Extraordinary responder cell lines reveal unique targetable genetic dependencies

 描述(申请人提供)：我们实验室、布罗德研究所和Dana-Farber癌症研究所的成员已经在数百个癌细胞株和肿瘤样本中生成了大规模数据集，其中包括遗传相关性筛选和基因表达谱。我们小组分析了大规模RNAi实验的现有数据，发现了腔内乳腺癌细胞生存所需的多个基因。这些基因包括转录因子SPDEF、先驱因子FOXA1以及组蛋白修饰酶KDM1A和MLL2。由于这些基因的敲除会导致存活率的大幅下降，特别是在管腔癌细胞中，用小分子抑制这些必要的蛋白质可能会导致一个很大的治疗窗口，在这个窗口中，癌细胞将成为靶点，正常细胞将得以幸免。在以前的研究中，这些基因都与雌激素受体(ER)信号相关；然而，我们的数据表明，这些基因在ER阴性的腔内乳腺癌细胞生长中也是必要的。这项建议旨在确定这些基因在腔内乳腺癌细胞信号传递和生存中的作用，以便设计和测试潜在的治疗策略。我们实验室在乳腺癌基因组学方面的专业知识以及通过癌症细胞系百科全书(CCLE)和癌症基因组图谱(TCGA)访问大型基因组数据库的能力为研究这些基因提供了独特的机会。我们将利用这些数据来确定内质网非依赖性SPDEF的表达是否由基因组改变驱动。我们还将评估抑制染色质修饰物KDM1A和MLL2作为治疗这一亚型乳腺肿瘤的潜在策略的有效性。虽然存在治疗选择，但大量的管腔性乳腺癌患者对最新的靶向治疗如抗雌激素激素治疗或抗ERBB2抗体没有反应。彻底研究这些额外的依赖基因的作用可能会为那些临床需求未得到满足的患者开辟新的治疗途径或加强现有的治疗方法。验证这些相关性将增加治疗靶点的数量，并进一步对管腔乳腺癌患者进行分层，从而使肿瘤遗传背景和靶向治疗最佳匹配。

 DESCRIPTION (provided by applicant): Members of our laboratory, the Broad Institute and the Dana-Farber Cancer Institute have generated large-scale datasets in hundreds of cancer cell lines and tumor samples, which include genetic dependency screens and gene expression profiles. Our group analyzed existing data from large-scale RNAi experiments and found multiple genes that are required for luminal breast cancer cell survival. These include the transcription factor SPDEF, the pioneer factor FOXA1, and the histone modifying enzymes KDM1A and MLL2. Because knockdown of these genes results in a robust decrease in survival specifically in luminal breast cancer cells, inhibiting these essential proteins with small molecules would likely result in a large therapeutic window where cancer cells would be targeted and normal cells would be spared. These genes have all been associated with estrogen receptor (ER) signaling in previous studies; however, our data suggest that these genes are also necessary in ER-negative luminal breast cancer cell growth. This proposal seeks to determine the role of these genes in luminal breast cancer cell signaling and survival so that potential therapeutic strategies can be designed and tested. Our laboratory's expertise in breast cancer genomics and access to large genomic datasets via the Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Atlas (TCGA) presents unique opportunities to study these genes. We will utilize these data to determine if ER-independent SPDEF expression is driven by genomic alterations. We will also assess the efficacy of inhibiting the chromatin modifiers KDM1A and MLL2 as a potential strategy to treat this subset of breast tumors. While treatment options exist, a large number of luminal breast cancer patients do not respond to the latest targeted therapies such as anti-estrogen hormone treatment or anti-ERBB2 antibodies. Thoroughly studying the role of these additional dependent genes may open new therapeutic avenues or enhance existing treatments for those patients with unmet clinical needs. Validating these dependencies would increase the number of therapeutic targets and further stratify luminal breast cancer patients so that tumor genetic contexts and targeted therapies are optimally matched.