Assessment of mammary adiposity in breast cancer using digital pathology

One out of 8 eight women develops BC in her lifetime and one out of two is overweight or obese in industrialized countries. While heavier women have an increased risk of developing BC and heavier BC patients present with worse disease characteristics, BC is so far still treated regardless of patient adiposity because of the limited knowledge accumulated so far. At histological level, the breast is a unique structure, since adipose tissue can occupy up to 56% of the total breast volume, with adipocytes constituting up to 90% of adipose tissue volume. Adipocytes are normally separated from the human mammary epithelium by a fibrous membrane, but this membrane is disrupted during tumor initiation/growth, bringing the adipocytes in close contact with BC cells. These so-called cancer-associated adipocytes (CAAs) are able to communicate with the tumor cells and to deliver building blocks for the new tumor cells. Different image analysis software solutions exist for counting and measuring adipocytes, however, it is unclear which is the most suited for BC samples. The aims of the present research are: 1) to identify the best software for counting and measuring distant adipocytes and CAAs; 2) to set criteria for digital analysis of adipocytes in BC; 3) to apply the identified software for comparing digital measurements of distant adipocytes and CAAs in a series of breast tumors

Publication year:2021

Accessibility:Closed