Dysregulation of Alternative Splicing Contributes to Multiple Myeloma Pathogenesis

doi:10.21203/rs.3.rs-1649660/v1

Download PDF

Article

Dysregulation of Alternative Splicing Contributes to Multiple Myeloma Pathogenesis

https://doi.org/10.21203/rs.3.rs-1649660/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Dysregulation of alternative splicing (AS) triggers many tumors, understanding the roles of splicing factors and splicing events during tumorigenesis would open new avenues for targeted therapies in multiple myeloma (MM). We show here that GSEA reveals a significant difference in the expression pattern of the alternative splicing pathway genes, notably enriched in MM patients. Upregulation of the splicing factor SRSF1 is observed in the progression of plasma cell dyscrasias and predicts MM patients’ poor prognosis. The c-indices of the Cox model indicated that SRSF1 improved the prognostic stratification of patients with MM. Moreover, SRSF1 knockdown exerts a broad anti-myeloma activity in vitro and in vivo It is further found that the up-regulation of SRSF1 is caused by the transcription factor YY1, which also functions as an oncogene in myeloma cells. Through RNA-Seq, we systematically verify that SRSF1 promotes the tumorigenesis of myeloma cells by switching the AS of RBBP6. Together, our results emphasize the importance of the splicing factor SRSF1-mediated AS for promoting tumorigenesis of MM. SRSF1 might be considered as a valuable therapeutic target and a potential prognostic biomarker for MM.

Multiple myeloma (MM) is a cancer of neoplastic plasma cells that is typically accompanied by clonal proliferation of malignant plasma cells in the bone marrow microenvironment, monoclonal protein in the blood or urine, and associated organ dysfunction (1). The introduction of proteasome inhibitors, immunomodulatory drugs, antibodies targeting cell surface molecules, high-dose therapy and autologous stem-cell transplantation (ASCT) has markedly improved outcomes in patients with multiple myeloma (2). Despite multiple therapeutic advances, almost all people with multiple myeloma eventually become resistant to treatment and die of the disease (3). It is preceded by monoclonal gammopathy of undetermined significance (MGUS), an asymptomatic premalignant accumulation of clonal plasma cells that shares genetic features with MM (4). Multiple myeloma is difficult to treat because physicians have conventionally delayed therapy until end-organ damage, which in myeloma consists of bone destruction, anemia and renal failure, is detected (2, 5). It is time to improved understanding of molecular abnormalities related to disease initiation and progression, and of how genes were altered in tumor cells, enabled the development of new drugs, including interventions based on biomarkers for personalized therapeutic treatment of specific molecular subtypes.

Alternative splicing (AS) is a key control point in generation of distinct mRNA and protein isoforms from a single gene (6). Cancer cells have general as well as cancer type-specific and subtype-specific alterations in the splicing process that can have prognostic value and contribute to every hallmark of cancer progression (7). Splicing perturbations are common in cancer and are associated with altered expression of the components of the splicing machinery (8). The spliceosome, composed of five small nuclear ribonucleoproteins (snRNPs) and numerous additional proteins. RNA-binding motif (RBM) proteins, arginine–serine-rich (SR) proteins and heterogeneous nuclear ribonucleoproteins (hnRNPs) are the major class of alternative splicing decisions (6).

SR family characterized by RNA-recognition motifs (RRM) and an RS domain is composed of 12 members, which can bind directly to a pre-mRNA and elicit changes in its AS (9). Transcriptome-wide analyses have uncovered numerous splicing-related RBPs that are differentially expressed in tumors when compared with normal tissues (10). However, the role of alternative splicing in myeloma is still not completely understood, so it is worthy of exploration.

Therefore, we sought to elucidate the expression, clinical relevance, biological function, and underlying mechanism of alternative splicing in MM. In this study, three main questions are addressed: (a) does alternative splicing events facilitate tumorigenesis and progression of MM, (b) What is the candidate mechanism underlying the aberrant AS in MM, (c) can we considered the crucial splicing factor SRSF1 as a promising therapeutic target and a prognostic factor for MM?

Cell cultures

MM.1S and LP-1 cells were cultured at 37°C in an atmosphere containing 5% CO2 and in RPMI-1640 medium (Hyclone, USA) supplemented with 10% Fetal Bovine Serum (FBS). 293T cells maintained in DMEM high glucose medium plus 10% FBS. Cell line authentication was performed by cell line characterization core using short tandem repeat profiling (Genetic Testing Biotechnology Corporation, China).

