Abstract 1787
Background
Jumonji domain-containing protein 2A (JMJD2A), belonging to the JMJD2 family of histone lysine demethylases, has been implicated in tumorigenesis. However, its expression profile and role in drug resistance of gastric cancer remains unknown. Previous studies show that docetaxel, cisplatin, and S-1 (DCS) therapy has a high response rate in patients with metastatic gastric cancer, but acquired drug resistance is often observed. In this study, we investigated the role of JMJD2A in drug susceptibility of DCS therapy in patients with gastric cancer, and its clinical relevance in gastric cancer.
Methods
siRNA-mediated downregulation of 14 relevant genes from previously identified gene signatures was performed to identify functional factor to modulate drug susceptibility in DCS therapy. In 34 clinical tissues with metastatic gastric cancer, we examined whether JMJD2A expression predicted tumor regression rate in patients. Furthermore, the downstream effects of JMJD2A on drug susceptibility were analyzed by whole-gene expression array and immunoprecipitation.
Results
After specific silencing of 14 candidate genes, inhibition of JMJD2A induced significant drug resistance in three anti-cancer drugs; IC50values for 5-FU, cisplatin, and docetaxel were 15.3-, 2.7-, and 4.0-fold increased, respectively. Overexpressed JMJD2A was universally expressed in 12 gastric cancer cell lines, positively correlated with tumor regression rate in DCS therapy. JMJD2A is physically associated with histone lysine demethylation. By analysis of downstream effect of JMJD2A, cooperation of Coiled-coil domain containing 8 (CCDC8) was identified, using whole-gene expression analysis. Direct interaction of CCDC8 and JMJD2A was verified by immunoprecipitation. Of note, inhibition of CCDC8 also induced significant drug resistance in docetaxel, cisplatin, and S-1.
Conclusions
JMJD2A sensitizes gastric cancer to combination chemotherapy of S-1, cisplatin, and docetaxel by cooperating CCDC8, and JMJD2A/CCDC8 would be a potential biomarker and therapeutic target.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
JSPS KAKENHI.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
3523 - Results of a global external quality assessment scheme for EGFR testing on liquid biopsy
Presenter: Nicola Normanno
Session: Poster Display session 3
Resources:
Abstract
3295 - Clinical impact of plasma Next-Generation Sequencing (NGS) in advanced Non-small cell lung cancer (aNSCLC)
Presenter: Laura Bonanno
Session: Poster Display session 3
Resources:
Abstract
5632 - Feasibility study of a ctEGFR prototype assay on the fully automated Idylla™ platform
Presenter: Martin Reijans
Session: Poster Display session 3
Resources:
Abstract
3614 - Enhanced Access to EGFR Molecular Testing in NSCLC using a Cell-Free DNA Tube for Liquid Biopsy
Presenter: Theresa May
Session: Poster Display session 3
Resources:
Abstract
5664 - Analysis of circulating tumor DNA in paired plasma and sputum samples of EGFR-mutated NSCLC patients
Presenter: Christina Grech
Session: Poster Display session 3
Resources:
Abstract
4945 - Liquid biopsy and Array Comparative Genomic Hybridization (aCGH)
Presenter: Panagiotis Apostolou
Session: Poster Display session 3
Resources:
Abstract
5746 - Next-generation sequencing panel verification to detect low frequency single nucleotide and copy number variants from mixing cell line studies
Presenter: Rocio Rosas-Alonso
Session: Poster Display session 3
Resources:
Abstract
5901 - Automated rarefaction analysis for precision B and T cell receptor repertoire profiling from peripheral blood and FFPE-preserved tumor
Presenter: Luca Quagliata
Session: Poster Display session 3
Resources:
Abstract
2027 - A Heptamethine cyanine dye is a potential diagnostic marker for Myeloid-Derived Suppressor Cells
Presenter: Chaeyong Jung
Session: Poster Display session 3
Resources:
Abstract
5517 - Molecular fingerprinting in breast cancer (BC) screening using Quantum Optics (QO) technology combined with an artificial intelligence (AI) approach applying the concept of “molecular profiles at n variables (MPnV)”: a prospective pilot study.
Presenter: Jean-Marc Nabholtz
Session: Poster Display session 3
Resources:
Abstract