Comprehensive Analysis of IGFBPs as Biomarkers in Gastric Cancer

Engineered hydrogel reveals contribution of matrix mechanics to esophageal adenocarcinoma and identifies matrix-activated therapeutic targets

Increased extracellular matrix (ECM) stiffness has been implicated in esophageal adenocarcinoma (EAC) progression, metastasis, and resistance to therapy. However, the underlying protumorigenic pathways are yet to be defined. Additional work is needed to develop physiologically relevant in vitro 3D culture models that better recapitulate the human tumor microenvironment and can be used to dissect the contributions of matrix stiffness to EAC pathogenesis. Here, we describe a modular, tumor ECM-mimetic hydrogel platform with tunable mechanical properties, defined presentation of cell-adhesive ligands, and protease-dependent degradation that supports robust in vitro growth and expansion of patient-derived EAC 3D organoids (EAC PDOs). Hydrogel mechanical properties control EAC PDO formation, growth, proliferation, and activation of tumor-associated pathways that elicit stem-like properties in the cancer cells, as highlighted through in vitro and in vivo environments. We also demonstrate that the engineered hydrogel serves as a platform for identifying potential therapeutic targets to disrupt the contribution of protumorigenic matrix mechanics in EAC. Together, these studies show that an engineered PDO culture platform can be used to elucidate underlying matrix-mediated mechanisms of EAC and inform the development of therapeutics that target ECM stiffness in EAC.

Diabetes Mellitus and Gastric Cancer: Correlation and Potential Mechanisms

This review summarizes the correlation between diabetes mellitus (DM) and gastric cancer (GC) from the perspectives of epidemiology, drug use, and potential mechanisms. The association between DM and GC is inconclusive, and the positive direction of the association reported in most published meta-analyses suggests that DM may be an independent risk factor for GC. Many clinical investigations have shown that people with DM and GC who undergo gastrectomy may have better glycemic control. The potential link between DM and GC may involve the interaction of multiple common risk factors, such as obesity, hyperglycemia and hyperinsulinemia, H. pylori infection, and the use of metformin. Although in vitro and in vivo data support that H. pylori infection status and metformin can influence GC risk in DM patients, there are conflicting results. Patient survival outcomes are influenced by multiple factors, so further research is needed to identify the patients who may benefit.

Analysis of IGFBP7 expression characteristics in pan-cancer and its clinical relevance to stomach adenocarcinoma

Background

Insulin-like growth factor (IGF) binding proteins (IGFBPs) are involved in tumorigenesis and cancer progression. IGFBP7 has been shown to act as either a tumor suppressive gene or an oncogene in many tumors, including stomach adenocarcinoma (STAD). To provide a more systematic and comprehensive understanding of IGFBP7 gene, we performed an integrative pan-cancer analysis and explored further with the case of STAD.

Methods

We compared the expression data of IGFBP7 in various cancer and normal tissues obtained from The Cancer Genome Atlas (TCGA) database and the Genotype-Tissue Expression (GTEx) database. The TISIDB web portal was used to analyze the associations of IGFBP7 with cancer molecular subtypes and immune subtypes. We also analyzed the predictive ability and prognostic values of IGFBP7 in pan-cancer, as well as explored its targeted binding proteins and their biological functions. Additionally, we examined the relationship between IGFBP7 and the clinical characteristics of STAD, investigated the co-expression genes and biological functions of differentially expressed genes (DEGs), and validated the mRNA and protein expression levels of IGFBP7 using gastric cancer (GC) and adjacent normal tissues in a small self-case-control study.

Results

IGFBP7 was found to be overexpressed in STAD and downregulated in many other cancers. The mRNA and protein expression levels of IGFBP7 were also significantly higher in the collected GC tissues compared with adjacent tissues. Expression of IGFBP7 varied significantly across molecular subtypes of nine different cancer types and immune subtypes of eight types, with the highest expression observed in the genomically stable molecular subtype and C3 inflammatory immune subtype in STAD. IGFBP7 demonstrated an area under the curve (AUC) >0.7 for predicting 16 cancer types, and an AUC >0.9 for seven types. Patients in the higher IGFBP7 expression group showed a poorer prognosis for adrenal cortical carcinoma (ACC) and low-grade glioma (LGG), while demonstrating a more favorable prognosis for kidney renal clear cell carcinoma (KIRC). IGFBP7 expression in STAD was significantly associated with T stage, pathological stage, histologic grade, and Helicobacter pylori infection.

