Pan-cancer analysis of GALNTs expression identifies a prognostic of GALNTs feature in low grade glioma
Pan-cancer analysis of GALNTs expression identifies a prognostic of GALNTs feature in low grade glioma
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GALNT 表达的泛癌分析确定了低级别胶质瘤中 GALNT 特征的预后。
DOI：
10.1002/jlb.5ma1221-468r
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发表时间：
2022-01-24
影响因子：
5.5
通讯作者：
Liao, Jing
中科院分区：
文献类型：
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作者：
Mao, Chengzhou;Zhuang, Shi-Min;Liao, Jing
多肽N-乙酰氨基半乳糖转移酶（GalNAc-Ts）是一组启动粘蛋白型O-糖基化的同工酶，已被证明在各种癌症类型中介导肿瘤生长和转移。然而，关于GalNAc-Ts的临床意义和特征的数据仍然很少。在这里，我们使用Oncomine和癌症基因组图谱（TCGA）数据库来分析GALNTs（N-乙酰氨基半乳糖转移酶基因）在泛癌症中的转录和生存效应。数据显示，GALNTs在各种人类癌症中异常表达，并与患者的临床结果显著相关。13种GALNTs的表达与脑低级别胶质瘤（LGG）患者的预后有关。此外，基于TCGA-LGG数据集中GALNT家族基因的表达谱，我们通过一致性聚类确定了2个分子亚型（cluster 1/2），并分析了肿瘤异质性。结果表明，第2组患者预后差，CD 8（+）T细胞、巨噬细胞和DC浸润，免疫检查点表达上调，肿瘤免疫功能障碍和排斥评分升高，提示GalNAc-Ts可能参与肿瘤免疫逃逸。此外，我们采用LASSO回归和时间依赖性ROC分析，利用TCGA-LGG数据集构建GALNTs相关的预后特征，然后使用2个外部队列验证该特征。总之，我们的研究成功地开发了一种新的LGG预后生物标志物，并为脑癌的个性化免疫治疗提供了基础。
Polypeptide N-acetylgalactosaminyltransferases (GalNAc-Ts), a group of isoenzymes that initiate mucin-type O-glycosylation, have been shown to mediate tumor growth and metastasis in various cancer types. However, data on the clinical significance and features of GalNAc-Ts remain scant. Here, we used Oncomine and The Cancer Genome Atlas (TCGA) databases to analyze the transcription and survival effect of GALNTs (N-acetylgalactosaminyltransferase genes) in pan-cancer. The data showed that the GALNTs were aberrantly expressed in various human cancers and significantly associated with patients' clinical outcomes. The expression of 13 GALNTs were correlated with prognosis in brain low grade glioma (LGG) patients. In addition, based on the expression profiles of GALNT family genes in TCGA-LGG dataset, we identified 2 molecular subtypes (cluster1/2) by consensus clustering and analyzed tumor heterogeneity. Our results demonstrated that cluster 2 group was associated with poor prognosis, CD8(+) T cells, macrophages and DCs infiltration, up-regulated expression of immune checkpoints, and higher tumor immune dysfunction and exclusion score, indicating that GalNAc-Ts might contribute to tumor immune escape. Furthermore, we employed LASSO regression and time-dependent ROC analysis to construct a GALNTs-related prognostic signature with the TCGA-LGG dataset, and then validated the signature using 2 external cohorts. Taken together, our study successfully developed a novel prognostic biomarker for LGG and provides a basis for personalized immunotherapy in brain cancer.