CTHRC1 expression is a novel shared diagnostic and prognostic biomarker of survival in six different human cancer subtypes

According to the previous reports, the collagen triple helix repeat containing 1 (CTHRC1) causes tumorigenesis by modulating the tumor microenvironment, however, the evidence is limited to a few human cancer subtypes. In the current study, we analyzed and validated the CTHRC1 expression variations in 24 different human cancer tissues paired with normal tissues using publically available databases. We observed that CTHRC1 was overexpressed in all the 24 major subtypes of human cancers and its overexpression was significantly associated with the reduced overall survival (OS) duration of head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), liver hepatocellular carcinoma (LIHC), Lung adenocarcinoma (LUAD), stomach adenocarcinoma (STAD), and Uterine corpus endometrial carcinoma (UCEC). This implies that CTHRC1 plays a significant role in the development and progression of these cancers. We further noticed that CTHRC1 was also overexpressed in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of CTHRC1 associated genes in seven diverse pathways. We also explored few interesting correlations between CTHRC1 expression and promoter methylation, genetic alterations, CNVs, CD8+ T immune cells infiltration, and tumor purity. In conclusion, CTHRC1 can serve as a shared diagnostic and prognostic biomarker in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients of different clinicopathological features.

www.nature.com/scientificreports/ cancer 8 , colorectal, breast, and prostate cancer [9][10][11] . Moreover, Ke et al. have also confirmed that overexpression of CTHRC1 at translational level is significantly associated with the reduced overall survival (OS) duration of the non-small cell lung cancer (NSCLC) patients, but the potential causes behind CTHRC1 up-regulation was not elucidated in this study 7 . However, to the best of our knowledge, CTHRC1 dysregulation and its impact on the various other subtypes of cancer is yet to uncover. Therefore, the main aim of our study is to comprehensively investigate CTHRC1 in distinct other subtypes of human cancers and find more closely CTHRC1-associated cancer subtypes through an integrated analyses approach. For this purpose, we used UALCAN, GENT2, and HPA databases, as well as the Kaplan-Meier (KM) plotter tool to analyze and validate CTHRC1 expression and its correlation with the prognosis of distinct cancer subtypes. Furthermore, we utilized the TIMER database to find the Spearman correlation between CTHRC1 expression and CD8+ T cells infiltration and tumor purity. Additionally, we also explored the CTHRC1-associated genetic alterations, copy number variations (CNVs), DNA methylation, pathways, and gene-drug network. Taken together, our results indicated that CTHRC1 can be a potential diagnostic and prognostic biomarker and therapeutic target in head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), liver hepatocellular carcinoma (LIHC), Lung adenocarcinoma (LUAD), stomach adenocarcinoma (STAD), and Uterine corpus endometrial carcinoma (UCEC).

Methods
UALCAN. UALCAN (http:// ualcan. path. uab. edu) webserver is based on the TCGA OMICS data and is frequently used for expression profiling of the gene(s) of interest across more than 20 cancer subtypes. In our study, transcription expression and methylation profiling of CTHRC1 expression profiles across multiple cancer subtypes was evaluated via UALCAN 12 . All the analyses were run with the default settings in UALCAN. For statistics, this tool employs student t-test and normalized mRNA expression level as transcript per million (TPM) reads while the level of promoter methylation as beta (β) value. A p-value of < 0.05 was regarded statistically significant.
Kaplan-Meier plotter. Kaplan-Meier plotter (http:// kmplot. com/ analy sis/) 13 is an intuitive online tool for analyzing prognostic values of the gene(s) of interest in more than 20 cancer subtypes. This resource includes the survival data of approximately 54,675 genes derived from 10,461 cancerous samples of 30 different cancer subtypes. We carried out the overall survival (OS) analysis of CTHRC1 in distinct cancer subtypes using this tool. To access the OS, based on gene expression, cancer patients were divided into two different groups (high and low expression). Hazard ratios (HRs), 95% confidence intervals (CIs), and the log-rank p-value were also computed and displayed.  14 , and GEPIA (http:// gepia. cancer-pku. cn/) 18 were used to further validate the prognostic value of CTHRC1 in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC. These databases acquired expression and survival information from the Gene Expression Omnibus (GEO) based datasets. During the analysis, we simply queue the CTHRC1 gene in these databases to acquire the KM OS plots with hazard ratios (95%). GENT2 database. GENT2 (http:// gent2. appex. kr/) is a cancer transcriptomics data analysis webserver 19 .
The NCBI GEO database (https:// www. ncbi. nlm. nih. gov/ geo/) is a source of transcriptomics data for GENT2, that is acquired by the Affymetrix U133A and U133 Plus2 microarray platforms. In the current study, we used this database for the transcription expression validation of CTHRC1 using independent cohorts of distinct cancer patients. For statistics, this tool use student t-test. A p-value of < 0.05 was regarded statistically significant.