Conclusions

IGFBP7 showed promise as a biomarker for prediction and prognosis in pan-cancer. IGFBP7 was found to be overexpressed in STAD, and its expression was closely associated with the clinical characteristics of STAD.

[High expression of RAB7A is associated with poor prognosis of gastric cancer by promoting tumor invasion]

OBJECTIVE

To explore the expression level of Ras-related protein 7A (RAB7A) in gastric cancer and its prognostic implications.

METHODS

Based on data from public databases and a cohort of 104 patients undergoing radical gastrectomy for gastric cancer in our hospital, we analyzed RAB7A expression level in gastric cancer and adjacent tissues and its association with clinicopathological parameters and prognosis of the patients. Bioinformatic analysis was performed to predict the pathways of RAB7A to affect gastric cancer invasion. In gastric cancer MGC803 cells with lentivirus-mediated interference or overexpression of RAB7A, the changes in extracellular matrix (ECM) degradation and cell migration and invasion were analyzed using immunoblotting, wound healing assay and Transwell experiments.

RESULTS

The data from public cancer databases and clinical samples showed a significantly higher expression of RAB7A in gastric cancer tissues than in normal or adjacent tissues (P<0.01) with a close correlation with a poorer patient survival (P<0.01) and a positive correlation with serum carcinoembryonic antigen and carbohydrate antigen 19-9 levels (P<0.001). Univariate and multivariate Cox regression analyses suggested that a high RAB7A expression was an independent risk factor affecting the 5-year survival rate of gastric cancer patients (HR: 2.882; 95% CI: 1.459-5.693). ROC curve analysis showed that at the cut-off value of 2.625, RAB7A expression level had a sensitivity of 84.62% and a specificity of 71.15% for predicting postoperative 5-year mortality of the patients. Bioinformatic analysis suggested that RAB7A was involved in ECM degradation and activation of PI3K/AKT signaling in gastric cancer. MGC803 cells with RAB7A overexpression showed activation of the PI3K/AKT signaling pathway (P<0.01) with enhanced expressions of MMP-2 and MMP-9 (P<0.01) and cell migration and invasion capacities (P<0.01).

CONCLUSION

RAB7A is highly expressed in gastric cancer tissues and affects the patients' prognosis possibly by activating the PI3K/AKT signaling pathway and enhancing ECM degradation to promote tumor invasion.

Expression patterns and immunological characterization of PANoptosis -related genes in gastric cancer

Background

Accumulative studies have demonstrated the close relationship between tumor immunity and pyroptosis, apoptosis, and necroptosis. However, the role of PANoptosis in gastric cancer (GC) is yet to be fully understood.

Methods

This research attempted to identify the expression patterns of PANoptosis regulators and the immune landscape in GC by integrating the GSE54129 and GSE65801 datasets. We analyzed GC specimens and established molecular clusters associated with PANoptosis-related genes (PRGs) and corresponding immune characteristics. The differentially expressed genes were determined with the WGCNA method. Afterward, we employed four machine learning algorithms (Random Forest, Support Vector Machine, Generalized linear Model, and eXtreme Gradient Boosting) to select the optimal model, which was validated using nomogram, calibration curve, decision curve analysis (DCA), and two validation cohorts. Additionally, this study discussed the relationship between infiltrating immune cells and variables in the selected model.

Results

This study identified dysregulated PRGs and differential immune activities between GC and normal samples, and further identified two PANoptosis-related molecular clusters in GC. These clusters demonstrated remarkable immunological heterogeneity, with Cluster1 exhibiting abundant immune infiltration. The Support Vector Machine signature was found to have the best discriminative ability, and a 5-gene-based SVM signature was established. This model showed excellent performance in the external validation cohorts, and the nomogram, calibration curve, and DCA indicated its reliability in predicting GC patterns. Further analysis confirmed that the 5 selected variables were remarkably related to infiltrating immune cells and immune-related pathways.

Conclusion

Taken together, this work demonstrates that the PANoptosis pattern has the potential as a stratification tool for patient risk assessment and a reflection of the immune microenvironment in GC.

