Unveiling the Stroma: Reproductive Factors and the Tumor Microenvironment in African Breast Cancer

Area of Science:

• Oncology
• Computational Pathology
• Genomics

Background:

• Breast cancer incidence is converging between Black and White women in the US, yet mortality remains disproportionately higher for Black women.
• Hormone receptor-negative tumors, more common in women of African ancestry, are aggressive and challenging to treat.
• Disparities in breast cancer outcomes are influenced by a complex interplay of biological, host, and socioeconomic factors.

Purpose of the Study:

• To investigate the characteristics of the tumor microenvironment in sub-Saharan African women with breast cancer.
• To explore the association between tumor-associated stromal cellularity and breast cancer aggressiveness.
• To evaluate the utility of machine learning in analyzing histopathological data for breast cancer prognostication in resource-limited settings.

Main Methods:

• Analysis of 792 breast cancer cases from the Ghana Breast Health Study.
• Utilized machine learning techniques to assess tumor-associated stromal cellular density from histopathological images.
• Employed traditional methods like hematoxylin and eosin staining alongside advanced computational approaches.

Main Results:

• Higher tumor-associated stromal cellular density was significantly associated with more aggressive tumors and higher tumor grade.
• Stromal cellular density showed a correlation with parity (having given birth) but not with breastfeeding.
• The study highlights the potential of integrating machine learning with traditional pathology for improved breast cancer prognostication.

Conclusions:

• Machine learning analysis of stromal cellularity provides valuable prognostic information for breast cancer in sub-Saharan African women.
• This approach offers a promising avenue for enhancing breast cancer prognostication in low-resource settings.
• Further research should adopt inclusive, equity-driven strategies considering diverse factors contributing to breast cancer disparities.