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Abstract：
Colorectal cancer (CRC) is a malignancy of the digestive system with high incidence rate and mortality, and reliable diagnostic and prognostic markers for CRC are still lacking. Glutamine metabolism is crucial to the occurrence and development of CRC. However, no research has systematically analyzed the biological role of glutamine metabolism-related genes (GMRGs) in CRC.
We downloaded gene expression data and clinical data of CRC patients from the TCGA database. The UCSC database downloads pan-cancer gene expression data and prognosis data. Characteristic GMRGs were screened out using differential analysis and two types of machine learning (SVM-REF and RandomForest). Single-cell RNA-sequencing data from CRC patients were downloaded from GEO data. ROC curve was used to evaluate the diagnostic value. Kaplan-Meier method and univariate Cox regression analysis were used to evaluate the prognostic value. The oncopredict package is used to calculate IC50 values for common drugs in CRC patients.
A total of 31 differentially expressed GMRGs were identified, 9 of which were identified as characteristic GMRGs. Further evaluation of diagnostic and prognostic value finally identified GPT as the most important GMRGs in CRC. scRNA-seq analysis revealed that GPT is almost exclusively expressed in epithelial cells. GPT expression is closely related to the tumor microenvironment and can effectively distinguish the sensitivity of different CRC patients to clinical drugs. In addition, pan-cancer analysis showed that GPT is an excellent diagnostic and prognostic marker for multiple cancers.
GPT is a reliable diagnostic, prognostic marker and therapeutic target in CRC.
We downloaded gene expression data and clinical data of CRC patients from the TCGA database. The UCSC database downloads pan-cancer gene expression data and prognosis data. Characteristic GMRGs were screened out using differential analysis and two types of machine learning (SVM-REF and RandomForest). Single-cell RNA-sequencing data from CRC patients were downloaded from GEO data. ROC curve was used to evaluate the diagnostic value. Kaplan-Meier method and univariate Cox regression analysis were used to evaluate the prognostic value. The oncopredict package is used to calculate IC50 values for common drugs in CRC patients.
A total of 31 differentially expressed GMRGs were identified, 9 of which were identified as characteristic GMRGs. Further evaluation of diagnostic and prognostic value finally identified GPT as the most important GMRGs in CRC. scRNA-seq analysis revealed that GPT is almost exclusively expressed in epithelial cells. GPT expression is closely related to the tumor microenvironment and can effectively distinguish the sensitivity of different CRC patients to clinical drugs. In addition, pan-cancer analysis showed that GPT is an excellent diagnostic and prognostic marker for multiple cancers.
GPT is a reliable diagnostic, prognostic marker and therapeutic target in CRC.
摘要：
背景：结直肠癌（CRC）是消化系统的恶性肿瘤，发病率和死亡率高，目前仍缺乏可靠的CRC诊断和预后标志物。谷氨酰胺代谢对CRC的发生发展至关重要。然而,目前尚无研究系统分析谷氨酰胺代谢相关基因(GMRGs)在CRC中的生物学作用.
方法：我们从TCGA数据库下载了CRC患者的基因表达数据和临床数据。UCSC数据库下载泛癌基因表达数据和预后数据。使用差异分析和两种类型的机器学习(SVM-REF和RandomForest)筛选出特征GMRG。从GEO数据下载来自CRC患者的单细胞RNA测序数据。采用ROC曲线评价诊断价值。采用Kaplan-Meier法和单因素Cox回归分析评价预后价值。共轴预测软件包用于计算CRC患者常用药物的IC50值。
结果：共鉴定出31个差异表达的GMRGs，其中9个被鉴定为特征性GMRG。对诊断和预后价值的进一步评估最终确定GPT是CRC中最重要的GMRG。scRNA-seq分析显示GPT几乎只在上皮细胞中表达。GPT表达与肿瘤微环境密切相关,能有效区分不同CRC患者对临床药物的敏感性。此外,泛癌症分析显示,GPT是多种癌症的优秀诊断和预后标志物.
结论：GPT是一种可靠的诊断，CRC的预后标志物和治疗靶点。
方法：我们从TCGA数据库下载了CRC患者的基因表达数据和临床数据。UCSC数据库下载泛癌基因表达数据和预后数据。使用差异分析和两种类型的机器学习(SVM-REF和RandomForest)筛选出特征GMRG。从GEO数据下载来自CRC患者的单细胞RNA测序数据。采用ROC曲线评价诊断价值。采用Kaplan-Meier法和单因素Cox回归分析评价预后价值。共轴预测软件包用于计算CRC患者常用药物的IC50值。
结果：共鉴定出31个差异表达的GMRGs，其中9个被鉴定为特征性GMRG。对诊断和预后价值的进一步评估最终确定GPT是CRC中最重要的GMRG。scRNA-seq分析显示GPT几乎只在上皮细胞中表达。GPT表达与肿瘤微环境密切相关,能有效区分不同CRC患者对临床药物的敏感性。此外,泛癌症分析显示,GPT是多种癌症的优秀诊断和预后标志物.
结论：GPT是一种可靠的诊断，CRC的预后标志物和治疗靶点。