Crosstalk between Cancer Cells and Cancer-Associated Fibroblasts Mediated by TGF-β1-IGFBP7 Signaling Promotes the Progression of Infiltrative Gastric Cancer

Patients with infiltrative-type gastric cancer (GC) (Ming's classification) have a poor prognosis due to more metastasis and recurrence. Cancer-associated fibroblasts (CAFs) in infiltrative-type extracellular matrix (ECM) have specific characteristics compared with those of expansive types with respect to metastasis, but the mechanism is still unclear. Based on our proteomics data, TCGA data analysis, and immunohistochemical staining results, significantly higher expression of IGFBP7 was observed in GC, especially in the infiltrative type, and was associated with a poor prognosis. Combining single-cell transcriptome data from GEO and multiple immunofluorescence staining on tissue showed that the differential expression of IGFBP7 mainly originated from myofibroblastic CAFs, the subgroup with higher expression of PDGFRB and α-SMA. After treating primary normal fibroblasts (NFs) with conditional medium or recombined protein, it was demonstrated that XGC-1-derived TGF-β1 upregulated the expression of IGFBP7 in the cells and its secretion via the P-Smad2/3 pathway and mediated its activation with higher FAP, PDGFRB, and α-SMA expression. Then, either conditional medium from CAFs with IGFBP7 overexpression or recombined IGFBP7 protein promoted the migration, invasion, colony formation, and sphere growth ability of XGC-1 and MGC-803, respectively. Moreover, IGFBP7 induced EMT in XGC-1. Therefore, our study clarified that in the tumor microenvironment, tumor-cell-derived TGF-β1 induces the appearance of the IGFBP7+ CAF subgroup, and its higher IGFBP7 extracellular secretion level accelerates the progression of tumors.

Effects of Obesity and Calorie Restriction on Cancer Development

The risk of malignant tumor development is increasing in the world. Obesity is an established risk factor for various malignancies. There are many metabolic alterations associated with obesity which promote cancerogenesis. Excessive body weight leads to increased levels of estrogens, chronic inflammation and hypoxia, which can play an important role in the development of malignancies. It is proved that calorie restriction can improve the state of patients with various diseases. Decreased calorie uptake influences lipid, carbohydrate and protein metabolism, hormone levels and cell processes. Many investigations have been devoted to the effects of calorie restriction on cancer development in vitro and in vivo. It was revealed that fasting can regulate the activity of the signal cascades including AMP-activated protein kinase (AMPK), mitogen-activated protein kinase (MAPK), p53, mTOR, insulin/ insulin-like growth factor 1 (IGF1) and JAK-STAT. Up- or down-regulation of the pathways results in the decrease of cancer cell proliferation, migration and survival and the increase of apoptosis and effects of chemotherapy. The aim of this review is to discuss the connection between obesity and cancer development and the mechanisms of calorie restriction influence on cancerogenesis that stress the importance of further research of calorie restriction effects for the inclusion of this approach in clinical practice.

IGFBP3 induced by the TGF-β/EGFRvIII transactivation contributes to the malignant phenotype of glioblastoma

Dual or multi-targets therapy targeting epidermal growth factor receptor variant III (EGFRvIII) and other molecular may relax the constraint for glioblastoma (GBM), putting forward the urgent requirement of finding candidate molecules. Here, the insulin-like growth factor binding protein-3 (IGFBP3) was considered a candidate, whereas the mechanisms of IGFBP3 production remain unclear. We treated GBM cells with exogenous transforming growth factor β (TGF-β) to simulate the microenvironment. We found that TGF-β and EGFRvIII transactivation induced the activation of transcription factor c-Jun, which specifically bound to the promoter region of IGFBP3 through Smad2/3 and ERK1/2 pathways and promoted the production and secretion of IGFBP3. IGFBP3 knockdown inhibited the activation of TGF-β and EGFRvIII signals and the malignant behaviors triggered by them in vitro and in vivo. Collectively, our results indicated a positive feedback loop of p-EGFRvIII/IGFBP3 under administration of TGF-β, blocking IGFBP3 may be an additional target in EGFRvIII-expressing GBM-selective therapeutic strategy.

