Phosphoglucose isomerase gene expression as a prognostic biomarker of gastric cancer

Integrated bioinformatics and network pharmacology identifying the mechanisms and molecular targets of Guipi Decoction for treatment of comorbidity with depression and gastrointestinal disorders

BACKGROUND

Guipi decoction (GPD) not only improves gastrointestinal (GI) function, but also depressive mood. The bioinformatics study aimed to reveal potential crosstalk genes and related pathways between depression and GI disorders. A network pharmacology approach was used to explore the molecular mechanisms and potential targets of GPD for the simultaneous treatment of depression comorbid GI disorders.

METHODS

Differentially expressed genes (DEGs) of major depressive disorder (MDD) were identified based on GSE98793 and GSE19738, and GI disorders-related genes were screened from the GeneCards database. Overlapping genes between MDD and GI disorders were obtained to identify potential crosstalk genes. Protein-protein interaction (PPI) network was constructed to screen for hub genes, signature genes were identified by LASSO regression analysis, and single sample gene set enrichment analysis (ssGSEA) was performed to analyze immune cell infiltration. In addition, based on the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, we screened the active ingredients and targets of GPD and identified the intersection targets of GPD with MDD and GI disorder-related genes, respectively. A "component-target" network was constructed using Cytoscape, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed.

RESULTS

The MDD-corrected dataset contained 2619 DEGs, and a total of 109 crosstalk genes were obtained. 14 hub genes were screened, namely SOX2, CRP, ACE, LEP, SHH, CDH2, CD34, TNF, EGF, BDNF, FN1, IL10, PPARG, and KIT. These genes were identified by LASSO regression analysis for 3 signature genes, including TNF, EGF, and IL10. Gamma.delta.T.cell was significantly positively correlated with all three signature genes, while Central.memory.CD4.T.cell and Central.memory.CD8.T.cell were significantly negatively correlated with EGF and TNF. GPD contained 134 active ingredients and 248 targets, with 41 and 87 relevant targets for the treatment of depression and GI disorders, respectively. EGF, PPARG, IL10 and CRP overlap with the hub genes of the disease.

CONCLUSION

We found that GPD may regulate inflammatory and oxidative stress responses through EGF, PPARG, IL10 and CRP targets, and then be involved in the treatment of both depression and GI disorders.

Transcriptome profiling of patient-derived tumor xenografts suggests novel extracellular matrix-related signatures for gastric cancer prognosis prediction

BACKGROUND

A major obstacle to the development of personalized therapies for gastric cancer (GC) is the prevalent heterogeneity at the intra-tumor, intra-patient, and inter-patient levels. Although the pathological stage and histological subtype diagnosis can approximately predict prognosis, GC heterogeneity is rarely considered. The extracellular matrix (ECM), a major component of the tumor microenvironment (TME), extensively interacts with tumor and immune cells, providing a possible proxy to investigate GC heterogeneity. However, ECM consists of numerous protein components, and there are no suitable models to screen ECM-related genes contributing to tumor growth and prognosis. We constructed patient-derived tumor xenograft (PDTX) models to obtain robust ECM-related transcriptomic signatures to improve GC prognosis prediction and therapy design.

METHODS

One hundred twenty two primary GC tumor tissues were collected to construct PDTX models. The tumorigenesis rate and its relationship with GC prognosis were investigated. Transcriptome profiling was performed for PDTX-originating tumors, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to extract prognostic ECM signatures and establish PDTX tumorigenicity-related gene (PTG) scores. The predictive ability of the PTG score was validated using two independent cohorts. Finally, we combined PTG score, age, and pathological stage information to establish a robust nomogram for GC prognosis prediction.

RESULTS

We found that PDTX tumorigenicity indicated a poor prognosis in patients with GC, even at the same pathological stage. Transcriptome profiling of PDTX-originating GC tissues and corresponding normal controls identified 383 differentially expressed genes, with enrichment of ECM-related genes. A robust prognosis prediction model using the PTG score showed robust performance in two validation cohorts. A high PTG score was associated with elevated M2 polarized macrophage and cancer-associated fibroblast infiltration. Finally, combining the PTG score with age and TNM stage resulted in a more effective prognostic model than age or TNM stage alone.

CONCLUSIONS

We found that ECM-related signatures may contribute to PDTX tumorigenesis and indicate a poor prognosis in GC. A feasible survival prediction model was built based on the PTG score, which was associated with immune cell infiltration. Together with patient ages and pathological TNM stages, PTG score could be a new approach for GC prognosis prediction.

