联系方式:huizong@szbl.ac.cn
利用小鼠遗传嵌合体模型、以极高的时空分辨率来研究肿瘤的起源和恶化过程,借以研发癌症预防和精准治疗的手段,从根本上改善疗效并提高病人的生活质量
Using a mouse genetic mosaic model, our lab studies tumor initiation and progression at unprecedented temporal and spatial resolution, aiming at developing cancer prevention and precision medicine to fundamentally improve therapeutic efficacy and life quality for patients
2022 皮尤创新奖,皮尤慈善信托基金(美国共6支队伍)
2020 弗吉尼亚大学医学院 Pinn 学者(该校共 3 名)
2011 Richard T. Jones 新研究员奖,医学研究基金会,俄勒冈健康与科学大学(俄勒冈州共 1 人)
2008 皮尤生物医学科学学者,皮尤慈善信托基金(美国共 20 位)
2022 Pew Innovation Award, the Pew Charitable Trust (6 teams total in the United States)
2020 Pinn Scholar, School of Medicine, University of Virginia (3 total in the university)
2011 Richard T. Jones New Investigator Award, Medical Research Foundation, OHSU (1 total in the state of Oregon)
2008 Pew Scholar in biomedical sciences, the Pew Charitable Trust (20 total in United States)
深圳湾实验室肿瘤研究所,资深研究员
斯坦福大学,博士后
我们实验室的研究主题集中于理解维持正常发育和成体稳态的精妙细胞间关系(合作与竞争)如何在癌症中发生紊乱,最终目标是开发颠覆性的治疗方法,通过恢复细胞间的关系来治愈癌症。我们实验室研究的独特之处在于运用了一个叫作MADM(双标记嵌合分析)的小鼠遗传嵌合体模型,让我们能够达到前所未有的时间和空间的高分辨率来研究肿瘤发生过程(Zong 2005 Cell)。从一个无色且携带肿瘤抑制基因杂合子突变的小鼠开始,Cre介导的染色体间有丝分裂重组可产生罕见的GFP标记的肿瘤抑制基因缺失细胞和RFP标记的同胞野生型细胞(图一)。凭借颜色与基因型之间的明确关联,我们得以通过监测绿色突变细胞相对于其红色野生型同胞细胞的异常行为,在远早于组织病理学可以检测到任何病变之前,可以清晰地研究肿瘤起始机制。
图一:From a colorless cell with a heterozygous mutation, MADM generates a GFP+, homozygous null cell and a RFP+, wildtype sibling cell. If the mutation is a tumor suppressor gene, MADM-generated GFP+ null cell becomes a cancer initiation cell. Due to the low efficiency of MADM, GFP+ null cells are rare, mimicking the clonal origin of human cancers and enabling phenotypic analysis at the single-cell resolution in vivo.
当我们用MADM建立髓母细胞瘤的模型后,我们发现这个一直被认为非常简单的、由于一种细胞过度增殖而产生的肿瘤包含一个前所未知的“三种细胞组成的社区”:首先肿瘤细胞当然是髓母细胞瘤的主要细胞,其次出乎意料的是MADM提供的谱系追踪能力揭示出少量但遍布肿瘤的星状细胞居然完全都是从肿瘤细胞转分化而来的,最后从肿瘤细胞转分化而来的星状细胞并不是一个被动的存在、而是通过分泌细胞因子来刺激小胶质细胞、促使其分泌IGF-1,来维持肿瘤的恶性发展(图二,Yao 2020 Cell)。这个研究工作揭示了肿瘤内的极端强大的合作关系,也打开了很多治疗这个肿瘤的全新思路。
图二:Using MADM model, we delineated TME evolution at single-cell resolution in medulloblastomas that originate from unipotent granule neuron progenitors in the brain. First, we found that astrocytes within the TME (TuAstrocytes) were trans-differentiated from tumor granule neuron precursors (GNPs), which normally never differentiate into astrocytes. Second, we identified that TME-derived IGF1 promotes tumor progression. Third, we uncovered that insulin-like growth factor 1 (IGF1) is produced by tumor-associated microglia in response to interleukin-4 (IL-4) stimulation, which is secreted by TuAstrocytes. Collectively, our studies reveal an evolutionary process that produces a multi-lateral cooperative network within the TME of medulloblastoma.