RNA N6-methyladenosine reader IGF2BP3 interacts with MYCN and facilitates neuroblastoma cell proliferation

Neuroblastoma (NB) is a kind of typical life-threatening extracranial tumor in children. N6-methyladenosine (m6A) modification is closely related to multiple cancer pathological processes. Insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3) is a top-ranked prognostic risk gene in NB; however, its function is uncertain. The expression of m6A-associated enzymes in patients with NB was analyzed using the Gene Expression Omnibus (GEO) and Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. The IGF2BP3 level in NB cell lines and primary samples was tested using quantitative real-time polymerase chain reaction (qRT-PCR), western blot method, and immunohistochemical analysis. The IGF2BP3 function in cell proliferation was clarified based on many functional in vitro and in vivo experiments. The interaction between IGF2BP3 and N-myc was researched via RNA immunoprecipitation (RIP), m6A RNA immunoprecipitation (MeRIP), and chromatin immunoprecipitation (ChIP) assays. The 16 m6A-regulated enzymes in NB were researched, and the result indicated that IGF2BP3 overexpression was related to cancer progression, COG risk, and survival based on the GEO and TARGET databases. Besides, the IGF2BP3 and MYCN levels were positively correlated. IGF2BP3 expression levels increased in MYCN-amplified NB clinical samples and cells. Knockdown of IGF2BP3 inhibited N-myc expression and NB cell proliferation in vitro and in vivo. IGF2BP3 regulates MYCN RNA stability by modifying m6A. In addition, we demonstrated that N-myc is a transcription factor that directly promotes IGF2BP3 expression in NB cells. IGF2BP3 regulates the proliferation of NB cells via m6A modification of MYCN. N-myc also acts as a transcription factor that regulates IGF2BP3 expression. A positive feedback loop between IGF2BP3 and N-myc facilitates NB cell proliferation.

Expression characteristics and their functional role of IGFBP gene family in pan-cancer

BACKGROUND

Insulin-like growth factor binding proteins (IGFBPs) are critical regulators of the biological activities of insulin-like growth factors. The IGFBP family plays diverse roles in different types of cancer, which we still lack comprehensive and pleiotropic understandings so far.

METHODS

Multi-source and multi-dimensional data, extracted from The Cancer Genome Atlas (TCGA), Oncomine, Cancer Cell Line Encyclopedia (CCLE), and the Human Protein Atlas (HPA) was used for bioinformatics analysis by R language. Immunohistochemistry and qRT-PCR were performed to validate the results of the database analysis results. Bibliometrics and literature review were used for summarizing the research progress of IGFBPs in the field of tumor.

RESULTS

The members of IGFBP gene family are differentially expressed in various cancer types. IGFBPs expression can affect prognosis of different cancers. The expression of IGFBPs expression is associated with multiple signal transduction pathways. The expression of IGFBPs is significantly correlated with tumor mutational burden, microsatellite instability, tumor stemness and tumor immune microenvironment. The qRT-PCR experiments verified the lower expression of IGFBP2 and IGFBP6 in gastric cancer and the lower expression of IGFBP6 in colorectal cancer. Immunohistochemistry validated a marked downregulation of IGFBP2 protein in gastric cancer tissues. The keywords co-occurrence analysis of IGFBP related publications in cancer showed relative research have been more concentrating on the potential of IGFBPs as tumor diagnostic and prognostic markers and developing cancer therapies.

CONCLUSIONS

These findings provide frontier trend of IGFBPs related research and new clues for identifying novel therapeutic targets for various cancers.

A prognostic gene signature for gastric cancer and the immune infiltration-associated mechanism underlying the signature gene, PLG

BACKGROUND

Globally, gastric cancer (GC) is a common and lethal solid malignant tumor. Identifying the molecular signature and its functions can provide mechanistic insights into GC development and new methods for targeted therapy.

