Identification of microrna editing sites in clear cell renal cell carcinoma

ABSTRACT Clear cell renal cell carcinoma (ccRCC) is a malignant tumor originating from the renal tubular epithelium. Although the microRNAs (miRNAs) transcriptome of ccRCC has been

extensively studied, the role of miRNAs editing in ccRCC is largely unknown. By analyzing small RNA sequencing profiles of renal tissues of 154 ccRCC patients and 22 normal controls, we

identified 1025 miRNA editing sites from 246 pre-miRNAs. There were 122 editing events with significantly different editing levels in ccRCC compared to normal samples, which include two

A-to-I editing events in the seed regions of _hsa-mir-376a-3p_ and _hsa-mir-376c-3p_, respectively, and one C-to-U editing event in the seed region of _hsa-mir-29c-3p_. After comparing the

targets of the original and edited miRNAs, we found that _hsa-mir-376a-1_49g_, _hsa-mir-376c_48g_ and _hsa-mir-29c_59u_ had many new targets, respectively. Many of these new targets were

deregulated in ccRCC, which might be related to the different editing levels of _hsa-mir-376a-3p_, _hsa-mir-376c-3p_, _hsa-mir-29c-3p_ in ccRCC compared to normal controls. Our study sheds

new light on miRNA editing events and their potential biological functions in ccRCC. SIMILAR CONTENT BEING VIEWED BY OTHERS ADAR1-DEPENDENT MIR-3144-3P EDITING SIMULTANEOUSLY INDUCES MSI2

EXPRESSION AND SUPPRESSES SLC38A4 EXPRESSION IN LIVER CANCER Article Open access 04 January 2023 THE RELATIONSHIP BETWEEN THE NETWORK OF NON-CODING RNAS-MOLECULAR TARGETS AND

N6-METHYLADENOSINE MODIFICATION IN TUMORS OF URINARY SYSTEM Article Open access 17 April 2024 PIRNAS AND CIRCRNAS ACTING AS DIAGNOSTIC BIOMARKERS IN CLEAR CELL RENAL CELL CARCINOMA Article

Open access 05 March 2025 INTRODUCTION Renal cell carcinoma (RCC), which is formed by malignant proliferation of tubular epithelial cells, is the most common malignant tumor of kidney1.

According to the histological classification, there are many subtypes of RCC, among which clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype, accounting for about 75% of

all RCCs1. Although some ccRCC cases can be surgically resected, the metastatic rate of ccRCC is high, and about 30% of patients who present with metastases at first screening are not

candidates for surgery2,3. Therefore, early detection and targeted therapy of ccRCC is the most effective way to reduce the number of deaths from this disease4. MicroRNAs (miRNAs) are a

class of single-stranded non-coding RNAs with approximately 22 nucleotides that can undergo extensive post-transcriptional modifications5,6. As important regulatory molecules in biological

processes, miRNAs are involved in almost all cellular pathways and pathological processes, including cancer initiation, progression and metastasis7. Mature miRNAs pair with their target

mRNAs through the seed regions (the first eight nucleotides from the 5\({\prime }\) ends of miRNAs) to induce mRNA degradation or translational repression8. The regulation of gene expression

by miRNAs is diverse and complex. A miRNA can bind to many different targets, and a target can be regulated by multiple miRNAs9. Therefore, even a single nucleotide change in a miRNA,

especially if it occurs within the seed region, leads to severe changes of its targets and also affects the expression of its targets. In ccRCC, miRNAs are reported as either oncomiRNAs or

tumor suppressors10. For example, _hsa-miR-21-5p_ was overexpressed in ccRCC tissues compared to normal controls and correlated with the downregulation of PPAR-\(\alpha\) in ccRCC11. Ji et

al. reported that _hsa-miR-155-5p_ was upregulated in ccRCC, and inhibition of _hsa-miR-155-5p_ could significantly suppress the proliferation, colony formation, migration and invasion and

induce G1 phase arrest and apoptosis12. In addition, _hsa-miR-193a-3p_ and _hsa-miR-224-3p_ as oncogenic miRNAs13, activated the PI3K/Akt pathway and targeted glycosylation-related enzymes

to mediate cell proliferation, migration and invasion in ccRCC. _hsa-miR-30a-5p_14 and _hsa-miR-30c-5p_15 were downregulated in ccRCC, and were associated with tumor aggressiveness16. Cui et

al. found that _hsa-miR-99a-5p_ was downregulated in ccRCC and correlated with overall survival17. Moreover, _hsa-miR-187-3p_ presents lower levels in tumor tissue and plasma of patients

with ccRCC, and lower levels of _hsa-miR-187-3p_ were associated with higher tumor grade and stage18. In summary, a large number of miRNAs play crucial roles in the initiation and

progression of ccRCC. RNA editing is a prevalent and conserved post-transcriptional mechanism that plays a crucial role in the diversification of gene expression and transcriptome complexity

across various organisms. This process involves specific proteins that catalyze chemical modifications to RNA molecules during their generation processes, leading to the alterations,

deletions, and/or insertions of bases19,20. RNA is edited in a variety of ways. The most widely reported editing type is adenosine to inosine (A-to-I) editing, catalyzed by adenosine

deaminase acting on RNA (ADAR) enzymes19. This is followed by editing of cytosine (C) to uracil (U), which is catalyzed by the apolipoprotein B mRNA editing catalytic polypeptide-like

