Comprehensive analysis reveals a CTHRC1-based fourteen-gene signature for prognosis prediction in colon cancer

doi:10.21203/rs.3.rs-1552687/v1

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Research Article

Comprehensive analysis reveals a CTHRC1-based fourteen-gene signature for prognosis prediction in colon cancer

https://doi.org/10.21203/rs.3.rs-1552687/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted 18 Apr, 2022

You are reading this latest preprint version

Background: Colon cancer is a malignant gastrointestinal tumor and is still a worldwide leading cause of cancer-related mortality. Owing to the development of high-throughput sequencing technologies, large-scale data have become available in public databases. We devoted to construct and validate a gene signature that can predict patients’ outcomes for colon cancer using bioinformatics methods.

Methods: We integrated GSE44076 and GSE39582 to identify differentially expressed genes (DEGs). Timer 2.0 was used to analysis CTHRC1 expression in various types of cancer. The relationship of clinicopathological features and CTHRC1 expression was explored based on TCGA database. Hub genes were identified by String database and Cytoscape software. The gene prognostic signature was established based on the Cox regression analysis.

Results: We obtained 170 common DEGs and confirmed CTHRC1 was significantly overexpressed in colon cancer samples (P < 0.001). High CTHRC1 level was associated with advanced stage and shorter overall survival (OS) time and relapse-free survival (RFS) time in colon cancer patients. We identified thirteen hub genes among 516 genes co-expressed with CTHRC1 and subsequently constructed a 14-gene risk signature, which associated advanced stage and poor OS (log-rank test p < 0.01). Multivariate Cox regression indicated that high risk score was an independent risk factor for poor prognosis (p < 0.01). Finally, Receiver operating characteristic curve analysis was performed to further confirm the validity of the signature.

Conclusions: We confirmed the important role of CTHRC1 in colon cancer and further constructed a 14-gene risk signature with promising prognostic accuracy for colon cancer patients.

colon cancer

CTHRC1

gene signature

prognosis prediction

Colon cancer is the fifth most frequently diagnosed malignancy and the fifth leading cause of cancer-related mortality worldwide[1]. Although the overall colon cancer incidence rate has declined owing to the increasing use of colonoscopy screening, incidence rates among people younger than 50 years have been rising since the end of the last century[2]. Despite many advances achieved in diagnostic and therapeutic strategies, the survival of colon cancer patients remains poor[3]. A previous study showed that deaths from colon cancer are predicted to increase substantially to 2035[4]. Hence, it is crucial to identify biomarkers for colon cancer prognosis and thus guide individualized therapeutics.

Collagen triple helix repeat containing-1 (CTHRC1) consists of an NH2-terminal peptide, a short collagen triple helix repeat of 36 amino acids, and a COOH-terminal globular domain[5, 6]. As an extracellular matrix (ECM) protein, CTHRC1 could interact with various intracellular and extracellular matrices in different ways of secretion[7, 8]. CTHRC1 has been proved to be involved in a variety of biological processes, including vascular remodeling[9], acute wound healing[10], bone formation and remodeling[11, 12], apoptosis[13], anti-inflammatory[14], fat and glycogen synthesis[7, 15]. Extensive evidence suggests that the high expression of CTHRC1 promotes tumorigenesis and development through positive regulation of tumor spread, invasion, migration, adhesion, and metastasis [16].

The occurrence and progression of colon cancer is a complicated process involving multiple gene expression alteration. Compared with the traditional prognostic predictors of colon cancer, such as the degree of tumor differentiation and the depth of tumor invasion, molecular signature has been reported more and more in the prediction of colon cancer in recent years with the development of high-throughput sequencing technology and bioinformatics tools. Although the past few years have seen the emergence of numerous molecular signatures for colon cancer prognosis[17, 18], the role of CTHRC1 in prognostic prediction of colon cancer has not been fully explored. Therefore, the analysis and integration of gene expression data from public databases and detailed analysis of CTHRC1 expression profile may reveal more representative gene expression characteristics associated with colon cancer prognosis.

