Comprehensive expression profiling of tumor cell lines identifies molecular signatures of melanoma progression.
Comprehensive expression profiling of tumor cell lines identifies molecular signatures of melanoma progression.
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肿瘤细胞系的全面表达分析鉴定了黑色素瘤进展的分子特征。
DOI：
10.1371/journal.pone.0000594
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发表时间：
2007-07-04
期刊：
影响因子：
3.7
通讯作者：
Alani, Rhoda M.
中科院分区：
文献类型：
--
作者：
Ryu, Byungwoo;Kim, Dave S.;DeLuca, Amena M.;Alani, Rhoda M.
基因表达谱已经彻底改变了我们对原发性人类肿瘤进行分子分类的能力，并显著增强了新型肿瘤标志物和疗法的开发;然而，在过去30年中，黑色素瘤的诊断和治疗进展有限，目前还没有批准的治疗方法可以显著延长晚期疾病患者的寿命。由于这种恶性肿瘤的异质性和疾病早期提供信息的组织标本的有限性，迄今为止对黑色素瘤的分析研究一直不一致。为了更好地了解黑色素瘤进展的分子基础，我们比较了一系列黑色素瘤细胞系的基因表达谱，这些细胞系代表了恶性进展的离散阶段，概括了它们所来源的原发性病变的关键特征。在这里，我们描述了来自黑色素瘤细胞系和黑素细胞的分析数据的无监督分层聚类。这种聚类鉴定了黑色素瘤的两种不同的分子亚类，将侵袭性转移性肿瘤细胞系与侵袭性较低的原发性肿瘤细胞系分离。使用功能注释对与黑素瘤进展相关的表达特征的进一步分析将这些转录物分类为三类基因：1）细胞周期进程、DNA复制和修复的激活剂的上调（CDCA 2、NCAPH、NCAPG、NCAPG 2、PBK、NUSAP 1、BIRC 5、ESCO 2、HELS、MELK、GINS 1、GINS 4、RAD 54 L、TYMS和DHFR），2）与细胞粘附和黑素细胞分化相关的基因（CDH 3、CDH 1、c-KIT、PAX 3、CITED 1/MSG-1、TYR、MELANA、MC 1 R和OCA 2）的丢失，3）与细胞凋亡抗性相关的基因（BIRC 5/存活素）的上调。虽然这些广泛类别的转录本先前已涉及黑色素瘤和其他恶性肿瘤的进展，但在每一类转录本中鉴定的特定基因是新颖的。此外，转录因子NF-κ B被特别鉴定为黑色素瘤侵袭的潜在“主调节因子”，因为NF-κ B结合位点被鉴定为进展相关基因启动子内的一致共有序列。我们的结论是，肿瘤细胞系是一个有价值的资源，早期识别的基因签名与恶性进展的肿瘤具有显着的异质性，如黑色素瘤。我们进一步得出结论，新的数据减少算法的发展，分析微阵列研究是至关重要的，允许优化挖掘重要的，临床相关的数据集。预计使用这种方法在原代人体组织中进行的后续验证研究将使这些研究更快速地转化为新的肿瘤生物标志物和治疗靶点的鉴定。
Gene expression profiling has revolutionized our ability to molecularly classify primary human tumors and significantly enhanced the development of novel tumor markers and therapies; however, progress in the diagnosis and treatment of melanoma over the past 3 decades has been limited, and there is currently no approved therapy that significantly extends lifespan in patients with advanced disease. Profiling studies of melanoma to date have been inconsistent due to the heterogeneous nature of this malignancy and the limited availability of informative tissue specimens from early stages of disease. In order to gain an improved understanding of the molecular basis of melanoma progression, we have compared gene expression profiles from a series of melanoma cell lines representing discrete stages of malignant progression that recapitulate critical characteristics of the primary lesions from which they were derived. Here we describe the unsupervised hierarchical clustering of profiling data from melanoma cell lines and melanocytes. This clustering identifies two distinctive molecular subclasses of melanoma segregating aggressive metastatic tumor cell lines from less-aggressive primary tumor cell lines. Further analysis of expression signatures associated with melanoma progression using functional annotations categorized these transcripts into three classes of genes: 1) Upregulation of activators of cell cycle progression, DNA replication and repair (CDCA2, NCAPH, NCAPG, NCAPG2, PBK, NUSAP1, BIRC5, ESCO2, HELLS, MELK, GINS1, GINS4, RAD54L, TYMS, and DHFR), 2) Loss of genes associated with cellular adhesion and melanocyte differentiation (CDH3, CDH1, c-KIT, PAX3, CITED1/MSG-1, TYR, MELANA, MC1R, and OCA2), 3) Upregulation of genes associated with resistance to apoptosis (BIRC5/survivin). While these broad classes of transcripts have previously been implicated in the progression of melanoma and other malignancies, the specific genes identified within each class of transcripts are novel. In addition, the transcription factor NF-KB was specifically identified as being a potential “master regulator” of melanoma invasion since NF-KB binding sites were identified as consistent consensus sequences within promoters of progression-associated genes. We conclude that tumor cell lines are a valuable resource for the early identification of gene signatures associated with malignant progression in tumors with significant heterogeneity like melanoma. We further conclude that the development of novel data reduction algorithms for analysis of microarray studies is critical to allow for optimized mining of important, clinically-relevant datasets. It is expected that subsequent validation studies in primary human tissues using such an approach will lead to more rapid translation of such studies to the identification of novel tumor biomarkers and therapeutic targets.
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影响因子：
3.3
作者：
CLARK, WH;ELDER, DE;VANHORN, M
通讯作者：
VANHORN, M
影响因子：
15.3
作者：
HOUGHTON, AN;ALBINO, AP;EISINGER, M
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EISINGER, M
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64.5
作者：
Hirano, T;Kobayashi, R;Hirano, M
通讯作者：
Hirano, M
影响因子：
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作者：
Jaeger, Jochen;Koczan, Dirk;Kunz, Manfred
通讯作者：
Kunz, Manfred
DOI：
10.1016/s0925-4439(02)00079-0
发表时间：
2002-07-18
影响因子：
6.2
作者：
Banerjee, D;Mayer-Kuckuk, P;Bertino, JR
通讯作者：
Bertino, JR