Immunohistochemistry (IHC) staining.
To analyze the differences in CTHRC1 proteomics expression level, CTHRC1 IHC images of proteomics expression in normal controls and six cancerous tissues (Head and neck cancer, kidney cancer, liver cancer, lung cancer, stomach cancer, and endometrial cancer) were taken from the HPA (Human Protein Atlas) database (http:// www. prote inatl as. org/) 20 and further analyzed. The observed proteomics expression level was graded as not detected, low, medium, and high, based on the intensity of staining and fraction of the stained cells.
cBioportal. cBioPortal (http:// www. cbiob ortal. org) database was created by Memorial Sloan Kettering Cancer Center (MSK) for analyzing TCGA genomic data of more than 30 cancer subtypes 21 . In our study, genetic mutational and copy number variations (CNVs) profiles of CTHRC1 in distinct human cancer subtypes were obtained using this database.
PPI network construction, visualization, and pathway enrichment analysis. In our study, we utilized the STRING database (https:// string-db. org/) 22 for subsequently analyzing the protein-protein interaction (PPI) network of CTHRC1. The main parameters for this PPI construction included: minimum required interaction score ["Low confidence (0.150)"], max numbers of interactors to show ("no more than 50 interactors" in 1st shell), and active interaction sources ("experiments"). The obtained PPI network was then visualized using Cytoscape software 3.7.2 23 24 . A p-value < 0.05 was considered as significant.

Tumor Immune Estimation Resource (TIMER) Database. Tumor Immune Estimation Resource
(TIMER) (http:// timer. cistr ome. org/) database in-house approximately 10,000 samples of more than 30 cancer subtypes from TCGA projects. It is an easy-to-use tool for systematically analyzing the Spearman correlation between immune infiltrate, tumor purity and expression level of the gene(s) of interest 25 . In this study, we evaluated the Spearman correlation between CTHRC1 expression and CD8+ T immune cells infiltration and tumor purity in distinct cancer subtypes using the TIMER database. A p-value < 0.05 was considered as significant.
CTHRC1 gene-drug interaction network analysis. In CTHRC1 drug-gene interaction network, we identified those drugs that interact with CTHRC1 and increase or decrease its mRNA expression using CTD (http:// ctdba se. org/) database and Cytoscape software 23 . The CTD database is a resource of physically curated drug-gene interactions from the literature 26 .     (Fig. 3). Taken together the results of CTHRC1 prognostic value analysis, it was observed that the higher expression level of SCTHRC1 is vital in the tumorgenesis of the HNSC, KIRC, LIHC, LUAD, STAD, and UCEC. Therefore the next part of our study will mainly focus on the unique role of CTHRC1 in these six types of human cancers.

