肿瘤细胞治疗研究
英文原题：Integrated analysis of single-cell and bulk transcriptome identifies a signature based on NK cell marker genes to predict prognosis and therapeutic response in clear cell renal cell carcinoma.
我们鉴定出一种新型特征，可作为独立的预测性生物标志物以及为ccRCC患者选择个体化治疗的工具。
越来越多的证据强调了自然杀伤（NK）细胞在塑造抗肿瘤免疫中的作用。本研究旨在构建一个NK细胞标志基因特征（NKMS），以预测透明细胞肾细胞癌（ccRCC）患者的预后和治疗反应。
从GEO、TCGA、ArrayExpress和ICGC数据库中收集了具有匹配临床信息的ccRCC患者的公开单细胞和批量RNA图谱。构建了一种新的NKMS，并在ccRCC患者中评估了其预后价值、相关免疫基因组特征以及对ICIs和抗血管生成治疗的预测能力。
我们通过单细胞RNA测序（scRNA-seq）分析在GSE152938和GSE159115中鉴定了52个NK细胞标记基因。经过最小绝对收缩和选择算子（LASSO）和Cox回归，最具预后价值的7个基因（CLEC2B、PLAC8、CD7、SH3BGRL3、CALM1、KLRF1和JAK1）利用TCGA的批量转录组构建了NKMS。生存分析和时间依赖性受试者工作特征（ROC）分析显示，该特征在训练集和两个独立验证队列（E-MTAB-1980和RECA-EU队列）中具有出色的预测能力。该七基因特征能够识别高Fuhrman分级（G3-G4）和美国癌症联合委员会（AJCC）分期（III-IV）内的患者。多因素分析证实了该特征的独立预后价值，并构建了列线图以供临床使用。高风险组的特征是高肿瘤突变负荷（TMB）和更高的免疫细胞浸润，特别是CD8+ T细胞、调节性T（Treg）细胞和滤泡辅助性T（Tfh）细胞，同时负调控抗肿瘤免疫的基因表达更高。此外，高风险肿瘤表现出更高的T细胞受体（TCR） repertoire丰富度和多样性。在两个ccRCC患者治疗队列（PMID32472114和E-MTAB-3267）中，我们证明高风险组对ICIs表现出更高的敏感性，而低风险组更可能从抗血管生成治疗中获益。
BACKGROUND: Accumulating evidence has highlighted the effects of natural killer (NK) cells on shaping anti-tumor immunity. This study aimed to construct an NK cell marker gene signature (NKMS) to predict prognosis and therapeutic response of clear cell renal cell carcinoma (ccRCC) patients. METHODS: Publicly available single-cell and bulk RNA profiles with matched clinical information of ccRCC patients were collected from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), ArrayExpress, and International Cancer Genome Consortium (ICGC) databases. A novel NKMS was constructed, and its prognostic value, associated immunogenomic features and predictive capability to immune checkpoint inhibitors (ICIs) and anti-angiogenic therapies were evaluated in ccRCC patients. RESULTS: We identified 52 NK cell marker genes by single-cell RNA-sequencing (scRNA-seq) analysis in GSE152938 and GSE159115. After least absolute shrinkage and selection operator (LASSO) and Cox regression, the most prognostic 7 genes ( CLEC2B, PLAC8, CD7, SH3BGRL3, CALM1, KLRF1, and JAK1 ) composed NKMS using bulk transcriptome from TCGA. Survival and time-dependent receiver operating characteristic (ROC) analysis exhibited exceptional predictive capability of the signature in the training set and two independent validation cohorts (E-MTAB-1980 and RECA-EU cohorts). The seven-gene signature was able to identify patients within high Fuhrman grade (G3-G4) and American Joint Committee on Cancer (AJCC) stage (III-IV). Multivariate analysis confirmed the independent prognostic value of the signature, and a nomogram was built for clinical utility. The high-risk group was characterized by a higher tumor mutation burden (TMB) and greater infiltration of immunocytes, particularly CD8 + T cells, regulatory T (Treg) cells and follicular helper T (Tfh) cells, in parallel with higher expression of genes negatively regulating anti-tumor immunity. Moreover, high-risk tumors exhibited higher richness and diversity of T-cell receptor (TCR) repertoire. In two therapy cohorts of ccRCC patients (PMID32472114 and E-MTAB-3267), we demonstrated that high-risk group showed greater sensitivity to ICIs, whereas the low-risk group was more likely to benefit from anti-angiogenic therapy. CONCLUSIONS: We identified a novel signature that can be utilized as an independent predictive biomarker and a tool for selecting the individualized treatment for ccRCC patients.
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