RETRACTED ARTICLE: HnRNP A1 - mediated alternative splicing of CCDC50 contributes to cancer progression of clear cell renal cell carcinoma via ZNF395

Forty-eight pairs of ccRCC samples and corresponding adjacent noncancerous tissues were obtained from primary ccRCC patients who underwent radical or partial nephrectomy in Tongji hospital between January 2015 and December 2017. The usage of human specimens was approved by the ethics committee of Tongji medical college, Huazhong University of Science and Technology, and written informed consent was obtained from each patient before surgery. The medical records of these patients were retrieved, and demographic characteristics, clinicopathological information, and survival data were recorded and analyzed in our further study.

Human renal cancer cell lines (786-O, A498, OS-RC-2) were cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) at 37 °C in humidified atmosphere with 5% CO₂, while other renal cancer cell line (ACHN), normal renal epithelial cells human kidney 2 (HK-2), and human embryonic kidney 293 (HEK293) were maintained in DMEM with 10% FBS.

Target fragments were inserted into lentiviral vectors such as pCDH-MSCV-MCS-EF1-copGFP (System biosciences, USA) and pSiCOR (Addgene, #11597), all plasmids were verified by DNA sequencing. Together with pGC-LV, pHelper 1.0, and pHelper 2.0 plasmids, recombinant lentiviral vectors were transfected into HEK293 cells, in which recombinant lentivirus was generated. Target cells were infected with lentivirus, then treated with puromycin for 14 days. After the efficiency of overexpression or depletion plasmids was confirmed, surviving cells were used for further experiments.

Total RNAs of cells or tissues were extracted using TRIzol reagent (Invitrogen, USA), and then reverse transcribed into cDNA using the Prime-Script™ one step real-time polymerase chain reaction (RT-PCR) kit (TAKARA, China). Semi-quantitative RT-PCR was performed with 2× Taq PCR Master Mix (Thermo Fisher Scientific, USA). GAPDH was used as internal control. RT-qPCR was performed using SYBR Green Mix (Roche, Germany). All primers used in our study were listed in Supplementary table 1 (Additional file 1).

FISH was performed on 12 pairs ccRCC and corresponding normal tissues in Wuhan Servicebio Technology following the manufacturer’s protocol. We labelled the truncated or full-length transcript with green or red fluorescence, respectively. The probe for truncated transcript was located at the junction fragment of exon 5 and exon 7, while probe for full-length transcript at exon 6. The fluorescence dots were counted by two experienced pathologists to represent the RNA expression of two CCDC50 isoforms.

In colony formation assays, approximately 1000 cells were seeded into six-well plates and cultured for two-weeks, the numbers of cell colonies were calculated after staining cells with crystal violet. In EdU incorporation assays, nucleus of proliferative cells were stained with red fluorescence while all nucleus could be stained with blue fluorescent light. In MTS assay, cells were treated with corresponding kit and then seeded into 96-well microplates at a density of 1000 cells per well, and the absorbance at 490 nm of each well was measured at different time points.

About 1 × 10⁵ of 786-O cells or 1.5 × 10⁵ OS-RC-2 cells were plated in the upper chambers of 24-well Transwell plates (Corning, USA) in FBS-free medium, and complete medium with 10% FBS was deposited in the lower chambers to serve as a chemo-attractant. For in vitro migration assay, cells which passed through the Transwell filter after 12 h were remained and stained by crystal violet. For in vitro invasion assay, Transwell membranes were coated with Matrigel prior to plating cells, cells which passed through the Matrigel membrane and Transwell filter after 24 h were stained and calculated. The relative number of passed cells represented the cells’ abilities of migration or invasion.

Following antibodies were used in western blot: anti-CCDC50 (ab127169, Abcam), anti-ZNF395 (11759–1-AP, Proteintech), anti-HnRNP A1 (ab5832, Abcam), anti-β-actin (BM0627, Boster), anti-PCNA (10205–2-AP, Proteintech), anti-Cyclin D1 (60186–1-Ig, Proteintech), N-Cadherin (22018–1-AP, Proteintech), anti-Vimentin (BM0135, Boster), anti-ZEB1 (3396, Cell Signaling Technology), anti-VEGF (19003–1-AP, Proteintech), goat anti-mouse IgG HRP-linked whole antibody (31,430, Thermo Scientific), and goat anti-rabbit secondary antibody (31,460, Thermo Scientific).

