Yang Lu, Tan Peixin, Sun Hengwen, Zeng Zijun, Pan Yi
Department of Radiation Oncology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Front Oncol. 2022 Apr 27;12:874731. doi: 10.3389/fonc.2022.874731. eCollection 2022.
The outcomes of some breast cancer patients remain poor due to being susceptible to recurrence, metastasis and drug resistance, and lactate metabolism has been described as a hallmark of cancer and a contributor to cancer progression and immune escape. Hence, it is worthy of seeking potentially novel biomarkers from lactate metabolism relevant perspectives for this particular cohort of patients. In this context, 205 available lactate metabolism-related genes (LMGs) were obtained by a search of multiple genesets, and the landscape of somatic mutation, copy number variation, and mRNA expression levels was investigated among these genes. Crucially, 9 overall survival-related LMGs were identified through univariate Cox regression analysis in The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases. Subsequently, a prognostic signature, defined as Lactate Metabolism Index (LMI), was established with 5 OS-related LMGs using Least Absolute Shrinkage and Selection Operator (LASSO) Cox hazard regression analysis in TCGA training set, and then validated in two external cohorts (METABRIC and GSE96058). From the comprehensive results, breast cancer patients with high LMI had considerably poorer survival probability across all cohorts, and the degree of clinical features tended to be more severe as the LMI value increased. Furthermore, a prognostic nomogram incorporating LMI, age, and AJCC stage was constructed and demonstrated great prediction performance for OS of breast cancer patients, which was evaluated by the calibration plot and the decision curve analysis. Moreover, the potential effect of different LMI values on levels of immune checkpoints, tumor-infiltrating immune cells, and cytokines were explored ultimately, and patients with higher LMI values might gain an immunosuppressive tumor microenvironment that contributed to immune escape of breast cancer and inferior prognosis. Collectively, all findings in the study indicated the potential prognostic value of LMI in breast cancer, providing further implications for the role of lactate metabolism in breast cancer prognosis, tumor immune microenvironment, and immunotherapy.
由于一些乳腺癌患者易复发、转移和产生耐药性,其预后仍然较差,而乳酸代谢已被描述为癌症的一个标志以及癌症进展和免疫逃逸的一个促成因素。因此,从乳酸代谢相关角度为这一特定患者群体寻找潜在的新型生物标志物是值得的。在此背景下,通过搜索多个基因集获得了205个可用的乳酸代谢相关基因(LMGs),并研究了这些基因中的体细胞突变、拷贝数变异和mRNA表达水平情况。至关重要的是,通过在癌症基因组图谱(TCGA)和国际乳腺癌分子分类联盟(METABRIC)数据库中进行单变量Cox回归分析,确定了9个与总生存相关的LMGs。随后,在TCGA训练集中使用最小绝对收缩和选择算子(LASSO)Cox风险回归分析,用5个与总生存相关的LMGs建立了一个预后特征,定义为乳酸代谢指数(LMI),然后在两个外部队列(METABRIC和GSE96058)中进行验证。从综合结果来看,LMI高的乳腺癌患者在所有队列中的生存概率明显更差,并且随着LMI值的增加,临床特征的严重程度往往更高。此外,构建了一个包含LMI、年龄和美国癌症联合委员会(AJCC)分期的预后列线图,该列线图对乳腺癌患者的总生存显示出良好的预测性能,通过校准图和决策曲线分析进行了评估。此外,最终探索了不同LMI值对免疫检查点水平、肿瘤浸润免疫细胞和细胞因子的潜在影响,LMI值较高的患者可能获得一个免疫抑制性肿瘤微环境,这有助于乳腺癌的免疫逃逸和较差的预后。总体而言,该研究中的所有发现表明LMI在乳腺癌中的潜在预后价值,为乳酸代谢在乳腺癌预后、肿瘤免疫微环境和免疫治疗中的作用提供了进一步的启示。