RUNX2 promotes malignant progression in gastric cancer by regulating COL1A1

Characterize molecular signatures and establish a prognostic signature of gastric cancer by integrating single-cell RNA sequencing and bulk RNA sequencing

Gastric cancer is a significant global health concern with complex molecular underpinnings influencing disease progression and patient outcomes. Various molecular drivers were reported, and these studies offered potential avenues for targeted therapies, biomarker discovery, and the development of precision medicine strategies. However, it was posed that the heterogeneity of the disease and the complexity of the molecular interactions are still challenging. By seamlessly integrating data from single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq), we embarked on characterizing molecular signatures and establishing a prognostic signature for this complex malignancy. We offered a holistic view of gene expression landscapes in gastric cancer, identified 226 candidate marker genes from 3 different dimensions, and unraveled key players' risk stratification and treatment decision-making. The convergence of molecular insights in gastric cancer progression occurs at multiple biological scales simultaneously. The focal point of this study lies in developing a prognostic model, and we amalgamated four molecular signatures (COL4A1, FKBP10, RNASE1, SNCG) and three clinical parameters using advanced machine-learning techniques. The model showed high predictive accuracy, with the potential to revolutionize patient care by using clinical variables. This will strengthen the reliability of the model and enable personalized therapeutic strategies based on each patient's unique molecular profile. In summary, our research sheds light on the molecular underpinnings of gastric cancer, culminating in a powerful prognostic tool for gastric cancer. With a firm foundation in biological insights and clinical implications, our study paves the way for future validations and underscores the potential of integrated molecular analysis in advancing precision oncology.

Identification of differentially expressed mRNAs as novel predictive biomarkers for gastric cancer diagnosis and prognosis

BACKGROUND

Gastric cancer (GC) has a high mortality rate worldwide. Despite significant progress in GC diagnosis and treatment, the prognosis for affected patients still remains unfavorable.

AIM

To identify important candidate genes related to the development of GC and identify potential pathogenic mechanisms through comprehensive bioinformatics analysis.

METHODS

The Gene Expression Omnibus database was used to obtain the GSE183136 dataset, which includes a total of 135 GC samples. The limma package in R software was employed to identify differentially expressed genes (DEGs). Thereafter, enrichment analyses of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed for the gene modules using the clusterProfile package in R software. The protein-protein interaction (PPI) networks of target genes were constructed using STRING and visualized by Cytoscape software. The common hub genes that emerged in the cohort of DEGs that was retrieved from the GEPIA database were then screened using a Venn Diagram. The expression levels of these overlapping genes in stomach adenocarcinoma samples and non-tumor samples and their association with prognosis in GC patients were also obtained from the GEPIA database and Kaplan-Meier curves. Moreover, real-time quantitative polymerase chain reaction (RT-qPCR) and western blotting were performed to determine the mRNA and protein levels of glutamic-pyruvic transaminase (GPT) in GC and normal immortalized cell lines. In addition, cell viability, cell cycle distribution, migration and invasion were evaluated by cell counting kit-8, flow cytometry and transwell assays. Furthermore, we also conducted a retrospective analysis on 70 GC patients diagnosed and surgically treated in Wenzhou Central Hospital, Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University between January 2017 to December 2020. The tumor and adjacent normal samples were collected from the patients to determine the potential association between the expression level of GPT and the clinical as well as pathological features of GC patients.

RESULTS

We selected 19214 genes from the GSE183136 dataset, among which there were 250 downregulated genes and 401 upregulated genes in the tumor samples of stage III-IV in comparison to those in tumor samples of stage I-II with a P-value < 0.05. In addition, GO and KEGG results revealed that the various upregulated DEGs were mainly enriched in plasma membrane and neuroactive ligand-receptor interaction, whereas the downregulated DEGs were primarily enriched in cytosol and pancreatic secretion, vascular smooth muscle contraction and biosynthesis of the different cofactors. Furthermore, PPI networks were constructed based on the various upregulated and downregulated genes, and there were a total 15 upregulated and 10 downregulated hub genes. After a comprehensive analysis, several hub genes, including runt-related transcription factor 2 (RUNX2), salmonella pathogenicity island 1 (SPI1), lysyl oxidase (LOX), fibrillin 1 (FBN1) and GPT, displayed prognostic values. Interestingly, it was observed that GPT was downregulated in GC cells and its upregulation could suppress the malignant phenotypes of GC cells. Furthermore, the expression level of GPT was found to be associated with age, lymph node metastasis, pathological staging and distant metastasis (P < 0.05).

