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AbstractBackgroundGene expression profiling is emerging as a tool for tuberculosis diagnosis and treatment response monitoring, but limited data specific to Indian children and incident tuberculosis infection (TBI) exist.MethodsSixteen pediatric Indian tuberculosis cases were age- and sex-matched to 32 tuberculosis-exposed controls (13 developed incident TBI without subsequent active tuberculosis). Longitudinal samples were collected for ribonucleic acid sequencing. Differential expression analysis generated gene lists that identify tuberculosis diagnosis and tuberculosis treatment response. Data were compared with published gene lists. Population-specific risk score thresholds were calculated.ResultsSeventy-one genes identified tuberculosis diagnosis and 25 treatment response. Within-group expression was partially explained by age, sex, and incident TBI. Transient changes in gene expression were identified after both infection and treatment. Application of 27 published gene lists to our data found variable performance for tuberculosis diagnosis (sensitivity 0.38–1.00, specificity 0.48–0.93) and treatment response (sensitivity 0.70–0.80, specificity 0.40–0.80). Our gene lists found similarly variable performance when applied to published datasets for diagnosis (sensitivity 0.56–0.85, specificity 0.50–0.85) and treatment response (sensitivity 0.49– 0.86, specificity 0.50–0.84).ConclusionsGene expression profiles among Indian children with confirmed tuberculosis were distinct from adult-derived gene lists, highlighting the importance of including distinct populations in differential gene expression models.

Abstract Background: NK/T cell non-Hodgkin lymphomas (NK/T NHL) are rare high-grade lymphomas that are diagnostically challenging and carry a poor prognosis. Incidence is notably higher in Asian countries as compared to North America and Europe. South Americans have an incidence similar to Asian countries though less well described. In this study we reviewed the incidence and outcomes of NK/T NHL in the US with a specific focus on patient race/ethnicity. Methods: Surveillance, Epidemiology and End Results (SEER) database was used to examine the standardized incidence rates (SIR) of NK/T cell NHL among adult (≥18 yrs) patients diagnosed between 1992-2013. Mutually exclusive race/ethnicity categories were: African-Americans (AA), Asians/Pacific Islanders (API), Hispanic whites (HW) and Non-Hispanic whites (NHW). Cases that received a diagnosis at death certificate/autopsy, no follow-up records, or lacking age at diagnosis, sex, or race/ethnicity documentation were excluded. Age adjusted incidence rates (AAIR) were calculated by race. Cox proportional hazards models, adjusted for confounding variables, were used to evaluate association between patient demographics and overall survival (OS). Results: A total of 706 cases met inclusion criteria. Of these, 64% were males and 36% females. AAIR was higher in males irrespective of race/ethnicity. Among different race/ethnic subgroups, API and HW had a higher AAIR than NHW and AA (0.2, 0.18, 0.05 and 0.04, respectively) (Figure 1). Median OS for males and females was similar (1.8 yr and 2 yr, respectively; p=0.76) There was a statistically significant difference in median OS by age for all patients with 4.3 yr for age 18-44 as compared with 0.8 yr for age >75 yr (p<0.001). Median OS by was different for HW (1.3 yr), API (1.8 yr), AA (2.3 yr) and HW (2.5 yr) but did not reach statistical significance (p=0.45). Median OS by stage varied as 7.3 yr for stage IE to 0.9 yr for all other stages combined (p<0.001) Cases with disease location as nasal cavity or sinus had a median OS of 3.5 yr as against 1.1 yr for those with all other sites (p<0.001) (Table 1). Conclusions: Significant disparities exist in the US for NK/T NHL incidence by race and gender, with highest AAIR among the racial minorities of API and HW, which are fastest and second fastest growing minority groups in the US respectively. Increasing age, advanced disease stage and site outside of the nasal cavity or sinus are independent predictors of poor prognosis. Some differences do exist in survival by race. These factors need to be considered for better resource allocation and utilization for this rare, often incurable and aggressive disease. Figure 1 Figure 1. Disclosures Ailawadhi: Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy. Kelly:Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau.

