dysfunction was most frequently (n = 157) the most bothersome symptom other than headache. Average migraine disability assessment (MIDAS) score was 52 ± 49 (n = 760), (very severe headache‐related disability); however, 17% of the ARMR population had MIDAS scores suggesting “no” or “mild” disability. The most common non‐headache health issues were allergies (n = 364), back pain (n = 296), neck pain (n = 296), depression (n = 292), and anxiety (n = 278). Nearly 85% (n = 695) of patients were using preventive medications and 24.7% were using non‐medication preventive therapy (eg, vitamins and neuromodulation). The most common preventive medication classes were neurotoxins, anticonvulsants, antidepressants, vitamins/supplements, and anticalcitonin gene‐related peptide ligand or receptor‐targeted monoclonal antibodies. Nearly 90% (n = 734) of ARMR participants was taking medications to treat migraine attacks, with the most common classes being triptans, non‐steroidal anti‐inflammatory drugs, antiemetics, acetaminophen, and combination analgesics. Conclusions ARMR is a source of real‐world patient data, biospecimens, and brain neuroimaging data that provides comprehensive insight into patients with migraine and other headache types being seen in headache specialty clinics in the United States. ARMR data will allow for longitudinal and advanced analytics that are expected to lead to a better characterization of patient heterogeneity, healthcare resource utilization, identification of endophenotypes, factors that predict treatment outcomes and clinical course, and ultimately advance the field toward precision headache medicine.

Abstract Introduction: CLL pts who qualify for participation in clinical trials are often thought of as a highly selected population. Therefore whether safety and efficacy data from these trials can be generalized to all CLL pts treated in the community setting is unknown. Prospective, observational studies can provide significant insight into pt and disease characteristics as well as practice patterns in different clinical settings. Here we report on baseline demographics and clinical characteristics for 1495 pts who participated in the Connect CLL observational study and were followed prospectively. Methods: Connect®CLL is a non study-specific intervention treatment registry which collects data on the management and outcomes of CLL pts in clinical, academic and community practices in the US. Clinical information was prospectively collected for pts treated in community (n=1312), academic (n=155), or government (n=28) centers in the US between March 2010 – Jan 2014. Pts eligible for treatment or on treatment not more than 2 months were eligible for enrollment. Here we report on the baseline demographics and clinical characteristics of a large CLL cohort stratified by AG, LOT and type of treatment center. Results: In total,1,495 pts were accrued with a median age at enrollment of 69 (range 22–99). Pts were Caucasian (92.2%), African American (6.9%), and male (63.7%). Median duration from diagnosis until initial therapy was 3.7 years (range 0-32). Age of enrolled pts was as follows; 527 pts age <65 years (AG1; 35%); 511 age 65–75 (AG2; 34%); and 457 age ≥75 (AG3; 31%) at the time of enrollment. Eight hundred and ninety-four pts (60%) were treated with front-line therapy (LOT1); 259 pts (17%) treated with second-line therapy (LOT2); and 342 pts (23%) treated beyond second-line therapy (LOT≥3). Patient age: Pt age was associated with significant variation in several clinical variables: Charlson comorbidity index (CCI) score ≥3 (AG 1-3 35/46/52%; p<0.0001), ECOG PS = 0 (AG1-3 60, 48, 33%, p<0.0001) and mean creatinine clearance (CrCl) decreased (AG 1-3 101/74/53 mL/min; p<0.0001). Line of therapy: Differences in baseline characteristics were observed between pts enrolled at LOT1 (previously untreated) and LOT2/≥3 (relapsed). Median age of pts accrued at LOT1 was 68 vs. 70 years for pts enrolled at LOT2/≥3 (p=0.007). ECOG PS = 0 was more frequent at LOT1 (50%) vs. LOT2/≥3 (42%) (p=0.0057). CCI ≥3 at LOT1 was 41% vs 48% at LOT2/≥3 (p=0.0072). When adjusted for differences in age, logistic regression also demonstrated significant differences in performance status (PS=0; p=0.02) and CCI (p=0.03) stratified by LOT. Treating institution: Baseline characteristics also differed by type of treating institution. Median age was 63 vs 70 at academic vs non-academic (p<0.0001). Pts treated at academic sites also had lower CCI (CCI≤2; 72.9% vs 54.2%, academic vs non-academic) and higher median CrCl (86.4 vs 71.4) (p=0.0017). In this