CONCLUSION

RUNX2, SPI1, LOX, FBN1 and GPT were identified key hub genes in GC by bioinformatics analysis. GPT was significantly associated with the prognosis of GC, and its upregulation can effectively inhibit the proliferative, migrative and invasive capabilities of GC cells.

Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC

Clear cell renal cell carcinoma (ccRCC) is the prevailing histological subtype of renal cell carcinoma and has unique metabolic reprogramming during its occurrence and development. Cell senescence is one of the newly identified tumor characteristics. However, there is a dearth of methodical and all-encompassing investigations regarding the correlation between the broad-ranging alterations in metabolic processes associated with aging and ccRCC. We utilized a range of analytical methodologies, such as protein‒protein interaction network analysis and least absolute shrinkage and selection operator (LASSO) regression analysis, to form and validate a risk score model known as the senescence-metabolism-related risk model (SeMRM). Our study demonstrated that SeMRM could more precisely predict the OS of ccRCC patients than the clinical prognostic markers in use. By utilizing two distinct datasets of ccRCC, ICGC-KIRC (the International Cancer Genome Consortium) and GSE29609, as well as a single-cell dataset (GSE156632) and real patient clinical information, and further confirmed the relationship between the senescence-metabolism-related risk score (SeMRS) and ccRCC patient progression. It is worth noting that patients who were classified into different subgroups based on the SeMRS exhibited notable variations in metabolic activity, immune microenvironment, immune cell type transformation, mutant landscape, and drug responsiveness. We also demonstrated that PTGER4, a key gene in SeMRM, regulated ccRCC cell proliferation, lipid levels and the cell cycle in vivo and in vitro. Together, the utilization of SeMRM has the potential to function as a dependable clinical characteristic to increase the accuracy of prognostic assessment for patients diagnosed with ccRCC, thereby facilitating the selection of suitable treatment strategies.

RUNX transcription factors: biological functions and implications in cancer

Runt-related transcription factors (RUNX) are a family of transcription factors that are essential for normal and malignant hematopoietic processes. Their most widely recognized role in malignancy is to promote the occurrence and development of acute myeloid leukemia. However, it is worth noting that during the last decade, studies of RUNX proteins in solid tumors have made considerable progress, suggesting that these proteins are directly involved in different stages of tumor development, including tumor initiation, progression, and invasion. RUNX proteins also play a role in tumor angiogenesis, the maintenance of tumor cell stemness, and resistance to antitumor drugs. These findings have led to the consideration of RUNX as a tumor biomarker. All RUNX proteins are involved in the occurrence and development of solid tumors, but the role of each RUNX protein in different tumors and the major signaling pathways involved are complicated by tumor heterogeneity and the interacting tumor microenvironment. Understanding how the dysregulation of RUNX in tumors affects normal biological processes is important to elucidate the molecular mechanisms by which RUNX affects malignant tumors.

Revealing PPP1R12B and COL1A1 as piRNA pathway genes contributing to abdominal aortic aneurysm through integrated analysis and experimental validation

BACKGROUND

Abdominal aortic aneurysm (AAA) is a permanent dilation of the abdominal aorta, with a high mortality rate when rupturing. Although lots of piRNA pathway genes (piRPGs) have recently been linked to both neoplastic and non-neoplastic illnesses, their role in AAA is still unknown. Utilizing integrative bioinformatics methods, this research discovered piRPGs as biomarkers for AAA and explore possible molecular mechanisms.

METHODS

The datasets were obtained from the Gene Expression Omnibus and piRPGs were identified from the Genecards database. The "limma" and "clusterProfiler" R-packages were used to discover differentially expressed genes and perform enrichment analysis, respectively. Hub piRPGs were further filtered using least absolute shrinkage and selection operator regression, random forests, as well as receiver operating characteristic curve. Additionally, multi-factor logistic regression (MLR), extreme gradient boosting (XGboost), and artificial neural network (ANN) were employed to construct prediction models. The relationship between hub piRPGs and immune infiltrating cells and sgGSEA were further studied. The expression of hub piRPGs was verified by qRT-PCR, immunohistochemistry, and western blotting in AAA and normal vascular tissues and analyzed by scRNA-seq in mouse AAA model. SRAMP and cMAP database were utilized for the prediction of N6-methyladenosine (m6A) targets therapeutic drug.