(APOBEC) proteins19,20. Furthermore, some RNAs are modified on their 3\({\prime }\) ends to add additional nucleotides, such as A or U21,22,23. It has been found that a large number of RNA

editing events also exist in miRNAs24,25,26,27,28,29,30,31,32,33,34,35,36,37 and the A-to-I miRNA editing events in cancer have attracted some attention38,39,40. For example, _ADAR2_ is

responsible for editing _hsa-miR-21-3p/5p_, _hsa-miR-221-5p_ and _hsa-miR-222-3p_, which exhibit high levels and are known to promote cancer progression in glioblastoma41. In a study on

miRNA editing in pan-cancer, the edited _hsa-miR-200b-3p_ promotes cell invasion and migration by targeting _LIFR_, a metastasis suppressor39. A-to-I edited _hsa-miR-589-3p_ targets _ADAM12_

and original _hsa-miR-589-3p_ targets _PCDH9_, a tumor suppressor related to glioma progression42. A-to-I editing level of _hsa-miR-589-3p_ is reduced in glioblastoma, which promotes the

proliferation and invasion of brain cancer cells42. In addition, miRNA editing also plays an important role in neurological diseases. For example, A-to-I editing of _hsa-miR-497-5p_ is

enhanced in Parkinson’s disease (PD), which potentially promotes progressive neurodegeneration of PD patients37. In summary, miRNA editing is associated with the initiation and progression

of numerous cancers. However, miRNA editing events in ccRCC are largely unknown, which has become a major obstacle and blind spot for the study of ccRCC. In this study, to comprehensively

characterize miRNA editing and/or modification sites in ccRCC, we systematically analyzed small RNA sequencing profiles of 154 ccRCC patients and 22 healthy controls. We identified 1025

miRNA mutation and/or editing (M/E) sites with significant editing levels in these samples. In addition, 122 M/E sites showed significantly different editing levels in ccRCC patients

compared to control samples. Among them, we focused on 3 editing events that occurred in the seed regions and predicted the target genes of their corresponding edited miRNAs. We explored the

potential functions of new target genes of edited miRNAs and examined expression patterns of these new targets in ccRCC using existing gene expression data. Our results suggested that

A-to-I edited _hsa-mir-376a-1-3p_ and _hsa-mir-376c-3p_ targeted _BCAT1_ and _MTHFD2_, respectively, and C-to-U edited _hsa-mir-29c-3p_ targeted _RASSF8_. Presumably, because the A-to-I

editing levels of _hsa-mir-376a-1-3p_ and _hsa-mir-376c-3p_ were reduced in ccRCC, _BCAT1_ and _MTHFD2_ were upregulated in ccRCC. Similarly, potentially due to increased C-to-U editing

level of _hsa-mir-29c-3p_, _RASSF8_ was significantly downregulated in ccRCC. These results suggest that miRNA editing contributes to initiation and progression of ccRCC. RESULTS SUMMARY OF

MUTATION AND EDITING SITES IDENTIFIED IN MIRNAS The MiRME pipeline43 was used to identify miRNA M/E sites from the collected 176 sRNA-seq profiles. In total, 1025 M/E sites with significant

editing levels were identified (as listed in Supplementary Table S2.1). As mentioned above, these M/E sites were divided into 9 categories (Fig. 1A and Supplementary Table S2.2). We found

that there were more 3\({\prime }\)-addition sites than 5\({\prime }\) editing sites (Fig.  1A and Supplementary Tables S2.3, S2.4). In addition, M/E sites in the central regions of mature

miRNAs include 9 (0.88%) A-to-I, 30 (2.93%) C-to-U, 5 (2.54%) Other and 2 (0.20%) SNP sites. We further investigated the miRNA editing events that occured in the central regions of mature

miRNAs (Supplementary Table S2.5), i.e., A-to-I, C-to-U and Other. We counted the base changes of these three editing types (Fig. 1B), and found 9 A-to-I, 30 C-to-U, and 5 Other editing

events. One insertion and two deletion events were also found (Fig. 1B). Furthermore, we also investigated the distributions of these events within different regions of mature miRNAs,

including the 5\({\prime }\) ends, 3\({\prime }\) ends, and central regions. Our results indicated that 3\({\prime }\)-addition was the most common type of RNA editing events of miRNAs. As

shown in Fig. 1C, the numbers of editing events at the 3\({\prime }\) ends were significantly higher than those at the 5\({\prime }\) ends and the central regions. For the vast majority of

miRNAs, only 1 or 2 editing events happened at the 5\({\prime }\) ends and the central regions. NINE MIRNA A-TO-I EDITING SITES IN CCRCC Totally, 9 A-to-I editing sites with significant

editing levels were identified from the 176 samples (Fig. 2A). The editing levels of _hsa-mir-376a-1_ and _hsa-mir-376a-2_ were almost identical, probably due to their high sequence

similarity. We then counted the nucleotides around these 9 A-to-I editing sites, and found that the 5\({\prime }\) and 3\({\prime }\) ends of these A-to-I editing sites had clear U and G

base preference, respectively (Fig. 2B), which was consistent with results in literature27,29,43. As examples, the detailed information of two A-to-I editing sites in _hsa-mir-411_ and

