The Extracellular Matrix: An Accomplice in Gastric Cancer Development and Progression

Neutrophil extracellular traps-related lncRNAs prognostic signature for gastric cancer and immune infiltration: potential biomarkers for predicting overall survival and clinical therapy

Gastric cancer (GC) is one of the most common digestive tract malignant tumors in the world. At the time of initial diagnosis, it frequently presents with local or distant metastasis, contributing to poor prognosis in patients. Neutrophil extracellular traps (NETs) constitute a mechanism employed by neutrophils that is intricately associated with tumor progression, prognosis, and response to immunotherapy and chemotherapy. Despite this, the specific involvement of NETs-related long non-coding RNAs (lncRNAs) in gastric cancer remains unclear. A prognostic model for NETs-related lncRNAs was constructed through correlation analysis, COX regression analysis, and least absolute shrinkage and selection operator regression (LASSO) analysis. The predictive performance of the model was assessed using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, facilitating the exploration of the relationship between disease onset and prognosis in gastric cancer. Additionally, differences in the tumor microenvironment and response to immunotherapy among gastric cancer patients across high- and low-risk groups were analyzed. Furthermore, a prognostic nomogram integrating the risk score with relevant clinicopathological parameters was developed. The prognostic prediction model for gastric cancer, derived from NETs-related lncRNAs in this study, demonstrates robust prognostic capabilities, serving as a valuable adjunct to traditional tumor staging. This model holds promise in offering novel guidelines for the precise treatment of gastric cancer, thereby potentially improving patient outcomes.

Prediction of novel biomarkers for gastric intestinal metaplasia and gastric adenocarcinoma using bioinformatics analysis

Background & aim

The histologic and molecular changes from intestinal metaplasia (IM) to gastric cancer (GC) have not been fully characterized. The present study sought to identify potential alterations in signaling pathways in IM and GC to predict disease progression; these alterations can be considered therapeutic targets.

Materials & methods

Seven gene expression profiles were selected from the GEO database. Discriminate differentially expressed genes (DEGs) were analyzed by EnrichR. The STRING database, Cytoscape, Gene Expression Profiling Interactive Analysis (GEPIA), cBioPortal, NetworkAnalyst, MirWalk database, OncomiR, and bipartite miRNA‒mRNA correlation network was used for downstream analyses of selected module genes.

Results

Analyses revealed that extracellular matrix-receptor interactions (ITGB1, COL1A1, COL1A2, COL4A1, FN1, COL6A3, and THBS2) in GC and PPAR signaling pathway interactions (FABP1, APOC3, APOA1, HMGCS2, and PPARA and PCK1) in IM may play key roles in both the carcinogenesis and progression of underlying GC from intestinal metaplasia. IM enrichment indicated that this is closely related to digestion and absorption. The TF-hub gene regulatory network revealed that AR, TCF4, SALL4, and ESR1 were more important for hub gene expression. It was revealed that the development and prediction of GC may be affected by hsa-miR-29. It was found that PTGR1, C1orf115, CRYL1, ALDOB, and SULT1B1 were downregulated in GC and upregulated in IM. Therefore, they might have tumor suppressor activity in GC progression.

Conclusion

New potential biomarkers and pathways involved in GC and IM were identified that are important for the transformation of GC from IM to adenocarcinoma and can be therapeutic targets for GC.

Nanoparticles in tumor microenvironment remodeling and cancer immunotherapy

Cancer immunotherapy and vaccine development have significantly improved the fight against cancers. Despite these advancements, challenges remain, particularly in the clinical delivery of immunomodulatory compounds. The tumor microenvironment (TME), comprising macrophages, fibroblasts, and immune cells, plays a crucial role in immune response modulation. Nanoparticles, engineered to reshape the TME, have shown promising results in enhancing immunotherapy by facilitating targeted delivery and immune modulation. These nanoparticles can suppress fibroblast activation, promote M1 macrophage polarization, aid dendritic cell maturation, and encourage T cell infiltration. Biomimetic nanoparticles further enhance immunotherapy by increasing the internalization of immunomodulatory agents in immune cells such as dendritic cells. Moreover, exosomes, whether naturally secreted by cells in the body or bioengineered, have been explored to regulate the TME and immune-related cells to affect cancer immunotherapy. Stimuli-responsive nanocarriers, activated by pH, redox, and light conditions, exhibit the potential to accelerate immunotherapy. The co-application of nanoparticles with immune checkpoint inhibitors is an emerging strategy to boost anti-tumor immunity. With their ability to induce long-term immunity, nanoarchitectures are promising structures in vaccine development. This review underscores the critical role of nanoparticles in overcoming current challenges and driving the advancement of cancer immunotherapy and TME modification.

The Impact of Transcriptional Profiling Cadherin Family and Therapeutic Approaches of Gastric Cancer: A Translational Outlook on Multi-omics Data Analysis

The classical cadherin gene has been linked to a variety of human malignancies, including gastric cancer. However, the link between cadherin genes and gastric cancer outcome is still unclear. This study used multi-omics data to examine the cadherin genes that were differentially regulated in gastric cancer. Differential expression of genes, epigenetic, molecular alterations, and protein expression analyses was conducted. Male SD rats were given N-methyl-N-nitrosourea (MNU) to induce stomach carcinoma in order to verify the activation of cadherin genes. CDH5, CDH6, CDH11, and CDH24 levels were found to be considerably higher in gastric cancer and may serve as useful indicators of stomach adenocarcinoma (STAD). Cadherin genes with variable expression had considerably more promoter methylation in cancers than in normal tissues. In individuals with gastric cancer, high expression of these cadherin genes was related to lower total mortality and disease-free survival rates. Furthermore, compared to normal rats, gastric cancer-induced rats had significantly higher expression and distribution of CDH5, CDH6, CDH11, and CDH24. This study sheds new light on the diagnosis and prognosis of gastric cancer by identifying potential prognostic markers such as CDH5, CDH6, CDH11, and CDH24. The multi-omics approach provided a potential tool for target-based therapy by accurately predicting the outcome of stomach cancer. Researchers may gain more knowledge about the role of cadherin genes in the development and dissemination of tumors to the activated rat model of gastric cancer.

Lipid Metabolism-Related Gene Signature Predicts Prognosis and Indicates Immune Microenvironment Infiltration in Advanced Gastric Cancer

Objective

Abnormal lipid metabolism is known to influence the malignant behavior of gastric cancer. However, the underlying mechanism remains elusive. In this study, we comprehensively analyzed the biological significance of genes involved in lipid metabolism in advanced gastric cancer (AGC).

Methods

We obtained gene expression profiles from The Cancer Genome Atlas (TCGA) database for early and advanced gastric cancer samples and performed differential expression analysis to identify specific lipid metabolism-related genes in AGC. We then used consensus cluster analysis to classify AGC patients into molecular subtypes based on lipid metabolism and constructed a diagnostic model using least absolute shrinkage and selection operator- (LASSO-) Cox regression analysis and Gene Set Enrichment Analysis (GSEA). We evaluated the discriminative ability and clinical significance of the model using the Kaplan-Meier (KM) curve, ROC curve, DCA curve, and nomogram. We also estimated immune levels based on immune microenvironment expression, immune checkpoints, and immune cell infiltration and obtained hub genes by weighted gene co-expression network analysis (WGCNA) of differential genes from the two molecular subtypes.

Results

We identified 6 lipid metabolism genes that were associated with the prognosis of AGC and used consistent clustering to classify AGC patients into two subgroups with significantly different overall survival and immune microenvironment. Our risk model successfully classified patients in the training and validation sets into high-risk and low-risk groups. The high-risk score predicted poor prognosis and indicated low degree of immune infiltration. Subgroup analysis showed that the risk model was an independent predictor of prognosis in AGC. Furthermore, our results indicated that most chemotherapeutic agents are more effective for AGC patients in the low-risk group than in the high-risk group, and risk scores for AGC are strongly correlated with drug sensitivity. Finally, we performed qRT-PCR experiments to verify the relevant results.

Conclusion

Our findings suggest that lipid metabolism-related genes play an important role in predicting the prognosis of AGC and regulating immune invasion. These results have important implications for the development of targeted therapies for AGC patients.

Influence of Tumor Stroma on the Aggressiveness of Poorly Cohesive Gastric Carcinoma

Tumor-stroma crosstalk promotes the adaptation of cancer cells to the local microenvironment and sustains their growth. We assessed the quantitative and qualitative impact of intralesional stroma on clinic-pathological features and the prognosis of poorly cohesive gastric cancer (PCGC) variants. Tissue microarrays including 75 PCGC specimens were immunostained for cytokeratin 8/18 and α-smooth muscle actin to assess the relative proportion of neoplastic cells versus stromal components and the cases were subsequently divided into stroma-rich (SR) and stroma-poor (SP) tumors. Stromal status is significantly associated with the depth of tumor invasion. Patient survival rate was found to be higher in the SP compared to the SR tumor group and, hence, abundant stroma was identified as a significant risk factor in univariable analysis but had no independent prognostic impact. We also investigated the mRNA levels of KRT8 and the associated transcriptional signatures using the molecular data of 82 PCGC cases divided into KRT8-high and KRT8-low groups. KRT8-high tumors were enriched in proteins localized in the extracellular compartment and their expression levels correlated with longer survival in the KRT8-high group and shorter overall survival in the KRT8-low group. Comprehensively, we find that relative intralesional stromal content is a marker of aggressiveness in PCGC tumors and that extracellular proteins characterize functionally and clinically different PCGC subgroups.

