Construction of an immune infiltration landscape based on immune-related genes in cervical cancer. (July 2022)
- Record Type:
- Journal Article
- Title:
- Construction of an immune infiltration landscape based on immune-related genes in cervical cancer. (July 2022)
- Main Title:
- Construction of an immune infiltration landscape based on immune-related genes in cervical cancer
- Authors:
- Yang, Yongli
Wang, Nana
Shi, Xuezhong
Wang, Yuping
Yang, Chaojun
Fan, Jingwen
Jia, Xiaocan - Abstract:
- Abstract: Clinical trials demonstrated that immunotherapy improved the prognosis of patients with cervical cancer (CC), which is strongly associated with immune infiltration landscape. We aimed to comprehensively analyze the immune infiltration landscape and provide directions for immunotherapy of CC. The study was based on the Cancer Genome Atlas (TCGA) database and utilized immune-related genes (IRGs) to identify heterogeneous immune subtypes. The ESTIMATE and CIBERSORT algorithms were performed to unravel the landscape of the tumor immune microenvironment. The IRGs score was constructed by principal component analysis. Then, we analyzed the differences in immune-related characteristics and prognosis between high and low IRGs score groups. An independent immunotherapy cohort (IMvigor210) was used to verify the reliability and stability of the IRGs score. Herein, a total of 272 TCGA-CC samples were divided into high (n = 199) and low (n = 73) IRGs score groups. The infiltration of CD8 T cells, memory resting CD4 T cells, and memory activated CD4 T cells, as well as better prognostic outcomes, mainly exhibited in the low IRGs score group and gene cluster A. GSEA analysis showed that JAK/STAT and VEGF signaling pathways were activated in the low IRGs score group. In contrast, the high IRGs score group with least lymphocyte infiltration may contribute to the poor prognosis. The prognosis of the IMvigor210 cohort was still significantly different between high and low IRGs scoreAbstract: Clinical trials demonstrated that immunotherapy improved the prognosis of patients with cervical cancer (CC), which is strongly associated with immune infiltration landscape. We aimed to comprehensively analyze the immune infiltration landscape and provide directions for immunotherapy of CC. The study was based on the Cancer Genome Atlas (TCGA) database and utilized immune-related genes (IRGs) to identify heterogeneous immune subtypes. The ESTIMATE and CIBERSORT algorithms were performed to unravel the landscape of the tumor immune microenvironment. The IRGs score was constructed by principal component analysis. Then, we analyzed the differences in immune-related characteristics and prognosis between high and low IRGs score groups. An independent immunotherapy cohort (IMvigor210) was used to verify the reliability and stability of the IRGs score. Herein, a total of 272 TCGA-CC samples were divided into high (n = 199) and low (n = 73) IRGs score groups. The infiltration of CD8 T cells, memory resting CD4 T cells, and memory activated CD4 T cells, as well as better prognostic outcomes, mainly exhibited in the low IRGs score group and gene cluster A. GSEA analysis showed that JAK/STAT and VEGF signaling pathways were activated in the low IRGs score group. In contrast, the high IRGs score group with least lymphocyte infiltration may contribute to the poor prognosis. The prognosis of the IMvigor210 cohort was still significantly different between high and low IRGs score groups ( P < 0.001). This study demonstrated that the IRGs score could be an independent prognostic biomarker and provide direction for tailoring immunotherapy strategies in the future clinical treatment. Highlights: This article constructed a novel IRGs scores based on IRGs by PCA. IRGs scores were applied to quantify the immune infiltration landscape of CC. High and low IRGs score groups showed differences in immune cell landscape. IRGs scores can be used to screen CC patients suitable for immunotherapy. … (more)
- Is Part Of:
- Computers in biology and medicine. Volume 146(2022)
- Journal:
- Computers in biology and medicine
- Issue:
- Volume 146(2022)
- Issue Display:
- Volume 146, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 146
- Issue:
- 2022
- Issue Sort Value:
- 2022-0146-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-07
- Subjects:
- Cervical cancer -- Immunotherapy -- Immune-related genes -- Immune cell infiltration -- Prognosis
Medicine -- Data processing -- Periodicals
Biology -- Data processing -- Periodicals
610.285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00104825/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compbiomed.2022.105638 ↗
- Languages:
- English
- ISSNs:
- 0010-4825
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.880000
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