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全面分析鉴定 PI3K/Akt 通路改变为接受免疫检查点抑制剂治疗的结肠腺癌患者的免疫相关预后生物标志物。

Comprehensive Analysis Identifies PI3K/Akt Pathway Alternations as an Immune-Related Prognostic Biomarker in Colon Adenocarcinoma Patients Receiving Immune Checkpoint Inhibitor Treatment.

机构信息

Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.

出版信息

J Immunol Res. 2022 Jun 6;2022:8179799. doi: 10.1155/2022/8179799. eCollection 2022.

DOI:10.1155/2022/8179799
PMID:35707003
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9192307/
Abstract

INTRODUCTION

In recent years, immune checkpoint inhibitors (ICIs) have attracted widespread attention and made breakthroughs in progress towards the treatment of various cancers. However, ICI therapy is selective, and its effects on many patients are not ideal. It is therefore critical to identify prognostic biomarkers of response to ICI therapy. The PI3K/Akt pathway plays important roles in tumor formation and metastasis. However, there are no published reports clarifying the relationship between PI3K/Akt pathway mutations and prognosis for colon adenocarcinoma (COAD) patients receiving immunotherapy.

METHODS

We collected data from a COAD cohort from The Cancer Genome Atlas (TCGA) database, including whole-exome sequencing (WES) data, RNA-seq data, and clinical data. We also collected data, including clinical prognosis and targeted sequencing data, from a cohort of COAD patients receiving immunotherapy. We collected 50 COAD patients (Local-COAD) from the Zhujiang Hospital of Southern Medical University and performed targeted sequencing. We analyzed the effects of PI3K/Akt pathway mutations on the patients' clinical prognosis, immunogenicity, and immune microenvironments. Gene set enrichment analysis (GSEA) was used to analyze the significantly upregulated and downregulated signaling pathways. We used these results to hypothesize potential mechanisms by which PI3K/Akt mutations could affect the prognosis of COAD patients.

RESULTS

Univariate and multivariate Cox analyses and Kaplan-Meier (KM) survival curves showed that patients with PI3K-Akt mutations had better overall survival (OS) than those without PI3K-Akt mutations. Genes with significant mutation rates in the two cohorts were screened by panoramic view. CIBERSORT was used to analyze changes in 22 types of immune cells to identify immune activated cells. Similarly, patients in the PI3K/Akt-mutated type (PI3K/Akt-MT) group had significantly increased immunogenicity, including increases in tumor mutation burden (TMB), neoantigen load (NAL), and MANTIS score. Using GSEA, we identified upregulated pathways related to immune response.

CONCLUSION

PI3K/Akt pathway mutation status can be used as an independent predictor of response to ICI treatment in COAD patients. PI3K/Akt mutations are correlated with improved OS, higher immunogenicity, greater immune response scores, and increases in activated immune cells.

摘要

简介

近年来,免疫检查点抑制剂(ICI)在治疗各种癌症方面的研究取得了突破性进展,受到了广泛关注。然而,ICI 治疗具有选择性,其对许多患者的疗效并不理想。因此,确定ICI 治疗反应的预后生物标志物至关重要。PI3K/Akt 通路在肿瘤的形成和转移中发挥着重要作用。然而,目前尚无文献报道阐明 PI3K/Akt 通路突变与接受免疫治疗的结肠腺癌(COAD)患者的预后之间的关系。

方法

我们从癌症基因组图谱(TCGA)数据库中收集了 COAD 队列的数据,包括全外显子组测序(WES)数据、RNA-seq 数据和临床数据。我们还从接受免疫治疗的 COAD 患者队列中收集了包括临床预后和靶向测序数据。我们从南方医科大学珠江医院收集了 50 例 COAD 患者(Local-COAD)进行靶向测序。我们分析了 PI3K/Akt 通路突变对患者临床预后、免疫原性和免疫微环境的影响。采用基因集富集分析(GSEA)分析显著上调和下调的信号通路。我们利用这些结果提出了 PI3K/Akt 突变可能影响 COAD 患者预后的潜在机制假说。

结果

单因素和多因素 Cox 分析及 Kaplan-Meier(KM)生存曲线显示,PI3K-Akt 突变患者的总生存期(OS)优于无 PI3K-Akt 突变患者。通过全景图筛选出两个队列中具有显著突变率的基因。使用 CIBERSORT 分析 22 种免疫细胞的变化,以鉴定免疫激活细胞。同样,PI3K/Akt 突变型(PI3K/Akt-MT)组患者的免疫原性也显著增加,包括肿瘤突变负荷(TMB)、新抗原负荷(NAL)和 MANTIS 评分增加。通过 GSEA,我们鉴定出与免疫反应相关的上调途径。

结论

PI3K/Akt 通路突变状态可作为 COAD 患者对 ICI 治疗反应的独立预测因子。PI3K/Akt 突变与 OS 改善、更高的免疫原性、更大的免疫反应评分以及激活免疫细胞的增加相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfa4/9192307/8db642092f74/JIR2022-8179799.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfa4/9192307/23ab12eed7b8/JIR2022-8179799.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfa4/9192307/288f8488378a/JIR2022-8179799.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfa4/9192307/8db642092f74/JIR2022-8179799.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfa4/9192307/23ab12eed7b8/JIR2022-8179799.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfa4/9192307/b5788fa8f523/JIR2022-8179799.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfa4/9192307/28bd841d018f/JIR2022-8179799.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfa4/9192307/288f8488378a/JIR2022-8179799.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfa4/9192307/8db642092f74/JIR2022-8179799.005.jpg

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