Co-expression Network Analysis Identified COL8A1 Is Associated with the Progression and Prognosis in Human Colon Adenocarcinoma

Identification of Novel lncRNAs Related to Colorectal Cancer Through Bioinformatics Analysis

Long noncoding RNA (lncRNA) plays a critical role in cancer cell proliferation, invasion, metastasis, and chemoresistance. The current study introduces novel lncRNAs in colorectal cancer (CRC) through bioinformatics analysis. GSE134834 CRC-related microarray of Gene Expression Omnibus (GEO) was analyzed to identify differentially expressed genes (DEGs) in CRC samples against normal samples. Analysis revealed 6763 DEGs (p < 0.05 and |log fold change (FC)| ≥ 0.5) that include differentially expressed mRNA (DEmRNA) and differentially expressed long noncoding RNA (DElncRNA). Novel lncRNAs were identified, and to better understand the biological function of the identified lncRNAs, gene modules were constructed using weighted gene coexpression network analysis (WGCNA), and finally, two modules for lncRNAs were obtained. The coexpression modules with these lncRNAs were subjected to enrichment analysis in FunRich software to predict their functions through their coexpressed genes. Gene ontology results of modules related to novel lncRNA revealed they significantly enriched the cellular pathways regulation in cancer. The protein-protein interaction (PPI) network of novel lncRNAs-related modules was constructed using Search Tool for the Retrieval of Interacting Genes (STRING) and visualized using the Cytoscape software. Hub genes were screened from the PPI network by the CytoHubba plug-in of Cytoscape. The hub genes were MRTO4, CDK1, CDC20, RPF2, NOP58, NIFK, GTPBP4, BUB1, BUB1B, and BOP1 for the lightpink4 module and BYSL, RPS23 (ribosomal protein S23), RSL1D1 (ribosomal L1 domain containing 1), NAT10, NOP14, GNL2, MRPS12, NOL6 (nucleolar protein 6), IMP4, and RRP12 (ribosomal RNA processing 12 homolog) for the pink module. The expression levels of the top DEmRNA and module hub genes in CRC were validated using the Gene Expression Profiling Interactive Analysis (GEPIA) database. Generally, our findings offer crucial insight into the hub genes and novel lncRNAs in the development of CRC by bioinformatics analysis, information that may prove useful in the identification of new biomarkers and treatment targets in CRC; however, more experimental investigation is required to validate the findings of the present study.

COL8A1 is a potential prognostic biomarker associated with migration, proliferation, and tumor microenvironment in glioma

Glioblastoma (GBM) is a common primary central nervous system tumor. The molecular mechanisms of glioma are unknown, and the prognosis is poor. Therefore, exploring the underlying mechanisms and screening for new prognostic markers and therapeutic targets is crucial. We utilized the weighted gene co-expression network analysis (WGCNA), Differentially Expressed Genes (DEGs), and LASSO-COX analysis to identify three target genes. Next, we constructed and evaluated a prognostic model, screening out COL8A1 as a risk gene. Through a sequence of cellular functional experiments, in vivo studies, and RNA sequencing, we delved into exploring the functional effects and molecular mechanisms of COL8A1 on GBM cells. Finally, the correlation between COL8A1 and tumor immune cells and different inflammatory responses was analyzed. Immunohistochemistry experiments revealed the influence of COL8A1 on macrophage polarization. The COL8A1 expression level was associated with the grade, prognosis, and tumor microenvironment (TME) of glioma. Functional experiments showed that COL8A1 inhibited GBM cell apoptosis and promoted migration, invasion, and proliferation in vitro and in vivo. We also found that COL8A1 promotes the epithelial-mesenchymal transition process and may mediate the activation of the ERK pathway through SHC1. In addition, immune infiltration analysis showed that COL8A1 was closely associated with macrophages in glioma tissues, significantly suppressing the signaling of M1-like -type macrophages and enhancing the signaling of M2-like -type macrophages. COL8A1 was first found to be associated with prognosis, progression, and immune microenvironment of glioma and may serve as a new marker of prognosis and a therapeutic target.

COL8A1 Regulates Esophageal Squamous Carcinoma Proliferation and Invasion Through PI3K/AKT Pathway

PURPOSE

Esophageal squamous carcinoma (ESCC) is a gastrointestinal malignancy with a high mortality, but the tumorigenesis is still unclear, restricting the target therapy development of ESCC. We explored the role of COL8A1 in ESCC development.

METHODS

Tissue microarrays were used to investigate the expression level of COL8A1 in ESCC tissues. The association between COL8A1 and the overall survival of ESCC patients was assessed. The effect of differential COL8A1 expression on tumor growth was investigated by the xenograft model. The regulation of COL8A1 on tumor growth, migration, and invasion was studied by using ESCC cell lines. The signal transduction pathways involved in COL8A1 were bioinformatically profiled and validated.

RESULTS

The COL8A1 was significantly expressed in cancerous tissues and was associated with poor prognosis in patients with ESCC. In vivo, the tumor growth obviously declined after inhibition of the COL8A1 expression. The abilities of cell proliferation and invasion were both decreased when the expression of COL8A1 was knockdown in ESCC cell line. Furthermore, we found the inactivation of the PI3K/AKT pathway that was mediated by knockdown of COL8A1 in ESCC cells, which was reversed with COL8A1 overexpression, whereas the cell proliferation and invasion ability were restored.

CONCLUSIONS

This is the first report that COL8A1 promote ESCC progression, which hopefully will provide a theoretical basis for clinical targeting of ESCC.

The collagen landscape in cancer: profiling collagens in tumors and in circulation reveals novel markers of cancer-associated fibroblast subtypes

Cancer-associated fibroblasts (CAFs) deposit and remodel collagens in the tumor stroma, impacting cancer progression and efficacy of interventions. CAFs are the focus of new therapeutics with the aim of normalizing the tumor microenvironment. To do this, a better understanding of CAF heterogeneity and collagen composition in cancer is needed. In this study, we sought to profile the expression of collagens at multiple levels with the goal of identifying cancer biomarkers. We investigated the collagen expression pattern in various cell types and CAF subtypes in a publicly available single-cell RNA sequencing (RNA-seq) dataset of pancreatic ductal adenocarcinoma. Next, we investigated the collagen expression profile in tumor samples across cancer types from The Cancer Genome Atlas (TCGA) database and evaluated if specific patterns of collagen expression were associated with prognosis. Finally, we profiled circulating collagen peptides using a panel of immunoassays to measure collagen fragments in the serum of cancer patients. We found that pancreatic stellate cells and fibroblasts were the primary producers of collagens in the pancreas. COL1A1, COL3A1, COL5A1, COL6A1 were expressed in all CAF subtypes, whereas COL8A1, COL10A1, COL11A1, COL12A1 were specific to myofibroblast CAFs (myCAF) and COL14A1 specific to inflammatory CAFs (iCAF). In TCGA database, myCAF collagens COL10A1 and COL11A1 were elevated across solid tumor types, and multiple associations between high expression and worse survival were found. Finally, circulating collagen biomarkers were elevated in the serum of patients with cancer relative to healthy controls with COL11A1 (myCAF) having the best diagnostic accuracy of the markers measured. In conclusion, CAFs express a noncanonical collagen profile with specific collagen subtypes associated with iCAFs and myCAFs in PDAC. These collagens are deregulated at the cellular, tumor, and systemic levels across different solid tumors and associate with survival. These findings could lead to new discoveries such as novel biomarkers and therapeutic targets. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

LINC02253 promote the malignant phenotype of Colon adenocarcinoma cells by up-regulating WWP1-mediated SMAD3 ubiquitination

OBJECTIVES

Colon adenocarcinoma (COAD) represents a type of common malignant tumor originating in the digestive tract. Long non-coding RNAs (lncRNAs) have been identified to engage in regulating the initiation and development of COAD. LncRNA LINC02253 has been reported abnormal expressed in COAD, but the underlying mechanism has not been discussed so far. This study aimed to determine the role and the molecular biology mechanism of LINC02253 in COAD progression and unearthed its specific molecular mechanism.

