Digital Pathology as an Innovative Tool for Improving Cancer Diagnosis and Treatment.

For more than a century, the "gold" standard for diagnosing malignant neoplasms has been pathohistology. However, the continuous advancement of modern technologies is leading to a radical transformation of this field and the emergence of digital pathology. The main advantages of digital pathology include the convenience of the data storage and transfer, as well as the potential for automating diagnostic processes through the application of artificial intelligence technologies.

PD-L1 Expression in Receptor-Negative Breast Cancer Tissue.

Background: The high heterogeneity and pathogenetic diversity of breast cancer (BCa) indicate the need for further study of tumor cell biology in order to identify molecular biological markers associated with the aggressiveness of tumors with a negative receptor status. Among many factors that may be involved in the initiation and progression of this form of cancer, the study of the immune components of tumor microenvironment, in particular PD-L1, is considered promising.

Aim: To investigate the relationship between PD-L1 expression in tumor tissue and clinical and pathological characteristics of BCa, taking into account the status of steroid hormone receptors.

EXPRESSION OF SPP1 AND SPARC GENES IN TUMOR TISSUE OF PATIENTS WITH BREAST CANCER.

Background: Breast cancer (BCa) is one of the most common oncological diseases in women in Ukraine and worldwide, which determines the need to search for new diagnostic and prognostic markers. In this aspect, the study of multicellular proteins, in particular osteopontin (OPN) and osteonectin (ON), in BCа tissue is relevant. The aim of the work was to investigate the expression of SPP1 and SPARC at the mRNA and protein levels in BCa tissue and to assess their relationship with the main clinicopathological BCa characteristics and the survival rates of patients.

Development of an algorithm for biomedical image analysis of the spatial organization of collagen in breast cancer tissue of patients with different clinical status.

Collagen, the main component of the tumor microenvironment, plays a key role in the development of breast cancer (BCa); however, the specific changes in its spatial organization during tumor progression have not been definitively elucidated. The existing and available methods for assessing the morphometric parameters of the stroma's fibrous component are insufficient for a detailed description of the state of collagen fibers and for assessing its changes to evaluate the aggressiveness of the BCa course. The aim of the work was to develop an algorithm for microphoto analysis to assess the spatial organization of collagen in BCa tissue of patients with different clinical statuses.