_hsa-mir-7977_ in two ccRCC samples (SRR11873730 and ERR4367258, respectively) were presented in Fig. 2C and D, respectively. As shown in Fig. 2E and F, a large number of sequencing reads in

these samples supported the two A-to-I editing sites. THIRTY MIRNA C-TO-U EDITING SITES IN CCRCC We carefully studied the 30 C-to-U editing sites and found that their editing levels were

generally low in the 176 sample (Fig. 3A). Furthermore, nucleotides on the 5\({\prime }\) sides of these C-to-U editing sites were biased toward C, while those on the 3\({\prime }\) sides

were biased toward A (Fig. 3B). Examples of two C-to-U editing sites were shown in Fig. 3C and D, respectively. In addition, the detailed editing sites and editing levels of these two miRNAs

were shown in Fig. 3E and F, respectively. These two C-to-U editing sites were supported by thousands of sequencing reads in the samples used, indicating good reliabilities of these two

editing sites. TWO MIRNA SNP SITES IN CCRCC The identified M/E sites were compared with SNPs in miRNAs previously reported44 and NCBI dbSNP (v151) according to the criteria mentioned in

Materials and Methods. Two SNPs (rs11614913 and rs2155248) were shown in Supplementary Fig. S1 and Supplementary Table S2.6, and the editing levels of these two SNPs in one normal and one

ccRCC sample, respectively, were shown in Supplementary Fig. S1A. As shown in Supplementary Fig. S1B and S1C, these SNPs were supported by many sequencing reads in SRR11873716 and

SRR11873719, respectively. Additionally, the editing levels of these two sites reached 100% (Supplementary Fig. S1D and S1E), consistent to the fact that these sites were SNPs. 122 M/E SITES

WITH SIGNIFICANTLY DIFFERENT EDITING LEVELS IN CCRCC We obtained 122 miRNA M/E sites with significantly different editing levels in ccRCC samples (n = 154) compared to normal controls (n =

22) by using Mann-Whitney _U_-tests (corrected \(p < 0.05\)) (Supplementary Table S3). The 122 miRNA M/E sites were divided into 7 categories. 112 of these 122 sites were 3\(^{\prime

}\)-addition events (3\(^{\prime }\)-A, 3\(^{\prime }\)-U, and 3\(^{\prime }\)-Other). In addition, there were 5 A-to-I editing sites, 2 C-to-U editing sites, and the remaining two were

5\(^{\prime }\) end sites and one Pseudo site, i.e., potential false positive site (Fig. 4A). Most of the 122 M/E sites had increased editing levels (77 M/E sites, 63.1%) and 45 M/E sites

(36.9%) had decreased editing levels in ccRCC samples when compared to normal controls (Fig. 4B). The categories of M/E sites with increased and decreased editing levels in ccRCC samples

were shown in Fig. 4C. In M/E sites with increased editing levels in ccRCC, the 3\({\prime }\)-A editing events accounted for the largest portion, while the 3\({\prime }\)-U editing events

accounted for the largest part in those with decreased editing levels in ccRCC compared to normal controls. In ccRCC, the editing levels of _hsa-mir-376a-1_49_A_g_ and _hsa-mir-376c_48_A_g_

were significantly decreased (Fig. 4D), while those of _hsa-mir-6503_59_A_g_ and _hsa-mir-29c_59_u_ were significantly increased (Fig. 4D and E, respectively). We also investigated the

levels of these edited miRNAs and found that _hsa-mir-376a-1_49g_ and _hsa-mir-376c_48g_ were significantly downregulated in ccRCC samples, while the levels of _hsa-mir-6503_59g_ and

_hsa-mir-29c_59u_ were significantly upregulated in ccRCC (Fig. 4F and G, respectively). Figure 4H–M illustrated the details of the three edited miRNAs, _hsa-mir-376a-1_49_A_g_,

_hsa-mir-376c_48_A_g_ and _hsa-mir-29c_59_u_ in one ccRCC sample (SRR11873721), one normal sample (SRR11873716) and one ccRCC sample (ERR4367209), respectively. THE EXPRESSION LEVELS OF

_ADAR_ AND _APOBEC_ GENES IN CCRCC As shown in Supplementary Fig. S2 and Supplementary Table S7, the expression levels of the _ADAR_ genes that catalyzed A-to-I editing of miRNAs were

examined. In the TCGA data, _ADAR1_ was downregulated in ccRCC compared to normal controls (Supplementary Fig. S2A) which was consistent with the decreased editing levels of

_hsa-mir-376a-1_49_A_g_, _hsa-mir-376a-2_55_A_g_, and _hsa-mir-376c_48_A_g_. However, in the other two cohorts of gene expression profiles, _ADAR1_ was upregulated, suggesting that more

researches were needed to reveal the role of _ADAR1_ in the editing of miRNAs in ccRCC. We found that _ADAR2_ was significantly upregulated in ccRCC samples compared to normal controls in

the three selected cohorts of gene expression datasets (Supplementary Fig. S2B). Meanwhile, the editing level of _hsa-mir-6503_59_A_g_ was significantly increased in ccRCC samples compared

to normal controls (Fig. 4D), suggesting that _ADAR2_ mediated the editing of _hsa-mir-6503_ in ccRCC and contributed to its increased editing levels in ccRCC compared to normal controls.

