子宮內膜癌是常見的婦女惡性腫瘤，近年來發生率持續攀升。許多的研究者已針對子宮內膜癌化過程進行研究，發現了不同表型的基因印記。然而，目前尚未有利用基因網路分析(gene network analysis)的方式，進行子宮內膜惡性腫瘤的表型分類和癌化機制之探究。因此本研究匯整不同平台子宮內膜癌之基因晶片，將其整合為一個大尺度的基因資料庫，利用weighted gene co-expression network (WGCNA)及elastic-net regression model的整合性模式，重新建構子宮內膜癌之基因網路，並找出影響子宮內膜癌癌化過程的基因印記。根據本研究所匯整的基因表現資料，可以建構為一個由620個基因組成的基因網路，從中可以找出19個影響子宮內膜癌之惡性程度(stage)、表型(type)及分化(grade)癌化過程中cell-cycle regulation、antigen processing和citric acid cycle相關的基因印記。由這些基因印記所建構而成的預測模型，可以成功地對不同表型之子宮內膜癌進行分類。
另外，本研究也應用了基因網路的分析方法，針對雙酚A (bisphenol A; BPA)的毒性測試進行研究。BPA是一種雌激素干擾物質，常用於塑膠物質及牙齒的塑化劑。本研究以基因網路的分析方法，將BPA改變子宮內膜細胞之基因表現的分子機制，具像化的呈現。
本研究提供了一個鑑定子宮內膜基因印記的平台，能夠更了解子宮內膜癌化的過程，並可以有效的發現潛在治療藥物的標靶。另外在BPA毒性分析中，也可以針對環境暴露評估及人體健康效應，提供更有力的依據。

Endometrial cancers (ECs) are the most common gynecologic malignancy. Many studies have investigated the tumorigenesis process and identified the biomarkers for signature classification. However, to the best of knowledge, there is no satisfactory gene network-based method on the investigation of tumorigenesis characterization and diagnosis of subtype of ECs. An integrative analysis of weighted gene co-expression network (WGCNA) and elastic-net regression model was used to reconstruct an ECs-specific gene co-expression network and to discover the cancer gene signatures driving tumorigenesis of ECs. This study reconstructed a co-expression network consisted of 620 genes, and discovered 19-gene diagnostic biomarker signatures for grade, type and stage in the EC-specific network contributing to the ECs progression via cell-cycle regulation, antigen processing and the citric acid (TCA) cycle. The predictive model achieved the good classifier performance for phenotypic characteristics of ECs.
On the other hand, this study also applied the network-based analysis to a case study of bisphenol A (BPA) toxicity testing. BPA can play as an endocrine disrupting chemical and is usually used as sealants in plastic materials. The primary route of human exposure to BPA is food intake. This study presented the toxicity evaluation of BPA exposure in the visualized perturbations of molecular and cellular changes.
This study provided a powerful biomarker discovery platform to better understand the progression of ECs to uncover potential therapeutic targets in the treatment of ECs, and the toxicity of environmental BPA exposure for health effect estimation and prevention.

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