Small-interfering RNA (siRNA) transfection

Small interfering RNAs and scrambled control non-targeting siRNA were synthesized by GenePharma (Shanghai, China). To downregulate SRSF1, YY1 and RBBP6 iso1, small interfering RNAs were transfected into cells, respectively. The transfections were performed per instructions provided by the manufacturer (Neon™). The transfected cells were incubated at 37°C with 5% CO₂ for 48h. The sequences of siRNAs are shown in supplementary table 1.

Western blot

Cells were crushed with RIPA buffer (150 PCL NaCl, 0.5% sodium deoxycholate, 0.1%, SDS, 1% NP40, 1 PCL EDTA and 50 PCL Tris pH 8.0). Proteins were quantitated by using the BCA (Boyetime, China) according to the manufacture’s instruction, followed by separation with SDS–PAGE and transferred to PVDF membranes. The membranes were blocked for 60 min with 5% bovine serum albumin in TBST and blotted with the following primary antibodies for 12–16 h at 4 °C:GAPDH (Proteintech 10494-1-AP), α/β-Tubulin (CST 2148S), SRSF1 (Abcam 129108), YY1 (CST 46395S), RBBP6 (Abcam ab237514). After washing with TBST three times, membranes were incubated with HRP-conjugated secondary antibodies for visualization.

shRNA-mediated SRSF1 Knockdown

The lentiviral-based vector LV16 (U6/Luciferase17&Puro) was used to express shRNA in cells. LP-1 cells were transduced with lentiviruses expressing luciferase and shRNAs (shRNA KD1, 5’-GGAACAACGATTGCCGCAT -3’ [GenePharma]; shRNA KD2, 5’- GGTCGCGACGGCTATGATT-3’ [GenePharma]; shRNA KD3, 5’- GGACTGCCTCCAAGTGGAA-3’ [GenePharma]) and control shRNA. The selection of efficiently transduced cells was achieved by treatment with puromycin (2 mg/mL final concentration). LP-1 were transfected lentiviruses according to the instruction, 24h after transfection, cells were collected and Dual-Luciferase reporter assays were performed using the Dual-Luciferase Reporter Assay System (Promega) following product protocol. According to the effects of these shRNAs, we selected shRNA KD1 to perform the in vivo experiment.

RNA sequencing

Total RNA was extracted using the mirVana miRNA Isolation Kit (Ambion) following the manufacturer’s protocol. RNA integrity was evaluated using the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The samples with RNA Integrity Number (RIN) ≥ 7 were subjected to the subsequent analysis. The libraries were constructed using TruSeq Stranded mRNA LTSample Prep Kit (Illumina, San Diego, CA, USA) according to the manufacturer’s instructions. Then these libraries were sequenced on the Illumina sequencing platform (HiSeqTM 2500 or Illumina HiSeq X Ten) and 125bp/150bp paired-end reads were generated.

Chromatin immunoprecipitation (ChIP)

ChIP assays were performed using SimpleChIP Plus Sonication Chromatin IP Kit (Cell Signaling) according to the manufacturer’s instructions. Briefly, 293T cells (1´ 10⁷) treated with dimethyl sulfoxide (2 mM) were fixed with formaldehyde to cross-link DNA and proteins, chromatin was sheared using Microson Ultrasonic Cell Disruptor XL (Misonix) (16 cycles of sonication: 15 s each, 2-min rest; amplitude = 10, power = 15 W), chromatin (10 mg) was incubated with antibodies (Sp1 at 7 ml, Ets1 at 10 ml, p65 at 10 ml, histone H3-positive control at 10 ml, and IgG negative control at 2 ml), and immunoprecipitates were bound to protein G magnetic beads (30 ml). The protein-DNA crosslink was reversed, DNA was purified, and enrichment of DNA sequences was detected using qPCR and primers listed in supplementary table 2. Data were normalized and analyzed using fold enrichment analysis.

Statistical analysis

Survival analysis was performed to investigate the associations between the censored outcomes and the clinical variables and the expression measures of SRSF1, YY1 and RBBP6 using the R package survival. PFS and OS were the primary outcomes of interest. Pearson correlation analysis was employed to determine the correlation between the expression of YY1 and SRSF1. Student’s t test was performed to analyze the difference of mean values between two groups for other continuous outcomes. All statistical analyses were performed in R (version 3.2.3). A p-value lower than 0.05 was considered as significant.

Data Availability Statement

The data generated in this study are publicly available in Gene Expression Omnibus (GEO) at GSE160724.

Other detailed assays are available in the supplemental methods.

