Abstract
Breast cancer has become the most common cancer in women, and nontriple negative breast cancer (non-TNBC) accounts for 80-90% of all invasive breast cancers. Early detection, diagnosis, and treatment are considered key to a successful cure. Conventionally, breast imaging and needle core biopsy are used for detection and monitoring. However, small variations in volume might be ignored in imaging, and traditional biopsies are spatially and temporally limited, leading to a significant delay in cancer detection and thus prompting renewed focus on early and accurate diagnosis. In this article, we investigated whether there is an accurate molecule in peripheral blood that can help diagnose breast cancer. Similar to microRNAs, tRNA-derived fragments (tRFs) have been reported to be involved in many pathological processes in breast cancer, but whether they can serve as candidate biomarkers for breast cancer remains unclear. Using high-throughput sequencing technology, we identified 4,021 differentially expressed tRFs in normal and breast cancer cell lines, and eight tRFs were selected to establish a signature as a predictive biomarker of non-TNBC. Furthermore, quantitative reverse-transcriptase polymerase chain reaction was performed to verify the expression of the signature and analyze the correlation between dysregulated tRFs and breast cancer. The results indicated that tDR-7816, tDR-5334, and tDR-4733 might be promising biomarkers. Through further bioinformatics analysis, we predicted that tDR-7816 influences the xenobiotic metabolic processes that support the oncogenesis of breast cancer. In summary, our results provide a rationale for using circulating tDR-7816 expression as a novel potential biomarker for the diagnosis of patients with early non-TNBC.
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