Oladimeji Aladelokun, Lingeng Lu, Jie Zheng, Hong Yan, Abhishek Jain, Joanna Gibson, Sajid A Khan, Caroline H Johnson
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引用次数: 0
Abstract
Background: Sex-related differences in colorectal (CRC) incidence and mortality are well-documented. However, the impact of sex on metabolic pathways that drive cancer growth is not well understood. High expression of asparagine synthetase (ASNS) is associated with inferior survival for female CRC patients only. Here, we used a CRISPR/Cas9 technology to generate HCT116 ASNS-/- and HCT 116 ASNS+/+ cancer cell lines. We examine the effects of ASNS deletion on tumor growth and the subsequent rewiring of metabolic pathways in male and female Rag2/IL2RG mice.
Results: ASNS loss reduces cancer burden in male and female tumor-bearing mice (40% reduction, q < 0.05), triggers metabolic reprogramming including gluconeogenesis, but confers a survival improvement (30 days median survival, q < 0.05) in female tumor-bearing mice alone. Transcriptomic analyses revealed upregulation of G-protein coupled estrogen receptor (GPER1) in tumors from male and female mice with HCT116 ASNS-/- xenograft. Estradiol activates GPER1 in vitro in the presence of ASNS and suppresses tumor growth.
Conclusions: Our study indicates that inferior survival for female CRC patients with high ASNS may be due to metabolic reprogramming that sustains tumor growth. These findings have translational relevance as ASNS/GPER1 signaling could be a future therapeutic target to improve the survival of female CRC patients.
期刊介绍:
Human Genomics is a peer-reviewed, open access, online journal that focuses on the application of genomic analysis in all aspects of human health and disease, as well as genomic analysis of drug efficacy and safety, and comparative genomics.
Topics covered by the journal include, but are not limited to: pharmacogenomics, genome-wide association studies, genome-wide sequencing, exome sequencing, next-generation deep-sequencing, functional genomics, epigenomics, translational genomics, expression profiling, proteomics, bioinformatics, animal models, statistical genetics, genetic epidemiology, human population genetics and comparative genomics.