AUNIP Expression Is Correlated With Immune Infiltration and Is a Candidate Diagnostic and Prognostic Biomarker for Hepatocellular Carcinoma and Lung Adenocarcinoma.

Chenxi Ma,Lu Yu,Wenyan Kang,Zongcheng Yang,Tian Ding

doi:10.3389/fonc.2020.590006

Abstract

AUNIP, a novel prognostic biomarker, has been shown to be associated with stromal and immune scores in oral squamous cell carcinoma (OSCC). Nonetheless, its role in other cancer types was unclear. In this study, AUNIP expression was increased in hepatocellular carcinoma (HCC) and lung adenocarcinoma (LUAD) according to data from The Cancer Genome Atlas (TCGA) database, Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB), and Gene Expression Omnibus (GEO) database (GSE45436, GSE102079, GSE10072, GSE31210, and GSE43458). Further, according to copy number variation analysis, AUNIP up-regulation may be associated with copy number variation. Immunohistochemistry showed AUNIP expression was higher in HCC and LUAD compared with the normal tissues. Receiver operating characteristic (ROC) curve analysis demonstrated that AUNIP is a candidate diagnostic biomarker for HCC and LUAD. Next, TCGA, International Cancer Genome Consortium (ICGC), and GEO (GSE31210 and GSE50081) data showed that increased AUNIP expression clearly predicted poor overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in HCC and LUAD. Additionally, multivariate Cox regression analysis involving various clinical factors showed that AUNIP is an independent prognostic biomarker for HCC and LUAD. Next, the role of AUNIP in HCC and LUAD was explored via a co-expression analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and a gene set variation analysis (GSVA). HCC and LUAD exhibited almost identical enrichment results. More specifically, high AUNIP expression was associated with DNA replication, cell cycle, oocyte meiosis, homologous recombination, mismatch repair, the p53 signal transduction pathway, and progesterone-mediated oocyte maturation. Lastly, the Tumor Immune Estimation Resource (TIMER) tool was used to determine the correlations of AUNIP expression with tumor immune infiltration. AUNIP expression was positively correlated with the infiltration degree of B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells in HCC. However, AUNIP expression was negatively correlated with the infiltration degree of B cells, CD4+ T cells, and macrophages in LUAD. In addition, AUNIP expression was correlated with immune infiltration in various other tumors. In conclusion, AUNIP, which is associated with tumor immune infiltration, is a candidate diagnostic and prognostic biomarker for HCC and LUAD.

Highlights

Hepatocellular carcinoma (HCC), a frequently occurring primary liver cancer, is the second most common cause of cancer-related death globally [1, 2], while lung cancer is the leading cause of cancer-related death globally [3]
RNA-seq and survival data from the The Cancer Genome Atlas (TCGA) database were used to investigate whether AUNIP expression was associated with overall survival (OS) in a pan-cancer analysis (Figure 2)
AUNIP expression was associated with OS in 10 diverse types of cancers, namely, liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), pancreatic adenocarcinoma (PAAD), uterine corpus endometrial carcinoma (UCEC), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), sarcoma (SARC), adrenocortical carcinoma (ACC), brain lower grade glioma (LGG), and mesothelioma (MESO)

Summary

Introduction

Hepatocellular carcinoma (HCC), a frequently occurring primary liver cancer, is the second most common cause of cancer-related death globally [1, 2], while lung cancer is the leading cause of cancer-related death globally [3]. The tumor microenvironment (TME) greatly affects cancer prognosis [7]. Immunocytes often infiltrate the TME, and the tumor cells constantly interact with them in this compartment [8]. The infiltration of cytotoxic T cells (CTLs) is related to good prognosis. The infiltration of myeloid-derived suppressor cells (MDSCs), tumor-associated macrophages (TAMs), and regulatory T cells (Tregs) is related to poor prognosis [7]. Immunotherapy targeting interactions between immune cells and tumor cells has shown promising results in some cancer patients. Some NSCLC patients benefit from treatment based on Treg blockade [9], while antiangiogenics and immune checkpoint inhibitors can be effective for HCC [2]. Only a sed proportion of cancer patients achieve a good treatment effect [10]. Identifying further prognostic biomarkers and possible therapeutic targets is of great significance

Methods

Results

Conclusion