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Dysregulation of alternative splicing contributes to multiple myeloma pathogenesis.


ABSTRACT:

Background

Dysregulation of alternative splicing (AS) triggers many tumours, understanding the roles of splicing events during tumorigenesis would open new avenues for therapies and prognosis in multiple myeloma (MM).

Methods

Molecular, genetic, bioinformatic and statistic approaches are used to determine the mechanism of the candidate splicing factor (SF) in myeloma cell lines, myeloma xenograft models and MM patient samples.

Results

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 MM patients. Moreover, SRSF1 knockdown exerts a broad anti-myeloma activity in vitro and in vivo. The upregulation 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 AS events.

Conclusion

Our results emphasise the importance of AS for promoting tumorigenesis of MM. The candidate SF might be considered as a valuable therapeutic target and a potential prognostic biomarker for MM.

SUBMITTER: Song S 

PROVIDER: S-EPMC10006196 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Publications

Dysregulation of alternative splicing contributes to multiple myeloma pathogenesis.

Song Sha S   Zhang Weimin W   Li Qi Q   Wang Zhiming Z   Su Qi Q   Zhang Xinyun X   Li Bingzong B   Zhuang Wenzhuo W  

British journal of cancer 20230102 6


<h4>Background</h4>Dysregulation of alternative splicing (AS) triggers many tumours, understanding the roles of splicing events during tumorigenesis would open new avenues for therapies and prognosis in multiple myeloma (MM).<h4>Methods</h4>Molecular, genetic, bioinformatic and statistic approaches are used to determine the mechanism of the candidate splicing factor (SF) in myeloma cell lines, myeloma xenograft models and MM patient samples.<h4>Results</h4>GSEA reveals a significant difference i  ...[more]

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2019-01-15 | GSE110525 | GEO