registry, only 16% of patients under age 75 had CCI <= 2, CrCl >= 70 mL/min, ECOG 0-1; 18% of patients on LOT1 and 12% of pts on LOT=2 would satisfy these criteria. They represent 36% of eligible pts from academic treating institutions and 13% from community/government centers. Only 20% of patients on LOT1 would satisfy enrollment criteria for CLL8 (FCR vs. FC; Hallek; Lancet 2010) CLL 10 (BR vs FCR; NCT00769522). which did not have enrollment restrictions for age. Conclusions:Baseline characteristics of pts with CLL vary by age, LOT, and type of treatment center. In this large prospective observational study, our data confirms that older pts typically have a worse ECOG PS, more medical comorbidities, more advanced disease when initiating therapy and a lower probability of being treated at an academic medical center. Based on inclusion criteria used for entry in either CLL10 or CLL8, fewer than 20% of pts satisfy age, renal clearance, and fitness profile to be considered suitable for aggressive chemoimmunotherapy in the front line setting. This observation supports the notion that current clinical trial data might not always be applicable to the general CLL population seen in the community and argues for designing clinical trials that are more generalizable to the broader pt population. Disclosures Sharman: Gilead: Research Funding; Calistoga: Honoraria; Phamacyclics: Honoraria, Research Funding; Celgene: Consultancy, Research Funding; TG therapeutics: Research Funding; Roche: Research Funding. Mato:Millennium: Speakers Bureau; Celgene: Speakers Bureau; Genentech: Speakers Bureau. Kay:Celgene: Research Funding. Kipps:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Lamanna:Genentech-Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Weiss:Celgene: Consultancy; Phamacyclics: Consultancy; Gilead: Consultancy. Nabhan:Celgene: Honoraria, Research Funding. Flinn:Celgene: Research Funding. Grinblatt:Celgene: Honoraria, Speakers Bureau. Kozloff:Celgene: Consultancy. Farber:Alexion: Equity Ownership, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Speakers Bureau; Janssen/Pharmacyclics: Speakers Bureau; Seattle Genetics: Speakers Bureau; Genentech: Membership on an entity's Board of Directors or advisory committees. Sullivan:Celgene: Employment, Equity Ownership. Street:Celgene: Employment, Equity Ownership. Swern:Celgene: Employment, Equity Ownership. Flowers:TG Therapeutics: Research Funding; Phamacyclics: Research Funding; Acerta: Research Funding; Abbvie: Research Funding; Infinity: Research Funding; Lymphoma Research Foundation: Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Spectrum: Research Funding; Gilead: Research Funding; Genentech: Unpaid consultancy Other; Millennium: Research Funding, Unpaid consultancy, Unpaid consultancy Other; Seattle Genetics: Consultancy; Prescription Solutions: Consultancy; Celgene: Unpaid consultancy Other.

Abstract Introduction: Rituximab (R) improves survival in CLL when added to intensive chemotherapy (such as fludarabine and cyclophosphamide [FCR]), and has been shown to improve progression-free survival when given as maintenance therapy following first- or second-line chemoimmunotherapy. However, early phase 2 studies demonstrated only modest activity of R monotherapy (R mono), particularly at standard dose, and its use as a single agent for pts with CLL has remained controversial. Here we describe the characteristics and outcomes of pts with CLL receiving R mono in a real-world setting. Methods: The Connect CLL registry (NCT01081015), a multicenter, prospective observational cohort study, enrolled 1,494 pts with CLL between 2010-2014 from 179 community, 17 academic, and 3 government sites throughout the USA. Pts were ≥ 18 years and were enrolled ≤ 2 months after initiating any line of therapy (LOT). Pts were treated according to individual physician/patient decision making, and adherence to IWCLL standards cannot be determined. Bone marrow biopsy and CT scans were at the physician's discretion; responses were physician assessed and not centrally reviewed. For this analysis, pts were stratified by first (LOT1) or subsequent LOT (LOT≥2), and by treatment with R mono or other treatments (Tx). Kaplan-Meier methods were used to estimate event-free survival (EFS; event defined as death, progression/relapse, or transformation). A log-rank test was used to evaluate differences in EFS. A multivariate analysis of EFS in LOT1 pts was performed using the Cox regression model. Results: Of the pts enrolled, 105 (11.8%) pts in LOT1 and 81 (13.4%) pts in LOT≥2 received R mono. Of the pts receiving other