Dr. Eng is a cancer geneticist and statistician with broad expertise in immunology, genetics, epidemiology and informatics. His research group combines a traditional bench laboratory and a computational group to execute translational studies in ovarian and prostate cancers. Dr. Eng earned his PhD and MS from the University of Wisconsin-Madison and ScB from Brown University. Dr. Eng studied statistical genomics, bioinformatics and ovarian cancer during his postdoctoral training at Wisconsin. Combining genomics, informatics and immunology, Dr. Eng has recently received an NIH career award (K award) developed through awards from the ovarian cancer SPORE and the Roswell Park Alliance Foundation.
We are a data science group and research laboratory that plans, coordinates, manages and analyzes studies across all areas of ovarian cancer research. Most of our work focuses on basic, translational and clinical studies at the intersection of genomics, informatics and immunotherapy for ovarian cancer.
- Daudi S, Eng KH, Mhawech-Fauceglia P, Morrison C, Miliotto A, Beck A, Matsuzaki J, Tsuji T, Groman A, Gnjatic S, Spagnoli G, Lele S, Odunsi K. Expression and immune responses to MAGE antigens predict survival in epithelial ovarian cancer. PloS one. 2014; 9(8):e104099. PMID: 25101620, PMCID: PMC4125181
- Eng KH, Tsuji T. Differential antigen expression profile predicts immunoreactive subset of advanced ovarian cancers. PloS one. 2014; 9(11):e111586. PMID: 25380171.
- Eng KH, Seagle BL. Covariate-Adjusted Restricted Mean Survival Times and Curves. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2017; 35(4):465-466. PMID: 28129530
RPCI Ovarian Cancer Study. We manage an ongoing study of over 1,400 women treated for ovarian cancer at RPCI using modern EHR based data abstraction. We often collaborate with residents and fellows to explore new ideas and test their hypotheses.
* Eng KH, Morrell K, Starbuck K, Spring-Robinson C, Khan A, Cleason D, Akman L, Zsiros E, Odunsi K, Szender JB. Prognostic value of miliary versus non-miliary sub-staging in advanced ovarian cancer. Gynecol Oncol. 2017 May 8. pii: S0090-8258(17)30844-2. PMID: 28495239.
* Szender JB, Papanicolau-Sengos A, Eng KH, Miliotto AJ, Lugade AA, Gnjatic S, Matsuzaki J, Morrison CD, Odunsi K. NY-ESO-1 expression predicts an aggressive phenotype of ovarian cancer. Gynecologic oncology. 2017; 145(3):420-425. PMID: 28392127
* Eng KH, Hanlon BM, Bradley WH, Szender JB. Prognostic factors modifying the treatment-free interval in recurrent ovarian cancer. Gynecologic oncology. 2015; 139(2):228-35. PMID: 26383827.
Familial Ovarian Cancer Registry. We assist in data management and research in this ongoing study of over 50,000 people, 5,600 ovarian cancers, 2,700 families tackling the genetic origins of hereditary ovarian cancer and studying the environmental and genetic effect that may alter predisposition to ovarian and other cancers in these families. Full publication list https://www.ncbi.nlm.nih.gov/myncbi/browse/collection/47265594/?sort=dat...
- Daudi, S., Eng, K.H., Mhawech-Fauceglia, P., Morrison, C., Miliotto, A., Beck, A., Matsuzaki, J., Tsuji, T., Groman, A., Gnjatic, S., Spagnoli, G., Lele, S. & Odunsi, K. Expression and immune responses to MAGE antigens predict survival in epithelial ovarian cancer. PLoS ONE 2014; 9(8):e104099. PMCID: PMC4125181
- Eng, K.H. & Tsuji, T. Differential antigen expression profile predicts immunoreactive subset of advanced ovarian cancers. PLoS ONE 2014; 9(11):e111586. PMCID: PMC4224408
- Eng, K.H. & Ruggeri, C. Connecting prognostic ligand receptor signaling loops in advanced ovarian cancer. PLoS ONE 2014; 9(9):e107193. PMCID: PMC4171104
- Eng, K.H. Randomized reverse marker strategy design for prospective biomarker validation. Statistics in Medicine 2014; 33(18):3089-3099. PMCID: PMC4107176
- Eng, K.H., Wang, S., Bradley, W.H., Rader, J.S. & Kendziorski, C. Pathway index models for construction of patient-specific risk profiles. Statistics in Medicine 2013; 32(9):1524-1535. PMCID: PMC3593986