_ADAR3_ was downregulated in one cohort of gene expression profiles, and had no significant change in the other two datasets (Supplementary Fig. S2C). The expression of the _APOBEC_ genes

that mediated C-to-U editing of miRNAs was also examined. As shown in Supplementary Fig. S3 and Supplementary Table S8, the expression levels of most _APOBEC_ family members showed a

significantly upward trend in ccRCC tumors, including _AICDA_, _APOBEC3A_, _APOBEC3B_, _APOBEC3C_, _APOBEC3D_,_ APOBEC3F_, _APOBEC3G_ and _APOBEC3H_ genes (Supplementary Fig. S3A, D–J,

respectively). In our results, the editing level of _hsa-mir-29c_59_C_u_ was significantly increased in ccRCC samples (Fig. 4E). More researches are needed to clarify which _APOBEC_ gene is

the most promising enzyme that mediates the C-to-U editing of _hsa-mir-29c_59_C_u_ and other miRNA C-to-U editing sites in ccRCC. THE EXPRESSION LEVELS OF _ TENT_ GENES IN CCRCC Terminal

nucleotidyltransferases (_TENTs_) modify RNA at post-transcriptional level, which regulates the stability and activity of RNA45. TENT2 and TENT4B proteins catalyze 3\({\prime }\) end

adenylation of miRNAs21,46,47,48,49,50. TUT4 and TUT7 proteins are terminal uridine transferases that belong to the TENT3 subfamily, which have the ability to catalyze the 3\({\prime }\)

uridylation of miRNAs23,51,52,53. The levels of these _TENT_ genes in ccRCC and normal controls were examined (Supplementary Table S9). In ccRCC, the level of _TENT2_ was significantly

higher (Supplementary Fig. S4A–C), while _TENT4B_ was significantly downregulated (Supplementary Fig. S4A and C). There are more 3\({\prime }\)-A sites with increased editing levels in ccRCC

than 3\({\prime }\)-A sites with decreased editing levels in ccRCC (Fig. 4C), suggesting that _TENT2_ might be the major enzyme for the 3\({\prime }\)-A editing of miRNAs in ccRCC, while

the downregulation of _TENT4B_ could be responsible for the decreased 3\({\prime }\)-A editing levels of some miRNAs in ccRCC. The levels of _TUT4_ had no significantly different expression

in ccRCC compared to normal controls (Supplementary Fig. S4A to C), but the expression of _TUT7_ was significantly upregulated in ccRCC (Supplementary Fig. S4A–C). These results suggest that

some 3\({\prime }\)-U editing sites of miRNAs with increased editing levels in ccRCC (Fig. 4C, left column) are mainly catalyzed by TUT7. IDENTIFICATION OF TARGETS FOR A-TO-I AND C-TO-U

EDITED MIRNAS Three M/E sites (_hsa-mir-376a-1_49_A_g_ and _hsa-mir-376c_48_A_g_ and _hsa-mir-29c_59_C_u_) in seed regions of mature miRNAs were selected for subsequent analysis, because

these sites had significantly different editing levels in ccRCC and the levels of their corresponding edited miRNAs were also significantly different and in the same directions of changes

when compared their editing levels in ccRCC with normal controls. To decrease false positives and increase the reliabilities of predicted miRNA targets, we used 11 PAR-CLIP sequencing

profiles. The principle of PAR-CLIP (Photoactivatable Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation) technology is used to detect the crosslinking of RNA-binding proteins

(RBPs) to RNA molecules, followed by immunoprecipitation and sequencing to identify the binding sites54. Through PAR-CLIP experiments, the interaction between RISC (including AGO proteins

and miRNAs) and mRNA can be identified54. The sequences of the miRNA binding sites were obtained through PAR-CLIP experiments (targeting one of the AGO proteins) and then were sequenced54.

Next, the MiCPAR algorithm55 was used to identify the targets of original and edited miRNAs by analyzing 11 PAR-CLIP profiles of AGO proteins (see Methods for details). We found that the

original and edited _hsa-mir-376a-1-3p_ had 102 common target genes, and 484 new target genes of _hsa-mir-376a-1_49g_ were found (Fig. 5A and Supplementary Tables S4.1–S4.3). The original

and edited _hsa-mir-376c-3p_ had 107 common target genes, and _hsa-mir-376c_48g_ had 568 new target genes (Fig. 5B and Supplementary Tables S5.1–S5.3). The original and edited

_hsa-mir-29c-3p_ had 107 identical target genes, and _hsa-mir-29c_59u_ had 480 new target genes (Fig. 5C and Supplementary Tables S6.1–S6.3). Next, we compared the new target genes of

_hsa-mir-376a-1_49g_, _hsa-mir-376c_48g_ and _hsa-mir-29c_59u_ to deregulated genes in ccRCC. We found that in the three gene expression datasets selected (GSE151419, GSE126964 and TCGA), 88

and 82 target genes of _hsa-mir-376a-1_49g_ and _hsa-mir-376c_48g_ were commonly significantly upregulated in ccRCC (Fig. 5D,E and Supplementary Tables S4.4, S5.4), respectively.