Host and Tumor Factor XII Drive Ovarian Cancer Maintenance and Progression Introduction . Epithelial ovarian cancer (EOC) is the leading cause of cancer death in women.Effective strategies to treat this disease are lacking due to the complexity of pathways involved and the multitude of cells that contribute to EOC biology. To this end, coagulation factor XII (FXII) and its receptor urokinase plasminogen activator receptor (uPAR) represent very promising therapeutic targets because i) uPAR is overexpressed in more than 90% of ovarian cancer patients, ii) FXII has been shown to be upregulated in the peritoneum of EOC patients and promotes EOC dissemination and iii) FXII-uPAR signal and upregulate key neutrophil functions, recently linked to tumor growth and metastasis. Through analysis of the TCGA ovarian cancer patient cohort, we have found that FXII and uPAR are co-expressed in ovarian tumors and their overexpression is associated with decreased overall survival (Fig 1A-B). Given that FXII and uPAR can be produced by both the EOC tumor and the host, the contribution of each of these compartments which has not been examined to date needs to be explored. Thus, we asked if the FXII-uPAR axis in neutrophils and EOC cells synergistically influences tumor biology. Methods - Results. We utilized a tissue microarray to determine FXII and uPAR expression. Both FXII and uPAR were co-expressed in all major histologic subtypes of EOC tumors but not in normal ovarian epithelium (Fig C-D). We adopted a composite expression score system and found significantly increased expression of FXII and uPAR in high grade tumors compared to low grade (grade 1-2) tumors, independently of tumor subtype and stage (Fig 1C-D). Given prior reports that neutrophils are enriched in the ovarian tumor microenvironment (TME) and our findings that FXII-uPAR are integral to neutrophil activation, tumors were also examined for their neutrophil content. Invariably, as tumor grade advanced, Neutrophil Elastase expression significantly increased (data not shown). We next asked if neutrophils contribute to EOC tumor progression or their recruitment merely correlates with advanced disease. We found that in the presence of neutrophils, EOC cells migrate significantly faster (p<0.0001). Since enhanced tumor cell migration implies a pro-mesenchymal phenotype, we examined if neutrophils facilitate EOC cell epithelial-to-mesenchymal transition (EMT). Murine EOC cancer cells (ID8) were co-cultured with wild type (WT) neutrophils for 24 h; cells were harvested and used for immunoblotting and mRNA studies. We found that WT neutrophils significantly increased the expression of mesenchymal marker(s) vimentin and N-cadherin while they decreased the expression of E-cadherin, suggesting that neutrophils promote EMT of EOC cancer cells (Fig 1E). To investigate whether the FXII-uPAR axis contributed to neutrophil-induced EMT, we next co-cultured ID8 cells with neutrophils from tumor-bearing FXII deleted (F12-/-)mice. In ID8 cells co-cultured with F12-/-neutrophils, EOC induced EMT was blocked. Similarly, treatment with 2 peptide inhibitors that block the FXII-uPAR interaction (collectively termed, SMPAs), reversed the pro-invasive effects of both ID8 cells and WT neutrophils (Fig 1F). Next, in order to assess whether host FXII could contribute to EOC dissemination and progression we utilized WT, F12-/-, and uPAR deficient (Plaur-/-) mice for in vivo EOC tumor model. After orthotopic injection of ID8 EOC cells, WT mice exhibited faster rates of tumor development and ascitic fluid accumulation (13.4 ± 0.92 ml), relative to F12-/- (0.37 ± 0.26 ml) and Plaur-/- (0.5 ± 0.5 ml) mice (Fig 1G). Blinded examination of tumors showed significantly higher tumor burden in WT mice compared to F12-/-and Plaur-/- mice, with F12-/-mice exhibiting the highest degree of protection (Fig 1H). Conclusions . Our studies indicate three novel aspects: i) a direct crosstalk between ovarian cancer cells and neutrophils, that enhances tumor cell migration through FXII-uPAR signaling; ii) the presence of neutrophils in the TME induces EMT of cancer cells which is abolished when the FXII-uPAR interaction is inhibited and; iii) abrogation of the FXII-uPAR axis in EOC tumor cells and neutrophils, synergistically restricts the pro-invasive phenotype of ovarian tumor cells. Disclosures No relevant conflicts of interest to declare.