Aberrant alternative splicing in MM

To investigate whether dysregulated alternative splicing events were implicated in MM initiation and progression, gene set enrichment analysis (GSEA) between healthy donors (HD) and MM patients were performed in Gene Expression Omnibus (GEO) database (GSE6691). This revealed a significant difference in the expression pattern of the alternative splicing pathway genes, notably enriched in MM patients (Figure 1A). AS is generally regulated by splicing factors and the main cause of splicing dysregulation is ascribed to the aberrant expression or activity of splicing factors (11). And 17 splicing factors have been recognized to function as proto-oncogenes or tumor suppressors (12). To identify crucial splicing factors in MM initiation and progression, we performed two rounds of screening consecutively (Figure 1B). The expression level of the 17 splicing factors mentioned above were analyzed and five of them showed concordant differential expression in MM versus normal donors in two datasets (Figure 1B, Supplementary table 3). Then, five selected genes were subjected to survival analysis to determine their prognostic significance in MM. Kaplan-Meier analysis showed that SRSF1 expression in CD138⁺ MM cells was associated with PFS and OS (Figure 1C), but not other four genes (Supplementary Figure 1). We furtherly used Cox survival regression to jointly fit all the clinical variables captured by revised international staging system (R-ISS) and SRSF1 expression. Univariate and multivariate analyses indicated that high SRSF1 expression was correlated with decreased PFS (Table 1). To further assess the prognostic value of SRSF1, we tested the models fit with ISS (International staging system, ISS), RISS (Revised International Staging System, RISS) alone, and ISS, RISS with SRSF1. Leave-one-out cross-validation was performed to validate the prognostic value of SRSF1. The c-indices of model fit with the combination of ISS and SRSF1 were higher than those of models fit without SRSF1, indicating that SRSF1 improved the prognostic stratification of patients with MM (Table 2). To further explore the role of SRSF1 in plasma cell tumor transformation, we analyzed the SRSF1 expression in patients with plasma cell disease at different stages (MGUS, SMM, MM and PCL) and PCs of normal donor (NC). Among these splicing factors, only the expression level of SRSF1 appeared a progressive increase in the progression of plasma cell dyscrasias (Figure 1D). The above results provided the critical clue about aberrant alternative splicing might facilitate myeloma development and progression, and SRSF1 may be the crucial splicing factor for AS in MM.

SRSF1 increases tumorigenic potentials of MM

Increasing evidence demonstrates that SRSF1 is a prototypical splicing factor overexpressed in many tumors and exerts oncogenic roles via control of AS of cancer-related genes (7, 13, 14, 15, 16). The emerging roles of SRSF1 in AS regulation in cancer are opening up a new therapeutic avenue. Prompted by the above findings, we examined whether SRSF1 exerted oncogenic functions in MM. To unveil potential function of SRSF1 in MM, we transiently silenced endogenous SRSF1 expression with 2 independent siRNAs in MM.1S and LP-1 cells. Knockdown efficiency of SRSF1 in MM.1S and LP-1 cells were confirmed by western blotting and qPCR (Figure 2A, Supplementary Figure 2A).

Compared with the control siRNA, SRSF1 siRNAs significantly inhibited the growth of myeloma cells (Figure 2B, Supplementary Figure 2B). Notably, knockdown of SRSF1 caused G1-phase arrest and promoted apoptosis in myeloma cells (Figure 2C,2D and Supplementary Figure 2C, 2D, 2E, 2F). To evaluate the tumorigenic effect of SRSF1, MM.1S cells transfected with SRSF1-shRNA or control plasmid-constructed lentivirus were injected via the tail vein into the NSG (NOD-SCID IL-2receptor gamma null) mice. Consistent with the in vitro results, bioluminescent imaging monitoring revealed a decreased burden of disease and a prolongation in overall survival in mice injected with SRSF1-shRNA cells compared to the controls (Figure 2E, 2F, 2G). Collectively, these findings prove that SRSF1 functioned as a potential proto-oncogene to facilitate tumorigenesis and its inhibition could impede myeloma progression.

SRSF1 is positively regulated by the transcription factor YY1.

Large-scale genomic studies have uncovered that cancer cells are capable of hijacking the expression of SR proteins, leading to dysfunctional gene splicing and tumor-specific dependencies (8, 17). In order to elucidate the mechanisms mediating the upregulation of SRSF1 in myeloma, we investigated the transcription factors which could bind to the promoter region of SRSF1 using the UCSC (University of California Santa Cruz) genome browser. We first screened out 99 transcription factors that may bind to the promoter region of SRSF1. From these transcription factors, we selected 25 transcription factors with high predicted scores (Cluster Score >= 500) for subsequent analysis. Correlation analysis was conducted to explore the relationship between 25 transcription factors and SRSF1. We found that 5 transcription factors which were correlated with SRSF1 overlapped in the five sets of data (Figure 3A). Furthermore, the results of Pearson correlation analysis indicated that among the five transcription factors, only the expression of YY1 (YY1 transcription factor) in multiple sets of data had the highest correlation coefficient (r>=0.25, p<0.05) with SRSF1 (Figure 3B), suggesting that YY1 probably has a regulatory role in SRSF1.

