Function of fibroblast growth factor 2 in gastric cancer occurrence and prognosis

Proteomic and functional comparison between human induced and embryonic stem cells

Human induced pluripotent stem cells (hiPSCs) have great potential to be used as alternatives to embryonic stem cells (hESCs) in regenerative medicine and disease modelling. In this study, we characterise the proteomes of multiple hiPSC and hESC lines derived from independent donors and find that while they express a near-identical set of proteins, they show consistent quantitative differences in the abundance of a subset of proteins. hiPSCs have increased total protein content, while maintaining a comparable cell cycle profile to hESCs, with increased abundance of cytoplasmic and mitochondrial proteins required to sustain high growth rates, including nutrient transporters and metabolic proteins. Prominent changes detected in proteins involved in mitochondrial metabolism correlated with enhanced mitochondrial potential, shown using high-resolution respirometry. hiPSCs also produced higher levels of secreted proteins, including growth factors and proteins involved in the inhibition of the immune system. The data indicate that reprogramming of fibroblasts to hiPSCs produces important differences in cytoplasmic and mitochondrial proteins compared to hESCs, with consequences affecting growth and metabolism. This study improves our understanding of the molecular differences between hiPSCs and hESCs, with implications for potential risks and benefits for their use in future disease modelling and therapeutic applications.

Unraveling the prognostic significance of RGS gene family in gastric cancer and the potential implication of RGS4 in regulating tumor-infiltrating fibroblast

Regulator of G-protein signaling (RGS) proteins are regulators of signal transduction mediated by G protein-coupled receptors (GPCRs). Current studies have shown that some molecules in the RGS gene family are related to the occurrence, development and poor prognosis of malignant tumors. However, the RGS gene family has been rarely studied in gastric cancer. In this study, we explored the mutation and expression profile of RGS gene family in gastric cancer, and evaluated the prognostic value of RGS expression. Then we established a prognostic model based on RGS gene family and performed functional analysis. Further studies showed that RGS4, as an independent prognostic predictor, may play an important role in regulating fibroblasts in the immune microenvironment. In conclusion, this study explores the value of RGS gene family in gastric cancer, which is of great significance for predicting the prognosis and guiding the treatment of gastric cancer.

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.

Issues of origin, morphology and clinical significance of tumor microvessels in gastric cancer

Gastric cancer (GC) remains a serious oncological problem, ranking third in the structure of mortality from malignant neoplasms. Improving treatment outcomes for this pathology largely depends on understanding the pathogenesis and biological characteristics of GC, including the identification and characterization of diagnostic, prognostic, predictive, and therapeutic biomarkers. It is known that the main cause of death from malignant neoplasms and GC, in particular, is tumor metastasis. Given that angiogenesis is a critical process for tumor growth and metastasis, it is now considered an important marker of disease prognosis and sensitivity to anticancer therapy. In the presented review, modern concepts of the mechanisms of tumor vessel formation and the peculiarities of their morphology are considered; data on numerous factors influencing the formation of tumor microvessels and their role in GC progression are summarized; and various approaches to the classification of tumor vessels, as well as the methods for assessing angiogenesis activity in a tumor, are highlighted. Here, results from studies on the prognostic and predictive significance of tumor microvessels in GC are also discussed, and a new classification of tumor microvessels in GC, based on their morphology and clinical significance, is proposed for consideration.

Construction of a ceRNA Network and Analysis of Tumor Immune Infiltration in Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is characterized by high malignancy, frequent metastasis, and recurrence with an unfavorable prognosis. This study is aimed at constructing a prognostic model for tumor-infiltrating immune cells and a competing endogenous RNA (ceRNA) network in PAAD and analyzing susceptibilities of chemotherapy and immunotherapy of PAAD. Gene expression profiles and clinical information of PAAD were downloaded from The Cancer Genome Atlas (TCGA) database and divided into the tumor group and the normal group. A total of five PAAD survival-related key genes in the ceRNA network and three survival-related immune infiltrating cells were uncovered, and two survival risk models and nomograms were constructed. The efficiency and performance of the two models were verified using multi-index area under the curve analysis at different time points, decision curve analysis, and calibration curves. Co-expression analysis showed that LRRC1, MIR600HG, and RNF166 in the ceRNA network and tumor-infiltrating immune cells including CD8 T cells and M1 macrophages were likely related to the PAAD prognosis, and the expression of key ceRNA-related genes was experimently validated in tissues and cell lines by RT-qPCR. Patients with low risk scores for key genes in the ceRNA network displayed a positive response to anti-programmed death-1 (PD-1) treatment and greater sensitivity to chemotherapeutic drugs such as docetaxel, lapatinib, and paclitaxel. More importantly, our results suggested that the IC50 values of gemcitabine in PAAD were not significantly different between the high and low risk groups. The expression levels of immune checkpoints were significantly different in the high-risk and low-risk groups. The prognostic model, nomogram, and drug analysis may provide an essential reference for PAAD patient management in the clinic.