Characterization of glycometabolism and tumor immune microenvironment for predicting clinical outcomes in gastric cancer

Recent evidence demonstrates that the reprogramming of energy metabolism can interact with the tumor immune microenvironment, thereby participating in the progression of cancer. In this study, multi-omics data of 2471 gastric cancer samples were used to identify tumor glycometabolism and its correlation with tumor immune microenvironment. A series of bioinformatic approaches were performed to establish a scoring system to predict the survival and response of chemotherapy and immunotherapy. Three glycometabolic subtypes and two immune clustering subgroups of gastric cancer were determined. We further established a Gluco-Immune Scoring system to quantify the cancer glycometabolic status and immune infiltration of individual patients. Patients with low Gluco-Immune Score were sensitive to adjuvant chemotherapy, while patients with high Gluco-Immune Score may benefit from immunotherapy. Our results indicate that in gastric cancer, the assessment of tumor glucose metabolism and immune microenvironment has application value for the prediction of curative effects and the formulation of combined treatment strategies.

Correlation of Glucose Metabolism with Cancer and Intervention with Traditional Chinese Medicine

Cancer is a complex disease with several distinct characteristics, referred to as “cancer markers” one of which is metabolic reprogramming, which is a common feature that drives cancer progression. Over the last ten years, researchers have focused on the reprogramming of glucose metabolism in cancer. In cancer, the oxidative phosphorylation metabolic pathway is converted into the glycolytic pathway in order to meet the growth requirements of cancer cells, thereby creating a microenvironment that promotes cancer progression. The precise mechanism of glucose metabolism in cancer cells is still unknown, but it is thought to involve the aberrant levels of metabolic enzymes, the influence of the tumor microenvironment (TME), and the activation of tumor-promoting signaling pathways. It is suggested that glucose metabolism is strongly linked to cancer progression because it provides energy to cancer cells and interferes with antitumor drug pharmacodynamics. Therefore, it is critical to unravel the mechanism of glucose metabolism in tumors in order to gain a better understanding of tumorigenesis and to lay the groundwork for future research into the identification of novel diagnostic markers and therapeutic targets for cancer treatment. Traditional Chinese Medicine (TCM) has the characteristics of multiple targets, multiple components, and less toxic side effects and has unique advantages in tumor treatment. In recent years, researchers have found that a variety of Chinese medicine monomers and compound recipes play an antitumor role by interfering with the reprogramming of tumor metabolism. The underlying mechanisms of metabolism reprogramming of tumor cells and the role of TCM in regulating glucose metabolism are reviewed in this study, so as to provide a new idea for antitumor research in Chinese medicine.

A Mixture of Baicalein, Wogonin, and Oroxylin-A Inhibits EMT in the A549 Cell Line via the PI3K/AKT-TWIST1-Glycolysis Pathway

Non-small cell lung cancer (NSCLC) is a worldwide disease with a high morbidity and mortality rate, which is most derived from its metastasis. Some studies show that the epithelial-mesenchymal transition (EMT) process promotes lung cancer cell migration and invasion, leading to NSCLC metastasis. Total flavonoid aglycones extract (TFAE) isolated from Scutellaria baicalensis was reported to inhibit tumor growth and induce apoptosis. In this study, we found that baicalein, wogonin, and oroxylin-A were the active compounds of TFAE. After reconstructing with these three compounds [baicalein (65.8%), wogonin (21.2%), and oroxylin-A (13.0%)], the reconstructed TFAE (reTFAE) inhibited the EMT process of A549 cells. Then, bioinformatic technology was employed to elucidate the potential pharmacodynamic mechanism network of reTFAE. We identified the relationship between reTFAE and PI3K/Akt signaling pathways, with TWIST1 as the key protein. LY294002, the inhibitor of the PI3K/Akt signaling pathway, and knock-down TWIST1 could significantly enhance the efficacy of reTFAE, with increasing expression of epithelial markers and decreasing expression of mesenchymal markers in A549 cells at the same time. Furthermore, stable isotope dimethyl-labeled proteomics technology was conducted to complement the follow-up mechanism that the EMT-inhibition process may be realized through the glycolysis pathway. In conclusion, we claim that TWIST1-targeted flavonoids could provide a new strategy to inhibit EMT progress for the treatment of NSCLC.

