DataSheet_1_Cancer cell immunity-related protein co-expression networks are associated with early-stage solid-predominant lung adenocarcinoma.pdf

BackgroundSolid-predominant lung adenocarcinoma (SPA), which is one of the high-risk subtypes with poor prognosis and unsatisfactory response to chemotherapy and targeted therapy in lung adenocarcinoma, remains molecular profile unclarified. Weighted correlation network analysis (WGCNA) was used for data mining, especially for studying biological networks based on pairwise correlations between variables. This study aimed to identify disease-related protein co-expression networks associated with early-stage SPA.MethodsWe assessed cancerous cells laser-microdissected from formalin-fixed paraffin-embedded (FFPE) tissues of a SPA group (n = 5), referencing a low-risk subtype, a lepidic predominant subtype group (LPA) (n = 4), and another high-risk subtype, micropapillary predominant subtype (MPA) group (n = 3) and performed mass spectrometry-based proteomic analysis. Disease-related co-expression networks associated with the SPA subtype were identified by WGCNA and their upstream regulators and causal networks were predicted by Ingenuity Pathway Analysis.ResultsAmong the forty WGCNA network modules identified, two network modules were found to be associated significantly with the SPA subtype. Canonical enriched pathways were highly associated with cellular growth, proliferation, and immune response. Upregulated HLA class I molecules HLA-G and HLA-B implicated high mutation burden and T cell activation in the SPA subtype. Upstream analysis implicated the involvement of highly activated oncogenic regulators, MYC, MLXIPL, MYCN, the redox master regulator NFE2L2, and the highly inhibited LARP1, leading to oncogenic IRES-dependent translation, and also regulators of the adaptive immune response, including highly activated IFNG, TCRD, CD3-TCR, CD8A, CD8B, CD3, CD80/CD86, and highly inhibited LILRB2. Interestingly, the immune checkpoint molecule HLA-G, which is the counterpart of LILRB2, was highly expressed characteristically in the SPA subtype and might be associated with antitumor immunity.ConclusionOur findings provide a disease molecular profile based on protein co-expression networks identified for the high-risk solid predominant adenocarcinoma, which will help develop future therapeutic strategies.

背景：实体型肺腺癌（SPA），作为肺腺癌中预后不良且对化疗和靶向治疗反应不满意的危重型亚型之一，其分子特征尚不明确。加权相关网络分析（WGCNA）被应用于数据挖掘，特别是在研究基于变量成对相关性的生物网络方面。本研究旨在识别与早期SPA相关的疾病相关蛋白共表达网络。方法：本研究评估了来自SPA组（n=5）石蜡包埋组织（FFPE）的癌变细胞的激光显微切割，并参考低风险亚型（LPA组，n=4）和另一高危亚型（MPA组，n=3）进行质谱蛋白质组学分析。通过WGCNA识别与SPA亚型相关的疾病相关共表达网络，并利用Ingenuity Pathway Analysis预测其上游调控器和因果网络。结果：在确定的四十个WGCNA网络模块中，发现两个网络模块与SPA亚型显著相关。经典富集通路与细胞生长、增殖和免疫反应高度相关。上调的HLA I类分子HLA-G和HLA-B暗示了SPA亚型中高突变负荷和T细胞激活。上游分析表明高度激活的致癌调控因子，包括MYC、MLXIPL、MYCN、氧化还原主调节因子NFE2L2以及高度抑制的LARP1，导致致癌性IRES依赖性翻译，以及适应性免疫反应的调节因子，包括高度激活的IFNG、TCRD、CD3-TCR、CD8A、CD8B、CD3、CD80/CD86和高度抑制的LILRB2。有趣的是，免疫检查点分子HLA-G，作为LILRB2的对应物，在SPA亚型中特异性高表达，可能与抗肿瘤免疫相关。结论：本研究基于识别的高危实体型腺癌蛋白共表达网络，构建了疾病分子特征，这将为未来治疗策略的开发提供帮助。