Tx, 620/784 pts (79%) in LOT1 and 333/524 pts (64%) in LOT≥2 received R in combination. In LOT1, pts receiving R mono were older than pts receiving other Tx (74 vs 67 years; P < 0.0001); in LOT≥2 median ages were comparable (71 vs 70 years). Pts receiving R mono were more likely to have Rai stage 0-1 CLL than pts receiving other Tx, both in LOT1 (63.9% vs 51.8%; P = 0.05) and LOT≥2 (70.4% vs 49.9%; P = 0.005). The proportion of pts receiving R mono vs other Tx with a CCI score of ≥ 4 was similar in LOT1 (25.7% vs 22.8%) and LOT≥2 (32.1% vs 28.4%). Median absolute lymphocyte count at enrollment was lower in pts on R mono vs other Tx in LOT1 (27.7 vs 46.1 x 109/L) but similar in LOT≥2 (35.6 vs 30.2 x 109/L). A lower proportion of pts receiving R mono had FISH/cytogenetics performed at enrollment than pts receiving other Tx in LOT1 (48.6% vs 67.0%; P = 0.0002) and LOT≥2 (30.9% vs 49.6%; P = 0.002). The most common Tx regimens in LOT1 were FCR (25.9%), bendamustine plus R ([BR] 21.0%), R mono (11.8%), fludarabine plus R ([FR] 6.3%), and chlorambucil (4.6%); and in LOT≥2, BR (27.6%), R mono (13.4%), FCR (8.6%), bendamustine (7.4%), FR (4.1%), and ofatumumab (4.0%). The most common reason to initiate treatment in any LOT was bone marrow failure (LOT1, 44.8% vs 39.3%; LOT≥2, 37.0% vs 31.5%; R mono vs other Tx). Duration of therapy was shorter for pts receiving R mono vs other Tx in LOT1 (1.4 vs 4.1 months) and LOT≥2 (1.6 vs 3.3 months). In LOT1, responses were lower in pts on R mono vs other Tx: overall response rate (ORR) was 38.1% vs 64.2% (complete response [CR], 16.2% vs 41.2%; P < 0.0001). In LOT≥2, ORR was 25.9% vs 24.6% for pts on R mono vs other Tx (CR, 9.9% vs 11.5%; P = 0.68). Partial response did not differ significantly between pts receiving R mono vs other Tx in LOT1 and LOT≥2. Pts receiving R mono in LOT1 had inferior median EFS vs other Tx (34 vs 50 months; log-rank P = 0.04); however, after adjusting for factors such as ECOG status and del(17p) status, there was no difference in EFS (HR 0.932; P = 0.79). In pts in LOT≥2, median EFS was similar for R mono and other Tx (15 months for both groups; P = 0.93). Conclusions: Pts receiving R mono as frontline CLL therapy were older than pts receiving other Tx. They also had lower stage disease and lower lymphocyte counts, a shorter duration of treatment, and inferior response rates. Pts receiving R mono in relapsed CLL, more closely approximated pts receiving other Tx in terms of age. Despite the shorter duration of therapy for pts receiving R mono in LOT1 and LOT≥2, both groups had similar ORR and EFS in LOT≥2. These data reinforce the idea that R mono is inadequate as frontline therapy in progressive CLL, and demonstrate the opportunity for improvement in relapsed/refractory disease with novel agents relative to traditional chemoimmunotherapy approaches. Disclosures Sharman: Celgene: Research Funding; Gilead: Research Funding; Pharmacyclics: Research Funding; Acerta: Research Funding; TG Therapeutics: Research Funding; Seattle Genetics: Research Funding. Davids:Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie, Janssen, Gilead: Consultancy; Celgene Corporation: Consultancy. Farber:Seattle Genetics: Research Funding. Grinblatt:Celgene Corporation: Consultancy, Speakers Bureau. Lamanna:Gilead: Research Funding; AbbVie: Research Funding; Genentech: Research Funding; Infinity: Research Funding; Pronai: Research Funding; Celgene Corporation: Research Funding. Mato:TG Therapeutics: Consultancy; Abbvie: Research Funding; Acerta Pharma: Research Funding; Gilead Sciences: Research Funding; ProNAi: Research Funding; TG Therapeutics: Research Funding; Theradex: Research Funding; Pharmacyclics: Consultancy; Gilead Sciences: Consultancy; Abbvie: Consultancy. Nabhan:Astellas: Research Funding; Seattle Genetics: Research Funding; Cardinal Health: Consultancy; Infinity: Consultancy; Abbvie: Consultancy; Genentech: Consultancy, Research Funding; Celgene Corporation: Consultancy, Research Funding. Sullivan:Celgene Corporation: Employment, Equity Ownership. Flick:Celgene Corporation: Employment, Equity Ownership. Kiselev:Celgene Corporation: Employment, Equity Ownership. Bhushan:Celgene Corporation: Employment, Equity Ownership. Swern:Celgene: Employment, Equity Ownership. Flowers:Seattle Genetics: Research Funding; Optum Rx, Seattle Genetics, Genentech/Roche: Consultancy; Celgene Corporation: Consultancy, Honoraria; Spectrum, Janssen, Infinity, AbbVie, Acerta, Pharmacyclics, TG Therapeutics: Research Funding; Millennium: Consultancy, Research Funding; Gilead: Consultancy, Research Funding.

