Toward predicting metastatic progression of melanoma based on gene expression data.
Toward predicting metastatic progression of melanoma based on gene expression data.
复制标题
DOI：
10.1111/pcmr.12374
复制
发表时间：
2015-07
影响因子：
4.3
通讯作者：
Li L
中科院分区：
文献类型：
--
作者：
Li Y;Krahn JM;Flake GP;Umbach DM;Li L
原发性和转移性黑色素瘤肿瘤具有相同的细胞起源，这使得识别能够区分它们的基因组生物标志物具有挑战性。原发性肿瘤本身可能是异质的，反映了它们在向转移发展过程中持续发生的基因组变化。我们开发了一种计算方法来探索这种异质性并预测原发肿瘤的转移进展。我们将我们的方法分别应用于来自癌症基因组图谱 (TCGA) 的约 450 个原发性和转移性皮肤黑色素瘤 (SKCM) 样本的基因表达和 microRNA (miRNA) 表达数据。 RNA-seq 数据的转移进展评分与患者淋巴结的临床分期显着相关，而 miRNA-seq 数据的转移进展评分与 Clark 水平显着相关。原发性 SKCM 肿瘤样本中许多特征性上皮谱系基因表达的丧失与预测的进展评分高度相关。我们认为这些基因/miRNA 可能作为 SKCM 转移进展的假定生物标志物。
Primary and metastatic melanoma tumors share the same cell origin, making it challenging to identify genomic biomarkers that can differentiate them. Primary tumors themselves can be heterogeneous, reflecting ongoing genomic changes as they progress toward metastasizing. We developed a computational method to explore this heterogeneity and to predict metastatic progression of the primary tumors. We applied our method separately to gene expression and to microRNA (miRNA) expression data from ~450 primary and metastatic skin cutaneous melanoma (SKCM) samples from the Cancer Genome Atlas (TCGA). Metastatic progression scores from RNA-seq data were significantly associated with clinical staging of patients’ lymph nodes whereas scores from miRNA-seq data were significantly associated with Clark’s level. The loss of expression of many characteristic epithelial lineage genes in primary SKCM tumor samples was highly correlated with predicted progression scores. We suggest that those genes/miRNAs might serve as putative biomarkers for SKCM metastatic progression.
登录
查看更多内容
影响因子：
3.3
作者：
Kondratiev, Svetlana;Gnepp, Douglas R.;Laver, Nora V.
通讯作者：
Laver, Nora V.
影响因子：
78.5
作者：
Bresnick, Anne R.;Weber, David J.;Zimmer, Danna B.
通讯作者：
Zimmer, Danna B.
影响因子：
14.8
作者：
Huang, Da Wei;Sherman, Brad T.;Lempicki, Richard A.
通讯作者：
Lempicki, Richard A.
影响因子：
50.3
作者：
Damsky WE;Curley DP;Santhanakrishnan M;Rosenbaum LE;Platt JT;Gould Rothberg BE;Taketo MM;Dankort D;Rimm DL;McMahon M;Bosenberg M
通讯作者：
Bosenberg M
影响因子：
64.5
作者：
Lemmon MA;Schlessinger J
通讯作者：
Schlessinger J