Genomic signatures, sometimes expressed as a weighted sum of genes, are an algebra over genes, such as "ESR1 + 0.5*ERBB2 - GRB7". Once a signature is entered, the value for each gene name for each sample are substituted and the algebraic expression is evaluated.
Open the Add column menu
Enter '=' and then your signature into the gene entry box
Select 'gene expression' as the dataset
Hess et.al. identified 30 genes whose gene expression profile is predictive of complete pathologic response to chemotherapy treatment in breast cancer.
=E2F3 + MELK + RRM2 + BTG3 - CTNND2 - GAMT - METRN - ERBB4 - ZNF552 - CA12 - KDM4B - NKAIN1 - SCUBE2 - KIAA1467 - MAPT - FLJ10916 - BECN1 - RAMP1 - GFRA1 - IGFBP4 - FGFR1OP - MDM2 - KIF3A - AMFR - MED13L - BBS4
Here we can see that the predicted chemo response signature is high in the basal subtype and low in luminal subtype. Additionally, the signature is high for ER negative samples and low for ER positive samples.
Hess KR, et. al. Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer. J Clin Oncol. 2006 Sep 10;24(26):4236-44. Epub 2006 Aug 8.
We also have a number of signature datasets under the TCGA Pan-Cancer study from the PanCan Atlas project:
To use these signatures, go to the dataset pages (links above) to see what the names of the specific signatures are (under Identifiers). Then in the visualization enter the name of the specific signature as a gene, click 'Advanced', choose the appropriate dataset, and click 'Done'