Genome-wide analysis of three-way interplay among gene expression, cancer cell invasion and anti-cancer compound sensitivity.
Genome-wide analysis of three-way interplay among gene expression, cancer cell invasion and anti-cancer compound sensitivity.
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DOI：
10.1186/1741-7015-11-106
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发表时间：
2013-04-16
期刊：
影响因子：
9.3
通讯作者：
Li KC
中科院分区：
文献类型：
--
作者：
Hsu YC;Chen HY;Yuan S;Yu SL;Lin CH;Wu G;Yang PC;Li KC
化疗敏感性和肿瘤转移是癌症管理中的两个主要问题。癌细胞通常对抗癌化合物表现出广泛的敏感性。为了深入了解药物敏感性的遗传机制，一种强有力的方法是使用由美国国家癌症研究所（NCI）开发的60种人类癌细胞系。癌细胞还表现出广泛的侵袭能力。然而，全基因组的画像的贡献分子因素入侵异质性是缺乏的。我们的实验室对NCI-60板进行了侵袭测定。我们通过将我们的侵袭谱数据与NCI-60上的Affyellow基因表达数据相关联来鉴定侵袭相关（IA）基因。然后，我们利用最近公布的99种已知机制的抗癌药物的化疗敏感性数据来研究基因-药物相关性，重点是IA基因。之后，我们从四个独立的药物测试实验中收集数据，以验证我们对化合物反应预测的发现。最后，我们从两个最近的辅助化疗队列（一个关于肺癌，一个关于乳腺癌）中获得了已发表的临床和分子数据，以测试我们的基因签名对患者结局预测的性能。首先，我们从侵袭基因表达相关性研究中发现了633个IA基因。然后，对于99种药物中的每一种，我们获得了IA基因的一个子集，其表达水平与药物敏感性相关。我们确定了一组8个基因（EGFR、ITGA 3、MYLK、RAI 14、AHNAK、GLS、IL 32和NNMT），这些基因与紫杉醇、多西他赛、厄洛替尼、依维莫司和达沙替尼具有显著的基因-药物相关性。通过对78种肿瘤细胞系进行的总共107项独立药物测试验证了用于化学敏感性预测的八个基因签名（来自NCI-60），其中大部分在NCI-60组之外。八个基因签名预测肺癌和乳腺癌患者的无复发生存率（对数秩P = 0.0263; 0.00021）。多变量考克斯回归得出我们的签名的风险比分别为5.33（95%CI = 1.76至16.1）和1.81（95%CI = 1.19至2.76）。八个基因签名的特点是癌症标志表皮生长因子受体（EGFR）和参与细胞粘附，迁移，侵袭，肿瘤生长和进展的基因。我们的研究揭示了基因表达，侵袭和化合物敏感性之间复杂的三向相互作用。我们报告了一个独特的标志，预测肺癌和乳腺癌化疗生存的发现。通过体外表征重要的表型样侵袭潜力来增强NCI-60模型是一种为基因组化学敏感性分析提供动力的具有成本效益的方法。
Chemosensitivity and tumor metastasis are two primary issues in cancer management. Cancer cells often exhibit a wide range of sensitivity to anti-cancer compounds. To gain insight on the genetic mechanism of drug sensitivity, one powerful approach is to employ the panel of 60 human cancer cell lines developed by the National Cancer Institute (NCI). Cancer cells also show a broad range of invasion ability. However, a genome-wide portrait on the contributing molecular factors to invasion heterogeneity is lacking. Our lab performed an invasion assay on the NCI-60 panel. We identified invasion-associated (IA) genes by correlating our invasion profiling data with the Affymetrix gene expression data on NCI-60. We then employed the recently released chemosensitivity data of 99 anti-cancer drugs of known mechanism to investigate the gene-drug correlation, focusing on the IA genes. Afterwards, we collected data from four independent drug-testing experiments to validate our findings on compound response prediction. Finally, we obtained published clinical and molecular data from two recent adjuvant chemotherapy cohorts, one on lung cancer and one on breast cancer, to test the performance of our gene signature for patient outcome prediction. First, we found 633 IA genes from the invasion-gene expression correlation study. Then, for each of the 99 drugs, we obtained a subset of IA genes whose expression levels correlated with drug-sensitivity profiles. We identified a set of eight genes (EGFR, ITGA3, MYLK, RAI14, AHNAK, GLS, IL32 and NNMT) showing significant gene-drug correlation with paclitaxel, docetaxel, erlotinib, everolimus and dasatinib. This eight-gene signature (derived from NCI-60) for chemosensitivity prediction was validated by a total of 107 independent drug tests on 78 tumor cell lines, most of which were outside of the NCI-60 panel. The eight-gene signature predicted relapse-free survival for the lung and breast cancer patients (log-rank P = 0.0263; 0.00021). Multivariate Cox regression yielded a hazard ratio of our signature of 5.33 (95% CI = 1.76 to 16.1) and 1.81 (95% CI = 1.19 to 2.76) respectively. The eight-gene signature features the cancer hallmark epidermal growth factor receptor (EGFR) and genes involved in cell adhesion, migration, invasion, tumor growth and progression. Our study sheds light on the intricate three-way interplay among gene expression, invasion and compound-sensitivity. We report the finding of a unique signature that predicts chemotherapy survival for both lung and breast cancer. Augmenting the NCI-60 model with in vitro characterization of important phenotype-like invasion potential is a cost-effective approach to power the genomic chemosensitivity analysis.
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DOI：
10.1001/jama.2011.593
发表时间：
2011-05-11
期刊：
JAMA
影响因子：
--
作者：
Hatzis C;Pusztai L;Valero V;Booser DJ;Esserman L;Lluch A;Vidaurre T;Holmes F;Souchon E;Wang H;Martin M;Cotrina J;Gomez H;Hubbard R;Chacón JI;Ferrer-Lozano J;Dyer R;Buxton M;Gong Y;Wu Y;Ibrahim N;Andreopoulou E;Ueno NT;Hunt K;Yang W;Nazario A;DeMichele A;O'Shaughnessy J;Hortobagyi GN;Symmans WF
通讯作者：
Symmans WF
DOI：
10.1158/1078-0432.ccr-09-1314
发表时间：
2010-03-01
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
Houghton PJ
通讯作者：
Houghton PJ
影响因子：
3.3
作者：
Bulgaru, Anca M;Mani, Sridhar;Perez-Soler, Roman
通讯作者：
Perez-Soler, Roman
影响因子：
11.4
作者：
Goi, T;Shipitsin, M;Feig, LA
通讯作者：
Feig, LA
影响因子：
50.3
作者：
Neve, Richard M.;Chin, Koei;Gray, Joe W.
通讯作者：
Gray, Joe W.