Distinct Reproductive Risk Profiles for Intrinsic-Like Breast Cancer Subtypes: Pooled Analysis of Population-Based...

Area of Science:

• Reproductive epidemiology
• Breast cancer subtypes
• Genomic and molecular epidemiology

Background:

• Reproductive factors are known to influence breast cancer risk, with differential associations observed for estrogen receptor (ER)-positive and ER-negative tumors.
• However, the relationship between reproductive factors and specific intrinsic-like breast cancer subtypes remains less understood.

Purpose of the Study:

• To investigate the associations between key reproductive factors and the risk of distinct intrinsic-like breast cancer subtypes.
• To clarify the distinct reproductive risk profiles for triple-negative breast cancer compared to other subtypes.

Main Methods:

• Pooled analysis of 31 population-based studies (23,353 cases, 71,072 controls) from the Breast Cancer Association Consortium across 16 countries.
• Utilized polytomous logistic regression to assess associations between reproductive factors and breast cancer risk across intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-HER2-like, HER2-enriched-like, and triple-negative breast cancer) and invasiveness.
• All statistical tests were two-sided.

Main Results:

• Parous women showed reduced risk for luminal A-like, luminal B-like, luminal B-HER2-like, and HER2-enriched-like breast cancer, with risk reduction increasing with time since last birth.
• Conversely, parous women exhibited increased risk for triple-negative breast cancer (TNBC) immediately postpartum, which attenuated but persisted over decades.
• Older age at first birth and breastfeeding were associated with lower TNBC risk, unlike other subtypes. Younger age at menarche increased risk for all subtypes, while older age at menopause increased luminal A-like risk.

Conclusions:

• This study highlights a distinct reproductive risk factor profile for triple-negative breast cancer compared to other breast cancer subtypes.
• Findings have significant implications for understanding the etiology of different breast cancer subtypes and for improving breast cancer risk prediction models.