RIP experiments were implemented to analyze the binding of HnRNP A1 to CCDC50 mRNA using Magna RIP Kit (17–701, Millipore) according to the manufacturer’s instructions.

For the subcutaneous injection experiment, 5 × 10⁶ OS-RC-2 cells were injected subcutaneously into 8 mice per group at a single site. Tumor sizes were measured and calculated every 5 days. At day 25, mice were executed and tumors were excised and weighted. For the caudal vein injection experiment, 1 × 10⁶ OS-RC-2 cells were injected into 4 mice per group at the tail vein. Finally, lungs were resected and prepared for hematoxylin and eosin (H.E.) staining.

The data were presented as the mean ± standard deviation (SD). Differences among groups were determined by a two-way analysis of variance followed by a post hoc Tukey test. Comparisons between two groups were performed using an unpaired Student t test. Survival curve was plotted using the Kaplan-Meier method and compared with the log-rank test. A value of P < 0.05 was considered as statistically significant. P < 0.05, P < 0.01 and P < 0.001 were marked as ‘*’, ‘**’, ‘***’.

The dysregulation of alternative RNA splicing plays a critical role in tumor development and progression. However, the roles of spliced variants and splicing factors that control splicing dysregulation in ccRCC carcinogenesis are still largely unexplored. In order to have a better understanding of the splicing events in ccRCC, we firstly analyzed the RNA-seq data of TCGA. We obtained the exon skip data of Kidney renal clear cell carcinoma (KIRC) from TCGA SpliceSeq Database (http://​bioinformatics.​mdanderson.​org/​TCGASpliceSeq/​singlegene.​jsp). This database provided the splicing information of 533 tumor samples and 72 normal tissues, so the data of 72 pairs of ccRCC tissues and corresponding adjacent noncancerous tissues were analyzed. The mean percent spliced-in index (PSI) value in both tumor samples and paired normal tissues were calculated and statistically compared. Candidate exon skip events in ccRCC were identified if the absolute difference value between cancer group and normal group was higher than 0.3 with statistical significance (Fig. 1a).

Dysregulated CCDC50 exon splicing was identified as a candidate splicing event after our analysis. The mean PSI in 72 tumors and all 533 tumors was 0.081 ± 0.049 and 0.124 ± 0.142, while the mean PSI in 72 paired normal tissues was 0.468 ± 0.146 (p < 0.01) (Fig. 1b). Apart from KIRC, significantly lower mean PSI in tumor tissues was also found in many types of other cancer (Fig. 1c). Furthermore, we retrieved the relative expression data of each exon of CCDC50 in ccRCC samples, which showed that the expression levels of all exons were significantly higher in renal cancer except for exon 6, with an attenuated expression in tumor tissues (Fig. 1d). We further evaluated the significance of CCDC50 alternative splicing for prognosis prediction using TCGA data. Kaplan-Meier curves showed that higher PSI was associated with better recurrence-free survival (hazard ratio [HR]: 0.6425, 95% confidence interval [CI]: 0.4421–0.9337, p = 0.0212) (Fig. 1Ea), although higher PSI had no significant predictive value for overall survival (HR: 0.9167, 95% CI: 0.6762–1;243, p = 0.5753) (Fig. 1Eb). Moreover, we investigated the relationship of CCDC50 alternative splicing and prognosis of 48 patients from our hospital. Interestingly, Kaplan-Meier curves showed that higher PSI was significantly related to both better recurrence-free survival (HR: 0.3901, 95% CI: 0.1573–0.9674, p = 0.0240) (Fig. 1Fa) and overall survival (HR: 0.3593, 95% CI: 0.1288–1.002, p = 0.0469) (Fig. 1Fb).