Correlation between CTHRC1 transcriptional expression level and different clinicopathological features of HNSC, KIRC, LIHC, LUAD, STAD, and UCEC.
Using UALCAN and KM plotter tool, transcriptional expression analysis of CTHRC1 and its correlation analysis with the OS duration of the cancer patients showed that CTHRC1 level was significantly (p > 0.05) elevated and associated with the reduced OS duration of the HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients. Therefore, we next also explored the correlation between CTHRC1 expression level and different clinicopathological parameters of HNSC, KIRC,  Table 1.
Translational expression level of CTHRC1 in head and neck, kidney, liver, lung, stomach, and endometrial cancers. We also analyzed the CTHRC1 translational level in normal and head and neck, kidney, liver, lung, stomach, and endometrial cancers tissues using HPA. The obtained images from HPA revealed that CTHRC1 protein was not expressed or detected at a low level in head and neck (not expressed), kidney (not expressed), liver (low), lung (not expressed), and stomach (low), and endometrial normal tissues. However, its overexpression (medium) was detected in cancer tissues of the head and neck, kidney, liver, lung, stomach, and endometrial (Fig. 11).  27 . Therefore, we further analyzed that whether CTHRC1 transcription expression level was influenced by its promoter methylation level or not using UAL-CAN. As highlighted in Fig. 12, the box plots indicated that CTHRC1 transcription expression level was significantly (p > 0.005) influenced by its promoter hypomethylation in HNSC and UCEC, therefore, we speculate that the up-regulation of CTHRC1 in HNSC and UCEC might be the outcome of its promoter hypomethylation. However, the observed significant hypermethylation of CTHRC1 promoter in KIRC, LIHC, LUAD, and STAD challenges the classical view of methylation where overexpression is always associated with hypomethylation. Therefore, further detailed work is required to be done to explore the connection between hypermethylation of CTHRC1 promoter and its expression in KIRC, LIHC, LUAD, and STAD. In addition to promoter methylation, we also analyzed the contribution of genetic alterations and CNVs in the up-regulation of CTHRC1 via cBioPortal webserver using PanCancer Atlas datasets of HNSC, KIRC, LIHC, LUAD, STAD, and UCEC from TCGA. Our results revealed that CTHRC1 was genetically altered in only 4%, 0.6%, 9%, 4%, 5%, and 6% of the queued HNSC, KIRC, LIHC, LUAD, STAD, and UCEC samples, respectively, and deep amplification genetic abnormality was most frequent in these cancer subtypes (Fig. 13). Altogether, these results suggested that deep amplification may also participate in the overexpression of CTHRC1 in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC.
Pathway enrichment analysis of CTHRC1. To explore the CTHRC1 enriched pathways, a protein-protein interaction (PPI) network of CTHRC1 associated genes was obtained using the STRING database and visualized through Cytoscape. In total 11 nodes and 138 edges were found in the obtained PPI network (Fig. 13A).  Table 3).

CD8+ T immune cells infiltration and tumor purity of CTHRC1 in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients.
Tumor development is closely associated with immunity 28 . As CD8+ T immune cells are the major components of the immune system, we evaluated the Spearman correlation between CTHRC1 expression and CD8+ T immune infiltration in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC via TIMER database. Results of this analysis suggested a significant (p > 0.005) negative correlation between CD8+ T immune cells level and CTHRC1 higher expression in HNSC, KIRC, LUAD, and UCEC while a significant (p > 0.005) positive correlation between these two parameters in LIHC and STAD (Fig. 15). Collectivly these results highlighted a significant relationship between the CTHRC1 expression and CD8+ T immune cells infiltration. In addition, we have also explored the correlation between CTHRC1 expression and tumor purity in  (Fig. 15).

Gene-drug interaction network analysis of the CTHRC1.
In order to explore the relationship between CTHRC1 and available cancer therapeutic drugs, a gene-drug interaction network was developed using the CTD database. The expression of CTHRC1 could potentially influence by a variety of drugs. For example, cyciosperine and dicrotophos could elevate the expression level of CTHRC1 while valporic acid and doxorubicin could reduce CTHRC1 expression level (Fig. 16).