We next sought to determine the regulation role of YY1 on the transcription of SRSF1. YY1 silencing led to a reduced level of SRSF1 (Figure 3C, Figure 3D). In order to further define the specific site of YY1 regulating SRSF1, CHIP-seq BigWig files were downloaded from GSE31477 and loaded in Integrative Genomics Viewer (IGV) to generate representative image tracks of the YY1 binding site at SRSF1 locus, we noticed that IGV tracks displayed the binding site of YY1 at SRSF1 promoter locus from chr17: 56084421 to 56084751 (Figure 3E). To further validate this finding, we characterized the binding regions of SRSF1 promoter by CHIP-qPCR and observed that the expression of SRSF1 promoter regions pulled down with anti-YY1 were significantly reduced upon YY1 knockdown (Figure 3F). We further performed dual-luciferase reporter assay to determine the interactions. Consistently, YY1 silencing led to a reduced the luciferase activity of the reporter constructs carrying wild-type SRSF1 promoter region, supporting a direct interaction between YY1 and SRSF1 promoter regions (Figure 3G). Taken all together, these data indicated that YY1 plays a pivotal role in regulation of SRSF1.

Dysregulated YY1 promotes myeloma progression and is associated with a poor prognosis

Since YY1 acted as a crucial regulator of the transcription of SRSF1, we next attempted to gain further insights into the effects of the YY1 in MM. We assessed the expression profile of YY1 and observed a significant increase of YY1 in the progression of plasma cell dyscrasias (Figure 4A). Likewise, Kaplan-Meier analysis indicated that high YY1 expression was a predictor of poor prognosis for both OS and PFS in MM patients, indicating that YY1 probably tend to participate in tumor growth (Figure 4B). To verify this hypothesis, loss-of-function studies were performed to identify the roles of YY1 in MM cell proliferation, apoptosis and cell cycle progression. The CCK8 assays showed that YY1 knockdown led to significantly decreased cell proliferation (Figure 4C). In parallel, knockdown of YY1 resulted in a significantly induced apoptosis (Figure 4D, Supplementary Figure 3A). Correspondingly, the flow cytometry analysis showed that the percentage of G1 increased and the percentage of S phase decreased in YY1 knockdown cells, further pointing to the critical role of YY1 in MM (Figure 4E, Supplementary Figure 3B). These above data suggest that YY1 effectively enhances tumor progression in MM cells by promoting the SRSF1 expression.

Global landscape alternative splicing events regulated by SRSF1

Previous studies demonstrate that splicing factor SRSF1 is a crucial family member of SR (serine/arginine-rich) proteins (11). SRSF1 plays a dual role in alternative splicing, as represented by promoting splicing by binding to exonic splicing enhancers and inhibiting splicing by binding to intronic elements (18). In order to investigate SRSF1-regulated AS (alternative splicing) events involved in myeloma, we conducted high-throughput sequencing of RNA (RNA-Seq) on LP-1 cells after SRSF1 depletion. A total of 2349 genes were identified with significant expression change in SRSF1-shRNA cells (Figure 5A and 5B). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis showed that these genes were associated with cell cycle, mRNA regulation and development processes (Figure 5C and 5D, Supplementary table 4 and 5). GSEA revealed that differentially expressed genes were involved in cell killing and cell growth pathway (Figure 5E and Supplementary table 6). These data support that SRSF1 is involved in multiple steps of RNA regulation and cell growth in MM. Furthermore, RNA-seq analysis revealed a total of 7678 SRSF1-regulated AS events in LP-1 cell with an FDR cut-off of <0.05 (Figure 5F and 5G). Various types of AS events, including skipped exons (SEs), alternative 5’ ss exons (A5SSs), alternative 3’ss exons (A3SSs), retained introns (RIs), and mutually exclusive exons (MXEs), can be regulated by SRSF1. Especially, the majority of these AS events belonged to the skipped exon (SE) category, implying a preference of SRSF1 regulating AS events of SE (Figure 5F and 5G). Among AS events, the index of percent spliced in (PSI) was upregulated in 4098 AS events and downregulated in 3580 AS events via the knockdown of SRSF1 (Figure 5H and Supplementary table 7). ClueGO and CluePedia further revealed that the SRSF1-regulated AS participated in multiple molecular pathways, and most of these were involved in RNA metabolic processes (Supplementary Figure 4 and Supplementary table 8). Overall, SRSF1 tend to promote exon inclusion and is critical to maintain the AS of genes related to RNA processes and cell growth in MM.

