Newhook Timothy E, Blais Edik M, Lindberg James M, Adair Sara J, Xin Wenjun, Lee Jae K, Papin Jason A, Parsons J Thomas, Bauer Todd W
Department of Surgery, University of Virginia, Charlottesville, Virginia, United States of America.
Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
PLoS One. 2014 Sep 2;9(9):e105631. doi: 10.1371/journal.pone.0105631. eCollection 2014.
Currently, prognostication for pancreatic ductal adenocarcinoma (PDAC) is based upon a coarse clinical staging system. Thus, more accurate prognostic tests are needed for PDAC patients to aid treatment decisions.
Affymetrix gene expression profiling was carried out on 15 human PDAC tumors and from the data we identified a 13-gene expression signature (risk score) that correlated with patient survival. The gene expression risk score was then independently validated using published gene expression data and survival data for an additional 101 patients with pancreatic cancer. Patients with high-risk scores had significantly higher risk of death compared to patients with low-risk scores (HR 2.27, p = 0.002). When the 13-gene score was combined with lymph node status the risk-score further discriminated the length of patient survival time (p<0.001). Patients with a high-risk score had poor survival independent of nodal status; however, nodal status increased predictability for survival in patients with a low-risk gene signature score (low-risk N1 vs. low-risk N0: HR = 2.0, p = 0.002). While AJCC stage correlated with patient survival (p = 0.03), the 13-gene score was superior at predicting survival. Of the 13 genes comprising the predictive model, four have been shown to be important in PDAC, six are unreported in PDAC but important in other cancers, and three are unreported in any cancer.
We identified a 13-gene expression signature that predicts survival of PDAC patients and could prove useful for making treatment decisions. This risk score should be evaluated prospectively in clinical trials for prognostication and for predicting response to chemotherapy. Investigation of new genes identified in our model may lead to novel therapeutic targets.
目前，胰腺导管腺癌（PDAC）的预后评估基于粗略的临床分期系统。因此，需要更准确的预后检测方法来辅助PDAC患者的治疗决策。
对15例人类PDAC肿瘤进行了Affymetrix基因表达谱分析，从数据中我们识别出一个与患者生存率相关的13基因表达特征（风险评分）。然后，使用已发表的另外101例胰腺癌患者的基因表达数据和生存数据对该基因表达风险评分进行独立验证。高风险评分的患者与低风险评分的患者相比，死亡风险显著更高（风险比2.27，p = 0.002）。当将13基因评分与淋巴结状态相结合时，风险评分能进一步区分患者生存时间的长短（p<0.001）。高风险评分的患者无论淋巴结状态如何，生存率都较差；然而，淋巴结状态增加了低风险基因特征评分患者生存的可预测性（低风险N1与低风险N0：风险比 = 2.0，p = 0.002）。虽然美国癌症联合委员会（AJCC）分期与患者生存率相关（p = 0.03），但13基因评分在预测生存方面更具优势。构成预测模型的13个基因中，有4个已被证明在PDAC中很重要，6个在PDAC中未被报道但在其他癌症中很重要，还有3个在任何癌症中都未被报道。
我们识别出一个13基因表达特征，可预测PDAC患者的生存情况，并可能有助于做出治疗决策。该风险评分应在临床试验中进行前瞻性评估，以用于预后评估和预测化疗反应。对我们模型中鉴定出的新基因进行研究可能会带来新的治疗靶点。