METHODS

Differentially expressed genes (DEGs) and prognostic genes (from univariate Cox regression analysis) were overlapped to obtain prognostic DEGs. Subsequently, molecular modules and the functions of these prognostic DEGs were identified by Metascape and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG)/Gene Set Enrichment Analysis (GSEA) enrichment analyses, respectively. Protein-protein interaction (PPI) networks of up- and down-regulated prognostic DEGs in GC were analyzed using the MCC algorithm of the Cytohubba plug-in in Cytoscape. The prognostic gene signature was defined on hub genes of the PPI networks by least absolute shrinkage and selection operator (LASSO)-Cox regression analysis. Furthermore, the expressional level of PLG in our clinical GC samples was validated by quantitative PCR (qPCR), western blotting, and immunohistochemistry (IHC). Subsequently, the PLG expression-correlation analysis was performed to assess the role of PLG in GC progression. Immune infiltration analysis was performed by single-sample gene set enrichment analysis (ssGSEA) to assess the inhibitory effect of PLG on immune infiltration.

RESULTS

Firstly, Up- and down-regulated prognostic DEGs and hub genes in protein-protein interaction (PPI) networks in GC were identified. A prognostic five-gene signature (i.e., PLG, SPARC, FGB, SERPINE1, and KLHL41) was identified. Among the five genes, the relationship between plasminogen (PLG) and GC remains largely unclear. Moreover, the functions of PLG-correlated genes in GC, like 'fibrinolysis', 'hemostasis', 'ion channel complex', and 'transporter complex' were identified. In addition, PLG expression correlated negatively with the infiltration of almost all immune cell types. Interestingly, the expression of PLG was significantly and highly correlated with that of CD160, an immune checkpoint inhibitor.

CONCLUSION

Our findings defined a new five-gene signature for predicting GC prognosis, but more validation is required to assess the effects and mechanism of the five genes, especially PLG, for the development of new GC therapies.

GPR176 Is a Biomarker for Predicting Prognosis and Immune Infiltration in Stomach Adenocarcinoma

Immunotherapy based on immune checkpoint inhibitors (ICIs) is considered to be a promising treatment for stomach adenocarcinoma (STAD), but only a minority of patients benefit from it. It is believed that the poor therapeutic efficacy is attributed to the complex tumor immune microenvironment (TIM) of STAD. Therefore, elucidating the specific regulatory mechanism of TIM in STAD is critical. Previous study suggests that GRP176 may be involved in regulating the pace of circadian behavior, and its role in tumors has not been reported. In this study, we first found that GPR176 was highly expressed in STAD and negatively correlated with patient prognosis. Next, we investigated the relationship between GPR176 and clinical characteristics, and the results showed that the stage is closely related to the level of GPR176. In addition, our further analysis found that GRP176 expression level was significantly correlated with chemotherapeutic drug sensitivity and ICI response. KEGG and GO analyses showed that GPR176 might be involved in stromal remodeling of STAD. Furthermore, we analyzed the association between GPR176 expression and immune implication, and the results revealed that GPR176 was negatively related to the infiltration of various immune cells. Interestingly, GPR176 induced the conversion of TIM while reducing the tumor immune burden (TMB). The expression of GRP176 is closely related to the level of various immunomodulators. Moreover, we performed univariate and multivariate regression analyses on the immunomodulators and finally obtained 4 genes (CRCR4, TNSF18, PDCD1, and TGFB1). Then, we constructed a GRP176-related immunomodulator prognostic model (GRIM) based on the above 4 genes, which was validated to have good predictive power. Finally, we developed a nomogram based on the risk score of GRIM and verified its accuracy. These results suggested that GPR176 is closely related to the prognosis and TIM of STAD. GPR176 may be a new potential target for immunotherapy in STAD.

A molecular classification of gastric cancer associated with distinct clinical outcomes and validated by an XGBoost-based prediction model

Gastric cancer (GC) is a heterogeneous disease and a leading cause of cancer-related deaths. Discovering robust, clinically relevant molecular classifications is critical for guiding personalized therapies for GC. Here, we propose a refined molecular classification scheme for GC using integrated optimal algorithms and multi-omics data. Based on the important features of mRNA, microRNA, and DNA methylation data selected by the multivariate Cox regression model, three subtypes linked to distinct clinical outcomes were identified by combining similarity network fusion and consensus clustering methods. Three subtypes were validated by an extreme gradient boosting machine learning prediction model with 125 differentially expressed genes in multiple independent cohorts. The molecular characteristics of mutation signatures, characteristic gene sets, driver genes, and chemotherapy sensitivity for each subtype were also identified: subtype 1 was associated with favorable prognosis and characterized by high ARID1A and PIK3CA mutations, subtype 2 was associated with a poor prognosis and harbored high recurrent TP53 mutations, and subtype 3 was associated with high CHD1, APOA1 mutations, and a poor prognosis. The proposed three-subtype scheme achieved a better clinical prediction performance (area under the curve value = 0.71) than The Cancer Genome Atlas classification, which may provide a practical subtyping framework to improve the treatment of GC.

