Using expression data from less than 100 specific genes of SFRP2+ fibroblast as input, the model can effectively identify whether a patient harbors a TP53 mutation, indicating the significance of tumor-associated fibroblast signature for deep learning and precision oncology. This evidence concerns the gene SFRP2 and neoplasm.