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Mechanisms by which acute myeloid leukemia (AML) interferes with normal hematopoiesis are under intense investigation. Emerging evidence suggests that exosomes produced by leukemia blasts suppress hematopoiesis. Exosomes isolated from AML patients' plasma at diagnosis significantly and dose-dependently suppressed colony formation of normal hematopoietic progenitor cells (HPC). Levels of HPC suppression mediated by exosomes of AML patients who achieved complete remission (CR) were significantly decreased compared to those observed at AML diagnosis. Exosomes from plasma of patients who had achieved CR but with incomplete cell count recovery (CRi) after chemotherapy suppressed in vitro colony formation as effectively as did exosomes obtained at AML diagnosis. Dipeptidylpeptidase4 (DPP4/CD26), a serine protease that cleaves select penultimate amino acids of various proteins, has been previously implicated in the regulation of hematopoiesis. DPP4 was carried by exosomes from AML plasma or leukemia cell lines. Leukemia exosomes which suppressed HSC colony formation had markedly higher DPP4 functional activity than that detected in the exosomes of normal donors. Pharmacological inhibition of DPP4 activity in AML exosomes reversed the effects of exosome-mediated myelosuppression. Reversing the negative effects of exosomes on AML hematopoiesis, and thus improving cell count recovery, might emerge as a new therapeutic approach to AML.

Introduction: Despite the availability of many effective agents, multiple myeloma is characterized by repeated cycles of treatment response and relapse, and remains incurable in almost all patients. Efforts to optimize treatment are complicated by variation in disease biology and by the combinatorial complexity inherent in assembling, sequencing and administering multi-agent regimens. Determining which strategies provide maximal therapeutic benefit requires deploying a variety of multi-agent regimens in a range of settings and assessing long-term outcomes; information that cannot be readily discerned from clinical trials. Here we present results from a real-world database that comprehensively tracks all treatments and responses in patients with multiple myeloma. Methods: Since March 2017, All4Cure has hosted an online platform for patients with multiple myeloma, clinicians and researchers that has been initially focused in the Pacific Northwest. Medical records from consenting patients are collected and information regarding all treatments and responses graphically displayed on their de-identified dashboards. A discussion panel allows for asynchronous communication between members of All4Cure's community of patients, clinicians and researchers (currently numbering over 1600 participants). There is no charge to patients who participate in All4Cure, and clinicians and researchers are neither charged nor paid for their participation. A summarized real-world database describes the lines of therapy that each patient has received, treatment start and stop dates, and responses in accordance with International Myeloma Working Group (IMWG) criteria. Results: The overall profile of patients with multiple myeloma enrolled in All4Cure (N=555) was benchmarked against myeloma patients from the National Program of Cancer Registries (NPCR) (diagnosis year 2017; N=25,895). Patients in all 50 States and D.C. were included in the comparison, and those with monoclonal gammopathy of undetermined significance (MGUS) were not considered. Myeloma patients enrolled in All4Cure are younger at diagnosis or start of treatment (median 61 versus between 65 and 69), more likely to be white (90.3% versus 73.5%), and more likely to reside in Washington State (41.2% versus 2%) compared to the NPCR cohort, reflecting participation influenced by geographic location as described above. After enrollment, All4Cure patients are followed longitudinally throughout the entirety of their disease course, with fewer than 2% having been lost to follow up. To gain insights uniquely available from the All4Cure database and to inform the future direction for our research, we focus our exploratory data analysis on the All4Cure cohort of patients who started treatment in June 2015 or later (N=299). Despite the relatively recent start of the All4Cure database, this timeframe allows up to 6 years of observation following the start of treatment, since the survival rates for the first 1-2 years of treatment are generally very high. Consistent with prior knowledge, increasing age and disease stage are associated with increased morality, as are high-risk cytogenetics such as 17p-, t(4:14) and t(14;16). We further explored the potential impact of early lines of therapy on long-term disease control. While the current literature is mixed on the merits of aggressive treatments in early lines of therapy in terms of overall survival, insights from our data suggest that more