Compounds targeting transforming growth factor-β pathway genes

The Baird Institute’s public online Connectivity Map (CMAP) Build02 (Lamb et al., 2006) (https://portals.broadinstitute.org/cmap/) can predict compounds that activate or inhibit targets based on gene expression signatures, and we used this tool to explore which drugs may target TGF-β pathway genes. We further used the CmapTools to conduct a special analysis to explore the mechanism of action of the compound (https://clue.io/) (Subramanian et al., 2017). Similar to the GSEA analysis, CMAP uses the pattern-matching strategy of the Kolmogorov–Smirnov test to find the similarity between differentially expressed genes (DEGs). Then, we compared the results of the CMAP analysis to the DEG ranking list to determine the positive or negative regulatory relationship of genes and to generate enrichment scores (ES) from −1 to 1. Finally, we used the aforementioned scores to rank all the case data in the database. After we obtained two tables in each type of tumor, we applied the results of the connection map to the expression signatures of the TGF-β pathway and then used p < 0.05 as our inclusion criteria to determine the average meaningful compounds for each type of tumor.