Identification of gene expression patterns in colon tumor

To investigate the unique gene expression patterns in colon tumor tissues, we analyzed two independent data sets of gene expression in colon tumors (GSE44076 and GSE39582). Analysis of GSE44076 and GSE39582 identified 404 (log2FC > 2, P < 0.05) and 274 (log2FC > 2, P < 0.05) differentially expressed genes (DEGs) in normal colon tissue and colon tumor tissue, respectively (Fig. 1A, B). In order to obtain more reliable results, we intersected these DEGs and obtained 170 common genes (Fig. 1C). Furthermore, we performed GO enrichment analysis and the result showed that DEGs were significantly enriched in extracellular matrix organization and extracellular structure organization in the biological process group; apical part of cell and apical plasma membrane in the cellular component group; receptor ligand activity and signaling receptor activator activity in the molecular function group (Fig. 1D).

CTHRC1 is up-regulated in colon cancer tissues

CTHRC1 is a cancer-associated protein and is involved in tissue damage repair, which has attracted our attention. Analysis of CTHRC1 gene expression data in TCGA-COAD and GSE115313 cohorts confirmed that CTHRC1 was overexpressed in colon cancer tissues (Fig. 2A, B). We used the Timer 2.0 tool to screen for CTHRC1 expression in multiple cancer types, and found that CTHRC1 was significantly upregulated in 23 cancer types, especially in colon adenocarcinoma (Fig.2C). These results suggest that CTHRC1 may play an important role in the occurrence and development of colon cancer.

CTHRC1 overexpression predicts poor prognosis in COAD patients

In addition, we conducted Kaplan-Meier survival analysis in three cohorts (GSE17536 cohort, GSE39582 cohort, TCGA-COAD cohort) to examine the association between CTHRC1 expression and the survival. The optimal threshold was determined by the surv_cutpoint function in the survminer R package, and the patients were thus divided into high- and low- CTHRC1 groups. The results indicated that high CTHRC1 expression significantly correlated to shorter OS and RFS in colon cancer patients (Fig. 3A-D). Interestingly, the multivariate Cox analysis result suggested that increased CTHRC1 expression [hazard ratio (HR) = 1.724, 95% confidence interval (CI) 1.0797–2.75; p < 0.05] have the potential to act as an independent predictor of poor prognosis (Fig. 3E).

GO and KEGG enrichment analysis of CTHRC1 and co-expression genes and identification of hub genes.

Subsequently, we analyzed gene expression data of GSE39582 cohort and acquired 516 genes co-expressed with CTHRC1 (absolute Pearson correlation coefficient > 0.5, p < 0.001). GO and KEGG enrichment analysis of the co-expressed genes showed the top 30 items. GO functional enrichment analysis indicated that these genes were enriched in extracellular matrix organization and extracellular structure organization in the biological process group; collagen-containing extracellular matrix and endoplasmic reticulum lumen in the cellular component group; extracellular matrix structural constituent and glycosaminoglycan binding in the molecular function group (Fig. 4A). KEGG enrichment analysis showing the enrichment of various pathways including PI3K-Akt signaling pathway, focal adhesion, proteoglycans in cancer and human papillomavirus infection, etc (Fig. 4B). STRING database was employed to establish a PPI network and by opening it with Cytoscape software, we constructed a co-expression network. Hub genes in the network were identified via the cytoHubba application in Cytoscape software. The 13 hub genes are COL1A2, COL3A1, COL12A1, FBN1, SDC2, POSTN, THBS2, ADAMTS12, COL1A1, MMP9, COL5A2, COL6A3 and CDH11(Fig. 4C).

