Biglycan as a potential diagnostic and prognostic biomarker in multiple human cancers

Identification of potential shared gene signatures between gastric cancer and type 2 diabetes: a data-driven analysis

Background

Gastric cancer (GC) and type 2 diabetes (T2D) contribute to each other, but the interaction mechanisms remain undiscovered. The goal of this research was to explore shared genes as well as crosstalk mechanisms between GC and T2D.

Methods

The Gene Expression Omnibus (GEO) database served as the source of the GC and T2D datasets. The differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) were utilized to identify representative genes. In addition, overlapping genes between the representative genes of the two diseases were used for functional enrichment analysis and protein-protein interaction (PPI) network. Next, hub genes were filtered through two machine learning algorithms. Finally, external validation was undertaken with data from the Cancer Genome Atlas (TCGA) database.

Results

A total of 292 and 541 DEGs were obtained from the GC (GSE29272) and T2D (GSE164416) datasets, respectively. In addition, 2,704 and 336 module genes were identified in GC and T2D. Following their intersection, 104 crosstalk genes were identified. Enrichment analysis indicated that "ECM-receptor interaction," "AGE-RAGE signaling pathway in diabetic complications," "aging," and "cellular response to copper ion" were mutual pathways. Through the PPI network, 10 genes were identified as candidate hub genes. Machine learning further selected BGN, VCAN, FN1, FBLN1, COL4A5, COL1A1, and COL6A3 as hub genes.

Conclusion

"ECM-receptor interaction," "AGE-RAGE signaling pathway in diabetic complications," "aging," and "cellular response to copper ion" were revealed as possible crosstalk mechanisms. BGN, VCAN, FN1, FBLN1, COL4A5, COL1A1, and COL6A3 were identified as shared genes and potential therapeutic targets for people suffering from GC and T2D.

Global impact of proteoglycan science on human diseases

In this comprehensive review, we will dissect the impact of research on proteoglycans focusing on recent developments involved in their synthesis, degradation, and interactions, while critically assessing their usefulness in various biological processes. The emerging roles of proteoglycans in global infections, specifically the SARS-CoV-2 pandemic, and their rising functions in regenerative medicine and biomaterial science have significantly affected our current view of proteoglycans and related compounds. The roles of proteoglycans in cancer biology and their potential use as a next-generation protein-based adjuvant therapy to combat cancer is also emerging as a constructive and potentially beneficial therapeutic strategy. We will discuss the role of proteoglycans in selected and emerging areas of proteoglycan science, such as neurodegenerative diseases, autophagy, angiogenesis, cancer, infections and their impact on mammalian diseases.

Involvement of small leucine-rich proteoglycans and telocytes in thin and thick human endometrium: immunohistochemical and ultrastructural examination

Thin endometrium, defined as an endometrial thickness of less than 7 mm during the late follicular phase, is a common cause of frequent cancelation of embryo transfers or recurrent implantation failure during assisted reproductive treatment. Small proteoglycans regulate intracellular signaling cascades by bridging other matrix molecules and tissue elements, affecting cell proliferation, adhesion, migration, and cytokine concentration. The aim of the study is to investigate the role of small leucine-rich proteoglycans in the pathogenesis of thin and thick human endometrium and their differences from normal endometrium in terms of fine structure properties. Normal, thin, and thick endometrial samples were collected, and small leucine-rich proteoglycans (SLRPs), decorin, lumican, biglycan, and fibromodulin immunoreactivities were comparatively analyzed immunohistochemically. The data were compared statistically. Moreover, ultrastructural differences among the groups were evaluated by transmission electron microscopy. The immunoreactivities of decorin, lumican, and biglycan were higher in the thin endometrial glandular epithelium and stroma compared to the normal and thick endometrium (p < .001). Fibromodulin immunoreactivity was also higher in the thin endometrial glandular epithelium than in the normal and thick endometrium (p < .001). However, there was no statistical difference in the stroma among the groups. Ultrastructural features were not profoundly different among cases. Telocytes, however, were not seen in the thin endometrium in contrast to normal and thin endometrial tissues. These findings suggest a possible role of changes in proteoglycan levels in the pathogenesis of thin endometrium.

