Ovarian carcinoma remains a leading cause of mortality from gynecologic cancer, with approximately 21,880 new cases and 13,850 deaths estimated in the United States in 2010. The standard treatment protocol for advanced-stage epithelial OvCa is cytoreductive surgery followed by platinum-based combination chemotherapy. However, the majority of patients eventually relapse with generally incurable disease, mainly due to the emergence of chemotherapy resistance. Early identification and differentiation of patients who are resistant to chemotherapy could lead to their enrollment in clinical trials with alternative therapeutics and is of utmost importance for improving the outcome of ovarian cancer. Understanding the molecular mechanisms for chemoresistance has been the subject of intense research. Various Regorafenib genomic methodologies have been applied to the study of OvCa to identify a gene signature associated with chemotherapy response. However, there is a lack of overlap between the discovered genes in different studies, possibly because of limited sample size in most studies. The Cancer Genome Atlas, a project of the National Cancer Institute and the National Human Genome Research Institute, generates a comprehensive catalog of genomic abnormalities with large-scale data sets that include cancers with the highest mortality rates including serous OvCa. In addition, the TCGA effort has led to the accumulation of a large set of tumor images in the repository. It is recognized that cell morphologies are intimately linked to multiple cell functions, such as cell growth, apoptosis, differentiation, and migration. Switches between different cell functions can be controlled by regulating cell shapes. It is reported that nuclear size is correlated with tumor prognosis in Stage III-IV ovarian cancer and is capable of distinguishing low- from high-grade serous OvCa. However, the molecular mechanism underlying this association remains unknown. The tumor image collections in TCGA provide the opportunity to systematically characterize the morphologic features associated with chemotherapy response and gene activity. In this study, we leverage the full scope of the TCGA database with a large population of patients, including gene expression and tumor images. Integration of the genomic and morphologic dimensions of OvCa will yield potential insights into mechanism of drug resistance and facilitate identification of novel system-level events for alternate therapeutic interventions. Several studies have described chemotherapy response in ovarian cancer using gene expression profiles, as summarized by Helleman et al. However, the number of ovarian cancer specimens used for the gene selection in those studies was relatively small, ranging from 6 to 119, and the corresponding gene sets discovered to be associated with platinum-based chemotherapy resistance exhibited a wide range of 14 to 1,727 genes where only seven genes were observed as an overlap and each between only two gene sets. Lack of overlap between the discovered gene sets is likely due to the limited sample size in most studies. However, ours is the first study performed on such a large scale, two genes in the 227-gene set, EPH receptor B3 and nuclear factor I/B, had been identified in one of the previous studies, and one gene, RNA binding protein 1, had been identified in a different study.