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.
- Kahn S, Karn T, Symmans WF, Rody A, Muller V, Holtrich U, Becker S, Pusztai L, Hatzis C (2015). "Genomic Predictor of Residual Risk of Recurrence after Adjuvant Chemotherapy and Endocrine Therapy in High Risk Estrogen Receptor Positive Breast Cancers". Breast Cancer Research and Treatment 149(3):789-97.
- Jiang T, Shi W, Natowicz R, Ononye S, Wali VB, Kluger Y, Pusztai L, Hatzis C (2014). "Statistical measures of transcriptional diversity capture genomic heterogeneity in cancer". BMC Genomics 15:876.
- Hatzis C, Bedard P, Juul-Birkbak N, Beck A, Aerts H, Stern D, Shi L, Clarke R, Quackenbush J, Haibe-Kains B. (2014) "Enhancing reproducibility in cancer drug screening: how do we move forward?" Cancer Research 74(15):4016-4023.
- Laurence M, Hatzis C, Brash D (2014). "Common contaminants in next-generation sequencing that hinder discovery of low-abundance microbes". PLOS One 16;9(5):e97876
- Hatzis C, Pusztai L, Valero V et al. (2011). "A genomic predictor of response and survival following taxane-anthracycline chemotherapy for invasive breast cancer." Journal of the American Medical Association 305(18): 1873-1881.
- Hatzis C, Sun H, Yao H et al. (2011). "Effects of tissue handling on RNA integrity and microarray measurements from resected breast cancers." J Natl Cancer Inst 103(24): 1871-1883.
- Symmans WF, Hatzis C, Sotiriou C et al. (2010). "Genomic index of sensitivity to endocrine therapy for breast cancer." J Clin Oncol 28(27): 4111-4119
- Shi L, Campbell G, Jones WD et al. (2010). "The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models." Nat Biotechnol 28(8): 827-838.
- Symmans WF, Peintinger F, Hatzis C et al. (2007). "Measurement of Residual Breast Cancer Burden to Predict Survival After Neoadjuvant Chemotherapy." J Clin Oncol 25:4414-4422.
- Peters BA, St Croix B, Sjoblom T et al. (2007). "Large-scale identification of novel transcripts in the human genome." Genome Res 17(3): 287-292.