Stemness-related gene signature for predicting therapeutic response in patients with esophageal cancer

Shaojin Zhu; Gengxin Zhang; Qi You; Fei Li; Boying Ding; Feng Liu; De Bi; Lan Jiang

doi:10.21037/tcr-22-1723

Stemness-related gene signature for predicting therapeutic response in patients with esophageal cancer

Transl Cancer Res. 2022 Jul;11(7):2359-2373. doi: 10.21037/tcr-22-1723.

Authors

Shaojin Zhu¹, Gengxin Zhang¹, Qi You¹, Fei Li¹, Boying Ding¹, Feng Liu², De Bi³, Lan Jiang^{1

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Affiliations

¹ Department of Thoracic Surgery, The First Affiliated Hospital of Wannan Medical College (Yijishan Hospital of Wannan Medical College), Wuhu, China.
² Department of Thoracic Surgery, Lishui Branch of Zhongda Hospital Affiliated to Southeast University, Nanjing, China.
³ Suzhou Polytechnic Institute of Agriculture, Suzhou, China.
⁴ Key Laboratory of Non-Coding RNA Transformation Research of Anhui Higher Education Institution, Yijishan Hospital of Wannan Medical College, Wuhu, China.
⁵ Central Laboratory, Yijishan Hospital of Wannan Medical College, Wuhu, China.
⁶ Clinical Research Center for Critical Respiratory Medicine of Anhui Province, Wuhu, China.

Abstract

Background: Extensive research has indicated that tumor stemness promotes tumor progression. However, the underlying role of stemness-related genes (SRGs) in esophageal cancer (ESCA) remains unclear.

Methods: This study identified differentially expressed stemness-related (DESR) messenger RNAs (mRNAs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) in ESCA, and correlated them with the clinical features of patients with ESCA to develop a prognostic risk assessment model. Functional analysis, protein-protein interaction (PPI) analysis, competing endogenous RNA (ceRNA) networks, and tumor-infiltrating immune cell analyses were performed to corroborate the results obtained from the model.

Results: Correlation analysis of the stemness enrichment scores revealed 1,106 DESR genes (DESRGs), 84 DESRmiRNAs, and 320 DESRlncRNAs were identified from The Cancer Genome Atlas Esophageal Carcinoma (TCGA-ESCA) dataset. Network clustering was performed and the top 20 connection points were identified, including CDC20 that connects to 136 adjacent nodes. A ceRNA network was constructed, including 17 DESRmiRNAs, 44 DESRlncRNAs, and 55 DESRGs.

Conclusions: NCAPG [log₂fold change (FC) =1.81; q value =2.68×10^-11] was significantly upregulated in ESCA and positively correlated with resting natural killer (NK) cells, suggesting that human NK cells rest via the overexpression of NCAPG in ESCA. hsa-miR-1269a is significantly upregulated in ESCA patients with poor prognostic features. CD4⁺ resting memory T cells (P<0.01) were significantly negatively correlated with hsa-miR-1269a. The insights presented in this study will contribute to the development of innovative therapeutics for the treatment of patients with ESCA.

Keywords: Stemness; biomarker; esophageal cancer (ESCA); prognostic; survival.