Precancer Niche Formation in the Fallopian Tube

背景：卵巢癌是妇科最致命的恶性肿瘤。虽然早期的治疗方法存在- 由于癌症的分期，缺乏用于检测癌前病变的特异性生物标志物，癌前病变通常发生在 输卵管上皮（FTE）。正常FTE由分泌细胞和纤毛细胞混合的小簇组成 大约1：1的比例。虽然FTE转化的机制还不完全清楚，但相信 卵泡液中的激素和生长因子使FTE在排卵期间暴露于遗传毒性应激， 逃避应激诱导的细胞死亡导致分泌细胞的异常积累。在这 在微环境中，分泌细胞有时会发生遗传和形态学变化，包括 卵巢癌是卵巢癌的一种重要表现，包括卵巢上皮细胞的分化、分层、脱落和细胞极性的丧失，这些都被认为是卵巢癌的先兆病变。 异常分泌细胞积聚与卵巢癌风险增加相关， BRCA1基因突变的女性然而，形态学变化和分子机制， 导致分泌细胞转化是未知的。具体来说，纤毛细胞在形成 前驱FTE病变尚不清楚。 初步数据：我们对BRCA 1突变携带者和非携带者的FTE进行的组织学和分子学分析 绝经后BRCA1突变携带者的分泌细胞与纤毛细胞的比例较高， 细胞存活相关基因CDK1和Survivin水平增加，表明分泌细胞逃逸 细胞死亡出乎意料的是，我们观察到同型细胞分离和纤毛细胞的损失， 分泌细胞积累。 假设：我们认为同型细胞信号传导和纤毛细胞的丧失创造了有利的细胞周期。 BRCA1突变体FTE中分泌细胞转化的微环境提供了其他条件， 荷尔蒙的变化和基因毒性的压力，同时向不受控制的扩散倾斜的平衡。 独特的资源：我们是第一个将诱导多能干细胞（iPSC）分化为FTE的团队， 从BRCA1突变携带者和非携带者建立iPSC类器官。我们有世界上最大的 FTE标本的详细临床病理学和人口统计学数据的高风险患者。我们将利用 我们最近开发的计算成像卷积神经网络管道，用于提取"隐藏" 用于生物标志物开发和鉴定潜在预防靶点的肿瘤前特征。 具体目标：在目标1中，我们将使用人类和小鼠FTE类器官和体内小鼠模型来测试 假设纤毛细胞保护分泌细胞免受遗传毒性应激。在目标2中，我们将检验假设 在遗传毒性应激下异常分泌细胞的存活可以被以下物质的药理学抑制剂抵消： 参与细胞存活的基因，如CDK1和Survivin。在目标3中，我们将整合RNA测序， 利用深度神经网络学习进行图像处理，以识别临床相关分子和 BRCA 1突变携带者输卵管癌前病变的组织形态学生物标志物 影响：这项研究将有助于更好地了解易感基因突变之间的相互作用。 以及卵巢癌发生前的微环境变化。识别潜在的分子和 形成癌前生态位的形态学贡献者将有助于新策略的发展 用于卵巢癌的预防和检测，这在临床实践中是迫切需要的。

Background: Ovarian cancer is the most fatal gynecologic cancer. While curative treatments exist for early- stage cancers, there is a lack of specific biomarkers for detecting preneoplastic lesions, which usually occur in the fallopian tube epithelia (FTE). Normal FTE consists of small clusters of secretory and ciliated cells intermixed in an approximately 1:1 ratio. Although the mechanism of FTE transformation is not fully understood, it is believed that hormones and growth factors in the follicular fluid expose FTE to genotoxic stress during ovulation and that escape from the stress-induced cell death leads to an aberrant accumulation of secretory cells. In this microenvironment, secretory cells sometimes undergo genetic and morphologic changes that include stratification, atypia, and loss of cell polarity, which are considered the precursor lesions to ovarian cancer. Aberrant secretory cell accumulation is associated with an increased risk of ovarian cancer and is more common in women with germline BRCA1 mutations. However, the morphologic changes and molecular mechanisms that lead to secretory cell transformation are unknown. Specifically, the role of ciliated cells in the formation of precursor FTE lesions is unknown. Preliminary data: Our histologic and molecular analyses of FTE from BRCA1 mutation carriers and non-carriers revealed that postmenopausal BRCA1 mutation carriers have a higher ratio of secretory to ciliated cells and increased levels of the cell survival-associated genes CDK1 and Survivin, suggesting that secretory cells escape cell death. Unexpectedly, we observed that homotypic cell segregation and loss of ciliated cells precede secretory cell accumulation. Hypothesis: We propose that homotypic cell signaling and loss of ciliated cells create a favorable microenvironment for secretory cell transformation in BRCA1 mutant FTE providing that other conditions, such as hormonal changes and genotoxic stress, coincide and tip the balance toward uncontrolled proliferation. Unique resources: We are the first group to differentiate induced pluripotent stem cells (iPSCs) into FTE and establish iPSC organoids from BRCA1 mutation carriers and non-carriers. We have one of the largest collections of FTE specimens with detailed clinicopathologic and demographic data from high-risk patients. We will leverage our recently developed computational imaging convolutional neural networks pipeline for extraction of “hidden” preneoplastic characteristics for biomarker development and identification of potential targets for prevention. Specific Aims: In Aim 1, we will use human and mouse FTE organoids and in vivo mouse models to test the hypothesis that ciliated cells protect secretory cells from genotoxic stress. In Aim 2, we will test the hypothesis that aberrant secretory cell survival under genotoxic stress can be counteracted by pharmacologic inhibitors of genes involved in cell survival, such as CDK1 and Survivin. In Aim 3, we will integrate RNA sequencing and image processing with deep-neural network learning to identify clinically-relevant molecular and histomorphometric biomarkers of preneoplastic lesions in fallopian tubes from BRCA1 mutation carriers. Impact: This research will lead to a better understanding of the interplay between predisposing genetic mutations and the microenvironmental changes that precede ovarian cancer initiation. Identifying potential molecular and morphometric contributors to the formation of the precancer niche will assist in the development of new strategies for ovarian cancer prevention and detection, which are urgently needed in clinical practice.