Li Chenyang, Nguyen Thinh T, Li Jian-Rong, Song Xingzhi, Fujimoto Junya, Little Latasha, Gumb Curtis, Chow Chi-Wan B, Wistuba Ignacio I, Futreal Andrew P, Zhang Jianhua, Hubert Shawna M, Heymach John V, Wu Jia, Amos Christopher I, Zhang Jianjun, Cheng Chao
Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center UTHealth Houston, Houston, TX, 77030, USA.
NPJ Precis Oncol. 2024 Oct 5;8(1):225. doi: 10.1038/s41698-024-00680-0.
Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic models. In this study, we used multiregional RNA-seq data (880 tumor samples from 350 individuals) from both public (TRACERx) and internal (MDAMPLC) cohorts to investigate the effect of RNA-ITH on prognosis in localized NSCLC at the gene, signature, and tumor microenvironment levels. At the gene level, the maximal expression of hazardous genes (expression negatively associated with survival) but the minimal expression of protective genes (expression positively associated with survival) across different regions within a tumor were more prognostic than the average expression. Following that, we examined whether multiregional expression profiling can improve the performance of prognostic signatures. We investigated 11 gene signatures collected from previous publications and one signature developed in this study. For all of them, the prognostic prediction accuracy can be significantly improved by converting the regional expression of signature genes into sample-specific expression with a simple function-taking the maximal expression of hazardous genes and the minimal expression of protective genes. In the tumor microenvironment, we found a similar rule also seems applicable to immune ITH. We calculated the infiltration levels of major immune cell types in each region of a sample based on expression deconvolution. Prognostic analysis indicated that the region with the lowest infiltration level of protective or highest infiltration level of hazardous immune cells determined the prognosis of NSCLC patients. Our study highlighted the impact of RNA-ITH on the prognostication of NSCLC, which should be taken into consideration to optimize the design and application of expression-based prognostic biomarkers and models. Multiregional assays have the great potential to significantly improve their applications to prognostic stratification.
肺癌仍然是美国乃至全球癌症死亡的主要原因。非小细胞肺癌（NSCLC）存在高度的转录组肿瘤内异质性（RNA-ITH），这限制了基于表达的预后模型的可重复性。在本研究中，我们使用了来自公共队列（TRACERx）和内部队列（MDAMPLC）的多区域RNA测序数据（来自350名个体的880个肿瘤样本），以研究RNA-ITH在局部NSCLC的基因、特征和肿瘤微环境水平上对预后的影响。在基因水平上，肿瘤内不同区域中有害基因的最大表达（表达与生存呈负相关）以及保护基因的最小表达（表达与生存呈正相关）比平均表达更具预后意义。在此之后，我们研究了多区域表达谱分析是否能提高预后特征的性能。我们调查了从先前出版物中收集的11个基因特征以及本研究中开发的一个特征。对于所有这些特征，通过使用一个简单的函数（取有害基因的最大表达和保护基因的最小表达）将特征基因的区域表达转换为样本特异性表达，预后预测准确性可以得到显著提高。在肿瘤微环境中，我们发现类似的规则似乎也适用于免疫ITH。我们基于表达反卷积计算了样本每个区域中主要免疫细胞类型的浸润水平。预后分析表明，保护免疫细胞浸润水平最低或有害免疫细胞浸润水平最高的区域决定了NSCLC患者的预后。我们的研究强调了RNA-ITH对NSCLC预后的影响，在优化基于表达的预后生物标志物和模型的设计与应用时应予以考虑。多区域检测在显著改善其在预后分层中的应用方面具有巨大潜力。