The entanglement of extracellular matrix molecules and immune checkpoint inhibitors in cancer: a systematic review of the literature

Introduction

Immune-checkpoint inhibitors (ICIs) have emerged as a core pillar of cancer therapy as single agents or in combination regimens both in adults and children. Unfortunately, ICIs provide a long-lasting therapeutic effect in only one third of the patients. Thus, the search for predictive biomarkers of responsiveness to ICIs remains an urgent clinical need. The efficacy of ICIs treatments is strongly affected not only by the specific characteristics of cancer cells and the levels of immune checkpoint ligands, but also by other components of the tumor microenvironment, among which the extracellular matrix (ECM) is emerging as key player. With the aim to comprehensively describe the relation between ECM and ICIs' efficacy in cancer patients, the present review systematically evaluated the current literature regarding ECM remodeling in association with immunotherapeutic approaches.

Methods

This review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines and was registered at the International Prospective Register of Systematic Reviews (PROSPERO, CRD42022351180). PubMed, Web of Science, and Scopus databases were comprehensively searched from inception to January 2023. Titles, abstracts and full text screening was performed to exclude non eligible articles. The risk of bias was assessed using the QUADAS-2 tool.

Results

After employing relevant MeSH and key terms, we identified a total of 5070 studies. Among them, 2540 duplicates, 1521 reviews or commentaries were found and excluded. Following title and abstract screening, the full text was analyzed, and 47 studies meeting the eligibility criteria were retained. The studies included in this systematic review comprehensively recapitulate the latest observations associating changes of the ECM composition following remodeling with the traits of the tumor immune cell infiltration. The present study provides for the first time a broad view of the tight association between ECM molecules and ICIs efficacy in different tumor types, highlighting the importance of ECM-derived proteolytic products as promising liquid biopsy-based biomarkers to predict the efficacy of ICIs.

Conclusion

ECM remodeling has an important impact on the immune traits of different tumor types. Increasing evidence pinpoint at ECM-derived molecules as putative biomarkers to identify the patients that would most likely benefit from ICIs treatments.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022351180, identifier CRD42022351180.

Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosis

Introduction

Gastric cancer is one of the most common cancers in the world. This study aimed to identify genes, biomarkers, and metabolic pathways affecting gastric cancer using bioinformatic analysis and meta-analysis.

Methods

Datasets containing gene expression profiles of tumor lesions and adjacent non-tumor mucosa samples were downloaded. Common differentially expressed genes between data sets were selected to identify hub genes and further analysis. Gene Expression Profiling and Interactive Analyses (GEPIA) and the Kaplan-Meier method were used to further validate the expression level of genes and plot the overall survivalcurve, respectively.

Results and disscussion

KEGG pathway analysis showed that the most important pathway was enriched in ECM-receptor interaction. Hub genes includingCOL1A2, FN1, BGN, THBS2, COL5A2, COL6A3, SPARC and COL12A1 wereidentified. The top interactive miRNAs including miR-29a-3p, miR-101-3p,miR-183-5p, and miR-15a-5p targeted the most hub genes. The survival chart showed an increase in mortality in patients with gastric cancer, which shows the importance of the role of these genes in the development of the disease and can be considered candidate genes in the prevention and early diagnosis of gastric cancer.

BGN/FAP/STAT3 positive feedback loop mediated mutual interaction between tumor cells and mesothelial cells contributes to peritoneal metastasis of gastric cancer

Peritoneal metastasis (PM) is most frequent in gastric cancer (GC) and cancer-associated fibroblasts (CAFs) play a critical role in this process. However, the concrete mechanism of crosstalk between CAFs and cancer cells in PM of GC remains unclear. Microarray sequencing of GC focus and PM lesions was performed, and biglycan (BGN) was screened for further study. Clinically, BGN expression was higher in GC tissues than adjacent normal tissues, and high expression correlated with poor prognosis. In vitro experiments demonstrated that BGN promoted tumor progression and the transformation of mesothelial cells (MCs) into cancer-associated fibroblasts like cells (CAFLCs). In turn, CAFLCs-derived fibroblast activation protein (FAP) facilitated the proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) of GC cells. GC-derived BGN combined with toll like receptor 2 (TLR2)/TLR4 on MCs to activate the NF-κB pathway and promote the transformation of MCs into CAFLCs by the recovery experiment, coimmunoprecipitation assay, nuclear and cytoplasmic protein extraction assay. CAFLCs-derived FAP could activate the JAK2/STAT3 signaling pathway in GC. Finally, activated STAT3 promoted BGN transcription in GC, resulting in a BGN/FAP-STAT3 positive feedback loop. Taken together, mutual interaction between tumor cells and activated MCs mediated by a BGN/FAP-STAT3 positive feedback loop facilitates PM of GC and provides a potential biomarker and therapeutic target for GC metastasis.

