Characterization of gastric cancer stem-like molecular features, immune and pharmacogenomic landscapes
Characterization of gastric cancer stem-like molecular features, immune and pharmacogenomic landscapes
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DOI:
10.1093/bib/bbab386
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发表时间:
2021-09
影响因子:
9.5
通讯作者:
Chen Wei;Mingkai Chen;W. Deng;L. Bie;Yijie Ma;Chi Zhang;Kangdong Liu;W. Shen;Shuyi Wang;Chaogang Yang;S. Luo;Ning Li
中科院分区:
文献类型:
--
作者:
Chen Wei;Mingkai Chen;W. Deng;L. Bie;Yijie Ma;Chi Zhang;Kangdong Liu;W. Shen;Shuyi Wang;Chaogang Yang;S. Luo;Ning Li
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.