Kathryn Driscoll

2020 UExB Student | Discher Lab

Katie Driscoll is a rising junior at Rowan University studying Biomedical Engineering with minors in Arabic, History, and Chemistry, and concentrations in the Honors College and Global Health. She (clearly) has a lot of interests and isn’t sure what she wants to do in the future but will likely be in school for a very long time. This summer she is very excited to be working on identifying scaling relationships of particular genes from cancer patients in the Discher Lab.


Research Abstract: 

Scaling Relationships and Patient Prognosis for COL1A1 and ACTA2 in Human Urinary Tract Cancers

Bulk mRNA-seq data obtained from The Cancer Genome Atlas (TCGA) can be used to elucidate gene expression and gene scaling relationships across cancers in order to identify common genes and groups of genes that predict significant survival changes in a cohort of patients. In this analysis, gene scaling relationships among two fibrosis-associated genes of interest (COL1A1 and ACTA2) and four urinary tract cancers were assessed for survival trends across data sets. Bladder cancer (BLCA), Kidney Chromophobe Cancer (KICH), Kidney Clear Cell Carcinoma (KIRC), and Kidney Papillary Cell Carcinoma (KIRP) were chosen for this analysis because they represent a common system and each cancer expressed gene scaling for each gene of interest. For COL1A1, a gene associated with fibrosis and positive survival trends in other cancers1, KIRC and KIRP showed significantly decreased survival of high expressors of the gene and none of the cohorts showed improved survival. Further, in ACTA2, a gene associated with cancer metastasis and fibrosis, only KIRP and BLCA showed significantly reduced survival with KICH indicating non-significant positive survival with high ACTA2 expression. A significant finding in this analysis is that COL5A1, COL6A3, and COL1A2 not only scaled with COL1A1 in all four cancers, but also predicted significantly poor survival with elevated expression in two of the four urinary cancers. These genes are associated with tumor growth and poor prognosis in both urinary cancers and cancers from other systems2,3,4,5. Furthermore, PLN and CNN1 scaled with ACTA2 across all four cancers and indicated negative survival in two of the four. CNN1 has been identified as a possible oncogene in bladder cancer related to poor survival outcomes and PLN has not been previously explored in the context of cancer prognosis6. Taken together, these genes have potential as targets for gene therapies and as prognostic biomarkers. Since many of these genes indicate fibrosis, emerging ultrasound technology could be used as a non-invasive detection tool for urinary cancers7.


  1. Vashisth, M., Cho, S., Irianto, J., Xia, Y., Wang M., Hayes B., Jafarpour, F., Wells, R., Liu, A., Discher, D. (2020). Scaling concepts in ‘omics: nuclear lamin-B scales with tumor growth and predicts poor prognosis, whereas fibrosis can be pro-survival [unpublished manuscript]. Physical Science Oncology Center at Penn, University of Pennsylvania.
  2. Di, Y., Chen, D., Yu, W., & Yan, L. (2019, 1 28). Bladder cancer stage-associated hub genes revealed by WGCNA co-expression network analysis. Hereditas, 156(1), 7.
  3. Kang, C., Wang, J., Axell-House, D., Soni, P., Chu, M.-L., Chipitsyna, G., . . . Arafat, H. (n.d.). 2013 SSAT PLENARY PRESENTATION Clinical Significance of Serum COL6A3 in Pancreatic Ductal Adenocarcinoma.
  4. Li, J., Ding, Y., & Li, A. (2016, 11 29). Identification of COL1A1 and COL1A2 as candidate prognostic factors in gastric cancer. World Journal of Surgical Oncology, 14(1), 297.
  5. Liu, W., Wei, H., Gao, Z., Chen, G., Liu, Y., Gao, X., . . . Xiao, J. (2018, 7 30). COL5A1 may contribute the metastasis of lung adenocarcinoma. Gene, 665, 57-66.
  6. Liu, Y., Wu, X., Wang, G., Hu, S., Zhang, Y., & Zhao, S. (2019, 1 1). CALD1, CNN1, and TAGLN identified as potential prognostic molecular markers of bladder cancer by bioinformatics analysis. Medicine, 98(2), e13847.
  7. Correas, J. M., Anglicheau, D., Joly, D., Gennisson, J. L., Tanter, M., & Hélénon, O. (2016). Ultrasound-based imaging methods of the kidney-recent developments. Kidney international, 90(6), 1199–1210. https://doi.org/10.1016/j.kint.2016.06.042
  8. Phillips, J., Pavlovich, C., Walther, M., Ried, T., & Linehan, W. (2001). The genetic basis of renal epithelial tumors: Advances in research and its impact on prognosis and therapy. Current Opinion in Urology, 11(5), 463-469.
  9. Takahashi, M., Rhodes, D., Furge, K., Kanayama, H., Kagawa, S., Haab, B., & Teh, B. (2001, 8 14). Gene expression profiling of clear cell renal cell carcinoma: Gene identification and prognostic classification. Proceedings of the National Academy of Sciences of the United States of America, 98(17), 9754-9759.