RESULTS

34 differentially expressed piRPGs were identified in AAA and enriched in pathways of immune regulation and gene silence. Three piRPGs (PPP1R12B, LRP10, and COL1A1) were further screened as diagnostic genes and used to construct prediction model. Compared with MLR and ANN, Xgboost showed better predictive ability, and PPP1R12B might have the ability to distinguish small and large AAA. Furthermore, the expression levels of PPP1R12B and COL1A1 were consistent with the results of bioinformatics analysis, and PPP1R12B showed a downward trend that may be related to m6A.

CONCLUSION

The results suggest that piRPGs might serve a significant role in AAA. PPP1R12B, COL1A1, and LRP10 had potential as diagnostic-specific biomarkers for AAA and performed better in XGboost model. The expression and localization of PPP1R12B and COL1A1 were experimentally verified. Besides, downregulation of PPP1R12B caused by m6A might contribute to the formation of AAA.

RUNX2 as a Prognostic Factor in Human Cancers

The RUNX2 transcription factor was discovered as an essential transcriptional regulator for commitment to osteoblast lineage cells and bone formation. Expression of RUNX2 in other tissues, such as breast, prostate, and lung, has been linked to oncogenesis, cancer progression, and metastasis. In this study, we sought to determine the extent of RUNX2 involvement in other tumors using a pan-cancer analysis strategy. We correlated RUNX2 expression and clinical-pathological parameters in human cancers by interrogating publicly available multiparameter clinical data. Our analysis demonstrated that altered RUNX2 expression or function is associated with several cancer types from different tissues. We identified three tumor types associated with increased RUNX2 expression and four other tumor types associated with decreased RUNX2 expression. Our pan-cancer analysis for RUNX2 revealed numerous other discoveries for RUNX2 regulation of different cancers identified in each of the pan-cancer databases. Both up and down regulation of RUNX2 was observed during progression of specific types of cancers in promoting the distinct types of cancers.

Loss of SLC27A5 Activates Hepatic Stellate Cells and Promotes Liver Fibrosis via Unconjugated Cholic Acid

Although the dysregulation of bile acid (BA) composition has been associated with fibrosis progression, its precise roles in liver fibrosis is poorly understood. This study demonstrates that solute carrier family 27 member 5 (SLC27A5), an enzyme involved in BAs metabolism, is substantially downregulated in the liver tissues of patients with cirrhosis and fibrosis mouse models. The downregulation of SLC27A5 depends on RUNX family transcription factor 2 (RUNX2), which serves as a transcriptional repressor. The findings reveal that experimental SLC27A5 knockout (Slc27a5-/- ) mice display spontaneous liver fibrosis after 24 months. The loss of SLC27A5 aggravates liver fibrosis induced by carbon tetrachloride (CCI4 ) and thioacetamide (TAA). Mechanistically, SLC27A5 deficiency results in the accumulation of unconjugated BA, particularly cholic acid (CA), in the liver. This accumulation leads to the activation of hepatic stellate cells (HSCs) by upregulated expression of early growth response protein 3 (EGR3). The re-expression of hepatic SLC27A5 by an adeno-associated virus or the reduction of CA levels in the liver using A4250, an apical sodium-dependent bile acid transporter (ASBT) inhibitor, ameliorates liver fibrosis in Slc27a5-/- mice. In conclusion, SLC27A5 deficiency in mice drives hepatic fibrosis through CA-induced activation of HSCs, highlighting its significant implications for liver fibrosis treatment.