Additionally, 51 target genes of _hsa-mir-29c_59u_ were commonly significantly downregulated in ccRCC (Fig. 5F and Supplementary Table S6.4). The numbers of PAR-CLIP reads for the 88, 82 and

51 overlapped target genes in Fig. 5D–F were shown in Fig. 5G–I, respectively. Then, among these target genes of _hsa-mir-376a-1_49g_, _hsa-mir-376c_48g_, and _hsa-mir-29c_59u_, genes with

more than 10 PAR-CLIP reads with T-to-C variations were retained for further analysis (Supplementary Tables S4.5, S5.5, S6.5, respectively). Among the retained target genes of

_hsa-mir-376a-1_49g_, _hsa-mir-376c_48g_ and _hsa-mir-29c_59u_, _BCAT1_, _MTHFD2_ and _RASSF8_ were further analyzed after examining their functional relevance in ccRCC by reading their

literature, respectively. Figure 6A–C showed the distribution of PAR-CLIP reads for _BCAT1_,_ MTHFD2_ and_ RASSF8_, respectively. These results indicated that PAR-CLIP reads were

significantly accumulated at the complementary sites of _hsa-mir-376a-1_49g_, _hsa-mir-376c_48g_ and _hsa-mir-29c_59u_, respectively. The identified miRNA complementary sites and their

_P_\(_{s}\) values on _BCAT1_, _MTHFD2_ and _RASSF8_ were shown in Fig. 6D–F, respectively. The complementary sites of _hsa-mir-376a-1_49g_, _hsa-mir-376c_48g_ and _hsa-mir-29c_59u_ were

located in the 3\(^{\prime }\)UTR, CDS and 3\(^{\prime }\)UTR of _BCAT1_, _MTHFD2_ and _RASSF8_, respectively (as shown in Fig. 6G to 6I, respectively). _BCAT1_ and _MTHFD2_ were upregulated

in ccRCC, while _RASSF8_ was downregulated in ccRCC (Supplementary Fig. S5 and Supplementary Tables S10.1–S10.3). Figure 6J–L showed the details of complementary sites of

_hsa-mir-376a-1_49g_, _hsa-mir-376c_48g_ and _hsa-mir-29c_59u_ on _BCAT1_ (NM_001178093.1), _MTHFD2_ (NM_006636.3) and _RASSF8_ (NM_001164746.1), respectively, as well as the PAR-CLIP reads

at these sites. FUNCTIONAL ANALYSIS OF A-TO-I AND C-TO-U EDITED MIRNAS We performed Gene Ontology (GO) and KEGG pathway enrichment analysis to investigate the functions of the new target

genes that were commonly deregulated in the three gene expression datasets selected for _hsa-mir-376a-1_49g_, _hsa-mir-376c_48g_, and _hsa-mir-29c_59u_, respectively (Supplementary Fig. S6,

Supplementary Tables S11.1–S11.3 and S12.1–S12.3). The target genes of _hsa-mir-376a-1_49g_ were enriched in many cancer-related pathways, including “Transcriptional misregulation in

cancer”, “Small cell lung cancer”, “Prostate cancer”, “Pathways in cancer”, “p53 signaling pathway”, “Non-small cell lung cancer”, “Melanoma”, “Glioma”, “Endometrial cance”, “Colorectal

cancer”, “Chronic myeloid leukemia” and “Breast cancer” (Supplementary Fig. S6A). The target genes of _hsa-mir-376c_48g_ were mainly enriched in the “Pathways in cancer” and the “Rap1

signaling pathway” (Supplementary Fig. S6C). Additionally, “Metabolic pathways” was the most enriched pathway of the 51 target genes of _hsa-mir-29c_59u_ (Supplementary Fig. S6E). These

results suggest that _hsa-mir-376a-1_49g_ and _hsa-mir-376c_48g_ are directly related to ccRCC by targeting genes in many cancer-related pathways, while _hsa-mir-29c_59u_ seems to be

involved in the deregulation of genes in metabolic pathways. DISCUSSION We identified 1025 M/E sites with significant editing levels by analyzing 176 sRNA-seq profiles of ccRCC patients (n =

154) and healthy controls (n = 22). The M/E sites at the 3\(^{\prime }\) end accounted for the majority, which was consistent with previous work37,40,43,56,57,58,59. We identified 122

editing events with significantly different editing levels in ccRCC samples compared to healthy control samples. The editing levels of 63.1% and 36.9% of these 122 miRNA editing events were

increased and decreased in ccRCC patients, respectively, which may be related to the pathogenesis of ccRCC. Subsequently, we focused on A-to-I and C-to-U miRNA editing events that occurred

in the seed regions and were dysregulated in ccRCC. The editing levels of _hsa-mir-376a-1_49g_ and _hsa-mir-376c_48g_ were significantly lower in ccRCC than those in normal samples. In

addition, their levels also showed the same significant downregulation in ccRCC samples compared to normal controls. The editing level of _hsa-mir-29c_59_C_u_ and level of _hsa-mir-29c_59u_

showed significant increases in ccRCC compared to normal controls. We compared the targets of original _hsa-miR-376a-3p_, _hsa-miR-376c-3p_ and _hsa-miR-29c-3p_ with the targets of edited

miRNAs, _hsa-mir-376a-1_49g_, _hsa-mir-376c_48g _ and _hsa-mir-29c_59u_. We found that _hsa-mir-376a-1_49g_, _hsa-mir-376c_48g_ and _hsa-mir-29c_59u_ could target 484, 568 and 480 additional

novel targets, respectively. C-to-U editing of miRNA was not widely reported. Interestingly, we detected 30 C-to-U editing events, much more than A-to-I editing events identified, in ccRCC.

