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Alternative splicing events in tumor immune infiltration in renal clear cell carcinomas

Cancer Gene Therapy volume 29, pages 1418–1428 (2022)Cite this article

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Abstract

Alternative splicing (AS) is a gene regulatory mechanism that drives protein diversity and dysregulation of AS plays a significant role in tumorigenesis. This study aimed to develop a prognostic signature based on AS and elucidate the role in tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC). The prognosis-related AS events were analyzed by univariate Cox regression analysis. Gene set enrichment analyses (GSEA) were performed for functional annotation. Prognostic signatures were identified and validated using univariate and multivariate Cox regression, LASSO regression, Kaplan–Meier survival analysis, and proportional hazards model. The context of TIME in ccRCC was also analyzed. Gene and protein expression data of C4orf19 were obtained from ONCOMINE website and Human Protein Altas. Splicing factors (SFs) regulatory networks were visualized. 4431 survival-related AS events in ccRCC were screened. Based on splicing subtypes, eight AS prognostic signatures were constructed. A nomogram with good prognostic prediction was generated. Furthermore, the prognostic signatures were significantly correlated with TIME diversity and immune checkpoint inhibitor (ICI)-related genes. C4orf19 was the only gene whose expression levels were downregulated among the prognostic AS-related genes, which is considered as a promising prognostic factor in ccRCC. Potential functions of SFs were determined by splicing regulatory networks. In our study, AS patterns of novel indicators for prognostic prediction of ccRCC were explored. The AS-SF networks provide information of regulatory mechanisms. Players of AS events related to TIME were investigated, which contribute to prognosis monitoring of ccRCC.

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Fig. 1: Overall study design.
Fig. 2: Different AS types in ccRCC.
Fig. 3: The survival-related AS events.
Fig. 4: Confirmation of ALL AS-based prognostic signature.
Fig. 5: Correlation of ALL prognostic signature with clinical features and construction of AS-clinicopathological nomogram.
Fig. 6: Correlation between infiltrating immune cells and ALL AS-based prognostic signature.
Fig. 7: Association between ALL AS-based prognostic signature and key ICI genes.
Fig. 8: The clinical significance of C4orf19 in ccRCC.
Fig. 9: The role of C4orf19 in TIME features.
Fig. 10: The regulatory network between SFs and survival-related AS events.

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Data availability

Publicly available datasets were analyzed in this study.

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Author information

Author notes

  1. These authors contributed equally: Zhiqiang Wang, Liping Zhu.

Authors and Affiliations

  1. Department of Urology, Shouguang Hospital of Traditional Chinese Medicine, Shouguang, Shandong Province, China

    Zhiqiang Wang

  2. Department of Medical Oncology, Shouguang Hospital of Traditional Chinese Medicine, Shouguang, Shandong Province, China

    Liping Zhu

  3. Department of Hematology and Oncology, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, 315000, Zhejiang Province, China

    Kesang Li

  4. Department of Respiratory Disease, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Hangzhou Medical College, Hangzhou, Zhejiang Province, China

    Yilan Sun & Ling Peng

  5. Department of Biochemistry and Biomedicine, School of Life Sciences, University of Sussex, Brighton, UK

    Georgios Giamas

  6. Division of Cancer, Department of Surgery and Cancer, Imperial College London, London, UK

    Justin Stebbing

  7. Department of Thoracic Surgery, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China

    Zhentao Yu

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Contributions

ZW, LP, KL, and PZ designed and supervised the study. ZW, LZ, LL, YS, and LP analyzed the data and wrote the original draft. LP, GG, and JS edited the draft. All the authors have read and approved the final manuscript.

Corresponding authors

Correspondence to Ling Peng or Zhentao Yu.

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Competing interests

JS’ conflicts can be found at https://www.nature.com/onc/editors. GG is Editor in Chief in Cancer Gene Therapy and the Founder and Chief Scientific Advisor of Stingray Bio. None are relevant here. Other authors do not declare conflict of interest.

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Wang, Z., Zhu, L., Li, K. et al. Alternative splicing events in tumor immune infiltration in renal clear cell carcinomas. Cancer Gene Ther 29, 1418–1428 (2022). https://doi.org/10.1038/s41417-022-00426-9

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