基于代谢组学方法的影像学难辨肝占位诊断体系的建立

About 10% of the hepatic lesions in clinic can not be properly diagnosed by the routine imaging approaches. These lesions are therefore termed as radiologically indistinguishable hepatic lesions (RIHL). Currently, RIHL can only be diagnosed by invasive diagnostic methods such as liver biopsy. However, considering invasive methods harbor potential serious complications and are not well accepted by patients, novel non-invasive diagnostic method is thus urgently needed. In our preliminary study, we explored the metabolic characterizations of 3 most common types of RIHL with 70 tumor tissues. The results demonstrated that despite manifesting similar imaging features, the 3 tested types of RIHL showed significantly different metabolic profiles that could be used to completely separate them from each other. Our data suggested that metabolomics could be an important tool for the development of new diagnostic system for RIHL. Therefore, in the current study, we aimed to further determine the signature metabolites in an expanded spectrum of RIHL with much more comprehensive analysis. We will finally establish and evaluate a novel metabolomics-based diagnostic model for RIHL. In addition, we will particularly focus on the signature metabolites we found in hepatocellular carcinoma (HCC), and carry out a series of functional experiments digging the related genes and proteins. Moreover, the correlation between the signature metabolites and the clinical characteristics of patients will also be analyzed. We believe that our study will gain a major step forward to the resolution for the diagnosis of RIHL and a better understanding of HCC.

临床中大约有10%的肝脏占位无法通过影像学检查获得正确的诊断，我们将这类肝占位称为影像学难辨肝占位(RIHL)。RIHL目前仅能依靠有创方法确诊，但有创方法存在患者依从性差及潜在的并发症等诸多限制，使得肝占位的临床诊断存在部分盲区，亟需新的无创性诊断方法介入。我们在前期研究中用代谢组学方法检测了70例RIHL肿瘤组织内的全代谢物谱，结果显示尽管这些肝占位的影像学表现类似，但却存在着的各自不同的特征性的代谢物谱，利用这些差异代谢物可以将RIHL明确的区分开来。因此，我们拟在前期研究的基础上，通过更为系统的代谢组学比对，从代谢物的角度还原出各种常见RIHL的代谢组学特征，最终建立一套精确、多维的诊断体系，为解决临床RIHL的诊断提供新思路、新方法。此外，我们还将就肝癌的特征性代谢物进行功能学和临床相关性的分析，为更好的理解肝癌的发生和发展相关机制提供新的证据。

临床中大约有10%的肝脏占位无法通过影像学检查获得正确的诊断，我们将这类肝占位称.为影像学难辨肝占位(RIHL)。RIHL目前仅能依靠有创方法确诊，但有创方法存在患者依从性差及潜在的并发症等诸多限制，使得肝占位的临床诊断存在部分盲区，亟需新的无创性诊断方法介入。我们在本研究中利用代谢组学方法检测了大量原发性肝细胞癌、肝腺瘤、局灶结节性增生、炎性假瘤、胆管细胞癌等5种临床上常见的肝脏良、恶性占位性病变的肿瘤组织，并建立了上述肝脏占位特征性代谢物谱。在此基础上，通过大量无创标本检测，建立了两套基于代谢组学技术的无创诊断模型，实现了基于代谢组学技术的肝脏占位良性/恶性的鉴别诊断以及肝细胞癌与胆管细胞癌的鉴别诊断。在此基础上，我们通过大量完成代谢组学检测的临床病例随访，进一步明确了我们鉴别的肝脏占位特异性代谢谱是否可以用于鉴别两种肝脏恶性肿瘤生物学行为及恶性程度，评估治疗效果，预测临床预后。进一步拓展代谢组学模型的潜在临床应用场景，扩大了我们研究的临床应用价值。此外，我们还通过生物信息学分析，从特征性代谢物出发，结合基因组学、转录组学数据，反向回溯研究的各种RIHL发生发展中可能的机制，特别是代谢相关机制，进一步丰富上述肝脏占位的发病机制。