hsa_circ_0020378 regulating miR-339-3p/COL1A1 promotes osteosarcoma progression

Osteosarcoma is a malignant orthopedic tumor that is frequently diagnosed in the pediatric population. Several studies have summarized the functions of circular RNAs (circRNAs) in the progression of osteosarcoma. This study aimed to investigate a novel circRNA, hsa_circ_0020378 (circ_0020378), and elucidate its functions and underlying mechanisms during osteosarcoma progression. The expression levels of circ_0020378, miR-339-3p, and COL1A1 in osteosarcoma cells and tissues were determined using RT-qPCR or Western blotting. CCK8, transwell migration, colony formation, and xenograft experiments were performed to assess the malignancy of osteosarcoma cells. Luciferase and RNA immunoprecipitation (RIP) experiments were employed to validate the interactions of miR-339-3p with circ_0020378 and COL1A1 3'UTR. Osteosarcoma cells and tissues showed significant upregulation of circ_0020378 and COL1A1 and downregulation of miR-339-3p. Silencing circ_0020378 in osteosarcoma cells inhibited their proliferation, colony formation, and migration. The inhibitive influence of circ_0020378 silencing during osteosarcoma tumorigenesis in vitro was verified in vivo. Circ_0020378 sponged miR-339-3p which targeted COL1A1 3'UTR. Circ _0020378 silencing disrupted the tumor-promoting effect of the miR-339-3p inhibitor in osteosarcoma cells. Furthermore, miR-339-3p inhibitor attenuated the suppressive effect of COL1A1 downregulation on malignant osteosarcoma cell phenotypes. Circ_0020378 stimulates osteosarcoma progression by downregulating miR-339-3p/COL1A1 expression. These findings provide a theoretical basis for the discovery of novel osteosarcoma targets.

Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis

AIM

Gastric cancer (GC) is one of the most diagnosed cancers worldwide. GC is a heterogeneous disease whose pathogenesis has not been entirely understood. Besides, the GC prognosis for patients remains poor. Hence, finding reliable biomarkers and therapeutic targets for GC patients is urgently needed.

METHODS

GSE54129 and GSE26942 datasets were downloaded from Gene Expression Omnibus (GEO) database to detect differentially expressed genes (DEGs). Then, gene set enrichment analyses and protein-protein interactions were investigated. Afterward, ten hub genes were identified from the constructed network of DEGs. Then, the expression of hub genes in GC was validated. Performing survival analysis, the prognostic value of each hub gene in GC samples was investigated. Finally, the databases were used to predict microRNAs that could regulate the hub genes. Eventually, top miRNAs with more interactions with the list of hub genes were introduced.

RESULTS

In total, 203 overlapping DEGs were identified between both datasets. The main enriched KEGG pathway was "Protein digestion and absorption." The most significant identified GO terms included "primary alcohol metabolic process," "basal part of cell," and "extracellular matrix structural constituent conferring tensile strength." Identified hub modules were COL1A1, COL1A2, TIMP1, SPP1, COL5A2, THBS2, COL4A1, MUC6, CXCL8, and BGN. The overexpression of seven hub genes was associated with overall survival. Moreover, among the list of selected miRNAs, hsa-miR-27a-3, hsa-miR-941, hsa-miR-129-2-3p, and hsa-miR-1-3p, were introduced as top miRNAs targeting more than five hub genes.

CONCLUSIONS

The present study identified ten genes associated with GC, which may help discover novel prognostic and diagnostic biomarkers as well as therapeutic targets for GC. Our results may advance the understanding of GC occurrence and progression.

Transcriptome sequencing identifies prognostic genes involved in gastric adenocarcinoma

Gastric adenocarcinoma (GAC) is one of the world's most lethal malignant tumors. It has been established that the occurrence and progression of GAC are linked to molecular changes. However, the pathogenesis mechanism of GAC remains unclear. In this study, we sequenced 6 pairs of GAC tumor tissues and adjacent normal tissues and collected GAC gene expression profile data from the TCGA database. Analysis of this data revealed 465 differentially expressed genes (DEGs), of which 246 were upregulated and 219 were downregulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis demonstrated that DEGs were observably enriched in ECM-receptor interaction, protein digestion and absorption, and gastric acid secretion pathways. Six key genes (MATN3, COL1A1, COL5A2, P4HA3, SERPINE1 and VCAN) associated with poor GAC prognosis were screened from the protein‒protein interaction (PPI) network by survival analysis, and P4HA3 and MATN3 have rarely been reported to be associated with GAC. We further analyzed the function of P4HA3 in the GAC cell line SGC-7901 by RT‒qPCR, MTT, flow cytometry, colony formation, wound healing, Transwell and western blot assays. We found that P4HA3 was upregulated in the SGC-7901 cell line versus normal control cells. The outcomes of the loss-of-function assay illustrated that P4HA3 significantly enhanced the ability of GAC cells to proliferate and migrate. This study provides a new basis for the selection of prognostic markers and therapeutic targets for GAC.