Prognosis-Related Molecular Subtypes and Immune Features Associated with Hepatocellular Carcinoma

Bioinformatics tools were used to identify prognosis-related molecular subtypes and biomarkers of hepatocellular carcinoma (HCC). Differential expression analysis of four datasets identified 3330 overlapping differentially expressed genes (DEGs) in the same direction in all four datasets. Those genes were involved in the cell cycle, FOXO signaling pathway, as well as complement and coagulation cascades. Based on non-negative matrix decomposition, two molecular subtypes of HCC with different prognoses were identified, with subtype C2 showing better overall survival than subtype C1. Cox regression and Kaplan-Meier analysis showed that 217 of the overlapping DEGs were closely associated with HCC prognosis. The subset of those genes showing an area under the curve >0.80 was used to construct random survival forest and least absolute shrinkage and selection operator models, which identified seven feature genes (SORBS2, DHRS1, SLC16A2, RCL1, IGFALS, GNA14, and FANCI) that may be involved in HCC occurrence and prognosis. Based on the feature genes, risk score and recurrence models were constructed, while a univariate Cox model identified FANCI as a key gene involved mainly in the cell cycle, DNA replication, and mismatch repair. Further analysis showed that FANCI had two mutation sites and that its gene may undergo methylation. Single-sample gene set enrichment analysis showed that Th2 and T helper cells are significantly upregulated in HCC patients compared to controls. Our results identify FANCI as a potential prognostic biomarker for HCC.

Secretome analysis reveals reduced expression of COL4A2 in hypoxic cancer-associated fibroblasts with a tumor-promoting function in gastric cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) are major components of the tumor microenvironment (TME). Hypoxic TME is known to promote tumor progression. However, how a hypoxic condition regulates CAFs remains elusive.

METHODS

To investigate the underlying mechanism involved in the regulation of gastric cancer (GC) progression by hypoxic CAFs, we performed secretome profiling. Normoxic or hypoxic CAFs conditioned media (CM) were filter-concentrated and in-gel trypsin digested. Resulting peptides were analyzed with LC-MS/MS.

RESULTS

We observed that CM derived from hypoxic CAFs could promote migration of a panel of GC cell lines (AGS, SNU668, SNU638). Mass spectrometry analysis of hypoxic or normoxic CAFs CM identified 1595 proteins, of which 19 proteins (10 upregulated and 9 downregulated) were differentially expressed in the hypoxic secretome. We focused on COL4A2, whose expression was significantly decreased in hypoxic CAFs in HIF-1α-independent manner. Silencing of COL4A2 expression in normoxic CAFs phenocopied the effect of hypoxic CAFs in promoting GC cell migration.

CONCLUSIONS

The reduced expression of COL4A2 in a hypoxic environment might be associated with the tumor-promoting role of hypoxic CAFs in GC.

IGFBP-6: At the Crossroads of Immunity, Tissue Repair and Fibrosis

Insulin-like growth factors binding protein-6 (IGFBP-6) is involved in a relevant number of cellular activities and represents an important factor in the immune response, particularly in human dendritic cells (DCs). Over the past several years, significant insights into the IGF-independent effects of IGFBP-6 were discovered, such as the induction of chemotaxis, capacity to increase oxidative burst and neutrophils degranulation, ability to induce metabolic changes in DCs, and, more recently, the regulation of the Sonic Hedgehog (SHH) signaling pathway during fibrosis. IGFBP-6 has been implicated in different human diseases, and it plays a rather controversial role in the biology of tumors. Notably, well established relationships between immunity, stroma activity, and fibrosis are prognostic and predictive of response to cancer immunotherapy. This review aims at describing the current understanding of mechanisms that link IGFBP-6 and fibrosis development and at highlighting the multiple roles of IGFBP-6 to provide an insight into evolutionarily conserved mechanisms that can be relevant for inflammation, tumor immunity, and immunological diseases.