GSE134992
Serum tRNA-derived fragments (tRFs) as potential candidates for diagnosis of non-triple-negative breast cancer
Breast cancer is one of the most common cancers in the world and non-triple-negative breast cancer (non-TNBC) accounts for 80-90% of all invasive breast cancers. Early detection of breast cancer is considered as key to successful treatment. Conventionally,breast imaging and needle core biopsy are used for detection and monitoring of disease progression. However, small volume changes may be ignored on imaging and traditional biopsy is spatially and temporally limited, leading to a significant lag time in detecting cancer progression. This thus prompted renewed focus on early and accurate diagnosis. In this article, we committed to investigate whether there exists accurate molecule in peripheral blood which can help diagnose breast cancer. tRNA-derived fragments (tRFs) have been reported to be involved in many pathological processes, but whether it can serve as biomarkers for the diagnosis of breast cancer remains unclear. Using high-throughput sequencing technology, we identified 4021 differentially expressed tRFs in normal breast epithelial cell lines and non-triple-negative breast cancer cell lines and 8 tRFs were selected to construct a signature to predict the non-TNBC. Further, qRT-PCR was conducted to verify its expression and to analyze the correlation between dysregulated tRFs and breast cancer. The results indicated that tDR-7816, tDR-5334, tDR-4733 might be promising biomarkers. Through further bioinformatics analysis, we predicted that tDR-7816 influences xenobiotic metabolic process that support the oncogenesis of breast cancer. Taken together, our results provide a rationale for using circulating tDR-7816 expression as a novel potential biomarker to diagnose early non-TNBC patients. Overall design: Examination of differentially expressed tRFs in non-triple-negative breast cancer cell lines and normal cell lines.