Abstract The nucleoside analogue cytarabine is part of standard therapy for acute myelogenous leukemia (AML) and is also widely used in various acute lymphocytic leukemia (ALL) regimens. During a 7-day infusion at 100 mg/m2/d, which is part of the “7 + 3” AML induction regimen, steady-state cytarabine concentrations in the 100-200 nM range are achieved. Previous literature suggesting the mechanism of cytarabine-induced killing in AML examined cytarabine concentrations in the micromolar range, which might be less pertinent to routinely achieved drug exposure. To better understand the mechanism of cytarabine-induced killing, AML and ALL cell lines were exposed to varying cytarabine concentrations (25-200 nM) for 24-48 hours and assayed for cell death using a variety of assays. Dose- and time-dependent induction of apoptosis was observed in both AML and ALL cell lines, as detected by phosphatidylserine externalization (Annexin V staining), DNA fragmentation (propidium iodide staining for subdiploid cells), nuclear morphological changes, and cleavage of caspase substrates. Jurkat T cell ALL variants lacking critical components of the death receptor pathway (FADD or procaspase 8) underwent apoptosis with kinetics indistinguishable from parental cells, arguing against involvement of the death receptor pathway. Immunoblotting for Bcl-2 family members in AML and ALL cell lines revealed upregulation of the BH3-only proteins Bim, Puma and Noxa across multiple lines. In further experiments, small interfering RNA (siRNA)-mediated knockdown of Bim, Puma, and Noxa or the mitochondrial proteins Bax and Bak markedly diminished the apoptotic response to cytarabine. These results suggest that cytarabine at nanomolar concentrations kills cells through the mitochondrial apoptotic pathway but, in contrast to more targeted agents, does so by upregulating multiple BH3-only Bcl-2 family members simultaneously. Additional studies to determine the mechanisms of Bim, Puma, and Noxa upregulation are underway. (Supported in part by R01 CA166741 and predoctoral fellowships from the Mayo Foundation for Education and Research.) Disclosures No relevant conflicts of interest to declare.

