Background: Triple-negative breast cancer (TNBC) has a poor prognosis, an ineffective diagnosis, and a high degree of aggressiveness. Therefore, novel therapeutic targets for TNBC urgently need to be identified.
Methods: Through a series of bioinformatics analyses, including analysis of differential gene expression, protein-protein interaction (PPI) network, univariate cox regression, immune infiltration, pathway enrichment, etc, as well as auxiliary immunohistochemistry (IHC) and protein quantitativae analysis, to explore prognostic marker for TNBC.
Results: In TNBC tissues, we found that SPDL1 (CCDC99) was considerably overexpressed at both the mRNA and protein levels compared to that in normal and non-TNBC tissues. Additionally, we found that SPDL1-high expression was strongly linked to poor prognosis in TNBC patients. Excessive SPDL1 expression was positively correlated with tumor growth and strongly linked to the cell cycle, DNA replication, and the p53 signaling pathway. In addition, CIBERSORT analysis revealed that SPDL1 can affect the tumor immune microenvironment (TME) in TNBC, encourage the development of TNBC and act as a potential prognostic biomarker for TNBC. Patients with SPDL1-high expression were more sensitive to AZD8055. Notably, we discovered that SPDL1 is highly expressed in the majority of malignancies and may have an impact on the pancancer prognosis.
Conclusions: SPDL1 can serve as a novel prognostic marker for TNBC and pancancer patients.
Keywords: SPDL1; TNBC; bioinformatics analysis; biomarker; prognosis.
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