Abstract A59: RNA-seq analysis of high-grade serous ovarian cancer patients before and after chemotherapy reveals chemoresistance-associated genes and pathways
Authors: Jamalzadeh Sanaz , Zhang Kaiyang , Häkkinen Antti , Huhtinen Kaisa , Hynninen Johanna , Andersson Noora , Mansuri Naziha , Carpén Olli , Erdogan Erkan , Dai Jun , Vähärautio Anna , Hietanen Sakari , Oikkonen Jaana , Lehtonen Rainer , Hautaniemi Sampsa 
Published: September 2020

Abstract
Introduction: To identify genes and pathways that drive platinum-taxane resistance in high-grade serous ovarian cancer (HGSOC), we analyzed 108 samples subjected to RNA-seq before and after chemotherapy.
Experimental Procedure: We collected prospectively 108 tissue samples from various anatomic locations (omentum, ovary, mesothelium, peritoneum) for 53 HGSOC patients with high enough tumor purity (&gt;25%) and follow-up information to calculate platinum free interval (PFI). These samples were subjected to RNA-seq to obtain gene expression data for known protein coding genes. Additionally, data from 16,826 samples (cells) with single-cell RNA-seq were used in the decomposition analysis to overcome cell heterogeneity in the samples. For validation we used 306 The Cancer Genome Atlas (TCGA) HGSOC samples that were analyzed with the decompose algorithm. Differential expressions for selected resistance associated genes were validated with immunohistochemistry (IHC).
Results: We examined firstly whether gene expressions values are systematically influenced by anatomic location of the samples and chemotherapy. Our results show that bias due to anatomic locations can be controlled by relatively simple computational adjusting. However, chemotherapy-treated samples have significantly lower tumor purity than treatment-naive samples and samples have varying cell compositions. We developed a computational decomposition method to correct these biases. Secondly, we compared gene expression values of cancer cells between 1) well and poor responding patients, and 2) before and after chemotherapy followed by pathway analysis. We identified several genes that were significantly upregulated in the poor-responder group, such as FOXK1 and FBXO32, which also had significant survival association in the TCGA cohort. Our results highlight genes whose expression values are significantly enriched after chemotherapy, such as BTG2, CITED2, CTGF, FOS, DUSP1, and EGR1, which have been shown to promote resistance to platinum or paclitaxel in HGSOC or other cancers. In addition to these known chemoresistant-associated genes, we identified several hitherto unknown genes and validated them with IHC. Pathway analysis revealed actionable targets in the B-cell receptor and MAPK signaling pathways, which were the most significant enriched signaling pathways after chemotherapy.
Conclusions: We have shown that successful comparison of gene expression values before and after chemotherapy requires heavy computational correction of the strong and systematic bias caused by chemotherapy and tumor heterogeneity. To overcome these biases, we have developed a novel decomposition algorithm. This method allows to obtain reliable data for the subsequent analyses. The gene expression analyses herein identified several genes and pathways that play central roles in chemoresistance and are rational targets for overcoming platinum-taxane resistance in HGSOC.
Citation Format: Sanaz Jamalzadeh, Kaiyang Zhang, Antti Häkkinen, Kaisa Huhtinen, Johanna Hynninen, Noora Andersson, Naziha Mansuri, Olli Carpén, Erkan Erdogan, Jun Dai, Anna Vähärautio, Sakari Hietanen, Jaana Oikkonen, Rainer Lehtonen, Sampsa Hautaniemi. RNA-seq analysis of high-grade serous ovarian cancer patients before and after chemotherapy reveals chemoresistance-associated genes and pathways [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A59.