Biglycan as a mediator of proinflammatory response and target for MDS and sAML therapy

Myelodysplastic syndromes (MDS) and their progression to secondary acute myeloid leukemia (sAML) are associated with an altered protein expression including extracellular matrix (ECM) components thereby promoting an inflammatory environment. Since the role of the proteoglycan biglycan (BGN) as an inflammatory mediator has not yet been investigated in both diseases and might play a role in disease progression, its expression and/or function was determined in cell lines and bone marrow biopsies (BMBs) of MDS and sAML patients and subpopulations of MDS stem cells by Western blot and immunohistochemistry. The bone marrow (BM) microenvironment was analyzed by multispectral imaging, patients' survival by Cox regression. ROC curves were assessed for diagnostic value of BGN. All cell lines showed a strong BGN surface expression in contrast to only marginal expression levels in mononuclear cells and CD34⁺ cells from healthy donors. In the MDS-L cell line, CD34^-CD33⁺ and CD34⁺CD33⁺ blast subpopulations exhibited a differential BGN surface detection. Increased BGN mediated inflammasome activity of CD34^-CD33⁺TLR4⁺ cells was observed, which was inhibited by direct targeting of BGN or NLRP3. BGN was heterogeneously expressed in BMBs of MDS and sAML, but was not detected in control biopsies. BGN expression in BMBs positively correlated with MUM1⁺ and CD8⁺, but negatively with CD33⁺TLR4⁺ cell infiltration and was accompanied by a decreased progression-free survival of MDS patients. BGN-mediated inflammasome activation appears to be a crucial mechanism in MDS pathogenesis implicating its use as suitable biomarker and potential therapeutic target. Abbreviations: Ab, antibody; alloSCT, allogenic stem cell transplant; AML, acute myeloid leukemia; BGN, biglycan; BM, bone marrow; BMB, bone marrow biopsy; casp1, caspase 1; CTLA-4, cytotoxic T lymphocyte-associated protein 4; DAMP, danger-associated molecular pattern; ECM, extracellular matrix; FCS, fetal calf serum; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; HD, healthy donor; HSPC, hematopoietic stem and progenitor cell; HSC, hematopoietic stem cell; IFN, interferon; IHC, immunohistochemistry; IL, interleukin; MDS, myelodysplastic syndrome; MPN, myeloproliferative neoplasm; MSI, multispectral imaging; NGS, next-generation sequencing; NLRP3, NLR family pyrin domain containing 3; OS, overall survival; PBMC, peripheral blood mononuclear cell; PD-1, programmed cell death protein 1; PD-L1, programmed death-ligand 1, PFS, progression-free survival; PRR, pattern recognition receptor; SC, stem cell; SLRP, small leucine-rich proteoglycan; TGF, transforming growth factor; TIRAP, toll/interleukin 1 receptor domain-containing adapter protein; TLR, toll-like receptor; Treg, regulatory T cell.

Policosanol suppresses tumor progression in a gastric cancer xenograft model

Gastric cancer (GC) is the most common cancer worldwide and the third leading cause of cancer death, with the fifth highest incidence. The development of effective chemotherapeutic agents is needed to decrease GC mortality. Policosanol (PC) extracted from Cuban sugar cane wax is a healthy functional food ingredient that helps improve blood cholesterol levels and blood pressure. Its various physiological activities, such as antioxidant, anti-inflammatory, and anticancer activities, have been reported recently. Nevertheless, the therapeutic efficacy of PC in gastric xenograft models is unclear. We aimed to investigate the anticancer effect of PC on human GC SNU-16 cells and a xenograft mouse model. PC significantly inhibited GC cell viability and delayed tumor growth without toxicity in the SNU-16-derived xenograft model. Therefore, we investigated protein expression levels in tumor tissues; the expression levels of Ki-67, a proliferation marker, and cdc2 were decreased. In addition, we performed proteomic analysis and found thirteen differentially expressed proteins. Our results suggested that PC inhibited GC progression via cdc2 suppression and extracellular matrix protein regulation. Notably, our findings might contribute to the development of novel and effective therapeutic strategies for GC.