The CCDC50 gene can generate two mRNA transcripts through pre-mRNA alternative splicing. The pre-mRNA of CCDC50 consists of 12 exons and 11 introns. Exon 6 (528 bp) can be regulated by alternative splicing, and skipping and inclusion of exon 6 can generate the truncated (CCDC50-S) or full-length transcript (CCDC50-FL), respectively. The length of coding sequence (CDS) for different transcript is 921 bp and 1449 bp, which further generates protein products with 306 or 482 amino acids (Fig. 2a). We made further efforts to explore whether the expression pattern of CCDC50 transcripts existed in our ccRCC and normal tissues or renal cell lines. Semi-quantitative RT-PCR analysis of 12 pairs of ccRCC samples and corresponding noncancerous tissues revealed that CCDC50-FL was predominately examined in normal tissues and barely appeared in ccRCC tissues, while CCDC50-S was significantly more abundant in cancerous tissues (Fig. 2b). Moreover, compared to human immortalized kidney proximal tubular cell HK-2, all renal cancer cell lines showed notable elevated expression of CCDC50-S, while the full-length transcript was quenched in cancer cells (Fig. 2c). We also examined the subcellular localization of CCDC50 protein isoforms, both isoforms localized in the cytoplasm of OS-RC-2 cells (Fig. 2d). Furthermore, we conducted RT-qPCR using primers which amplified shared exons of both transcripts or separated exon 6 of CCDC50 to examine the expression of total CCDC50 transcripts and CCDC50-FL in 12 pairs tissues. The results demonstrated higher overall CCDC50 expression in majority of tumor samples, while exon 6 expression levels were significantly more abundant in normal tissues (Additional file 2, Supplementary Figure 1A-1B).

To further validate the aberrant alternative splicing of CCDC50, we conducted FISH to label CCDC50-S with green fluorescence and CCDC50-FL with red fluorescence using 12 pairs ccRCC and corresponding normal tissues. The results showed that CCDC50-S was extremely elevated in tumor samples, while paired normal samples presented significantly more CCDC50-FL, which is in accordance with the results above (Fig. 2E-Fa). We next assessed the association between the expression of CCDC50 transcripts and clinicopathological features. We found that CCDC50-S expression increased significantly when T stage and Fuhrman Grade advanced, although CCDC50-FL showed no significant difference (Fig. 2Fb-Fc).

We first assessed the tumorigenic effects of CCDC50 isoforms on ccRCC cells to have a better understanding of the importance of CCDC50 in regulating renal cancer biology. RCC cell lines stably overexpressing CCDC50-S or CCDC50-FL, and stably silencing the CCDC50 transcripts with short hairpin RNA (shRNAs) were constructed and validated (Additional file 2, Supplementary Figure 2A-2B). Stable overexpression of CCDC50-S in RCC cell lines accelerated the cell proliferation and survival abilities as shown by colony formation, EdU incorporation assay and MTS, while ectopic expression of CCDC50-FL exhibited opposite effects on cells (Fig. 3a-c). Besides, two shRNAs which deprived the mRNA and protein expression of CCDC50 significantly repressed the cell proliferation (Fig. 3a-c). We also performed Transwell assays to examine the cell migration and invasion abilities, the results showed that CCDC50-S overexpression significantly promoted cell migration and invasion, but CCDC50-FL exerted adverse effects (Fig. 3d-e). Furthermore, the silence of CCDC50 transcripts obviously inhibited cell migration and invasion (Fig. 3d-e). Given that the predominant transcript of CCDC50-S, these results validated that CCDC50-S exerted an oncogenic function on ccRCC in vitro, while CCDC50-FL played tumor-suppressive roles in ccRCC.

Xenograft experiments in immunodeficient mice also supported this conclusion, as OS-RC-2 cells with CCDC50-S overexpression exhibited accelerated tumor growth velocity and larger tumors, while CCDC50-FL in OS-RC-2 cells emerged as inhibitor for tumor growth (Fig. 3f). Additionally, OS-RC-2 cells with sh-CCDC50 inhibited tumor growth significantly (Fig. 3f). Furthermore, we constructed caudal vein injection model and performed H.E. staining on lung metastases in order to assess the metastasis ability of OS-RC-2 cells with different transcripts. The results validated that CCDC50-S promote tumor metastasis, but CCDC50-FL and sh-CCDC50 suppressed tumor metastasis ability (Fig. 3g-h).