The Analysis of Gene Expression Data Incorporating Tumor Purity Information

The tumor microenvironment is composed of tumor cells, stroma cells, immune cells, blood vessels, and other associated non-cancerous cells. Gene expression measurements on tumor samples are an average over cells in the microenvironment. However, research questions often seek answers about tumor cells rather than the surrounding non-tumor tissue. Previous studies have suggested that the tumor purity (TP)-the proportion of tumor cells in a solid tumor sample-has a confounding effect on differential expression (DE) analysis of high vs. low survival groups. We investigate three ways incorporating the TP information in the two statistical methods used for analyzing gene expression data, namely, differential network (DN) analysis and DE analysis. Analysis 1 ignores the TP information completely, Analysis 2 uses a truncated sample by removing the low TP samples, and Analysis 3 uses TP as a covariate in the underlying statistical models. We use three gene expression data sets related to three different cancers from the Cancer Genome Atlas (TCGA) for our investigation. The networks from Analysis 2 have greater amount of differential connectivity in the two networks than that from Analysis 1 in all three cancer datasets. Similarly, Analysis 1 identified more differentially expressed genes than Analysis 2. Results of DN and DE analyses using Analysis 3 were mostly consistent with those of Analysis 1 across three cancers. However, Analysis 3 identified additional cancer-related genes in both DN and DE analyses. Our findings suggest that using TP as a covariate in a linear model is appropriate for DE analysis, but a more robust model is needed for DN analysis. However, because true DN or DE patterns are not known for the empirical datasets, simulated datasets can be used to study the statistical properties of these methods in future studies.

Reversal of Chemotherapy Resistance to Cisplatin in NSCLC by miRNA-195-5p via Targeting the FGF2 Gene

Objective

To explore the mechanism of miR-195-5p in the pathogenesis non-small cell lung cancer (NSCLC) and cisplatin resistance.

Methods

The function of miR-195-5p in NSCLC and cisplatin resistance were determined by MTT, scratch assay, transwell assay, and nude mice xenograft experiments. miR-195-5p target gene was identified by dual-luciferase reporter assays and real-time PCR analysis.

Results

miR-195-5p content was lower in A549/DDP than that in A549 cells, with reduced chemotherapy sensitivity and increased cell invasion and migration ability. The loss-of-function and gain-of-function assays illustrated that miR-195-5p might have increased the chemosensitivity to cisplatin in the A549/DDP cells and decreased cell migration and invasion. FGF2 is a negatively correlated action target of miR-195-5p. miR-195-5p might affect EMT by inhibiting FGF2. Overexpression of FGF2 resulted in enhanced cisplatin resistance in the cells, while miR-195-5p might have reversed this resistance.

Conclusion

Overall, miR-195-5p might target FGF2 to reduce cisplatin resistance in A549/DDP cells and enhance chemosensitivity.

Identification of New Therapeutic Targets for Gastric Cancer With Bioinformatics

We aimed to identify new targets affecting gastric cancer (GC) prognosis. Six target genes were identified from hub genes based on their relationship with important factors affecting tumor progression, like immune infiltration, purity, tumor mutation burden (TMB), and tumor microenvironment (TME) score. The effect of target genes' somatic mutations and copy number alteration (CNA) was examined to determine their effect on GC prognosis. Six target genes (FBN1, FN1, HGF, MMP9, THBS1, and VCAN) were identified. Reduced expression of each target gene, except MMP9, indicated better prognosis and lower grade in GC. FBN1, THBS1, and VCAN showed lower expression in stage I GC. Non-silencing mutations of the six genes played a role in significantly higher TMB and TME scores. THBS1 mutation was associated with earlier stage GC, and VCAN mutation was associated with lower grade GC. However, patients with target gene CNA displayed higher tumor purity. MMP9, THBS1, and VCAN CNA was associated with lower grade GC, while FBN1 CNA reflected earlier T stage. Additionally, the target genes may affect GC prognosis by influencing multiple oncogenic signaling pathways. FBN1, FN1, HGF, MMP9, THBS1, and VCAN may be new GC prognostic targets by affecting tumor purity, TMB, TME score, and multiple oncogenic signaling pathways.

