Gastric cancer (GC) is one of the most commonly occurring cancers, and metabolism-related genes (MRGs) are associated with its development. Transcriptome data and the relevant clinical data were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases, and we identified 194 MRGs differentially expressed between GC and adjacent nontumor tissues. Through univariate Cox and lasso regression analyses we identified 13 potential prognostic differentially expressed MRGs (PDEMRGs). These PDEMRGs (CKMT2, ME1, GSTA2, ASAH1, GGT5, RDH12, NNMT, POLR1A, ACYP1, GLA, OPLAH, DCK, and POLD3) were used to build a Cox regression risk model to predict the prognosis of GC patients. Further univariate and multivariate Cox regression analyses showed that this model could serve as an independent prognostic parameter. Gene Set Enrichment Analysis showed significant enrichment pathways that could potentially contribute to pathogenesis. This model also revealed the probability of genetic alterations of PDEMRGs. We have thus identified a valuable metabolic model for predicting the prognosis of GC patients. The PDEMRGs in this model reflect the dysregulated metabolic microenvironment of GC and provide useful noninvasive biomarkers.
Chemotherapy is the main clinical treatment method of gastric cancer. Multidrug resistance (MDR) has become a common phenomenon with the development of tumors, which alleviates the effect of chemotherapy and makes it difficult to break the bottleneck of survival rate of advanced gastric cancer. Therefore, the exploration of MDR reversal agents for gastric cancer is the focus and also the difficulty of current treatment. Currently, the researches on the mechanisms of drug resistance in gastric cancer have been continuously deepened, which reveal different pathways and targets of MDR, laying a solid foundation for studying reversal agents. As a kind of natural medicine, traditional Chinese medicine (TCM) owns the characteristics of low toxicity, high safety and effectiveness. It can inhibit the occurrence, growth and metastasis of tumors, and reverse MDR via multiple pathways and mechanisms, the pathological function of which has become a research hotspot in recent years. TCM reversers are mainly divided into Chinese medicine monomers, Chinese patent medicines, and Chinese herbal compounds. With certain quantity and advantage, TCM reversers for MDR play an important role in the clinical treatment and show great potential in gastric cancer.
Sparganii rhizoma (SL) has potential therapeutic effects on gastric cancer (GC), but its main active ingredients and possible anticancer mechanism are still unclear. In this study, we used HPLC-Q-TOF–MS/MS to comprehensively analyse the chemical components of the aqueous extract of SL. On this basis, a network pharmacology method incorporating target prediction, gene function annotation, and molecular docking was performed to analyse the identified compounds, thereby determining the main active ingredients and hub genes of SL in the treatment of GC. Finally, the mRNA and protein expression levels of the hub genes of GC patients were further analysed by the Oncomine, GEPIA, and HPA databases. A total of 41 compounds were identified from the aqueous extract of SL. Through network analysis, we identified seven main active ingredients and ten hub genes: acacetin, sanleng acid, ferulic acid, methyl 3,6-dihydroxy-2-[(2-hydroxyphenyl) ethynyl]benzoate, caffeic acid, adenine nucleoside, azelaic acid and PIK3R1, PIK3CA, SRC, MAPK1, AKT1, HSP90AA1, HRAS, STAT3, FYN, and RHOA. The results indicated that SL might play a role in GC treatment by controlling the PI3K-Akt and other signalling pathways to regulate biological processes such as proliferation, apoptosis, migration, and angiogenesis in tumour cells. In conclusion, this study used HPLC-Q-TOF–MS/MS combined with a network pharmacology approach to provide an essential reference for identifying the chemical components of SL and its mechanism of action in the treatment of GC.
Background: Flap Endonuclease 1(FEN1) has been considered as a new tumor marker in recent years and Jianpi Yangwei Decoction (JPYW) is a basic Traditional Chinese Medicine (TCM) for the treatment of gastric cancer. This study aimed to explore the role of FEN1-mediated DNA damage repair in the drug resistance of gastric cancer and the effect of JPYW on it by employing BGC823/5-Fu drug-resistant cell model. Methods: The DNA repair efficiency of BGC823 and BGC823/5-Fu was compared intracellularly and extracellularly using an extrachromosomal assay system and the reconstituted base excision repair assay. By comparing gene and protein expression and identifying cell survival rates after knockdown or high expression of FEN1, the correlation between FEN1 high expression and 5-Fluorouracil (5-Fu) drug resistance was revealed. The effect of JPYW on DNA damage repair and FEN1 expression was observed by the degree of γ-H2AX phosphorylation in the cells, DNA repair efficiency and enzyme activity, et al. Results: BGC823/5-Fu had a higher DNA repair efficiency than BGC823(P < 0.001), which proved to be both intracellular and extracellular. FEN1 was highly expressed in BGC823/5-Fu regardless of gene level(P < 0.001) or protein level. Furthermore, manipulating FEN1 altered the sensitivity of cancer cells to chemotherapeutic drug 5-Fu. Different concentrations of JPYW were used to investigate the inhibitory effect on the expression of FEN1 and DNA damage repair. JPYW inhibited DNA damage repair both intracellularly and extracellularly: the phosphorylation of γ-H2AX increased, with more DNA damage in the cells; the synthetic 8-oxo dG damage repair was reduced; and the ability of cell lysates to repair DNA damage decreased. The decrease of FEN1 expression in BGC823/5-Fu had a concentration dependent relationship with JYPW. In addition, JPYW inhibited the activity of FEN1 at the enzymatic level, as the amount of cutoff synthetic 32 p labeled DNA substrates were decreased. Conclusion: FEN1 was highly expressed in drug-resistance gastric cancer cells BGC823/5-Fu, which leading to BGC823 resistant to (5-Fu) by acting on DNA damage repair. JPYW inhibited DNA damage repair and reversed 5-Fu drug resistance by reducing FEN1 expression and inhibiting FEN1 functional activity.