MATERIALS AND RESULTS

RT-qPCR and Western blot assays were conducted to detect gene expression. Function assays were performed to evaluate the effect of gene expression on COAD cell phenotype. Mechanism analyses were done to verify the association among genes after bioinformatics analysis. The obtained data revealed that LINC02253 demonstrated a high expression in COAD tissues and cells. This gene served as an oncogene, permitting to stimulate proliferation and suppress apoptosis of COAD cells. Mechanically, it was found that LINC02253 recruited FUS to stabilize WWP1 mRNA and WWP1 could mediate SMAD3 ubiquitination, thereby promoting the malignant phenotype formation of COAD cells.

CONCLUSIONS

LINC02253 was uncovered to exert an oncogenic role, enhancing the proliferation of COAD cells and repressing the cell apoptosis by recruiting FUS and encouraging WWP1-mediated SMAD3 ubiquitination.

MicroRNA-210-3p Regulates Endometriotic Lesion Development by Targeting IGFBP3 in Baboons and Women with Endometriosis

MicroRNAs (miRs) play an important role in the pathophysiology of endometriosis; however, the role of miR-210 in endometriosis remains unclear. This study explores the role of miR-210 and its targets, IGFBP3 and COL8A1, in ectopic lesion growth and development. Matched eutopic (EuE) and ectopic (EcE) endometrial samples were obtained for analysis from baboons and women with endometriosis. Immortalized human ectopic endometriotic epithelial cells (12Z cells) were utilized for functional assays. Endometriosis was experimentally induced in female baboons (n = 5). Human matched endometrial and endometriotic tissues were obtained from women (n = 9, 18-45 years old) with regular menstrual cycles. Quantitative reverse transcript polymerase chain reaction (RT-qPCR) analysis was performed for in vivo characterization of miR-210, IGFBP3, and COL8A1. In situ hybridization and immunohistochemical analysis were performed for cell-specific localization. Immortalized endometriotic epithelial cell lines (12Z) were utilized for in vitro functional assays. MiR-210 expression was decreased in EcE, while IGFBP3 and COL8A1 expression was increased in EcE. MiR-210 was expressed in the glandular epithelium of EuE but attenuated in those of EcE. IGFBP3 and COL8A1 were expressed in the glandular epithelium of EuE and were increased compared to EcE. MiR-210 overexpression in 12Z cells suppressed IGFBP3 expression and attenuated cell proliferation and migration. MiR-210 repression and subsequent unopposed IGFBP3 expression may contribute to endometriotic lesion development by increasing cell proliferation and migration.

Digital image analysis workflows for evaluation of cell behavior and tumor microenvironment to aid therapeutic assessment in high-risk neuroblastoma

Digital pathology and artificial intelligence are promising emerging tools in precision oncology as they provide more robust and reproducible analysis of histologic, morphologic and topologic characteristics of tumor cells and the surrounding microenvironment. This study aims to develop digital image analysis workflows for therapeutic assessment in preclinical in vivo models. For this purpose, we generated pipelines that enable automatic detection and quantification of vitronectin and αvβ3 in heterotopic high-risk neuroblastoma xenografts, demonstrating that digital analysis workflows can be used to provide robust detection of vitronectin secretion and αvβ3 expression by malignant neuroblasts and to evaluate the possibility of combining traditional chemotherapy (etoposide) with extracellular matrix-targeted therapies (cilengitide). Digital image analysis added evidence for the relevance of territorial vitronectin as a therapeutic target in neuroblastoma, since its expression is modified after treatment, with a mean percentage of 60.44% in combined therapy tumors vs 45.08% in control ones. In addition, the present study revealed the efficacy of cilengitide for reducing αvβ3 expression, with a mean αvβ3 positivity of 34.17% in cilengitide treated material vs 66.14% in control and with less tumor growth when combined with etoposide, with a final mean volume of 0.04 cm3 in combined therapy vs 1.45 cm3 in control. The results of this work highlight the importance of extracellular matrix-focused therapies in preclinical studies to improve therapeutic assessment for high-risk neuroblastoma patients.

COL8A1 enhances the invasion/metastasis in MDA-MB-231 cells via the induction of IL1B and MMP1 expression

BACKGROUND

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer with a high probability of metastasis and a lack of specific targets and targeted therapeutics. Previously, we have reported that COL8A1, which is highly expressed in the mesenchymal stem-like (MSL) subtype of TNBC, facilitates TNBC growth via FAK/Src activation. Furthermore, we have found that COL8A1 enhances the invasion and metastasis of MDA-MB-231 cells, classified into MSL. However, the mechanism of invasion and metastasis by COL8A1 remains unclear. Here, we investigated the biological function of COL8A1 on the invasion and metastasis of MDA-MB-231 cells.

METHODS

The invasion and metastasis of MDA-MB-231 cells were evaluated using three-dimensional (3D) culture methods and xenograft mouse models. DNA microarray analysis examined the gene expression in COL8A1-overexpressing MDA-MB-231 cells and control cells. Gene expression was verified using RT-qPCR.

RESULTS

COL8A1-deficient cells showed little or no metastasis, whereas forced expression of COL8A1 in MDA-MB-231 cells, the MSL subtype of TNBC cell lines, significantly promoted distant metastasis after tumor resection. As with in vivo, 3D invasion assay revealed that COL8A1 increased the invasion capacity of MDA-MB-231 and Hs578T cells, classified into the MSL subtype of TNBC. DNA microarray analysis for COL8A1-overexpressing cells indicated that COL8A1 induces interleukin 1B (IL1B) and matrix metalloproteinase-1 (MMP1) expression, both of which are correlated with COL8A1 expression in the mesenchymal subtypes of TNBC, and the Kaplan-Meier plotter provided evidence that the prognosis in the MSL subtype was strongly associated with both gene expressions and COL8A1 expression. Pharmacological inhibitor treatment showed that COL8A1 regulated IL1B and MMP1 expression through a different pathway. Moreover, the knockdown of each gene expression reduced the invasion capacity of COL8A1-overexpressing MDA-MB-231 and Hs578T cells.

CONCLUSION

Our findings indicate that COL8A1-induced IL1B and MMP1 enhanced the invasion and metastasis of the MSL subtype of TNBC. Considering our previous findings that COL8A1 promotes tumor growth, COL8A1 may be a prognostic and practical therapeutic target in TNBC.