CLEC11A expression as a prognostic biomarker in correlation to immune cells of gastric cancer

Gastric cancer (GC) is a prevalent malignant cancer characterized by a poor survival rate. The C-type lectin domain family 11 member A (CLEC11A) is part of the C-type lectin superfamily, and its dysregulation has been implicated in the progression of several cancers. The specific role of CLEC11A and its association with immune infiltration in GC, however, remains unclear. In this study, we employed The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, Tumor IMmune Estimation Resource (TIMER) database, Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, Kaplan-Meier plotter databases, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and the CIBERSORT algorithm to investigate CLEC11A expression, its prognostic significance, its association with tumor immune infiltration, and gene function enrichment in GC. We conducted western blotting, Cell Counting Kit-8 (CCK-8), wound healing, and transwell assays to validate CLEC11A's function. We found that CLEC11A expression was significantly elevated in GC when compared to adjacent non-tumor tissues. Elevated CLEC11A expression was strongly associated with poor survival outcomes and advanced clinicopathological stages.  Moreover, heightened CLEC11A expression positively correlated with immunomodulators, chemokines, and the infiltration of immune cells, especially M2 macrophages, in GC. Additionally, CLEC11A silencing suppressed GC cells proliferation, migration and invasion in vitro. Our results elucidate the functions of CLEC11A in GC, suggesting its potential as a valuable prognostic biomarker and therapeutic target for GC immunotherapy.

The role of senescence genes in the treatment, prognosis, and tumor microenvironment of gastric cancer

AIM

Gastric cancer (GC) has a high incidence and poor prognosis. Senescence genes are suggested to participate in immune cell infiltration, thus affecting the immunotherapy of GC. In this research, we established a senescence-related GC model to explore and verify the role of senescence genes in the prognosis, treatment, and tumor microenvironment (TME) of GC.

METHODS

The TCGA GC (TCGA-STAD) dataset was used to screen key senescence genes from differentially expressed genes (DEGs). A prognostic risk model was trained utilizing the TCGA-STAD dataset and validated using an external GEO dataset. The CIBERSORT algorithm was run to explore the relationship between senescence genes and TME. The chemotherapy drug sensitivities in GC patients were calculated utilizing R package pRRophetic.

RESULTS

A total of 37 senescence-related DEGs were obtained. Five key senescence-related genes were further screened to establish a senescence-related risk model based on Cox regression. The survival status of GC patients in the high-risk group was found to be worse than that in the low-risk group. According to the results of gene set enrichment analysis, the senescence-related risk was mainly associated with cytokine activity, immune mechanism, and related pathways. By analyzing the sensitivity of common chemotherapy drugs in GC patients, it was revealed that the sensitivities of high-risk patients to Dasatinib, Lapatinib, and Pazopanib were lower than those of low-risk patients. The CIBERSORT algorithm was executed to analyze the TME in the high-risk group, revealing elevated levels of CD8 T cells, Macrophages M2, and resting Mast cells. In addition, decreased levels of resting memory CD4 T cells , resting NK cells, activated Dendritic cells, and activated Mast cells were also observed.

CONCLUSION

Senescence genes were related to the prognosis, response to chemotherapy drugs, and TME of GC. Our senescence-related risk model could forecast the survival of patients, their response to chemotherapy drugs, and the TME to a certain extent.

The ECM and tissue architecture are major determinants of early invasion mediated by E-cadherin dysfunction

Germline mutations of E-cadherin cause Hereditary Diffuse Gastric Cancer (HDGC), a highly invasive cancer syndrome characterised by the occurrence of diffuse-type gastric carcinoma and lobular breast cancer. In this disease, E-cadherin-defective cells are detected invading the adjacent stroma since very early stages. Although E-cadherin loss is well established as a triggering event, other determinants of the invasive process persist largely unknown. Herein, we develop an experimental strategy that comprises in vitro extrusion assays using E-cadherin mutants associated to HDGC, as well as mathematical models epitomising epithelial dynamics and its interaction with the extracellular matrix (ECM). In vitro, we verify that E-cadherin dysfunctional cells detach from the epithelial monolayer and extrude basally into the ECM. Through phase-field modelling we demonstrate that, aside from loss of cell-cell adhesion, increased ECM attachment further raises basal extrusion efficiency. Importantly, by combining phase-field and vertex model simulations, we show that the cylindrical structure of gastric glands strongly promotes the cell's invasive ability. Moreover, we validate our findings using a dissipative particle dynamics simulation of epithelial extrusion. Overall, we provide the first evidence that cancer cell invasion is the outcome of defective cell-cell linkages, abnormal interplay with the ECM, and a favourable 3D tissue structure.

Characterization of pathological stomach tissue using polarization-sensitive second harmonic generation microscopy

Alterations in collagen ultrastructure between human gastric adenocarcinoma and normal gastric tissue were investigated using polarization-resolved second harmonic generation (PSHG) microscopy. Cylindrical and trigonal symmetries were assumed to extract quantitative PSHG parameters, ρ, κ and S, from each image pixel. Statistically significant variations in these values were observed for gastric adenocarcinoma, indicating a higher disorder of collagen. Numerical focal volume simulations of crossing fibrils indicate increased S parameter is due to more intersecting collagen fibrils of varying diameters. These parameters were also able to distinguish between different grades of gastric adenocarcinoma indicating that PSHG may be useful for automated cancer diagnosis.

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.

Identification of miR-143-3p as a diagnostic biomarker in gastric cancer

BACKGROUND

Gastric cancer (GC) is among the most common types of gastrointestinal cancers and has a high incidence and mortality around the world. To suppress the progression of GC, it is essential to develop diagnostic markers. MicroRNAs regulate GC development, but a clearer insight into their role is needed before they can be applied as a molecular markers and targets.

METHODS

In this study, we assessed the diagnostic value of differentially expressed microRNAs as potential diagnostic biomarkers for GC using data for 389 tissue samples from the Cancer Genome Atlas (TCGA) and 21 plasma samples from GC patients.

RESULTS

The expression of hsa-miR-143-3p (also known as hsa-miR-143) was significantly downregulated in GC according to the TCGA data and plasma samples. The 228 potential target genes of hsa-miR-143-3p were analyzed using a bioinformatics tool for miRNA target prediction. The target genes correlated with extracellular matrix organization, the cytoplasm, and identical protein binding. Furthermore, the pathway enrichment analysis of target genes showed that they were involved in pathways in cancer, the phosphoinositide 3-kinase (PI3K)-protein kinase B (Akt) signaling pathway, and proteoglycans in cancer. The hub genes in the protein-protein interaction (PPI) network, were matrix metallopeptidase 2 (MMP2), CD44 molecule (CD44), and SMAD family member 3 (SMAD3).

CONCLUSIONS

This study suggests that hsa-miR-143-3p may be used as a diagnostic marker for GC, contributing via the pathways involved in the development of GC.

The conundrum of Helicobacter pylori-associated apoptosis in gastric cancer

Helicobacter pylori is a human microbial pathogen that colonizes the gastric epithelium and causes type B gastritis with varying degrees of active inflammatory infiltrates. The underlying chronic inflammation induced by H. pylori and other environmental factors may promote the development of neoplasms and adenocarcinoma of the stomach. Dysregulation of various cellular processes in the gastric epithelium and in different cells of the microenvironment is a hallmark of H. pylori infection. We address the conundrum of H. pylori-associated apoptosis and review distinct mechanisms induced in host cells that either promote or suppress apoptosis in gastric epithelial cells, often simultaneously. We highlight key processes in the microenvironment that contribute to apoptosis and gastric carcinogenesis.

PI3K/AKT/mTOR inhibitors as potential extracellular matrix modulators for targeting EMT subtype gastric tumors

Targeting the extracellular matrix (ECM) is considered as a promising strategy in cancer therapeutics. This study was designed to identify the potential ECM modulators for gastric cancer therapeutics. Exploration of the expression profiles of gastric tumors revealed the elevated expression of ECM genes in gastric tumor tissues compared to the adjacent normal tissues with increased expression in diffuse subtype gastric tumors and specifically in epithelial to mesenchymal transition (EMT) molecular subtype tumors. Consensus ECM gene set was derived from the expression profiles of gastric tumors. The correlative analysis was performed between the expression pattern of the ECM gene set and the drug sensitivity pattern of a panel of drugs across gastric cancer cell lines. Negative correlation between the expression of ECM genes and sensitivity of a number of drugs targeting PI3K/mTOR signaling, chromatin histone acetylation and ABL signaling was observed. These pathways are known for their role in cell-mediated adhesion, differentiation and epithelial to mesenchymal transition. The current results reveal the possibility of using PI3K/AKT/mTOR modulators for targeted gastric cancer therapy in patients with dysregulated ECM.