Integrated Bioinformatics Analysis for Identifying the Significant Genes as Poor Prognostic Markers in Gastric Adenocarcinoma

Gastric adenocarcinoma (GAC) is the most common histological type of gastric cancer and imposes a considerable health burden globally. The purpose of this study was to identify significant genes and key pathways participated in the initiation and progression of GAC. Four datasets (GSE13911, GSE19826, GSE54129, and GSE79973) including 171 GAC and 77 normal tissues from Gene Expression Omnibus (GEO) database were collected and analyzed. Through integrated bioinformatics analysis, we obtained 69 commonly differentially expressed genes (DEGs) among the four datasets, including 20 upregulated and 49 downregulated genes. The prime module in protein-protein interaction network of DEGs, including ADAMTS2, COL10A1, COL1A1, COL1A2, COL8A1, BGN, and SPP1, was enriched in protein digestion and absorption, ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and amoebiasis. Furthermore, expression and survival analysis found that all seven hub genes were highly expressed in GAC tissues and 6 of them (except for SPP1) were able to predict poor prognosis of GAC. Finally, we verified the 6 high-expressed hub genes in GAC tissues via immunohistochemistry, Western blot, and RNA quantification analysis. Altogether, we identified six significantly upregulated DEGs as poor prognostic markers in GAC based on integrated bioinformatical methods, which could be potential molecular markers and therapeutic targets for GAC patients.

The Analysis of Potential Diagnostic and Therapeutic Targets for the Occurrence and Development of Gastric Cancer Based on Bioinformatics

Objective

Gastric cancer is among the most common malignant tumors of the digestive system. This study explored the molecular mechanisms and potential therapeutic targets for gastric cancer occurrence and progression using bioinformatics.

Methods

The gastric cancer microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database. The R package was used for data mining and screening differentially expressed genes (DEGs). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Based on the protein-protein interaction (PPI) network analysis, core targets and core subsets were screened. Then, the relationship between the expression level of the core genes and the prognosis of gastric cancer patients was analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA) database.

Results

Using the GSE19826 and GSE54129 datasets, a total of 550 DEGs were identified, including 248 upregulated and 302 downregulated genes. GO and KEGG analyses showed that the upregulated DEGs were mainly enriched in the extracellular matrix (ECM) organization of the biological process (BP), the collagen-containing ECM of cellular component (CC), and the ECM structural constituent of molecular function (MF). DEGs were also enriched in human papillomavirus infections, the focal adhesion pathway, PI3K-Akt signaling pathway, and among others. The downregulated DEGs were mainly enriched in digestion, basal part of the cell, and aldo-keto reductase (NADP) activity. And the above pathways were enriched primarily in the metabolism of xenobiotics by cytochrome P450, drug metabolism-cytochrome P450, and retinol metabolism. Five core genes, including COL1A2, COL3A1, BGN, FN1, and VCAN, were significantly highly expressed in gastric cancer patients and were associated with poor prognosis.

Conclusion

This study identified new potential molecular targets closely related to gastric cancer occurrence and development via mining public data using bioinformatics analysis methods.

Collagen Family and Other Matrix Remodeling Proteins Identified by Bioinformatics Analysis as Hub Genes Involved in Gastric Cancer Progression and Prognosis

Gastric cancer has remained in the top five cancers for over ten years, both in terms of incidence and mortality due to the shortage of biomarkers for disease follow-up and effective therapies. Aiming to fill this gap, we performed a bioinformatics assessment on our data and two additional GEO microarray profiles, followed by a deep analysis of the 40 differentially expressed genes identified. PPI network analysis and MCODE plug-in pointed out nine upregulated hub genes coding for proteins from the collagen family (COL12A1, COL5A2, and COL10A1) or involved in the assembly (BGN) or degradation of collagens (CTHRC1), and also associated with cell adhesion (THBS2 and SPP1) and extracellular matrix degradation (FAP, SULF1). Those genes were highly upregulated at the mRNA and protein level, the increase being correlated with pathological T stages. The high expression of BGN (p = 8 × 10⁻¹²), THBS2 (p = 1.2 × 10⁻⁶), CTHRC1 (p = 1.1 × 10⁻⁴), SULF1 (p = 3.8 × 10⁻⁴), COL5A1 (p = 1.3 × 10⁻⁴), COL10A1 (p = 5.7 × 10⁻⁴), COL12A1 (p = 2 × 10⁻³) correlated with poor overall survival and an immune infiltrate based especially on immunosuppressive M2 macrophages (p-value range 4.82 × 10⁻⁷–1.63 × 10⁻¹³). Our results emphasize that these genes could be candidate biomarkers for GC progression and prognosis and new therapeutic targets.

