Molecular characterisation and diagnosis of malignant mesothelioma

恶性间皮瘤是一种与石棉相关的侵袭性肿瘤，在全球范围内发病率不断上升，估计每年导致约20,000人死亡。多发性骨髓瘤在大约20-30年前还很罕见，但现在在澳大利亚，它更像是一种常见的死因，如骨癌、肝癌、子宫颈癌、膀胱癌和卵巢癌。尽管在大多数发达国家，石棉使用量已经下降到几乎为零，但由于这种疾病的潜伏期为30到40年，间皮瘤病例的高峰预计要到2010年才会达到。MM是已知的最具侵袭性和衰弱的肿瘤之一，中位生存期为7-10个月，临床模式通常包括剧烈疼痛和呼吸困难。间皮瘤治疗预防方面的进展不仅会对健康产生重大影响，而且可能会产生非同寻常的经济影响。据预测，MM将在未来35-40年内让澳大利亚经济损失约50亿美元的补偿。政府、保险公司和行业将分担这一成本。因此，这种疾病的重要性超出了它的实际发病率。在许多肿瘤类型中，越来越多的证据表明，了解癌症发生的分子逻辑，并相应地设计治疗方法和诊断方法，将产生最好的癌症诊断和治疗方法。我们将开展一个项目，利用现有的最全面的微阵列来分析恶性间皮瘤的基因表达。我们将使用我们获得的表情数据来实现三个目标。首先，我们将使用患者结果信息来搜索其表达指示治疗反应的基因。其次，我们将搜索数据，以确定可能有助于MM早期检测的候选分泌分子。最后，我们将建立一种分子检测方法，从收集的胸腔积液细胞中明确诊断MM。

Malignant mesothelioma (MM) is an aggressive, asbestos-related tumour of increasing incidence throughout the world that is estimated to be cause approximately 20,000 deaths per annum . MM was rare until approximately 20-30 years ago but it is now more, or as, common a cause of death in Australia as cancers of the bone, liver, cervix, bladder and ovary. Although asbestos use has declined to virtually zero across most of the developed world, due to 30 to 40 year latency of the disease, the peak in cases of mesothelioma is not expected until 2010. MM is one of the most aggressive and debilitating tumours known, with a median survival of 7-10 months and a clinical pattern that usually involves substantial pain and dyspnea. Advances in therapy-prevention of mesothelioma will have not only have a major health impact, but potentially an extraordinary economic impact. MM is predicted to cost the Australian economy around $5 billion in compensation over the next 35-40 years. Government, insurance companies and industry will share that cost. The significance of this disease therefore extends beyond its actual incidence. There is growing evidence in many tumour types that the best diagnostics and treatments for cancer will come about as a result of understanding the molecular logic that underpins carcinogenesis, and designing therapies and diagnostics accordingly. We will carry out a project using the most comprehensive microarrays available to profile gene expression in malignant mesothelioma. We will use the expression data we obtain to fulfil three aims. Firstly, we will use patient outcome information to search for genes whose expression is indicative of response to therapy. Secondly, we will search the data to identify candidate secreted molecules which may be useful in the early detection of MM. Finally, we will develop a molecular assay to unequivocally diagnose MM from cells collected from pleural effusions.