The proposed framework was trained on an in-house BC dataset consisting of 22 training pairs of slides (58,942 and 62,218 of H&E and PgR overlapping 256 × 256 px patches, respectively) and 8 different pairs for evaluation, achieving better image metrics when compared to cycleGAN, MUNIT74 or UGATIT73 models, while also showing high agreement with the biomarker status, when evaluated by a pathologist. The gene discussed is PGR; the disease is breast cancer.