Identification of tRNA-derived small noncoding RNAs as potential biomarkers for prediction of recurrence in triple-negative breast cancer

Abstract

Triple-negative breast cancer (TNBC), an intrinsic subtype of breast cancer, is characterized by aggressive pathology and shorter overall survival. Yet there is no effective therapy for these patients. Breast cancer stem cells (BCSCs) in TNBC may account for treatment failure. It is urgent to identify new therapeutic targets for TNBC. tRNA-derived small noncoding RNAs (tDRs) represent a new class of small noncoding RNAs (sncRNA), which have been reported in some human diseases and biological processes. However, there is no detailed information about the relationship between tDRs and BCSCs. In this study, a population of CD44⁺ /CD24^-/low cells was isolated and identified by reliable BCSC surface markers. tDR expression profiles in TNBC and non-TNBC CSCs were performed by RNA sequencing. A total of 1327 differentially expressed tDRs contained 18 upregulated and 54 downregulated in TNBC group. Furthermore, the selected tDRs were validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). tDR-000620 expression level was consistently lower in TNBC cell lines CSCs (all P < 0.05) and serum samples (t = 2.597, P = 0.013). tDR-000620 expression was significant association with age (P = 0.018), node status (P = 0.026) and local recurrence (P = 0.019) by chi-square test. Kaplan-Meier method with log-rank test for comparison of recurrence curves. The results showed that the tDR-000620 expression (P = 0.002) and node status (P = 0.001) group were statistically significant with recurrence-free survival. Furthermore, multivariate Cox regression demonstrated that lymphatic metastasis (HR, 3.616; 95% CI, 1.234-10.596; P = 0.019) and low tDR-000620 expression (HR, 0.265; 95% CI, 0.073-0.959; P = 0.043) were two independent adverse predictive factors for recurrence-free survival. Finally, we found that tDR-000620 participated in some important biological processes though GO and KEGG analysis. Taken together, our study reveals the expression profiles of tDRs in TNBC and non-TNBC CSCs. It offers helpful information to understand the tDR-000620 expression is responsible for the aggressive phenotype of BCSCs. It may provide predictive biomarkers and therapeutic targets for TNBC recurrence.

Keywords: biomarker; stem cells; tDRs; triple-negative breast cancer.

Figure 1

Isolation and characterization of BCSCs. A, Flow cytometry for analysis of CD24 and CD44 expression in two cell line CSCs (MDA‐MB‐231 and MCF‐7). B, qRT‐PCR analysis of CD24, CD44, ALDH1, Oct‐4, and Sox2 expression in all cell lines. C, The expression of ALDH1, Oct‐4, and Sox2 proteins was analyzed by western blot. D, Image of mammospheres generated by MDA‐MB‐231 and MCF‐7 CSCs at Day 7. Pictures were taken at 400× magnification

Figure 2

Summary of mapping results of aligned reads by MDA‐MB‐231 and MCF‐7 CSCs. A, The percentage of reads aligned to known pre‐miRNA and tRFs&tiRNAs. B, The sequence read length distribution of MDA‐MB‐231 and MCF‐7 CSCs

Figure 3

Differentially expressed tDRs between MDA‐MB‐231 and MCF‐7 CSCs. A, Heatmaps of differentially expressed tDRs in MDA‐MB‐231 and MCF‐7 CSCs. B, The gene number which expressed in the two groups and the specific expressed in each group. C, Scatter plot of differentially expressed tRFs&tiRNAs: Genes above the top line showed upregulation, and genes below the bottom line represented downregulation; gray dots indicated genes without differentially expression

Figure 4

Characterization of tRFs&tiRNAs derived from tRNAs. A and B, Stacked plot for the number of tRFs&tiRNAs derived from the same anticodon of the tRNA: The X‐ and Y‐axis represented the tRNAs with the same anticodon tRNA and the number of different tRFs&tiRNAs derived from the same anticodon, respectively. C and D, The unique tRFs&tiRNAs of expressed level percentage of each subtype

Figure 5

Validation of six dysregulated tDRs in triple‐negative breast cancer (TNBC) and non‐TNBC stem cell lines and serum samples. A and B, The expression level of tDR‐000620 and tDR‐001262 in HCC‐1937, MDA‐MB‐453 CSCs, and T47D, SKBR3 CSCs by qRT‐PCR appeared to be consistent with the result in MDA‐MB‐231 CSC group compared with the MCF‐7 CSC group. C, tDR‐000620 was significantly downregulated in serum of TNBC patients compared with non‐TNBC. D, The serum expression level of tDR‐001262 between two groups was not statistically significant; tDR‐001267, tDR‐008406, tDR‐000106, and tDR‐007257 were not detected in serum samples. (*P < 0.05, n = 3)

Figure 6

Gene ontology (GO) and KEGG analyses for target genes of tDR‐000620. A‐C, The mainly molecular function, biological process, and cellular component of target genes with fold changes >2. D, The pathway analysis indicated that these genes were involved in the cytokine–cytokine receptor interaction, AMPK signaling pathways, adipocytokine signaling pathways, toxoplasmosis, galactose metabolism, TNF signaling pathways, osteoclast differentiation, Jak‐STAT signaling pathways

Figure 7

Comparison of recurrence‐free survival in tDR‐000620 and node status group of the triple‐negative breast cancer (TNBC) patients using Kaplan‐Meier method with log‐rank test. A, TNBC patients with low tDR‐000620 expression had significantly shorter recurrence‐free survival than those in high expression group. B, TNBC patients with lymphatic metastasis group had significantly shorter recurrence‐free survival than those in lymph node negative group