Molecular Medicine Division, Translational Genomics Research Institute, 445 N. Fifth St., Phoenix, AZ, 85004, USA.
HonorHealth Research Institute, Scottsdale, AZ, USA.
Genome Med. 2020 Sep 29;12(1):80. doi: 10.1186/s13073-020-00776-9.
Solid tumors such as pancreatic ductal adenocarcinoma (PDAC) comprise not just tumor cells but also a microenvironment with which the tumor cells constantly interact. Detailed characterization of the cellular composition of the tumor microenvironment is critical to the understanding of the disease and treatment of the patient. Single-cell transcriptomics has been used to study the cellular composition of different solid tumor types including PDAC. However, almost all of those studies used primary tumor tissues.
In this study, we employed a single-cell RNA sequencing technology to profile the transcriptomes of individual cells from dissociated primary tumors or metastatic biopsies obtained from patients with PDAC. Unsupervised clustering analysis as well as a new supervised classification algorithm, SuperCT, was used to identify the different cell types within the tumor tissues. The expression signatures of the different cell types were then compared between primary tumors and metastatic biopsies. The expressions of the cell type-specific signature genes were also correlated with patient survival using public datasets.
Our single-cell RNA sequencing analysis revealed distinct cell types in primary and metastatic PDAC tissues including tumor cells, endothelial cells, cancer-associated fibroblasts (CAFs), and immune cells. The cancer cells showed high inter-patient heterogeneity, whereas the stromal cells were more homogenous across patients. Immune infiltration varies significantly from patient to patient with majority of the immune cells being macrophages and exhausted lymphocytes. We found that the tumor cellular composition was an important factor in defining the PDAC subtypes. Furthermore, the expression levels of cell type-specific markers for EMT cancer cells, activated CAFs, and endothelial cells significantly associated with patient survival.
Taken together, our work identifies significant heterogeneity in cellular compositions of PDAC tumors and between primary tumors and metastatic lesions. Furthermore, the cellular composition was an important factor in defining PDAC subtypes and significantly correlated with patient outcome. These findings provide valuable insights on the PDAC microenvironment and could potentially inform the management of PDAC patients.
实体瘤,如胰腺导管腺癌(PDAC),不仅包含肿瘤细胞,还包含与肿瘤细胞不断相互作用的微环境。详细描述肿瘤微环境的细胞组成对于理解疾病和治疗患者至关重要。单细胞转录组学已被用于研究包括 PDAC 在内的不同实体瘤类型的细胞组成。然而,几乎所有这些研究都使用了原发性肿瘤组织。
在这项研究中,我们使用单细胞 RNA 测序技术对来自 PDAC 患者的分离原发性肿瘤或转移性活检组织中的单个细胞的转录组进行了分析。无监督聚类分析以及一种新的有监督分类算法 SuperCT 被用于鉴定肿瘤组织中的不同细胞类型。然后比较了原发性肿瘤和转移性活检组织中不同细胞类型的表达特征。使用公共数据集,还将细胞类型特异性特征基因的表达与患者生存相关联。
我们的单细胞 RNA 测序分析揭示了原发性和转移性 PDAC 组织中的不同细胞类型,包括肿瘤细胞、内皮细胞、癌症相关成纤维细胞(CAF)和免疫细胞。癌细胞表现出高度的患者间异质性,而基质细胞在患者间更为同质。免疫浸润在患者间差异显著,大多数免疫细胞为巨噬细胞和耗竭淋巴细胞。我们发现肿瘤细胞组成是定义 PDAC 亚型的重要因素。此外,EMT 肿瘤细胞、激活的 CAF 和内皮细胞的细胞类型特异性标志物的表达水平与患者生存显著相关。
综上所述,我们的工作确定了 PDAC 肿瘤和原发性肿瘤与转移性病变之间的细胞组成存在显著异质性。此外,细胞组成是定义 PDAC 亚型的重要因素,并与患者预后显著相关。这些发现为 PDAC 微环境提供了有价值的见解,并可能为 PDAC 患者的管理提供信息。