Association of ABC gene profiles with time to progression and resistance in ovarian cancer revealed by bioinformatics analyses

Level of mRNA was measured by quantitative RT‐PCR in tumor tissues from ovarian cancer patients. This study stressed the connection between two well‐documented ABC genes and clinicopathological features (time to progression, chemotherapy resistance)—ABCB1 and ABCG2. Moreover, we showed a comparable connection also for several other ABC genes—ABCB11, ABCC4, ABCC10, ABCD3, ABCE1, ABCF1, ABCF2, and ABCF3.

Abstract

Introduction

Ovarian cancer (OC) represents a serious disease with high mortality and lack of efficient predictive and prognostic biomarkers. ATP‐binding cassette (ABC) proteins constitute a large family dedicated to active transmembrane transport including transport of xenobiotics.

Materials and methods

mRNA level was measured by quantitative RT‐PCR in tumor tissues from OC patients. Bioinformatics analyses were applied to two gene expression datasets (60 primary tumors and 29 peritoneal metastases). Two different approaches of expression data normalization were applied in parallel, and their results were compared. Data from publically available cancer datasets were checked to further validate our conclusions.

Results

The results showed significant connections between ABC gene expression profiles and time to progression (TTP), chemotherapy resistance, and metastatic progression in OC. Two consensus ABC gene profiles with clinical meaning were documented. (a) Downregulation of ABCC4, ABCC10, ABCD3, ABCE1, ABCF1, ABCF2, and ABCF3 was connected with the best sensitivity to chemotherapy and TTP. (b) Oppositely, downregulation of ABCB11 and upregulation of ABCB1 and ABCG2 were connected with the worst sensitivity to chemotherapy and TTP. Results from publicly available online databases supported our conclusions.

Conclusion

This study stressed the connection between two well‐documented ABC genes and clinicopathological features—ABCB1 and ABCG2. Moreover, we showed a comparable connection also for several other ABC genes—ABCB11, ABCC4, ABCC10, ABCD3, ABCE1, ABCF1, ABCF2, and ABCF3. Our results add new clinically relevant information to this oncology field and can stimulate further exploration.

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