Tumor-Infiltrating CD8 T Cells Predict Clinical Breast Cancer Outcomes in Young Women

• Main Authors: Yong Won Jin, Pingzhao Hu
• Format: Article
• Language: English
• Published: MDPI AG 2020-04-01
• Series: Cancers
• Subjects: early-onset breast cancer; deconvolution; tumor infiltration lymphocytes; mutational signatures; pathway analysis
• Online Access: https://www.mdpi.com/2072-6694/12/5/1076

Young women with breast cancer have disproportionately poor clinical outcomes compared to their older counterparts. The underlying biological differences behind this age-dependent disparity are still unknown and warrant investigation. Recently, the tumor immune landscape has received much attention for its prognostic value and therapeutic targets. The differential tumor immune landscape between age groups in breast cancer has not yet been characterized, and may contribute to the age-related differences in clinical outcomes. Computational deconvolution was used to quantify abundance of immune cell types from bulk transcriptome profiles of breast cancer patients from two independent datasets. No significant differences in immune cell composition that were consistent in the two cohorts were found between the young and old age groups. Regardless of absence of significant differences, the higher tumor infiltration of several immune cell types, such as CD8+ T and CD4+ T cells, was associated with better clinical outcomes in the young but not in the old age group. Mutational signatures analysis showed signatures previously not found in breast cancer to be associated with tumor-infiltrating lymphocyte (TIL) levels in the young age group, whereas in the old group, all significant signatures were those previously found in breast cancer. Pathway analysis revealed different gene sets associated with TIL levels for each age group from the two cohorts. Overall, our results show trends towards better clinical outcomes for high TIL levels, especially CD8+ T cells, but only in the young age group. Furthermore, our work suggests that the underlying biological differences may involve multiple levels of tumor physiology.