Advancing proliferation assessment in invasive breast cancer: integrating digital pathology, artificial intelligence, and molecular insights for improved diagnostic and prognostic strategies - Ibrahim, Asmaa (2024)
Background: Mitotic score is one of the three components of the Nottingham grading system of breast cancer (BC), and it represents the tumour’s rate of proliferation and aggressiveness. However, the optimal method of mitoses assessment in BC remains to be defined. Digital pathology (DP), combined with artificial intelligence (AI) algorithms, offers solutions for the challenges associated with the manual counting of mitotic figures. AI algorithms can improve the detection and quantification of mitotic figures. However, the lack of consistent methodology and definitions hinders their integration into clinical practice. In addition to sustained proliferation, the evasion of apoptosis is one of the prerequisites for carcinogenesis and tumour progression. High levels of apoptosis may appear to be a good prognostic factor; however, apoptosis is frequently increased in high-grade tumours, particularly when it is accompanied by high levels of proliferation, and the evidence for apoptosis as an independent prognostic marker remains inconclusive. This suggests that the regulators that control proliferation and apoptosis in normal tissues persist, at least in part, during malignancy. This can in part justify why these two parameters, mitosis, and apoptosis, should be analysed together; the targeting of their regulatory mechanisms could offer the opportunity to discover new therapies and to identify potential drug targets.