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  • Frontiers Media SA  (2)
  • Lu, Yuanjun  (2)
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  • Frontiers Media SA  (2)
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  • 1
    Online Resource
    Online Resource
    Frontiers Media SA ; 2023
    In:  Frontiers in Cell and Developmental Biology Vol. 11 ( 2023-6-7)
    In: Frontiers in Cell and Developmental Biology, Frontiers Media SA, Vol. 11 ( 2023-6-7)
    Abstract: Gastric cancer (GC) is the fifth most common cancer worldwide. Cuproptosis is associated with cell growth and death as well as tumorigenesis. Aiming to lucubrate the potential influence of CRGs in gastric cancer, we acquired datasets of gastric cancer patients from TCGA and GEO. The identification of molecular subtypes with CRGs expression was achieved through unsupervised learning-cluster analysis. To evaluate the application value of subtypes, the K-M survival analysis was conducted to evaluate the clinical prognostic characteristics. Subsequently, we performed Gene Set Variation Analysis (GSVA) and utilized ssGSEA to quantify the extent of immune infiltration. Further, the K-M survival analysis was used to identify the prognosis-related CRGs. Next, signature genes of diagnostic predictive value were screened using the least absolute shrinkage and selection operator (LASSO) algorithm from the expression matrix for TCGA, as well as the signature gene-related subtype was clustered by the “ConsensusClusterPlus” package. Finally, the immunological and drug sensitivity assessments of the signature gene-related subtypes were conducted. A total of 173 CRGs were identified, most of the CRGs undergo copy number variation in gastric cancer. Under different patient subtypes, immune cell levels differed significantly, and the subtype exhibiting high expression of the CRGs had a better prognosis. Furthermore, we selected 34 CRGs that were highly correlated with the prognosis of gastric cancer. By constructing a multivariate Cox proportional-hazards model and a hazard scoring system, we were able to categorize patients into high- and low-risk groups based on their hazard score. K-M analysis demonstrated a significant survival disadvantage in the high-risk group. Based on Lasso regression analysis, we screened 16 signature genes, a multivariate logistic regression model [cutoff: 0.149 (0.000, 0.974), AUC:0.987] and a prognosis network diagram was constructed and their prediction efficiency for gastric cancer prognostic diagnosis was well validated. According to the signature genes, the patients were separated to two signature subtypes. We found that patients with higher CRGs expression and better prognosis had lower levels of immune infiltration. Finally, according to the results of drug susceptibility analysis, docetaxel, 5-Fluorouracil, gemcitabin, and paclitaxel were found to be more sensitive to gastric cancer.
    Type of Medium: Online Resource
    ISSN: 2296-634X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2737824-X
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  • 2
    In: Frontiers in Immunology, Frontiers Media SA, Vol. 13 ( 2022-3-8)
    Abstract: Glypican 2 (GPC2), a member of glypican (GPC) family genes, produces proteoglycan with a glycosylphosphatidylinositol anchor. It has shown its ascending significance in multiple cancers such as neuroblastoma, malignant brain tumor, and small-cell lung cancer. However, no systematic pan-cancer analysis has been conducted to explore its function in diagnosis, prognosis, and immunological prediction. Methods By comprehensive use of datasets from The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), Genotype-Tissue Expression Project (GTEx), cBioPortal, Human Protein Atlas (HPA), UALCAN, StarBase, and Comparative Toxicogenomics Database (CTD), we adopted bioinformatics methods to excavate the potential carcinogenesis of GPC2, including dissecting the correlation between GPC2 and prognosis, gene mutation, immune cell infiltration, and DNA methylation of different tumors, and constructed the competing endogenous RNA (ceRNA) networks of GPC2 as well as explored the interaction of GPC2 with chemicals and genes. Results The results indicated that GPC2 was highly expressed in most cancers, except in pancreatic adenocarcinoma, which presented at a quite low level. Furthermore, GPC2 showed the early diagnostic value in 16 kinds of tumors and was positively or negatively associated with the prognosis of different tumors. It also verified that GPC2 was a gene associated with most immune-infiltrating cells in pan-cancer, especially in thymoma. Moreover, the correlation with GPC2 expression varied depending on the type of immune-related genes. Additionally, GPC2 gene expression has a correlation with DNA methylation in 20 types of cancers. Conclusion Through pan-cancer analysis, we discovered and verified that GPC2 might be useful in cancer detection for the first time. The expression level of GPC2 in a variety of tumors is significantly different from that of normal tissues. In addition, the performance of GPC2 in tumorigenesis and tumor immunity also confirms our conjecture. At the same time, it has high specificity and sensitivity in the detection of cancers. Therefore, GPC2 can be used as an auxiliary indicator for early tumor diagnosis and a prognostic marker for many types of tumors.
    Type of Medium: Online Resource
    ISSN: 1664-3224
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2606827-8
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