This BRP application aims to establish a highly collaborative and multidisciplinary cancer nanotechnology program by integrating the bioengineering strengths of Georgia Tech (Atlanta, GA), the spectral imaging expertise of CSRI (Woburn, MA), and the cancer biology and clinical oncology experiences of Emory University School of Medicine (Urology, Pathology, Radiation Oncology, Winship Cancer Institute, and the VA Hospital, Atlanta, GA). With faculty participation from eight science, engineering, and clinical departments, and advised by a prominent Scientific Advisory Board (SAB), this Partnership incorporates broad expertise in bioengineering, bioinformatics, tumor biology, bioanalytical chemistry, systems biology, hematology / oncology, pathology, and urology. Its broad and long-term goal is to develop biomedical nanotechnology, biomolecular engineering, and bioinformatics tools for linking molecular signatures (biomarkers) of cancer and the host microenvironment with cancer behavior and clinical outcome. The proposed research is broadly applicable to many types of malignant tumors such as breast cancer, colorectal carcinoma, and lymphoma, but a particular focus will be placed on the biological behavior of human prostate cancer and its clinically lethal phenotypes. A compelling reason for this focus is that prostate cancer presents a number of unique challenges and opportunities in human oncology. Its widespread occurrence (about 220,000 new cases this year in the US), tendency for a long natural history, highly heterogeneous and multi-focal histopathology, and progression to hormone independence are still poorly understood. Faced with this reality, we propose to develop advanced nanoparticle technologies (e.g., molecular beacons, semiconductor quantum dots, and enhanced Raman probes) for ultrasensitive and multiplexed profiling of biomarkers on intact cancer cells or tissue specimens. In contrast to current molecular-profiling technologies, the use of encoded nanoparticle probes allows a seamless integration of traditional pathology and cancer biology with sensitive molecular analysis, a central theme that runs across the entire proposed research. Underlying this BRP is a strong track record of the senior investigators who have worked together successfully in attracting joint research grants. In addition, the Department of Biomedical Engineering, which was jointly established in 1997 by Georgia Tech and Emory University, has presented an unusual opportunity for research collaboration to bring bioengineering technologies and discoveries into medicine and vice versa. If funded, this cancer nanotechnology program will be housed in the Winship Cancer Institute, a new 280,000 sq ft cancer research and care building located on the Emory Campus and with a truly outstanding environment for collaborative and translational cancer research. In additional to basic knowledge on cancer biology and biomarkers, this Partnership is expected to yield at least three practical outcomes: (a) a database linking molecular signatures with cancer biology and clinical outcome, (b) bioconjugated nanoparticles for molecular profiling of cancer, and (c) muiltiplexed spectral imaging microscopes and software.
| Mishra, Sameer; Kaddi, Chanchala D; Wang, May D (2016) Pan-cancer analysis for studying cancer stage using protein and gene expression data. Conf Proc IEEE Eng Med Biol Soc 2016:2440-2443 |
| Kaddi, Chanchala D; Bennett, Rachel V; Paine, Martin R L et al. (2016) DetectTLC: Automated Reaction Mixture Screening Utilizing Quantitative Mass Spectrometry Image Features. J Am Soc Mass Spectrom 27:359-65 |
| Mishra, Sameer; Kaddi, Chanchala D; Wang, May D (2015) Pan-cancer analysis for studying cancer stage using protein expression data. Conf Proc IEEE Eng Med Biol Soc 2015:8189-92 |
| Zarkogianni, Konstantia; Litsa, Eleni; Mitsis, Konstantinos et al. (2015) A Review of Emerging Technologies for the Management of Diabetes Mellitus. IEEE Trans Biomed Eng 62:2735-49 |
| Kaddi, Chanchala D; Wang, May D (2014) Models for predicting stage in head and neck squamous cell carcinoma using proteomic data. Conf Proc IEEE Eng Med Biol Soc 2014:5216-9 |
| Sarkari, Sanaiya; Kaddi, Chanchala D; Bennett, Rachel V et al. (2014) Comparison of clustering pipelines for the analysis of mass spectrometry imaging data. Conf Proc IEEE Eng Med Biol Soc 2014:4771-4 |
| Kaddi, Chanchala D; Parry, R Mitchell; Wang, May D (2013) Multivariate hypergeometric similarity measure. IEEE/ACM Trans Comput Biol Bioinform 10:1505-16 |
| Wang, May Dongmei (2013) In the spotlight: Bioinformatics. IEEE Rev Biomed Eng 6:3-8 |
| Phan, John H; Young, Andrew N; Wang, May D (2013) omniBiomarker: A Web-Based Application for Knowledge-Driven Biomarker Identification. IEEE Trans Biomed Eng 60:3364-7 |
| Parry, R Mitchell; Wang, May D (2013) A fast least-squares algorithm for population inference. BMC Bioinformatics 14:28 |
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