背景:结直肠癌(CRC)的特征是恶性程度高,预后困难。癌症的一个重要方面是代谢重编程,其中乳酸作为一种关键的代谢产物,有助于癌症和肿瘤微环境(TME)的发展。目前的研究表明,乳酸在CRC的进展中起着重要作用。然而,乳酸与肿瘤微环境之间的关系仍未得到充分研究,强调乳酸作为一种新型生物标志物的潜力。
方法:我们从癌症基因组图谱(TCGA)中获取了结直肠癌(CRC)患者的转录组数据,国际癌症基因组联盟(ICGC),和基因表达综合(GEO)门户网站,以及相应的临床信息。利用单变量Cox回归和LASSO回归分析,我们鉴定了与CRC预后相关的乳酸代谢相关的基因.随后,我们建立了基于多因素Cox回归的模型。为了评估肿瘤突变负荷(TMB)之间的相关性,肿瘤微环境(TME),乳酸评分与患者生存率的关系,我们进行了基因集富集分析(GSEA)和免疫原性特征分析.
结果:使用3个乳酸代谢相关基因(LMRGs)(SLC16A8,GATA1和PYGL)构建模型,根据患者的乳酸评分将患者分为2个亚组。2个亚组之间的差异基因的功能主要富集在细胞周期和mRNA分裂,而高分亚组患者预后较差。此外,高评分组的TMB和LMRGs评分之间存在显著正相关(P=0.003,r2=0.12).最后,LMRGs也反映了TME的特点,两个亚组之间的免疫细胞和免疫检查点存在差异。
结论:LMRGs可作为预测CRC患者预后生存和评估TME的一个有前景的生物标志物。
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BACKGROUND: Colorectal cancer (
CRC) is characterized by its high malignancy and challenging prognosis. A significant aspect of cancer is metabolic reprogramming, where lactate serves as a crucial metabolite that contributes to the development of cancer and the tumor microenvironment (TME). Current studies have indicated that lactate plays a significant role in the progression of
CRC. However, the relationship between lactate and the tumor microenvironment remains understudied, underscoring the potential of lactate as a novel biomarker.
METHODS: We sourced transcriptomic data for colorectal cancer (
CRC) patients from The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), and the Gene Expression Omnibus (GEO) portals, along with the corresponding clinical information. Utilizing univariate Cox regression in conjunction with LASSO regression analysis, we identified genes involved in lactate metabolism that are associated with
CRC prognosis. Subsequently, we developed models based on multi-factor Cox regression. To evaluate the correlation between tumor mutational burden (TMB), tumor microenvironment (TME), and lactate scores with patient survival, we conducted gene set enrichment analysis (GSEA) and immunogenic signature analyses.
RESULTS: 3 lactate metabolism-related genes (LMRGs) (SLC16A8, GATA1, and PYGL) were used to construct models that categorized patients into 2 subgroups based on their lactate scores. The function of the differential genes between the 2 subgroups was mainly enriched in cell cycle and mRNA division, and the prognosis of patients in the high score subgroup was poor. Furthermore, a significant positive correlation was observed between TMB and LMRGs scores in the high-scoring group (P = 0.003, r2 = 0.12). Lastly, LMRGs also reflected the characteristics of TME, with differences in immune cells and immune checkpoints between the 2 subgroups.
CONCLUSIONS: LMRGs may serve as a promising biomarker for predicting prognostic survival in
CRC patients and to assess the TME.
不适用.