aggressive front-line therapies (such as SCT) are associated with improved disease control over time, although this is evolving with the impact of novel therapies and in particular the use of triplet and now quadruplet induction regimens and adapting treatment to achieve measurable residual disease (MRD) negativity. Conclusions: Even with the current limitations regarding the size and representativeness of All4Cure's database, these preliminary results support the validity of this approach for gaining insight into the treatments and outcomes of patients with multiple myeloma in real-world settings. Disclosures Blau: Oncopeptides: Other: Oncopeptides is an All4Cure customer. Blau: All4Cure: Current equity holder in publicly-traded company. Richter: Tisch Cancer Institute: Icahn School of Medicine at Mount Sinai: Current Employment; Janssen, Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Adaptive biotechnologies: Speakers Bureau; BMS, Karyopharm, Antengene: Membership on an entity's Board of Directors or advisory committees. Bensinger: BMS, Janssen, Poseida, Regeneron, Trillium: Research Funding; Amgen, BMS, Janssen, Sanofi: Speakers Bureau. Richardson: Secura Bio: Consultancy; Protocol Intelligence: Consultancy; Sanofi: Consultancy; Jazz Pharmaceuticals: Consultancy, Research Funding; AstraZeneca: Consultancy; Oncopeptides: Consultancy, Research Funding; AbbVie: Consultancy; GlaxoSmithKline: Consultancy; Regeneron: Consultancy; Janssen: Consultancy; Karyopharm: Consultancy, Research Funding; Celgene/BMS: Consultancy, Research Funding; Takeda: Consultancy, Research Funding. Anderson: Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Scientific Founder of Oncopep and C4 Therapeutics: Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Mana Therapeutics: Membership on an entity's Board of Directors or advisory committees.

Background: Here we describe an online network of patients with cancer, clinicians and researchers, layered on top of a comprehensive real world database of treatments and outcomes, continuously updated in near real time, and initially focused on multiple myeloma. Methods: Patients with multiple myeloma register at www.all4cure.com and sign HIPAA release forms to provide access to all of their medical records from all of the institutions from which they have received care. From the medical records, a structured dataset of treatments and lab results is extracted by a myeloma-dedicated team for display on each patient's de-identified, personalized dashboard. A discussion panel allows more than 1200 participating patients, clinicians and researchers to post comments or questions regarding each patient's specific circumstances. For each patient, lines of therapy and responses are determined according to IMWG and published criteria (Blood [2015] 126: 921-922). Here we report initial results from the treatments and responses among patients with multiple myeloma and plasma cell leukemia. Results: A total of 493 patients includes 26 with monoclonal gammopathy of undetermined significance (MGUS), 51 with smoldering myeloma, 408 with multiple myeloma, and 8 with primary plasma cell leukemia. Among patients with multiple myeloma, 42 (10.3%) had antecedent MGUS and/or smoldering myeloma. The average age is 65.6 (+/- 9.7). 50.9% are male and 49.1% are female. 42 states in the U.S. and 8 other countries are represented. Two patients with multiple myeloma had not started treatment by the time of this report. The remaining 414 patients with multiple myeloma or plasma cell leukemia received 1 to 16 lines of therapy. Among the 414 patients that received at least one line of therapy, a remarkable 89 distinct first line therapies were administered. The most common first line therapies were lenalidomide, bortezomib, dexamethasone (n=92), cyclophosphamide, bortezomib, dexamethasone (n=50), lenalidomide, bortezomib, dexamethasone + autologous stem cell transplant + lenalidomide maintenance (n=41), lenalidomide and dexamethasone (n=29), and bortezomib and dexamethasone (n=22). 62 patients received a first line therapy that was not received by any other patient in our database. This variation was attributable to participation in clinical trials, variation in the availability of drugs over time and different geographic locations, and the very large number of distinct combinations associated with multi-agent regimens. Seventy six percent of patients with multiple myeloma or plasma cell leukemia received a second line of therapy, 52% received a third line of therapy, 34% received a fourth line of therapy, 23% received a fifth line of therapy, and 18% received a sixth line of therapy. We observed a trend toward a decline in favorable responses with successive lines of therapy (Table 1) consistent with previous reports, with a correlation coefficient between the line of therapy and overall response rate of -0.74. Among the 76 patients who received 6 or more lines of therapy (247 lines of therapy in total), only 7 achieved stringent complete responses (sCRs), of which 5 were associated with a CAR-T therapy. Table 1 also shows a trend toward more rapid changes in treatment associated with later lines of therapy. 