Breast Neoplasms; Medical Oncology; Genetic Heterogeneity; Molecular Diagnostic Techniques
Subset Medical Oncology Faculty
Dr. Hatzis continues to be involved in the design of biomarker validation clinical studies and development of strategies for translating genomic diagnostic assays to clinical practice. His current research interests focus on developing methods to characterize the genetic and molecular heterogeneity of breast cancer subtypes and the implications it might have on response and resistance to treatment. A key area of interest is to develop methodology that integrates genomic level information of individual patients to lead to more focused treatment decisions tailored for the individual tumor.
Speciailized Terms: Personalized medicine; Molecular diagnostics; Cancer heterogeneity; Next generation sequencing; Diagnostic study design
Extensive Research Description
Characterization of molecular and genetic heterogeneity in breast cancer and its association with treatment response or resistance.
Evaluation of high-throughput drug screens for triple negative breast cancer and assocation of sensitivity to genetic background.
Translation of microarray based prognostic tests to next generation platforms.
- Characterization of DNA variants in the human kinome in breast cancer Agarwal D, Qi Y, Jiang T, Liu J, Shi W, Wali VB, Turk B, Symmans WF, Pusztai L, Hatzis C. Scientific Reports 2015 5:14736
- Chemotherapy and Endocrine Therapy in High Risk Estrogen Receptor Positive Breast Cancers Kahn S, Karn T, Symmans WF, Rody A, Muller V, Holtrich U, Becker S, Pusztai L, Hatzis C. Breast Cancer Research and Treatment 2015 149(3):789-97.
- Statistical measures of transcriptional diversity capture genomic heterogeneity in cancer Jiang T, Shi W, Natowicz R, Ononye S, Wali VB, Kluger Y, Pusztai L, Hatzis C. BMC Genomics 2014 15:876.
- Enhancing reproducibility in cancer drug screening: how do we move forward? Hatzis C, Bedard P, Juul-Birkbak N, Beck A, Aerts H, Stern D, Shi L, Clarke R, Quackenbush J, Haibe-Kains B. Cancer Research 2014 74(15):4016-4023.
- Common contaminants in next-generation sequencing that hinder discovery of low-abundance microbes Laurence M, Hatzis C, Brash D. PLOS One 2014 16;9(5):e97876
- A genomic predictor of response and survival following taxane-anthracycline chemotherapy for invasive breast cancer Hatzis C, Pusztai L, Valero V et al. JAMA 2011 305(18): 1873-1881.
- Effects of tissue handling on RNA integrity and microarray measurements from resected breast cancers Hatzis C, Sun H, Yao H et al. J Natl Cancer Inst 2011 103(24): 1871-1883.
- Genomic index of sensitivity to endocrine therapy for breast cancer Symmans WF, Hatzis C, Sotiriou C et al. J Clin Oncol 2010 28(27): 4111-4119
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models Shi L, Campbell G, Jones WD et al. Nat Biotechnol 2010 28(8): 827-838.
- Measurement of Residual Breast Cancer Burden to Predict Survival After Neoadjuvant Chemotherapy Symmans WF, Peintinger F, Hatzis C et al. J Clin Oncol 2007 25:4414-4422.
- Large-scale identification of novel transcripts in the human genome Peters BA, St Croix B, Sjoblom T et al. Genome Res 2007 17(3): 287-292.