Tumor and stroma COL8A1 secretion induces autocrine and paracrine progression signaling in pancreatic ductal adenocarcinoma

Several collagen subtypes are involved in pancreatic ductal adenocarcinoma (PDAC) desmoplasia, which constrains therapeutic efficacy. We evaluated collagen type VIII alpha 1 chain (COL8A1), whose function in PDAC is currently unknown. We identified COL8A1 expression in 7 examined PDAC cell lines by microarray analysis, western blotting, and RT‒qPCR. Higher COL8A1 expression occurred in 2 gemcitabine-resistant PDAC cell lines; pancreas tissue (n=15) from LSL-Kras^G12D/+; p48-Cre mice with advanced PDAC predisposition; and PDAC parenchyma and stroma of a patient tissue microarray (n=82). Bioinformatic analysis confirmed higher COL8A1 expression in PDAC patient tissue available from TCGA (n=183), GTEx (n=167), and GEO (n=261) databases. siRNA or lentiviral sh-mediated COL8A1 inhibition in PDAC cells reduced migration, invasion and gemcitabine resistance and resulted in lower cytidine deaminase and thymidine kinase 2 expression and was rescued by COL8A1-secreting cancer-associated fibroblasts (CAFs). The activation of COL8A1 expression involved cJun/AP-1, as demonstrated by CHIP assay and siRNA inhibition. Downstream of COL8A1, activation of ITGB1 and DDR1 receptors and PI3K/AKT and NF-κB signaling occurred, as detected by expression, adhesion and EMSA binding studies. Orthotopic transplantation of PDAC cells with downregulated COL8A1 expression resulted in reduced tumor xenograft growth and lower gemcitabine resistance but was prevented by cotransplantation of COL8A1-secreting CAFs. Most importantly, COL8A1 expression in PDAC patient tissues from our clinic (n=84) correlated with clinicopathological data, and we confirmed these findings by the use of patient data (n=177) from the TCGA database. These findings highlight COL8A1 expression in tumor and stromal cells as a new biomarker for PDAC progression.

Role of gasdermin family proteins in the occurrence and progression of hepatocellular carcinoma

Primary liver cancer is the sixth most common cancer and the third leading cause of cancer mortality worldwide, hepatocellular carcinoma (HCC) is the most common type of liver cancer, accounting for 75%-85% of cases. The occurrence and progression of HCC involve multiple events. Pyroptosis is a gasdermins mediated programmed cell death and is intricately associated with cancerogenesis, including HCC. This review mainly concerns the recent research advances of the gasdermin family members in HCC. The biological roles and specific expression patterns of the family members are discussed, especially those that are involved in the regulatory pathways in the occurrence and progression of HCC. We provide the latest progress into the distinct molecular mechanisms of gasdermin family members involved in the occurrence and development of HCC.

Modulation of the extracellular matrix by Streptococcus gallolyticus subsp. gallolyticus and importance in cell proliferation

Streptococcus gallolyticus subspecies gallolyticus (Sgg) has a strong clinical association with colorectal cancer (CRC) and actively promotes the development of colon tumors. Previous work showed that this organism stimulates CRC cells proliferation and tumor growth. However, the molecular mechanisms underlying these activities are not well understood. Here, we found that Sgg upregulates the expression of several type of collagens in HT29 and HCT116 cells, with type VI collagen (ColVI) being the highest upregulated type. Knockdown of ColVI abolished the ability of Sgg to induce cell proliferation and reduced the adherence of Sgg to CRC cells. The extracellular matrix (ECM) is an important regulator of cell proliferation. Therefore, we further examined the role of decellularized matrix (dc-matrix), which is free of live bacteria or cells, in Sgg-induced cell proliferation. Dc-matrix prepared from Sgg-treated cells showed a significantly higher pro-proliferative activity than that from untreated cells or cells treated with control bacteria. On the other hand, dc-matrix from Sgg-treated ColVI knockdown cells showed no difference in the capacity to support cell proliferation compared to that from untreated ColVI knockdown cells, suggesting that the ECM by itself is a mediator of Sgg-induced cell proliferation. Furthermore, Sgg treatment of CRC cells but not ColVI knockdown CRC cells resulted in significantly larger tumors in vivo, suggesting that ColVI is important for Sgg to promote tumor growth in vivo. These results highlight a dynamic bidirectional interplay between Sgg and the ECM, where Sgg upregulates collagen expression. The Sgg-modified ECM in turn affects the ability of Sgg to adhere to host cells and more importantly, acts as a mediator for Sgg-induced CRC cell proliferation. Taken together, our results reveal a novel mechanism in which Sgg stimulates CRC proliferation through modulation of the ECM.

Collagen Remodeling along Cancer Progression Providing a Novel Opportunity for Cancer Diagnosis and Treatment

The extracellular matrix (ECM) is a significant factor in cancer progression. Collagens, as the main component of the ECM, are greatly remodeled alongside cancer development. More and more studies have confirmed that collagens changed from a barrier to providing assistance in cancer development. In this course, collagens cause remodeling alongside cancer progression, which in turn, promotes cancer development. The interaction between collagens and tumor cells is complex with biochemical and mechanical signals intervention through activating diverse signal pathways. As the mechanism gradually clears, it becomes a new target to find opportunities to diagnose and treat cancer. In this review, we investigated the process of collagen remodeling in cancer progression and discussed the interaction between collagens and cancer cells. Several typical effects associated with collagens were highlighted in the review, such as fibrillation in precancerous lesions, enhancing ECM stiffness, promoting angiogenesis, and guiding invasion. Then, the values of cancer diagnosis and prognosis were focused on. It is worth noting that several generated fragments in serum were reported to be able to be biomarkers for cancer diagnosis and prognosis, which is beneficial for clinic detection. At a glance, a variety of reported biomarkers were summarized. Many collagen-associated targets and drugs have been reported for cancer treatment in recent years. The new targets and related drugs were discussed in the review. The mass data were collected and classified by mechanism. Overall, the interaction of collagens and tumor cells is complicated, in which the mechanisms are not completely clear. A lot of collagen-associated biomarkers are excavated for cancer diagnosis. However, new therapeutic targets and related drugs are almost in clinical trials, with merely a few in clinical applications. So, more efforts are needed in collagens-associated studies and drug development for cancer research and treatment.

COL8A1 Predicts the Clinical Prognosis of Gastric Cancer and Is Related to Epithelial-Mesenchymal Transition

Background

Gastric cancer (GC) is the fifth most common malignant tumor and the third leading cause of cancer-related deaths. Because GC has the characteristics of high heterogeneity, unclear mechanism, limited treatment methods, and low five-year survival rate, it is necessary to find the prognostic biomarkers of GC and explore the mechanism of GC.

Methods

We first identified differentially expressed genes (DEGs) between gastric cancer and normal gastric cells through expression analysis. A protein-protein interaction (PPI) network was constructed to find tightly connected modules. We performed survival analysis on the DEGs in the modules to identify genes with prognostic significance. Gene set enrichment analysis (GSEA) was used to identify gene enrichment pathways. Finally, we used our own collected clinical samples of 119 gastric adenocarcinoma (STAD) tissues and 40 normal gastric tissues to perform immunohistochemical (IHC) staining to verify the differential expression of COL8A1 in STAD tissues and normal gastric tissues and its correlation with epithelial-mesenchymal transition- (EMT-) related factors.

Results

We identified 356 DEGs through differential expression analysis. Through PPI analysis and survival analysis, we determined that the collagen type VII alpha-1 chain (COL8A1) gene has prognostic significance. GSEA analysis showed that COL8A1 was significantly enriched in the EMT. IHC results showed that COL8A1 was upregulated in STAD tissues and could be used as an independent prognostic factor and was related to EMT.

Conclusion

This study shows that COL8A1 is related to the prognosis of GC patients and might affect the progress of GC through the EMT pathway. Therefore, COL8A1 may be a biomarker for predicting the prognosis of GC.