SRSF1 as a key splicing factor regulates the AS of RBBP6

To investigate the biological role of the interaction between SRSF1 and target genes, we analyzed the AS events and their transcripts expression regulated by SRSF1, and identified 420 genes with significant change of AS events and transcripts expression. In this regard, it is notable that RBBP6 (RB binding protein 6, ubiquitin ligase), which is closely related to the occurrence and development of tumors and has 3 alternatively spliced transcript variants that encode different isoforms (19). Additionally, The RBBP6 gene encodes three protein isoforms. Isoforms 1 and 2 consist of zinc, RING, retinoblastoma (Rb) and p53 binding domains, while isoform 3 is comprised of the Domain With No Name (DWNN) domain (20). Owing to the RING finger domain, RBBP6 serves as an E3 ubiquitin ligase and has pro-apoptotic functions through ubiquitinating Y-box binding protein 1 (YB-1). YB-1 is a transcription factor involved in suppressing p53 (20, 21). Consistent with the previous observation (22, 23), three isoforms of RBBP6 exit in MM cells (Figure 6A). SRSF1 knockdown caused a significantly decreased iso1 and increased iso3 of RBBP6 (Figure 6A). Depletion of RBBP6 isoform1 (Figure 6B) and ectopic over-expression of RBBP6 isoform3 (Figure 6C) uniformly suppressed cell growth, suggesting their opposite effect on myeloma cell proliferation (Figure 6D and 6E). Moreover, the level of RBBP6 iso1 is associated with poor prognosis (Figure 6F), whereas iso3 expression is associated with favorable prognosis in MM patients. Collectively, these data support the view that SRSF1 regulated RNA splicing of RBBP6 to mediate tumor growth.

Our current understanding of regulatory roles of splicing factors in cancers is mainly based in the limited information about the changes in gene copy number and/or expression (6, 8, 24), however the detailed mechanisms and biological consequences are still elusive. In particular, it is unknown whether aberrant AS plays vital roles in the development of myeloma remains unknown. In this study, we provided convincing evidence that up-regulation of the splicing factor SRSF1 could act as an oncoprotein in MM, and its expression was mediated by the oncogenic transcription factor YY1. In addition, our present work represented a comprehensive study of the splicing factor SRSF1 and its downstream AS landscape in myeloma. During this study, we identified a key AS target, RBBP6, whose full-length isoform (RBBP6 isoform1) was closely associated with the onset and progression of myeloma and the outcome of the patients. We concluded that SRSF1 promoted myelosis by controlling the AS of tumor-associated genes, further highlighting the importance of AS as a crucial contributor to tumorigenesis.

Alternative splicing is frequently regulated by trans-acting splicing factors, which bind to sequence motifs that are associated with the promotion (enhancers) or repression (silencers) of splicing (24). Splicing enhancers and silencers are bound by diverse RNA-binding proteins, exemplified by the serine/arginine-rich proteins (SR proteins) and heterogeneous nuclear ribonucleoproteins (hnRNPs) (12). Some SR proteins can act as oncoproteins when overexpressed in the correct cellular context. For instance, insightful reports from other scholars have demonstrated that SR splicing factor 1 (SRSF1; also known as ASF/SF2) is overexpressed in extracranial tumors and plays oncogenic roles via control of the AS of several tumor-related genes (7, 14, 15, 25). Notably, titration of SRSF1 activity using decoy oligonucleotides containing SRSF1-binding sites results in the inhibition of cancer cell growth and apoptosis in vitro and in mouse xenograft models in glioblastoma (26). Consistent with previous studies, we have presented a number of findings demonstrating the significance evidence that SRSF1 was appeared a progressive increase during the progression of plasma cell dyscrasias and its overexpression was associated with a poorer survival. The subsequent functional study verified that SRSF1 knockdown caused the proliferation inhibition, G1-phase arrest and the increase of apoptosis of MM cells in vitro and suppressed the tumor growth of myeloma xenografts in vivo. These findings indicated that SRSF1 played a critical role in the pathogenesis of myeloma and tumor cell proliferation.