CHSY3 promotes proliferation and migration in gastric cancer and is associated with immune infiltration

BACKGROUND

The glycosyltransferase CHSY3 is a CHSY family member, yet its importance in the context of gastric cancer development remains incompletely understood. The present study was thus developed to explore the mechanistic importance of CHSY3 as a regulator of gastric cancer.

METHODS

Expression of CHSY3 was verified by TCGA, GEO and HPA databases. Kaplan-Meier curve, ROC, univariate cox, multivariate cox, and nomogram models were used to verify the prognostic impact and predictive value of CHSY3. KEGG and GO methods were used to identify signaling pathways associated with CHSY3. TIDE and IPS scores were used to assess the immunotherapeutic value of CHSY3. WGCNA, Cytoscape constructs PPI networks and random forest models to identify key Hub genes. Finally, qRT-PCR and immunohistochemical staining were performed to verify CHSY3 expression in clinical specimens. The ability of CHSY3 to regulate tumor was further assessed by CCK-8 assay and cloning assay, EDU assay, migration assay, invasion assay, and xenograft tumor model analysis.

RESULTS

The expression of CHSY3 was discovered to be abnormally upregulated in GC tissues through TCGA, GEO, and HPA databases, and the expression of CHSY3 was associated with poor prognosis in GC patients. Correlation analysis and Cox regression analysis revealed higher CHSY3 expression in higher T staging, an independent prognostic factor for GC. Moreover, elevated expression of CHSY3 was found to reduce the benefit of immunotherapy as assessed by the TIDE score and IPS score. Then, utilizing WGCNA, the PPI network constructed by Cytoscape, and random forest model, the Hub genes of COL5A2, POSTN, COL1A1, and FN1 associated with immunity were screened. Finally, the expression of CHSY3 in GC tissues was verified by qRT-PCR and immunohistochemical staining. Moreover, the expression of CHSY3 was further demonstrated by in vivo and in vitro experiments to promote the proliferation, migration, and invasive ability of GC.

CONCLUSIONS

The results of this study suggest that CHSY3 is an important regulator of gastric cancer progression, highlighting its promise as a therapeutic target for gastric cancer.

Reviewing the Regulators of COL1A1

The collagen family contains 28 proteins, predominantly expressed in the extracellular matrix (ECM) and characterized by a triple-helix structure. Collagens undergo several maturation steps, including post-translational modifications (PTMs) and cross-linking. These proteins are associated with multiple diseases, the most pronounced of which are fibrosis and bone diseases. This review focuses on the most abundant ECM protein highly implicated in disease, type I collagen (collagen I), in particular on its predominant chain collagen type I alpha 1 (COLα1 (I)). An overview of the regulators of COLα1 (I) and COLα1 (I) interactors is presented. Manuscripts were retrieved searching PubMed, using specific keywords related to COLα1 (I). COL1A1 regulators at the epigenetic, transcriptional, post-transcriptional and post-translational levels include DNA Methyl Transferases (DNMTs), Tumour Growth Factor β (TGFβ), Terminal Nucleotidyltransferase 5A (TENT5A) and Bone Morphogenic Protein 1 (BMP1), respectively. COLα1 (I) interacts with a variety of cell receptors including integrinβ, Endo180 and Discoidin Domain Receptors (DDRs). Collectively, even though multiple factors have been identified in association to COLα1 (I) function, the implicated pathways frequently remain unclear, underscoring the need for a more spherical analysis considering all molecular levels simultaneously.

RUNX2 promotes gastric cancer progression through the transcriptional activation of MGAT5 and MMP13

Introduction

RUNX2 is overexpressed in gastric cancer but the mechanism(s) through which it promotes tumor progression remain undefined. Here, we investigated the role of RUNX2 on gastric cancer pathogenesis at the molecular level.