COL8A1 facilitates the growth of triple-negative breast cancer via FAK/Src activation

PURPOSE

Triple-negative breast cancer (TNBC) is one of the most aggressive breast cancer subtypes, and treatment options are limited because of the lack of signature molecules and heterogeneous properties of cancer. COL8A1 expression is higher in breast cancer than in normal tissues and is strongly correlated with worse overall survival in patients with breast cancer. However, the biological function of COL8A1 on cancer progression is not fully understood. In this study, we investigated the biological function of COL8A1 on TNBC progression.

METHODS

COL8A1-deficient cells were generated using the CRISPR-Cas9 system. The tumor growth and metastasis of TNBC cells were evaluated using three-dimensional culture (3D) methods and xenograft mouse models. The activation of focal adhesion kinase (FAK)/Src by COL8A1 in TNBC cells was evaluated by immunoblotting.

RESULTS

COL8A1 expression was primarily distributed into TNBC cell lines. Further, relapse-free survival in TNBC patients with the MSL subtype was strongly associated with the COL8A1 expression. MDA-MB-231 and Hs578T cells, classified as the MSL subtype, strongly express COL8A1, and COL8A1 protein expression was induced by hypoxia in both cell lines. Loss of COL8A1 expression inhibited spheroid /tumor growth and metastasis in vitro and in vivo. Further, exogenous COL8A1 promoted TNBC growth via the FAK/Src activation. Finally, the spheroid growth of MDA-MB-231 and Hs578T cells was inhibited by defactinib, a FAK inhibitor, without cytotoxicity.

CONCLUSION

These results indicate that COL8A1-mediated FAK/Src activation produces a more aggressive phenotype in TNBC, and its target inhibition may be an efficacious treatment for TNBC.

The role of network-forming collagens in cancer progression

Collagens are the main components of extracellular matrix in the tumor microenvironment. Both fibrillar and nonfibrillar collagens are involved in tumor progression. The nonfibrillar network-forming collagens such as type IV and type VIII collagens are frequently overexpressed in various types of human cancers, which promotes tumor cell proliferation, adhesion, invasion, metastasis and angiogenesis. Studies on the roles of these collagens have shed light on the mechanisms underpinning the effects of this protein family. Future research has to explicit the role of network-forming collagens with respect to cancer progression and treatment. Herein, we review the regulation of network-forming collagens expression in cancer; the roles of network-forming collagens in tumor invasion, metastasis and angiogenesis; and the clinical significance of network-forming collagens expression in cancer patients. This article is protected by copyright. All rights reserved.

COL8A1 Promotes NSCLC Progression Through IFIT1/IFIT3-Mediated EGFR Activation

Activation of EGFR is a major risk factor for non-small cell lung cancer (NSCLC). Understanding the molecular events promoting EGFR activation can help us gain more insights into the progression of NSCLC. In this study, we demonstrate that collagen type VIII alpha 1 chain (COL8A1), an extracellular matrix component, was overexpressed in NSCLC. In NSCLC cells, knockdown of COL8A1 suppressed cell growth, cycle progression, and migration, and induced cell apoptosis. While COL8A1 overexpression promoted cell proliferation and inhibited cell apoptosis. In addition, we found that COL8A1 depletion reduced interferon response signaling and downregulated (IFIT1) and interferon-induced proteins with tetratricopeptide repeats 3 (IFIT3). Moreover, we indicated that COL8A1 could upregulate IFIT1 and IFIT3 mediated EGFR activation in vitro and in vivo. Lastly, there was a positive correlation among COL8A1, IFIT1, and IFIT3 expression, and EGFR activity in patients with NSCLC. Overall, our data demonstrate that COL8A1 contributes to NSCLC proliferation and invasion through EGFR activation, dependent on IFIT1 and IFIT3 expression.

Extracellular Matrix Biomarkers in Colorectal Cancer

The cellular microenvironment composition and changes therein play an extremely important role in cancer development. Changes in the extracellular matrix (ECM), which constitutes a majority of the tumor stroma, significantly contribute to the development of the tumor microenvironment. These alterations within the ECM and formation of the tumor microenvironment ultimately lead to tumor development, invasion, and metastasis. The ECM is composed of various molecules such as collagen, elastin, laminin, fibronectin, and the MMPs that cleave these protein fibers and play a central role in tissue remodeling. When healthy cells undergo an insult like DNA damage and become cancerous, if the ECM does not support these neoplastic cells, further development, invasion, and metastasis fail to occur. Therefore, ECM-related cancer research is indispensable, and ECM components can be useful biomarkers as well as therapeutic targets. Colorectal cancer specifically, is also affected by the ECM and many studies have been conducted to unravel the complex association between the two. Here we summarize the importance of several ECM components in colorectal cancer as well as their potential roles as biomarkers.

Collagen type VIII alpha 2 chain (COL8A2), an important component of the basement membrane of the corneal endothelium, facilitates the malignant development of glioblastoma cells via inducing EMT

Glioblastoma (GBM) is one of the most lethal tumor of all human cancers. Due to its poor response to chemotherapy and radiotherapy as well as its high rate of recurrence after treatment, the treatment is still undesired. The identification of potential related genes and bio-markers in the development of GBM could provide some new targets for the treatment of GBM. Our purpose in this study was to evaluate the mission of COL8A2 in GBM. Combined with TCGA, Oncomine databases, CGGA, GEPIA website and qRT-PCR analyses, we found that COL8A2 was up-regulated both in GBM tissues and cells compared to the controls. Moreover, the high COL8A2 expression was associated with the shorter overall survival of patients with GBM. The expression of COL8A2 was also positively correlated with metastasis-associated genes including vimentin, snail, slug, MMP2 and MMP7 according to GEPIA website. Knockdown of COL8A2 could suppress the cell proliferation, cell migration and invasion, whereas the overexpression of COL8A2 significantly expedited these processes. What's more, the outcome of western blot analysis manifested that COL8A2 could induced the expression of vimentin, snail, slug, MMP2 and MMP7. Taken together, COL8A2 activated cell proliferation, cell migration and invasion via raising the relative expression of EMT-related proteins in GBM. Therefore, our investigation suggests the oncogenic role of COL8A2 in GBM and provides a potential application of COL8A2 for GBM therapy.

Identifying MMP14 and COL12A1 as a potential combination of prognostic biomarkers in pancreatic ductal adenocarcinoma using integrated bioinformatics analysis

Background

Pancreatic ductal adenocarcinoma (PDAC) is a fatal malignant neoplasm. It is necessary to improve the understanding of the underlying molecular mechanisms and identify the key genes and signaling pathways involved in PDAC.

Methods

The microarray datasets GSE28735, GSE62165, and GSE91035 were downloaded from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified by integrated bioinformatics analysis, including protein-protein interaction (PPI) network, Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The PPI network was established using the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. GO functional annotation and KEGG pathway analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery. Hub genes were validated via the Gene Expression Profiling Interactive Analysis tool (GEPIA) and the Human Protein Atlas (HPA) website.