Establishment of the risk model on colon cancer

The risk signature based on CTHRC1 and 13 hub genes was established. For each patient in the TCGA-COAD cohort, the risk score was calculated, and patients were divided into high-risk and low-risk groups based on the median risk score (Fig. 5A). More deaths occurred in patients with high-risk group than those with low-risk group and the gene expression of risk signature showed significant difference between high-risk group and low-risk group (Fig. 5B-C). Multivariate Cox analyses revealed that the risk score of a 14-gene signature was an independent prognostic factor for colon cancer patients in TCGA cohort (Fig. 5D). In addition, risk score showed significant changes between early stage (I and II) and normal tissue though non-significant difference between early and advanced (III and IV) stages in COAD patients was observed (Fig. 5E). Kaplan-Meier survival curves showed that the high-risk group had a worse prognosis (p < 0.01, Fig. 5F). The area under curve (AUC) values of the 1-, 3-, and 5-year Receiver Operating Characteristic (ROC) curves were 0.656, 0.654, and 0.627, respectively (Fig. 5G).

Validation of the risk model

To validate the risk model, we selected a test cohort based on GSE39582 and performed univariate and multivariate Cox regression analyses. In accord with the TCGA cohort, the risk score of the 14-gene signature could be an independent prognostic factor for colon cancer patients. (p < 0.01, Fig. 6 A, B). Patients in the high risk score group showed poor OS. (p < 0.001, Fig. 6 C). Receiver Operating Characteristic (ROC) curve was employed for the assessment of predictive ability of the risk model, and the area under curve indicated that the risk model was effective (Fig. 6 D). Taken together, the model we provided was proved to be an effective and well-predicting model.

Gene Set Enrichment Analysis of the high-risk group

GSEA was used to determine the functions of gene sets in the high-risk group. We set the cutoff value of FDR q-value at < 0.05 and NES at > 2.0. We found that epithelial mesenchymal transition (FDR q-value, 0.023; normalized enrichment score, 2.07) and angiogenesis (FDR q-value, 0.023; normalized enrichment score, 2.03) were significantly enriched in high-risk group in the TCGA dataset (Fig. 7 A, B). Taken together, we deduced that patients in high-risk group could promote the development of colon cancer through the activation of EMT and angiogenesis pathways and subsequently influence their outcomes.

The collagen triple helix repeat containing 1 (CTHRC1) gene was first reported in a screen for genes differentially expressed in balloon-injured versus normal rat arteries[5]. It was transiently expressed by fibroblasts of the remodeling adventitia and by smooth muscle cells of the neointima on injury in rat aorta, and it may contribute to vascular remodeling by limiting collagen matrix deposition and promoting cell migration[5]. Moreover, Tang et al.[19] found that CTHRC1 could be aberrantly expressed in various types of human solid tumors, including melanoma, breast cancer, gastrointestinal, and HCC. Meanwhile, CTHRC1 was functionally associated with melanoma migration, invasiveness, and metastasis[19]. Thus, the relationship between CTHRC1 expression and tumor was established. However, the concrete regulatory mechanism underlying the effect of CTHRC1 expression on tumor environment remains to be elucidated. Studies have revealed that CpG methylation levels were very low in primary colorectal cancer compared to paired normal tissues, suggesting demethylation of CTHRC1 promoter may give rise to CTHRC1 upregulation[20]. CTHRC1 could exert different effects through several signaling pathways such as TGF-β, Wnt, integrin β/FAK, Src/FAK, MEK/ERK, PI3K/AKT/ERK, HIF-1α, and PKC-δ/ERK signaling pathways[16]. In cervical cancer, E6/E7 regulates the expression of CTHRC1 and thus activates Wnt/PCP signaling pathway, which aggravates tumor malignancy[8]. CTHRC1 promotes liver fibrosis through the TGF-β pathway, thereby increasing the likelihood of developing liver cancer[21]. Here, an integrated bioinformatic analysis was performed to explore the role of CTHRC1 in a potential prognostic biomarker for colon cancer. We showed that CTHRC1 expression was up-regulated in colon cancer tissues, and high CTHRC1 expression was associated with worse OS and clinicopathological features. Moreover, CTHRC1 expression showed potential as an independent prognostic factor for colon cancer patients.

