Bioinformatic Tools in Cancer Research

癌症基因组图谱计划（TCGA）等大规模肿瘤基因组改变研究产生的多维癌症基因组数据有望极大地促进对癌症病因的理解、新药物靶点的鉴定以及基于肿瘤基因组图谱的个性化治疗的开发。我们小组开发了分析工具，并积极参与TCGA整合基因组数据的分析。我们首先发现NF1是多形性胶质母细胞瘤（GBM）中最常见的突变基因之一，这一发现后来在《自然》杂志上发表的TCGA网络论文中得到了验证和报道(1)。TCGA网络成员使用我们的可视化工具来识别GBM的核心通路。最近，我们发现并向TCGA项目领导报告了TCGA卵巢肿瘤中BRCA1/2种系突变的广泛杂合性缺失和逆转。这些发现已经被下一代测序数据所证实。我们还与TCGA项目团队合作，准备一份手稿，提供在试点研究中发现的重要基因的突变谱的更新。除了为TCGA做出贡献外，我们小组还负责NCI的治疗应用研究以产生有效治疗（TARGET）项目的突变分析。最近，我们发现了一种新的复发性体细胞突变，这种突变仅在临床预后较差的急性淋巴细胞白血病（ALL）患者中发现（2,3）。这些突变引起JAK受体酪氨酸激酶基因的组成性激活，该基因的化学抑制剂的可用性表明，这一发现可以转化为治疗预后不良的ALL患者的新疗法(2)。基于这一发现的I期临床试验目前正在由NCI CTEP和儿童肿瘤组组织。我们目前正在准备一份手稿，总结ALL中受体细胞突变和拷贝数改变影响的主要生物学途径。我们还在TARGET神经母细胞瘤（NBL）肿瘤中发现了激活ALK的体细胞突变。在TARGET NBL的领导下，一项ALK抑制治疗难治性NBL儿童的临床试验正在进行中。我们正在与博士合作。圣犹达儿童医院的James Downing和Charles Mulligan比较了诊断时和复发时发生的体细胞突变变化，以深入了解导致治疗失败的生物学途径。我们开发了新的分析方法来分析下一代测序数据，重点分析融合蛋白和插入/缺失。这些事件很难被当前的下一代映射方法检测到。在对三个ALL样本的下一代数据的分析中，我们发现了新的插入/缺失，这些插入/缺失可以破坏蛋白质功能和影响25%转录组的选择性剪接事件。当有数据时，我们将参与TCGA项目中TCGA卵巢和GBM的Next-gen测序数据分析。了解药物反应的机制对于开发有效的癌症治疗至关重要。在与博士合作。Jim Doroshow和Anne Monks，我们分析了NCI-60细胞系面板中药物诱导的基因表达变化与药物敏感性的相关性。从未处理的细胞系以及低或高浓度药物处理2hr、6hr和24hr的细胞系中收集表达数据。每个细胞系的药物敏感性计算为GI50（即50%生长抑制浓度）。到目前为止，我们已经分析了阿霉素、硼替佐米、紫杉醇、达沙替尼和舒尼替尼收集的数据。每种药物在大规模细胞转录变化的开始，对低与高治疗的反应以及受影响的生物学途径方面都是独特的。对于阿霉素，我们发现了MDR-1和p53通路的激活对doxo敏感性的双重贡献，在NCI60细胞系面板上建立了p53通路激活与野生型p53突变体p16的复合基因型之间的强烈关联。对于达沙替尼，2小时诱导MYC似乎是与药物敏感性相关的标志。对于舒尼替尼，参与细胞生长的酪氨酸激酶基因（如EGFR、STAT和KRAS）的激活似乎与药物敏感性有关。实验验证正在进行中，以评估我们的分析确定的候选基因。

Multi-dimensional cancer genomic data generated by large-scale investigations of tumor genomic alterations such as the The Cancer Genome Atlas Project (TCGA) is expected to greatly facilitate understanding of cancer etiology, identification of novel drug targets and development of personalized treatment based on tumor genomic profiling. Our group has developed analytical tools and has actively participated in the analysis of the integrated genomic data for TCGA. We were the first to identify NF1 as one of the most frequently mutated genes in glioblastoma multiforme (GBM), a finding that was later validated and reported in the TCGA network paper published in Nature (1). Our visualization tools were used by the TCGA network members in identifying core pathways involved in GBM. Recently we discovered and reported to TCGA project leadership extensive loss of heterozygosity and reversion of germline mutations in BRCA1/2 in TCGA ovarian tumors. These findings have been validated by Next-generation sequencing data. We are also collaborating with TCGA project team on preparing a manuscript that gives an update of mutation profile of the significant genes identified in the pilot study. Besides contributing to TCGA, our group has been responsible for analyzing mutations for NCI's Therapeutically Applicable Research to Generate Effective Treatments (TARGET) project. Recently we identified novel recurrent somatic mutations that were only found in acute lymphoblastic leukemia (ALL) patients with poor clinical outcome (2, 3). These mutations cause constitutive activation of the JAK receptor tyrosine kinase gene, and the availability of chemical inhibitors of this gene suggest that this finding can be translated into a novel therapy for poor outcome ALL patients (2). Phase I clinical trial based on this finding is currently being organized by NCI CTEP and Childrens Oncology Group. We are currently preparing a manuscript that summarizes the major biological pathways affected by somatic mutations and copy number alterations in ALL. We have also identified activating somatic mutations in ALK in TARGET neuroblastoma (NBL) tumors. A clinical trial of ALK inhibition therapy for children with refractory NBL is ongoing under the leadership of TARGET NBL. We have ongoing collaboration with Drs. James Downing and Charles Mulligan at St. Jude Childrens Hospital to compare the somatic mutation changes occurred at diagnosis and those at the relaps to gain insight into biological pathways that involved in failure to treatment. We have developed novel analytical methods for analyzing Next-generation sequencing data focusing on the analysis of fusion protein and insertion/deletions. These events are difficult to be detected by current Next-gen mapping methods. In an analysis of Next-gen data of three ALL samples, we have identified novel insertion/deletions that can disrupt protein function and alternative splicing events that affect 25% of the transcriptome. We will participate in the Next-gen sequencing data analysis of TCGA Ovarian and GBM for the TCGA project when the data is available. Understanding the mechanisms of drug response is critical for developing effective cancer therapy. In collaboration with Drs. Jim Doroshow and Anne Monks, we analyzed the correlation between drug-induced gene expression changes and drug sensitivity in the NCI-60 cell line panel. Expression data were collected from untreated cell lines as well as those treated with low- or high-concentration drug for 2hr, 6hr and 24hr. Drug sensitivity was calculated as GI50 (i.e. 50% growth inhibitory concentration) for each cell line. To date, we have analyzed data collected from doxorubicin, bortezomib, taxol, dasatinib, and sunitinib. Each drug is unique in the onset of massive cellular transcription change, response to low versus high treatment and affected biological pathways. For doxorubicin, we identified that the dual contribution of MDR-1 and activation of the p53 pathway to DOXO-sensitivity, establishing a strong association between the p53 pathway activation with the composite genotype of wild-type p53 mutant p16 across the NCI60 cell line panel. For dasatinib, induction of MYC at 2 hours appear to be a hallmark associated with drug sensitivity. For sunitinib, activation of tyrosine kinase genes involved in cellular growth such as EGFR, STAT and KRAS appear to be associated with drug sensitivity. Experimental validation is ongoing to evaluate the candidate genes identified by our analysis.