Methods

The qRT-PCR and western bolt were utilized to examine the mRNA and protein levels. CCK-8, Transwell and wound healing assays were used to measure cell proliferation, invasion and migration. CHIP-PCR gel electrophoresis was used to verify RUNX2 as a transcription factor for MMP13 and MGAT5. The in vivo assay was utilized to assess tumor growth. In vivo assay was used to evaluate tumor growth, aberrant expression of RUNX2 and lung metastasis of gastric cancer.

Results

RUNX2 is overexpressed in MKN-45 and AGS cells. Genetic RUNX2 silencing reduced the proliferation, invasion and migration of MKN-45 and AGS cells. Analysis of the gastric cancer samples from the database revealed a significant positive correlation between MGAT5, MMP13, and RUNX2 expression. JASPAR analysis revealed that there was a potential binding site of RUNX2 in the promoter regions of MGAT5 and MMP13, and the experimental results confirmed that RUNX2 could regulate the expression of MGAT5 and MMP13 respectively. In vivo assays confirmed the aberrant expression of RUNX2 in mouse models of gastric cancer and reduced growth and lung metastasis in RUNX2 silenced xenograft tumors assessed.

Conclusion

Collectively, these data reveal that RUNX2 enhances MGAT5 and MMP13 expression in gastric cancer cells and represents a biomarker and potential therapeutic target for gastric cancer therapy.

Runt-related transcription factors in human carcinogenesis: a friend or foe?

PURPOSE

Cancer is one of the deadliest pathologies with more than 19 million new cases and 10 million cancer-related deaths across the globe. Despite development of advanced therapeutic interventions, cancer remains as a fatal pathology due to lack of early prognostic biomarkers, therapy resistance and requires identification of novel drug targets.

METHODS

Runt-related transcription factors (Runx) family controls several cellular and physiological functions including osteogenesis. Recent literatures from PubMed was mined and the review was written in comprehensive manner RESULTS: Recent literature suggests that aberrant expression of Runx contributes to tumorigenesis of many organs. Conversely, cell- and tissue-specific tumor suppressor roles of Runx are also reported. In this review, we have provided the structural/functional properties of Runx isoforms and its regulation in context of human cancer. Moreover, in an urgent need to discover novel therapeutic interventions against cancer, we comprehensively discussed the reported oncogenic and tumor suppressive roles of Runx isoforms in several tumor types and discussed the discrepancies that may have risen on Runx as a driver of malignant transformation.

CONCLUSION

Runx may be a novel therapeutic target against a battery of deadly human cancers.

RUNX2 and Cancer

Runt-related transcription factor 2 (RUNX2) is critical for the modulation of chondrocyte osteoblast differentiation and hypertrophy. Recently discovered RUNX2 somatic mutations, expressional signatures of RUNX2 in normal tissues and tumors, and the prognostic and clinical significance of RUNX2 in many types of cancer have attracted attention and led RUNX2 to be considered a biomarker for cancer. Many discoveries have illustrated the indirect and direct biological functions of RUNX2 in orchestrating cancer stemness, cancer metastasis, angiogenesis, proliferation, and chemoresistance to anticancer compounds, warranting further exploration of the associated mechanisms to support the development of a novel therapeutic strategy. In this review, we focus mainly on critical and recent research developments, including RUNX2's oncogenic activities, by summarizing and integrating the findings on somatic mutations of RUNX2, transcriptomic studies, clinical information, and discoveries about how the RUNX2-induced signaling pathway modulates malignant progression in cancer. We also comprehensively discuss RUNX2 RNA expression in a pancancer panel and in specific normal cell types at the single-cell level to indicate the potential cell types and sites for tumorigenesis. We expect this review to shed light on the recent mechanistical findings and modulatory role of RUNX2 in cancer progression and provide biological information that can guide new research in this field.

