Chengcheng Hu

Chengcheng Hu

Director, Biostatistics - Phoenix Campus
Professor, Public Health
Professor, Statistics-GIDP
Professor, BIO5 Institute
Primary Department
Department Affiliations
Contact
(520) 626-9308

Work Summary

Chengcheng Hu has worked on a broad range of areas including cancer, occupational health, HIV/AIDS, and aging. He has extensive collaborative research in conducting methodological research in the areas of survival analysis, longitudinal data, high-dimensional data, and measurement error. His current methodological interest, arising from studies of viral and human genetics and biomarkers, is to develop innovative methods to investigate the relationship between high-dimensional information and longitudinal outcomes or survival endpoints.

Research Interest

Chengcheng Hu, Ph.D., is an Associate Professor, Public Health and Director, Biostatistics, Phoenix campus at the Mel and Enid Zuckerman College of Public Health, University of Arizona. He is also Director of the Biometry Core on the Chemoprevention of Skin Cancer Project at the University of Arizona Cancer Center. Hu has worked on multiple federal grants in a broad range of areas including cancer, occupational health, HIV/AIDS, and aging. In addition to extensive experience in collaborative research, he has conducted methodological research in the areas of survival analysis, longitudinal data, high-dimensional data, and measurement error. His current methodological interest, arising from studies of viral and human genetics and biomarkers, is to develop innovative methods to investigate the relationship between high-dimensional information and longitudinal outcomes or survival endpoints. Hu joined the UA Mel and Enid Zuckerman College of Public Health in 2008. Prior to this he was an assistant professor of Biostatistics at the Harvard School of Public Health from 2002 to 2008. While at Harvard, he also served as senior statistician in the Pediatric AIDS Clinical Trials Group (PACTG) and the International Maternal Pediatric Adolescent AIDS Clinical Trials Group (IMPAACT). Hu received his Ph.D. and M.S. in Biostatistics from the University of Washington and a M.A. in Mathematics from the Johns Hopkins University.

Publications

Lacombe, J., Brooks, C., Hu, C., Menashi, E., Korn, R., Yang, F., & Zenhausern, F. (2017). Analysis of Saliva Gene Expression during Head and Neck Cancer Radiotherapy: A Pilot Study. Radiation research, 188(1), 75-81.

Saliva, a biological fluid, is a promising candidate for novel approaches to prognosis, clinical diagnosis, monitoring and management of patients with both oral and systemic diseases. However, to date, saliva has not been widely investigated as a biomarker for radiation exposure. Since white blood cells are also present in saliva, it should theoretically be possible to investigate the transcriptional biomarkers of radiation exposure classically studied in whole blood. Therefore, we collected whole blood and saliva samples from eight head and neck cancer patients before the start of radiation treatment, at mid-treatment and after treatment. We then used a panel of five genes: BAX, BBC3, CDKN1A, DDB2 and MDM2, designated for assessing radiation dose in whole blood to evaluate gene expression changes that can occur during radiotherapy. The results revealed that the expression of the five genes did not change in whole blood. However, in saliva, CDKN1A and DDB2 were significantly overexpressed at the end, compared to the start, of radiotherapy, and MDM2 was significantly underexpressed between mid-treatment and at the end of treatment. Interestingly, CDKN1A and DDB2 expressions also showed an increasing monotonic relationship with total radiation dose received during radiotherapy. To our knowledge, these results show for the first time the ability to detect gene expression changes in saliva after head and neck cancer radiotherapy, and pave the way for further promising studies validating saliva as a minimally invasive means of biofluid collection to directly measure radiation dose escalation during treatment.

Murphy, R. A., Bobrow, B. J., Spaite, D. W., Hu, C., McDannold, R., & Vadeboncoeur, T. F. (2016). Association between Prehospital CPR Quality and End-Tidal Carbon Dioxide Levels in Out-of-Hospital Cardiac Arrest. Prehospital emergency care : official journal of the National Association of EMS Physicians and the National Association of State EMS Directors, 20(3), 369-77.

International Guidelines recommend measurement of end-tidal carbon dioxide (EtCO2) to enhance cardiopulmonary resuscitation (CPR) quality and optimize blood flow during CPR. Numerous factors impact EtCO2 (e.g., ventilation, metabolism, cardiac output), yet few clinical studies have correlated CPR quality and EtCO2 during actual out-of-hospital cardiac arrest (OHCA) resuscitations. The purpose of this study was to describe the association between EtCO2 and CPR quality variables during OHCA.

Banerjee, B., Rial, N. S., Renkoski, T., Graves, L. R., Reid, S. A., Hu, C., Tsikitis, V. L., Nfonsom, V., Pugh, J., & Utzinger, U. (2013). Enhanced visibility of colonic neoplasms using formulaic ratio imaging of native fluorescence. Lasers in surgery and medicine, 45(9).

Colonoscopy is the preferred method for colon cancer screening, but can miss polyps and flat neoplasms with low color contrast. The objective was to develop a new autofluorescence method that improves image contrast of colonic neoplasms.

Bea, J. W., Wright, N. C., Thompson, P., Hu, C., Guerra, S., & Chen, Z. (2011). Performance evaluation of a multiplex assay for future use in biomarker discovery efforts to predict body composition. Clinical chemistry and laboratory medicine, 49(5), 817-24.

Interest in biomarker patterns and disease has led to the development of immunoassays that evaluate multiple analytes in parallel while using little sample. However, there are no current standards for multiplex configuration, validation, and quality. Thus, validation by platform, population, and question of interest is recommended. We sought to determine the best blood fraction for multiplex evaluation of circulating biomarkers in post-menopausal women, and to explore body composition phenotype discrimination by biomarkers.

Bea, J. W., Thomson, C. A., Wertheim, B. C., Nicholas, J. S., Ernst, K. C., Hu, C., Jackson, R. D., Cauley, J. A., Lewis, C. E., Caan, B., Roe, D. J., & Chen, Z. (2015). Risk of Mortality According to Body Mass Index and Body Composition Among Postmenopausal Women. AMERICAN JOURNAL OF EPIDEMIOLOGY, 182(7), 585-596.