Low expression of CHRDL1 and SPARCL1 predicts poor prognosis of lung adenocarcinoma based on comprehensive analysis and immunohistochemical validation

Abstract

Purpose: Exploring the molecular mechanisms of lung adenocarcinoma (LUAD) is beneficial for developing new therapeutic strategies and predicting prognosis. This study was performed to select core genes related to LUAD and to analyze their prognostic value.

Methods: Microarray datasets from the GEO (GSE75037) and TCGA-LUAD datasets were analyzed to identify differentially coexpressed genes in LUAD using weighted gene coexpression network analysis (WGCNA) and differential gene expression analysis. Functional enrichment analysis was conducted, and a protein-protein interaction (PPI) network was established. Subsequently, hub genes were identified using the CytoHubba plug-in. Overall survival (OS) analyses of hub genes were performed. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Human Protein Atlas (THPA) databases were used to validate our findings. Gene set enrichment analysis (GSEA) of survival-related hub genes were conducted. Immunohistochemistry (IHC) was carried out to validate our findings.

Results: We identified 486 differentially coexpressed genes. Functional enrichment analysis suggested these genes were primarily enriched in the regulation of epithelial cell proliferation, collagen-containing extracellular matrix, transforming growth factor beta binding, and signaling pathways regulating the pluripotency of stem cells. Ten hub genes were detected using the maximal clique centrality (MCC) algorithm, and four genes were closely associated with OS. The CPTAC and THPA databases revealed that CHRDL1 and SPARCL1 were downregulated at the mRNA and protein expression levels in LUAD, whereas SPP1 was upregulated. GSEA demonstrated that DNA-dependent DNA replication and catalytic activity acting on RNA were correlated with CHRDL1 and SPARCL1 expression, respectively. The IHC results suggested that CHRDL1 and SPARCL1 were significantly downregulated in LUAD.

Conclusions: Our study revealed that survival-related hub genes closely correlated with the initiation and progression of LUAD. Furthermore, CHRDL1 and SPARCL1 are potential therapeutic and prognostic indicators of LUAD.

Keywords: Differential coexpression genes; Lung adenocarcinoma; Protein–protein interaction network; Survival analysis; Weighted gene coexpression network analysis.

Fig. 1

Study design and workflow of our study

Fig. 2

Identification of modules correlated with the clinical traits in GSE75037. a Sample dendrogram and trait heatmap. b Scale independence and Mean connectivity. c The Cluster dendrogram of co-expression network modules is ordered by a hierarchical clustering of genes based on the 1-TOM matrix. Different colors represent different modules. d Module-trait relationships. Each row represents a color module and every column represents a clinical trait (normal and tumor). Each cell contains the corresponding correlation and P-value

Fig. 3

Identification of modules correlated with the clinical traits in TCGA-LUAD dataset. a Sample dendrogram and trait heatmap. b Scale independence and mean connectivity. c The Cluster dendrogram of co-expression network modules is ordered by a hierarchical clustering of genes based on the 1-TOM matrix. Different colors represent different modules. d Module-trait relationships. Each row represents a color module and every column represents a clinical trait (normal and tumor). Each cell contains the corresponding correlation and P-value

Fig. 4

Identification of differentially expressed genes (DEGs) among GSE75037 TCGA-LUAD dataset with the cut-off criteria of |logFC| > 1 and adj.P < 0.05. a Heatmap of 50 upregulated and 50 downregulated DEGs of GSE75037. b Heatmap of 50 upregulated and 50 downregulated DEGs of TCGA-LUAD dataset. c Volcano plot of DEGs in GSE75037. d Volcano plot of DEGs in TCGA-LUAD dataset. e The Venn diagram of genes among the two DEG lists and the two lists of co-expression genes. In total, 486 overlapping differential co-expression genes are found

Fig. 5

Functional enrichment analysis of differential co-expression genes using the clusterProfiler package. a Gene ontology (GO) enrichment analysis of differential co-expression genes. b Kyoto encyclopedia of genes and genomes pathway (KEGG) of differential co-expression genes

Fig. 6

Visualization of the protein–protein interaction (PPI) network, the most significant module and hub genes. a PPI network of differential co-expression genes. b The most significant module from PPI network. c Selection of hub genes from PPI network through maximal clique centrality (MCC) algorithm. The turquoise nodes represent the genes. Edges suggest the protein–protein relations. The red nodes represent genes with high MCC values, while the yellow nodes represent genes with low MCC values

Fig. 7

Prognostic roles of 10 hub genes and relation with pathological stages in patients of TCGA-LUAD dataset. Survival analysis for a CHRDL1, SPARCL1, SPP1, PENK, CYR61, CP, GAS6, GPC3, IL6 and WFS1 in LUAD. The LUAD patients are divided into high expression cohort (red) and low expression cohort (blue) according to the median expression of hub genes. Log-rank P < 0.05 is believed a statistical difference. b The relations of b CHRDL1, c SPARCL1, d SPP1 and e PENK with pathological stages among patients from TCGA-LUAD dataset

Fig. 8

External validation of the expression patterns of survival-related hub genes based on GSE19188 and Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. The mRNA (a) and protein (b) expression patterns of CHRDL1 are compared between LUAD and normal lung tissues. The mRNA (c) and protein (d) expression patterns of SPARCL1 are compared between LUAD and normal lung tissues. The mRNA (e) and protein (f) expression patterns of SPP1 are compared between LUAD and normal lung tissues. The mRNA (e) expression pattern of PENK is compared between LUAD and normal lung tissues

Fig. 9

Enrichment plots by gene set enrichment analysis (GSEA). Relative pathways associated with the expression of CHRDL1 (a), SPARCL1 (b), SPP1 (c), and PENK (d) are illustrated

Fig. 10

The distribution and expression of CHRDL1 and SPARCL1 proteins in twenty pairs of LUAD and normal tissues. Representative pictures of immunohistochemistry of CHRDL1 and SPARCL1 proteins are shown (a, b). The score of immunohistochemistry of CHRDL1 and SPARCL1 proteins are displayed (c, d). ***P = 0.001; ****P < 0.001