Alternative splicing is strictly regulated by the interaction between multiple trans-acting proteins and corresponding cis-acting silencers and enhancers on the pre-mRNA [18]. Splicing factors are regulatory proteins with pre-mRNA - binding potential, such as serine and arginine-rich (SR) proteins and heterogeneous nuclear ribonucleoproteins (hnRNPs). Firstly, using TCGA gene expression RNAseq data, we sought to identify splicing factors with differential expression in ccRCC (data not shown). Besides, we previously found that many splicing factors presented differential expression in renal cancer by microarray [19]. We reasonably conjectured that among these differentially expressed splicing factors, some might regulate the CCDC50 alternative splicing. Thus, in order to explore the effects of splicing factors on CCDC50 pre-mRNA splicing, we constructed a series of shRNA plasmids targeting these splicing factors, namely HnRNP A1, HnRNP A2B1, HnRNP A3, HnRNP H3, PTBP1 (HnRNP I), PSIP1, SFPQ, SRPK3, SRSF1, SF3A1, SF3A2, SF3B3. Furthermore, we constructed overexpression plasmids of several splicing factors according to our initial semi-quantitative RT-PCR results. We then treated HEK293 cells with these plasmids of interest and control plasmids, and examined the expression of two isoforms via semi-quantitative RT-PCR. Combining the TCGA expression data with our PCR results, we found that HnRNP A1 promoted the skipping of exon 6, which was proved by the increase of the PSI (portion of full-length transcript) by sh-HnRNP A1 and obvious decrease of PSI by HnRNP A1 overexpression (Fig. 4a). Furthermore, Pearson correlation analysis indicated that the relative expression of HnRNP A1 was negatively correlated with the expression level of CCDC50 exon 6 (r = − 0.361, p < 0.0001) in TCGA cohort (Fig. 4b), which was in accordance with the theory that HnRNP A1 impeded the inclusion of exon 6 and decreased the proportion of full-length transcript. As we have shown in Fig. 2c, we did not detect any full-length CCDC50 transcript in RCC cell lines, therefore, we had to construct a splicing minigene which included the full-sequence of exon 5, exon 6, exon 7 and flanking part of intron 5 and intron 6. This minigene generated two transcripts with length of 722 bp and 198 bp (Fig. 4c). After stably transfecting 786-O and OS-RC-2 cells with minigene, we treated these cells with HnRNP A1 expressing vector or shRNAs against HnRNP A1. The results in 786-O (Fig. 4Da) and OS-RC-2 (Fig. 4Db) both demonstrated that HnRNP A1 overexpression decreased the full-length transcript while knockdown of HnRNP A1 increased the relative expression of full-length transcript. Furthermore, we examined the regulation effect of HnRNP A1 on CCDC50 at protein level in cells transfected with HnRNP A1 or sh-HnRNP A1 plasmids, and the results confirmed the conclusion of minigene experiment (Fig. 4Ea-Eb). In addition, using the RIP with anti-HnRNP A1 antibody, we detected an enrichment of CCDC50-S and pre-mRNA sequence on HnRNP A1 protein, which validated that HnRNP A1 could bind to CCDC50 pre-mRNA (Fig. 4f). These data also strengthened our conclusion that HnRNP A1 could regulate the alternative splicing of CCDC50 pre-mRNA by promoting skipping of its exon 6.

Since the role of HnRNP A1 in renal cancer remain undiscovered, we further explored its expression level and biological functions in ccRCC. TCGA data showed that HnRNP A1 was significantly overexpressed in KIRC (Additional file 2, Supplementary Figure 3A). Then, we evaluated the expression pattern of HnRNP A1 in renal cancer cell lines, which validated the overexpressed pattern of HnRNP A1 in these cell lines (Additional file 2, Supplementary Figure 3B). Together, these revealed that HnRNP A1 expression level might help to predict the prognosis of ccRCC patients.