The collagen family comprises 28 members, including COL1A1, COL1A2, COL3A1, COL5A2, COL6A3, COL12A1. Collagens are deposited in the extracellular matrix, which could explain the GO enrichment analysis results: most terms in biological process group and cellular components group are extracellular matrix and collagen related. The extracellular matrix (ECM) plays an important role in cancer progression, and the major components of the ECM are the collagens[22]. Previous studies have reported that collagen could facilitate the CRC stemness and metastasis[23]. Abnormal COL12A1 expression is associated with carcinogenesis of CRC[24]. Besides, a study indicated COL1A1, a major component of collagen type I, was overexpressed in a variety of tumor tissues and promoted metastasis in CRC[25]. KEGG analysis showed that the PI3K (phosphatidylinositol-4,5-bisphosphate 3-kinase)/AKT (v-akt murine thymoma viral oncogene homologue) pathway and focal adhesion were enriched in the CTHRC1 and co-expressed genes. The PI3K/AKT pathway is frequently activated in various human cancers and has been considered a promising therapeutic target[26]. Kim et al[27] observed that THBS2 influences the proteolysis of tumor cytoplasm, thus contributing to the activation and expression of certain proteins in the PI3K/Akt signaling pathway. MMPs represent a family of zinc metallo-endopeptidases, and MMP9 can degrade type I collagen and break tumor cells from the primary tumor site, leading to invasion and metastasis[28]. Kim et al[20] found that CTHRC1 has a positive correlation with MMP9 and CTHRC1 promotes cancer cell invasiveness through ERK-dependent induction of MMP9 expression in human colon cancer, which is consistent with our study that MMP9 is one of the hub genes of CTHRC1.

In the present study, we first verified CTHRC1 was highly overexpressed in colon cancer cells and correlated with a worse prognosis, which was consistent with earlier studies[29]. Subsequently, we explored the relationship of CTHRC1 expression and tumor immune microenvironment. To describe more accurate and reliable prognostic characteristics of colon cancer patients, A risk model was determined according to CTHRC1 and its hub genes, which could stratify patients with colon cancer into high- and low-risk groups. The risk model was established using the TCGA dataset and validated in the GSE39582 dataset. Our results suggested that OS in the high-risk group was shorter than that noted in the low-risk group. Additionally, the ROC curve and AUC verified accuracy of the risk model in survival prediction. Taken together, we concluded that the risk signature was a strong and independent predictor for colon cancer and correlated with OS.

Nevertheless, some limitations to our study should be acknowledged. First of all, we cannot avoid that our research results are based on published database, and the results should be verified in prospective studies. Second, functional experimental studies should be conducted on these genes to progressively elucidate the function of these genes in colon cancer.

In summary, we screened DEGs between colon cancer tissues and adjacent normal colon tissues and identified CTHRC1 was overexpressed in colon cancer. Increased CTHRC1 expression was related to advanced stage and shorter OS. We finally constructed and validated a 14-gene risk signature to predict the prognosis of patients with colon cancer.

Data Source and Analysis

The gene expression data and clinical information used in this study were obtained from Gene-Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/) and the Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). We included four GEO datasets and a TCGA cohort: (1) the GSE44076 datasets, which included paired normal adjacent mucosa and colon cancer samples from 98 individuals and 50 healthy colon mucosae; (2) the GSE39582 datasets, which included 566 colon cancer samples and 19 non-tumoral colorectal mucosae; (3) the GSE115313 datasets, which included paired normal adjacent mucosa and colon cancer samples from 42 individuals; (4) the GSE17536 datasets, which included 177 colon cancer patients; (5) the TCGA-COAD cohort, which included 452 COAD patients. GSE44076 and GSE39582 was normalized and processed to identify differentially expressed genes (DEGs) using the limma package (version 3.46.0). Probe IDs were converted to the corresponding gene symbols according to the platform annotation information. We used the Timer 2.0 (http://timer.cistrome.org/) database to analyze the expression of specific genes in different types of cancer[30].

Gene Ontology (GO) and Pathway Enrichment Analysis

GO analysis covered three domains: biological process (BP), cellular components (CC) and molecular functions (MF). Using the GO database, we obtain the biological functions of our target genes at the three levels of CC, MF and BP[31]. Kyoto Encyclopedia of Genes and Genomes (KEGG) (https://www.kegg.jp/), a database integrating genomic, chemical, and system functional information, is commonly used for biological pathway information analysis[32]. Both GO analysis and KEGG analysis were performed using the clusterProfiler package (version 3.18.1) of R software (version 4.0.3).