Discussion
CTHRC1 is an extracellular matrix protein that has earlier been linked to different cancers including cervical carcinoma 6 , non-small cell lung cancer 29 , endometrial cancer 8 , colorectal, breast, and prostate cancer 9-11 by the limited number of studies. In the current study, we comprehensively analyzed CTHRC1 in distinct human cancer subtypes for the first time and find more closely CTHRC1-associated cancer subtypes through the integrated analyses approach. In our study, we revealed that CTHRC1 expression was elevated in 24 major subtypes of human cancers, compared to normal controls. Moreover, CTHRC1 elevated expression was significantly associated with the reduced OS duration of the HNSC, KIRC, LIHC, LUAD, STAD, and UCEC, these results suggested the unique role of CTHRC1 up-regulation in the tumorgenesis of HNSC, KIRC, LIHC, LUAD, STAD, and UCEC. Therefore, in the present study, our main focus is these six cancers.
Following this, we next re-analyzed the CTHRC1 expression in different clinicopathological features of HNSC, KIRC, LIHC, LUAD, STAD, and UCEC, as a results, we also observed the significant (p < 0.05) up-regulation of CTHRC1 in different clinicopathological features of HNSC, KIRC, LIHC, LUAD, STAD, and UCEC including different cancer stages, patients races, genders, and age groups.
Epigenetic alterations are the main causes of gene expression fluctuations 30 . CTHRC1 has been reported to be overexpressed by its promoter hypomethylation in gastric cancer by earlier research 31 . In this study, we have shown that CTHRC1 expression was significantly affected by its promoter hypomethylation in HNSC and UCEC. Beside, along with up-regulation, we also revealed the hypermethylation of CTHRC1 promoter in KIRC, LIHC, LUAD, and STAD. This scenario challenges the classical view of methylation where overexpression is always associated with hypomethylation and demands further extensive research to resolve the conflict. Furthermore, genetic mutations and CNVs, including deep amplification, gain, loss, and deep deletion are known to alter the gene expression in tumorgenesis 32 . In our study, we observed that CTHRC1 was genetically altered in only 4%, 0.6%, 9%, 4%, 5%, and 6% of the queued HNSC, KIRC, LIHC, LUAD, STAD, and UCEC samples, respectively. The most frequently observed genetic abnormality in these cancer was maximum deep amplification. Taken together, our data suggest the slight influence of CNVs on the up-regulation of CTHRC1 in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC.  44 . However, best to our knowledge, none of these or any other biomarkers have been generalized so far in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients of different clinicopathological features. In our study, we have shown the significant (p < 0.05) up-regulation of CTHRC1 expression in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients of various clinicopathological features (different cancer stages, patients races, genders, and age groups) as compared to the normal controls. Furthermore, CTHRC1 promoter methylation level and OS information have also proven its useful values as a novel potential biomarker of these cancers. Therefore, this is the first study that reported the shared clinicopathological features-specific diagnostic and prognostic potential of CTHRC1 in six different cancers including HNSC, KIRC, LIHC, LUAD, STAD, and UCEC, which may provide new therapeutic possibilities for cancer patients.
Immunotherapy has proven to be very successful in treating solid tumors 45 . Interestingly, we revealed that there is a close correlation between CTHRC1 expression and CD8+ T immune infiltration, which may contribute to the development of HNSC, KIRC, LIHC, LUAD, STAD, and UCEC by affecting the tumor microenvironment. To date, no previous study has reported these such correlations between CTHRC1 and CD8+ T cells level in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients of different clinicopathological features. Therefore, this valuable knowledge may help to design more precise immunotherapy for cancer patients. Moreover, we have also found that CTHRC1 expression was inversely correlated with tumor purity in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC, this knowledge may also help in predicting the clinical outcomes in HNSC, KIRC, LIHC, LUAD, STAD, and UCEC.
Protein-protein interactions are the core of biological pathways. The CTHRC1 PPI network revealed a set of ten genes that directly interact with CTHRC1. Most of them were involved in different signaling pathways including Basal cell carcinoma, Melanogenesis, Wnt signaling pathway, Signaling pathways regulating pluripotency www.nature.com/scientificreports/ of stem cells, Hippo signaling pathway, Proteoglycans in cancer, and Notch signaling pathway. Additionally, we have also identified few potential drugs that could influence the expression level of CTHRC1 in cancer, however, whether HNSC, KIRC, LIHC, LUAD, STAD, and UCEC patients with overexpressed CTHRC1 can benefit from these drugs or whether CTHRC1 may be targeted by these drugs in the treatment of these cancers needs biological experimental support.