构建一种新型免疫反应预测特征以预测免疫检查点抑制剂在透明细胞肾细胞癌患者中的疗效。
Construction of a novel immune response prediction signature to predict the efficacy of immune checkpoint inhibitors in clear cell renal cell carcinoma patients.
作者信息
Yao Jiannan, Liang Ziwei, Duan Ling, G Yang, Liu Jian, An Guangyu
机构信息
Department of Oncology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.
Medical Research Center, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China.
出版信息
Heliyon. 2023 May 25;9(6):e15925. doi: 10.1016/j.heliyon.2023.e15925. eCollection 2023 Jun.
BACKGROUND
Immune checkpoint inhibitor (ICI) treatment has enhanced survival outcomes in clear cell renal cell carcinoma (ccRCC) patients. Nevertheless, the effectiveness of immunotherapy in ccRCC patients is restricted and we intended to develop and characterize an immune response prediction signature (IRPS) to forecast the efficacy of immunotherapy.
METHODS
RNA-seq expression profile and clinicopathologic characteristics of 539 kidney cancer and 72 patients with normal specimens, were downloaded from the Cancer Genome Atlas (TCGA) database, while the Gene Expression Omnibus (GEO) database was used as the validation set, which included 24 ccRCC samples. Utilization of the TCGA data and immune genes databases (ImmPort and the InnateDB), we explored through Weighted Gene Co-expression Network Analysis (WGCNA), along with Least Absolute Shrinkage and Selection Operator method (LASSO), and constructed an IRPS for kidney cancer patients. GSEA and CIBERSORT were performed to declare the molecular and immunologic mechanism underlying the predictive value of IRPS. The Human Protein Atlas (HPA) was deployed to verify the protein expressions of IRPS genes. Tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS) were computed to determine the risk of immune escape and value the discrimination of IRPS. A ccRCC cohort with anti-PD-1 therapy was obtained as an external validation data set to verify the predictive value of IRPS.
RESULTS
We constructed a 10 gene signature related to the prognosis and immune response of ccRCC patients. Considering the IRPS risk score, patients were split into high and low risk groups. Patients with high risk in the TCGA cohort tended towards advanced tumor stage and grade with poor prognosis (p < 0.001), which was validated in GEO database (p = 0.004). High-risk group tumors were related with lower PD-L1 expression, higher TMB, higher MSIsensor score, lower IPS, higher TIDE score, and enriched Treg cells, which might be the potential mechanism of immune dysfunction and exclusion. Patients in the IRPS low risk group had better PFS (HR:0.73; 95% CI: 0.54-1.0; P = 0.047).
CONCLUSION
A novel biomarker of IRPS was constructed to predict the benefit of immunotherapy, which might lead to more individualized prognoses and tailored therapy for kidney cancer patients.
背景
免疫检查点抑制剂（ICI）治疗提高了透明细胞肾细胞癌（ccRCC）患者的生存预后。然而，免疫疗法在ccRCC患者中的有效性受到限制，我们旨在开发并表征一种免疫反应预测特征（IRPS），以预测免疫疗法的疗效。
方法
从癌症基因组图谱（TCGA）数据库下载了539例肾癌患者和72例正常样本患者的RNA测序表达谱及临床病理特征，同时将基因表达综合数据库（GEO）用作验证集，其中包括24例ccRCC样本。利用TCGA数据和免疫基因数据库（ImmPort和InnateDB），我们通过加权基因共表达网络分析（WGCNA）以及最小绝对收缩和选择算子方法（LASSO）进行探索，并为肾癌患者构建了一个IRPS。进行基因集富集分析（GSEA）和CIBERSORT以阐明IRPS预测价值背后的分子和免疫机制。利用人类蛋白质图谱（HPA）验证IRPS基因的蛋白质表达。计算肿瘤免疫功能障碍和排除（TIDE）评分和免疫表型评分（IPS），以确定免疫逃逸风险并评估IRPS的辨别力。获取一个接受抗PD-1治疗的ccRCC队列作为外部验证数据集，以验证IRPS的预测价值。
结果
我们构建了一个与ccRCC患者预后和免疫反应相关的10基因特征。根据IRPS风险评分，将患者分为高风险组和低风险组。TCGA队列中高风险患者倾向于肿瘤分期和分级较高，预后较差（p < 0.001），这在GEO数据库中得到验证（p = 0.004）。高风险组肿瘤与较低的PD-L1表达、较高的肿瘤突变负荷（TMB）、较高的微卫星不稳定性（MSI）传感器评分、较低的IPS、较高的TIDE评分以及富集的调节性T细胞（Treg）相关，这可能是免疫功能障碍和排除的潜在机制。IRPS低风险组患者的无进展生存期（PFS）更好（风险比：0.73；95%置信区间：0.54 - 1.0；P = 0.047）。
结论
构建了一种新型的IRPS生物标志物来预测免疫疗法的益处，这可能为肾癌患者带来更个体化的预后和量身定制的治疗方案。
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