Collagen type Ⅳ alpha 1 (COL4A1) silence hampers the invasion, migration and epithelial-mesenchymal transition (EMT) of gastric cancer cells through blocking Hedgehog signaling pathway

Association of COL4A2 indel polymorphism with the development of stomach adenocarcinoma in Chinese populations

OBJECTIVE

The objective of the study was to assess the potential association between the indel polymorphism (rs34802628) located within the intron of the collagen type ⅳ alpha 2 gene (COL4A2) and the susceptibility to stomach adenocarcinoma (STAD) within a Chinese population.

METHODS

Peripheral venous blood samples were collected from a total of 497 STAD patients and 804 healthy control individuals to extract genomic DNA. The genotyping of the COL4A2 rs34802628 polymorphism was carried out using a polymerase chain reaction assay. Additionally, statistical analyses were conducted on the expression levels of COL4A2 mRNA using the GEPIA database. Meanwhile, the expression of COL4A2 mRNA was also validated by Real-time PCR using STAD tissue samples. Then, based on an analysis of patient tumor RNA seq data available from the Cancer Genome Atlas (TCGA), we assessed the prognostic value of mRNA expression of the COL4A2 gene in STAD patients using K-M plotter.

RESULTS

The study presented compelling evidence supporting an association between the rs34802628 polymorphism in the COL4A2 gene and susceptibility to STAD. Logistic regression analysis revealed that both the heterozygote and homozygote 4-bp del/del genotypes were significantly associated with a decreased risk of STAD, even after controlling for other variables (adjusted odds ratio [OR] = 0.663, 95% confidence interval [CI] 0.519-0.848, p = 0.037; OR = 0.422, 95% CI 0.290-0.614, p = 0.000005, respectively). Importantly, individuals carrying the 4-bp deletion allele demonstrated a notably lower risk of developing the disease (OR = 0.696, 95% CI 0.591-0.820, p = 0.000014). Furthermore, Genotype-phenotype correlation studies in human STAD tissue samples demonstrated that the higher mRNA expression levels of COL4A2 were associated with the ins allele of rs34802628. Bioinformatics analysis revealed that higher expression of the COL4A2 gene was significant with development and poor prognosis of STAD.

CONCLUSION

The results of our study provide strong evidence indicating a potential involvement of genetic variants in the COL4A2 gene in the development of STAD. Nonetheless, to validate and consolidate these findings, additional investigations incorporating larger sample sizes and functional experiments are necessary.

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 Key Genes Associated with Tumor Microenvironment Infiltration and Survival in Gastric Adenocarcinoma via Bioinformatics Analysis

OBJECTIVE

Gastric carcinoma (GC) is the fifth most commonly diagnosed cancer and the third leading cause of cancer-related deaths globally. The tumor microenvironment plays a significant role in the pathogenesis, prognosis, and response to immunotherapy. However, the immune-related molecular mechanisms underlying GC remain elusive. Bioinformatics analysis of the gene expression of GC and paracancerous healthy tissues from the same patient was performed to identify the key genes and signaling pathways, as well as their correlation to the infiltration of the tumor microenvironment (TME) by various immune cells related to GC development.

METHODS

We employed GSE19826, a gene expression profile from the Gene Expression Omnibus (GEO), for our analysis. Functional enrichment analysis of Differentially Expressed Genes (DEGs) was conducted using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes database.

RESULTS

Cytoscape software facilitated the identification of nine hub DEGs, namely, FN1, COL1A1, COL1A2, THBS2, COL3A1, COL5A1, APOE, SPP1, and BGN. Various network analysis algorithms were applied to determine their high connectivity. Among these hub genes, FN1, COL1A2, THBS2, COL3A1, COL5A1, and BGN were found to be associated with a poor prognosis for GC patients. Subsequent analysis using the TIMER database revealed the infiltration status of the TME concerning the overexpression of these six genes. Specifically, the abovementioned genes demonstrated direct correlations with cancer-associated fibroblasts, M1 and M2 macrophages, myeloid-derived suppressor cells, and activated dendritic cells.

CONCLUSION

Our findings suggest that the identified hub genes, particularly BGN, FN1, COL1A2, THBS2, COL3A1, and COL5A1, play crucial roles in GC prognosis and TME cell infiltration. This comprehensive analysis enhances our understanding of the molecular mechanisms underlying GC development and may contribute to the identification of potential therapeutic targets and prognostic markers for GC patients.

Characterization of tumor-associated endothelial cells and the development of a prognostic model in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by a complex tumor microenvironment. Angiogenesis is of paramount importance in the proliferation and metastasis of PDAC. However, currently, there are no well-defined biomarkers available to guide the prognosis and treatment of PDAC. In this study, we investigated the interactions between tumor-associated endothelial cells (TAECs) and tumor cells in PDAC, and identified a specific subset of TAECs characterized by high expression of COL4A1. COL4A1+ endothelial cells interact with tumor cells through the COLLAGEN signaling pathway to promote tumor cell proliferation, migration, and invasion. We also observed activation of HOXD9 in COL4A1+ endothelial cells. Based on these findings, we developed a prognostic model called TaEMS, which accurately predicts patient prognosis. TaEMS identified high-risk patients enriched in cell cycle-related pathways and low-risk patients enriched in focal adhesions, smooth muscle regulation, and immune pathways. Moreover, high-risk patients displayed a reduced level of immune cell infiltration, indicating the presence of a "cold tumor" phenotype. Overall, our study uncovered an intricate crosstalk between TAECs and tumor cells in PDAC, emphasizing the role of HOXD9 and highlighting the potential of TaEMS as a prognostic biomarker for precise therapies.

