A recent study showed that a habitat radiomics model predicted overall survival risk in esophageal squamous cell carcinoma, reaching a C‐index of 0.705.[36] Another report found that space‐resolved radiomics and deep learning methods outperformed conventional radiomics for predicting breast cancer response to NAT.[44] Consistent with those findings, we observed strong correlations between certain spatial habitat radiomics features and tumor outcomes. The gene discussed is BRD2; the disease is breast cancer.