Objective Volumetric laser endomicroscopy (VLE) is an advanced imaging modality used in Barrett’s oesophagus (BE) to help identify dysplasia in the oesophagus. VLE criteria exist for oesophageal dysplasia but not for dysplasia in the gastric cardia. The aim of this study was to determine if there are in vivo VLE features that can predict gastric cardia dysplasia in BE. Design This was a single-centre observational cohort study from August 2016 to August 2018. Patients were included if they had BE, were undergoing a VLE exam as standard of care, and had a suspicious target laser marked at the gastric cardia. The following VLE features were correlated to histology to determine if an association existed between histology subtype and VLE feature: wide crypts, irregular surface, one large isolated gland, multiple glands, and complex glands. Results A total of 110 in vivo gastric cardia targets in 77 patients with BE were analysed. The following abnormalities were identified: 61 wide crypts, 34 isolated glands, 16 irregular surfaces, 15 multiple glands, and 11 complex glands. Complex glands were the only VLE feature that correlated to any histology subtype. They were present in 71% of targets with high-grade dysplasia (HGD), T1a cancer or T1b cancer and had a sensitivity, specificity, and accuracy of 71%, 99%, and 85%, respectively. Of the 10 patients with complex glands on VLE and HGD/cancer on histology, 4 had a normal-appearing mucosa (40%) on endoscopy. Conclusion Identification of complex glands on VLE may aid in detection of HGD or early cancer in the gastric cardia in BE. This is particularly important, as dysplasia at the gastric cardia can be difficult to see endoscopically.

Abstract Introduction: Several prognostic models for overall survival (OS) in chronic lymphocytic leukemia (CLL) have been developed, but none were derived for patients (pts) with relapsed or refractory (R/R) CLL treated in the era of novel agents. We used a comprehensive approach to derive and validate a novel risk model for OS in 2,475 pts with R/R CLL who received therapy in randomized phase 3 trials evaluating ibrutinib (IBR), idelalisib (IDELA), and venetoclax (VEN) vs control arms, or the Mayo Clinic CLL Database (MCCD). Methods: In collaboration with Janssen, Gilead, Pharmacyclics, and Genentech/Roche, the analysis included 2,475 pts from 6 multicenter randomized phase 3 trials or the MCCD. Trials included were: IBR plus bendamustine-rituximab (BR) vs placebo plus BR (HELIOS: NCT01611090), IBR vs ofatumumab (RESONATE: NCT01578707), IDELA plus BR vs placebo plus BR (Study 115: NCT01569295); IDELA plus rituximab vs placebo plus rituximab (Study 116: NCT01539512); IDELA plus ofatumumab vs ofatumumab (Study 119: NCT01659021); VEN plus rituximab vs BR (MURANO: NCT02005471). All pts had R/R CLL and required treatment by iwCLL criteria. The model-building dataset (n=969) included pts from HELIOS and RESONATE, and was randomly assigned to the IBR/chemoimmunotherapy (CIT) training dataset (n=727) and IBR/CIT internal-validation dataset(n=242). Three independent external validation datasets included IDELA/CIT (n=897), VEN/CIT (n=389), and MCCD (n=220). We applied univariate and multivariate analyses (MVA) to 28 candidate clinical/laboratory and genetic prognostic factors to derive the risk model in the training dataset. The primary endpoint was OS. We assessed the need for separate models for targeted agents by interactions with treatment in univariate analyses. We proceeded to develop a single model for all pts with R/R CLL, as only one candidate factor (del(13q), interaction p value <0.1) demonstrated a marginal differential effect. We evaluated cutoffs for dichotomized covariates and for definition of risk groups after the final factors were selected. We fit a Cox regression on the training and internal/external validation datasets using the risk categories as the covariate to test the difference among the groups, and calculated the C-statistic as a measure of discrimination. Results: Of 11 selected factors with a significant univariate effect on OS (p<0.1), 6 were independently prognostic in the MVA of OS (p<0.05): Baseline β2-microglobubulin (B2M), lactate dehydrogenase (LDH), hemoglobin (HGB), IGHV mutational status, number of prior therapies, and time from initiation of last therapy. We excluded number of prior therapies from the model, reasoning that its optimal cutoff might change with advances in CLL therapies. IGHV did not remain significant (p=0.0592) in MVA of 5 remaining prognostic factors. Notably, del(17p) was not independently prognostic for OS. The final risk model consisted of 