Artificial intelligence-guided discovery of gastric cancer continuum

BACKGROUND

Detailed understanding of pre-, early and late neoplastic states in gastric cancer helps develop better models of risk of progression to gastric cancers (GCs) and medical treatment to intercept such progression.

METHODS

We built a Boolean implication network of gastric cancer and deployed machine learning algorithms to develop predictive models of known pre-neoplastic states, e.g., atrophic gastritis, intestinal metaplasia (IM) and low- to high-grade intestinal neoplasia (L/HGIN), and GC. Our approach exploits the presence of asymmetric Boolean implication relationships that are likely to be invariant across almost all gastric cancer datasets. Invariant asymmetric Boolean implication relationships can decipher fundamental time-series underlying the biological data. Pursuing this method, we developed a healthy mucosa → GC continuum model based on this approach.

RESULTS

Our model performed better against publicly available models for distinguishing healthy versus GC samples. Although not trained on IM and L/HGIN datasets, the model could identify the risk of progression to GC via the metaplasia → dysplasia → neoplasia cascade in patient samples. The model could rank all publicly available mouse models for their ability to best recapitulate the gene expression patterns during human GC initiation and progression.

CONCLUSIONS

A Boolean implication network enabled the identification of hitherto undefined continuum states during GC initiation. The developed model could now serve as a starting point for rationalizing candidate therapeutic targets to intercept GC progression.

A novel metabolism-related prognostic gene development and validation in gastric cancer

BACKGROUND

The importance of metabolism-related alterations in the development of gastric cancer (GC) is increasingly recognized. The present study aimed to identify metabolism-related genes to facilitate prognosis of GC patients.

METHODS

Gene expression datasets and clinical information of GC patients were downloaded from TCGA and GEO databases. We scored the enrichment of human metabolism-related pathways (n = 86) in GC samples by GSV, constructed prognostic risk models using LASSO algorithm and multivariate Cox regression analysis, combined with clinical information to construct a nomogram, and finally cis score algorithm to analyze the abundance of immune-related cells in different subtypes. We used Weka software to screen for prognosis-related marker genes and finally validated the expression of the selected genes in clinical cancer patient tissues.

RESULTS

We identified that two GC metabolism-related signatures were strongly associated with OS and the levels of immune cell infiltration. Moreover, a survival prediction model for GC was established based on six GC metabolism-related genes. Time-dependent ROC analysis showed good stability of the risk prediction scoring model. The model was successfully validated in an independent ACRG cohort, and the expression trends of key genes were also verified in the GC tissues of patients. DLX1, LTBP2, FGFR1 and MMP2 were highly expressed in the cluster with poorer prognosis while SLC13A2 and SLCO1B3 were highly expressed in the cluster with better prognosis.

CONCLUSIONS

We identified a risk predictive score model based on six metabolism-related genes related to survival, which may serve as prognostic indicators and potential therapeutic targets for GC.

3D printed tissue models: From hydrogels to biomedical applications

The development of new advanced constructs resembling structural and functional properties of human organs and tissues requires a deep knowledge of the morphological and biochemical properties of the extracellular matrices (ECM), and the capacity to reproduce them. Manufacturing technologies like 3D printing and bioprinting represent valuable tools for this purpose. This review will describe how morphological and biochemical properties of ECM change in different tissues, organs, healthy and pathological states, and how ECM mimics with the required properties can be generated by 3D printing and bioprinting. The review describes and classifies the polymeric materials of natural and synthetic origin exploited to generate the hydrogels acting as "inks" in the 3D printing process, with particular emphasis on their functionalization allowing crosslinking and conjugation with signaling molecules to develop bio-responsive and bio-instructive ECM mimics.

Bioinspired human stomach-on-a-chip with in vivo like function and architecture

The lack of biomimetic in vitro models capable of reproducing the complex architecture and the dynamic environment of the gastric mucosa, delay the development of diagnostic and therapeutic tools. Recent advances in microengineering made possible the fabrication of bioinspired microdevices capable of replicating the physiological properties of an organ, inside a microfluidics chip. Herein, a bioinspired stomach-on-a-chip (SoC) device is described, supporting peristalsis-like motion and reconstituting organ-level epithelial architecture and function. The device simulates the upper epithelial interface, representing the three innermost layers of the gastric mucosa, namely the epithelial barrier, the basement membrane and the lamina propria. The dynamic environment imparted by mechanical actuation of the flexible on-chip cell culture substrate, was the main driver in the development of epithelial polarization and differentiation traits characteristic of the native gastric mucosa, and allowed partial recapitulation of gastric barrier function. These traits were not affected by the addition of a mesenchymal population to the system, which was able to remodel the surrounding extracellular matrix, nor by the potential epithelial-mesenchymal cross-talk. The engineered platform highlights the importance of addressing the mechanical microenvironment of the native organ, to potentiate an organ-level response of the artificial tissue. The proposed SoC represents an appealing tool in personalized medicine, with bio-relevance for the study of gastric diseases and an alternative to current animal models.

Comprehensive Profiling of Early Neoplastic Gastric Microenvironment Modifications and Biodynamics in Impaired BMP-Signaling FoxL1+-Telocytes

FoxL1⁺telocytes (TC^FoxL1+) are novel gastrointestinal subepithelial cells that form a communication axis between the mesenchyme and epithelium. TC^FoxL1+ are strategically positioned to be key contributors to the microenvironment through production and secretion of growth factors and extracellular matrix (ECM) proteins. In recent years, the alteration of the bone morphogenetic protein (BMP) signaling in TC^FoxL1+ was demonstrated to trigger a toxic microenvironment with ECM remodeling that leads to the development of pre-neoplastic gastric lesions. However, a comprehensive analysis of variations in the ECM composition and its associated proteins in gastric neoplasia linked to TC^FoxL1+ dysregulation has never been performed. This study provides a better understanding of how TC^FoxL1+ defective BMP signaling participates in the gastric pre-neoplastic microenvironment. Using a proteomic approach, we determined the changes in the complete matrisome of BmpR1a^△FoxL1+ and control mice, both in total antrum as well as in isolated mesenchyme-enriched antrum fractions. Comparative proteomic analysis revealed that the deconstruction of the gastric antrum led to a more comprehensive analysis of the ECM fraction of gastric tissues microenvironment. These results show that TC^FoxL1+ are key members of the mesenchymal cell population and actively participate in the establishment of the matrisomic fraction of the microenvironment, thus influencing epithelial cell behavior.

Activation of Laminin γ2 by Helicobacter pylori Promotes Invasion and Survival of Gastric Cancer Cells With E-Cadherin Defects

BACKGROUND

Helicobacter pylori infection induces cellular phenotypes relevant for cancer progression, namely cell motility and invasion. We hypothesized that the extracellular matrix (ECM) could be involved in these deleterious effects.

METHODS

Microarrays were used to uncover ECM interactors in cells infected with H. pylori. LAMC2, encoding laminin γ2, was selected as a candidate gene and its expression was assessed in vitro and in vivo. The role of LAMC2 was investigated by small interference RNA (siRNA) combined with a set of functional assays. Laminin γ2 and E-cadherin expression patterns were evaluated in gastric cancer cases.

RESULTS

Laminin γ2 was found significantly overexpressed in gastric cancer cells infected with H. pylori. This finding was validated in vitro by infection with clinical isolates and in vivo by using gastric biopsies of infected and noninfected individuals. We showed that laminin γ2 overexpression is dependent on the bacterial type IV secretion system and on the CagA. Functionally, laminin γ2 promotes cell invasion and resistance to apoptosis, through modulation of Src, JNK, and AKT activity. These effects were abrogated in cells with functional E-cadherin.

CONCLUSIONS

These data highlight laminin γ2 and its downstream effectors as potential therapeutic targets, and the value of H. pylori eradication to delay gastric cancer onset and progression.

Comprehensive analysis to identify pseudogenes/lncRNAs-hsa-miR-200b-3p-COL5A2 network as a prognostic biomarker in gastric cancer

OBJECTIVE

Gastric cancer is one of the most common and deadly types of cancer. The molecular mechanism of gastric cancer progression remains unclear.

MATERIALS AND METHODS

Four hub genes were identified through GEO and TCGA database screening and analysis. Prognostic analysis revealed that COL5A2 was the most likely to affect the prognosis of gastric cancer among the four hub genes. The relationships between COL5A2 and clinical variables and immune cell infiltration were analyzed. Then, COL5A2 was analyzed for single-gene differences and related functional enrichment. Using the starBase database for prediction and analysis, miRNAs and pseudogenes/lncRNAs that might combine with COL5A2 were identified; thus, the ceRNA network was constructed. Finally, the network was verified by Cox analysis and qPCR, and a nomogram was constructed.

