空间代谢组学可识别肺鳞状细胞癌患者的不同肿瘤特异性和基质特异性亚型。
Spatial metabolomics identifies distinct tumor-specific and stroma-specific subtypes in patients with lung squamous cell carcinoma.
发表日期:2023 Nov 02
作者:
Jun Wang, Na Sun, Thomas Kunzke, Jian Shen, Philipp Zens, Verena M Prade, Annette Feuchtinger, Sabina Berezowska, Axel Walch
来源:
npj Precision Oncology
摘要:
肺鳞状细胞癌(LUSC)的分子亚型已在基因组、转录组和蛋白质组水平上进行。然而,基于组织代谢组学的LUSC分层仍然缺乏。将高分辨率成像质谱与共识聚类相结合,在 330 名 LUSC 患者中鉴定出了具有不同代谢模式的四种肿瘤特异性亚型和四种基质特异性亚型。第一个肿瘤亚型 T1 与 DNA 损伤和免疫学特征(包括 CD3、CD8 和 PD-L1)呈负相关。相同的特征与肿瘤亚型T2呈正相关。 T4 肿瘤亚型与 PD-L1 高表达相关。与T1和T4亚型相比,T3亚型患者的预后改善,T3是UICC分期的独立预后因素。同样,基质亚型与不同的免疫学特征和代谢途径相关。基质亚型 S4 的预后优于 S2。随后,基于接受新辅助治疗的独立 LUSC 队列的分析表明,S2 基质亚型与化疗耐药相关。通过基于组织的空间代谢组学确定的临床相关患者亚型是对现有分子分类系统的有价值的补充。亚型之间的代谢差异及其与免疫学特征的关联可能有助于改善个性化治疗。© 2023。作者。
Molecular subtyping of lung squamous cell carcinoma (LUSC) has been performed at the genomic, transcriptomic, and proteomic level. However, LUSC stratification based on tissue metabolomics is still lacking. Combining high-mass-resolution imaging mass spectrometry with consensus clustering, four tumor- and four stroma-specific subtypes with distinct metabolite patterns were identified in 330 LUSC patients. The first tumor subtype T1 negatively correlated with DNA damage and immunological features including CD3, CD8, and PD-L1. The same features positively correlated with the tumor subtype T2. Tumor subtype T4 was associated with high PD-L1 expression. Compared with the status of subtypes T1 and T4, patients with subtype T3 had improved prognosis, and T3 was an independent prognostic factor with regard to UICC stage. Similarly, stroma subtypes were linked to distinct immunological features and metabolic pathways. Stroma subtype S4 had a better prognosis than S2. Subsequently, analyses based on an independent LUSC cohort treated by neoadjuvant therapy revealed that the S2 stroma subtype was associated with chemotherapy resistance. Clinically relevant patient subtypes as determined by tissue-based spatial metabolomics are a valuable addition to existing molecular classification systems. Metabolic differences among the subtypes and their associations with immunological features may contribute to the improvement of personalized therapy.© 2023. The Author(s).