AUTHOR=Zou Qiyuan , Lv Yufeng , Gan Zuhuan , Liao Shulan , Liang Zhonghui 

TITLE=Identification and Validation of a Malignant Cell Subset Marker-Based Polygenic Risk Score in Stomach Adenocarcinoma Through Integrated Analysis of Bulk and Single-Cell RNA Sequencing Data

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 9 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2021.720649

DOI=10.3389/fcell.2021.720649

ISSN=2296-634X

ABSTRACT=Background: Recently, single-cell RNA-seq (scRNA-seq) highlights intra-tumoral heterogeneity (ITH) with identification of malignant cell subpopulations and their marker genes. Whether these cell subpopulation marker genes associated with prognosis remain elusive in stomach adenocarcinoma (STAD).
Methods: We firstly identified malignant and non-malignant cell markers from three bulk RNA expression profiles. High-quality cells in an early STAD scRNA-seq profile were identified as malignant and non-malignant cells, and the malignant cell were subjected to dimension reduction, cell clustering, pseudotime analysis and gene set enrichment analysis. The marker genes of each malignant cell cluster were used to create a polygenic risk score (PRS). Combined with the PRS and routine clinicopathological characteristics, a nomogram tool was generated to predict prognosis of STAD. In addition, an independent external data set is used to validated the PRS.
Results：The malignant cells were divided into eight clusters with different marker genes and biological characteristics. Pseudotime analysis shows the potential differentiation trajectory of these eight malignant cell clusters and identified genes that affect cell differentiation. Four-malignant cell marker-based PRS is associated with both overall survival and progression-free survival, an independent prognostic factor, could successfully divide patients with STAD into high- and low-risk groups, and validated in an external data set. Combined with the PRS and routine clinicopathological characteristics, a nomogram tool was generated to help predict the survival of patients with STAD.
Conclusion: We revealed limited but significant ITH in STAD and proposed a cell marker-based PRS through integrated analysis of bulk sequencing and scRNA-seq analysis.