Characterization of gastric cancer stem-like molecular features, immune and pharmacogenomic landscapes. Issue 1 (24th September 2021)

• Record Type: Journal Article
• Authors: Wei, Chen; Chen, Mingkai; Deng, Wenying; Bie, Liangyu; Ma, Yijie; Zhang, Chi; Liu, Kangdong; Shen, Wei; Wang, Shuyi; Yang, Chaogang; Luo, Suxia; Li, Ning
• Is Part Of: Briefings in bioinformatics. Volume 23:Issue 1(2022)
• Publication Date: 2021-09-24
• Subjects: cancer stem cells -- gastric cancer -- tumor microenvironment -- immunotherapy -- tumor associated macrophage -- prognosis; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbab386
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: Cancer stem cells (CSCs) actively reprogram their tumor microenvironment (TME) to sustain a supportive niche, which may have a dramatic impact on prognosis and immunotherapy. However, our knowledge of the landscape of the gastric cancer stem-like cell (GCSC) microenvironment needs to be further improved. A multi-step process of machine learning approaches was performed to develop and validate the prognostic and predictive potential of the GCSC-related score (GCScore). The high GCScore subgroup was not only associated with stem cell characteristics, but also with a potential immune escape mechanism. Furthermore, we experimentally demonstrated the upregulated infiltration of CD206 + tumor-associated macrophages (TAMs) in the invasive margin region, which in turn maintained the stem cell properties of tumor cells. Finally, we proposed that the GCScore showed a robust capacity for prediction for immunotherapy, and investigated potential therapeutic targets and compounds for patients with a high GCScore. The results indicate that the proposed GCScore can be a promising predictor of prognosis and responses to immunotherapy, which provides new strategies for the precision treatment of GCSCs.