Identification of exosome-related SERPINB1 as a novel predictor for tumor immune microenvironment and clinical outcomes in ovarian cancer.

Abstract

Background: With a high global incidence of over three million new cases in 2020 and a high mortality of over two million fatalities, ovarian cancer is one of the most common malignant tumors in gynecology. Exosomes can control the immunological condition of the tumor microenvironment (TME) by participating in intercellular interactions. Therefore, we aimed to construct an exosome-related prognostic model to predict the clinical outcomes of ovarian cancer patients.

Methods: In this research, expression patterns of exosome-related genes were examined in multiple single-cell RNA-sequencing and bulk RNA-sequencing datasets. In addition, a novel exosome-related prognostic model was established by the least absolute shrinkage and selection operator (LASSO) regression method. Then, the correlations between risk score and immunological characteristics of the TME were explored. Moreover, SERPINB1, a gene in the prognostic signature, was further analyzed to reveal its value as a novel biomarker.

Results: In the current study, combined with single-cell and bulk omics datasets, we constructed an exosome-related prognostic model of four genes (LGALS3BP, SAT1, SERPINB1, and SH3BGRL3). Moreover, the risk score was associated with worse overall survival (OS) in ovarian cancer patients. Further analysis found that patients with high-risk score tended to shape a desert TME with hardly infiltration of immune cells. Then, SERPINB1, positively correlated with the favorable OS and negatively with the risk score, was chosen as the representative biomarker of the model. Moreover, SERPINB1 was positively correlated with the infiltration of immune subpopulations in both public and in-house cohort. In addition, the high-resolution analysis found that SERPINB1⁺ tumor cells communicated with microenvironment cells frequently, further explaining the potential reason for shaping an inflamed TME.

Conclusion: To sum up, we established a novel exosome-related prognostic model (LGALS3BP, SAT1, SERPINB1, and SH3BGRL3) to predict the prognosis of patients with ovarian cancer and identify the immunological characteristics of the TME. In addition, SERPINB1 was identified as a promising biomarker for prognostic prediction in ovarian cancer.