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1.
Article in English | MEDLINE | ID: mdl-38064625

ABSTRACT

Objective: This study uses existing research results and literature to explore the effectiveness and safety of apatinib combined with trastuzumab in treating advanced gastric cancer. The goal is to establish a theoretical foundation for gastric cancer treatment and assist doctors in developing improved treatment plans. Methods: Three databases were used in this study: the Cochrane Library, PubMed, and Embase. Keywords such as "gastric cancer," "trastuzumab," and "apatinib" were searched to screen and collect the data of the eligible studies. Data extraction and treatment evaluation were performed on the collected literature before conducting a meta-analysis. Results: The combination of apatinib and trastuzumab showed promising results. The objective response rate, disease control rate, and median survival rate were significantly improved compared to trastuzumab alone. The treatment effect of apatinib combined with trastuzumab was found to be superior. However, it was noted that the incidence of hypertension was higher in the apatinib combined with the trastuzumab group. Furthermore, the levels of IFN-γ and TNF-α were higher in the combination group, while IL-10, IL-4, TSGF, CA199, and CEA levels were lower in the trastuzumab group. These findings suggest that apatinib combined with trastuzumab may offer better patient outcomes, although it is important to consider the potential adverse reactions associated with this combination therapy. Conclusions: Current evidence shows that compared with trastuzumab, apatinib combined with trastuzumab has advantages in many aspects of treatment, and the therapeutic effect is more significant, which can effectively manage the disease progression in patients with gastric cancer, reduce the adverse reactions of patients to a certain extent, and improve the quality of life of patients. The sample size of this study was relatively small. Expanding the sample size will be necessary to obtain more accurate research results to enhance reliability and validity.

2.
Int J Clin Exp Pathol ; 7(7): 3853-64, 2014.
Article in English | MEDLINE | ID: mdl-25120762

ABSTRACT

Breast cancer (BC) is the most common malignancy among women. We aimed to illuminate the molecular dysfunctional mechanisms of BC progression. The mRNA expression profile of BC GSE15852 was downloaded from Gene Expression Omnibus database, including 43 normal samples and 43 cancer samples. Differentially expressed genes (DEGs) in BC were screened using the t-test by Benjamin and Hochberg method. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the selected DEGs were enriched using Hypergeomeric distribution model. In addition, functional similarity network among the enriched pathways was constructed to further analyze the collaboration of these pathways. We found 848 down-regulated DEGs were associated with 16 significant dysfunctional pathways, including PPAR signaling fatty acid metabolism, and 1584 up-regulated DEGs were related to 6 significant dysfunctional pathways, like cell cycle, protein export, and antigen processing and presentation in BC samples. Crosstalk network analysis of pathways indicated that pyruvate metabolism, propanoate metabolism, and glycolysis gluconeogenesis were the pathways with closest connections with other pathways in BC. In addition, other antigen processing and presentation, including 19 DEGs; PPAR signaling pathway, including 18 DEGs; and pyruvate metabolism pathway, including 13 DEGs were further analyzed. Our results suggested that dysfunctional of significant pathways can greatly affect the progression of BC. Several significant disorder pathways were enriched in our comprehensive study. They may provide guidelines to explore the dysfunctional mechanism of BC progression.


Subject(s)
Breast Neoplasms/genetics , Gene Expression Regulation, Neoplastic/genetics , Gene Regulatory Networks/genetics , Signal Transduction/physiology , Transcriptome , Breast Neoplasms/metabolism , Female , Gene Expression Profiling , Humans , Oligonucleotide Array Sequence Analysis , RNA, Messenger/analysis
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