Development of a breast cancer invasion score to predict tumor aggressiveness and prognosis via PI3K/AKT/mTOR pathway analysis

Invasiveness is a key indicator of tumor malignancy and is often linked to poor prognosis in breast cancer (BC). To explore the diverse characteristics of invasive cells, single-cell RNA sequencing (scRNA-seq) data from three ductal carcinoma stages were analyzed, classifying samples into invasion and non-invasion groups. Nine genes (MCTS1, PGK1, PCMT1, C8orf76, TMEM242, QPRT, SLC16A2, AFG1L, and SPINK8) were identified as key discriminators between these groups. A breast cancer invasion score (BCIS) model was developed using LASSO Cox regression, revealed that high BCIS correlated with poorer overall survival in TCGA-BRCA patients and was validated across GSE20685 and METABRIC datasets (five-year and ten-year survival). Functional experiments demonstrated that knockdown of PGK1 or PCMT1 inhibited tumor cell proliferation and reduced the phosphorylation levels of mTORC, P70S6K, S6, and AKT, indicating suppression of the PI3K/AKT/mTOR pathways. High-BCIS tumors exhibited enrichment in protein secretion and PI3K/AKT/mTOR pathways, associated with aggressiveness and therapy resistance. This study introduced the BCIS score, distinguishing invasion from non-invasion cells, linked to PI3K/AKT/mTOR pathways, offering insights into BRCA prognosis and tumor aggressiveness.