Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts.
Cancer Center and Dept. of Pathology, Massachusetts General Hospital, Boston, Massachusetts.
Cancer Res. 2022 Nov 2;82(21):3917-3931. doi: 10.1158/0008-5472.CAN-22-0432.
Lung adenocarcinoma (LUAD) is one of the most common cancer types and has various treatment options. Better biomarkers to predict therapeutic response are needed to guide choice of treatment modality and to improve precision medicine. Here, we used a consensus hierarchical clustering approach on 509 LUAD cases from The Cancer Genome Atlas to identify five robust LUAD expression subtypes. Genomic and proteomic data from patient samples and cell lines was then integrated to help define biomarkers of response to targeted therapies and immunotherapies. This approach defined subtypes with unique proteogenomic and dependency profiles. Subtype 4 (S4)-associated cell lines exhibited specific vulnerability to loss of CDK6 and CDK6-cyclin D3 complex gene (CCND3). Subtype 3 (S3) was characterized by dependency on CDK4, immune-related expression patterns, and altered MET signaling. Experimental validation showed that S3-associated cell lines responded to MET inhibitors, leading to increased expression of programmed death-ligand 1 (PD-L1). In an independent real-world patient dataset, patients with S3 tumors were enriched with responders to immune checkpoint blockade. Genomic features in S3 and S4 were further identified as biomarkers for enabling clinical diagnosis of these subtypes. Overall, our consensus hierarchical clustering approach identified robust tumor expression subtypes, and our subsequent integrative analysis of genomics, proteomics, and CRISPR screening data revealed subtype-specific biology and vulnerabilities. These LUAD expression subtypes and their biomarkers could help identify patients likely to respond to CDK4/6, MET, or PD-L1 inhibitors, potentially improving patient outcome.
Integrative analysis of multiomic and drug dependency data uncovers robust lung adenocarcinoma expression subtypes with unique therapeutic vulnerabilities and subtype-specific biomarkers of response.
肺腺癌(LUAD)是最常见的癌症类型之一,有多种治疗选择。需要更好的生物标志物来预测治疗反应,以指导治疗方式的选择,并提高精准医学的水平。在这里,我们使用共识层次聚类方法对来自癌症基因组图谱的 509 例 LUAD 病例进行分析,确定了 5 种稳健的 LUAD 表达亚型。然后整合来自患者样本和细胞系的基因组和蛋白质组数据,以帮助确定对靶向治疗和免疫治疗有反应的生物标志物。这种方法定义了具有独特的蛋白质组学和依赖性特征的亚型。亚型 4(S4)相关的细胞系表现出对 CDK6 和 CDK6-周期蛋白 D3 复合物基因(CCND3)缺失的特定脆弱性。亚型 3(S3)的特征是依赖 CDK4、免疫相关表达模式和改变的 MET 信号。实验验证表明,S3 相关的细胞系对 MET 抑制剂有反应,导致程序性死亡配体 1(PD-L1)的表达增加。在一个独立的真实世界患者数据集,S3 肿瘤患者对免疫检查点阻断的反应率更高。在 S3 和 S4 中发现的基因组特征进一步被确定为这些亚型的临床诊断的生物标志物。总的来说,我们的共识层次聚类方法确定了稳健的肿瘤表达亚型,我们随后对基因组学、蛋白质组学和 CRISPR 筛选数据的综合分析揭示了亚型特异性的生物学和脆弱性。这些 LUAD 表达亚型及其生物标志物可以帮助识别可能对 CDK4/6、MET 或 PD-L1 抑制剂有反应的患者,从而有可能改善患者的预后。
多组学和药物依赖性数据的综合分析揭示了具有独特治疗弱点和亚型特异性反应生物标志物的稳健肺腺癌表达亚型。