RESULTS

First, we found that COL5A2, COL12A1, BGN and THBS2 were highly expressed in gastric cancer. COL5A2 had statistical significance in overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) analysis. Immune infiltration analysis suggested that COL5A2 might influence the changes in the tumor immune microenvironment. The StarBase database was used to predict that 3 pseudogenes and 7 lncRNAs might inhibit the hsa-miR-200b-3p-COL5A2 axis in gastric cancer. The pseudogenes/lncRNA-hsa-miR-200b-3p-COL5A2 ceRNA network was identified and verified using Cox regression analysis and PCR. Finally, we constructed a nomogram.

CONCLUSIONS

We elucidated the regulatory role of the pseudogenes/lncRNA-hsa-miR-200b-3p-COL5A2 network in gastric cancer progression and constructed a nomogram. These studies may provide effective treatments and potential prognostic biomarkers for gastric cancer.

The Regulatory Network of Gastric Cancer Pathogenesis and Its Potential Therapeutic Active Ingredients of Traditional Chinese Medicine Based on Bioinformatics, Molecular Docking, and Molecular Dynamics Simulation

Objective. This study aims to investigate the functional gene network in gastric carcinogenesis by using bioinformatics; besides, the diagnostic utility of key genes and potential active ingredients of traditional Chinese medicine (TCM) for treatment in gastric cancer have been explored. Methods. The Cancer Genome Atlas and Gene Expression Omnibus databases have been applied to analyze the differentially expressed genes (DEGs) between gastric cancer and normal gastric tissues. Then, the DEGs underwent Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the Metascape database. The STRING database and the Cytoscape software were utilized for the protein-protein interaction network of DEGs and hub genes screening. Furthermore, survival and expression analyses of hub genes were conducted using Gene Expression Profiling Interactive Analysis and Human Protein Atlas databases. By using the Comparative Toxicogenomics Database, the hub genes interconnected with active ingredients of TCM were analyzed to provide potential information for the treatment of gastric cancer. After the molecular docking of the active ingredients of TCM to specific hub gene receptor proteins, the molecular dynamics simulation GROMACS was applied to validate the conformation of the strongest binding ability in the molecular docking. Results. A total of 291 significant DEGs were found, from which 12 hub genes were screened out. Among these hub genes, the expressions of five hub genes including COL1A1, COL5A2, MMP12, SERPINE1, and VCAN were significantly correlated with the overall survival. Furthermore, four potential therapeutic active ingredients of TCM were acquired, including quercetin, resveratrol, emodin, and schizandrin B. In addition, the molecular docking results exhibited that the active ingredients of TCM formed stable binding with the hub gene targets. SERPINE1 (3UT3)-Emodin and COL1A1 (7DV6)-Quercetin were subjected to molecular dynamics simulations as conformations of continuing research significance, and both were found to be stably bound as a result of the interaction of van der Waals potentials, electrostatic, and hydrogen bonding. Conclusion. Our findings may provide novel insights and references for the screening of biomarkers, the prognostic evaluation, and the identification of potential active ingredients of TCM for gastric cancer treatment.

Tumor microenvironment-mediated immune tolerance in development and treatment of gastric cancer

Tumor microenvironment is the general term for all non-cancer components and their metabolites in tumor tissue. These components include the extracellular matrix, fibroblasts, immune cells, and endothelial cells. In the early stages of tumors, the tumor microenvironment has a tumor suppressor function. As the tumor progresses, tumor immune tolerance is induced under the action of various factors, such that the tumor suppressor microenvironment is continuously transformed into a tumor-promoting microenvironment, which promotes tumor immune escape. Eventually, tumor cells manifest the characteristics of malignant proliferation, invasion, metastasis, and drug resistance. In recent years, stress effects of the extracellular matrix, metabolic and phenotypic changes of innate immune cells (such as neutrophils, mast cells), and adaptive immune cells in the tumor microenvironment have been revealed to mediate the emerging mechanisms of immune tolerance, providing us with a large number of emerging therapeutic targets to relieve tumor immune tolerance. Gastric cancer is one of the most common digestive tract malignancies worldwide, whose mortality rate remains high. According to latest guidelines, the first-line chemotherapy of advanced gastric cancer is the traditional platinum and fluorouracil therapy, while immunotherapy for gastric cancer is extremely limited, including only Human epidermal growth factor receptor 2 (HER-2) and programmed death ligand 1 (PD-L1) targeted drugs, whose benefits are limited. Clinical experiments confirmed that cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), vascular endothelial growth factor receptor (VEGFR) and other targeted drugs alone or in combination with other drugs have limited efficacy in patients with advanced gastric cancer, far less than in lung cancer, colon cancer, and other tumors. The failure of immunotherapy is mainly related to the induction of immune tolerance in the tumor microenvironment of gastric cancer. Therefore, solving the immune tolerance of tumors is key to the success of gastric cancer immunotherapy. In this study, we summarize the latest mechanisms of various components of the tumor microenvironment in gastric cancer for inducing immune tolerance and promoting the formation of the malignant phenotype of gastric cancer, as well as the research progress of targeting the tumor microenvironment to overcome immune tolerance in the treatment of gastric cancer.

Comprehensive characterization of extracellular matrix-related genes in PAAD identified a novel prognostic panel related to clinical outcomes and immune microenvironment: A silico analysis with in vivo and vitro validation

The extracellular matrix (ECM) is a vital component of the tumor microenvironment, which interplays with stromal and tumor cells to stimulate the capacity of cancer cells to proliferate, migrate, invade, and undergo angiogenesis. Nevertheless, the crucial functions of ECM-related genes (ECMGs) in pancreatic adenocarcinoma (PAAD) have not been systematically evaluated. Hence, a comprehensive evaluation of the ECMGs is required in pan-cancer, especially in PAAD. First, a pan-cancer overview of ECMGs was explored through the integration of expression profiles, prognostic values, mutation information, methylation levels, and pathway-regulation relationships. Seven ECMGs (i.e. LAMB3, LAMA3, ITGB6, ITGB4, ITGA2, LAMC2, and COL11A1) were identified to be hub genes of PAAD, which were obviously up-regulated in PAAD and considerably linked to tumor stage as well as prognosis. Subsequently, patients with PAAD were divided into 3 clusters premised on ECMG expression and ECM scores. Cluster 2 was the subtype with the best prognosis accompanied by the lowest ECM scores, further verifying ECM’s significant contribution to the pathophysiological processes of PAAD. Significant differences were observed for oncogene and tumor suppressor gene expression, immune microenvironment, and chemotherapy sensitivity across three ECM subtypes. After applying a variety of bioinformatics methods, a novel and robust ECM-associated mRNA-lncRNA-based prognostic panel (ECM-APP) was developed and validated for accurately predicting clinical outcomes of patients with PAAD. Patients with PAAD were randomly categorized into the train, internal validation, and external validation cohorts; meanwhile, each patient was allocated into high-risk (unfavorable prognosis) and low-risk (favorable prognosis) populations premised on the expression traits of ECM-related mRNAs and lncRNAs. The discrepancy in the tumor mutation burden and immune microenvironment might be responsible for the difference in prognoses across the high-risk and low-risk populations. Overall, our findings identified and validated seven ECMGs remarkably linked to the onset and progression of PAAD. ECM-based molecular classification and prognostic panel aid in the prognostic assessment and personalized intervention of patients with PAAD.

Identification of key genes with prognostic value in gastric cancer by bioinformatics analysis

Background: Gastric cancer (GC) is a digestive system tumor with high morbidity and mortality. It is urgently required to identify genes to elucidate the underlying molecular mechanisms. The aim of this study is to identify the key genes which may affect the prognosis of GC patients and be a therapeutic strategy for GC patients by bioinformatic analysis.

Methods: The significant prognostic differentially expressed genes (DEGs) were screened out from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. The protein–protein interaction (PPI) network was established by STRING and screening key genes by MCODE and CytoNCA plug-ins in Cytoscape. Functional enrichment analysis, construction of a prognostic risk model, and nomograms verify key genes as potential therapeutic targets.

Results: In total, 997 genes and 805 genes were related to the prognosis of GC in the GSE84437 and TCGA datasets, respectively. We define the 128 genes shared by the two datasets as prognostic DEGs (P-DEGs). Then, the first four genes (MYLK, MYL9, LUM, and CAV1) with great node importance in the PPI network of P-DEGs were identified as key genes. Independent prognostic risk analysis found that patients with high key gene expression had a poor prognosis, excluding their age, gender, and TNM stage. GO and KEGG enrichment analyses showed that key genes may exert influence through the PI3K-Akt pathway, in which extracellular matrix organization and focal adhesion may play important roles in key genes influencing the prognosis of GC patients.