Prognostic and Predictive Value of BGN in Colon Cancer Outcomes and Response to Immunotherapy

Background

Colon cancer is one of the most frequent malignancies and causes high mortality worldwide. Exploring the tumor-immune interactions in the tumor microenvironment and identifying new prognostic and therapeutic biomarkers will assist in decoding the novel mechanism of tumor immunotherapy. BGN is a typical extracellular matrix protein that was previously validated as a signaling molecule regulating multiple processes of tumorigenesis. However, its role in tumor immunity requires further investigation.

Methods

The differentially expressed genes in three GEO datasets were analyzed, and BGN was identified as the target gene by intersection analysis of PPIs. The relevance between clinical outcomes and BGN expression levels was evaluated using data from the GEO database, TCGA and tissue microarray of colon cancer samples. Univariable and multivariable Cox regression models were conducted for identifying the risk factors correlated with clinical prognosis of colon cancer patients. Next, the association between BGN expression levels and the infiltration of immune cells as well as the process of the immune response was analyzed. Finally, we predicted the immunotherapeutic response rates in the subgroups of low and high BGN expression by TIS score, ImmuCellAI and TIDE algorithms.

Results

BGN expression demonstrated a statistically significant upregulation in colon cancer tissues than in normal tissues. Elevated BGN was associated with shorter overall survival as well as unfavorable clinicopathological features, including tumor size, serosa invasion and length of hospitalization. Mechanistically, pathway enrichment and functional analysis demonstrated that BGN was positively correlated with immune and stromal scores in the TME and primarily involved in the regulation of immune response. Further investigation revealed that BGN was strongly expressed in the immunosuppressive phenotype and tightly associated with the infiltration of multiple immune cells in colon cancer, especially M2 macrophages and induced Tregs. Finally, we demonstrated that high BGN expression presented a better immunotherapeutic response in colon cancer patients.

Conclusion

BGN is an encouraging predictor of diagnosis, prognosis and immunotherapeutic response in patients with colon cancer. Assessment of BGN expression represents a novel approach with great promise for identifying patients who may potentially benefit from immunotherapy.

Biglycan Promotes Cancer Stem Cell Properties, NFκB Signaling and Metastatic Potential in Breast Cancer Cells

Simple Summary

Breast cancer stem cells (BCSCs) are a small sub-population of cells within tumors with high metastatic potential. We identified biglycan (BGN) as a prospective molecular target in BCSCs that regulates the aggressive phenotypes of these cells. These findings establish a foundation for the development of therapeutics against BGN to eliminate BCSCs and prevent metastatic breast cancer.

Abstract

It is a major challenge to treat metastasis due to the presence of heterogenous BCSCs. Therefore, it is important to identify new molecular targets and their underlying molecular mechanisms in various BCSCs to improve treatment of breast cancer metastasis. Here, we performed RNA sequencing on two distinct co-existing BCSC populations, ALDH⁺ and CD29^hi CD61⁺ from PyMT mammary tumor cells and detected upregulation of biglycan (BGN) in these BCSCs. Genetic depletion of BGN reduced BCSC proportions and tumorsphere formation. Furthermore, BCSC associated aggressive traits such as migration and invasion were significantly reduced by depletion of BGN. Glycolytic and mitochondrial metabolic assays also revealed that BCSCs exhibited decreased metabolism upon loss of BGN. BCSCs showed decreased activation of the NFκB transcription factor, p65, and phospho-IκB levels upon BGN ablation, indicating regulation of NFκB pathway by BGN. To further support our data, we also characterized CD24⁻/CD44⁺ BCSCs from human luminal MCF-7 breast cancer cells. These CD24⁻/CD44⁺ BCSCs similarly exhibited reduced tumorigenic phenotypes, metabolism and attenuation of NFκB pathway after knockdown of BGN. Finally, loss of BGN in ALDH⁺ and CD29^hi CD61⁺ BCSCs showed decreased metastatic potential, suggesting BGN serves as an important therapeutic target in BCSCs for treating metastasis of breast cancer.

