Predictive Models for HCC Prognosis, Recurrence Risk, and Immune Infiltration Based on Two Exosomal Genes: MYL6B and THOC2
Jinyu Zhu,1,2,* Bufu Tang,1,3,* Yang Gao,1,4 Suqin Xu,5 Jianfei Tu,1,4 Yajie Wang,4 Weibin Yang,1,4 Shiji Fang,4 Qiaoyou Weng,4 Zhongwei Zhao,1,4 Min Xu,1,4 Yang Yang,1,4 Minjiang Chen,1,4 Chenying Lu,1,4 Jiansong Ji1,4 1Key Laboratory of Imaging Diagnosis and Minimally Invasive Inte...
Guardado en:
| Autores principales: | , , , , , , , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Dove Medical Press
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/91cfa105c3ab4d929c05e8eaebb9328d |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:91cfa105c3ab4d929c05e8eaebb9328d |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:91cfa105c3ab4d929c05e8eaebb9328d2021-12-02T15:11:23ZPredictive Models for HCC Prognosis, Recurrence Risk, and Immune Infiltration Based on Two Exosomal Genes: MYL6B and THOC21178-7031https://doaj.org/article/91cfa105c3ab4d929c05e8eaebb9328d2021-08-01T00:00:00Zhttps://www.dovepress.com/predictive-models-for-hcc-prognosis-recurrence-risk-and-immune-infiltr-peer-reviewed-fulltext-article-JIRhttps://doaj.org/toc/1178-7031Jinyu Zhu,1,2,* Bufu Tang,1,3,* Yang Gao,1,4 Suqin Xu,5 Jianfei Tu,1,4 Yajie Wang,4 Weibin Yang,1,4 Shiji Fang,4 Qiaoyou Weng,4 Zhongwei Zhao,1,4 Min Xu,1,4 Yang Yang,1,4 Minjiang Chen,1,4 Chenying Lu,1,4 Jiansong Ji1,4 1Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, 323000, People’s Republic of China; 2Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, People’s Republic of China; 3Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, People’s Republic of China; 4Department of Radiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, 323000, People’s Republic of China; 5Clinical Laboratory, Fuyuan Hospital of Yiwu, Jinhua, 321000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jiansong Ji; Chenying Lu Email jijiansong@zju.edu.cn; luchenying@zju.edu.cnIntroduction: Hepatocellular carcinoma (HCC) is a heterogeneous molecular disease with complex molecular pathogenesis that influences the efficacy of therapies. Exosomes play a crucial role in tumorigenesis and poor disease outcomes in HCC.Objective: The aim of this study was to identify the optimal gene set derived from exosomes in HCC with substantial predictive value to construct models for determining prognosis, recurrence risk and diagnosis and to identify candidates suitable for immunotherapy and chemotherapy, thereby providing new ideas for the individualized treatment of patients and for improving prognosis.Methods: Weighted correlation network analysis (WGCNA) and univariate and multivariate Cox PH regression analyses were applied to identify exosome-related signatures in the TCGA and exoRbase databases associated with clinical relevance, immunogenic features and tumor progression in HCC. Cell experiments were performed to further confirm the oncogenic effect of MYL6B and THOC2.Results: The models for prognosis and recurrence risk prediction were built based on two exosomal genes (MYL6B and THOC2) and were confirmed to be independent predictive factors with superior predictive performance. Patients with high prognostic risk had poorer prognosis than patients with low prognostic risk in all HCC datasets, namely, the TCGA cohort (HR=2.5, P< 0.001), the ICGC cohort (HR=3.15, P< 0.001) and the GSE14520 cohort (HR=1.85, P=0.004). A higher recurrence probability was found in HCC patients with high recurrence risk than in HCC patients with low recurrence risk in the TCGA cohort (HR=2.44, P< 0.001) and the GSE14520 cohort (HR=1.54, P=0.025). High prognostic risk patients had higher expression of immune checkpoint genes, such as PD1, B7H3, B7H5, CTLA4 and TIM3 (P< 0.05). Diagnostic models based on the same two genes were able to accurately distinguish HCC patients from normal individuals and HCC from dysplastic nodules.Conclusion: Our findings lay the foundation for identifying molecular markers to increase the early detection rate of HCC, improve disease outcomes, and determine more effective individualized treatment options for patients.Keywords: exosome, hepatocellular carcinoma, HCC, immune checkpoint, prognosisZhu JTang BGao YXu STu JWang YYang WFang SWeng QZhao ZXu MYang YChen MLu CJi JDove Medical Pressarticleexosomehepatocellular carcinoma (hcc)immune checkpointprognosisPathologyRB1-214Therapeutics. PharmacologyRM1-950ENJournal of Inflammation Research, Vol Volume 14, Pp 4089-4109 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
exosome hepatocellular carcinoma (hcc) immune checkpoint prognosis Pathology RB1-214 Therapeutics. Pharmacology RM1-950 |
| spellingShingle |
exosome hepatocellular carcinoma (hcc) immune checkpoint prognosis Pathology RB1-214 Therapeutics. Pharmacology RM1-950 Zhu J Tang B Gao Y Xu S Tu J Wang Y Yang W Fang S Weng Q Zhao Z Xu M Yang Y Chen M Lu C Ji J Predictive Models for HCC Prognosis, Recurrence Risk, and Immune Infiltration Based on Two Exosomal Genes: MYL6B and THOC2 |
| description |