BACKGROUND: Axi-cel is an autologous anti-CD19 chimeric antigen receptor (CAR) T-cell therapy that is approved for treatment of relapsed/refractory (R/R) large B-cell lymphoma and is associated with high response rates and durable remissions. Recent data show that axi-cel is effective across various adverse prognostic features, namely cell of origin, disease bulkiness, and extranodal disease, among others. Hypoalbuminemia is a known adverse prognostic factor in lymphomas. It is unknown if axi-cel overcomes the adverse prognostic feature of hypoalbuminemia in R/R large B-cell or transformed follicular lymphoma. METHODS: We conducted a retrospective analysis of patients treated with axi-cel across three Mayo Clinic campuses (Rochester, Jacksonville, and Phoenix) from 06/01/2018 until 04/01/2019. The primary objective of this analysis was to assess the impact of hypoalbuminemia (defined at day 0, prior to infusion) on outcome after axi-cel therapy. RESULTS: A total of 50 (male=37, 74%) patients (pts), median age of 53 (26-67) years received axi-cel. The median number of prior lines of therapy was 3 (2-8) (Table 1). Two pts had no available serum albumin levels at time of axi-cel infusion. Seven (15%) of 48 pts had serum albumin levels lower than 3.5 g/dL (median= 3.3 g/dL (range 2.6-3.4)) and the median follow up of survivors was 7.6 (1.9-14.3) months. The best overall response rate (ORR) and complete remission (CR) rates in these pts were 57% and 57%, respectively. One (14%) patient had stable disease and 2 (29%) had disease progression. The median overall survival (OS) for pts with hypoalbuminemia was not reached. On the other hand, 41 (85%) pts had a normal serum albumin level (median=4.0 (range 3.5-5.1) g/dL) and the median follow up for survivors was 6.3 months. The best objective response rate (ORR) and complete remission (CR) rates in these pts were 82% and 44%, respectively. The median OS for pts with normal serum albumin was 14 (95%CI=6.3-29.6) months. There was no significant difference at 6-months and 1-year OS between pts with hypoalbuminemia vs. those with normal baseline serum albumin levels [6-month=100% vs. 79%(95%CI=64-93%); 1-year (100% vs. 54% (95%CI=26-82%), p=0.17] (Figure 1). All grades cytokine release syndrome (CRS) was diagnosed in all 7 pts with hypoalbuminemia (100%) and in 38 of 41 (92%) pts without hypoalbuminemia. There was no difference in the median duration of CRS between pts with or without hypoalbuminemia [6 (range 1-11) days vs 5 (range 1-19) days, p=0.89]. Neurotoxicity (all grades) was observed in 5 (71%) pts with hypoalbuminemia compared 26 (63%) with normal albumin levels. There was no statistically significant difference in median duration of neurotoxicity between pts with hypoalbuminemia and those with normal baseline albumin levels [9 (range 1-10) days vs. 3 (range 0-25) days, p= 0.72]. CONCLUSIONS: Hypoalbuminemia does not have a significant impact on the outcomes of axi-cel therapy, including the incidence of CRS or neurotoxicity. These results need to be validated in a large collaborative multicenter study. Further investigation is needed to assess the prognostic impact of severe hypoalbuminemia (<3g/dL) on axi-cel therapy. Disclosures Ansell: Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Affimed: Research Funding. Bennani:Seattle Genetics: Other: Advisory board; Kite Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Adicet Bio: Other: Advisory board; Seattle Genetics: Other: Advisory board; Purdue Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board. Paludo:Verily Life Sciences: Research Funding; Celgene: Research Funding; Verily Life Sciences: Research Funding; Celgene: Research Funding. Tun:DTRM Biopharma: Research Funding; Mundi-pharma: Research Funding; BMS: Research Funding; Celgene: Research Funding; Curis: Research Funding; TG Therapeutics: Research Funding. Foran:Agios: Honoraria, Research Funding. Kharfan-Dabaja:Daiichi Sankyo: Consultancy; Pharmacyclics: Consultancy.

Introduction: Globin gene sequencing has long been impeded by repetitive regions, homology and structural variation. Currently, long-read sequencing technology has been limited by high cost and error rate. These challenges can be mitigated by sample multiplexing of targeted capture sequencing and the use of consensus reads, respectively. This ongoing study analyzes the utility of long range sequencing technology in identifying historically problematic beta globin cluster mutations. Materials and methods: Long range sequencing was performed on complex beta globin gene cluster cases utilizing the Sequel platform (Pacific Biosciences, Menlo Park, California, United States). Sample input was 1 microgram of DNA extracted from whole blood. Circular Consensus Sequence (CCS) FASTQ sequences files were mapped to reference genome (GRCh37/hg19) using NGMLR, followed by annotation of variants using a custom bioinformatics workflow. Comparison to multiplex ligation-dependent probe amplification (MLPA), Sanger sequencing, array CGH, short-range NGS (300 bp), hemoglobin protein, and clinical data was performed. Results: CCS read length varied from 1 to 10 kb, average 3.5. Analysis of the beta globin cluster region showed impressive superiority and comprehensiveness to Sanger, MLPA, array CGH and short range sequencing technology: 1) single nucleotide variants (SNVs) were identified to a sensitivity and specificity of 99.5%; 2) large structural variants (SVs) such as large deletions, duplications, insertions, crossovers and fusions spanning many kilobases were characterized in the heterozygous, homozygous and compound heterozygous state to a precise genomic coordinate (table 1); 3) phasing SNVs identified Hb S haplotypes (Central African region (CAR), Benin, Senegal, Arab-Indian and Cameroon). Conclusion: 1) Long range sequencing holds significant promise in genotyping hemoglobin disorders. This method improves efficiency with potential for a single test offering with increased resolution, particularly in large deletion analysis. Complex cases greatly benefited from improved range and resolution. 2) The decreased requirement of blood volume for extensive testing is of particular interest for the pediatric population. 3) Genotyping of Hb S patients detected by positive newborn screening will help predict need for prophylaxis or therapy by assessing variant zygosity, phasing and haplotypes. In conclusion, we believe that long range sequencing has immense potential to contribute extensively to thalassemia and hemoglobinopathy diagnostics and is far superior to the currently available technologies for beta globin cluster analysis. Disclosures Jen: Celgene: Employment.