Molecular Insight into Gastric Cancer Invasion-Current Status and Future Directions

Gastric cancer (GC) is one of the most common malignancies worldwide. There has been no efficient therapy for stage IV GC patients due to this disease's heterogeneity and dissemination ability. Despite the rapid advancement of molecular targeted therapies, such as HER2 and immune checkpoint inhibitors, survival of GC patients is still unsatisfactory because the understanding of the mechanism of GC progression is still incomplete. Invasion is the most important feature of GC metastasis, which causes poor mortality in patients. Recently, genomic research has critically deepened our knowledge of which gene products are dysregulated in invasive GC. Furthermore, the study of the interaction of GC cells with the tumor microenvironment has emerged as a principal subject in driving invasion and metastasis. These results are expected to provide a profound knowledge of how biological molecules are implicated in GC development. This review summarizes the advances in our current understanding of the molecular mechanism of GC invasion. We also highlight the future directions of the invasion therapeutics of GC. Compared to conventional therapy using protease or molecular inhibitors alone, multi-therapy targeting invasion plasticity may seem to be an assuring direction for the progression of novel strategies.

Identification of key genes associated with poor prognosis and neoplasm staging in gastric cancer

BACKGROUND

Gastric cancer (GC) is highly biologically and genetically heterogeneous disease with poor prognosis. Increasing evidence indicates that biomarkers can serve as prediction and clinical intervention. Therefore, it is vital to identify core molecules and pathways participating in the development of GC.

METHODS

In this study, GSE54129, GSE56807, GSE63089, and GSE118916 were used for identified overlapped 75 DEGs. GO and Kyoto Encyclopedia of Genes and Genomes pathway analysis showed DEGs mainly enriched in biological process about collagen-containing extracellular matrix and collagen metabolic. Next, protein-protein interaction network was built and the hub gene was excavated. Clinicopathological features and prognostic value were also evaluated.

RESULTS

Hub genes were shown as below, FN1, COL1A2, COL1A1, COL3A1, COL4A1, COL6A3, COL5A2, SPARC, PDGFRB, COL12A1. Those genes were upregulation in GC and related to the poor prognosis (except COL5A2, P = .73). What is more, high expression indicated worse T stage and tumor, node, metastasis stage in GC patients. Later, the results of 25 GC tumor specimens and 34 normal tissues showed that FN1, COL3A1, COL4A1, SPARC, COL5A2, and COL12A1 were significantly upregulated in cancer samples.

CONCLUSION

Our study systematically explored the core genes and crucial pathways in GC, providing insights into clinical management and individual treatment.

Epigenetic and transcriptomic characterization reveals progression markers and essential pathways in clear cell renal cell carcinoma

Identifying tumor-cell-specific markers and elucidating their epigenetic regulation and spatial heterogeneity provides mechanistic insights into cancer etiology. Here, we perform snRNA-seq and snATAC-seq in 34 and 28 human clear cell renal cell carcinoma (ccRCC) specimens, respectively, with matched bulk proteogenomics data. By identifying 20 tumor-specific markers through a multi-omics tiered approach, we reveal an association between higher ceruloplasmin (CP) expression and reduced survival. CP knockdown, combined with spatial transcriptomics, suggests a role for CP in regulating hyalinized stroma and tumor-stroma interactions in ccRCC. Intratumoral heterogeneity analysis portrays tumor cell-intrinsic inflammation and epithelial-mesenchymal transition (EMT) as two distinguishing features of tumor subpopulations. Finally, BAP1 mutations are associated with widespread reduction of chromatin accessibility, while PBRM1 mutations generally increase accessibility, with the former affecting five times more accessible peaks than the latter. These integrated analyses reveal the cellular architecture of ccRCC, providing insights into key markers and pathways in ccRCC tumorigenesis.

Identification of the diagnostic genes and immune cell infiltration characteristics of gastric cancer using bioinformatics analysis and machine learning