Conclusion: We found that MYLK, MYL9, LUM, and CAV1 are potential and reliable prognostic key genes that affect the invasion and migration of gastric cancer.

Regulatory roles of fibronectin and integrin α5 in reorganization of the actin cytoskeleton and completion of adipogenesis

Cellular differentiation is characterized by changes in cell morphology that are largely determined by actin dynamics. We previously showed that depolymerization of the actin cytoskeleton triggers the differentiation of preadipocytes into mature adipocytes as a result of inhibition of the transcriptional coactivator activity of megakaryoblastic leukemia 1 (MKL1). The extracellular matrix (ECM) influences cell morphology via interaction with integrins, and reorganization of the ECM is associated with cell differentiation. Here we show that interaction between actin dynamics and ECM rearrangement plays a key role in adipocyte differentiation. We found that depolymerization of the actin cytoskeleton precedes disruption and degradation of fibrillar fibronectin (FN) structures at the cell surface after the induction of adipogenesis in cultured preadipocytes. A FN matrix suppressed both reorganization of the actin cytoskeleton into the pattern characteristic of adipocytes and terminal adipocyte differentiation, and these inhibitory effects were overcome by knockdown of integrin α5 (ITGα5). Peroxisome proliferator–activated receptor γ was required for down-regulation of FN during adipocyte differentiation, and MKL1 was necessary for the expression of ITGα5. Our findings suggest that cell-autonomous down-regulation of FN-ITGα5 interaction contributes to reorganization of the actin cytoskeleton and completion of adipocyte differentiation.

Increased ANXA5 expression in stomach adenocarcinoma infers a poor prognosis and high level of immune infiltration

BACKGROUND: The prognostic role of annexin A5 (ANXA5) in stomach adenocarcinoma (STAD) has not been studied, and its relationship with immune infiltration is still unclear. OBJECTIVE: This investigation aimed at exploring the role of ANXA5 in STAD using an integrated bioinformatics analysis. METHODS: The expression of ANXA5 in STAD and the correlations between the effect of ANXA5 and survival of STAD patients were investigated using database. The clusterProfiler package in R software was used to perform enrichment analysis on the top 100 co-expressed genes of ANXA5 from the COXPRESdb online database. Correlations between ANXA5 and immune cell infiltrates were analyzed using the TIMER database. RESULTS: In STAD, ANXA5 expression was significantly upregulated and increased ANXA5 expression was significantly correlated with poor overall survival (P< 0.05). In multivariate analysis, upregulated ANXA5 expression was an independent predictive factors of poor prognosis (P< 0.05). The co-expressed genes were involved in extracellular matrix (ECM)-related processes. In STAD, ANXA5 expression was significantly correlated with various infiltrating immune cells (P< 0.05). CONCLUSIONS: Together with our findings, ANXA5 could serve as a potential biomarker to assess prognosis and immune infiltration level in STAD.

A phase 1b study of andecaliximab in combination with S-1 plus platinum in Japanese patients with gastric adenocarcinoma

Andecaliximab (ADX) is a monoclonal antibody that inhibits matrix metalloproteinase 9 (MMP9), an extracellular enzyme involved in matrix remodeling, tumor growth, and metastasis. In preclinical models, MMP9 inhibitors have been shown to enhance the cytotoxic effects of chemotherapeutic agents and to suppress distant metastasis. In this phase Ib, multicenter study, the safety and efficacy of ADX combined with S-1 plus cisplatin (SP) or S-1 plus oxaliplatin (SOX) as a first-line treatment were evaluated in Japanese patients with advanced gastric or gastroesophageal junction (GEJ) adenocarcinoma. ADX was administrated at a dose of 800 mg every 2 weeks for the SP cohort and 1200 mg every three weeks for the SOX cohort. As of December 2019, 16 patients were enrolled (six patients in the SP cohort and 10 patients in the SOX cohort). Peripheral sensory neuropathy (69%), anorexia (63%), nausea (56%), and decreased neutrophil counts (44%) were the most common adverse events (AEs). The grade 3 or higher AEs attributed to ADX were stomatitis and abnormal hepatic function (each one patient) in the SP cohort and decreased neutrophil counts (two patients) in the SOX cohort. The objective response rate in 11 patients with measurable target lesions was 73% (8/11), based on the investigator’s evaluation. Median progression-free survival was11.9 months (90% confidence interval, 5.6–16.6), and median overall survival was not reached. In conclusion, ADX combined with S-1 plus platinum demonstrated a manageable safety profile and promising clinical activity in the first-line treatment of patients with advanced gastric or GEJ adenocarcinoma.

Clinical Trial Registration information: ClinicalTrials.gov Identifier: NCT02862535 (11/08/2016) and protocol ID: GS-US-296-1884.

The HIF-1α as a Potent Inducer of the Hallmarks in Gastric Cancer

Simple Summary

Gastric cancer is one of the most aggressive tumors in the clinic that is resistant to chemotherapy. Gastric tumors are rich in hypoxic niches, and high expression of hypoxia-inducible factor-1α is associated with poor prognosis. Therefore, strategies that target hypoxia-inducible factor-1α signaling may be highly effective in gastric cancer treatment. However, the precise mechanisms by which hypoxia-inducible factor-1α induces tumor hallmarks in gastric cancer are yet unrevealed. Here, we review the role of hypoxia-inducible factor-1α as a potent inducer of the cancer hallmarks in gastric cancer to provide a broad perspective and reveal missing links investigating which may offer new strategies to target hypoxia-inducible factor-1α signaling in gastric cancer.

Abstract

Hypoxia is the principal architect of the topographic heterogeneity in tumors. Hypoxia-inducible factor-1α (HIF-1α) reinforces all hallmarks of cancer and donates cancer cells with more aggressive characteristics at hypoxic niches. HIF-1α potently induces sustained growth factor signaling, angiogenesis, epithelial–mesenchymal transition, and replicative immortality. Hypoxia leads to the selection of cancer cells that evade growth suppressors or apoptotic triggers and deregulates cellular energetics. HIF-1α is also associated with genetic instability, tumor-promoting inflammation, and escape from immunity. Therefore, HIF-1α may be an important therapeutic target in cancer. Despite that, the drug market lacks safe and efficacious anti-HIF-1α molecules, raising the quest for fully unveiling the complex interactome of HIF-1α in cancer to discover more effective strategies. The knowledge gap is even wider in gastric cancer, where the number of studies on hypoxia is relatively low compared to other well-dissected cancers. A comprehensive review of the molecular mechanisms by which HIF-1α induces gastric cancer hallmarks could provide a broad perspective to the investigators and reveal missing links to explore in future studies. Thus, here we review the impact of HIF-1α on the cancer hallmarks with a specific focus on gastric cancer.

Differential Impacts on Tensional Homeostasis of Gastric Cancer Cells Due to Distinct Domain Variants of E-Cadherin

In epithelia, breakdown of tensional homeostasis is closely associated with E-cadherin dysfunction and disruption of tissue function and integrity. In this study, we investigated the effect of E-cadherin mutations affecting distinct protein domains on tensional homeostasis of gastric cancer cells. We used micropattern traction microscopy to measure temporal fluctuations of cellular traction forces in AGS cells transfected with the wild-type E-cadherin or with variants affecting the extracellular, the juxtamembrane, and the intracellular domains of the protein. We focused on the dynamic aspect of tensional homeostasis, namely the ability of cells to maintain a consistent level of tension, with low temporal variability around a set point. Cells were cultured on hydrogels micropatterned with different extracellular matrix (ECM) proteins to test whether the ECM adhesion impacts cell behavior. A combination of Fibronectin and Vitronectin was used as a substrate that promotes the adhesive ability of E-cadherin dysfunctional cells, whereas Collagen VI was used to test an unfavorable ECM condition. Our results showed that mutations affecting distinct E-cadherin domains influenced differently cell tensional homeostasis, and pinpointed the juxtamembrane and intracellular regions of E-cadherin as the key players in this process. Furthermore, Fibronectin and Vitronectin might modulate cancer cell behavior towards tensional homeostasis.

Deep Learning-Based Protein Features Predict Overall Survival and Chemotherapy Benefit in Gastric Cancer

Gastric cancer (GC) is one of the most common malignant tumors with a high mortality rate worldwide and lacks effective methods for prognosis prediction. Postoperative adjuvant chemotherapy is the first-line treatment for advanced gastric cancer, but only a subgroup of patients benefits from it. Here, we used 833 formalin-fixed, paraffin-embedded resected tumor samples from patients with TNM stage II/III GC and established a proteomic subtyping workflow using 100 deep-learned features. Two proteomic subtypes (S-I and S-II) with overall survival differences were identified. S-I has a better survival rate and is sensitive to chemotherapy. Patients in the S-I who received adjuvant chemotherapy had a significant improvement in the 5-year overall survival rate compared with patients who received surgery alone (65.3% vs 52.6%; log-rank P = 0.014), but no improvement was observed in the S-II (54% vs 51%; log-rank P = 0.96). These results were verified in an independent validation set. Furthermore, we also evaluated the superiority and scalability of the deep learning-based workflow in cancer molecular subtyping, exhibiting its great utility and potential in prognosis prediction and therapeutic decision-making.