Objectives. This network meta-analysis (NMA) was designed to assess the comparative effectiveness and safety of oral Chinese patent medicines combined with chemotherapy for gastric cancer on the National Basic Medical Insurance Drugs List of China. Methods. A comprehensive literature search was performed in seven electronic databases from their inception to February 25, 2020, aiming to collect all related randomized controlled trials (RCTs) to evaluate the effectiveness and safety of oral Chinese patent medicines as an adjuvant for gastric cancer. Two researchers independently screened the literature, extracted data, and assessed the risk of bias of included studies using the Cochrane Risk of Bias Scale. NMA was then performed by using STATA 16.0 software and ADDIS 1.16.8 software. Results. Finally, 30 RCTs were included, involving seven kinds of oral Chinese patent medicines, with a total of 2602 patients. For improvement of clinical efficacy, Bazhen granule combined with chemotherapy was ranked first for effectiveness, followed by the Cinobufacin capsule combined with chemotherapy and Xiao’aiping tablet combined with chemotherapy. Meanwhile, Bazhen granules combined with chemotherapy also were ranked first in reducing gastrointestinal reactions. In terms of improving performance status, the Xiao’aiping tablet was the best and significantly better than other oral Chinese patent medicines. Besides, the Zhenqi Fuzheng granule combined with chemotherapy was best for reducing the incidence of leucopenia. Conclusions. Since only one RCT of Bazhen granule was included in this study for analysis, its statistical efficiency is low. Therefore, this study recommends that the Cinobufacin capsule combined with chemotherapy should be a priority in improving clinical efficacy. In terms of improving patients’ quality of life, Xiao’aiping tablet is the best choice. Safety was best for Zhenqi Fuzheng granule and Bazhen granule combined with chemotherapy. Limited by the quantity, quality, and possible bias of included studies, the above conclusions need to be further verified by more high-quality RCTs.
Aim: To explore the mechanism of gastric carcinogenesis by mining potential hub genes and to search for promising small-molecular compounds for gastric cancer (GC). Materials & methods: The microarray datasets were downloaded from Gene Expression Omnibus database and the genes and compounds were analyzed by bioinformatics-related tools and software. Results: Six hub genes ( MKI67, PLK1, COL1A1, TPX2, COL1A2 and SPP1) related to the prognosis of GC were confirmed to be upregulated in GC and their high expression was correlated with poor overall survival rate in GC patients. In addition, eight candidate compounds with potential anti-GC activity were identified, among which resveratrol was closely correlated with six hub genes. Conclusion: Six hub genes identified in the present study may contribute to a more comprehensive understanding of the mechanism of gastric carcinogenesis and the predicted potential of resveratrol may provide valuable clues for the future development of targeted anti-GC inhibitors.
Colorectal cancer (CRC) is continuously rising among young adult patients, necessitating more forethoughtful study and understanding of the mechanisms behind CRC and the development of the new diagnostic and therapeutic strategies. Our research demonstrated that SPT6 synergized with staphylococcal nuclease and Tudor domain containing 1 (SND1) to promote CRC progression by targeting human telomerase reverse transcriptase (hTERT) and put forward that inhibiting SPT6‐SND1‐hTERT axis may create a therapeutic vulnerability in CRC.
Dilated Cardiomyopathy (DCM) is a complex heart disease affecting the heart musculature and vasculature, involving one or several underlying pathophysiological mechanisms. Identifying potential biomarkers for dilated cardiomyopathy is a challenge owing to various aetiologies involved. Studying the biomarkers involved in DCM will ultimately give a better insight about which pathophysiological pathways are involved in the onset of the disease. Owing to its multifactorial aetiologies, response to treatment is usually poor. If we can find the exact underlying causes, a better treatment approach could be implemented. One way to obtain better insight of DCM is to study the biomarkers released. Through biomarkers, we can know which underlying mechanisms are involved. Biomarkers can provide us with clinical information such as diagnostic, prognostic, risk stratification as well as response to treatment. Underlying mechanisms such as inflammation, stress/strain, myocyte injury, matrix remodelling, oxidative stress, neurohormones involvement, among others, can contribute to the onset of DCM. Different mechanisms will yield different biomarkers. So it would be wise to classify those biomarkers involving in DCM based on their respective pathogenesis. Moreover, most importantly is to be able to make use of the information that biomarker pertains. However, specificity of those biomarkers poses a problem. One way of making these biomarkers clinically useful is to make use of a biomarker modelling score system.
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