Browsing by Author "Yang, Lili"

Now showing 1 - 5 of 5
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    IND-Enabling Studies for a Clinical Trial to Genetically Program a Persistent Cancer-Targeted Immune System
    (American Association for Cancer Research, 2019-02-01) Puig-Saus, Cristina; Parisi, Giulia; Garcia-Diaz, Angel; Krystofinski, Paige E.; Sandoval, Salemiz; Zhang, Ruixue; Champhekar, Ameya S.; McCabe, James; Cheung-Lau, Gardenia C.; Truong, Nhat A.; Vega-Crespo, Agustin; Komenan, Marie Desiles S.; Pang, Jia; Macabali, Mignonette H.; Saco, Justin D.; Goodwin, Jeffrey L.; Bolon, Brad; Seet, Christopher S.; Montel-Hagen, Amelie; Crooks, Gay M.; Hollis, Roger P.; Campo-Fernandez, Beatriz; Bischof, Daniela; Cornetta, Kenneth; Gschweng, Eric H.; Adelson, Celia; Nguyen, Alexander; Yang, Lili; Witte, Owen N.; Baltimore, David; Comin-Anduix, Begonya; Kohn, Donald B.; Wang, Xiaoyan; Cabrera, Paula; Kaplan-Lefko, Paula J.; Berent-Maoz, Beata; Ribas, Antoni; Medical and Molecular Genetics, School of Medicine
    PURPOSE: To improve persistence of adoptively transferred T-cell receptor (TCR)-engineered T cells and durable clinical responses, we designed a clinical trial to transplant genetically-modified hematopoietic stem cells (HSCs) together with adoptive cell transfer of T cells both engineered to express an NY-ESO-1 TCR. Here, we report the preclinical studies performed to enable an investigational new drug (IND) application. EXPERIMENTAL DESIGN: HSCs transduced with a lentiviral vector expressing NY-ESO-1 TCR and the PET reporter/suicide gene HSV1-sr39TK and T cells transduced with a retroviral vector expressing NY-ESO-1 TCR were coadministered to myelodepleted HLA-A2/Kb mice within a formal Good Laboratory Practice (GLP)-compliant study to demonstrate safety, persistence, and HSC differentiation into all blood lineages. Non-GLP experiments included assessment of transgene immunogenicity and in vitro viral insertion safety studies. Furthermore, Good Manufacturing Practice (GMP)-compliant cell production qualification runs were performed to establish the manufacturing protocols for clinical use. RESULTS: TCR genetically modified and ex vivo-cultured HSCs differentiated into all blood subsets in vivo after HSC transplantation, and coadministration of TCR-transduced T cells did not result in increased toxicity. The expression of NY-ESO-1 TCR and sr39TK transgenes did not have a detrimental effect on gene-modified HSC's differentiation to all blood cell lineages. There was no evidence of genotoxicity induced by the lentiviral vector. GMP batches of clinical-grade transgenic cells produced during qualification runs had adequate stability and functionality. CONCLUSIONS: Coadministration of HSCs and T cells expressing an NY-ESO-1 TCR is safe in preclinical models. The results presented in this article led to the FDA approval of IND 17471.
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    Joint models for longitudinal and survival data
    (2014-07-11) Yang, Lili; Gao, Sujuan; Yu, Menggang; Tu, Wanzhu; Callahan, Christopher M.; Zollinger, Terrell
    Epidemiologic and clinical studies routinely collect longitudinal measures of multiple outcomes. These longitudinal outcomes can be used to establish the temporal order of relevant biological processes and their association with the onset of clinical symptoms. In the first part of this thesis, we proposed to use bivariate change point models for two longitudinal outcomes with a focus on estimating the correlation between the two change points. We adopted a Bayesian approach for parameter estimation and inference. In the second part, we considered the situation when time-to-event outcome is also collected along with multiple longitudinal biomarkers measured until the occurrence of the event or censoring. Joint models for longitudinal and time-to-event data can be used to estimate the association between the characteristics of the longitudinal measures over time and survival time. We developed a maximum-likelihood method to joint model multiple longitudinal biomarkers and a time-to-event outcome. In addition, we focused on predicting conditional survival probabilities and evaluating the predictive accuracy of multiple longitudinal biomarkers in the joint modeling framework. We assessed the performance of the proposed methods in simulation studies and applied the new methods to data sets from two cohort studies.
