Unbiased high-dimensional flow cytometry identified NK and DC immune cell signature in Luminal A-type and triple negative breast cancer

Abstract

Breast cancer is the most common malignancy in women worldwide and a highly heterogeneous disease. Four different subtypes are described that differ in the expression of hormone receptors as well as the growth factor receptor HER2. Treatment modalities and survival rate depend on the subtype of breast cancer. However, it is still not clear which patients benefit from immunotherapeutic approaches such as checkpoint blockade. Thus, we aimed to decipher the immune cell signature of the different breast cancer subtypes based on high-dimensional flow cytometry followed by unbiased approaches. Here, we show that the frequency of NK cells is reduced in Luminal A and B as well as triple negative breast cancer and that the phenotype of residual NK cells is changed toward regulatory CD11b − CD16 − NK cells. Further, we found higher frequencies of PD-1 + CD4 + and CD8 + T cells in triple negative breast cancer. Moreover, while Luminal A-type breast cancer was enriched for CD14 + cDC2 (named type 3 DC (DC3)), CD14 − cDC2 (named DC2) were more frequent in triple negative breast cancer. In contrast, HER2-enriched breast cancer did not show major alterations in the composition of the immune cell compartment in the tumor microenvironment. These findings suggest that patients with Luminal A- and B-type as well as triple negative breast cancer might benefit from immunotherapeutic approaches targeting NK cells.

The metabolism-related lncRNA signature predicts the prognosis of breast cancer patients

“…Breast cancer (BC), a common malignancy in women, is the most common cancer and the second most common cause of cancer-related deaths globally 1 , 2 . The molecular mechanisms driving BC pathogenesis have been extensively researched and categorized into three major subtypes (luminal, HER2-enriched, and triple-negative breast cancer) based on markers such as expression of estrogen receptor (ER) and progesterone receptor (PR) 3 . However, a robust molecular signature is still needed to accurately predict and stratify disease outcomes 4 .…”