Quantitative MRI features: Molecular Correlates

1. The lack of noninvasive predictive markers of therapy response is an unmet clinical need in the treatment of advanced kidney cancers. To address this, Dr. Udayakumar’s team utilizes pre-clinical patient-derived tumorgraft and cell line xenograft platforms to validate quantitative MRI measures as predictive and response biomarkers. This overcomes the limitations of tissue-based analysis from biopsies, which are often challenging in metastatic lesions, and can guide chemotherapy for better patient management. This project is facilitated through active collaboration between the Radiology MRI program and the SCCC Kidney Cancer Program.
2. Dr. Udayakumar and Pedrosa Lab have implemented a novel vertically-integrated radiogenomics platform to non-invasively decipher tumor heterogeneity in clear cell renal cell carcinoma (ccRCC). This project combines the analyses of in vivo phenotypes from quantitative MRI with histopathological and molecular assessment of spatially co-localized tumor areas in multi-region samples obtained from kidney cancer patients.
3. Dr. Udayakumar and Vinogradov Lab are evaluating next-generation quantitative MRI features such as chemical exchange saturation transfer (CEST) with correlations to histopathological findings and molecular and metabolic signatures as prognostic and predictive biomarkers in breast and kidney cancer patients .

Biomarkers for Bone Tropism in Metastatic Breast Cancers

Bone metastases profoundly affect Breast cancer patient’s quality of life due to skeletal related events. The early detection of breast cancers with high propensity to develop bone metastases will facilitate targeted adjuvant therapies, and vastly improve patient’s quality of life and survival outcome. Dr. Udayakumar in collaboration with Radiology Cyclotron and Radiochemistry program, is developing Immuno-PET based non-invasive molecular imaging biomarkers to predict the risk of bone metastases in breast cancer.