The more prevalence of C-to-U miRNA editing in ccRCC may be related to the high levels of _APOBEC_ gene family in ccRCC (Supplementary Fig. S4). For examples, _APOBEC3C_, _APOBEC3F_ and

_APOBEC3G_ were highly expressed in ccRCC samples compared to normal controls (as shown in Supplementary Figs. S4F, H and I, respectively). The fifth position of _hsa-miR-100-5p_ was

specifically edited in Treg60. C-to-U edited _hsa-miR-100-5p_ repressed a new target _SMAD2_, which reduced the fraction of Treg in peripheral blood mononuclear cells60. The C-to-U editing

of _hsa-mir-29c_59_C_u_ in ccRCC might represent another case of functional C-to-U editing sites in miRNAs, because its editing levels significantly increased in ccRCC and the C-to-U edited

_hsa-mir-29c-3p_ potentially repressed _RASSF8_ in ccRCC. As 11 of these 30 C-to-U editing sites were in seed regions (Fig. 3 and Supplementary Table S2.5), more of these C-to-U editing

might be functional in tissue- or time-specific manners. In our study, _BCAT1_ and _MTHFD2_ were upregulated in ccRCC and identified as target genes of _hsa-mir-376a-1_49g_ and

_hsa-mir-376c_48g_ in ccRCC, respectively. _BCAT1_ is overexpressed in many cancers and has been proposed as a marker for predicting cancer prognosis61. For example, overexpression of

_BCAT1_ promotes tumor growth in renal clear cell carcinoma62, lung cancer63, glioma64, ovarian cancer65, breast cancer66, hepatocellular carcinoma67,68, myeloid leukemia69, gastric

cancer70,71, endometrial cancer72, non-small cell lung cancer73 and pan-cancer74. Moreover, _BCAT1_ and its metabolites participate in the metabolism of cancer cells through different

mechanisms. For example, the PI3K/AKT/mTOR signaling pathway is activated by _BCAT1_ to promote the proliferation and angiogenesis of gastric cancer cells in vitro70. At the same time, in

the study of lung adenocarcinoma, _BCAT1_ promotes lung adenocarcinoma progression by enhancing mitochondrial function and NF-\(\kappa\)B pathway75. Recent reports have shown that _MTHFD2_

is also highly expressed in many cancers, including renal clear cell carcinoma76,77, pancreatic cancer,78 breast cancer79, myeloid leukemia80, non-small cell lung cancer81,82, hepatocellular

carcinoma83, colorectal cancer84, breast cancer85,86, ovarian cancer87 , bladder cancer88, glioblastoma89, nasopharyngeal carcinoma90, oral squamous cell carcinoma91, and pan-cancer92. In

addition, studies have reported the role of _MTHFD2_ in tumor immune evasion. _MTHFD2_ is induced by IFN-\(\gamma\) and promotes basal and IFN-\(\gamma\)-induced PD-L1 expression.

Mechanistically, _MTHFD2_ drives folate circulation to maintain intracellular UDP-GlcNAc and cMYC O-GlcNAcylation, which promotes PD-L1 transcription93. Huang et al. found that _MTHFD2_

promoted breast cancer cell proliferation through AKT signaling pathway, and high level of _MTHFD2_ reduced the survival rate of breast cancer patients79. In summary, the upregulation of

_BCAT1_ and_ MTHFD2_ in ccRCC may be due to the lower levels of _hsa-mir-376a_49g_ and _hsa-mir-376c_48g_ in ccRCC, respectively, which may contribute to the initiation and/or progression of

ccRCC. Reduced A-to-I editing level of miRNAs were also noticed previously38,39. The editing levels of _hsa-mir-376a-1_49_A_g_ and/or _hsa-mir-376c_48_A_g_ were also reduced in many other

cancers, such as glioblastoma94 and lung cancer95. The increased expression of _BCAT1_ and _MFTHD2_ might be due to the reduced editing levels of _hsa-mir-376a-1_49_A_g_ and

_hsa-mir-376c_48_A_g_ in many cancers. Furthermore, it has been shown that the higher the editing level of _hsa-mir-376c_48_A_g_ site in ccRCC, the better the prognosis and the longer the

survival time of patients38. Therefore, reduced editing levels of _hsa-mir-376a-1_49_A_g_ and _hsa-mir-376c_48_A_g_ might represent a general mechanism in the initiation and/or progression

of different cancers. _RASSF8_ has been reported to be a tumor suppressor gene with lower expression in gastric cancer96,97, colorectal cancer98,99, cervical cancer100, ovarian cancer101,

melanoma102, esophageal squamous cell carcinoma103, lung cancer104,105 and osteosarcoma106. In addition, _RASSF8_ is a potential therapeutic target for the prevention of many

cancers97,100,103,105. In this study, _RASSF8_, the target gene of _hsa-mir-29c_59u_, was downregulated in ccRCC. Therefore, _RASSF8_ may also play similar tumor suppressor function in

ccRCC, and the higher level of _hsa-mir-29c_59u_ in ccRCC may lead to the decreased expression of _RASSF8_ in ccRCC, which consequently promotes the initiation and/or progression of ccRCC.

