肿瘤细胞治疗研究
英文原题：A hierarchical Bayesian framework for inferring mitochondrial clonal selection from single-cell data.
A hierarchical Bayesian framework for inferring mitochondrial clonal selection from single-cell data.
这些发现确立了MitoBayes作为一个稳健的统计框架，将线粒体遗传多样性与疾病表型联系起来，并强调线粒体克隆选择作为机制和临床上可操作的治疗和诊断开发靶点。
线粒体遗传异质性源于体细胞线粒体DNA（mtDNA）突变在单个细胞内积累，形成细胞内克隆群体；这些克隆在疾病中的选择动态仍缺乏充分认识。本文介绍MitoBayes，一种分层贝叶斯框架，可联合建模线粒体克隆谱系结构、等位基因频率变化和与疾病相关的单细胞表型负担，以推断克隆特异性选择压力。广泛的基准测试显示，在多种遗传异质性、数据稀疏性和谱系复杂度情形下，MitoBayes均能准确恢复真实选择系数。将MitoBayes应用于阿尔茨海默病（AD）皮层、未经治疗的非小细胞肺癌（NSCLC）和化疗耐药小细胞肺癌（SCLC）的单细胞图谱后，发现了疾病特异性的线粒体克隆选择模式，包括：AD中与PVALB中间神经元稳态破坏相关的高风险线粒体克隆选择性扩增；NSCLC肿瘤中循环T/NK细胞由疾病驱动的克隆重塑，其特征为线粒体生物发生增加和免疫调节程序受损；以及SCLC中肿瘤相关MT-ATP6（m.8859A>G）克隆优先富集，与代谢适应和铂类耐药相关。泛癌生存分析进一步确认MT-ATP6活性升高具有临床意义，并与较差化疗结局相关。此外，在肝细胞癌（HCC）中，优势m.2356C>G克隆与POLR2A活化和广泛转录放大相关，这符合线粒体-细胞核信号轴参与该癌种不良预后的假设。综合而言，本研究建立了MitoBayes这一稳健统计框架，连接线粒体遗传多样性和疾病表型，并凸显线粒体克隆选择是具有机制和临床可操作性的治疗及诊断开发靶点。
Mitochondrial genetic heterogeneity arises from the accumulation of somatic mitochondrial DNA (mtDNA) mutations within individual cells, generating intracellular clonal populations whose selective dynamics in disease remain poorly characterized. Here, we present MitoBayes, a hierarchical Bayesian framework that jointly models mitochondrial clonal lineage structure, allele frequency variation, and single-cell disease-relevant phenotypic burdens to infer clone-specific selection pressures. Extensive benchmarking demonstrates that MitoBayes accurately recovers ground-truth selection coefficients across a wide range of genetic heterogeneity, data sparsity, and lineage complexity scenarios. Application of MitoBayes to single-cell atlases of Alzheimer's disease (AD) cortex, treatment-naïve non-small-cell lung cancer (NSCLC), and chemotherapy-resistant small-cell lung cancer (SCLC) revealed distinct, disease-specific patterns of mitochondrial clonal selection. These include selective expansion of high-risk mitochondrial clones associated with disruption of PVALB interneuron homeostasis in AD; disease-driven clonal remodeling in cycling T/NK cells from NSCLC tumors characterized by increased mitochondrial biogenesis and impaired immune regulatory programs; and preferential enrichment of a tumor-associated MT-ATP6 (m.8859A>G) clone linked to metabolic adaptation and platinum resistance in SCLC. Pan-cancer survival analyses further confirmed the clinical relevance of elevated MT-ATP6 activity, which was associated with inferior chemotherapy outcomes. Additionally, in hepatocellular carcinoma (HCC), a dominant m.2356C>G clone correlated with POLR2A activation and widespread transcriptional amplification, consistent with a mitochondria-nucleus signaling axis contributing to adverse prognosis in this cancer type. Collectively, these findings establish MitoBayes as a robust statistical framework linking mitochondrial genetic diversity to disease phenotypes and highlight mitochondrial clonal selection as a mechanistically and clinically actionable target for therapeutic and diagnostic development.
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