Jinyu Zhu,1,2,* Bufu Tang,1,3,* Yang Gao,1,4 Suqin Xu,5 Jianfei Tu,1,4 Yajie Wang,4 Weibin Yang,1,4 Shiji Fang,4 Qiaoyou Weng,4 Zhongwei Zhao,1,4 Min Xu,1,4 Yang Yang,1,4 Minjiang Chen,1,4 Chenying Lu,1,4 Jiansong Ji1,4 1Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui, 323000, People’s Republic of China; 2Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, People’s Republic of China; 3Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, People’s Republic of China; 4Department of Radiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, 323000, People’s Republic of China; 5Clinical Laboratory, Fuyuan Hospital of Yiwu, Jinhua, 321000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jiansong Ji; Chenying Lu Email jijiansong@zju.edu.cn; luchenying@zju.edu.cnIntroduction: Hepatocellular carcinoma (HCC) is a heterogeneous molecular disease with complex molecular pathogenesis that influences the efficacy of therapies. Exosomes play a crucial role in tumorigenesis and poor disease outcomes in HCC.Objective: The aim of this study was to identify the optimal gene set derived from exosomes in HCC with substantial predictive value to construct models for determining prognosis, recurrence risk and diagnosis and to identify candidates suitable for immunotherapy and chemotherapy, thereby providing new ideas for the individualized treatment of patients and for improving prognosis.Methods: Weighted correlation network analysis (WGCNA) and univariate and multivariate Cox PH regression analyses were applied to identify exosome-related signatures in the TCGA and exoRbase databases associated with clinical relevance, immunogenic features and tumor progression in HCC. Cell experiments were performed to further confirm the oncogenic effect of MYL6B and THOC2.Results: The models for prognosis and recurrence risk prediction were built based on two exosomal genes (MYL6B and THOC2) and were confirmed to be independent predictive factors with superior predictive performance. Patients with high prognostic risk had poorer prognosis than patients with low prognostic risk in all HCC datasets, namely, the TCGA cohort (HR=2.5, P< 0.001), the ICGC cohort (HR=3.15, P< 0.001) and the GSE14520 cohort (HR=1.85, P=0.004). A higher recurrence probability was found in HCC patients with high recurrence risk than in HCC patients with low recurrence risk in the TCGA cohort (HR=2.44, P< 0.001) and the GSE14520 cohort (HR=1.54, P=0.025). High prognostic risk patients had higher expression of immune checkpoint genes, such as PD1, B7H3, B7H5, CTLA4 and TIM3 (P< 0.05). Diagnostic models based on the same two genes were able to accurately distinguish HCC patients from normal individuals and HCC from dysplastic nodules.Conclusion: Our findings lay the foundation for identifying molecular markers to increase the early detection rate of HCC, improve disease outcomes, and determine more effective individualized treatment options for patients.Keywords: exosome, hepatocellular carcinoma, HCC, immune checkpoint, prognosis |
| format |
article |
| author |
Zhu J Tang B Gao Y Xu S Tu J Wang Y Yang W Fang S Weng Q Zhao Z Xu M Yang Y Chen M Lu C Ji J |
| author_facet |
Zhu J Tang B Gao Y Xu S Tu J Wang Y Yang W Fang S Weng Q Zhao Z Xu M Yang Y Chen M Lu C Ji J |
| author_sort |
Zhu J |
| title |
Predictive Models for HCC Prognosis, Recurrence Risk, and Immune Infiltration Based on Two Exosomal Genes: MYL6B and THOC2 |
| title_short |
Predictive Models for HCC Prognosis, Recurrence Risk, and Immune Infiltration Based on Two Exosomal Genes: MYL6B and THOC2 |
| title_full |
Predictive Models for HCC Prognosis, Recurrence Risk, and Immune Infiltration Based on Two Exosomal Genes: MYL6B and THOC2 |
| title_fullStr |
Predictive Models for HCC Prognosis, Recurrence Risk, and Immune Infiltration Based on Two Exosomal Genes: MYL6B and THOC2 |
| title_full_unstemmed |
Predictive Models for HCC Prognosis, Recurrence Risk, and Immune Infiltration Based on Two Exosomal Genes: MYL6B and THOC2 |
| title_sort |
predictive models for hcc prognosis, recurrence risk, and immune infiltration based on two exosomal genes: myl6b and thoc2 |
| publisher |
Dove Medical Press |
| publishDate |
2021 |
| url |
https://doaj.org/article/91cfa105c3ab4d929c05e8eaebb9328d |
| work_keys_str_mv |
AT zhuj predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT tangb predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT gaoy predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT xus predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT tuj predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT wangy predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT yangw predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT fangs predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT wengq predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT zhaoz predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT xum predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT yangy predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT chenm predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT luc predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 AT jij predictivemodelsforhccprognosisrecurrenceriskandimmuneinfiltrationbasedontwoexosomalgenesmyl6bandthoc2 |
| _version_ |
1718387644933603328 |