Biomarkers of Cancer Stem Cells for Experimental Research and Clinical Application

The use of biomarkers in cancer diagnosis, therapy, and prognosis has been highly effective over several decades. Studies of biomarkers in cancer patients pre- and post-treatment and during cancer progression have helped identify cancer stem cells (CSCs) and their related microenvironments. These analyses are critical for the therapeutic application of drugs and the efficient targeting and prevention of cancer progression, as well as the investigation of the mechanism of the cancer development. Biomarkers that characterize CSCs have thus been identified and correlated to diagnosis, therapy, and prognosis. However, CSCs demonstrate elevated levels of plasticity, which alters their functional phenotype and appearance by interacting with their microenvironments, in response to chemotherapy and radiotherapeutics. In turn, these changes induce different metabolic adaptations of CSCs. This article provides a review of the most frequently used CSCs and stem cell markers.

Long Noncoding RNA: Shining Stars in the Immune Microenvironment of Gastric Cancer

Gastric cancer (GC) is a kind of malignant tumor disease that poses a serious threat to human health. The GC immune microenvironment (TIME) is a very complex tumor microenvironment, mainly composed of infiltrating immune cells, extracellular matrix, tumor-associated fibroblasts, cytokines and chemokines, all of which play a key role in inhibiting or promoting tumor development and affecting tumor prognosis. Long non-coding RNA (lncRNA) is a non-coding RNA with a transcript length is more than 200 nucleotides. LncRNAs are expressed in various infiltrating immune cells in TIME and are involved in innate and adaptive immune regulation, which is closely related to immune escape, migration and invasion of tumor cells. LncRNA-targeted therapeutic effect prediction for GC immunotherapy provides a new approach for clinical research on the disease.

Prognostic and Diagnostic Values of Semaphorin 5B and Its Correlation With Tumor-Infiltrating Immune Cells in Kidney Renal Clear-Cell Carcinoma

Background: Semaphorin 5B (SEMA5B) has been described to be involved in the development and progression of cancer. However, the potential diagnostic and prognosis roles and its correlation with tumor-infiltrating immune cells in KIRC have not been clearly reported yet. Methods: The mRNA level of SEMA5B was analyzed via the TCGA and GTEx database as well as the CCLE dataset and verified by GSE53757 and GSE40435 datasets. Meanwhile, the protein level of SEMA5B was analyzed by CPTAC and validated by HPA. The diagnostic value of SEMA5B was analyzed according to the TCGA database and validated by GSE53757, GSE46699, and GSE11024 + GSE46699 datasets. Then, the survival analysis was conducted using GEPIA2. R software (v3.6.3) was applied to investigate the relevance between SEMA5B and immune checkpoints and m6A RNA methylation regulator expression. The correlation between SEMA5B and MMRs and DNMT expression and tumor-infiltrating immune cells was explored via TIMER2. Co-expressed genes of SEMA5B were assessed by cBioPortal, and enrichment analysis was conducted by Metascape. The methylation analysis was conducted with MEXPRESS and MethSurv online tools. Gene set enrichment analysis (GSEA) was applied to annotate the biological function of SEMA5B. Results: SEMA5B was significantly upregulated at both the mRNA and protein levels in KIRC. Further analysis demonstrated that the mRNA expression of SEMA5B was significantly correlated with gender, age, T stage, pathologic stage, and histologic grade. High levels of SEMA5B were found to be a favorable prognostic factor and novel diagnostic biomarker for KIRC. SEMA5B expression was shown to be significantly associated with the abundance of immune cells in KIRC. Also, SEMA5B expression was significantly correlated with the abundance of MMR genes, DNMTs, and m6A regulators in KIRC. Enrichment analysis indicated that the co-expressed genes may involve in crosslinking in the extracellular matrix (ECM). GSEA disclosed that SYSTEMIC_LUPUS_ERYTHEMATOSUS and NABA_ECM_REGULATORS were prominently enriched in the SEMA5B low-expression phenotype. Finally, the methylation analysis demonstrated a correlation between hypermethylation of the SEMA5B gene and a poor prognosis in KIRC. Conclusion: Increased SEMA5B expression correlated with immune cell infiltration, which can be served as a favorable prognostic factor and a novel diagnostic biomarker for KIRC.

Tissue extracellular matrix hydrogels as alternatives to Matrigel for culturing gastrointestinal organoids

Matrigel, a mouse tumor extracellular matrix protein mixture, is an indispensable component of most organoid tissue culture. However, it has limited the utility of organoids for drug development and regenerative medicine due to its tumor-derived origin, batch-to-batch variation, high cost, and safety issues. Here, we demonstrate that gastrointestinal tissue-derived extracellular matrix hydrogels are suitable substitutes for Matrigel in gastrointestinal organoid culture. We found that the development and function of gastric or intestinal organoids grown in tissue extracellular matrix hydrogels are comparable or often superior to those in Matrigel. In addition, gastrointestinal extracellular matrix hydrogels enabled long-term subculture and transplantation of organoids by providing gastrointestinal tissue-mimetic microenvironments. Tissue-specific and age-related extracellular matrix profiles that affect organoid development were also elucidated through proteomic analysis. Together, our results suggest that extracellular matrix hydrogels derived from decellularized gastrointestinal tissues are effective alternatives to the current gold standard, Matrigel, and produce organoids suitable for gastrointestinal disease modeling, drug development, and tissue regeneration.

Proteomic Identification of a Gastric Tumor ECM Signature Associated With Cancer Progression

The extracellular matrix (ECM) plays an undisputable role in tissue homeostasis and its deregulation leads to altered mechanical and biochemical cues that impact cancer development and progression. Herein, we undertook a novel approach to address the role of gastric ECM in tumorigenesis, which remained largely unexplored. By combining decellularization techniques with a high-throughput quantitative proteomics approach, we have performed an extensive characterization of human gastric mucosa, uncovering its composition and distribution among tumor, normal adjacent and normal distant mucosa. Our results revealed a common ECM signature composed of 142 proteins and indicated that gastric carcinogenesis encompasses ECM remodeling through alterations in the abundance of 24 components, mainly basement membrane proteins. Indeed, we could only identify one de novo tumor-specific protein, the collagen alpha-1(X) chain (COL10A1). Functional analysis of the data demonstrated that gastric ECM remodeling favors tumor progression by activating ECM receptors and cellular processes involved in angiogenesis and cell-extrinsic metabolic regulation. By analyzing mRNA expression in an independent GC cohort available at the TGCA, we validated the expression profile of 12 differentially expressed ECM proteins. Importantly, the expression of COL1A2, LOX and LTBP2 significantly correlated with high tumor stage, with LOX and LTBP2 further impacting patient overall survival. These findings contribute for a better understanding of GC biology and highlight the role of core ECM components in gastric carcinogenesis and their clinical relevance as biomarkers of disease prognosis.

Systematic Analysis of Expression and Prognostic Values of Lysyl Oxidase Family in Gastric Cancer

Background: Gastric cancer (GC) remains the fifth most commonly diagnosed malignancy worldwide, with a poor prognosis. The lysyl oxidase (LOX) family, a type of secreted copper-dependent amine oxidases, is comprised of LOX and four LOX-like (LOXL) 1–4 isoforms and has been reported to be dysregulated in a number of different type cancers. However, the diverse expression patterns and prognostic values of LOX family in GC have yet to be systematically analyzed.

Methods: ONCOMINE, GEPIA, UALCAN, Kaplan–Meier Plotter, LOGpc, cBioPortal, GeneMANIA and Metascape databases were utilized in this study to analyze the expression, prognostic values, mutations and functional networks of LOX family in GC.

Results: The mRNA expression levels of LOX, LOXL1 and LOXL2 were significantly higher in GC, the expression level of LOXL3 was contrary in different databases, while the expression level of LOXL4 made no difference; the expression levels of LOX, LOXL1 and LOXL3 were higher in stages 2–4 than that of normal tissues and stage 1, while the mRNA level of LOXL2 in stage 1–4 was higher than normal tissues; patients with high expression of LOX and LOXL 2-4 had poor OS; the genes correlated with LOX and LOXL2 were enriched in extracellular matrix organization, vasculature development and skeletal system development.

Conclusion: Our results indicated that the LOX family, especially LOX and LOXL2, might play an important role in GC oncogenesis, and they may become biomarkers for predicting tumor prognosis and potential targets for tumor therapy.