In addition, we studied the biological functions of HnRNP A1 in renal cancer cell lines. We constructed and validated renal cancer cell lines stably overexpressing HnRNP A1 and stably silencing HnRNP A1 with shRNA (Additional file 2, Supplementary Figure 4). As shown in Fig. 5a-c, knockdown of HnRNP A1 significantly reduced the proliferative ability of 786-O and OS-RC-2 cells, while ectopic expression of HnRNP A1 increased these capacities of renal cancer cells. Moreover, Transwell assay supported that HnRNP A1 could increase the migration and invasion capacities of two renal cancer cell lines (Fig. 5d-e).

We further conducted rescue assay to evaluate the regulatory correlation between CCDC50 and HnRNP A1. Overexpression of CCDC50-S could reverse the reduction of proliferation and migration ability caused by HnRNP A1, while overexpression of CCDC50-FL had no significant effect (Additional file 2, Supplementary Figure 5A-5C). These findings consolidated our theory that HnRNP A1 could exert its oncogenic function in ccRCC through modulating the alternative splicing of CCDC50 and increasing the relative expression of truncated CCDC50.

As the truncated transcript of CCDC50 was the predominant transcript which exerted oncogenic functions, we sought to identify its downstream molecules and corresponding mechanism which explained its roles in ccRCC. Through digging from TCGA data and the RNAseq data from previous article about CCDC50, we found that ZNF395, PFKFB4, SLC2A3, LAMP1, BNIP3L and TP53I3 were among the most affected proteins after CCDC50 knockdown. Because CCDC50-S was the main transcript and CCDC50-FL was hard to detect in renal cancer tissues and cell lines, we used CCDC50 knockdown plasmid to represent the knockdown of CCDC50-S. Our RT-qPCR and western blot results validated that the mRNA and protein expression levels of ZNF395 were attenuated after CCDC50 knockdown in vitro, and the tendency was reversed after ectopic expression of CCDC50-S (Fig. 6Aa and Ab), while the other candidate genes were not obviously influenced by CCDC50 knockdown or overexpression (data not shown). Interestingly, RT-qPCR also showed that CCDC50-FL overexpression could attenuate the expression level of ZNF395 (Additional file 2, Supplementary Figure 6). Furthermore, our RT-qPCR results in renal cancer cell lines and 12 pairs ccRCC tissues elucidated the enhanced expression pattern of ZNF395 (Fig. 6Ba and Bb). Kaplan-Meier curve also indicated that higher expression of ZNF395 was significantly capable of predicting worse overall survival of ccRCC patients in TCGA (Additional file 2, Supplementary Figure 7). RNA-seq data in 17 cancer types generated by the TCGA demonstrated the enriched expression of ZNF395 in renal cancer compared to other cancer types (Additional file 2, Supplementary Figure 8), which highlighted the possible pivotal roles of ZNF395 in ccRCC carcinogenesis.

After the RCC cell lines stably overexpressing ZNF395 or silencing ZNF395 with shRNA was constructed and validated (Additional file 2, Supplementary Figure 9), we made an inquiry for the specific roles of ZNF395 in renal cancer. The colony formation, EdU, and Transwell assays proved unequivocal evidence that ZNF395 was a pro-proliferative protein which also promoted cell migration and invasion (Fig. 6c-f). We further conducted western blot to find that ZNF395 exerted its oncogenic function through proliferation, epithelial - mesenchymal transition (EMT), and angiogenesis pathways (Fig. 6g).

Finally, we evaluated the association of CCDC50-S combined with HnRNP A1 or ZNF395 and the overall survival of renal cancer patients in TCGA. Kaplan-Meier curves showed that high CCDC50-S / high HnRNP A1 was associated with poor overall survival (p = 0.0079), while there was no significant relation between high CCDC50-S / high ZNF395 and overall survival (p = 0.64) (Additional file 2, Supplementary Figure 10A-10B).