大约 30% 的早期肺腺癌患者在成功手术切除后出现疾病进展。尽管在绘制遗传图谱方面做出了努力，但在发现疾病结果的预测生物标志物方面取得的成功有限。在这里，我们对 143 个肿瘤进行了系统的多组学评估，并匹配了肿瘤邻近、组织学正常的肺组织，并对患者进行了长期随访。通过对肿瘤和邻近正常组织的组织学、突变和转录组学分析，我们发现肿瘤邻近组织中的炎症基因特征是疾病进展的最强临床预测因子。单细胞转录组分析表明，与进展相关的炎症特征在免疫细胞和非免疫细胞中都有表达，单核细胞中的细胞类型特异性分析进一步改善了结果预测。对癌症基因组图谱中肿瘤邻近转录组数据的进一步分析验证了炎症特征与癌症较差结果之间的关联。总的来说，我们的研究表明，肿瘤邻近组织的分子分析可以识别疾病进展高风险的患者。© 2023。Springer Nature Limited。

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.© 2023. Springer Nature Limited.