Forecasting Gastric Cancer Diagnosis, Prognosis, and Drug Repurposing with Novel Gene Expression Signatures

Gastric cancer (GC) is a prevalent disease worldwide with high mortality and poor treatment success. Early diagnosis of GC and forecasting of its prognosis with the use of biomarkers are directly relevant to achieve both personalized/precision medicine and innovation in cancer therapeutics. Gene expression signatures offer one of the promising avenues of research in this regard, as well as guiding drug repurposing analyses in cancers. Using publicly accessible gene expression datasets from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA), we report here original findings on co-expressed gene modules that are differentially expressed between 133 GC samples and 46 normal tissues, and thus hold potential for novel diagnostic candidates for GC. Furthermore, we found two co-expressed gene modules were significantly associated with poor survival outcomes revealed by survival analysis of the RNA-Seq TCGA datasets. We identified STAT6 (signal transducer and activator of transcription 6) as a key regulator of the identified gene modules. Finally, potential therapeutic drugs that may target and reverse the expression of the identified altered gene modules examined for drug repurposing analyses and the unraveled compounds were further investigated in the literature by the text mining method. Accordingly, we found several repurposed drug candidates, including Trichostatin A, Vorinostat, Parthenolide, Panobinostat, Brefeldin A, Belinostat, and Danusertib. Through text mining analysis and literature search validation, Belinostat and Danusertib were suggested as possible novel drug candidates for GC treatment. These findings collectively inform multiple aspects of GC medical management, including its precision diagnosis, forecasting of possible outcomes, and drug repurposing for innovation in GC medicines in the future.

Helicobacter pylori and gastric cancer: a lysosomal protease perspective

The intimate involvement of pathogens with the heightened risk for developing certain cancers is an area of research that has captured a great deal of attention over the last 10 years. One firmly established paradigm that highlights this aspect of disease progression is in the instance of Helicobacter pylori infection and the contribution it makes in elevating the risk for developing gastric cancer. Whilst the molecular mechanisms that pinpoint the contribution that this microorganism inflicts towards host cells during gastric cancer initiation have come into greater focus, another picture that has also emerged is one that implicates the host's immune system, and the chronic inflammation that can arise therefrom, as being a central contributory factor in disease progression. Consequently, when taken with the underlying role that the extracellular matrix plays in the development of most cancers, and how this dynamic can be modulated by proteases expressed from the tumor or inflammatory cells, a complex and detailed relationship shared between the individual cellular components and their surroundings is coming into focus. In this review article, we draw attention to the emerging role played by the cathepsin proteases in modulating the stage-specific progression of Helicobacter pylori-initiated gastric cancer and the underlying immune response, while highlighting the therapeutic significance of this dynamic and how it may be amenable for novel intervention strategies within a basic research or clinical setting.

Diabetes mellitus contribution to the remodeling of the tumor microenvironment in gastric cancer

Compelling pieces of evidence derived from both clinical and experimental research has demonstrated the crucial contribution of diabetes mellitus (DM) as a risk factor associated with increased cancer incidence and mortality in many human neoplasms, including gastric cancer (GC). DM is considered a systemic inflammatory disease and therefore, this inflammatory status may have profound effects on the tumor microenvironment (TME), particularly by driving many molecular mechanisms to generate a more aggressive TME. DM is an active driver in the modification of the behavior of many cell components of the TME as well as altering the mechanical properties of the extracellular matrix (ECM), leading to an increased ECM stiffening. Additionally, DM can alter many cellular signaling mechanisms and thus favoring tumor growth, invasion, and metastatic potential, as well as key elements in regulating cellular functions and cross-talks, such as the microRNAs network, the production, and cargo of exosomes, the metabolism of cell stroma and resistance to hypoxia. In the present review, we intend to highlight the mechanistic contributions of DM to the remodeling of TME in GC.

Development and Verification of an Immune-Based Gene Signature for Risk Stratification and Immunotherapeutic Efficacy Assessment in Gastric Cancer

Objective

Due to the molecular heterogeneity of gastric cancer, only minor patients respond to immunotherapeutic schemes. This study is aimed at developing an immune-based gene signature for risk stratification and immunotherapeutic efficacy assessment in gastric cancer.

Methods

An immune-based gene signature was developed in gastric cancer by LASSO method in the training set. The predictive performance was validated in the external datasets. KEGG pathways related to risk scores were assessed by GSEA. Based on multivariate Cox regression analysis, a nomogram was established. Sensitivity to chemotherapy drugs was evaluated between high- and low-risk samples. The relationships of risk scores with infiltration levels of immune cells, stromal scores, immune scores, immune cell subgroups, and overall response to anti-PD-L1 therapy were determined.

Results

Our results showed that high risk scores were indicative of undesirable survival outcomes both in the training set (p < 0.0001) and the validation set (p = 0.002). Moreover, this signature could independently predict patients' survival (HR: 2.656 (1.919-3.676) and p < 0.001). Subgroup analysis confirmed the sensitivity of this signature in predicting prognosis (all p < 0.05). Cancer-related pathways were primarily enriched in high-risk samples, such as MAPK and TGF-β pathways (p < 0.05). By incorporating stage and the risk score, we established a nomogram for predicting one-, three-, and five-year survival probability. Patients with high-risk scores were more sensitive to chemotherapy drugs (p < 0.05). There was heterogeneity in immune cells between high- and low-risk samples (p < 0.05). Samples with progressive disease exhibited the highest risk score, and those with complete response had the lowest risk score (p < 0.05).

Conclusion

This immune-based gene signature might be representative of a promising prognostic classifier for predicting risk stratification and immunotherapeutic efficacy in gastric cancer, assisting personalized therapy and follow-up plan.

Comprehensive Analysis of IGFBPs as Biomarkers in Gastric Cancer

OBJECTIVE

Gastric cancer is the fifth most common cancer worldwide and the third leading cause of cancer-related deaths. Insulin-like growth-factor-binding proteins (IGFBPs) were initially identified as passive inhibitors that combined with insulin-like growth factors (IGFs) in serum. However, more recent data have shown that they have different expression patterns and a variety of functions in the development and occurrence of cancers. Thus, their various roles in cancer still need to be elucidated. This study aimed to explore the IGFBPs and their prognostic value as markers in gastric cancer.

METHODS

Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier Plotter, cBioPortal, GeneMANIA, and TIMER were used to analyze the differential expression, prognostic value, genetic alteration, and association with immune cell infiltration of IGFPBs in gastric cancer.

RESULTS

Expression levels of IGFBP3, IGFBP4, and IGFBP7 were significantly elevated in gastric cancer tissues, whereas those of IGFBP1 were reduced in normal tissues. IGFBP1/5/7 expression was significantly associated with overall survival whereas IGFBP6/7 expression was significantly correlated with disease-free survival in gastric cancer patients. IGFBP3/5/6/7 were associated with clinical cancer stage. Gene ontology and Kyoto Encyclopedia of Genes and Genome analyses showed that IGFBP3/5/7 were mainly enriched in focal adhesion, extracellular matrix structural constituent, cell-substratist junction, extracellular structure, and matrix organization. Stomach adenocarcinoma (STAD) and gastric cancer had more IGFBP1-7 mutations than other tumor types. Hub gene analysis showed that TP53 and IGF2 expression was significantly elevated in STAD patients; PLG, PAPPA, AFP, and CYR61 were associated with overall survival rate; and IGFALS, PLG, IGF1, AHSG, and FN1 were associated with disease-free survival. Finally, IGFBP3-7 were all associated with cancer-associated fibroblast infiltration in STAD, colon adenocarcinoma, and rectal adenocarcinoma.

CONCLUSION

Our study provides a comprehensive analysis and selection of IGFBPs as prognostic biomarkers in STAD. This was the first bioinformatic analysis study to describe the involvement of IGFBPs, especially IGFBP7, in gastric cancer development through the extracellular matrix.

The role of extracellular matrix in tumour angiogenesis: the throne has NOx servants

The extracellular matrix (ECM) dynamics in tumour tissue are deregulated compared to the ECM in healthy tissue along with disorganized architecture and irregular behaviour of the residing cells. Nitric oxide (NO) as a pleiotropic molecule exerts different effects on the components of the ECM driving or inhibiting augmented angiogenesis and tumour progression and tumour cell proliferation and metastasis. These effects rely on the concentration of NO within the tumour tissue, the nature of the surrounding microenvironment and the sensitivity of resident cells to NO. In this review article, we summarize the recent findings on the correlation between the levels of NO and the ECM components towards the modulation of tumour angiogenesis in different types of cancers. These are discussed principally in the context of how NO modulates the expression of ECM proteins resulting in either the promotion or inhibition of tumour growth via tumour angiogenesis. Furthermore, the regulatory effects of individual ECM components on the expression of the NO synthase enzymes and NO production were reviewed. These findings support the current efforts for developing effective therapeutics for cancers.

