A surprising cross-species conservation in the genomic landscape of mouse and human oral cancer identifies a transcriptional signature predicting metastatic disease.
A surprising cross-species conservation in the genomic landscape of mouse and human oral cancer identifies a transcriptional signature predicting metastatic disease.
复制标题
DOI：
10.1158/1078-0432.ccr-14-0205
复制
发表时间：
2014-06-01
期刊：
影响因子：
--
通讯作者：
Uppaluri R
中科院分区：
文献类型：
--
作者：
Onken MD;Winkler AE;Kanchi KL;Chalivendra V;Law JH;Rickert CG;Kallogjeri D;Judd NP;Dunn GP;Piccirillo JF;Lewis JS Jr;Mardis ER;Uppaluri R
提高对口腔鳞状细胞癌（OSCC）侵袭性生长的分子基础的认识具有重要的临床意义。本文中，致癌物诱导的具有惰性或转移性生长的鼠和人OSCC的跨物种基因组比较产生了具有令人惊讶的翻译相关性的结果。对小鼠OSCC细胞系进行下一代测序（NGS），以确定其突变景观，确定新的候选癌症基因，并评估与人类OSCC中已知驱动因素的相似性。表达阵列鉴定了小鼠转移特征，并且我们使用加权投票和基因集富集分析（GSEA）评估了其在包括324名患者的4个独立人类数据集中的代表性。Kaplan-Meier分析和多变量考克斯比例风险模型用于分层结局。开发了一种基于小鼠特征结合机器学习算法的qRT-PCR测定法，并用于对一组独立的31例转移性淋巴结病患者进行分层。NGS揭示了小鼠OSCC中人类驱动途径突变的保守性，包括Trp 53，MAPK，PI 3 K，NOTCH，JAK/STAT和FAT 1 -4。此外，癌症基因组图谱（TCGA）和小鼠样本之间的比较分析确定AKAP 9，MED 12 L和MYH 6为新的推定癌症基因。表达分析确定了预测侵袭性和临床结果的转录特征，其在4个独立的人类OSCC数据集中得到验证。最后，我们通过创建一种临床可行的检测方法来利用该特征的翻译潜力，该检测方法对OSCC患者进行分层，准确率为93.5%。这些数据证明了令人惊讶的跨物种基因组保守性，其与人类口腔鳞状细胞癌具有翻译相关性。
Improved understanding of the molecular basis underlying oral squamous cell carcinoma (OSCC) aggressive growth has significant clinical implications. Herein, cross-species genomic comparison of carcinogen-induced murine and human OSCCs with indolent or metastatic growth yielded results with surprising translational relevance. Murine OSCC cell lines were subjected to next-generation sequencing (NGS) to define their mutational landscape, to define novel candidate cancer genes and to assess for parallels with known drivers in human OSCC. Expression arrays identified a mouse metastasis signature and we assessed its representation in 4 independent human datasets comprising 324 patients using weighted voting and Gene Set Enrichment Analysis (GSEA). Kaplan-Meier analysis and multivariate Cox proportional hazards modeling were used to stratify outcomes. A qRT-PCR assay based on the mouse signature coupled to a machine-learning algorithm was developed and used to stratify an independent set of 31 patients with respect to metastatic lymphadenopathy. NGS revealed conservation of human driver pathway mutations in mouse OSCC including in Trp53, MAPK, PI3K, NOTCH, JAK/STAT and FAT1–4. Moreover, comparative analysis between The Cancer Genome Atlas (TCGA) and mouse samples defined AKAP9, MED12L and MYH6 as novel putative cancer genes. Expression analysis identified a transcriptional signature predicting aggressiveness and clinical outcomes, which were validated in 4 independent human OSCC datasets. Finally, we harnessed the translational potential of this signature by creating a clinically feasible assay that stratified OSCC patients with a 93.5% accuracy. These data demonstrate surprising cross-species genomic conservation that has translational relevance for human oral squamous cell cancer.