As shown in Fig. 5G–I, some genes with many PAR-CLIP reads were identified as targets of _hsa-mir-376a-1_49g_ and _hsa-mir-376c_48g_, and _hsa-mir-29c_59u_, respectively. Although there

currently are limited evidences about their functions in ccRCC, our results suggest that these genes represent promising directions for revealing the mechanisms of ccRCC in the future. In

summary, we presented a comprehensive view of miRNA editing and/or modification events in ccRCC, which promoted our understanding of miRNA editing and/or modification events in ccRCC. More

researches are needed in the future to clarify the functional roles of different miRNA editing patterns in the pathogenesis of ccRCC. Our results also provided new clues for the clinical

treatment of ccRCC, such as to promote the editing levels of _hsa-mir-376a_49_A_g_ and _hsa-mir-376c_48_A_g_ and to repress the editing level of _hsa-mir-29c_59_C_u_. METHODS SMALL RNA-SEQ

DATA USED We collected 176 small RNA-Seq (sRNA-seq) profiles of ccRCC patients and healthy controls, including 154 samples of cancer tissue and 22 normal kidney tissue samples. These 176

sRNA-seq profiles were obtained from previous studies107,108, and their accession numbers were shown in Supplementary Table S1.1. The qualities of these sRNA-seq sequence data were evaluated

with FastQC (v0.11.9)109. GENOME AND ANNOTATION OF MIRNAS USED The human genome sequence used was GRCh38, and downloaded from the UCSC Genome Browser110. The pri-miRNA sequences in GFF3

format and mature miRNA annotation files were derived from miRBase (v21)111. IDENTIFICATION OF MUTATION AND EDITING SITES IN MIRNAS Totally, 176 sRNA-seq profiles were analyzed using the

MiRME pipeline with default settings43. Briefly, the raw reads were checked to retain the qualified reads with the sequencing scores greater than 30 for the first 25 nucleotides. Then, reads

of at least 18 nt were retained after removal of the 3\({\prime }\) adapters. BLASTN112 was used to compare the retained reads with the pre-miRNAs and the reads mapped to pre-miRNAs were

retrieved. These reads, which were mapped to pre-miRNAs, were then aligned with the genome using Bowtie (v1.0.0)113. Then, the cross-mapping correction algorithm28 was used to examine the

alignment of reads to the genome to calculate the weights or percentages of reads at different genomic loci. Results from different samples were then combined using separate programs in the

MiRME package43,55. According to the location of M/E sites in miRNAs and mutations status of dbSNP, the M/E sites were divided into nine different editing types, i.e., A-to-I, C-to-U,

3\(^{\prime }\)-A, 3\(^{\prime }\)-U, 3\(^{\prime }\)-Other, 5\(^{\prime }\)-editing, Other, SNP and Pseudo43. The identified M/E site was named with the pre-miRNA name, M/E site position in

pre-miRNA, original nucleotide in upper case, the edited/mutated nucleotide in lower case. For example, _hsa-mir-376c_48_A_g_ means an A-to-I editing at the 48th nucleotide of

_hsa-mir-376c_. And edited miRNA was named by the pre-miRNA name, the M/E site position in pre-miRNA, and the edited/mutated nucleotide in lower case. For example, _hsa-mir-376c_48g _ is the

A-to-I edited _miR-376c-3p_. The criteria for defining M/E sites with significant editing levels were as follows: (i) the relative levels of editing were at least 5%; (ii) editing events

were supported by at least 10 reads; (iii) the threshold for sequencing reads score was 30; (iv) multiple test corrected _p_-values (with the Benjamini and Hochberg method114) were smaller

than 0.05. In order to remove M/E sites due to random sequencing errors, 1025 M/E sites that had significant editing levels in at least 10% of the 176 samples (18 samples) used in this study

were retained for further analysis. The identified M/E sites were compared with known human miRNA editing sites, including the DARNED database115, the RADAR database116 and relevant

literature27,29,34,43,95,117,118. Finally, A-to-I, C-to-U, and Other predicted M/E sites were manually checked. IDENTIFICATION OF SNPS SITES The identified M/E sites were compared with the

dbSNP (v151) database119 and previously reported SNPs in miRNAs44. An M/E site was considered as SNP if it satisfied the following criteria: (i) the genomic position of M/E site and SNP was

identical, (ii) the original and edited nucleotides had the same nucleotides as the SNP’s allele, (iii) the M/E site had editing level of 100% in at least one of the 176 samples selected,

and (iv) the M/E site occurred in the center of the miRNA. IDENTIFICATION OF M/E SITES WITH SIGNIFICANTLY DIFFERENT EDITING LEVELS IN CCRCC The Mann-Whitney _U_-tests were used to analyze

the differences between the editing levels of 1025 miRNA M/E sites in ccRCC (n = 154) and normal samples (n = 22). The _p_-values were corrected with the Benjamini-Hochberg correction

method114. The M/E sites with corrected _p_-values smaller than 0.05 were defined as having significantly different editing levels in ccRCC. DESeq2120 was used to analyze different

expression levels (TPTM) of edited miRNAs between ccRCC and normal control samples. The miRNAs with corrected _p_-values smaller than 0.05 were defined as having different expression levels

in ccRCC and normal control samples. IDENTIFICATION OF TARGETS FOR ORIGINAL AND EDITED MIRNAS Among the editing sites with significant differences in editing levels between ccRCC tumors and