Structural characterization and anti-lung cancer activity of a sulfated glucurono-xylo-rhamnan from Enteromorpha prolifera

A sulfated glucurono-xylo-rhamnan (EP-3-H) was purified from a green alga, Enteromorpha prolifera. EP-3-H and its oligomers were characterized by high performance liquid chromatography, mass spectrometry and one and two-dimensional nuclear magnetic resource spectroscopy. The structural analysis showed EP-3-H has a backbone of glucurono-xylo-rhamnan, branches with glucuronic acid and sulfated at C3 of rhamnose and/or C2 of xylose. The inhibition of EP-3-H on human lung cancer A549 cell proliferation in vitro and its therapeutic effects in BALB/c-nu mice in vivo were determined to evaluate the anti-lung cancer activity of EP-3-H. The tumor inhibition level was 59 %, suggesting that EP-3-H might be a good candidate for the treatment of lung cancer. Surface plasmon resonance (SPR) studies revealed the IC₅₀ on the binding of fibroblast growth factors, (FGF1 and FGF2), to heparin were 0.85 and 1.47 mg/mL, respectively. These results suggest that EP-3-H inhibits cancer proliferation by interacting with these growth factors.

Role of Extracellular Matrix in Gastrointestinal Cancer-Associated Angiogenesis

Gastrointestinal tumors are responsible for more cancer-related fatalities than any other type of tumors, and colorectal and gastric malignancies account for a large part of these diseases. Thus, there is an urgent need to develop new therapeutic approaches to improve the patients' outcome and the tumor microenvironment is a promising arena for the development of such treatments. In fact, the nature of the microenvironment in the different gastrointestinal tracts may significantly influence not only tumor development but also the therapy response. In particular, an important microenvironmental component and a potential therapeutic target is the vasculature. In this context, the extracellular matrix is a key component exerting an active effect in all the hallmarks of cancer, including angiogenesis. Here, we summarized the current knowledge on the role of extracellular matrix in affecting endothelial cell function and intratumoral vascularization in the context of colorectal and gastric cancer. The extracellular matrix acts both directly on endothelial cells and indirectly through its remodeling and the consequent release of growth factors. We envision that a deeper understanding of the role of extracellular matrix and of its remodeling during cancer progression is of chief importance for the development of new, more efficacious, targeted therapies.

Fibroblast Growth Factor (FGF) Signaling Protects Against Acute Pancreatitis-Induced Damage by Modulating Inflammatory Responses

BACKGROUND Acute pancreatitis (AP) is a symptom of sudden pancreas inflammation, which causes patients severe suffering. In general, fibroblast growth factor (FGF) levels are increased and amylase and lipase activities are elevated during AP pathogenesis, but protein concentration are low. However, the mechanism through which FGF signaling regulates AP pathogenesis remains elusive. MATERIAL AND METHODS The concentrations of PGE2, TNF-alpha, sCRP, FGF1, and FGF2 in the serum samples of the AP group and healthy control group were detected by enzyme-linked immunosorbent assay. In addition, IkappaBalpha and p-IkappaBalpha levels were analyzed in the serum samples. Subsequently, the AP rat model was established, and FGF1, FGF2, anti-FGF1, and anti-FGF2 antibodies and Bay11-7082 were injected into AP rats. TNF-alpha, PAI-1 JNK, p-JNK, IkappaBalpha, and p-IkappaBalpha levels were also examined. RESULTS Results showed that levels of PGE2, TNF-alpha, sCRP, p-IkappaBalpha, FGF1, and FGF2, as well as amylase and lipase activity were increased in patients with AP compared with those in healthy people. In addition, protein concentrations were lower in patients with AP than in the healthy group. Activation of FGF signaling by injecting FGF1 or FGF2 also inhibited AP-induced inflammation response in the pancreas and increased amylase and lipase activities, as well as protein concentration. However, the injection of FGF1 and FGF2 antibodies accelerated AP-mediated inflammation responses in the serum. In addition, Bay11-7082 injection inhibited AP activation of inflammation response and amylase and lipase activities. Protein concentration were also increased in AP rats. CONCLUSIONS FGF signaling protects against AP-mediated damage by inhibition of AP-activating inflammatory responses.