A Necessary Role for Increased Biglycan Expression during L1-Mediated Colon Cancer Progression

Aberrant activation of Wnt/β-catenin signaling and downstream β-catenin-TCF target genes is a hallmark of colorectal cancer (CRC) development. We identified the immunoglobulin-like cell adhesion receptor L1CAM (L1) as a target of β-catenin-TCF transactivation in CRC cells. Overexpression of L1 in CRC cells confers enhanced proliferation, motility, tumorigenesis, and liver metastasis, and L1 is exclusively localized at invasive areas of human CRC tissue. Several genes are induced after L1 transfection into CRC cells by a mechanism involving the L1-ezrin-NF-κB pathway. We conducted a secretomic analysis of the proteins in the culture medium of L1-overexpressing CRC cells. We detected a highly increased level of biglycan, a small leucine-rich ECM component, and a signaling molecule. We found that induction of biglycan is required for the cellular processes conferred by L1, including enhanced proliferation, motility, tumorigenesis, and liver metastasis. The suppression of endogenous biglycan levels or a point mutation in the L1 ectodomain that regulates cell–cell adhesion mediated by L1 blocked the enhanced tumorigenic properties conferred by L1. The mechanism of biglycan induction by L1 involves the L1-NF-κB pathway. Blocking NF-κB signaling in L1 expressing cells suppressed the induction of biglycan and the tumorigenic properties conferred by L1. Biglycan expression was undetectable in the normal colonic mucosa, but expressed at highly increased levels in the tumor tissue, especially in the stroma. The therapeutic strategies to target biglycan expression might provide a useful approach for CRC treatment in L1-overexpressing tumors.

The Role of Decorin and Biglycan Signaling in Tumorigenesis

The complex and adaptive nature of malignant neoplasm constitute a major challenge for the development of effective anti-oncogenic therapies. Emerging evidence has uncovered the pivotal functions exerted by the small leucine-rich proteoglycans, decorin and biglycan, in affecting tumor growth and progression. In their soluble forms, decorin and biglycan act as powerful signaling molecules. By receptor-mediated signal transduction, both proteoglycans modulate key processes vital for tumor initiation and progression, such as autophagy, inflammation, cell-cycle, apoptosis, and angiogenesis. Despite of their structural homology, these two proteoglycans interact with distinct cell surface receptors and thus modulate distinct signaling pathways that ultimately affect cancer development. In this review, we summarize growing evidence for the complex roles of decorin and biglycan signaling in tumor biology and address potential novel therapeutic implications.

Mechanical Pressure Driving Proteoglycan Expression in Mammographic Density: a Self-perpetuating Cycle?

Regions of high mammographic density (MD) in the breast are characterised by a proteoglycan (PG)-rich fibrous stroma, where PGs mediate aligned collagen fibrils to control tissue stiffness and hence the response to mechanical forces. Literature is accumulating to support the notion that mechanical stiffness may drive PG synthesis in the breast contributing to MD. We review emerging patterns in MD and other biological settings, of a positive feedback cycle of force promoting PG synthesis, such as in articular cartilage, due to increased pressure on weight bearing joints. Furthermore, we present evidence to suggest a pro-tumorigenic effect of increased mechanical force on epithelial cells in contexts where PG-mediated, aligned collagen fibrous tissue abounds, with implications for breast cancer development attributable to high MD. Finally, we summarise means through which this positive feedback mechanism of PG synthesis may be intercepted to reduce mechanical force within tissues and thus reduce disease burden.

mRBioM: An Algorithm for the Identification of Potential mRNA Biomarkers From Complete Transcriptomic Profiles of Gastric Adenocarcinoma

Purpose

In this work, an algorithm named mRBioM was developed for the identification of potential mRNA biomarkers (PmBs) from complete transcriptomic RNA profiles of gastric adenocarcinoma (GA).

Methods

mRBioM initially extracts differentially expressed (DE) RNAs (mRNAs, miRNAs, and lncRNAs). Next, mRBioM calculates the total information amount of each DE mRNA based on the coexpression network, including three types of RNAs and the protein-protein interaction network encoded by DE mRNAs. Finally, PmBs were identified according to the variation trend of total information amount of all DE mRNAs. Four PmB-based classifiers without learning and with learning were designed to discriminate the sample types to confirm the reliability of PmBs identified by mRBioM. PmB-based survival analysis was performed. Finally, three other cancer datasets were used to confirm the generalization ability of mRBioM.

Results

mRBioM identified 55 PmBs (41 upregulated and 14 downregulated) related to GA. The list included thirteen PmBs that have been verified as biomarkers or potential therapeutic targets of gastric cancer, and some PmBs were newly identified. Most PmBs were primarily enriched in the pathways closely related to the occurrence and development of gastric cancer. Cancer-related factors without learning achieved sensitivity, specificity, and accuracy of 0.90, 1, and 0.90, respectively, in the classification of the GA and control samples. Average accuracy, sensitivity, and specificity of the three classifiers with machine learning ranged within 0.94–0.98, 0.94–0.97, and 0.97–1, respectively. The prognostic risk score model constructed by 4 PmBs was able to correctly and significantly (^∗∗∗p < 0.001) classify 269 GA patients into the high-risk (n = 134) and low-risk (n = 135) groups. GA equivalent classification performance was achieved using the complete transcriptomic RNA profiles of colon adenocarcinoma, lung adenocarcinoma, and hepatocellular carcinoma using PmBs identified by mRBioM.