Several lines of evidences have demonstrated deleterious outcomes when transcription factors become dysfunctionally activated or inactivated, leading to cellular malfunction, instability, and in some cases, tumorigenesis (27). Based on the dysregulated expression of SRSF1, we further explored the transcription factors which could bind to the promoter region of SRSF1 and alter transcriptional regulation on SRSF1. Previous study identify SRSF1 is a direct target of the transcription-factor oncoprotein MYC in lung tumors (28). However, this study did not include other transcription factors except MYC. It is highly possible that the other more important transcription factors may regulate SRSF1 transcription. To overcome this possible drawback, we analyzed all the transcription factors could bind to the promoter region of SRSF1 in order to more accurately reveal the transcription factors that regulate the SRSF1 transcript. According to the results of bioinformatics analysis, we focused on YY1 (Yin Yang 1). YY1 is a 65-kDa member of the GLI-kruppel family of zinc finger transcription factors, which regulate various developmental and differentiation processes (29). Most processes mediated by YY1 are cancer-related, strongly implicating its importance in cancer development and progression (30). Indeed, overexpression of YY1 has been observed in various types of cancers (31, 32). Hence, it is important to divulge how transcription factors such as YY1 function in SRSF1 transcription processes and ultimately shape the growth and viability of MM cells. Subsequent experiments confirmed that YY1 could positively regulate SRSF1 expression by directly binding to its promoter region. Thus, YY1 is a novel transcriptional activator of SRSF1 expression. Moreover, consistent with other studies (30, 33, 34), we were able to show that YY1 as oncoproteins enhanced tumor progression in MM cells.

Alternative splicing can be categorized into five major events, which include skipped exons, alternative 3′ or 5′ splice site selection, mutually exclusive exons, and intron retention (8). Analysis of 8705 patients from The Cancer Genome Atlas (TCGA) identified a significant amount of aberrant transcripts in tumor cells, including exon skipping and alternative 3′ splice sites when compared with normal human tissues (35). SRSF1 regulates AS of target genes involved in apoptosis, cell motility, proliferation, and other cellular functions (36). In parallel, SRSF1 overexpression promotes expression of isoforms that stimulate translation and cell proliferation, by increasing phosphorylation of translation activators, such as S6 or eIF4E, or by inhibiting translational repressors, such as 4EBP1 (15, 37). SRSF1 can also interact with and activate WNT signaling pathway to promote tumorigenesis (13). However, whether SRSF1 participate in splicing events in MM is still unknown. In an attempt to determine the alternative splice events regulated by SRSF1 in MM, we preformed RNA-seq upon SRSF1 depletion. Our study provided convincing evidence that SRSF1 played a significant role in regulating pre-mRNA splicing events, especially in skipping exon category, in MM. Meanwhile, we also found that SRSF1 regulated some AS events of genes associated with cell killing, cell growth and RNA metabolic processes. For instance, SRSF1 controls splicing of RBBP6, which has been demonstrated to participate in the regulation of cell cycle and apoptosis (21). RBBP6 has three isoforms. Isoforms 1 and 2 are multidomain proteins containing a domain with no name (DWNN) domain, a Zinc Finger, a RING Finger, an Rb-binding domain and a p53-binding domain. The RBBP6 isoform 3 comprises the DWNN domain only (38). RBBP6 isoform 1 been shown to regulate p53 through its ubiquitin ligase activity, thus implicating in cell cycle regulation and apoptosis (39). In support, we found that SRSF1 regulated RNA splicing of RBBP6 and increased the level of isoform1, leading to tumor cell proliferation.

The evidence gathered from the present studies has placed SRSF1 as the key regulator in pre-mRNA splicing of MM, therefore, reveals exciting and important mechanistic insights into how transcription factor YY1 directly regulates SRSF1 transcription, further pointing to the critical role SRSF1 in the splicing regulation of RBBP6.

Authors' contributions

Wenzhuo Zhuang and Bingzong Li designed the research, Sha Song and Weimin Zhang performed research, Sha Song and Qi Li wrote the paper, Zhiming Wang, Qi Su, Xinyun Zhang performed research and modified the paper.

Conflict of Interest

The authors declare that they have no competing interests.

Acknowledgments

The research leading to these results has received funding fromNatural Science Foundation of Jiangsu Province China (BK20201408), The special project of “Technological innovation” project of CNNC Medical Industry Co. Ltd) (ZHYLYB2021002), Jiangsu Social Development Project- New Clinical Diagnosis and Treatment Technology (BE2019664).

