Molecular cancer, 2020-05, Vol.19 (1), p.92-18, Article 92
2020
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- Autor(en) / Beteiligte
- Titel
- Circular RNA circMET drives immunosuppression and anti-PD1 therapy resistance in hepatocellular carcinoma via the miR-30-5p/snail/DPP4 axis
- Ist Teil von
- Molecular cancer, 2020-05, Vol.19 (1), p.92-18, Article 92
- Ort / Verlag
- England: BioMed Central Ltd
- Erscheinungsjahr
- 2020
- Quelle
- Electronic Journals Library
- Beschreibungen/Notizen
- Amplification of chromosome 7q21-7q31 is associated with tumor recurrence and multidrug resistance, and several genes in this region are powerful drivers of hepatocellular carcinoma (HCC). We aimed to investigate the key circular RNAs (circRNAs) in this region that regulate the initiation and development of HCC. We used qRT-PCR to assess the expression of 43 putative circRNAs in this chromosomal region in human HCC and matched nontumor tissues. In addition, we used cultured HCC cells to modify circRNA expression and assessed the effects in several cell-based assays as well as gene expression analyses via RNA-seq. Modified cells were implanted into immunocompetent mice to assess the effects on tumor development. We performed additional experiments to determine the mechanism of action of these effects. circMET (hsa_circ_0082002) was overexpressed in HCC tumors, and circMET expression was associated with survival and recurrence in HCC patients. By modifying the expression of circMET in HCC cells in vitro, we found that circMET overexpression promoted HCC development by inducing an epithelial to mesenchymal transition and enhancing the immunosuppressive tumor microenvironment. Mechanistically, circMET induced this microenvironment through the miR-30-5p/Snail/ dipeptidyl peptidase 4(DPP4)/CXCL10 axis. In addition, the combination of the DPP4 inhibitor sitagliptin and anti-PD1 antibody improved antitumor immunity in immunocompetent mice. Clinically, HCC tissues from diabetic patients receiving sitagliptin showed higher CD8 T cell infiltration than those from HCC patients with diabetes without sitagliptin treatment. circMET is an onco-circRNA that induces HCC development and immune tolerance via the Snail/DPP4/CXCL10 axis. Furthermore, sitagliptin may enhance the efficacy of anti-PD1 therapy in a subgroup of patients with HCC.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 1476-4598eISSN: 1476-4598DOI: 10.1186/s12943-020-01213-6Titel-ID: cdi_doaj_primary_oai_doaj_org_article_c04084b82de94621b6820d97eb69f9a9
- Format
- –
- Schlagworte
- Analysis, Animals, Antibodies, Antineoplastic agents, Apoptosis, Biomarkers, Tumor - genetics, Biomarkers, Tumor - metabolism, Cancer treatment, Carcinoma, Hepatocellular - drug therapy, Carcinoma, Hepatocellular - genetics, Carcinoma, Hepatocellular - immunology, Carcinoma, Hepatocellular - pathology, CD8 antigen, Cell adhesion & migration, Cell Movement, Cell Proliferation, Chromosome 7, circMET, circRNA, Circular RNA, CXCL10 protein, Deoxyribonucleic acid, Development and progression, Diabetes mellitus, Diabetics, Dipeptidyl Peptidase 4 - genetics, Dipeptidyl Peptidase 4 - metabolism, Dipeptidyl-peptidase IV, DNA, DPP4, Drug Resistance, Neoplasm, Female, Gene expression, Gene Expression Regulation, Neoplastic, Genes, Hepatocellular carcinogenesis, Hepatocellular carcinoma, Humans, Immune Checkpoint Inhibitors - pharmacology, Immune system, Immunological tolerance, Immunosuppression, Immunotherapy, Kinases, Liver cancer, Liver Neoplasms - drug therapy, Liver Neoplasms - genetics, Liver Neoplasms - immunology, Liver Neoplasms - pathology, Lymphocytes, Lymphocytes T, Male, Medical prognosis, Mesenchyme, Metastases, Mice, Mice, Inbred C57BL, Microbial drug resistance, MicroRNAs, MicroRNAs - genetics, Middle Aged, miR-30-5p, Multidrug resistance, Neoplasm Invasiveness, Patients, PD-1 protein, Peptidase, Polymerase chain reaction, Prognosis, Programmed Cell Death 1 Receptor - antagonists & inhibitors, Proto-Oncogene Proteins c-met - genetics, Ribonucleic acid, RNA, RNA, Circular - genetics, Sitagliptin, Snail Family Transcription Factors - genetics, Snail Family Transcription Factors - metabolism, Software, Survival Rate, T cells, Tumor Cells, Cultured, Tumors, Xenograft Model Antitumor Assays