Protein-protein Interaction (PPI) Network Analysis for Co-expressed Genes

STRING database (https://string-db.org/)[33] was employed to predict the protein-protein interactions among genes co-expressed with CTHRC1. Furthermore, Cytoscape (version 3.8.2)[34] was used to visualize the obtained PPI network data files, and hub genes were identified by cytoHubba plugin (version 0.1, https://apps.cytoscape.org/apps/cytohubba).

Establishment of the Risk Signature

We incorporated CTHRC1 and its 13 hub genes into a multivariate Cox regression model to establish risk signature. For each patient, we will calculate a risk score using the following formula: risk score = β_gene1 × exp_gene1 + β_gene2 × exp_gene2 + . . . + β_genen × exp_genen. The risk score may act as a prognostic marker for colon cancer patient. The risk scores were assigned according to linear combinations of the gene expression values weighted by the regression coefficients (β). According to the median risk score, the patients were divided into high- and low-risk groups. The expression level of gene is deﬁned as exp_genen.

Gene set enrichment analysis (GSEA)

GSEA was performed using Java GSEA software v4.1.0 (http://www.broadinstitute.org/gsea). Enrichment scores (ES) were calculated with random gene set permutation 1000. Gene sets were created with h.all.v7.4.symbols.gmt [Hallmarks]. Significance was considered at a false discovery rate (FDR) of <0.05.

Statistics Analysis

All statistical analyses were performed using R (v.4.0.3). To evaluate the correlation between CTHRC1 expression and other variables (TNM stage, tumor size, lymph node metastasis, distant metastasis, and OS), we performed Chi-square Tests and Wilcoxon/Kruskal–Wallis test. P values < 0.05 was considered statistically significant differences.

CTHRC1: Collagen triple helix repeat containing-1, COAD: Colorectal adenocarcinoma.

Ethics approval and consent to participate:

Not necessary.

Consent for publication:

Not applicable.

Availability of data and materials:

The raw data of this study are derived from the TCGA database (https://portal.gdc.cancer.gov/) and GEO data portal (https://www.ncbi.nlm.nih.gov/geo/), which are publicly available databases.

Competing interests:

The authors declare that they have no competing interests.

Funding:

We are very grateful for the support of the National Natural Science Foundation of China (Grant number: 81672364, Grant number: 81871917).

Authors’ contributions:

This research was conducted in collaboration with all authors. XM and MJ performed the data curation and analysis. CY and MY analyzed and interpreted the results. YX, ZQ and WJW drafted and reviewed the manuscript. All authors read and approved the final manuscript.

Acknowledgements:

The authors gratefully acknowledge the Gene Expression Omnibus (GEO) database, and the Cancer Genome Atlas (TCGA) database, which made the data available.

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No competing interests reported.

PDF

Version 1

posted 18 Apr, 2022

You are reading this latest preprint version

Comprehensive analysis reveals a CTHRC1-based fourteen-gene signature for prognosis prediction in colon cancer

Status:

Version 1

Abstract

Figures

Introduction

Results

Identification of gene expression patterns in colon tumor

CTHRC1 is up-regulated in colon cancer tissues

CTHRC1 overexpression predicts poor prognosis in COAD patients

GO and KEGG enrichment analysis of CTHRC1 and co-expression genes and identification of hub genes.

Establishment of the risk model on colon cancer

Validation of the risk model

Gene Set Enrichment Analysis of the high-risk group

Discussion

Conclusion

Materials And Methods

Data Source and Analysis

Gene Ontology (GO) and Pathway Enrichment Analysis

Protein-protein Interaction (PPI) Network Analysis for Co-expressed Genes

Establishment of the Risk Signature

Gene set enrichment analysis (GSEA)

Statistics Analysis

Abbreviations

Declarations

References

Competing Interests

Status:

Version 1