Palumbo A and Anderson K. Multiple myeloma. N Engl J Med 2011; 364: 1046–60.
van de Donk NWCJ, Pawlyn C, and Yong KL. Multiple myeloma. The Lancet 2021; 397: 410–427.
Rajkumar SV. The screening imperative for multiple myeloma. Nature 2020; 587: S63.
van Andel H, Kocemba KA, Spaargaren M, and Pals ST. Aberrant Wnt signaling in multiple myeloma: molecular mechanisms and targeting options. Leukemia 2019; 33: 1063–1075.
Pawlyn C and Davies FE. Toward personalized treatment in multiple myeloma based on molecular characteristics. Blood 2019; 133: 660–675.
Rahman MA, Krainer AR, and Abdel-Wahab O. SnapShot: Splicing Alterations in Cancer. Cell 2020; 180: 208–208 e1.
Anczukow O, Akerman M, Clery A, Wu J, Shen C, Shirole NH, et al. SRSF1-Regulated Alternative Splicing in Breast Cancer. Mol Cell 2015; 60: 105–17.
Wang E and Aifantis I. RNA Splicing and Cancer. Trends Cancer 2020; 6: 631–644.
Long JC and Caceres JF. The SR protein family of splicing factors: master regulators of gene expression. Biochem J 2009; 417: 15–27.
Seiler M, Peng S, Agrawal AA, Palacino J, Teng T, Zhu P, et al. Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types. Cell Rep 2018; 23: 282–296.e4.
Kahles A, Lehmann KV, Toussaint NC, Huser M, Stark SG, Sachsenberg T, et al. Comprehensive Analysis of Alternative Splicing Across Tumors from 8,705 Patients. Cancer Cell 2018; 34: 211–224 e6.
Dvinge H, Kim E, Abdel-Wahab O, and Bradley RK. RNA splicing factors as oncoproteins and tumour suppressors. Nat Rev Cancer 2016; 16: 413–30.
Fu Y, Huang B, Shi Z, Han J, Wang Y, Huangfu J, et al. SRSF1 and SRSF9 RNA binding proteins promote Wnt signalling-mediated tumorigenesis by enhancing beta-catenin biosynthesis. EMBO Mol Med 2013; 5: 737–50.
Chen L, Luo C, Shen L, Liu Y, Wang Q, Zhang C, et al. SRSF1 Prevents DNA Damage and Promotes Tumorigenesis through Regulation of DBF4B Pre-mRNA Splicing. Cell Rep 2017; 21: 3406–3413.
Xie N, Chen M, Dai R, Zhang Y, Zhao H, Song Z, et al. SRSF1 promotes vascular smooth muscle cell proliferation through a Delta133p53/EGR1/KLF5 pathway. Nat Commun 2017; 8: 16016.
Wu H, Sun S, Tu K, Gao Y, Xie B, Krainer AR, et al. A splicing-independent function of SF2/ASF in microRNA processing. Mol Cell 2010; 38: 67–77.
Sciarrillo R, Wojtuszkiewicz A, Assaraf YG, Jansen G, Kaspers GJL, Giovannetti E, et al. The role of alternative splicing in cancer: From oncogenesis to drug resistance. Drug Resist Updat 2020; 53: 100728.
Fu XD and Ares M, Jr. Context-dependent control of alternative splicing by RNA-binding proteins. Nat Rev Genet 2014; 15: 689–701.
Batra J, Hultquist JF, Liu D, Shtanko O, Von Dollen J, Satkamp L, et al. Protein Interaction Mapping Identifies RBBP6 as a Negative Regulator of Ebola Virus Replication. Cell 2018; 175: 1917–1930 e13.
Mbita Z, Meyer M, Skepu A, Hosie M, Rees J, and Dlamini Z. De-regulation of the RBBP6 isoform 3/DWNN in human cancers. Mol Cell Biochem 2012; 362: 249–62.
Di Giammartino DC, Li W, Ogami K, Yashinskie JJ, Hoque M, Tian B, et al. RBBP6 isoforms regulate the human polyadenylation machinery and modulate expression of mRNAs with AU-rich 3' UTRs. Genes Dev 2014; 28: 2248–60.
Mbita Z, Meyer M, Skepu A, Hosie M, Rees J, and Dlamini Z. De-regulation of the RBBP6 isoform 3/DWNN in human cancers. Molecular and Cellular Biochemistry 2012; 362: 249–262.
Dlamini Z, Ledwaba T, Hull R, Naicker S, and Mbita Z. RBBP6 Is Abundantly Expressed in Human Cervical Carcinoma and May Be Implicated in Its Malignant Progression. Biomarkers in cancer 2019; 11: 1179299X19829149-1179299X19829149.
Bonnal SC, Lopez-Oreja I, and Valcarcel J. Roles and mechanisms of alternative splicing in cancer - implications for care. Nat Rev Clin Oncol 2020; 17: 457–474.
Malakar P, Shilo A, Mogilevsky A, Stein I, Pikarsky E, Nevo Y, et al. Long Noncoding RNA MALAT1 Promotes Hepatocellular Carcinoma Development by SRSF1 Upregulation and mTOR Activation. Cancer Res 2017; 77: 1155–1167.
Denichenko P, Mogilevsky M, Clery A, Welte T, Biran J, Shimshon O, et al. Specific inhibition of splicing factor activity by decoy RNA oligonucleotides. Nat Commun 2019; 10: 1590.
Bushweller JH. Targeting transcription factors in cancer - from undruggable to reality. Nat Rev Cancer 2019; 19: 611–624.
Das S, Anczukow O, Akerman M, and Krainer AR. Oncogenic splicing factor SRSF1 is a critical transcriptional target of MYC. Cell Rep 2012; 1: 110–7.
Gordon S, Akopyan G, Garban H, and Bonavida B. Transcription factor YY1: structure, function, and therapeutic implications in cancer biology. Oncogene 2006; 25: 1125–42.
Tang W, Zhou W, Xiang L, Wu X, Zhang P, Wang J, et al. The p300/YY1/miR-500a-5p/HDAC2 signalling axis regulates cell proliferation in human colorectal cancer. Nat Commun 2019; 10: 663.
YY1 Facilitates Enhancer-Promoter Contacts to Promote Gene Expression. Cancer Discov 2018; 8: 135.
Han J, Meng J, Chen S, Wang X, Yin S, Zhang Q, et al. YY1 Complex Promotes Quaking Expression via Super-Enhancer Binding during EMT of Hepatocellular Carcinoma. Cancer Res 2019; 79: 1451–1464.
Shi J, Hao A, Zhang Q, and Sui G. The role of YY1 in oncogenesis and its potential as a drug target in cancer therapies. Curr Cancer Drug Targets 2015; 15: 145–57.
Wang J, Zhou L, Li Z, Zhang T, Liu W, Liu Z, et al. YY1 suppresses FEN1 over-expression and drug resistance in breast cancer. BMC Cancer 2015; 15: 50.
Scotti MM and Swanson MS. RNA mis-splicing in disease. Nat Rev Genet 2016; 17: 19–32.
Anczukow O, Rosenberg AZ, Akerman M, Das S, Zhan L, Karni R, et al. The splicing factor SRSF1 regulates apoptosis and proliferation to promote mammary epithelial cell transformation. Nat Struct Mol Biol 2012; 19: 220–8.
Michlewski G, Sanford JR, and Caceres JF. The splicing factor SF2/ASF regulates translation initiation by enhancing phosphorylation of 4E-BP1. Mol Cell 2008; 30: 179–89.
Mbita Z, Hull R, Mbele M, Makhafola T, and Dlamini Z. Expression Analysis of RbBP6 in human cancers: a Prospective biomarker. Anticancer Drugs 2019; 30: 767–773.
Ntwasa M. Retinoblastoma Binding Protein 6, Another p53 Monitor. Trends Cancer 2016; 2: 635–637.