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    Joint Models for Multiple Longitudinal Processes and Time-to-event Outcome
    (Taylor & Francis, 2016) Yang, Lili; Yu, Menggang; Gao, Sujuan; Department of Biostatistics, Richard M. Fairbanks School of Public Health
    Joint models are statistical tools for estimating the association between time-to-event and longitudinal outcomes. One challenge to the application of joint models is its computational complexity. Common estimation methods for joint models include a two-stage method, Bayesian and maximum-likelihood methods. In this work, we consider joint models of a time-to-event outcome and multiple longitudinal processes and develop a maximum-likelihood estimation method using the expectation–maximization algorithm. We assess the performance of the proposed method via simulations and apply the methodology to a data set to determine the association between longitudinal systolic and diastolic blood pressure measures and time to coronary artery disease.
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    Prediction of Coronary Artery Disease Risk Based on Multiple Longitudinal Biomarkers
    (Wiley, 2016-04) Yang, Lili; Yu, Menggang; Gao, Sujuan; Department of Biostatistics, Richard M. Fairbanks School of Public Health
    In the last decade, few topics in the area of cardiovascular disease (CVD) research have received as much attention as risk prediction. One of the well-documented risk factors for CVD is high blood pressure (BP). Traditional CVD risk prediction models consider BP levels measured at a single time and such models form the basis for current clinical guidelines for CVD prevention. However, in clinical practice, BP levels are often observed and recorded in a longitudinal fashion. Information on BP trajectories can be powerful predictors for CVD events. We consider joint modeling of time to coronary artery disease and individual longitudinal measures of systolic and diastolic BPs in a primary care cohort with up to 20 years of follow-up. We applied novel prediction metrics to assess the predictive performance of joint models. Predictive performances of proposed joint models and other models were assessed via simulations and illustrated using the primary care cohort.
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    The relationship between cholesterol and cognitive function is homocysteine-dependent
    (Dove Press Ltd, 2014-10-23) Cheng, Yibin; Jin, Yinlong; Unverzagt, Frederick W.; Su, Liqin; Yang, Lili; Ma, Feng; Hake, Ann M.; Kettler, Carla; Chen, Chen; Liu, Jingyi; Bian, Jianchao; Li, Ping; Murrell, Jill R.; Hendrie, Hugh C.; Gao, Sujuan; Department of Biostatistics, School of Medicine
    Introduction Previous studies have identified hyperlipidemia as a potential risk factor for dementia and Alzheimer’s disease. However, studies on cholesterol measured in late-life and cognitive function have been inconsistent. Few studies have explored nonlinear relationships or considered interactions with other biomarker measures. Methods A cross-sectional sample of 1,889 participants from four rural counties in the People’s Republic of China was included in this analysis. Serum total cholesterol, high-density lipoprotein, triglycerides, and homocysteine levels were measured in fasting blood samples. A composite cognitive score was derived based on nine standardized cognitive test scores. Analysis of covariance models were used to investigate the association between biomarker measures and the composite cognitive scores. Results There was a significant interaction between the homocysteine quartile group and the cholesterol quartile group on cognitive scores (P=0.0478). In participants with normal homocysteine levels, an inverse U-shaped relationship between total cholesterol level and cognitive score was found, indicating that both low and high cholesterol levels were associated with lower cognitive scores. In participants with high homocysteine levels, no significant association between cholesterol and cognition was found. Conclusion The relationship between cholesterol levels and cognitive function depends upon homocysteine levels, suggesting an interactive role between cholesterol and homocysteine on cognitive function in the elderly population. Additional research is required to confirm our findings in other populations, and to explore potential mechanisms underlying the lipid–homocysteine interaction.