Background: Finding reliable diagnostic markers for gastric cancer (GC) is important. This work uses machine learning (ML) to identify GC diagnostic genes and investigate their connection with immune cell infiltration. Methods: We downloaded eight GC-related datasets from GEO, TCGA, and GTEx. GSE13911, GSE15459, GSE19826, GSE54129, and GSE79973 were used as the training set, GSE66229 as the validation set A, and TCGA & GTEx as the validation set B. First, the training set screened differentially expressed genes (DEGs), and gene ontology (GO), kyoto encyclopedia of genes and genomes (KEGG), disease Ontology (DO), and gene set enrichment analysis (GSEA) analyses were performed. Then, the candidate diagnostic genes were screened by LASSO and SVM-RFE algorithms, and receiver operating characteristic (ROC) curves evaluated the diagnostic efficacy. Then, the infiltration characteristics of immune cells in GC samples were analyzed by CIBERSORT, and correlation analysis was performed. Finally, mutation and survival analyses were performed for diagnostic genes. Results: We found 207 up-regulated genes and 349 down-regulated genes among 556 DEGs. gene ontology analysis significantly enriched 413 functional annotations, including 310 biological processes, 23 cellular components, and 80 molecular functions. Six of these biological processes are closely related to immunity. KEGG analysis significantly enriched 11 signaling pathways. 244 diseases were closely related to Ontology analysis. Multiple entries of the gene set enrichment analysis analysis were closely related to immunity. Machine learning screened eight candidate diagnostic genes and further validated them to identify ABCA8, COL4A1, FAP, LY6E, MAMDC2, and TMEM100 as diagnostic genes. Six diagnostic genes were mutated to some extent in GC. ABCA8, COL4A1, LY6E, MAMDC2, TMEM100 had prognostic value. Conclusion: We screened six diagnostic genes for gastric cancer through bioinformatic analysis and machine learning, which are intimately related to immune cell infiltration and have a definite prognostic value.

The role of Hedgehog and Notch signaling pathway in cancer

Notch and Hedgehog signaling are involved in cancer biology and pathology, including the maintenance of tumor cell proliferation, cancer stem-like cells, and the tumor microenvironment. Given the complexity of Notch signaling in tumors, its role as both a tumor promoter and suppressor, and the crosstalk between pathways, the goal of developing clinically safe, effective, tumor-specific Notch-targeted drugs has remained intractable. Drugs developed against the Hedgehog signaling pathway have affirmed definitive therapeutic effects in basal cell carcinoma; however, in some contexts, the challenges of tumor resistance and recurrence leap to the forefront. The efficacy is very limited for other tumor types. In recent years, we have witnessed an exponential increase in the investigation and recognition of the critical roles of the Notch and Hedgehog signaling pathways in cancers, and the crosstalk between these pathways has vast space and value to explore. A series of clinical trials targeting signaling have been launched continually. In this review, we introduce current advances in the understanding of Notch and Hedgehog signaling and the crosstalk between pathways in specific tumor cell populations and microenvironments. Moreover, we also discuss the potential of targeting Notch and Hedgehog for cancer therapy, intending to promote the leap from bench to bedside.

The role of cancer-associated fibroblasts in tumorigenesis of gastric cancer

Despite advances in anticancer therapy, the prognosis of gastric cancer (GC) remains unsatisfactory. Research in recent years has shown that the malignant behavior of cancer is not only attributable to tumor cells but is partly mediated by the activity of the cancer stroma and controlled by various molecular networks in the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) are one of the most abundant mesenchymal cell components of the stroma and extensively participate in the malignant development of GC malignancy. CAFs modulate the biological properties of tumor cells in multiple ways, including the secretion of various bioactive molecules that have effects through paracrine and autocrine signaling, the release of exosomes, and direct interactions, thereby affecting GC initiation and development. However, there is marked heterogeneity in the cellular origins, phenotypes, and functions of CAFs in the TME of GC. Furthermore, variations in factors, such as proteins, microRNAs, and lncRNAs, affect interactions between CAFs and GC cells, although, the potential molecular mechanisms are still poorly understood. In this review, we aim to describe the current knowledge of the cellular features and heterogeneity of CAFs and discuss how these factors are regulated in CAFs, with a focus on how they affect GC biology. This review provides mechanistic insight that could inform therapeutic strategies and improve the prognosis of GC patients.

Silencing of immunoglobulin superfamily containing leucine-rich repeat inhibits gastric cancer cell growth and metastasis by regulating epithelial-mesenchymal transition

This study aims to investigate the immunoglobulin superfamily containing leucine-rich repeat (ISLR) expression in gastric cancer (GC) and ISLR’s underlying mechanisms regulation of GC progression. Through The Cancer Genome Atlas (TCGA) cohort datasets, we analyzed the ISLR expression in GC tumor tissues and normal tissues. ISLR expression in GC tissues and cells was determined using quantitative real-time polymerase chain reaction. Cell viability, proliferation, migration, and invasion assays were performed in GC cells transfected with sh-ISLR, ISLR plasmids, or controls. TCGA results showed that ISLR expression was higher in GC tumor tissues compared to normal tissues, and its expression levels were related to lymph node metastasis, tumor size, and clinical stage. ISLR was highly expressed in tumor cells. ISLR knockdown suppressed cell viability, proliferation, migration, and invasion in HGC-27 cells, whereas ISLR overexpression led to opposite effects in AGS cells. Gene Set Enrichment Analysis showed that ISLR could activate the epithelial–mesenchymal transition (EMT) signaling pathway. Silencing of ISLR suppressed EMT in HGC-27 cells and overexpression of ISLR promoted EMT in AGS cells. ISLR was overexpressed in both GC cell lines and tumor tissues, and our study first showed that silencing of ISLR inhibited GC cell growth and metastasis by reversing EMT.