Increased Expression of SRSF1 Predicts Poor Prognosis in Multiple Myeloma

Jiawei Zhang; Zanzan Wang; Kailai Wang; Dijia Xin; Luyao Wang; Yili Fan; Yang Xu

doi:10.1155/2023/9998927

Increased Expression of SRSF1 Predicts Poor Prognosis in Multiple Myeloma

J Oncol. 2023 May 10:2023:9998927. doi: 10.1155/2023/9998927. eCollection 2023.

Authors

Jiawei Zhang^{1

2}, Zanzan Wang³, Kailai Wang², Dijia Xin¹, Luyao Wang¹, Yili Fan¹, Yang Xu^{1

4}

Affiliations

¹ Department of Hematology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China.
² Zhejiang University Cancer Institute, Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China.
³ Department of Hematology, Ningbo First Hospital, Ningbo 315010, China.
⁴ Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang 310058, China.

Abstract

Background: Multiple myeloma (MM) is a clonal plasma cell disorder which still lacks sufficient prognostic factors. The serine/arginine-rich splicing factor (SRSF) family serves as an important splicing regulator in organ development. Among all members, SRSF1 plays an important role in cell proliferation and renewal. However, the role of SRSF1 in MM is still unknown.

Methods: SRSF1 was selected from the primary bioinformatics analysis of SRSF family members, and then we integrated 11 independent datasets and analyzed the relationship between SRSF1 expression and MM clinical characteristics. Gene set enrichment analysis (GSEA) was conducted to explore the potential mechanism of SRSF1 in MM progression. ImmuCellAI was used to estimate the abundance of immune infiltrating cells between the SRSF1^high and SRSF1^low groups. The ESTIMATE algorithm was used to evaluate the tumor microenvironment in MM. The expression of immune-related genes was compared between the groups. Additionally, SRSF1 expression was validated in clinical samples. SRSF1 knockdown was conducted to explore the role of SRSF1 in MM development.

Results: SRSF1 expression showed an increasing trend with the progression of myeloma. Besides, SRSF1 expression increased as the age, ISS stage, 1q21 amplification level, and relapse times increased. MM patients with higher SRSF1 expression had worse clinical features and poorer outcomes. Univariate and multivariate analysis indicated that upregulated SRSF1 expression was an independent poor prognostic factor for MM. Enrichment pathway analysis confirmed that SRSF1 takes part in the myeloma progression via tumor-associated and immune-related pathways. Several checkpoints and immune-activating genes were significantly downregulated in the SRSF1^high groups. Furthermore, we detected that SRSF1 expression was significantly higher in MM patients than that in control donors. SRSF1 knockdown resulted in proliferation arrest in MM cell lines.

Conclusion: The expression value of SRSF1 is positively associated with myeloma progression, and high SRSF1 expression might be a poor prognostic biomarker in MM patients.