当我们用MADM建立胶质瘤的模型后,基于“根基决定病情”的理念,我们决定探究其“起源细胞”的问题。在我们这个工作之前,由于肿瘤细胞的基因表达与“起源细胞”已经有了巨大的差别,领域中的看法众说纷纭,有人认为是神经干细胞、而反对意见认为是胶质细胞,但是由于无法在胶质瘤完全病理恶化之前分析这个问题,一直无法定论。由于MADM凭借GFP标记能够在远早于病理恶化前的阶段研究突变细胞在脑内的扩张,我们借用G/R ratio(突变细胞相对正常细胞的比率)来观察每一种脑细胞,发现除了 oligodendrocyte precursor cells (OPCs,少突胶质前体细胞)突增一百多倍之外,其它细胞种类、包括神经干细胞都没有很明显的扩增,因此确定OPC是胶质瘤的“起源细胞”,平息了领域内多年的辩论(图三,Liu 2011 Cell)。那么OPC有什么特别的活力来促成胶质瘤几乎百分之百的致死率呢?我们最新的工作发现突变的OPCs不仅仅是被动的增殖,而是通过细胞之间的竞争来杀死正常的OPCs,为自己“开拓疆土”,在恶化之前就已经侵占全脑。这个发现说明传统的治疗对于胶质瘤很难奏效,也展示出早期检测的手段和针对细胞竞争的精准治疗方法将会对胶质瘤的防治起到革命性的进步。
图三:Using MADM, we introduced two gliomagenic mutations (Trp53, Nf1) in all brain cell lineages. Because GFP+, Trp53, Nf1-null cells are siblings to RFP+, wildtype cells, the ratio increase of their cell numbers indicate pre-malignant expansion, thereby revealing the “cell of origin” for glioma. The fact that G/R ratio of OPCs but no other brain cell types increase massively suggests that OPC is the cell of origin” for glioma.
· Jiang Y#*, Ahn R#, Huang A, Gonzalez PP, Kim J, Zhang G, Liu Z, He Z, Dudley L, Patel KS, Crowl S, Przanowski P, Quesada-Camacho L, Hao S, Zeng J, Fallahi-Sichani M, Janes KA, Naegle KM, Goldman SA, Kornblum KI, Yao M*, White F*, Zong H* (2026) Critical role of cell competition in gliomagenesis. bioRxiv [Preprint]. 2026 Jan 16:2026.01.15.699808.
· Zeng J, Singh S, Jiang Y, Casarez E, Atkins KA, Janes KA, Zong H* (2023) A genetic mosaic mouse model illuminates the pre-malignant progression of basal-like breast cancer. Disease Models and Mechanisms, 16, dmm050219. doi:10.1242/dmm.050219, PMC10168298
· Zeng J, Alvarez-Yela AC, Casarez E, Jiang Y, Wang L, Kelly BE, Ke E, Jenkins T, Atkins KA, Janes KA, Slack-Davis JK*, Zong H* (2023) Dichotomous ovarian cancer-initiating potential of Pax8+ cells revealed by a mouse genetic mosaic model. iScience (Cell Press), 26(5) 106742. PMC10189502
· Yao M, Ventura PB, Jiang Y, Rodriguez FJ, Wang L, Perry JSA, Yang Y, Wahl K, Crittenden RB, Bennett ML, Qi L, Gong C, Li X, Barres BA, Bender TP, Ravichandran K, Janes KA, Eberhart CG, Zong H* (2020) Astrocytic trans-differentiation completes a multicellular paracrine feedback loop required for medulloblastoma tumor growth. Cell, 180(3):502-520 DOI: 10.1016/j.cell.2019.12.024. PMC7259679
· Gonzalez PP, Kim J, Galvao RP, Cruickshanks N, Abounader R, and Zong H.* (2018) p53 and NF1 loss plays distinct but complementary roles in glioma initiation and progression. Glia, 66(5):999-1015. PMC7808243
· Ledur P, Liu C, He H, Harris A, Minussi D, Zhou H, Shaffrey M, Asthagiri A, Lopes M, Schiff D, Lu Y, Mandell J, Lenz G, Zong H.* (2016) Culture conditions tailored to the cell of origin are critical for maintaining native properties and tumorigenicity of glioma cells Neuro-Oncology, 18(10):1413-24. PMC5035523
· Galvao, R.P., Kasina, A., McNeill, R.S., Harbin, J.E., Foreman, O., Verhaak, R.G.W., Nishiyama, A., Miller, C.R., Zong, H.* (2014) Transformation of quiescent adult oligodendrocyte precursor cells into malignant glioma through a multi-step reactivation process. PNAS, 111(40):E4214-23. PMC4210043
· Liu, C., Sage, J.C., Miller, M.R., Verhaak, R.G.W., Hippenmeyer, S., Vogel, H., Foreman, O., Bronson, R.T., Nishiyama, A., Luo, L., Zong, H.* (2011) Mosaic Analysis with Double Markers Reveals Tumor Cell-of-Origin in Glioma. Cell, 146:209-221. PMC3143261
· Muzumdar, M.D., Luo, L., Zong, H* (2007) Modeling sporadic loss of heterozygosity in mice by using mosaic analysis with double markers (MADM). PNAS, 104:4495-4500. PMC1810340
· Zong, H., Espinosa, S., Su, H., Muzumdar, M.D., and Luo, L* (2005) Mosaic analysis with double markers in mice. Cell, 121:479-492