57 of 493 patients (12%) are deceased. Conclusions: Our findings reveal remarkable variation in the treatment of myeloma and provide a potentially valuable resource of up to date and current clinical features, prognosis, treatments, side effects, and outcomes of patients with myeloma in the real world. Table 1. Summary of lines of therapy and outcomes across 414 patients with multiple myeloma and plasma cell leukemia. The percentages of patients achieving sCR, ≥ PR (overall response rate - ORR), and ≥MR (clinical benefit rate - CBR) are shown for each line of therapy. Also depicted is the interval mortality and the mean and median number of days between the beginning of a line therapy and the beginning of the next line of therapy. Table Disclosures Richter: Janssen: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Sanofi: Consultancy; X4 pharmaceuticals: Consultancy; Oncopeptides: Consultancy; Adaptive biotechnologies: Consultancy; Secura bio: Consultancy; Astra Zeneca: Consultancy; BMS: Consultancy; Karyopharm: Consultancy; Antengene: Consultancy. Chhun:All4Cure: Current Employment. Zheng:All4Cure: Current Employment. Piboonvaranggoon:All4Cure: Current Employment. Mallick:All4Cure: Current Employment. Wren:All4Cure: Current Employment. Nam:All4Cure: Current Employment. Lopez Barquilla:All4Cure: Current equity holder in private company. Blau:All4Cure: Current equity holder in private company. Cowan:Janssen: Consultancy, Research Funding; Abbvie: Research Funding; Cellectar: Consultancy; Sanofi: Consultancy; Bristol Myers Squibb: Research Funding. Bensinger:BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria, Research Funding, Speakers Bureau; Regeneron: Consultancy, Honoraria, Research Funding, Speakers Bureau. Kumar:Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Genecentrix: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Merck: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Carsgen: Other, Research Funding; Dr. Reddy's Laboratories: Honoraria; Adaptive Biotechnologies: Consultancy; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; MedImmune: Research Funding; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; Cellectar: Other; Sanofi: Research Funding; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding. Richardson:Celgene/BMS, Oncopeptides, Takeda, Karyopharm: Research Funding. Anderson:Oncopep and C4 Therapeutics.: Other: Scientific Founder of Oncopep and C4 Therapeutics.; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees. Blau:All4Cure: Current Employment, Current equity holder in private company.

Vaccine therapy has been a widely explored immunotherapy modality in sarcoma. Ongoing studies continue to explore its future role in the therapeutic landscape of sarcoma. Many subtypes of sarcoma are ideal vaccine targets given their wide expression of immunogenic proteins and antigens, including cancer-testis antigen family (NY-ESO-1, MAGE-A3, PRAME, and LAGE-1), gangliosides (GM2, GD2, and GD3), and sarcoma-specific fusion proteins (SSX, FOXO1, EWSR1, and TLS CHOP). These sarcoma features and others, including tumor lysate and dendritic cells pulsed with antigen, have been exploited in various vaccine strategies. While vaccine therapy has induced some responses in sarcomas, further research will help to identify optimal treatment strategies in these patients and tailoring of immunotherapeutic approaches by sarcoma subtype and each unique biology.

Background The majority of invasive methicillin-resistant Staphylococcus aureus (MRSA) infections in the United States are community-onset and occur in persons with recent health care exposure. Methods We performed a matched case-control study to identify risk factors for invasive MRSA infection among recently discharged patients. Cases had MRSA cultured from a normally sterile body site within 100 days following hospital discharge. Controls were matched on hospital, week of admission, and age. Results Among 77 cases, the most common types of invasive MRSA infection were bloodstream infection and osteomyelitis. Independent risk factors were a history of a MRSA-positive clinical culture from a superficial body site in the 12 months preceding the invasive infection (matched odds ratio [mOR], 23; 95% confidence interval [CI]: 3.7-142), hemodialysis (mOR, 21; 95% CI: 1.7-257), prior hospitalization length of stay >5 days (mOR, 4.5; 95% CI: 1.6-12), and male sex (mOR, 2.9; 95% CI: 1.1-7.9). Conclusion Risk factors for postdischarge invasive MRSA infections can be identified prior to discharge and remain with the patient after the hospitalization ends. Measures to prevent community-onset invasive MRSA infections might start in the hospital but should also be evaluated in postdischarge settings.