Conclusions

GA-related PmBs have high specificity and sensitivity and strong prognostic risk prediction. MRBioM has also good generalization. These PmBs may have good application prospects for early diagnosis of GA and may help to elucidate the mechanism governing the occurrence and development of GA. Additionally, mRBioM is expected to be applied for the identification of other cancer-related biomarkers.

Proteoglycans and their functions in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a highly malignant disease that has a poor prognosis. Its high lethality is mainly due to the lack of symptoms at early stages, which culminates in diagnosis at a late stage when the tumor has already metastasized. Unfortunately, the common cancer biomarkers have low sensitivity and specificity in esophageal cancer. Therefore, a better understanding of the molecular mechanisms underlying ESCC progression is needed to identify novel diagnostic markers and therapeutic targets for intervention. The invasion of cancer cells into the surrounding tissue is a crucial step for metastasis. During metastasis, tumor cells can interact with extracellular components and secrete proteolytic enzymes to remodel the surrounding tumor microenvironment. Proteoglycans are one of the major components of extracellular matrix. They are involved in multiple processes of cancer cell invasion and metastasis by interacting with soluble bioactive molecules, surrounding matrix, cell surface receptors, and enzymes. Apart from having diverse functions in tumor cells and their surrounding microenvironment, proteoglycans also have diagnostic and prognostic significance in cancer patients. However, the functional significance and underlying mechanisms of proteoglycans in ESCC are not well understood. This review summarizes the proteoglycans that have been studied in ESCC in order to provide a comprehensive view of the role of proteoglycans in the progression of this cancer type. A long term goal would be to exploit these molecules to provide new strategies for therapeutic intervention.

Identification and Validation of Biglycan as Prognosis and Therapy Markers for Patients with Stomach Adenocarcinoma

Objective

Previous studies have confirmed the biglycan (BGN) as a core gene in stomach adenocarcinoma (STAD). Present study aimed at conducting further investigations to reveal the potential function of BGN in STAD.

Methods

The mRNA and protein expressions of BGN in STAD were firstly evaluated, followed by immune infiltration analyses. The influence of BGN expression on the overall survival of STAD patients was subsequently analyzed, and a restrict survival analysis was performed as well. The protein–protein interaction (PPI) network analysis on the co-expressed genes with BGN was finally adopted to obtain the most important module in the whole network, and significant Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway associated with hub genes within the main module was further predicted.

Results

(1) We verified the mRNA high expression of BGN in STAD (all P<0.05), and higher expression was observed in patients with stage 4 (P<0.001) and grade 3 (P<0.001). The BGN protein was mainly localized to the golgi apparatus, and protein expression displayed an individual difference. (2) Immune infiltration analysis showed the strongest correlation between BGN expression and abundance of natural killer cell (P<0.001), Transforming Growth Factor beta 1 (TGFB1) (P<0.001), TNF Receptor Superfamily Member 4 (TNFRSF4) (P<0.001) and C-X-C Motif Chemokine Ligand 12 (CXCL12) (P<0.001) in STAD. BGN expression was also correlated to immune subtypes (P=0.0347) and molecular subtypes (P=0.0263) in STAD. (3) High expression of BGN shortened the overall survival time of STAD patients (all P<0.01). The influence of BGN expression on the prognosis was statistically affected by several clinical phenotypes and cohorts of patients. Cox regression showed that BGN can be considered as a prognostic predictor of STAD (P<0.05). (4) Pathway analysis indicated that BGN possibly participated in ECM–receptor interaction, focal adhesion, human papillomavirus infection and PI3K-Akt signaling pathway (all P<0.001).

Conclusion

BGN was highly expressed in STAD, implying a poor prognosis of patients. Relevant signal pathways associated with BGN were distinguished as well. BGN could be used as a potential therapeutic biomarker for STAD.

