LCN2-interacting proteins and their expression patterns in brain tumors

Highlights

• LCN2 and its interacting proteins cross-talk in the PPIN.

• Enrichment analyses revealed the functions of LCN2 and its interacting proteins.

• LCN2 PPIN have distinct expression patterns in each of five types of brain tumor.

• LCN2 and nine interacting proteins are prognostic factors for glioblastomas.

• LCN2 is an independent prognostic factor for glioblastoma.

Abstract

Lipocalin 2 (LCN2) is a member of the lipocalin family. Elevated expression of LCN2 has been observed in many human tumors, suggesting it might be a potential biomarker and/or therapeutic target in malignancies. In this study, we aimed to explore LCN2 interacting proteins through bioinformatics, as well as their biological functions. Protein-protein interaction networks (PPIN) were constructed using LCN2 and its interacting proteins as the core node. These PPINs were scale free biological networks in which LCN2 and its interacting proteins could connect or cross-talk with at least one partner protein. Both functional and KEGG pathway enrichment analyses identified the known and potential biological functions of the PPIN, such as cell migration and cancer-related pathways. Expression levels of the PPIN proteins, as well as their expression correlations, in five types of brain tumor, were analyzed and integrated into the PPIN to illustrate a dynamic change. A significant correlation was found between the survival time of glioblastoma patients and the expression level of 10 genes (LCN2, MMP9, MMP2, PDE4DIP, L2HGDH, HNRNPA1, DDX31, LOXL2, FAM60A and RNF25). Taken together, our results suggest that LCN2 and its interacting proteins are mostly differentially expressed and have a distinguishing co-expression pattern. They might promote proliferation and migration via cell migration signaling and cancer-related pathways. LCN2 and its interacting proteins might be potential biomarkers in glioblastoma.

Introduction

Lipocalin 2 (LCN2), also known as neutrophil gelatinase-associated lipocalin (NGAL), is a 25 kDa secreted glycoprotein and a member of the lipocalin family, which is involved in the transport of small hydrophobic molecules, such as retinol and vitamin D (Goetz et al., 2002, Flower, 1996). Elevated LCN2 expression has been observed in various human solid tumors, including breast, colorectal, ovarian, gastric, ovarian, bladder, kidney, lung cancers, and esophageal squamous cell carcinoma (ESCC) (Ören et al., 2016, McLean et al., 2013, Roli et al., 2017a, Roli et al., 2017b, Chakraborty et al., 2012, Lippi et al., 2014, Du et al., 2011). A higher expression level of LCN2 is usually associated with tumor size, development stage and invasion of carcinoma cells, serving as a poor prognostic factor. These characteristics strongly suggest LCN2 might be a potential biomarker and therapy target in malignancies. Many reports have demonstrated that LCN2 forms a protein complex with MMP9 by disulfide bond in the extracellular matrix to increase MMP9 enzymatic activity by preventing its degradation, resulting in the promotion of the invasive and metastatic potential of cancer cells both in vivo and in vitro (Yan et al., 2001, Fernandez et al., 2005, Kubben et al., 2007). In previous studies, we found the expression level of LCN2, as well as the activity of LCN2/MMP9 complex, were up-regulated in glioblastoma clinical tissues (Liu et al., 2011, Liu et al., 2015). This evidence strongly suggests that LCN2 and its interacting proteins, such as MMP9, might play important roles in brain tumors.

Since proteins perform different functions depending on the time-space interaction with other proteins, we may predict their functions through the interactions with neighboring proteins. Analyses based on protein-protein interaction networks (PPINs) have become prevalent and important after the generation of high-throughput data (Lotfi Shahreza et al., 2018). The PPIN is able to illustrate a large amount of information, such as expression level and correlations, to identify hub genes or predict drug targets (Barabasi et al., 2011). Network-based analyses aim to systematically integrate measurements from high-throughput data to gain a global understanding of cellular function under changing conditions, e.g. different disease sub-types or progressive stages of cancer (Barabasi et al., 2011, Zhang et al., 2016).

Thus, in this study, we constructed PPINs using LCN2 and its interacting proteins as core nodes. Our results show that LCN2 and its interacting proteins have various expression patterns in different brain tumors to promote the proliferation and migration in gliomas via cell migration signaling and cancer-related pathways. LCN2 and some of its interacting proteins might be potential biomarkers in glioblastoma.