normal tissues, a total of five editing events occurred in seed regions of mature miRNAs. We chose two A-to-I editing sites (_hsa-mir-376a-1_49_A_g_ and _hsa-mir-376c_48_A_g_) and one C-to-U

editing site (_hsa-mir-29c_59_C_u_), because their editing levels and the levels of their corresponding edited miRNAs had significant differences in ccRCC tumor tissues compared to normal

controls. Then, we predicted the targets of original and edited miRNAs using the MiCPAR algorithm55. As shown in Supplementary Table S1.2, 11 PAR-CLIP sequences were used in the

identification of miRNA targets and were downloaded from the NCBI SRA database. Seven PAR-CLIP profiles of HEK293 cell lines stably expressing FLAG/HA-tagged AGO1, AGO2, AGO3, and AGO4

proteins were reported by54. Another study included four PAR-CLIP profiles derived from HEK293 cell lines stably expressing HIS/FLAG/HA-tagged AGO1 and AGO2 proteins121. In order to obtain

reads of acceptable quality, the raw reads of these 11 PAR-CLIP profiles were filtered to keep reads with sequencing scores of at least 30 for their first 25 nucleotides from 5\({\prime }\)

ends. The qualified reads were combined and the targets of miRNA were identified by the MiCPAR algorithm. The targets with at least one PAR-CLIP read with T-to-C variation were retained for

further analysis. ANALYZING EXPRESSION OF TARGETS OF EDITED MIRNAS In order to understand the expression of targets of edited miRNAs in ccRCC tumor tissues, we identified genes that were

significantly differentially expressed in ccRCC samples compared to normal samples. We collected three batches of gene expression profiles of ccRCC and controls (Supplementary Table S1.3),

of which two batches were obtained from107,122. Another set of gene expression profiles was obtained from TCGA (https://portal.gdc.cancer.gov/). The edgeR (v3.34.1) package123 was used for

differential analysis of target genes. The glmFit and glmLRT functions in edgeR were used to build generalized linear models and to perform likelihood ratio tests, respectively. Genes with

corrected _p_-values smaller than 0.05 were defined as having significantly different expression levels in ccRCC. FUNCTIONAL ANALYSIS OF NEW TARGET GENES OF EDITED MIRNAS We kept targets

with at least one PAR-CLIP read with T-to-C variation. Then, the targets of original and edited miRNAs were compared to obtain the new targets of edited miRNAs. For edited miRNAs with

increased editing levels in ccRCC, we compared their targets with genes that were downregulated in ccRCC because miRNAs normally repressed their target genes, and vice versa. We also

analyzed the numbers of PAR-CLIP reads for the targets of edited miRNAs. We manually examined the functional relevance of some selected targets by reading the literature of the genes in the

NCBI Gene database. The targets with more PAR-CLIP reads and functional relevance in ccRCC were preferred in our analysis. KOBAS3.0124 was used to perform enrichment analysis of GO terms and

KEGG pathways for new target genes of edited miRNAs. Significantly enriched GO terms and KEGG pathways were filtered with multiple test corrected _p_-values smaller than 0.05. DATA

AVAILIBILITY The 176 sRNA-seq sequencing profiles and 11 PAR-CLIP sequencing profiles were obtained from NCBI SRA database, and 3 gene expression profiles were obtained from NCBI GEO and

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supported in part by a grand (No. 31460295) of the National Natural Science Foundation of China and an Open Research Fund (No. SKLGE-2107) of State Key Laboratory of Genetic Engineering,

Fudan University, China to YZ. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming

University of Science and Technology, Kunming, 650500, Yunnan, China Yulong Liu, Wanran Li & Chunyi Mao * College of Landscape and Horticulture, Yunnan Agricultural University, Kunming,

650201, Yunnan, China Shiyong Guo, Wenping Xie, Huaide Yang, Wanran Li, Nan Zhou, Guangchen Zhou, Chunyi Mao & Yun Zheng * Faculty of Life Science and Technology, Kunming University of

Science and Technology, Kunming, 650500, Yunnan, China Wenping Xie * Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650500, Yunnan,

China Huaide Yang * School of Criminal Investigation, Yunnan Police College, Kunming, 650223, Yunnan, China Jun Yang Authors * Yulong Liu View author publications You can also search for

this author inPubMed Google Scholar * Shiyong Guo View author publications You can also search for this author inPubMed Google Scholar * Wenping Xie View author publications You can also

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publications You can also search for this author inPubMed Google Scholar * Yun Zheng View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS Y.L.:

data curation, formal analysis, investigation, validation, visualisation, writing - original draft; S.G.: data curation, formal analysis, investigation, validation, visualisation; W.X.: data

curation, formal analysis, investigation, validation; H.Y.: data curation, formal analysis; W.L.: investigation, validation; N.Z.: formal analysis, visualisation; J.Y.: formal analysis;

G.Z.: validation; C.M.: validation; Y.Z.: conceptualisation, formal analysis, funding acquisition, methodology, project administration, resources, software, supervision, writing - review

& editing. CORRESPONDING AUTHOR Correspondence to Yun Zheng. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PUBLISHER'S

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microRNA editing sites in clear cell renal cell carcinoma. _Sci Rep_ 13, 15117 (2023). https://doi.org/10.1038/s41598-023-42302-y Download citation * Received: 15 May 2023 * Accepted: 07

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