Introduction: Treatment of patients with acute myeloid leukemia (AML) aims at achieving complete remission (CR) and restoration of normal bone marrow function. However, patients who achieve CR following induction chemotherapy often have incomplete count recovery (CRi< 100,000/μL platelets or Methods: Venous blood (20-50 mL) was obtained from 10 patients newly diagnosed with AML prior to therapy and at CR or CRi. Exosomes were isolated from plasma of AML patients and normal donors (n=5) by size exclusion chromatography. Protein levels, numbers and size (qNano), and exosome morphology (transmission electron microscopy) were determined. Exosome cargos were studied by Western blots for Leukemia Associated Antigens and for evidence of proteins involved in hematopoiesis, including dipeptidyllpeptidase-4 (DPP-4/CD26), a serine protease that enzymatically cleaves the proteins regulating hematopoiesis. Effects of exosomes on HPC proliferation and differentiation were evaluated in vitro by colony forming cell (CFC) assays. CFC assays were plated in triplicate. Total CFCs numbers ± exosomes (1-50 µg protein) were determined in the presence/absence of DPP-4 inhibitors. Results: Exosomes isolated from the plasma of AML patients at diagnosis carried Leukemia Associated Antigens, DPP-4, interleukin-3 receptor subunit alpha (CD123), erythropoietin receptor (EPO-R), tumor necrosis factor alpha (TNF-α), and transforming growth factor beta (TGF-β). Blast-derived exosomes at AML diagnosis suppressed the differentiation and proliferation of normal HPCs. The degree of inhibition was exosome dose-dependent. Pharmacologic inhibition of DPP-4 activity reversed suppression of CFC formation (p Conclusion: We report, for the first time, that exosomes in CRi patients inhibit normal human hematopoiesis in vitro. The data implicate AML blast-derived exosomes in suppression of normal hematopoiesis and suggest that in the future reversing the negative effects of exosomes and thus improving platelet and neutrophil counts, might emerge as a new therapeutic approach to AML. Disclosures No relevant conflicts of interest to declare.

Background: Mammographic density (MD) represents one of the strongest predictors of breast cancer risk. Tamoxifen, a selective estrogen receptor modulator (SERM) and proven chemopreventive agent, causes reductions in MD which correlate with subsequent breast cancer risk. Current methods for measuring MD, such as the Cumulus technique, are labor intensive and not fully automated, which limits utility in the clinical setting. Breast MRI is being used with increasing frequency in high-risk women for breast cancer screening and yields 3-dimensional views of breast volume. Breast MRI fibroglandular tissue volume (MRIV) has been correlated with MD in cross-sectional studies, but less is known about changes in breast density over time on MRI and its relation to breast cancer risk. One study reported a significant reduction in breast MRIV but not MD with the SERM, raloxifene, in high-risk women. We implemented a novel MRI segmentation method to measure MRIV compared to MD in 20 high-risk postmenopausal women that received high-dose vitamin D supplementation for 1 year. Methods: Twenty high-risk postmenopausal women [defined as a 5-year breast cancer risk per the Gail model of ≥1.67%, lobular or ductal carcinoma in situ (LCIS/DCIS)] were assigned to a 1-year intervention of vitamin D3 20,000 IU or 30,000 IU weekly. Other eligibility criteria included baseline MD ≥25% (as assessed qualitatively by BIRADS category) and no current SERM use. Women underwent a digital mammogram and breast MRI at baseline and 12 months. MD was evaluated by the Cumulus technique and MRIV was measured using a novel segmentation method on noncontrast T1-weighted images from breast MRIs. The method incorporated two well-established image analysis techniques, the region-based active contour model and watershed algorithm, into a unified framework. Specific anatomical landmarks were introduced into the algorithm to consistently identify breast boundaries on longitudinal MRI slices. For fibroglandular tissue segmentation, an algorithm combining region-based active contours and level-set approach was used to allow for easy initialization and fast speed. Correlation coefficients and paired t-tests were used to compare MD and MRIV and changes from baseline to 12 months. Results: From Nov 2007 to Jan 2011, 20 postmenopausal women were enrolled and 16 were evaluable at 12 months. Mean baseline breast density measurements were lower for MD compared to MRIV, 12.89% (SD 11.99) vs. 26.64% (SD 6.95), respectively. After 1 year of high-dose vitamin D, there was no significant change in MD or MRIV, mean absolute changes of -0.14% vs. -1.12%, respectively. We did not observe a significant correlation between MD and MRIV density measurements (correlation coefficient= -0.31, p=0.08). Discussion: We observed greater changes over time in breast density on serial breast MRI compared to mammography, however, no significant changes in MD or MRIV was noted after a 1-year intervention of vitamin D. Longer follow-up may be required in order to detect changes in breast density with non-hormonal interventions. Citation Format: Parijatham S Thomas, Mary Beth Terry, Xiaotao Guo, Binsheng Zhao, Richard Ha, Swathi Namburi, Tong Xiao, Dawn Hershman, Susan Refice, Katherine D Crew. Changes in breast density with mammography and breast MRI among high-risk postmenopausal women [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-01-08.