Purpose: B-cell acute lymphoblastic leukemia/lymphoma (B-ALL/LBL) represents the most common childhood malignancy. Classification of recurrent genetic abnormalities in B-ALL/LBL is essential for risk stratification and patient management. Observed in approximately 5% of B-ALL/LBL cases, hypodiploidy is considered a poor prognostic finding and can be further characterized as near-haploidy (24-31 chromosomes), low hypodiploidy (32-39 chromosomes) and high hypodiploidy (40-43 chromosomes). Importantly, masked hypodiploid clones that have undergone endoreduplication can be mischaracterized as hyperdiploidy, a favorable prognostic finding in B-ALL/LBL. These "doubled" hypodiploid clones are termed pseudo-hyperdiploid and their accurate detection is critical. Mate-pair sequencing (MPseq) is a next-generation sequencing (NGS) technology designed to sequence larger DNA fragments (2000-5000bp) than paired-end sequencing. This allows for the detection of large genetic rearrangements (e.g. translocations, inversions, etc.) and copy number variants (CNVs) at a high resolution with low base coverage. It has demonstrated particular clinical utility for genetic characterization of hematologic malignancies. To expand the role of MPseq in the evaluation of hematologic neoplasms, we aimed to improve the analysis of MPseq results to allow for the detection of copy-neutral loss of heterozygosity (cnLOH) that would enable the differentiation between hyperdiploid and pseudo-hyperdiploid clones. Methods: A new algorithm was applied that statistically analyzes common SNP locations in MPseq data in order to detect both cnLOH regions, and provides global heterozygosity levels at a resolution that allows for the detection of hypodiploidy. This method accounts for the low base-coverage of MPseq data (<10x) in order to provide the highest possible accuracy and precision without increasing cost by requiring changes to the input or sequencing requirements. The algorithm was applied to 17 B-ALL samples classified by conventional chromosome analysis, FISH, and/or chromosomal microarray as either pseudo-hyperdiploidy (n=8) or hyperdiploidy (n=9). The cases were sequenced using MPseq with 101bp read lengths across a range of base coverages (1-10x; 30-135 million fragments) and tumor percentages (50-100%). Results: We demonstrate the method's ability to differentiate between hyperdiploidy and pseudo-hyperdiploidy in all cases without any changes to the MPseq input or sequencing requirements. We detected an average of 11.5 whole-chromosome cnLOH (range 8-20) in the pseudo-hyperdiploidy cases, compared to an average of 0.67 whole-chromosome cnLOH (range 0-2) in the hyperdiploidy cases. Additionally, the method allows for the detection of cnLOH regions across the genome. For example, we observed a recurrent cnLOH of chromosome 9 in the hyperdiploid subtype (3/9 hyperdiploid cases), which is a recurrent abnormality in the disease. The method provides an easy to read visual output that compares favorably to the output of chromosomal microarray, increasing its utility for clinical application. Conclusions: This advancement in the analysis of low-coverage sequencing data makes MPseq available for the genetic characterization of B-ALL/LBL, where hypodiploidy is a primary cytogenetic abnormality and is sometimes missed by conventional cytogenetic techniques. Additionally, the algorithm allows for the detection of cnLOH regions across the genome, which is important across many disease types for diagnosis, prognosis, and the detection of potential therapeutic targets. The addition of the algorithm to the MPseq analysis pipeline makes it a more complete genetic characterization tool and brings it closer to its promise as a potential single assay replacement for conventional cytogenetic techniques. Disclosures No relevant conflicts of interest to declare.