Breast Cancer Res:開發出針對乳腺癌特殊調節程序的新型預測技術

2015年1月9日 訊 /生物谷BIOON/ --近日，來自達特茅斯Norris癌症研究中心的研究者Chao Cheng表示，通過在乳腺癌中觀察調節子下遊基因的表達水平，我們就可以鑑別出E2F4的基因特性，其可以幫助預測雌激素受體陽性的乳腺癌，相關研究成果刊登於國際雜誌Breast Cancer Research上，該研究或為開發治療女性乳腺癌的個體化療法提供希望。

研究數據或可幫助設計針對雌激素陽性的乳腺癌患者E2F4活性的有效預測性的基因組標記，同時也可幫助開發簡單的臨床檢測技術來幫助醫生們選擇個體化的療法來治療不同的乳腺癌患者。研究者表示，未來我們的技術或許具有高度的靈活性，由於E2F4在多種癌症中廣泛存在，因此其可以幫助研究者來解決許多生物醫學難題。

為了設計準確快速的基因組測試技術來測定和E2F4相關的調節子的活性水平，研究小組通過觀察轉錄因子的異常行為，以此來追蹤並且預測癌症發生的根源，同時揭示為何異常的基因表達會引發細胞增殖的失控，促進腫瘤發生，乃至癌症發生轉移。

文章中，研究者利用染色質免疫共沉澱測序技術對靶向基因進行測序，並且對比了癌症組織中E2F4的調節活性分值，從而確定調節活性和病人生存之間的關係；而E2F4的預後特性或許可以有效預測乳腺癌患者的預後結果。Cheng解釋道，通過開發一種靈活可複製的預測技術，我們就可以在很多癌症領域為醫生們提供幫助，來指導其針對不同病情的病人開展不同的療法治療。（生物谷Bioon.com）

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E2F4 regulatory program predicts patient survival prognosis in breast cancer

Sari S Khaleel1, Erik H Andrews1, Matthew Ung1, James DiRenzo2 and Chao Cheng134*

Introduction Genetic and molecular signatures have been incorporated into cancer prognosis prediction and treatment decisions with good success over the past decade. Clinically, these signatures are usually used in early-stage cancers to evaluate whether they require adjuvant therapy following surgical resection. A molecular signature that is prognostic across more clinical contexts would be a useful addition to current signatures. Methods We defined a signature for the ubiquitous tissue factor, E2F4, based on its shared target genes in multiple tissues. These target genes were identified by chromatin immunoprecipitation sequencing (ChIP-seq) experiments using a probabilistic method. We then computationally calculated the regulatory activity score (RAS) of E2F4 in cancer tissues, and examined how E2F4 RAS correlates with patient survival. Results Genes in our E2F4 signature were 21-fold more likely to be correlated with breast cancer patient survival time compared to randomly selected genes. Using eight independent breast cancer datasets containing over 1,900 unique samples, we stratified patients into low and high E2F4 RAS groups. E2F4 activity stratification was highly predictive of patient outcome, and our results remained robust even when controlling for many factors including patient age, tumor size, grade, estrogen receptor (ER) status, lymph node (LN) status, whether the patient received adjuvant therapy, and the patient’s other prognostic indices such as Adjuvant! and the Nottingham Prognostic Index scores. Furthermore, the fractions of samples with positive E2F4 RAS vary in different intrinsic breast cancer subtypes, consistent with the different survival profiles of these subtypes. Conclusions We defined a prognostic signature, the E2F4 regulatory activity score, and showed it to be significantly predictive of patient outcome in breast cancer regardless of treatment status and the states of many other clinicopathological variables. It can be used in conjunction with other breast cancer classification methods such as Oncotype DX to improve clinical outcome prediction.