利用基因表現及世代研究分析探討statin藥物與攝護腺癌之相關性

近幾年來，服用statin他汀類藥物與癌症潛在威脅是大家共同關心的議題。2015年1月日本研究為了去檢測statin他汀類藥物與癌症關聯性，根據美國不良事件回報系統(FAERS)與日本藥物之大型資料庫(JDMC)等相關資訊進行分析。其研究分析結果說明了下列幾種高強度的statin他汀類藥物包括atorvastatin、 rosuvastatin等statin藥物對於直腸癌、肺癌、胃癌以及攝護腺癌都有提高癌症風險的趨勢。為了鑑別攝護腺癌上服用statin他汀類藥物之相關影響，本研究使用TCGA癌症資料庫內攝護腺癌之基因表現量資料與R軟體分別進行Case control病例對照組分析、DESeq基因差異化表現量分析及使用SAS軟體進行疾病存活分析(Disease Free Survival Analysis)。經各類型分析後得到基因組後利用LINCSCLOUD平台篩選出statin他汀類藥物並計算connectivity score整合性評分。Connectivity score可搭配箱型圖(boxplot)視覺化呈現並鑑定statin他汀類藥物與癌症之風險趨勢。除使用TCGA癌症資料庫外，本研究也加入健保研究資料庫重大傷病明細檔(HV)搭配SAS軟體進行生命量表分析(life table analysis)以及比例涉險模型(Cox proportional hazards model)。結果整合了先前世代研究、TCGA之病例對照組研究、DESeq基因差異表現量分析、TCGA疾病存活分析研究以及NHIRD臺灣健保資料庫之生命量表分析研究進行比較與討論。結果發現在病例對照組研究分析上除了fatostatin呈現高度表現外，其他類型如pravastatin、simvastatin、lovastatin、atorvastatin、rosuvastatin、fluvastatin與pitavastatin等statin他汀類藥物對攝護腺癌表現出相對抑制的表現；TCGA疾病存活分析在各條件考慮下發現除了pravastatin與fatostatin顯示其高表現外，pitavastatin此類他汀類藥物對於攝護腺癌呈現低風險之趨勢；DESeq基因差異表現量分析卻顯示simvastatin、fluvastatin、pitavastatin、mevastatin等表現高度風險之趨勢，相對atorvastatin與rosuvastatin兩個則顯示低度風險；臺灣健保資料庫NHIRD生命量表分析研究顯示服用atorvastatin、rosuvastatin、fluvastatin與pitavastatin此類statins藥物的攝護腺癌患者之存活曲線相對比服用非statins之患者來的高；pravastatin、simvastatin與lovastatin等藥物則對服用非statins患者存活曲線來的低。總結分析結果顯示rosuvastatin與pitavastatin此類statin他汀類藥物對於一般藥物使用或是療程上使用之病患在治療攝護腺癌時為相對有效治療方法。未來目標期望根據特定癌症使用多方分析標誌出癌性相關基因以及搜尋出更多具有抑制癌性趨勢之statin他汀類藥物。

關鍵字

攝護腺癌； statin他汀藥物；癌症資料庫；差異化基因表現量；存活分析

並列摘要

The potential risk of prostate cancer associated with statins use has been a focus of much interest. Japanese research combines both the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and a large organized database from The Japan Medical Data Center (JDMC) data to examine the association between statins and cancer. The FAERS is a computerized information database designed to support the FDA's post-marketing safety surveillance program for all approved drugs and therapeutic biological products. In the FAERS database analysis, significant signals for colorectal cancer、pancreatic cancer and prostate cancer were found for “atorvastatin”、“rosuvastatin” and “pitavastatin”. The hypothesis in our research is certain statin related drugs displays high or low antitumor activity in prostate cancer. If the hypothesis is correct, cells treated with statin related drugs will show similar/reverse gene expressions as cancer cells do after analyzed by bioinformatics approach. This paper focuses on statin related drugs on prostate cancer. To testify whether the results will be concordant with the gene expression profiling and related cohort studies. Data part using prostate cancer RNA-seqV2 gene expression profiling from TCGA by R DESeq package. Tools part uses program Perl and R to analyze overall survival and disease free survival analysis. After survival analysis, LINCSCLOUD web platform get this differential gene expression data then calculate and offer connectivity score. The connectivity score can visualize the risk between statins and cancer by boxplot. In addition to TCGA data, we also using 1997 to 2013 NHIRD HV data to validate gene expression profiling by life table analysis and Cox proportional hazards model. Comparison with analysis of various type, Statin related drugs “atorvastatin” and ”pitavastatin” displays oncogenesis effects both in tumor v.s. normal analysis with TCGA by DESeq tool and NHIRD analysis. It imply that these statins possess potential oncogenesis ability and may lead oncogenesis effect in prostate cancer. In contrast, statins “pravastatin” displays anti-oncogenesis effects both in gene expression profiling and related cohort studies. It probably represent the opposite side of cell growth control, normally acting to inhibit cell proliferation and tumor development potentially.

並列關鍵字

Prostate Cancer ； statin ； TCGA ； Database ； DESeq ； Gene expression ； Disease Free Survival Analysis ； LINCSCLOUD ； Connectivity score ； NHIRD ； SAS ； life table analysis ； Cox proportional hazards model

參考文獻

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利用基因表現及世代研究分析探討statin藥物與攝護腺癌之相關性

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