Prostate cancer treatment depends on whether the cancer exists only inside the gland or within the prostate capsule or on the outside surface of the gland. The presence on the outside surface indicates migration of the cancer to adjacent organs. This study presents a novel method for detecting prostate cancer (PCa) on the surface of excised prostate glands using Raman spectroscopy and stiffness measurements. The workflow involves assessing the location and extent of PCa via MRI before surgery, followed by 3D scanning of the excised prostate. Key positions on ten excised prostates, 211 positions with 56 deemed as cancer, are measured using Raman spectroscopy and stiffness probes. The results are mapped onto a digital representation of the prostate to aid surgical decision-making. Statistical analysis of the Raman data indicates that spectra could be divided into two components, one more related to cancer and one more related to normal tissue. A stiffness parameter was calculated from resonance measurements from the stiffness probe. The Raman components and stiffness parameters were converted to z-scores. Logistic generalized linear mixed modelling revealed that the stiffness parameter was statistically associated with cancer presence in prostate regions (p = 0.009). The scanning equipment is easy to handle and makes further larger studies possible. This method holds promise for providing real-time support during surgery, reducing the need for post-surgical therapies and minimizing patient distress.