MODELING MALIGNANT PROGRESSION IN GLIOMA

摘要 胶质瘤是人类最常见、最致命的原发脑瘤。高度恶性的胶质瘤 更多的惰性较低级别的胶质瘤。尽管低级别胶质瘤(LGG)的患者可以存活 多年来，他们的肿瘤几乎不可避免地发展为高级别胶质瘤(HGG)，之后死亡发生在 12到15个月。恶性进展的过程人们知之甚少。我们已发表的研究(由 临床科学家指导计划[K08])表明，抗凋亡信号在促进 从LGG到HGG的演变。我们还表明，抑制细胞凋亡导致了 肿瘤微环境中的免疫抑制。此外，我们已经使用几个 免疫治疗策略，逆转肿瘤内免疫抑制可减轻恶性 小鼠脑胶质瘤模型的进展。我们现在假设，抗细胞凋亡信号促进恶性 诱导免疫抑制的肿瘤微环境在胶质瘤中的进展。一个主要障碍是 对恶性进展的研究一直是缺乏匹配的LGGs和HGGs的患者样本 他们进步了。然而，我们已经确定了250多名同时接受了LGG和后来的HGG治疗的患者 安德森癌症中心。对来自这些患者的匹配肿瘤样本的分析代表了一种独特的 为研究恶性进展提供了机会。在拟议的工作中，我们将利用下一步- 世代测序(NGS)来研究LGG退化为HGG的机制。在AIM 1，我们将使用NGS来鉴定在HGGs中相对于LGGs过表达的抗凋亡基因。一个 对这些基因在免疫活性小鼠胶质瘤模型中的功能分析将确定它们的 免疫抑制和促进恶性转化的作用。在目标2中，我们将研究两种抗细胞凋亡药物 基因(MCL-1和BIRC3)已成为免疫抑制的主要促进剂 TCGA、LGG和HGG的表达数据以及我们自己的患者内部队列。我们将对这些进行建模 体内基因，以确定它们对恶性进展的影响。在目标3中，我们将分析我们的标本以 识别激活趋化因子的转录因子，已知的趋化因子可导致KEY的肿瘤内流入 免疫抑制细胞。这些转录因子将在体内模拟，以确定它们对 恶性进展。识别导致恶性进展的因素将有可能使我们 以减轻疾病进展的原因。因此，肿瘤可能维持在更惰性的低级别状态。 而不是进展为HGG，显著延长生存时间。最终，我们的结果可能也适用于 到其他肿瘤类型，表现出从低级别病变到高级别病变的进展。这项工作正在进行中 与基因表达谱、计算生物学、生物统计学和 脑瘤免疫学。我们还将利用MD Anderson的测序和微阵列设备。

SUMMARY Glioma is the most common and deadliest primary brain tumor in humans. Highly malignant gliomas often arise from more indolent lower grade gliomas. Although patients with low-grade gliomas (LGG) may survive for many years, their tumors almost inevitably progress to high-grade gliomas (HGG), after which death occurs in 12 to 15 months. The process of malignant progression is poorly understood. Our published studies (funded by a Mentored Clinical Scientist Program [K08]) showed that anti-apoptotic signaling plays a key role in facilitating the progression of LGG to HGG. We also showed that suppression of apoptosis caused profound immunosuppression in the tumor microenvironment. Furthermore, we have shown, using several immunotherapeutic strategies, that reversing intratumoral immunosuppression can mitigate malignant progression in a murine model of glioma. We now hypothesize that antiapoptotic signaling promotes malignant progression in glioma by inducing an immunosuppressive tumor microenvironment. A major obstacle to studying malignant progression has been the lack of matched patient samples of LGGs and the HGGs to which they progress. However, we have identified over 250 patients who were treated for both LGG and later HGG at MD Anderson Cancer Center. The analysis of matched tumor samples from these patients represents a unique opportunity for the study of malignant progression. In the proposed work, we will take advantage of next- generation sequencing (NGS) to investigate the mechanisms through which LGG degenerates to HGG. In Aim 1, we will use NGS to identify anti-apoptotic genes that are overexpressed in HGGs relative to LGGs. A functional analysis of these genes in an immune competent murine model of glioma will determine their immunosuppression- and malignant transformation–promoting effects. In Aim 2, we will study two antiapoptotic genes (MCL-1 and BIRC3) that have emerged as lead facilitators of immunosuppression from analysis of TCGA LGG and HGG expression data as well as our own internal cohort of patients. We will model these genes in vivo to determine their impact on malignant progression. In Aim 3, we will profile our specimens to identify transcription factors that activate chemokines known to cause the intratumoral influx of key immunosuppressive cells. These transcription factors will be modeled in vivo to determine their effect on malignant progression. Identifying the factors that contribute to malignant progression will potentially enable us to mitigate the causes of progression. Thus, tumors may be maintained in the more indolent low-grade state rather than progressing to HGG, significantly prolonging survival. Ultimately, our results may also be applicable to other tumor types that demonstrate progression from a low- to high-grade lesion. This work is being done in collaboration with recognized experts in gene expression profiling, computational biology, biostatistics, and brain tumor immunology. We will also leverage MD Anderson’s Sequencing and Microarray Facility.