Abstract
Background
It was indicated that tumor intrinsic heterogeneity and the tumor microenvironment (TME) of ovarian cancer (OV) influence immunotherapy efficacy and patient outcomes. Leucyl and cystinyl aminopeptidase (LNPEP) encodes a zinc-dependent aminopeptidase, which has been proved to participant in the vesicle-mediated transport and class I MHC mediated antigen processing and presentation. However, the function of LNPEP in TME of OV and its potential molecular mechanisms have not been determined. Therefore, we aimed to investigate a prognostic biomarker which may be helpful in identifying TME heterogeneity of ovarian cancer.
Methods
In this study, bioinformatics databases were used to explore the expression profile and immune infiltration of LNPEP. Bioinformatics analyses of survival data and interactors of LNPEP were conducted to predict the prognostic value of LNPEP in OV. The protein levels of LNPEP were validated by Western blot and immunohistochemistry.
Results
Based on the TCGA data, our data displayed that the mRNA expression of LNPEP was markedly down-regulated in ovarian cancer than that in para-cancer tissues, contrary to the protein level. Importantly, high LNPEP expression was associated with poor prognosis in patients with OV. Furthermore, Cox regression analysis showed that LNPEP was an independent prognostic factor in OV. GO and KEGG pathway analyses indicated the co-expressed genes of LNPEP were mainly related to a variety of immune-related pathways, including Th1 and Th2 cell differentiation, Th17 cell differentiation, and immunoregulatory interaction. Our data also demonstrated that the expression of LNPEP was strongly correlated with immune infiltration levels, immunomodulators, chemokines and chemokine receptors.
Conclusion
In our study, we identified and established a prognostic signature of immune-related LNPEP in OV, which will be of great value in predicting the prognosis of clinical trials and may become a new therapeutic target for immunological research and potential prognostic biomarker in OV.
Data Sharing Statement
All original data generated or analyzed during the study are included in the article and Supplementary Materials. Further inquiries can be directed to the corresponding author.
Acknowledgment
We thank Bullet Edits Limited for the linguistic editing and proofreading of the manuscript.
Disclosure
The authors declare that they have no competing interests in this work.