A bioinformatics-to-clinic sequential approach to analysis of prostate cancer biomarkers using TCGA datasets and clinical samples: a new method for precision oncology?
A bioinformatics-to-clinic sequential approach to analysis of prostate cancer biomarkers using TCGA datasets and clinical samples: a new method for precision oncology?
复制标题
DOI：
10.18632/oncotarget.20448
复制
发表时间：
2017-11-21
期刊：
影响因子：
--
通讯作者：
Sato K
中科院分区：
文献类型：
--
作者：
Yoshie H;Sedukhina AS;Minagawa K;Oda K;Ohnuma S;Yanagisawa N;Maeda I;Takagi M;Kudo H;Nakazawa R;Sasaki H;Kumai T;Chikaraishi T;Sato K
生物标志物驱动的癌症治疗取得了显著的临床成功。如果我们要开发这些类型的治疗方法，就需要识别与恶性表型相关并与不良临床结果相关的生物标志物。前列腺癌（PACa）病例的一个子集是治疗耐药的，使它们成为这种方法的一个有吸引力的目标。为了确定与缩短PACa患者生存期有关的靶分子，我们建立了一种生物信息学到临床的序列分析方法，首先对局部PACa的TCGA数据集进行两步计算机分析。通过计算机分析确定的候选基因对生存的影响，然后使用在初始诊断局部和转移性PACa时采集的活检标本进行评估。我们将PEG10确定为候选生物标志物。来自临床样本的数据表明，在初始诊断时PEG10的表达增加与较短的生存时间有关。有趣的是，PEG10的过表达也与嗜铬粒蛋白A和突触素的表达相关，这是神经内分泌前列腺癌（一种治疗抵抗性前列腺癌）的标志物。这些结果表明，PEG10是缩短PACa患者生存期的一种新的生物标志物。此外，初步诊断时PEG10的表达可以预测PACa的局灶性神经内分泌分化。因此，PEG10可能是生物标志物驱动的癌症治疗的一个有吸引力的靶点。因此，生物信息学到临床的序列分析是确定精确肿瘤学靶点的有效工具。
Biomarker-driven cancer therapy has met with significant clinical success. Identification of a biomarker implicated in a malignant phenotype and linked to poor clinical outcome is required if we are to develop these types of therapies. A subset of prostate adenocarcinoma (PACa) cases are treatment-resistant, making them an attractive target for such an approach. To identify target molecules implicated in shorter survival of patients with PACa, we established a bioinformatics-to-clinic sequential analysis approach, beginning with 2-step in silico analysis of a TCGA dataset for localized PACa. The effect of candidate genes identified by in silico analysis on survival was then assessed using biopsy specimens taken at the time of initial diagnosis of localized and metastatic PACa. We identified PEG10 as a candidate biomarker. Data from clinical samples suggested that increased expression of PEG10 at the time of initial diagnosis was linked to shorter survival time. Interestingly, PEG10 overexpression also correlated with expression of chromogranin A and synaptophysin, markers for neuroendocrine prostate cancer, a type of treatment-resistant prostate cancer. These results indicate that PEG10 is a novel biomarker for shorter survival of patients with PACa. Also, PEG10 expression at the time of initial diagnosis may predict focal neuroendocrine differentiation of PACa. Thus, PEG10 may be an attractive target for biomarker-driven cancer therapy. Thus, bioinformatics-to-clinic sequential analysis is a valid tool for identifying targets for precision oncology.
登录
查看更多内容
影响因子：
50.3
作者：
Taylor BS;Schultz N;Hieronymus H;Gopalan A;Xiao Y;Carver BS;Arora VK;Kaushik P;Cerami E;Reva B;Antipin Y;Mitsiades N;Landers T;Dolgalev I;Major JE;Wilson M;Socci ND;Lash AE;Heguy A;Eastham JA;Scher HI;Reuter VE;Scardino PT;Sander C;Sawyers CL;Gerald WL
通讯作者：
Gerald WL
影响因子：
3
作者：
Sun J;Nishiyama T;Shimizu K;Kadota K
通讯作者：
Kadota K
影响因子：
3.7
作者：
Nagasawa S;Sedukhina AS;Nakagawa Y;Maeda I;Kubota M;Ohnuma S;Tsugawa K;Ohta T;Roche-Molina M;Bernal JA;Narváez AJ;Jeyasekharan AD;Sato K
通讯作者：
Sato K
影响因子：
23.4
作者：
Barbieri, Christopher E.;Chinnaiyan, Arul M.;Lerner, Seth P.;Swanton, Charles;Rubin, Mark A.
通讯作者：
Rubin, Mark A.
影响因子：
158.5
作者：
Druker, Brian J.;Guilhot, Francois;Larson, Richard A.
通讯作者：
Larson, Richard A.