Table 1

Summary for the results of univariate and multivariable analysis (GSE136400)
Factors	PFS
	Univariate			Multivariate
	HR	p-Value	95%CI	HR	p-Value	95%CI
Age	1.0246	0.0000	1.0129–1.0364	1.0220	0.0000	1.0096–1.0333
Albumin	0.6920	0.0000	0.6087–0.7866	0.8419	0.0137	0.7371–0.9702
Beta-2 microglobulin	1.0832	0.0000	1.0640–1.1027	1.0440	0.0054	1.0133–1.0755
Lactate dehydrogenase	1.0021	0.0003	1.0009–1.0032	1.0010	0.1036	0.9998–1.0025
Del (17p)	0.7311	0.3807	0.3630–1.4726	0.5795	0.1529	1.1909–1.6365
t (4;14) (p16;q32)	1.4219	0.2306	0.7996–2.5286	1.7510	0.0752	1.0100-1.3024
t (14;16) (q32;q23)	356.71	0.0000	69.788–1823.3	167.10	0.0000	32.448–870.71
ISS	1.6118	0.0000	1.4301–1.8166	1.2940	0.0243	1.0344–1.6036
RISS	1.5687	0.0000	1.3333–1.8456	0.9784	0.8627	0.7711–1.2481
SRSF1	1.1843	0.0305	1.0160–1.3806	1.2050	0.0179	1.0304–1.3979

Table 2

C-index of ISS and RISS alone, ISS and RISS with SRSF1 (GSE136400)
		PFS
	C-index	C-index (Cross-validated)
ISS	0.6413	0.6296
ISS + SRSF1	0.6414	0.6316
RISS	0.6361	0.6266
RISS + SRSF1	0.6366	0.6272

There is NO conflict of interest to disclose.

SupplementalInformation.docx
Supplemental Information
Supplementarytable.pdf
Supplementary table
SupplementaryFigure1.tif
Supplementary Figure 1
SupplementaryFigure2.tif
SupplementaryFigure3.tif
SupplementaryFigure4.tif
Supplementary Figure 4
SupplementaryFigure5.tif
Supplementary Figure 5

Download PDF

Version 1

posted

You are reading this latest preprint version

Dysregulation of Alternative Splicing Contributes to Multiple Myeloma Pathogenesis

Status:

Version 1

Abstract

Figures

Introduction

Materials And Methods

Results

Discussion

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1