Results

A total of 263 DEGs (167 upregulated and 96 downregulated) were common to the three datasets. We used STRING and Cytoscape software to establish the PPI network and then identified key modules. From the PPI network, 225 nodes and 803 edges were selected. The most significant module, which comprised 11 DEGs, was identified using the Molecular Complex Detection plugin. The top 20 hub genes, which were filtered by the CytoHubba plugin, comprised FN1, COL1A1, COL3A1, BGN, POSTN, FBN1, COL5A2, COL12A1, THBS2, COL6A3, VCAN, CDH11, MMP14, LTBP1, IGFBP5, ALB, CXCL12, FAP, MATN3, and COL8A1. These genes were validated using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, and the encoded proteins were subsequently validated using the HPA website. The GO analysis results showed that the most significantly enriched biological process, cellular component, and molecular function terms among the 20 hub genes were cell adhesion, proteinaceous extracellular matrix, and calcium ion binding, respectively. The KEGG pathway analysis showed that the 20 hub genes were mainly enriched in ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and protein digestion and absorption. These findings indicated that FBN1 and COL8A1 appear to be involved in the progression of PDAC. Moreover, patient survival analysis performed via the GEPIA using TCGA and GTEx databases demonstrated that the expression levels of COL12A1 and MMP14 were correlated with a poor prognosis in PDAC patients (p < 0.05).

Conclusions

The results demonstrated that upregulation of MMP14 and COL12A1 is associated with poor overall survival, and these might be a combination of prognostic biomarkers in PDAC.

Construction of a Nomogram Based on a Hypoxia-Related lncRNA Signature to Improve the Prediction of Gastric Cancer Prognosis

Background

Gastric cancer is one of the most common malignant tumors and has a poor prognosis. Hypoxia is related to the poor prognosis of cancer patients. We searched for hypoxia-related long non-coding RNAs (lncRNAs) to predict both overall survival (OS) and disease-free survival (DFS) of gastric cancer patients.

Methods

We obtained hypoxia-related lncRNA expression profiles and clinical follow-up data of patients with gastric cancer from The Cancer Genome Atlas and the Molecular Signatures Database. The patients were randomly divided into a training group, test group and combined group. The hypoxia-related prognostic signature was constructed by Lasso regression and Cox regression models, the prognoses in different groups were compared by Kaplan-Meier (K-M) analysis, and the accuracy of the prognostic model was assessed by receiver operating characteristic (ROC) analysis.

Results

A hypoxia-related prognostic signature comprising 10 lncRNAs was constructed to predict both OS and DFS in gastric cancer. In the training, test and combined groups, patients were divided into high- and low-risk groups according to the formula. Kaplan-Meier analysis showed that patients in the high-risk group have poor prognoses, and the difference was significant in the subgroup analyses. Receiver operating characteristic analysis revealed that the predictive power of the model prediction is more accurate than that of standard benchmarks. The signature differed across Helicobacter pylori (Hp) status and T stages. Multivariate Cox analysis showed that the signature is an independent risk factor for both OS and DFS. A clinically predictive nomogram combining the lncRNA signature and clinical features was constructed; the nomogram accurately predicted both OS and DFS and had high clinical application value. Weighted correlation network analysis combined with enrichment analysis showed that the primary pathways were the PI3K-Akt, JAK-STAT, and IL-17 signaling pathways. The target genes NOX4, COL8A1, and CHST1 were associated with poor prognosis in the Gene Expression Profiling Interactive Analysis, Gene Expression Omnibus, and K-M Plotter databases.

Conclusions

Our 10-lncRNA prognostic signature and nomogram are accurate, reliable tools for predicting both OS and DFS in gastric cancer.

Mechanical Cues Affect Migration and Invasion of Cells From Three Different Directions

Cell migration and invasion is a key driving factor for providing essential cellular functions under physiological conditions or the malignant progression of tumors following downward the metastatic cascade. Although there has been plentiful of molecules identified to support the migration and invasion of cells, the mechanical aspects have not yet been explored in a combined and systematic manner. In addition, the cellular environment has been classically and frequently assumed to be homogeneous for reasons of simplicity. However, motility assays have led to various models for migration covering only some aspects and supporting factors that in some cases also include mechanical factors. Instead of specific models, in this review, a more or less holistic model for cell motility in 3D is envisioned covering all these different aspects with a special emphasis on the mechanical cues from a biophysical perspective. After introducing the mechanical aspects of cell migration and invasion and presenting the heterogeneity of extracellular matrices, the three distinct directions of cell motility focusing on the mechanical aspects are presented. These three different directions are as follows: firstly, the commonly used invasion tests using structural and structure-based mechanical environmental signals; secondly, the mechano-invasion assay, in which cells are studied by mechanical forces to migrate and invade; and thirdly, cell mechanics, including cytoskeletal and nuclear mechanics, to influence cell migration and invasion. Since the interaction between the cell and the microenvironment is bi-directional in these assays, these should be accounted in migration and invasion approaches focusing on the mechanical aspects. Beyond this, there is also the interaction between the cytoskeleton of the cell and its other compartments, such as the cell nucleus. In specific, a three-element approach is presented for addressing the effect of mechanics on cell migration and invasion by including the effect of the mechano-phenotype of the cytoskeleton, nucleus and the cell's microenvironment into the analysis. In precise terms, the combination of these three research approaches including experimental techniques seems to be promising for revealing bi-directional impacts of mechanical alterations of the cellular microenvironment on cells and internal mechanical fluctuations or changes of cells on the surroundings. Finally, different approaches are discussed and thereby a model for the broad impact of mechanics on cell migration and invasion is evolved.

Clinical Correlation of Wnt2 and COL8A1 With Colon Adenocarcinoma Prognosis

Wnt2 mRNA is widely expressed in various tumor tissues. Wnt2 overexpression promotes tumor growth, migration, invasion, and metastasis. However, its underlying molecular action mechanisms and clinical implications in colon adenocarcinoma (COAD) remain unclear. mRNA expression data, obtained from tissue samples, and pathophysiological data of 368 COAD patients were obtained from the Cancer Genome Atlas (TCGA) database. Further, Pearson's correlation analysis was performed to explore the correlation between the expression levels of Wnt2 and other genes in the human genome. Subsequently, a protein-protein interaction (PPI) network was constructed for hub gene identification. Overall survival and significance were determined by Kaplan-Meier analysis, and the log-rank test was used to further identify genes with prognostic significance in COAD from GEO datasets (GSE17538 and GSE39582). Subsequently, 158 tissue samples from Affiliated Hospital of Jiangnan University were used for expression verification. Gene set enrichment analysis (GSEA) was performed on high and low Wnt2 expression datasets to identify potential signaling pathways activated in COAD. In all, 10 hub genes associated with Wnt2 were screened by Pearson's correlation analysis and PPI network, with Wnt2 and COL8A1 having significantly poor prognosis by Kaplan-Meier analysis and log-rank test. Furthermore, high expressions of COL8A1 and Wnt2 were associated with poor survival both in TCGA and GEO cohorts. We further found a correlation between the expressions of Wnt2 and COL8A1 in COAD as per immunohistochemical analysis. To further elucidate the underlying molecular mechanisms of Wnt2 in COAD, we searched for pathways enriched in Wnt2 overexpressing datasets by GSEA. Our findings revealed that high Wnt2 levels were significantly associated with extracellular matrix receptor and focal adhesion pathways. Wnt2 expression correlated with COL8A1 expression in COAD; patients with high Wnt2 and COL8A1 expressions had worse survival outcomes. Pathways identified in this study prompt the molecular role of Wnt2 in COAD and provide directions to further elucidate the involved molecular mechanisms in COAD.

Clinical value and potential mechanisms of COL8A1 upregulation in breast cancer: a comprehensive analysis

Background

The situation faced by breast cancer patients, especially those with triple-negative breast cancer, is still grave. More effective therapeutic targets are needed to optimize the clinical management of breast cancer. Although collagen type VIII alpha 1 chain (COL8A1) has been shown to be downregulated in BRIP1-knockdown breast cancer cells, its clinical role in breast cancer remains unknown.