4 prognostic factors: B2M ≥5 mg/L, LDH elevated, HGB <110 mg/L for women or <120 mg/L for men, and time from initiation of last therapy <24 months. Because hazard ratios for each factor were similar (range, 0.55-0.68) with overlapping confidence intervals, 1 point was assigned to each factor. The resulting score separated pts into low (score 0-1), intermediate (score 2-3), and high risk (score 4) groups. Our risk model was prognostic for OS in the IBR/CIT training dataset (C-statistic 0.74 [95% CI 0.60-0.85]; log-rank p<0.0001) and was validated in the IBR/CIT internal validation (C-statistic 0.79 [95% CI 0.56-0.97]; log-rank p<0.0001), as well as in all 3 external validations: IDELA/CIT dataset (CS=0.71, 95% CI 0.59-0.81; log-rank p<0.001); VEN/CIT dataset (CS=0.76, 95% CI 0.66-0.85; log-rank p=0.01); MCCD (CS=0.61, 95% CI 0.56-0.66; log-rank p<0.001). Conclusions: We present the first validated risk model for OS in R/R CLL in the era of targeted therapies. Our model consists of 4 readily available factors (B2M ≥5 mg/L, LDH elevated, HGB <110 mg/L for women or <120 mg/L for men, and time from initiation of last therapy <24 months), identifies 3 prognostic groups with significantly different OS, and has been validated for pts treated with all FDA approved targeted therapies: IBR, IDELA, and VEN. This identifies a well-defined cohort of pts with R/R disease with an unmet clinical need who are suitable for prospective trials targeting these pts. An exploratory analysis regarding prediction of MRD is ongoing. Figure. Figure. Disclosures Darif: Jannsen: Employment. Londhe:Jannsen: Employment. Xing:Gilead Sciences, Inc.: Employment. Mun:Genentech: Employment, Equity Ownership. Kay:Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees. Shanafelt:Mayo Clinic: Patents & Royalties: Physician Well-being Index, Medical Student Well-being Index, Well-being index; GlaxoSmithKline: Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Janssen: Research Funding; Abbvie: Research Funding; Celgene: Research Funding. Furman:Loxo Oncology: Consultancy; Pharmacyclics LLC, an AbbVie Company: Consultancy; Sunesis: Consultancy; TG Therapeutics: Consultancy; Verastem: Consultancy; Gilead: Consultancy; Incyte: Consultancy, Other: DSMB; Acerta: Consultancy, Research Funding; Genentech: Consultancy; Janssen: Consultancy; AbbVie: Consultancy. Hillmen:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Pharmacyclics: Research Funding; Alexion Pharmaceuticals, Inc: Consultancy, Honoraria; Novartis: Research Funding; Gilead Sciences, Inc.: Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Acerta: Membership on an entity's Board of Directors or advisory committees. Sharman:Acerta: Consultancy, Research Funding; Pharmacyclics, an AbbVie Company: Consultancy, Research Funding. Seymour:AbbVie: Consultancy, Honoraria, Research Funding; Celgene: Consultancy; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Genentech Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding. Jones:Celgene: Employment, Equity Ownership. Ferrante:Jannsen: Employment. Dreiling:Gilead: Employment. Mobasher:F. Hoffmann-La Roche Ltd: Other: Ownership interests non-PLC; Genentech Inc: Employment. Stark:Genentech: Employment. Reddy:Actinium Pharmaceuticals: Employment, Equity Ownership; Pharmacyclics: Employment. Howes:Janssen: Employment. James:Pharmacyclics: Employment. Bhargava:Gilead: Employment. Zelenetz:Novartis/Sandoz: Consultancy; Abbvie: Research Funding; Celgene: Consultancy; Amgen: Consultancy; Gilead: Consultancy, Research Funding; AstraZeneca: Consultancy; Genentech/Roche: Consultancy, Research Funding.

This prospective cohort study aimed to improve hospital outcomes through geographic location of hospitalist patients and conducting daily multidisciplinary team rounds—Goal-directed Achievements through Geographic Location (GAGL). Patients were admitted to a geographic (GAGL) study unit where daily multidisciplinary rounds took place among nursing, case management, a hospitalist, pharmacy, physical and occupational therapy, respiratory therapy, and nutrition services. A total of 985 (56.4%) patients were admitted to the GAGL study unit and 760 patients (43.6%) were admitted to non-GAGL units. Patients admitted to the GAGL study unit had a shorter average length of stay (3.64 days vs 4.35 days, P = .0001) and a lower number of risk events (91 [9.2%] vs 93 [12.2%], P = .038). There was no significant difference in 30-day readmissions, avoidable day events, or code blue team activations. GAGL provides a framework for hospital organizations to improve provider communication, hospital efficiency, and patient safety.