Lehtiö Janne, Arslan Taner, Siavelis Ioannis, Pan Yanbo, Socciarelli Fabio, Berkovska Olena, Umer Husen M, Mermelekas Georgios, Pirmoradian Mohammad, Jönsson Mats, Brunnström Hans, Brustugun Odd Terje, Purohit Krishna Pinganksha, Cunningham Richard, Foroughi Asl Hassan, Isaksson Sofi, Arbajian Elsa, Aine Mattias, Karlsson Anna, Kotevska Marija, Gram Hansen Carsten, Drageset Haakensen Vilde, Helland Åslaug, Tamborero David, Johansson Henrik J, Branca Rui M, Planck Maria, Staaf Johan, Orre Lukas M
Department of Oncology and Pathology, Karolinska Institutet, SciLifeLab, Solna, Sweden.
Division of Oncology, Department of Clinical Sciences, Lund and CREATE Health Strategic Center for Translational Cancer Research, Lund University, Lund, Sweden.
Nat Cancer. 2021 Nov;2(11):1224-1242. doi: 10.1038/s43018-021-00259-9. Epub 2021 Nov 22.
Despite major advancements in lung cancer treatment, long-term survival is still rare, and a deeper understanding of molecular phenotypes would allow the identification of specific cancer dependencies and immune evasion mechanisms. Here we performed in-depth mass spectrometry (MS)-based proteogenomic analysis of 141 tumors representing all major histologies of non-small cell lung cancer (NSCLC). We identified six distinct proteome subtypes with striking differences in immune cell composition and subtype-specific expression of immune checkpoints. Unexpectedly, high neoantigen burden was linked to global hypomethylation and complex neoantigens mapped to genomic regions, such as endogenous retroviral elements and introns, in immune-cold subtypes. Further, we linked immune evasion with LAG3 via STK11 mutation-dependent HNF1A activation and FGL1 expression. Finally, we develop a data-independent acquisition MS-based NSCLC subtype classification method, validate it in an independent cohort of 208 NSCLC cases and demonstrate its clinical utility by analyzing an additional cohort of 84 late-stage NSCLC biopsy samples.
尽管肺癌治疗取得了重大进展,但长期生存仍然罕见,对分子表型的更深入理解将有助于识别特定的癌症依赖性和免疫逃逸机制。在此,我们对141例代表非小细胞肺癌(NSCLC)所有主要组织学类型的肿瘤进行了基于质谱(MS)的深入蛋白质基因组分析。我们鉴定出六种不同的蛋白质组亚型,它们在免疫细胞组成和免疫检查点的亚型特异性表达方面存在显著差异。出乎意料的是,高新生抗原负荷与整体低甲基化有关,并且在免疫冷亚型中,复杂的新生抗原映射到基因组区域,如内源性逆转录病毒元件和内含子。此外,我们通过STK11突变依赖的HNF1A激活和FGL1表达将免疫逃逸与LAG3联系起来。最后,我们开发了一种基于数据非依赖采集MS的NSCLC亚型分类方法,在208例NSCLC病例的独立队列中对其进行验证,并通过分析另外84例晚期NSCLC活检样本队列证明了其临床实用性。