三阴性乳腺癌耐药：适者生存有代价
任何生物都在随着时间推移而演变，某些特征进化，某些特征退化，从而适应环境压力，即适者生存。癌症也不例外，尤其三阴性乳腺癌，三大受体均为阴性、内分泌治疗和HER2靶向治疗无效、基因突变、免疫逃逸、化疗耐药等适者生存能力超强，成为最难治疗的乳腺癌。因此，预测肿瘤如何随着时间演变，尤其对治疗的反应，是科学家面临的重要挑战之一。不过，由于缺乏多克隆细胞群连续时间单细胞采样手段和时间统计学模型，实时观察癌症基因组适应特征全过程动态变化存在困难，尤其对于基因拷贝数量动态变化。
2021年6月23日，全球自然科学三大旗舰期刊之首、英国《自然》正刊在线发表加拿大温哥华癌症中心、不列颠哥伦比亚大学、多伦多大学、美国纽约纪念医院斯隆凯特林癌症中心、麻省理工学院、哥伦比亚大学、纽约基因组中心、哈佛大学、英国剑桥大学、瑞士苏黎世大学和洛桑大学的研究报告，通过建立单细胞癌症基因组连续时间模型和人工智能机器学习方法，实时观察到三阴性乳腺癌细胞克隆适应人体环境和化疗药物而演变的全过程。
该研究首先利用人工智能机器学习方法对乳腺上皮和原发三阴性乳腺癌患者来源异种移植物4.2万个基因组进行连续长达3年单细胞全基因组测序，发现基因组守护者TP53突变和顺铂化疗可诱导基因拷贝数量改变，从而引起某些细胞克隆适者生存。
该研究随后利用新的赖特和费希尔群体遗传学模型对克隆适者生存进行推理，发现TP53突变可改变适者生存特征分布，可重复将适者生存特征分布于不同拷贝数量改变相关的大量克隆。
此外，对于TP53突变的三阴性乳腺癌患者来源异种移植模型，该研究从拷贝数量改变的基因型推理出的适者生存系数可准确预测克隆竞争动态变化。
有趣的是，对3个长期连续传代的三阴性乳腺癌患者来源异种移植物进行顺铂化疗，可引起顺铂化疗前适者生存能力较低的细胞株产生顺铂耐药克隆。相反，顺铂化疗前适者生存能力较高的对照细胞株被顺铂杀灭，表明适者生存特征分布发生逆转。顺铂化疗结束后，选择压力发生动态逆转，表明顺铂耐药的适者生存需要付出代价。
因此，该研究结果表明，三阴性乳腺癌多克隆肿瘤顺铂耐药和拷贝数量改变与克隆适者生存密切相关，三阴性乳腺癌细胞的适者生存过程，既可预测，也可重复。事实证明，顺铂化疗结束后，耐药细胞减少或消失，被敏感细胞取代，表明耐药进化需要付出代价，也就是说，有利于耐药的特征不一定有利于在失去这些药物的环境中茁壮成长。该研究为进一步攻克三阴性乳腺癌耐药难题奠定了基础，将来有望能够对患者血液采用这种方法发现肿瘤特定克隆，预测其可能如何进化，并相应地个体化用药。
Nature. 2021 Jun 23. Online ahead of print.
Clonal fitness inferred from time-series modelling of single-cell cancer genomes.
Sohrab Salehi, Farhia Kabeer, Nicholas Ceglia, Mirela Andronescu, Marc J. Williams, Kieran R. Campbell, Tehmina Masud, Beixi Wang, Justina Biele, Jazmine Brimhall, David Gee, Hakwoo Lee, Jerome Ting, Allen W. Zhang, Hoa Tran, Ciara O'Flanagan, Fatemeh Dorri, Nicole Rusk, Teresa Ruiz de Algara, So Ra Lee, Brian Yu Chieh Cheng, Peter Eirew, Takako Kono, Jenifer Pham, Diljot Grewal, Daniel Lai, Richard Moore, Andrew J. Mungall, Marco A. Marra, IMAXT Consortium, Andrew McPherson, Alexandre Bouchard-Coté, Samuel Aparicio, Sohrab P. Shah.
BC Cancer, Vancouver, British Columbia, Canada; University of British Columbia, Vancouver, British Columbia, Canada; University of Toronto, Toronto, Ontario, Canada; Memorial Sloan Kettering Cancer Center, New York, NY, USA; Massachusetts Institute of Technology, Cambridge, MA, USA; Columbia University, New York, NY, USA; New York Genome Center, New York, NY, USA; Harvard University, Cambridge, MA, USA; University of Cambridge, Cambridge, UK; University of Zurich, Zurich, Switzerland; University of Lausanne, Lausanne, Switzerland; Súil Interactive Ltd, Dublin, Ireland.
Progress in defining genomic fitness landscapes in cancer, especially those defined by copy number alterations (CNAs), has been impeded by lack of time-series single-cell sampling of polyclonal populations and temporal statistical models. Here we generated 42,000 genomes from multi-year time-series single-cell whole-genome sequencing of breast epithelium and primary triple-negative breast cancer (TNBC) patient-derived xenografts (PDXs), revealing the nature of CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy. Using a new Wright-Fisher population genetics model to infer clonal fitness, we found that TP53 mutation alters the fitness landscape, reproducibly distributing fitness over a larger number of clones associated with distinct CNAs. Furthermore, in TNBC PDX models with mutated TP53, inferred fitness coefficients from CNA-based genotypes accurately forecast experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDXs resulted in cisplatin-resistant clones emerging from low-fitness phylogenetic lineages in the untreated setting. Conversely, high-fitness clones from treatment-naive controls were eradicated, signalling an inversion of the fitness landscape. Finally, upon release of drug, selection pressure dynamics were reversed, indicating a fitness cost of treatment resistance. Together, our findings define clonal fitness linked to both CNA and therapeutic resistance in polyclonal tumours.
DOI: 10.1038/s41586-021-03648-3