肾透明细胞癌（ccRCCs）中的肿瘤内异质性（ITH）是一个关键特征，它会影响侵略性、治疗反应或复发等结果。特别是，在临床低风险患者中，外科手术后肿瘤复发可能会解释为何不能从辅助治疗中获益。最近，单细胞RNA测序（scRNA-seq）已成为揭示表达式ITH（eITH）的强大工具，并可能使我们更好地评估ccRCC的临床结果。本研究旨在探索ccRCC中的eITH，重点关注恶性细胞（MCs），并评估其与改善低风险患者预后的相关性。我们对来自未经治疗的5例ccRCC患者（范围从pT1a到pT3b）的肿瘤样本进行了scRNA-seq。数据与由匹配的正常和ccRCC样本组成的已发布数据集相结合。未经治疗的ccRCC患者进行根治性或部分肾切除手术。细胞存活率和类型比例通过流式细胞术确定。在scRNA-seq后，进行了功能分析，并推断了肿瘤进展轨迹。在外部队列上应用了一种去卷积方法，并估计了Kaplan-Meier生存曲线，关于恶性簇的普遍性进行了估计。我们分析了54,812个细胞，确定了35个细胞亚群。eITH分析揭示了每个肿瘤包含不同程度的克隆多样性。尤其是，在一个特别异质的样本中的MCs的转录组标志被用来设计了一种基于去卷积的策略，允许对310名低风险ccRCC患者进行风险分层。我们描述了ccRCCs中的eITH，并利用此信息建立了显著的基于细胞种群的预后标记，并更好地区分ccRCC患者。这种方法有潜力改善临床低风险患者的分层和治疗管理。我们测序了由透明细胞肾细胞癌组成的单个细胞亚群的RNA内容，并确定了特定的恶性细胞的遗传信息，可以用来预测肿瘤进展。版权所有© 2023。Elsevier B.V.发表。

Intratumor heterogeneity (ITH) is a key feature in clear cell renal cell carcinomas (ccRCCs) that impacts outcomes such as aggressiveness, response to treatments, or recurrence. In particular, it may explain tumor relapse after surgery in clinically low-risk patients who did not benefit from adjuvant therapy. Recently, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to unravel expression ITH (eITH) and might enable better assessment of clinical outcomes in ccRCC.To explore eITH in ccRCC with a focus on malignant cells (MCs) and assess its relevance to improve prognosis for low-risk patients.We performed scRNA-seq on tumor samples from five untreated ccRCC patients ranging from pT1a to pT3b. Data were complemented with a published dataset composed of pairs of matched normal and ccRCC samples.Radical or partial nephrectomy on untreated ccRCC patients.Viability and cell type proportions were determined by flow cytometry. Following scRNA-seq, a functional analysis was performed and tumor progression trajectories were inferred. A deconvolution approach was applied on an external cohort, and Kaplan-Meier survival curves were estimated with respect to the prevalence of malignant clusters.We analyzed 54 812 cells and identified 35 cell subpopulations. The eITH analysis revealed that each tumor contained various degrees of clonal diversity. The transcriptomic signatures of MCs in one particularly heterogeneous sample were used to design a deconvolution-based strategy that allowed the risk stratification of 310 low-risk ccRCC patients.We described eITH in ccRCCs, and used this information to establish significant cell population-based prognostic signatures and better discriminate ccRCC patients. This approach has the potential to improve the stratification of clinically low-risk patients and their therapeutic management.We sequenced the RNA content of individual cell subpopulations composed of clear cell renal cell carcinomas and identified specific malignant cells the genetic information of which can be used to predict tumor progression.Copyright © 2023. Published by Elsevier B.V.