Methods

Gene microarrays and mRNA sequencing data were downloaded and integrated into larger matrices based on various platforms. Therefore, this is a multi-centered study, which contains 5048 breast cancer patients and 1161 controls. COL8A1 mRNA expression in breast cancer was compared between molecular subtypes. In-house immunohistochemistry staining was used to evaluate the protein expression of COL8A1 in breast cancer. A diagnostic test was performed to assess its clinical value. Furthermore, based on differentially expressed genes (DEGs) and co-expressed genes (CEGs) positively related to COL8A1, functional enrichment analyses were performed to explore the biological function and potential molecular mechanisms of COL8A1 underlying breast cancer.

Results

COL8A1 expression was higher in breast cancer patients than in control samples (standardized mean difference = 0.79; 95% confidence interval [CI] 0.55–1.03). Elevated expression was detected in various molecular subtypes of breast cancer. An area under a summary receiver operating characteristic curve of 0.80 (95% CI 0.76–0.83) with sensitivity of 0.77 (95% CI 0.69–0.83) and specificity of 0.70 (95% CI 0.61–0.78) showed moderate capacity of COL8A1 in distinguishing breast cancer patients from control samples. Worse overall survival was found in the higher than in the lower COL8A1 expression groups. Intersected DEGs and CEGs positively related to COL8A1 were significantly clustered in the proteoglycans in cancer and ECM-receptor interaction pathways.

Conclusions

Elevated COL8A1 may promote the migration of breast cancer by mediating the ECM-receptor interaction and synergistically interplaying with DEGs and its positively related CEGs independently of molecular subtypes. Several genes clustered in the proteoglycans in cancer pathway are potential targets for developing effective agents for triple-negative breast cancer.

Upregulation of COL8A1 indicates poor prognosis across human cancer types and promotes the proliferation of gastric cancer cells

Gastric cancer (GC) was one of the most common types of the digestive system. COL8A1 was reported to be associated with cancer progression. The present study showed COL8A1 was overexpressed and correlated to shorter overall survival (OS) time across human cancer types. Specially, our results showed COL8A1 was up-regulated in advanced stage GC compared to low stage GC samples. Higher expression of COL8A1 was significantly correlated to shorter OS time in patients with GC. Bioinformatics analysis revealed COL8A1 was involved in regulating cell proliferation and metastasis. Experimental validations of COL8A1 showed that silencing of COL8A1 could significantly suppressed cell proliferation, migration and invasion in GC. These results provided a potential target for the clinical prognosis and treatment of gastric cancer.

BICC1 as a novel prognostic biomarker in gastric cancer correlating with immune infiltrates

AIM

BicC family RNA-binding protein 1 (BICC1) codes an RNA-binding protein that regulates gene expression and modulates cell proliferation and apoptosis. We aim at investigating the role of BICC1 in gastric carcinogenesis.

METHODS

BICC1 mRNA expression in gastric cancer (GC) was examined using the Tumor Immune Estimation Resource (TIMER), The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Correlations between BICC1 expression and clinicopathological parameters were analyzed. The Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier plotter databases were used to examine the clinical prognostic significance of BICC1 in GC. Signaling pathways related to BICC1 expression were identified by gene set enrichment analysis (GSEA). TIMER and CIBERSORT were used to analyze the correlations among BICC1, BICC1-coexpressed genes and tumor-infiltrating immune cells.

RESULTS

BICC1 was highly expressed in GC and significantly correlated with grade (P = 0.002), TNM stage (P = 0.033), invasion depth (P = 0.001) and vital status (P = 0.009) of GC patients. High BICC1 expression correlated with poor overall survival. The GSEA results showed that cell adhesion-, tumor- and immune- related pathways were significantly enriched in samples with high BICC1 expression. BICC1 and its coexpressed genes were positively related to tumor-infiltrating immune cells and were strongly correlated with tumor-infiltrating macrophages (all r ≥ 0.582, P < 0.0001). The CIBERSORT database revealed that BICC1 correlated with M2 macrophages (P < 0.0001), regulatory T cells (P < 0.0001), resting mast cells (P < 0.0001), activated memory CD4+ T cells (P = 0.002), resting NK cells (P = 0.002), activated dendritic cells (P = 0.002), and follicular helper T cells (P = 0.016). The results from TIMER database confirmed that BICC1 is closely associated with the markers of M2 macrophages and tumor-associated macrophages (all r ≥ 0.5, P < 0.0001).

CONCLUSION

BICC1 may be a potential prognostic biomarker in GC and correlates with immune infiltrates.

WISP1 Predicts Clinical Prognosis and Is Associated With Tumor Purity, Immunocyte Infiltration, and Macrophage M2 Polarization in Pan-Cancer

Cancer is becoming the leading cause of death and a major public health problem. Although many advanced treatment strategies are currently in use, the general prognosis of cancer patients remains dismal due to the high frequency of recurrence, metastasis. The identification of effective biomarkers is important for predicting survival of cancer patients and improving treatment efficacy. In this study, we comprehensively analyzed WNT1-inducible-signaling pathway protein 1 (WISP1) expression and explored its correlation with prognosis in pan-cancer using tumor IMmune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis 2 (GEPIA2). We also examined correlations between WISP1 and immunocyte infiltration using TIMER. We identified genes co-expressed with WISP1 using the LinkedOmics database and analyzed associated gene ontology using Metascape. Finally, we constructed protein-protein interaction networks and examined correlations between genes co-expressed with WISP1 and immunocyte infiltration in pan-cancer. WISP1 level differed between human pan-cancer tissues and normal tissues, indicating its potential as a prognostic biomarker. WISP1 expression was correlated with tumor purity and immunocyte infiltration, especially monocyte-macrophage trafficking and M2 polarization. Genes co-expressed with WISP1 were mainly associated with extracellular matrix organization, with collagen members COL6A3, COL5A1, and COL8A1 being key genes correlated with macrophage infiltration and M2 polarization in pan-cancer. Conversely, in certain types of cancer with better prognoses, WISP1 was associated with low M2 macrophage infiltration. These results suggest that WISP1 affect clinical prognosis through associations with tumor purity, immune cell infiltration, and macrophage M2 polarization in pan-cancer, with collagen member proteins may serving as effector molecules of WISP1.

A novel prognostic model based on multi-omics features predicts the prognosis of colon cancer patients

Background

As a common malignant tumor in the colon, colon cancer (CC) has high incidence and recurrence rates. This study is designed to build a prognostic model for CC.

Methods

The gene expression dataset, microRNA‐seq dataset, copy number variation (CNV) dataset, DNA methylation dataset, and transcription factor (TF) dataset of CC were downloaded from UCSC Xena database. Using limma package, the differentially methylated genes (DMGs), and differentially expressed genes (DEGs) and miRNAs (DEMs) were identified. Based on random forest method, prognostic model for each omics dataset were constructed. After the omics features related to prognosis were selected using logrank test, the prognostic model based on multi‐omics features was built. Finally, the clinical phenotypes correlated with prognosis were screened using Kaplan–Meier survival analysis, and the nomogram model was established.

Results

There were 1625 DEGs, 268 DEMs, and 386 DMGs between the tumor and normal samples. A total of 105, 29, 159, five, and six genes/sites significantly correlated with prognosis were identified in the gene expression dataset (GABRD), miRNA‐seq dataset (miR‐1271), CNV dataset (RN7SKP247), DNA methylation dataset (cg09170112 methylation site [located in SFSWAP]), and TF dataset (SIX5), respectively. The prognostic model based on multi‐omics features was more effective than those based on single omics dataset. The number of lymph nodes, pathologic_M stage, and pathologic_T stage were the clinical phenotypes correlated with prognosis, based on which the nomogram model was constructed.

