Novel genetically engineered mouse models for clear cell renal cell carcinoma.
Novel genetically engineered mouse models for clear cell renal cell carcinoma.
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DOI：
10.1038/s41598-023-35106-7
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发表时间：
2023-05-22
影响因子：
4.6
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中科院分区：
文献类型：
--
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基因工程小鼠模型（GEMM）是研究单个基因在癌症中的作用和开发新疗法的重要免疫活性模型。在这里，我们使用诱导型 CRISPR-Cas9 系统开发了两种 GEMM，旨在模拟透明细胞肾细胞癌 (ccRCC) 中常见的广泛染色体 p3 缺失。我们在包含由四环素 (tet) 响应元件 (TRE3G) 驱动的 Cas9D10A（切口酶、hSpCsn1n）的构建体中克隆了针对 Bap1、Pbrm1 和 Setd2 早期外显子的配对引导 RNA，以开发我们的第一个 GEMM。将创始小鼠与两个先前建立的转基因品系杂交，一种携带tet反式激活子（tTA，Tet-Off），另一种携带三重突变稳定的HIF1A-M3（TRAnsgenic Cancer of the Kidney，TRACK），两者均由截短的近端小管特异性γ-谷氨酰转移酶1（ggt或γGT）启动子驱动，以产生三重转基因动物。我们的结果表明，该模型 (BPS-TA) 在 Bap1 和 Pbrm1（但不在 Setd2）（人类 ccRCC 中已知的肿瘤抑制基因）中诱导少量体细胞突变。这些突变主要局限于肾脏和睾丸，在一组 13 个月大的小鼠中没有诱导可检测到的组织转化 (N = 10)。为了深入了解 BPS-TA 小鼠中低频率的插入和缺失 (indel)，我们通过 RNAseq 分析了野生型 (WT，N = 7) 和 BPS-TA (N = 4) 肾脏。这表明 DNA 损伤和免疫反应都被激活，表明基因组编辑响应肿瘤抑制机制的激活。然后，我们修改了我们的方法，生成了第二个模型，其中采用 ggt 驱动、cre 调节的 Cas9WT(hSpCsn1) 在 TRACK 系 (BPS-Cre) 中引入 Bap1、Pbrm1 和 Setd2 基因组编辑。 BPS-TA 和 BPS-Cre 系分别受到多西环素 (dox) 和他莫昔芬 (tam) 的时空方式严格控制。此外，BPS-TA 系依赖于配对引导 RNA (gRNA)，而 BPS-Cre 系仅需要单个 gRNA 来进行基因扰动。在 BPS-Cre 中，我们发现与 BPS-TA 模型相比，Pbrm1 基因编辑频率有所增加。虽然我们没有在 BPS-TA 肾脏中检测到 Setd2 编辑，但我们在 BPS-Cre 模型中发现了 Setd2 的广泛编辑。两种模型的 Bap1 编辑效率相当。 虽然我们的研究中没有观察到严重的恶性肿瘤，但这是第一个报道的 GEMM，它模拟了肾癌患者中经常观察到的广泛染色体 3p 缺失。需要进一步的研究（1）来模拟更广泛的 3p 缺失，例如影响其他基因，以及（2）提高细胞分辨率，例如通过使用单细胞 RNAseq 来确定特定组合基因失活的影响。
Genetically engineered mouse models (GEMMs) are important immunocompetent models for research into the roles of individual genes in cancer and the development of novel therapies. Here we use inducible CRISPR-Cas9 systems to develop two GEMMs which aim to model the extensive chromosome p3 deletion frequently observed in clear cell renal cell carcinoma (ccRCC). We cloned paired guide RNAs targeting early exons of Bap1, Pbrm1, and Setd2 in a construct containing a Cas9D10A (nickase, hSpCsn1n) driven by tetracycline (tet)-responsive elements (TRE3G) to develop our first GEMM. The founder mouse was crossed with two previously established transgenic lines, one carrying the tet-transactivator (tTA, Tet-Off) and one with a triple-mutant stabilized HIF1A-M3 (TRAnsgenic Cancer of the Kidney, TRACK), both driven by a truncated, proximal tubule-specific γ-glutamyltransferase 1 (ggt or γGT) promoter, to create triple-transgenic animals. Our results indicate that this model (BPS-TA) induces low numbers of somatic mutations in Bap1 and Pbrm1 (but not in Setd2), known tumor suppressor genes in human ccRCC. These mutations, largely restricted to kidneys and testis, induced no detectable tissue transformation in a cohort of 13 month old mice (N = 10). To gain insights into the low frequencies of insertions and deletions (indels) in BPS-TA mice we analyzed wild type (WT, N = 7) and BPS-TA (N = 4) kidneys by RNAseq. This showed activation of both DNA damage and immune response, suggesting activation of tumor suppressive mechanisms in response to genome editing. We then modified our approach by generating a second model in which a ggt-driven, cre-regulated Cas9WT(hSpCsn1) was employed to introduce Bap1, Pbrm1, and Setd2 genome edits in the TRACK line (BPS-Cre). The BPS-TA and BPS-Cre lines are both tightly controlled in a spatiotemporal manner with doxycycline (dox) and tamoxifen (tam), respectively. In addition, whereas the BPS-TA line relies on paired guide RNAs (gRNAs), the BPS-Cre line requires only single gRNAs for gene perturbation. In the BPS-Cre we identified increased Pbrm1 gene-editing frequencies compared to the BPS-TA model. Whereas we did not detect Setd2 edits in the BPS-TA kidneys, we found extensive editing of Setd2 in the BPS-Cre model. Bap1 editing efficiencies were comparable between the two models. Although no gross malignancies were observed in our study, this is the first reported GEMM which models the extensive chromosome 3p deletion frequently observed in kidney cancer patients. Further studies are required (1) to model more extensive 3p deletions, e.g. impacting additional genes, and (2) to increase the cellular resolution, e.g. by employing single-cell RNAseq to ascertain the effects of specific combinatorial gene inactivation.
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影响因子：
64.5
作者：
Jaitin, Diego Adhemar;Weiner, Assaf;Amit, Ido
通讯作者：
Amit, Ido
影响因子：
4.7
作者：
Laursen KB;Chen Q;Khani F;Attarwala N;Gross SS;Dow L;Nanus DM;Gudas LJ
通讯作者：
Gudas LJ
影响因子：
16.6
作者：
Bailey ST;Smith AM;Kardos J;Wobker SE;Wilson HL;Krishnan B;Saito R;Lee HJ;Zhang J;Eaton SC;Williams LA;Manocha U;Peters DJ;Pan X;Carroll TJ;Felsher DW;Walter V;Zhang Q;Parker JS;Yeh JJ;Moffitt RA;Leung JY;Kim WY
通讯作者：
Kim WY
影响因子：
56.9
作者：
Bunz, F;Dutriaux, A;Vogelstein, B
通讯作者：
Vogelstein, B
影响因子：
158.5
作者：
Choueiri, T. K.;Tomczak, P.;Powles, T.
通讯作者：
Powles, T.