Identification of Potential Diagnostic and Prognostic Biomarkers for Gastric Cancer Based on Bioinformatic Analysis

Gastric cancer (GC) ranks third for cancer-related fatalities worldwide. It is still unclear what causes GC to progress. Using integrated bioinformatics analysis, COL5A2 has been proved to be related to GC development, which may identify the likely pathogenic mechanism. Data from GC patients were gathered using The Cancer Gene Atlas (TCGA) and the gene expression omnibus (GEO). The level of COL5A2 expression was compared between paired GC and normal tissues. The differentially expressed genes (DEGs) in GC patients with high and low COL5A2 expression were identified using functional enrichment analysis to identify the signature pathways linked to the DEGs. The clinical pathologic traits connected to overall survival (OS) of GC patients were examined utilizing Cox regression and the Kaplan-Meier method. To assess the prognostic significance of COL5A2, receiver operating characteristic (ROC) curves was drawn. How the immune system infiltrate both normal gastric and GC tumor tissues was investigated. Using the human protein atlas (HPA) database, regression, and the Kaplan-Meier method, immunohistochemical analysis of DEG COL5A2 expression in GC tissues was carried out. The correlation between COL5A2 expression and the GC grouping was found to be highly significant. Functional annotations revealed that COL5A2 participates in extracellular matrix structure, collagen metabolism, and other biological processes (BPs). High COL5A2 expression was associated with poor prognostic and clinical features, such as clinical T, N, and M stages. ROC curves exhibited that COL5A2 might predict the occurrence of gastric cancer. The infiltration degree of 21 immune cell subsets, including activated dendritic cells (aDCs), CD8+ T cells, and cytotoxic cells, was found to be dramatically relevant to COL5A2. Immunohistochemical analysis indicated that the expression of COL5A2 in tumor tissues is higher than that in normal tissues. The COL5A2 gene may offer fresh perspectives on the pathogenic mechanism underlying GC, as well as potential biomarkers for estimating GC patient prognosis. As a result, COL5A2 may be a useful biomarker for predicting patient survival.

RUNX2 facilitates aggressiveness and chemoresistance of triple negative breast cancer cells via activating MMP1

Breast cancer remains the most common malignancy in women and constantly threatens the lives of patients worldwide. State-of-the-art renewal has indicated the involvement of RUNX-associated transcription factor 2 (RUNX2) in tumorigenesis and cancer progression, yet the detailed information during breast cancer is largely obscure. Herein, we took advantage of breast cancer cell lines and in vivo tumorigenicity test as well as multifaceted phenotypic analyses (e.g., RNA-sequencing, ChIP and qRT-PCR assay) to verify the pathogenic mechanism of RUNX2 in triple negative breast cancer aggressiveness and chemoresistance. Strikingly, the proliferation, migration, invasion and chemoresistance of resistant cell lines in triple negative breast cancer was effectively suppressed by RUNX2 silencing, and the in vivo tumorigenicity was significantly weakened as well. Furthermore, with the aid of transcriptomic and bioinformatic analyses, we found MMP1 was highly expressed in triple negative breast cancer (TNBC) and showed a strong correlation with the poor prognosis of the patients, which was consistent with the expression pattern of RUNX2. Finally, by conducting ChIP and qRT-PCR assessment, we verified that RUNX2 functioned via directly binding to the specific motifs in the promoter of MMP1 and thus activating the transcriptional process. Collectively, our data demonstrated the facilitating effect of RUNX2 during triple negative breast cancer progression by directly orchestrating the expression of MMP1, which supplied overwhelming new references for RUNX2-MMP1 axis serving as a novel candidate for breast cancer diagnosis and treatment.

Roles of H19/miR-29a-3p/COL1A1 axis in COE-induced lung cancer

Occupational lung cancer caused by coke oven emissions (COE) has attracted increasing attention, but the mechanism is not clear. Many evidences show ceRNA (competing endogenous RNA) networks play important regulatory roles in cancers. In this study, we aimed to construct and verify the ceRNA regulatory network in the occurrence of COE-induced lung squamous cell carcinoma (LUSC). We performed RNA sequencing with lung bronchial epithelial cell (16HBE) and COE induced malignant transformed cell (Rf). Furthermore, we analyzed RNA sequencing data of LUSC and adjacent tissues in the cancer genome atlas (TCGA) database. Combined our data and TCGA data to determine the differentially expressed lncRNAs, miRNAs, mRNAs. lncBASE, miRDB and miRTarBase were used to predict the binding relationship between lncRNA and miRNA, miRNA and mRNA. Based on these, we construct the ceRNA network. FREMSA, dual-luciferase reporter assay, quantitative real-time PCR (qRT-PCR), western-blot were used to verify the regulatory axis. CCK8 assay, phalloidin staining, p53 detection were used to explore the roles of this axis in the COE induced malignant transformation. Results showed 7 lncRNAs, 7 miRNAs and 146 mRNAs were identified. Among these, we constructed a ceRNA network including 1 lncRNA, 2 miRNAs and 9 mRNAs. Further verification confirmed the trend of lncRNA H19, miR-29a-3p and COL1A1 were consistent with sequencing results. H19 and COL1A1 were significantly higher in Rf than in 16HBE and miR-29a-3p was reverse. Regulatory investigation revealed H19 increased COL1A1 expression by sponging miR-29a-3p. Knockdown of H19, COL1A1 or overexpression of miR-29a-3p in Rf cells could inhibit cell proliferation, increased cell adhesion and p53 level. However, knockdown of H19 while suppressing the miR-29a-3p partially rescue the malignant phenotype of Rf caused by H19. In conclusion, all these indicated H19 functioned as a ceRNA to increase COL1A1 by sponging miR-29a-3p and promoted COE-induced cell malignant transformation.

