Research Papers:

Integrating the dysregulated inflammasome-based molecular functionome in the malignant transformation of endometriosis-associated ovarian carcinoma

Chia-Ming Chang, Mong-Lien Wang, Kai-Hsi Lu, Yi-Ping Yang, Chi-Mou Juang, Peng-Hui Wang, Ren-Jun Hsu, Mu-Hsien Yu and Cheng-Chang Chang _

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Oncotarget. 2018; 9:3704-3726. https://doi.org/10.18632/oncotarget.23364

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Chia-Ming Chang1,2, Mong-Lien Wang1,3, Kai-Hsi Lu4, Yi-Ping Yang3, Chi-Mou Juang1,2, Peng-Hui Wang1,2,5, Ren-Jun Hsu6,7, Mu-Hsien Yu8 and Cheng-Chang Chang8

1School of Medicine, National Yang-Ming University, Taipei, Taiwan

2Department of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan

3Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan

4Department of Medical Research and Education, Cheng-Hsin Hospital, Taipei, Taiwan

5Department of Medical Research, China Medical University Hospital, Taichung, Taiwan

6Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan

7Biobank Management Center of Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan

8Department of Obstetrics and Gynecology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan

Correspondence to:

Cheng-Chang Chang, email: [email protected]

Keywords: endometriosis; ovarian carcinoma; inflammasome; gene-set integrative analysis; gene expression microarray

Received: September 07, 2017    Accepted: October 29, 2017    Published: December 18, 2017


The coexistence of endometriosis (ES) with ovarian clear cell carcinoma (CCC) or endometrioid carcinoma (EC) suggested that malignant transformation of ES leads to endometriosis associated ovarian carcinoma (EAOC). However, there is still lack of an integrating data analysis of the accumulated experimental data to provide the evidence supporting the hypothesis of EAOC transformation. Herein we used a function-based analytic model with the publicly available microarray datasets to investigate the expression profiling between ES, CCC, and EC. We analyzed the functional regularity pattern of the three type of samples and hierarchically clustered the gene sets to identify key mechanisms regulating the malignant transformation of EAOC. We identified a list of 18 genes (NLRP3, AIM2, PYCARD, NAIP, Caspase-4, Caspase-7, Caspase-8, TLR1, TLR7, TOLLIP, NFKBIA, TNF, TNFAIP3, INFGR2, P2RX7, IL-1B, IL1RL1, IL-18) closely related to inflammasome complex, indicating an important role of inflammation/immunity in EAOC transformation. We next explore the association between these target genes and patient survival using Gene Expression Omnibus (GEO), and found significant correlation between the expression levels of the target genes and the progression-free survival. Interestingly, high expression levels of AIM2 and NLRP3, initiating proteins of inflammasomes, were significantly correlated with poor progression-free survival. Immunohistochemistry staining confirmed a correlation between high AIM2 and high Ki-67 in clinical EAOC samples, supporting its role in disease progression. Collectively, we established a bioinformatic platform of gene-set integrative molecular functionome to dissect the pathogenic pathways of EAOC, and demonstrated a key role of dysregulated inflammasome in modulating the malignant transformation of EAOC.

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