tsRNA signatures in cancer

Abstract

Small, noncoding RNAs are short untranslated RNA molecules, some of which have been associated with cancer development. Recently we showed that a class of small RNAs generated during the maturation process of tRNAs (tRNA-derived small RNAs, hereafter "tsRNAs") is dysregulated in cancer. Specifically, we uncovered tsRNA signatures in chronic lymphocytic leukemia and lung cancer and demonstrated that the ts-4521/3676 cluster (now called "ts-101" and "ts-53," respectively), ts-46, and ts-47 are down-regulated in these malignancies. Furthermore, we showed that tsRNAs are similar to Piwi-interacting RNAs (piRNAs) and demonstrated that ts-101 and ts-53 can associate with PiwiL2, a protein involved in the silencing of transposons. In this study, we extended our investigation on tsRNA signatures to samples collected from patients with colon, breast, or ovarian cancer and cell lines harboring specific oncogenic mutations and representing different stages of cancer progression. We detected tsRNA signatures in all patient samples and determined that tsRNA expression is altered upon oncogene activation and during cancer staging. In addition, we generated a knocked-out cell model for ts-101 and ts-46 in HEK-293 cells and found significant differences in gene-expression patterns, with activation of genes involved in cell survival and down-regulation of genes involved in apoptosis and chromatin structure. Finally, we overexpressed ts-46 and ts-47 in two lung cancer cell lines and performed a clonogenic assay to examine their role in cell proliferation. We observed a strong inhibition of colony formation in cells overexpressing these tsRNAs compared with untreated cells, confirming that tsRNAs affect cell growth and survival.

Keywords: ncRNA; tDR; tRF; tRNA fragments; tsRNA.

Fig. 1.

tsRNA signatures in colon adenomas and adenocarcinomas, breast invasive ductal carcinoma, and ovary cancers. (A) Paired comparison between samples of colon adenomas and respective surrounding normal tissues from seven patients. We found a signature of eight tsRNAs. (B) Paired comparison between samples of colon carcinomas and respective surrounding normal tissues from eight patients. We found a signature of seven tsRNAs. (C) Paired comparison between breast cancer samples and respective surrounding normal tissues from nine patients. We found two dysregulate tsRNAs. (D) Unpaired comparison between ovary cancer samples from nine patients and normal ovary samples from ten different patients. We found a signature of 10 tsRNAs. All data were analyzed by applying normexp negative background correction, quantile data normalization, and moderated t-statistics for differential expression analysis. All tsRNAs considered are significantly differentially expressed (P < 0.05).

Fig. 2.

tsRNA tissues signatures. tsRNA heat map across tissue samples from patients with CLL, lung, colon, ovary, or breast cancer. All values are in log2 scale; red depicts overexpression, and blue represents underexpression.

Fig. S1.

(A) Heat map of the tsRNA signature generated with data from paired samples from colon adenoma patients. (B) Heat map of the tsRNA signature generated with data from paired samples from colon adenocarcinoma patients. (C) Heat map of the tsRNA signature generated with data from paired samples from breast cancer patients. (D) Heat map of the tsRNA signature generated with data from samples from ovary cancer patients and normal ovary tissues from controls.

Fig. 3.

Heatmaps from breast and prostate cell lines. (A) Unsupervised clustering of all cell lines from breast. (B) Unsupervised clustering of normal vs. cancer prostate cell lines. All values are in log2 scale; red depicts overexpression, and blue represents underexpression.

Fig. S2.

(A) Unsupervised clustering of normal vs. cancer breast cell lines. (B) Unsupervised clustering of breast cell lines derived from MCF10A. All values are in log2 scale; red depicts overexpression, and blue represents underexpression.

Fig. S3.

Gene-expression profile. We generated ts-46 (A) and ts-101 (B) KO stable clones from HEK-293 cells by using CRISPR technology. RNA from two ts-46 KO clones, two ts-101 KO clones, and two samples transfected with the empty pCAS9 vector were used for Affymetrix gene-expression profiles. By setting a linear 1.5-fold change, we found 270 genes differentially expressed in the ts-46 clones and 216 genes differentially expressed in the ts-101 clones compared with the WT. Some examples of up-regulated genes in ts-46 and ts-101 clones are MAP3K19, miR-222, and MED28. As expected, mir-4521 is strongly down-regulated in ts-101 clones. Among down-regulated genes we found FILIP1, OCLN, and HIST1H3-A, -B, -C, -D, -E, -F, -G, -H, -I, -J, supporting our hypothesis that tsRNAs can interfere with chromatin structure. All values are in log2 scale; red depicts overexpression, and blue represents underexpression.

Fig. S4.

Ingenuity Pathway Analyses of canonical pathways in gene-expression profiles from ts-46 KO (A) and ts-101 KO (B) cells.

Fig. S4.

Ingenuity Pathway Analyses of canonical pathways in gene-expression profiles from ts-46 KO (A) and ts-101 KO (B) cells.

Fig. 4.

Colony assay on lung cancer cell lines transfected with ts-46 or ts-47. Colony assay performed on H1299 (Left) and A549 (Right) cells. (Upper) The top wells were transfected with the empty vector, and the lower wells were transfected with the vector expressing ts-46. (Lower) The top wells were transfected with the empty vector, and the lower wells were transfected with the vector expressing ts-47. A graphic representation of the colony count is provided beside each plate.