Bacteriophages are the most abundant forms of life in the biosphere and carry genomes characterized by high genetic diversity and mosaic architectures. The complete sequences of 30 mycobacteriophage genomes show them collectively to encode 101 tRNAs, three tmRNAs, and 3,357 proteins belonging to 1,536 “phamilies” of related sequences, and a statistical analysis predicts that these represent approximately 50% of the total number of phamilies in the mycobacteriophage population. These phamilies contain 2.19 proteins on average; more than half (774) of them contain just a single protein sequence. Only six phamilies have representatives in more than half of the 30 genomes, and only three—encoding tape-measure proteins, lysins, and minor tail proteins—are present in all 30 phages, although these phamilies are themselves highly modular, such that no single amino acid sequence element is present in all 30 mycobacteriophage genomes. Of the 1,536 phamilies, only 230 (15%) have amino acid sequence similarity to previously reported proteins, reflecting the enormous genetic diversity of the entire phage population. The abundance and diversity of phages, the simplicity of phage isolation, and the relatively small size of phage genomes support bacteriophage isolation and comparative genomic analysis as a highly suitable platform for discovery-based education., Synopsis Bacteriophages are viruses that infect bacterial hosts and are estimated to be the most numerous biological entities in the biosphere. Insights into the genetic diversity of the bacteriophage population and the evolutionary mechanisms that give rise to it can be obtained using comparative genomic analyses. The genomic analysis of 30 complete mycobacteriophages—viruses that infect mycobacterial hosts—reveals them to be genetically diverse and to contain many previously unidentified genes. The high diversity and relatively small genome sizes of these phages provide an ideal platform for introducing high school and undergraduate students to the research laboratory, isolating and naming novel viruses, and determining their genomic sequences. The thrill of discovering new viruses and previously unidentified genes, coupled with ownership of individual phage projects, provides strong motivations for students to engage in and pursue scientific research.

8103 Background: Monoclonal Gammopathy of Unknown Significance (MGUS) is characterized by the presence of a monoclonal immunoglobulin in the serum or the urine with no evidence of hematologic malignancy. A possible relationship between MGUS and increased incidence of NHM has been suggested in Caucasian populations. However, data in African Americans with MGUS are lacking. Methods: Non-MGUS controls were selected randomly from patients who did not have a paraprotein detected on electrophoresis (NMGUS) and were matched 2-to-1 to MGUS cases. Descriptive statistics and comparisons are presented to compare MGUS and NMGUS groups. Results: 492 male patients with MGUS patients were matched with 984 male NMGUS patients. 451 patients had abnormal serum protein studies (91.6%) and 40 had light chain disease (8.4%). Median age at diagnosis of MGUS was 68 years (28-81). 144 MGUS patients (29.2%) and 296 NMGUS patients (30%) had 1 or more NHM. The median age of diagnosis of 1st NHM was 70 (25-94) in the MGUS group and 68.4 in the NMGUS group (34.5-94.4). 19 MGUS patients (3.8%) and 27 NMGUS patients had 2 different types of NHM (2.7%). 1 MGUS patient (0.2%) and 3 NMGUS patients (0.3%) had 3 NHM. 57 patients had MGUS before NHM (11.5%) and 69 patients were diagnosed with MGUS after the diagnosis of NHM (14%), and median differences between diagnosis of MGUS and 1st NHM were 4 years (1-12 years) and 5 years (1-38 years) respectively. Types of NHM were comparable, and prostate cancer was the most prevalent NHM in both groups (15% of MGUS patients and 17% of NMGUS patients). Median time of follow up was 49.3 months for MGUS patients and 35.2 months for NMGUS patients 140 of the MGUS patients (28.4%) and 214 non-MGUS patients (21.75%) had died at data cut-off. Conclusions: Based on these observational data, prevalence and types of NHM appear to be comparable in MGUS and NMGUS African American patients. All cause mortality appears to be higher for NHM patients if they had MGUS. This pattern will need to be verified prospectively in a larger group of patients.