Study identifies 80 genes linked to increased risk of breast cancer

Breast cancer is the most common malignancy among Western women, with up to 10% of cases attributed to genetic variants. Despite this, the roots of many familial cases remain unexplored, largely due to the complex nature of the genetic factors involved. Addressing this critical gap, a recent study led by Prof. Dina Schneidman-Duhovny from the Rachel and Selim Benin School of Computer Science and Engineering at the Hebrew University of Jerusalem has provided new insights into the genetic underpinnings of familial breast cancer, especially prevalent in families of Middle Eastern descent.

The study utilizes an innovative analysis method tailored for examining genetic variations in families with a history of breast cancer. This method combines cutting-edge machine learning with detailed analysis of protein structures to investigate rare genetic variants. Through the examination of 1218 variants found among members of 12 families, researchers identified 80 genes that could significantly influence breast cancer risk. This discovery includes 70 genes previously unknown to be linked to breast cancer, significantly expanding our understanding of the genetic landscape of the disease.

Hereditary or familial breast cancer accounts for about 15% of all breast cancer cases. Historically, mutations in well-known genes like BRCA1 and BRCA2 have been linked to increased risks of familial breast and ovarian cancer. Yet, they only account for about 30%-40% of familial breast cancer cases. This leaves a substantial number of cases with unknown genetic origins, particularly in families where the illness is evident across generations.

The study revealed key roles for certain cellular pathways related to peroxisomes and mitochondria in predisposing individuals to breast cancer and affecting patient survival. These pathways were found to be particularly significant across a diverse range of ethnic groups in seven of the families studied, highlighting the broader applicability and importance of the findings.

The researchers used full genome sequencing and AI analysis to study genetic variations in women from Middle Eastern families. This approach identified significant genetic changes, linking subgroups of genes to critical cellular pathways involving peroxisomes, which play a key role in fat metabolism.

Our research not only sheds light on the elusive genetic factors behind familial breast cancer but also heralds the possibility of new, targeted treatment strategies that could eventually benefit a wider array of patients, particularly those from underrepresented groups."

Prof. Dina Schneidman-Duhovny, Rachel and Selim Benin School of Computer Science and Engineering, Hebrew University of Jerusalem

These discoveries open up potential avenues for genetic testing and the development of targeted therapies, promising a significant impact on the management and treatment of breast cancer across diverse populations. Additionally, the findings may eventually support the creation of a specialized genetic testing panel for these patient groups, enhancing early detection and personalized treatment plans as research progresses.

Source:

Hebrew University of Jerusalem

Journal reference:

Passi, G., et al. (2024). Discovering predisposing genes for hereditary breast cancer using deep learning. Briefings in Bioinformatics. doi.org/10.1093/bib/bbae346.

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