In Breast cancer (Tokyo, Japan)
BACKGROUND : PTPRF-interacting protein alpha 1 (PPFIA1) plays an important role as a regulator of cell motility and tumor cell invasion and is frequently amplified in breast cancer. The aim of this study was to investigate the clinicopathologic features, survival, anticancer immunities and specific gene sets related to high PPFIA1 expression in patients with breast cancer. We verified the importance of PPFIA1 and survival rates using machine learning and identified drugs that can effectively reduce breast cancer cells with high PPFIA1 expression.
METHODS : This study analyzed clinicopathologic factors, survival rates, immune profiles and gene sets according to PPFIA1 expression in 3457 patients with breast cancer from the Kangbuk Samsung Medical Center cohort (456 cases), Molecular Taxonomy of Breast Cancer International Consortium (1904 cases) and The Cancer Genome Atlas (1097 cases). We applied gene set enrichment analysis (GSEA), in silico cytometry, pathway network analyses, in vitro drug screening, and gradient boosting machine (GBM) analysis.
RESULTS : High PPFIA1 expression in breast cancer was associated with worse prognosis, with reduced tumor-infiltrating lymphocytes, especially CD8+ T cells, and increased PD-L1 expression. In pathway network analysis, PPFIA1 was linked directly to the tyrosine-protein phosphatase pathway and indirectly to immune pathways. The importance of PPFIA1's association with survival in GBM analysis was higher than that of perineural and lymphovascular invasion. In in vitro drug screening, expression of PPFIA1 on mRNA level positively correlated with sensitivity of cell lines to erlotinib.
CONCLUSION : High PPFIA1 in patients with breast cancer is related to poor prognosis and decreased anticancer immune response, and erlotinib may be promising for development of therapeutic approaches in patients with tumors overexpressing PPFIA1.
Chu Jinah, Min Kyueng-Whan, Kim Dong-Hoon, Son Byoung Kwan, Kim Hyung Suk, Jung Un Suk, Kwon Mi Jung, Do Sung-Im
2022-Dec-07
Breast cancer, Drug, Machine learning, PPFIA1, Prognosis, Tumor-infiltrating lymphocytes