GRHL2 Expression Functions in Breast Cancer Aggressiveness and Could Serve as Prognostic and Diagnostic Biomarker for Breast Cancer

Background

Breast cancer (BC) is the most frequent malignancy in women worldwide and the leading cause of female cancer-associated death in the world. Grainyhead-like 2 (GRHL2) is an important gene involved in human cancer progression. However, the role of GRHL2 in BC is unknown.

Methods

In this study, we used in vitro experiments to verify the role of GRHL2 expression in BC progression. We used 14 databases to analyse the expression level of GRHL2 in BC and its prognostic and diagnostic value. In addition, the correlation between GRHL2 expression and immune cell infiltration and DNA methylation was also analysed.

Results

At the cellular level, overexpression of GRHL2 induced E-cadherin expression in BC cells with a mesenchymal phenotype and resulted in a hybrid epithelial/mesenchymal (E/M) phenotype, which is more strongly correlated with tumour aggressiveness than a pure mesenchymal phenotype. Through analysis of various databases, we found that tumour tissue had a higher expression level of GRHL2. High expression of GRHL2 was associated with worse prognosis of BC patients and indicated that GRHL2 had significant diagnostic value. Grainyhead-like 2 is also related to immune infiltration and regulated by DNA methylation. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses showed that GRHL2-related signalling pathways in BC were related to tumour cell proliferation, invasion, and angiogenesis.

Conclusions

In summary, evidence indicates that GRHL2 can be used as a prognostic and diagnostic biomarker for BC.

Identification of Potential Diagnostic and Prognostic Biomarkers for Gastric Cancer Based on Bioinformatic Analysis

Background: Gastric cancer (GC) is one of the most prevalent cancers all over the world. The molecular mechanisms of GC remain unclear and not well understood. GC cases are majorly diagnosed at the late stage, resulting in a poor prognosis. Advances in molecular biology techniques allow us to get a better understanding of precise molecular mechanisms and enable us to identify the key genes in the carcinogenesis and progression of GC.

Methods: The present study used datasets from the GEO database to screen differentially expressed genes (DEGs) between GC and normal gastric tissues. GO and KEGG enrichments were utilized to analyze the function of DEGs. The STRING database and Cytoscape software were applied to generate protein–protein network and find hub genes. The expression levels of hub genes were evaluated using data from the TCGA database. Survival analysis was conducted to evaluate the prognostic value of hub genes. The GEPIA database was involved to correlate key gene expressions with the pathological stage. Also, ROC curves were constructed to assess the diagnostic value of key genes.

Results: A total of 607 DEGs were identified using three GEO datasets. GO analysis showed that the DEGs were mainly enriched in extracellular structure and matrix organization, collagen fibril organization, extracellular matrix (ECM), and integrin binding. KEGG enrichment was mainly enriched in protein digestion and absorption, ECM-receptor interaction, and focal adhesion. Fifteen genes were identified as hub genes, one of which was excluded for no significant expression between tumor and normal tissues. COL1A1, COL5A2, P4HA3, and SPARC showed high values in prognosis and diagnosis of GC.

Conclusion: We suggest COL1A1, COL5A2, P4HA3, and SPARC as biomarkers for the diagnosis and prognosis of GC.