Filtering cells with high mitochondrial content depletes viable metabolically altered malignant cell populations in cancer single-cell studies

IF 10.1 1区 生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Josephine Yates, Agnieszka Kraft, Valentina Boeva
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Abstract

Single-cell transcriptomics has transformed our understanding of cellular diversity, yet noise from technical artifacts and low-quality cells can obscure key biological signals. A common practice is filtering out cells with a high percentage of mitochondrial RNA counts (pctMT), typically indicative of cell death. However, commonly used filtering thresholds, primarily derived from studies on healthy tissues, may be overly stringent for malignant cells, which often naturally exhibit higher baseline mitochondrial gene expression. We examine nine public single-cell RNA-seq datasets from various cancers, including 441,445 cells from 134 patients, and public spatial transcriptomics data, assessing the viability of malignant cells with high pctMT. Our analysis reveals that malignant cells exhibit significantly higher pctMT than nonmalignant cells, without a notable increase in dissociation-induced stress scores. Malignant cells with high pctMT show metabolic dysregulation, including increased xenobiotic metabolism, relevant to therapeutic response. Analysis of pctMT in cancer cell lines further reveals links to drug resistance. We also observe associations between pctMT and malignant cell transcriptional heterogeneity, as well as patient clinical features. This study provides insights into the functional characteristics of malignant cells with elevated pctMT, challenging current quality control practices in tumor single-cell RNA-seq analyses and offering potential improvements in data interpretation for future cancer studies.
在癌症单细胞研究中,具有高线粒体含量的过滤细胞消耗了代谢改变的恶性细胞群
单细胞转录组学已经改变了我们对细胞多样性的理解,然而来自技术人工制品和低质量细胞的噪音可能会掩盖关键的生物信号。一种常见的做法是过滤掉线粒体RNA计数(pctMT)百分比高的细胞,这通常表明细胞死亡。然而,常用的过滤阈值主要来源于健康组织的研究,对于恶性细胞可能过于严格,因为恶性细胞通常自然表现出更高的基线线粒体基因表达。我们研究了来自不同癌症的9个公共单细胞RNA-seq数据集,包括来自134名患者的441,445个细胞,以及公共空间转录组学数据,评估了具有高pctMT的恶性细胞的活力。我们的分析显示,恶性细胞的pctMT明显高于非恶性细胞,而解离诱导的应激评分没有显著增加。高pctMT的恶性细胞显示代谢失调,包括增加的异种代谢,这与治疗反应有关。对癌细胞系中pctMT的分析进一步揭示了其与耐药性的联系。我们还观察到pctMT与恶性细胞转录异质性以及患者临床特征之间的关联。该研究为pctMT升高的恶性细胞的功能特征提供了见解,挑战了目前肿瘤单细胞RNA-seq分析的质量控制实践,并为未来的癌症研究提供了数据解释的潜在改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Genome Biology
Genome Biology Biochemistry, Genetics and Molecular Biology-Genetics
CiteScore
21.00
自引率
3.30%
发文量
241
审稿时长
2 months
期刊介绍: Genome Biology stands as a premier platform for exceptional research across all domains of biology and biomedicine, explored through a genomic and post-genomic lens. With an impressive impact factor of 12.3 (2022),* the journal secures its position as the 3rd-ranked research journal in the Genetics and Heredity category and the 2nd-ranked research journal in the Biotechnology and Applied Microbiology category by Thomson Reuters. Notably, Genome Biology holds the distinction of being the highest-ranked open-access journal in this category. Our dedicated team of highly trained in-house Editors collaborates closely with our esteemed Editorial Board of international experts, ensuring the journal remains on the forefront of scientific advances and community standards. Regular engagement with researchers at conferences and institute visits underscores our commitment to staying abreast of the latest developments in the field.
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