Conclusion

The prognostic model based on multi‐omics features and the nomogram model might be valuable for the prognostic prediction of CC.

Functional Interplay Between Collagen Network and Cell Behavior Within Tumor Microenvironment in Colorectal Cancer

Colorectal cancer is the second most common cancer diagnosed in men and the third most commonly occurring in women worldwide. Interactions between cells and the surrounding extracellular matrix (ECM) are involved in tumor development and progression of many types of cancer. The organization of the ECM molecules provides not only physical scaffoldings and dynamic network into which cells are embedded but also allows the control of many cellular behaviors including proliferation, migration, differentiation, and survival leading to homeostasis and morphogenesis regulation. Modifications of ECM composition and mechanical properties during carcinogenesis are critical for tumor initiation and progression. The core matrisome consists of five classes of macromolecules, which are collagens, laminins, fibronectin, proteoglycans, and hyaluronans. In most tissues, fibrillar collagen is the major component of ECM. Cells embedded into fibrillar collagen interact with it through their surface receptors, such as integrins and discoidin domain receptors (DDRs). On the one hand, cells incorporate signals from ECM that modify their functionalities and behaviors. On the other hand, all cells within tumor environment (cancer cells, cancer-associated fibroblasts, endothelial cells, and immune cells) synthesize and secrete matrix macromolecules under the control of multiple extracellular signals. This cell-ECM dialog participates in a dynamic way in ECM formation and its biophysical and biochemical properties. Here, we will review the functional interplay between cells and collagen network within the tumor microenvironment during colorectal cancer progression.

Weighted gene co-expression network analysis identified MYL9 and CNN1 are associated with recurrence in colorectal cancer

Colorectal cancer (CRC) is one of the most common carcinomas and the fourth leading cause of cancer-related death worldwide. One of the obstacles in the successful treatment of CRC is a high rate of recurrence. We aimed to construct weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes in association with recurrence in CRC patients. We firstly used the microarray data, GSE41258, to construct a co-expression network and identify gene modules. Furthermore, protein and protein interaction (PPI) network was also performed to screen hub genes. To validate the hub genes, an independent dataset GSE17536 was used for survival analyses. Additionally, another two databases were also performed to investigate the survival rates and expression levels of hub genes. Gene set enrichment analyses (GSEA) combined with gene ontology (GO) were performed to further explore function and mechanisms. In our study, the midnightblue module was identified to be significant, 15 hub genes were screened, four of which were identified as hub nodes in the PPI network. In the test dataset, we found higher expression of MYL9 and CNN1 were significantly associated with shorter survival time of CRC patients. GO analyses showed that MYL9 and CNN1 were enriched in “muscle system process” and “cytoskeletal protein binding”. GSEA found the two hub genes were enriched in “pathways in cancer” and “calcium signaling pathway”. In conclusion, our study demonstrated that MYL9 and CNN1 were hub genes associated with the recurrence of CRC, which may contribute to the improvement of recurrence-free survival time of CRC patients.

Collagen Induces a More Proliferative, Migratory and Chemoresistant Phenotype in Head and Neck Cancer via DDR1

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide and includes squamous cell carcinomas of the oropharynx and oral cavity. Patient prognosis has remained poor for decades and molecular targeted therapies are not in routine use. Here we showed that the overall expression of collagen subunit genes was higher in cancer-associated fibroblasts (CAFs) than normal fibroblasts. Focusing on collagen8A1 and collagen11A1, we showed that collagen is produced by both CAFs and tumour cells, indicating that HNSCCs are collagen-rich environments. We then focused on discoidin domain receptor 1 (DDR1), a collagen-activated receptor tyrosine kinase, and showed that it is over-expressed in HNSCC tissues. Further, we demonstrated that collagen promoted the proliferation and migration of HNSCC cells and attenuated the apoptotic response to cisplatin. Knockdown of DDR1 in HNSCC cells demonstrated that these tumour-promoting effects of collagen are mediated by DDR1. Our data suggest that specific inhibitors of DDR1 might provide novel therapeutic opportunities to treat HNSCC.

The relevance between the immune response-related gene module and clinical traits in head and neck squamous cell carcinoma

PURPOSE

Head and neck squamous cell carcinoma (HNSCC) is the sixth most prevalent cancer in the world, accounting for more than 90% of head and neck malignant tumors. However, its molecular mechanism is largely unknown. To help elucidate the potential mechanism of HNSCC tumorigenesis, we investigated the gene interaction patterns associated with tumorigenesis.

METHODS

Weighted gene co-expression network analysis (WGCNA) can help us to predict the intrinsic relationship or correlation between gene expression. Additionally, we further explored the combination of clinical information and module construction.

RESULTS

Sixteen modules were constructed, among which the key module most closely associated with clinical information was identified. By analyzing the genes in this module, we found that the latter may be related to the immune response, inflammatory response and formation of the tumor microenvironment. Sixteen hub genes were identified-ARHGAP9, SASH3, CORO1A, ITGAL, PPP1R16B, TBC1D10C, IL10RA, ITK, AKNA, PRKCB, TRAF3IP3, GIMAP4, CCR7, P2RY8, GIMAP7, and SP140. We further validated these genes at the transcriptional and translation levels.

CONCLUSION

The innovative use of a weighted network to analyze HNSCC samples provides new insights into the molecular mechanism and prognosis of HNSCC. Additionally, the hub genes we identified can be used as biomarkers and therapeutic targets of HNSCC, laying the foundation for the accurate diagnosis and treatment of HNSCC in clinical and research in the future.

Coexpression network analysis identified that plakophilin 1 is associated with the metastasis in human melanoma

BACKGROUND AND AIMS

Malignant melanoma is a fatal cancer with high metastatic characteristics. Approximately 80% of skin cancer deaths are caused by metastatic melanoma. It has been established that the metastatic ability of melanoma is regulated by an intricate gene interconnection network. Thus, the aim of this study was to identify and validate hub genes associated with metastatic melanoma and to further illustrate its potential mechanisms.

METHODS

The method of weighted gene coexpression network analysis (WGCNA) was applied to explore potential regulatory targets and investigate the relationship between the key module and hub genes associated with the metastasis ability of melanoma.

RESULTS

In the turquoise module, 26 hub genes were initially selected, and 6 of them were identified as "real" hub genes with high connectivity in the protein-protein interaction network. In terms of validation, PKP1 had the highest correlation with metastasis among all the "real" hub genes. Data obtained from the GEPIA database and the Gene Expression Omnibus database showed a lower expression of PKP1 in melanoma tissues compared to normal skin tissues. The results also showed that PKP1 was downregulated in metastatic melanomas (n = 367) compared with primary melanomas (n = 103) in The Cancer Genome Atlas (TCGA) database (n = 470). Furthermore, an ROC curve showed that PKP1 expression had good power in the diagnostics of both primary melanoma (p =  5.30e-06, AUC = 0.8) and metastatic melanoma (p =  1.13e-10, AUC = 0.925). We also found that PKP1 could distinguish low- and high-grade of metastatic melanomas and was associated with inflammatory melanoma. Moreover, in a tumor-bearing mouse model, melanoma tissues also showed lower mRNA expression of PKP1 than the adjacent normal skin. Finally, Gene Set Enrichment Analysis indicated that the calcium signaling was significantly enriched in metastatic melanoma with highly expressed PKP1.

