Application Potential of CTHRC1 as a Diagnostic and Prognostic Indicator for Colon Adenocarcinoma

Expression, Prognostic Value, and Biological Function of CTHRC1 in Different Types of Gliomas: A Bioinformatic Analysis and Experiment Validation

Background

In recent years, abnormal expression of collagen triple helix repeat containing 1 (CTHRC1) has been found in some tumors, closely related to the poor prognosis of cancer patients. However, the clinical significance of CTHRC1 in gliomas is not completely understood.

Methods

We investigated the expression, prognostic value, and potential biological function of CTHRC1 in different types of gliomas through bioinformatics analysis and experimental verification.

Results

Bioinformatics analysis revealed several key findings regarding the expression and clinical significance of CTHRC1 in gliomas. First, the analysis demonstrated a positive correlation between CTHRC1 expression and the World Health Organization (WHO) grading of gliomas, a relationship that was validated through immunohistochemistry experiments. In addition, a trend was observed in which CTHRC1 expression increased with the extent of glioma invasion, as supported by Western blot experiments. Subsequent bioinformatics analysis identified the mesenchymal subtype of gliomas as having the highest levels of CTHRC1 expression, a finding reinforced by immunohistochemical staining. Moreover, high CTHRC1 expression was associated with poor prognosis in gliomas and emerged as an independent prognostic factor, with varying impacts on prognosis between low-grade gliomas (LGGs) and glioblastoma (GBM) subgroups. Notably, comparative analysis unveiled distinct patterns of immune infiltration of CTHRC1 in LGG and GBM. Furthermore, alterations in copy number variations and DNA methylation were identified as potential mechanisms underlying elevated CTHRC1 levels in gliomas. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that CTHRC1 and its associated genes mainly function in the extracellular matrix and participate in tumor-related signaling pathways.

Conclusions

The CTHRC1 has shown significant clinical utility as a prognostic marker and mesenchymal subtype marker of glioma.

The role of collagen triple helix repeat containing 1 (CTHRC1) in cancer development and progression

INTRODUCTION

Collagen triple helix repeat containing 1 (CTHRC1) is a protein that has been implicated in pro-migratory pathways, arterial tissue-repair processes, and inhibition of collagen deposition via the regulation of multiple signaling cascades. Studies have also demonstrated an upregulation of CTHRC1 in multiple cancers where it has been linked to enhanced proliferation, invasion, and metastasis. However, the understanding of the exact role and mechanisms of CTHRC1 in cancer is far from complete.

AREAS COVERED

This review focuses on analyzing the role of CTHRC1 in cancer as well as its associations with clinicopathologies and cancer-related processes and signaling. We have also summarized the available literature information regarding the role of CTHRC1 in tumor microenvironment and immune signaling. Finally, we have discussed the mechanisms associated with CTHRC1 regulations, and opportunities and challenges regarding the development of CTHRC1 as a potential target for cancer management.

EXPERT OPINION

CTHRC1 is a multifaceted protein with critical roles in cancer progression and other pathological conditions. Its association with lower overall survival in various cancers, and impact on the tumor immune microenvironment make it an intriguing target for further research and potential therapeutic interventions in cancer.

A Novel Molecular Analysis Approach in Colorectal Cancer Suggests New Treatment Opportunities

Colorectal cancer (CRC) is a molecular and clinically heterogeneous disease. In 2015, the Colorectal Cancer Subtyping Consortium classified CRC into four consensus molecular subtypes (CMS), but these CMS have had little impact on clinical practice. The purpose of this study is to deepen the molecular characterization of CRC. A novel approach, based on probabilistic graphical models (PGM) and sparse k-means-consensus cluster layer analyses, was applied in order to functionally characterize CRC tumors. First, PGM was used to functionally characterize CRC, and then sparse k-means-consensus cluster was used to explore layers of biological information and establish classifications. To this aim, gene expression and clinical data of 805 CRC samples from three databases were analyzed. Three different layers based on biological features were identified: adhesion, immune, and molecular. The adhesion layer divided patients into high and low adhesion groups, with prognostic value. The immune layer divided patients into immune-high and immune-low groups, according to the expression of immune-related genes. The molecular layer established four molecular groups related to stem cells, metabolism, the Wnt signaling pathway, and extracellular functions. Immune-high patients, with higher expression of immune-related genes and genes involved in the viral mimicry response, may benefit from immunotherapy and viral mimicry-related therapies. Additionally, several possible therapeutic targets have been identified in each molecular group. Therefore, this improved CRC classification could be useful in searching for new therapeutic targets and specific therapeutic strategies in CRC disease.

Bioinformatics Analysis of LGR4 in Colon Adenocarcinoma as Potential Diagnostic Biomarker, Therapeutic Target and Promoting Immune Cell Infiltration

Colon adenocarcinoma is one of the tumors with the highest mortality rate, and tumorigenesis or development of colon adenocarcinoma is the major reason leading to patient death. However, the molecular mechanism and biomarker to predict tumor progression are currently unclear. With the goal of understanding the molecular mechanism and tumor progression, we utilized the TCGA database to identify differentially expressed genes. After identifying the differentially expressed genes among colon adenocarcinoma tissues with different expression levels of LGR4 and normal tissue, protein–protein interaction, gene ontology, pathway enrichment, gene set enrichment analysis, and immune cell infiltration analysis were conducted. Here, the top 10 hub genes, i.e., ALB, F2, APOA2, CYP1A1, SPRR2B, APOA1, APOB, CYP3A4, SST, and GCG, were identified, and relative correlation analysis was conducted. Kaplan–Meier analysis revealed that higher expression of LGR4 correlates with overall survival of colon adenocarcinoma patients, although expression levels of LGR4 in normal tissues are higher than in tumor tissues. Further functional analysis demonstrated that higher expression of LGR4 in colon adenocarcinoma may be linked to up-regulate metabolism-related pathways, for example, the cholesterol biosynthesis pathway. These results were confirmed by gene set enrichment analysis. Immune cell infiltration analysis clearly showed that the infiltration percentage of T cells was significantly higher than other immune cells, and TIMER analysis revealed a positive correlation between T-cell infiltration and LGR4 expression. Finally, COAD cancer cells, Caco-2, were employed to be incubated with squalene and 25-hydroxycholesterol-3-sulfate, and relative experimental results confirmed that the cholesterol biosynthesis pathway involved in modulating the proliferation of COAD tumorigenesis. Our investigation revealed that LGR4 can be an emerging diagnostic and prognostic biomarker for colon adenocarcinoma by affecting metabolism-related pathways.