Construction of novel hypoxia-related gene model for prognosis and tumor microenvironment in endometrial carcinoma

INTRODUCTION

Endometrial cancer is currently one of the three most common female reproductive cancers, which seriously threatens women's lives and health. Hypoxia disrupts the tumor microenvironment, thereby affecting tumor progression and drug resistance.

METHODS

We established hypoxia-related gene model to predict patient prognosis and 1-, 3-, and 5-year overall survival rates. Then, the expression level of hypoxia-related genes and survival data were extracted for comprehensive analysis by Cox regression analysis, and the model was established.

RESULTS

We analyzed the survival and prognosis of patients in the high and low-risk groups. The Kaplan-Meier curve showed that the low-risk group is associated with a better survival rate. The 1-, 3-, and 5-year AUC values of the model were 0.680, 0.698, and 0.687, respectively. Finally, we found that LAG3 may be a potential immune checkpoint for endometrial cancer.

CONCLUSION

We found four hypoxia-related genes (ANXA2, AKAP12, NR3C1, and GPI) associated with prognosis. The hypoxia-related gene model can also predict prognosis and tumor microenvironment in endometrial cancer.

CXCL16 Promotes Gastric Cancer Tumorigenesis via ADAM10-Dependent CXCL16/CXCR6 Axis and Activates Akt and MAPK Signaling Pathways

Abnormal expression of CXC motif chemokine ligand 16 (CXCL16) has been demonstrated to be associated with tumor progression and metastasis, served as a prognostic factor in many cancers, with higher relative expression behaving as a marker of tumor progression. However, its role and mechanisms underlying progression and metastasis of gastric cancer (GC) are yet to be elucidated. In our investigation, public datasets and human GC tissue samples were used to determine the CXCL16 expression levels. Our results revealed that CXCL16 was upregulated in GC. The high expression CXCL16 in GC was significantly associated with histologic poor differentiation and pTNM staging. And high CXCL16 was positively correlated with the poor survival of GC patients. Gain-and loss-of-function experiments were employed to investigate the biological role of CXCL16 in proliferation and migration both in vitro and in vivo. Mechanically, Gene set enrichment analysis (GSEA) revealed that the epithelial‑mesenchymal transition (EMT), Akt and MAPK signal pathway related genes were significantly enriched in the high CXCL16 group, which was confirmed by western blot. Moreover, overexpression CXCL16 promoted the disintegrin and metalloproteases (ADAM10) and the CXC motif chemokine receptor 6 (CXCR6) expression, which mediated the CXCL16/CXCR6 positive feedback loop in GC, with activating Akt and MAPK signaling pathways. Knocking down ADAM10 would interrupted the CXCL16/CXCR6 axis in the carcinogenesis and progression of GC. In conclusion, our findings offered insights into that CXCL16 promoted GC tumorigenesis by enhancing ADAM10-dependent CXCL16/CXCR6 axis activation.

The T-Cell-Inflammation Status Can Predict Outcomes of Adjuvant Chemotherapy in Patients with Gastric Cancer

BACKGROUND

Immunogenic chemotherapy promotes antitumor immune response in the tumor microenvironment (TME). In gastric cancer, the effect of a preexisting T-cell-inflamed TME on the efficacy of adjuvant chemotherapy (ACT) is unclear. The purpose of the present study was to evaluate the benefits of ACT in T-cell-inflamed gastric cancer.

METHODS

Three cohorts (n = 267, 300, and 198) of gastric cancer patients who underwent gastrectomy with or without ACT were included in this study. Based on a well-defined T-cell-inflamed gene signature, which includes 13 genes, these patients were classified into non-T-cell-inflamed, intermediate T-cell-inflamed, and T-cell-inflamed subgroups. The CIBERSORT software was used to estimate the immune cells infiltrating the TME, and the Kaplan-Meier curve was plotted for survival analysis.

RESULTS

The T-cell-inflamed patients had high levels of CD8 + T, gamma delta T, and activated CD4 + memory T cells, whereas low level of resting NK cells was observed in all the three cohorts (all P < 0.05). In patients with stage II-IV disease without distant metastasis, those who were T-cell-inflamed were more likely to benefit from ACT (all P < 0.05), regardless of the chemotherapy regimen. Furthermore, patients with both T-cell-inflamed and high microsatellite instability status also were likely to benefit from ACT (P = 0.019).

CONCLUSIONS

The present study shows that T-cell inflammation is predictive of a survival benefit from ACT. Our findings will be helpful in making decisions regarding the use of chemotherapy in combination with immunotherapy to improve the clinical outcomes in patients with gastric cancer.