Biglycan: an emerging small leucine-rich proteoglycan (SLRP) marker and its clinicopathological significance

Extracellular matrix (ECM) plays an important role in the structural organization of tissue and delivery of external cues to the cell. Biglycan, a class I small leucine-rich proteoglycans (SLRP), is a key component of the ECM that participates in scaffolding the collagen fibrils and mediates cell signaling. Dysregulation of biglycan expression can result in wide range of clinical conditions such as metabolic disorder, inflammatory disorder, musculoskeletal defects and malignancies. In this review, we aim to update our current understanding regarding the link between altered expression of biglycan and different clinicopathological states. Biglycan interacts with toll like receptors (TLR)-2 and TLR-4 on the immune cells which initiates inflammation and aggravates inflammatory disorders. ECM unbound soluble biglycan acts as a DAMP (danger associated molecular pattern) resulting in sterile inflammation. Dysregulation of biglycan expression is also observed in inflammatory metabolic conditions such as atherosclerosis and obesity. In cancer, high-biglycan expression facilitates tumor growth, invasion and metastasis which is associated with poor clinical outcome. As a pivotal structural component of the ECM, biglycan strengthens the musculoskeletal system and its absence is associated with musculoskeletal defects. Thus, SLRP biglycan is a potential marker which is significantly altered in different clinicopathological states.

Benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers: a case study of pancreatic cancer

Pancreatic cancer is a highly malignant tumor of the digestive tract that is difficult to diagnose and treat. It is more common in developed countries and has become one of the main causes of death in some countries and regions. Currently, pancreatic cancer generally has a poor prognosis, partly due to the lack of symptoms in the early stages of pancreatic cancer. Therefore, most cases are diagnosed at advanced stage. With the continuous in-depth research of glycoproteomics in precision medical diagnosis, there have been some reports on quantitative analysis of cancer-related cells, plasma or tissues to find specific biomarkers for targeted therapy. This research is based on the developed complete N-linked glycopeptide database search engine GPSeeker, combined with liquid-mass spectrometry and stable diethyl isotope labeling, providing a benchmark of site- and structure-specific quantitative tissue N-glycoproteomics for discovery of potential N-glycoprotein markers. With spectrum-level FDR ≤1%, 20,038 intact N-Glycopeptides corresponding to 4518 peptide backbones, 228 N-glycan monosaccharide compositions 1026 N-glycan putative structures, 4460 N-glycosites and 3437 intact N-glycoproteins were identified. With the criteria of ≥1.5-fold change and p value<0.05, 52 differentially expressed intact N-glycopeptides (DEGPs) were found in pancreatic cancer tussues relative to control, where 38 up-regulated and 14 down-regulated, respectively.

High expression of TREM2 promotes EMT via the PI3K/AKT pathway in gastric cancer: bioinformatics analysis and experimental verification

Background: To date, the pathogenesis of gastric cancer (GC) remains unclear. We combined public database resources and bioinformatics analysis methods, explored some novel genes and verified the experiments to further understand the pathogenesis of GC and to provide a promising target for anti-tumor therapy. Methods: We downloaded the chip data related to GC from the Gene Expression Omnibus (GEO) database, extracted differentially expressed genes (DEGs), and then determined the key genes in the development of GC via PPI networks and model analysis. Functional annotation via GO and KEGG enrichment of DEGs was used to understand the latent roles of DEGs. The expression of the triggering receptor expressed on myeloid cells 2 (TREM2) gene in GC cell lines was verified via RT-PCR and western blotting. Moreover, the CCK-8, wound healing assay, and transwell migration and invasion assays were used to understand the changes in the proliferation, migration, and invasion abilities of GC cells after silencing TREM2. Western blotting verified the interaction between TREM2 and PI3K predict of the string website, as well as the effect of TREM2 on EMT. Finally, a lung metastasis model was used to explore the relationship between TREM2 and metastasis. Results: Our study identified 16 key genes, namely BGN, COL1A1, COL4A1, COL5A2, NOX4, SPARC, HEYL, SPP1, TIMP1, CTHRC1, TREM2, SFRP4, FBXO32, GPX3, KIF4A, and MMP9 genes associated with GC. The EMT-related pathway was the most significantly altered pathway. TREM2 expression was higher in GC cell lines and was remarkably associated with tumor invasion depth, TNM stage, histological grade, histological type, anatomic subdivision, and Helicobacter pylori state. Knockdown of TREM2 expression inhibited the proliferation, migration, and invasion of GC cells as well as the progression of EMT by PI3K/AKT signaling in vitro. In addition, lung metastasis were decreased in vivo. Conclusions: We identified some important genes associated with the progression of GC via public database analysis, explored and verified the effects of proto-oncogene TREM2 on EMT via the PI3K/AKT pathway. TREM2 may be a novel target in the GC therapy.