CONCLUSIONS

PKP1 was identified as a new potential tumor suppressor in human melanoma, likely through regulating calcium signaling pathways.

Bladder cancer stage-associated hub genes revealed by WGCNA co-expression network analysis

Background

Bladder cancer was a malignant disease in patients, our research aimed at discovering the possible biomarkers for the diseases.

Results

The gene chip GSE31684, including 93samples, was downloaded from the GEO datasets and co-expression network was constructed by the data. Molecular complex detection(MCODE) was used to identify hub genes. The most significant cluster including 16 genes: CDH11, COL3A1, COL6A3, COL5A1, AEBP1, COL1A2, NTM, COL11A1, THBS2, COL8A1, COL1A1, BGN, MMP2, PXDN, THY1, and TGFB1I1 was identified. After annotated by BiNGO, they were suggested associated with collagen fibril organization and blood vessel development. In addition, the Kaplan Meier curves were obtained by UALCAN. The high expression of THY1, AEBP1, CDH11, COL1A1, COL1A2, COL11A1, MMP2, PXDN, BGN, COL5A1, COL8A1, and TGFB1I1 indicated poor prognosis of the patients(P < 0.05). Finally, we examined genes’ expression between low and high tumor stage by the Wilcoxon test(P < 0.05), TGFB1I1 was excluded.

Conclusion

THY1, AEBP1, CDH11, COL1A1, COL1A2, COL11A1, MMP2, PXDN, BGN, COL5A1, COL8A1 associated with the tumor stage as well as tumor patients’ prognosis. COL5A1, COL8A1(P < 0.01) may serve as therapeutic targets for the disease.

Vastatin (the NC1 domain of human type VIII collagen a1 chain) is linked to stromal reactivity and elevated in serum from patients with colorectal cancer

Vastatin, a fragment derived from type VIII collagen, is one of the least studied collagen-derived matrikines. Vastatin can be detected in serum but little is known regarding the relevance of serum vastatin in colorectal cancer (CRC). In this study, serum vastatin was measured (ELISA) in 67 healthy controls and 48 CRC patients prior to resection and compared to clinicopathological parameters and serum biomarkers of stromal reactivity (C3M, VICM). Impact of resection and chemotherapy were evaluated by comparing baseline values with a 3-month follow-up sample (n = 23). Serum vastatin was detectable in 114 of 115 subjects. At baseline vastatin was elevated in CRC compared to controls (P < 0.001) with a diagnostic accuracy (AUROC) of 0.865, p < 0.0001. Vastatin correlated with age in controls but not in patients with CRC; no association was seen with clinicopathological parameters. Vastatin was independently associated with C3M (stepwise linear regression coefficient 0.25, p = 0.046). Overall, no difference was seen in vastatin levels between baseline and follow-up. In conclusion, vastatin is elevated in serum from patients with CRC and correlate with interstitial matrix degradation (C3M). This indicates that vastatin is linked to stromal reactivity and suggests that vastatin has biomarker potential in CRC. The association with clinicopathological parameters and treatment effect needs further evaluation.

Expression and potential molecular mechanisms of miR‑204‑5p in breast cancer, based on bioinformatics and a meta‑analysis of 2,306 cases

Breast cancer (BC) is the most common cancer among women worldwide. However, there is insufficient research that focuses on the expression and molecular mechanisms of microRNA (miR)‑204‑5p in BC. In the current study, data were downloaded from the Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO) and the University of California Santa Cruz (UCSC) Xena databases. They were then used to undertake a meta‑analysis that leveraged the standard mean difference (SMD) and summarized receiver operating characteristic (sROC) to evaluate the expression of the precursor miR‑204 and mature miR‑204‑5p in BC. Additionally, an intersection of predicted genes, differentially expressed genes (DEGs) from the TCGA database and the GEO database were plotted to acquire desirable putative genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein‑protein interaction (PPI) network analyses were performed to assess the potential pathways and hub genes of miR‑204‑5p in BC. A decreased trend in precursor miR‑204 expression was detected in 1,077 BC tissue samples in comparison to 104 para‑carcinoma tissue samples in the TCGA database. Further, the expression of mature miR‑204‑5p was markedly downregulated in 756 BC tissue samples in comparison to 76 para‑carcinoma tissue samples in the UCSC Xena database. The outcome of the SMD from meta‑analysis also indicated that the expression of miR‑204‑5p was markedly reduced in 2,306 BC tissue samples in comparison to 367 para‑carcinoma tissue samples. Additionally, the ROC and sROC values indicated that miR‑204‑5p had a great discriminatory capacity for BC. In GO analysis, 'cell development', 'cell surface activity', and 'receptor agonist activity' were the most enriched terms; in KEGG analysis, 'endocytosis' was significantly enriched. Rac GTPase activating protein 1 (RACGAP1) was considered the hub gene in the PPI network. In conclusion, miR‑204‑5p may serve a suppressor role in the oncogenesis and advancement of BC, and miR‑204‑5p may have crucial functions in BC by targeting RACGAP1.

Identification of key lncRNAs in the carcinogenesis and progression of colon adenocarcinoma by co-expression network analysis

Colon adenocarcinoma (COAD) is one of the most common cancers, and its carcinogenesis and progression is influenced by multiple long non-coding RNAs (lncRNA), especially through the miRNA sponge effect. In this study, more than 4000 lncRNAs were re-annotated from the microarray datasets through probe sequence mapping to obtain reliable lncRNA expression profiles. As a systems biology method for describing the correlation patterns among genes across microarray samples, weighted gene co-expression network analysis was conducted to identify lncRNA modules associated with the five stepwise stages from normal colonic samples to COAD (n = 94). In the most relevant module (R²  = -0.78, P = 4E-20), four hub lncRNAs were identified (CTD-2396E7.11, PCGF5, RP11-33O4.1, and RP11-164P12.5). Then, these four hub lncRNAs were validated using two other independent datasets including GSE20916 (n = 145) and GSE39582 (n = 552). The results indicated that all hub lncRNAs were significantly negatively correlated with the three-stage colonic carcinogenesis, as well as TNM stages in COAD (one-way analysis of variance P < 0.05). Kaplan-Meier survival curve showed that patients with higher expression of each hub lncRNA had a significantly higher overall survival rate and lower relapse risk (log-rank P < 0.05). In conclusion, through co-expression analysis, we identified and validated four key lncRNAs in association with the carcinogenesis and progression of COAD, and these lncRNAs might have important clinical implications for improving the risk stratification, therapeutic decision and prognosis prediction in COAD patients.

Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis

Background and Objective: Despite striking advances in multimodality management, gastric cancer (GC) remains the third cause of cancer mortality globally and identifying novel diagnostic and prognostic biomarkers is urgently demanded. The study aimed to identify potential key genes associated with the pathogenesis and prognosis of GC.

Methods: Differentially expressed genes between GC and normal gastric tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Key genes related to the pathogenesis and prognosis of GC were identified by employing protein–protein interaction network and Cox proportional hazards model analyses.

Results: We identified nine hub genes (TOP2A, COL1A1, COL1A2, NDC80, COL3A1, CDKN3, CEP55, TPX2, and TIMP1) which might be tightly correlated with the pathogenesis of GC. A prognostic gene signature consisted of CST2, AADAC, SERPINE1, COL8A1, SMPD3, ASPN, ITGBL1, MAP7D2, and PLEKHS1 was constructed with a good performance in predicting overall survivals.

Conclusion: The findings of this study would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of GC.