Computational software for cancer diagnosis and prognosis
- Summary
- Carcinomas are a subset of cancers that originate in epithelial tissues. They represent the majority of cancers worldwide including lung, ovarian, and esophageal cancers. These epithelial cancers are thought to become invasive and pass through an epithelial-to-mesenchymal cell transition, but the process is poorly understood creating significant hurdles for diagnosing, treating, and predicting the prognosis of a patient's cancer. This technology is computational software that can identify biomarkers characteristic of particular metastasis stages in an unbiased manner. It can be developed into a diagnostic tool to evaluate a patient's prognosis, monitor disease progression, predict drug responses, and suggest appropriate courses of treatment.
- Technology Benefits
- More accurate diagnosis and staging of cancerPatent Information:Patent Pending (WO/2011/130435)Tech Ventures Reference: IR 2734
- Technology Application
- Computational tool for identifying biomarkers in a range of disease states Computational tool for diagnosis and staging of cancerComputational tool for predicting cancer drug responseComputational tool for suggesting cancer treatmentResearch tool for the development of metastasis-inhibiting therapeutics
- Detailed Technology Description
- None
- *Abstract
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None
- *Inquiry
- Beth KaudererColumbia Technology VenturesTel: (212) 854-8444Email: TechTransfer@columbia.edu
- *IR
- 2734
- *Principal Investigator
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- *Publications
- Ou Yang TH, Cheng WY, Zheng T, Maurer MA, and Anastassiou D. "Breast cancer prognostic biomarker using attractor metagenes and the FGD3-SUSD3 metagene." Cancer Epidemiol Biomarkers Prev. 2014 Dec;23(12):2850-6. Cheng WY1, Kandel JJ, Yamashiro DJ, Canoll P, Anastassiou D. "A multi-cancer mesenchymal transition gene expression signature is associated with prolonged time to recurrence in glioblastoma." PLoS One. 2012 Apr 6;7(4):e34705.Kim H1, Watkinson J, Anastassiou D. "Biomarker discovery using statistically significant gene sets." J Comput Biol. 2011 Oct;18(10):1329-38.
- Country/Region
- USA

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