Nishimura Toshihide, Kawamura Takeshi, Sugihara Yutaka, Bando Yasuhiko, Sakamoto Shigeru, Nomura Masaharu, Ikeda Norihiko, Ohira Tatsuo, Fujimoto Junichiro, Tojo Hiromasa, Hamakubo Takao, Kodama Tatsuhiko, Andersson Roland, Fehniger Thomas E, Kato Harubumi, Marko-Varga György
First Department of Surgery, Tokyo Medical University, 6-7-1 Nishishinjuku Shinjuku-ku, Tokyo, 160-0023 Japan.
Laboratory for Systems Biology and Medicine, Research Center for Advanced Science and Technology, The University of Tokyo, 4-6-1, Komaba, Meguro-Ku, Tokyo, 153-8904 Japan.
Clin Transl Med. 2014 Nov 22;3(1):61. doi: 10.1186/s40169-014-0038-x. eCollection 2014 Dec.
The Tokyo Medical University Hospital in Japan and the Lund University hospital in Sweden have recently initiated a research program with the objective to impact on patient treatment by clinical disease stage characterization (phenotyping), utilizing proteomics sequencing platforms. By sharing clinical experiences, patient treatment principles, and biobank strategies, our respective clinical teams in Japan and Sweden will aid in the development of predictive and drug related protein biomarkers. Data from joint lung cancer studies are presented where protein expression from Neuro- Endocrine lung cancer (LCNEC) phenotype patients can be separated from Small cell- (SCLC) and Large Cell lung cancer (LCC) patients by deep sequencing and spectral counting analysis. LCNEC, a subtype of large cell carcinoma (LCC), is characterized by neuroendocrine differentiation that small cell lung carcinoma (SCLC) shares. Pre-therapeutic histological distinction between LCNEC and SCLC has so far been problematic, leading to adverse clinical outcome. An establishment of protein targets characteristic of LCNEC is quite helpful for decision of optimal therapeutic strategy by diagnosing individual patients. Proteoform annotation and clinical biobanking is part of the HUPO initiative (http://www.hupo.org) within chromosome 10 and chromosome 19 consortia.
日本的东京医科大学医院和瑞典的隆德大学医院最近启动了一项研究计划,旨在利用蛋白质组学测序平台,通过临床疾病阶段特征描述(表型分析)来影响患者治疗。通过分享临床经验、患者治疗原则和生物样本库策略,我们在日本和瑞典的各自临床团队将助力预测性和药物相关蛋白质生物标志物的开发。文中展示了联合肺癌研究的数据,其中通过深度测序和光谱计数分析,可将神经内分泌肺癌(LCNEC)表型患者的蛋白质表达与小细胞肺癌(SCLC)和大细胞肺癌(LCC)患者的蛋白质表达区分开来。LCNEC是大细胞癌(LCC)的一种亚型,其特征是具有小细胞肺癌(SCLC)所共有的神经内分泌分化。到目前为止,LCNEC和SCLC之间的治疗前组织学区分一直存在问题,导致不良临床结果。建立LCNEC特有的蛋白质靶点对于通过诊断个体患者来决定最佳治疗策略非常有帮助。蛋白质异构体注释和临床生物样本库是人类蛋白质组组织(HUPO)计划(http://www.hupo.org)在10号染色体和19号染色体联盟中的一部分。