About
- Development of novel Boolean implication networks to analyze patient DNA copy number variation and transcriptomic profiles and CRISPR-Cas9/RNAi screening data for prognosis and the selection of immunotherapy, chemotherapy, and radiotherapy, as well as repositioning drugs. The Boolean implication networks outperformed Bayesian networks, Pearson’s correlation networks, and other Boolean networks in constructing genome-scale co-expression networks evaluated with comprehensive biological pathways and Gene Ontology in MSigDB. The biomarkers identified from genome-scale microarray and RNA-sequencing data have been experimentally validated with qRT-PCR, Western Blots, ELISA, Immunohistochemistry, and AQUA assays of non-small cell lung cancer patient tumors and cell lines. The identified prognostic and predictive 7-gene qRT-PCR microfluidic assay (US and International Patents pending) was validated in patient cohorts collected from multiple US hospitals and a clinical trial JBR.10. The 7-gene assay could predict the risk for recurrence/metastasis and inform the selection of optimal chemotherapeutic regimens for non-small cell lung cancer patients. One of the biomarkers in the 7-gene assay, CD27, is an emerging cancer immunotherapy target. We are the first group to report that CD27 has concordant mRNA and protein expression in non-small cell lung cancer tumors with prognostic implications.
