Identification of TP53-based Drug Candidates in Human Breast Cancer

Breast cancer (BC) is the most prevalent malignancy and the leading cause of cancer-related mortality in female. TP53 is the gene that is most frequently altered in caners including BC. However, the role of TP53 mutation as a prediction factor in clinical outcome of BC patients remains inclusive and the application of TP53 in companion diagnosis has yet to be determined. In this study, we aimed to verify the role of TP53 alteration in prognosis and screen of drug candidates. DriverDB was exploited to sorts the highly mutated genes and the display the corresponding tumor mutation burden (TMB) and impact of mutations of The Cancer Genome Atlas (TCGA)-sourced BC samples. R programming language was used to analyze the mutation landscape of TP53 protein change. Gene chip data was accessed from TNMplot web server to compare the TP53 gene expression between tumor and normal tissue. The immunohistochemistry (IHC) staining of p53 was retrieved from the Human Protein Atlas portal. Genomics of Drug Sensitivity in Cancer (GDSC) repository data analyzed on Q-omics 1.0 Bluebird was employed to screen the relationship between drug response and TP53 expression. BC cases showed topmost mutation rate in TP53 (41%), which is in synchronicity with tumor mutation burden (TMB) and involved in high/moderate impact on gene alteration. Increased TP53 copy number variation (CNV) correlated positively with the TP53 gene expression levels. High expression of TP53 was noted in malignant BC tumors and had an association with unfavorable overall survival. Importantly, docetaxel and fulvestrant were identified as effective drugs to BC cells harboring increased TP53 levels. Overall, gain of TP53 CNV accounts for the increased expression levels of TP53 in BC tumor. TP53 overexpression examined by sequencing and IHC is a hallmark for malignant tumor and indicates worse overall survival. Upregulated TP53 in BC cells represents an indicator of high sensitivity to docetaxel and fulvestrant.

關鍵字

Breast cancer ； TP53 ； Drug screening

並列摘要

乳癌是最常見的惡性腫瘤，也是女性癌症相關死亡的主要原因。TP53是在包括乳癌在內的癌症中最常突變的基因。然而，TP53突變作為預測因素在乳癌患者臨床結果中的作用仍不清楚，此外，TP53在伴隨診斷中的應用尚未確定。在本研究中，我們旨在驗證TP53改變在預後和候選藥物篩選中的作用。DriverDB被用來對高度突變的基因進行分類，並顯示相應的腫瘤突變負荷（和來自癌症基因組圖譜（TCGA）的乳癌樣本突變的影響。使用R編程語言分析TP53蛋白變化的突變景觀。TNMplot入口伺服器取得基因晶片數據，以比較腫瘤和正常組織之間的TP53基因表達。p5的免疫組織化學染色取自人類蛋白質圖譜門戶網站。在Q-omics 1.0 Bluebird上分析的GDSC存儲庫數據用於篩選藥物反應和TP53表達之間的關係。結果顯示乳癌病例的TP53突變率最高（41%），與腫瘤突變負荷同步，且對基因改變有高／中度影響。TP53拷貝數變異增加與基因表達水平正相關。TP53的高表達是惡性乳癌腫瘤之特徵，並與不利的總生存期有關。重要的是，多西他賽和氟維司群被確定為對TP53水平升高的乳癌細胞有效的藥物。TP53拷貝數增加是TP53在乳癌腫瘤中表達水平升高的原因。通過測序和免疫組織化學染色檢查的TP53過表達是惡性腫瘤的標誌，並且表明總體存活率較差。乳癌細胞中上調的TP53代表對多西紫杉醇和氟維司群高度敏感性的指標。

並列關鍵字

乳癌； TP53 ；藥物篩選

主題瀏覽