Prognostication of Primary Tumor Location in Early-Stage Nodal Diffuse Large B-Cell Lymphoma: An Analysis of the SEER Database

The prognostic role of primary tumor location for clinical outcomes of patients with early-stage nodal diffuse large B-cell lymphoma (DLBCL) remains uncertain. We evaluated the relationship between primary tumor site and overall survival (OS) in 9738 early-stage nodal DLBCL patients from the Surveillance, Epidemiology, and End Results (SEER) database. The primary site of the tumors was characterized as supradiaphragm and subdiaphragm according to the definition of lymph node distribution in the Ann Arbor staging. The OS was significantly better for patients of the supradiaphragm group (n = 6038) compared to the ones from the subdiaphragm group (n = 3655) (hazard ratio (HR) 1.24; 95%CI: 1.16-1.33; P < 0.001), and it was preserved after propensity score matching (PSM) (HR 1.15; 95% CI: 1.07-1.24; P < 0.001). Gene enrichment analyses demonstrated that the subdiaphragm group has an upregulated extracellular matrix (ECM)-related signaling, which reportedly can promote growth, invasion, and metastasis of the cancer, and downregulated interferon response, which is considered to have anti-tumor function. Our results indicate the two tumor locations (supradiaphragm and subdiaphragm) presented different prognostic implications for the overall survival, suggesting that the tumor's location could serve as a prognostic biomarker for early-stage nodal DLBCL patients.

Weighted correlation network analysis identifies FN1, COL1A1 and SERPINE1 associated with the progression and prognosis of gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most deadliest tumours worldwide, and its prognosis remains poor.

OBJECTIVE

This study aims to identify and validate hub genes associated with the progression and prognosis of GC by constructing a weighted correlation network.

METHODS

The gene co-expression network was constructed by the WGCNA package based on GC samples and clinical data from the TCGA database. The module of interest that was highly related to clinical traits, including stage, grade and overall survival (OS), was identified. GO and KEGG pathway enrichment analyses were performed using the clusterprofiler package in R. Cytoscape software was used to identify the 10 hub genes. Differential expression and survival analyses were performed on GEPIA web resources and verified by four GEO datasets and our clinical gastric specimens. The receiver operating characteristic (ROC) curves of hub genes were plotted using the pROC package in R. The potential pathogenic mechanisms of hub genes were analysed using gene set enrichment analysis (GSEA) software.

RESULTS

A total of ten modules were detected, and the magenta module was identified as highly related to OS, stage and grade. Enrichment analysis of magenta module indicated that ECM-receptor interaction, focal adhesion, PI3K-Akt pathway, proteoglycans in cancer were significantly enriched. The PPI network identified ten hub genes, namely COL1A1, COL1A2, FN1, POSTN, THBS2, COL11A1, SPP1, MMP13, COMP, and SERPINE1. Three hub genes (FN1, COL1A1 and SERPINE1) were finally identified to be associated with carcinogenicity and poor prognosis of GC, and all were independent risk factors for GC. The area under the curve (AUC) values of FN1, COL1A1 and SERPINE1 for the prediction of GC were 0.702, 0.917 and 0.812, respectively. GSEA showed that three hub genes share 15 common upregulated biological pathways, including hypoxia, epithelial mesenchymal transition, angiogenesis, and apoptosis.

CONCLUSION

We identified FN1, COL1A1 and SERPINE1 as being associated with the progression and poor prognosis of GC.

The Extracellular Small Leucine-Rich Proteoglycan Biglycan Is a Key Player in Gastric Cancer Aggressiveness

Simple Summary

Approximately 80% of gastric cancer patients are diagnosed at advanced stages with an average five-year survival rate of less than 30%. Alterations of the extracellular matrix proteins have been largely demonstrated in all steps of the disease. Thus, studies for the identification of novel prognostic biomarkers and efficient therapeutic strategies are urgently needed. In this study, we report the oncogenic role of biglycan, an extracellular proteoglycan, in gastric carcinogenesis. Biglycan was able to modulate gastric cancer aggressive features as cell survival, migration, and angiogenesis. Additionally, high levels of biglycan expression correlates with tumorigenic gene signatures and they are associated with poor patient prognosis in advanced stages of the disease. These results point biglycan as a key player in gastric cancer aggressiveness and further studies should be done to investigate the therapeutic potential of biglycan to tackle gastric cancer progression.

Abstract

Biglycan (BGN gene), an extracellular proteoglycan, has been described to be associated with cancer aggressiveness. The purpose of this study was to clarify the clinical value of biglycan as a biomarker in multiple independent GC cohorts and determine the in vitro and in vivo role of biglycan in GC malignant features. We found that BGN is commonly over-expressed in all analyzed cohorts, being associated with disease relapse and poor prognosis in patients with advanced stages of disease. In vitro and in vivo experiments demonstrated that biglycan knock-out GC cells display major phenotypic changes with a lower cell survival, migration, and angiogenic potential when compared with biglycan expressing cells. Biglycan KO GC cells present increased levels of PARP1 and caspase-3 cleavage and a decreased expression of mesenchymal markers. Importantly, biglycan deficient GC cells that were supplemented with exogenous biglycan were able to restore biological features, such as survival, clonogenic and migratory capacities. Our in vitro and in vivo findings were validated in human GC samples, where BGN expression was associated with several oncogenic gene signatures that were associated with apoptosis, cell migration, invasion, and angiogenesis. This study provided new insights on biglycan role in GC that should be taken in consideration as a key cellular regulator with major impact in tumor progression and patients’ clinical outcome.

Comprehensive Analysis of Survival-Related lncRNAs, miRNAs, and mRNAs Forming a Competing Endogenous RNA Network in Gastric Cancer

To analyze and construct a survival-related endogenous RNA (ceRNA) network in gastric cancer (GC) with lymph node metastasis, we obtained expression profiles of long non-coding RNAs (lncRNAs), mRNAs, and microRNAs (miRNAs) in GC from The Cancer Genome Atlas database. The edgeR package was used to screen differentially expressed lncRNAs, mRNAs, and miRNAs between GC patients with lymphatic metastasis and those without lymphatic metastasis. Then, we used univariate Cox regression analysis to identify survival-related differentially expressed RNAs. In addition, we used multivariate Cox regression analysis to screen lncRNAs, miRNAs, and mRNAs for use in the prognostic prediction models. The results showed that 2,247 lncRNAs, 155 miRNAs, and 1,253 mRNAs were differentially expressed between the two patient groups. Using univariate Cox regression analysis, we found that 395 lncRNAs, eight miRNAs, and 180 mRNAs were significantly related to the survival time of GC patients. We next created a survival-related network consisting of 59 lncRNAs, seven miRNAs, and 36 mRNAs. In addition, we identified eight RNAs associated with prognosis by multivariate Cox regression analysis, comprising three lncRNAs (AC094104.2, AC010457.1, and AC091832.1), two miRNAs (miR-653-5p and miR-3923), and three mRNAs (C5orf46, EPHA8, and HPR); these were used to construct the prognostic prediction models, and their risk scores could be used to assess GC patients' prognosis. In conclusion, this study provides new insights into ceRNA networks in GC and the screening of prognostic biomarkers for GC.

A Weighted Gene Co-Expression Network Analysis-Derived Prognostic Model for Predicting Prognosis and Immune Infiltration in Gastric Cancer

Background

Gastric cancer (GC) is a major public health problem worldwide. In recent decades, the treatment of gastric cancer has improved greatly, but basic research and clinical application of gastric cancer remain challenges due to the high heterogeneity. Here, we provide new insights for identifying prognostic models of GC.

Methods

We obtained the gene expression profiles of GSE62254 containing 300 samples for training. GSE15459 and TCGA-STAD for validation, which contain 200 and 375 samples, respectively. Weighted gene co-expression network analysis (WGCNA) was used to identify gene modules. We performed Lasso regression and Cox regression analyses to identify the most significant five genes to develop a novel prognostic model. And we selected two representative genes within the model for immunohistochemistry staining with 105 GC specimens from our hospital to verify the prediction efficiency. Moreover, we estimated the correlation coefficient between our model and immune infiltration using the CIBERSORT algorithm. The data from GSE15459 and TCGA cohort validated the robustness and predictive accuracy of this prognostic model.

Results

Of the 12 gene modules identified, 1,198 green-yellow module genes were selected for further analysis. Multivariate Cox analysis was performed on genes from univariate Cox regression and Lasso regression analysis using the Cox proportional hazards regression model. Finally, we constructed a five gene prognostic model: Risk Score = [(-0.7547) * Expression (ARHGAP32)] + [(-0.8272) * Expression (KLF5)] + [1.09 * Expression (MAMLD1)] + [0.5174 * Expression (MATN3)] + [1.66 * Expression (NES)]. The prognosis of samples in the high-risk group was significantly poorer than that of samples in the low-risk group (p = 6.503e-11). The risk model was also regarded as an independent predictor of prognosis (HR, 1.678, p < 0.001). The observed correlation with immune cells suggested that this risk model could potentially predict immune infiltration.

Conclusion

This study identified a potential risk model for prognosis and immune infiltration prediction in GC using WGCNA and Cox regression analysis.