Journal of Holistic Integrative Pharmacy (Mar 2023)

Pan-cancer analysis highlights the role of PSENEN in the prognosis and immunology of cancer

  • Zerui YANG,
  • Dingsheng WEN,
  • Yubing YE,
  • Kai CHEN,
  • Zhikun QIU,
  • Xingyun LIU,
  • Xiong LI

Journal volume & issue
Vol. 4, no. 1
pp. 83 – 102

Abstract

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Background: Presenilin enhancer-2 (PSENEN, PEN-2), one of the four components of the γ-secretase complex, has been increasingly revealed to be significant in cancer types such as pancreatic cancer, gastric cancer, and breast cancer. However, the pan-cancer clinical relevance of PSENEN remains unclear. Methods: Raw data on PSENEN expression in normal and cancer tissues were obtained from The Cancer Genome Atlas (TGCA) database and Genotype-Tissue Expression Project (GTEx). The difference of PSENEN expression was analyzed using data from the TCGA repository and TIMER2 database. Meanwhile, Cox regression analysis and KM plotter were used to analyze the pan-cancer prognostic significance of PSENEN. We also analyzed the correlation between PSENEN expression and tumor immune infiltration using the TIMER and XCELL algorithms. Moreover, we used the TISIDB database to determine PSENEN expression in different immune and molecular subtypes of human cancers. Pan-cancer analysis of genetic alteration of PSENEN was performed using online tools such as cBioPortal and UALCAN. Finally, six Gene Expression Omnibus datasets from the Gene Expression Profiling Interactive Analysis database were used to validate the expression level of PSENEN in lung adenocarcinoma (LUAD). Results: Contrary to nonmalignant tissues, the expression level of PSENEN was significantly upregulated in the cancerous tissues in 22 cancer types. Elevated PSENEN expression was correlated with worse overall survival in 7 cancer types and with worse disease-specific survival in 8 of them. By using xCell algorithm, TIMER algorithm, and Spearman's correlation analysis, we found that PSENEN expression was closely correlated with the infiltration of immune cells across all cancer types. Moreover, aberrant PSENEN expression was associated with 60 immune checkpoint pathway-related genes, microsatellite instability, and tumor mutation burden in various cancer types. Besides, PSENEN expression was significantly associated with different immune subtypes and molecular subtypes of various human cancers. Notably, ovarian epithelial tumor samples demonstrated the highest frequency of PSENEN mutation among all cancer types. Conclusions: Our pan-cancer analysis demonstrated that PSENEN might serve as a prognostic biomarker and revealed the importance of an in-depth understanding of the oncogenic role of PSENEN in various malignancies.

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