1
|
Zhang L, Liu J, Wang H, Xu Z, Wang Y, Chen Y, Peng H. Low UPB1 Level Correlates With Poor Prognosis in Lung Adenocarcinoma. Appl Immunohistochem Mol Morphol 2024; 32:44-52. [PMID: 37859333 DOI: 10.1097/pai.0000000000001159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 08/11/2023] [Indexed: 10/21/2023]
Abstract
OBJECTIVES Lung adenocarcinoma (LUAD) is a critical cancer with high mortality, worse prognosis, and crucial lymphatic metastasis. Consequently, prognostic biomarkers for LUAD are truly required. β-Ureidopropionase (UPB1) is abnormally expressed in various cancers. However, the function of UPB1 in LUAD is still ambiguous. This study aimed to explore the expression profile and prognostic significance of UPB1 in LUAD. MATERIALS AND METHODS The differential UPB1 levels in pan cancers and their prognostic significance were comprehensively investigated through Gene Expression Profiling Interactive Analysis, UALCAN, Tumor Immune Estimation Resource, and Kaplan-Meier plotter platform. The correlation between UPB1 and tumor infiltration immune cells was explored using Tumor Immune Estimation Resource, Gene Expression Profiling Interactive Analysis, and Tumor-Immune System Interactions and Drug Bank database databases. RESULTS The UPB1 level was abnormally expressed in pan-tumor tissue than in adjacent tissue from The Cancer Genome Atlas tool. Low UPB1 level was correlated with poor overall survival in patients with LUAD. Furthermore, a comparison of the various pathologic characteristics of LUAD between high and low UPB1 level subgroups revealed that low UPB1 expression was correlated with lymph node metastasis. Kaplan-Meier survival analysis indicated that a low UPB1 level was associated with worse progression‑free survival and overall survival in patients with LUAD. Univariate and multivariate analyses suggested that UPB1 could be a useful prognostic indicator for LUAD. Abnormal UPB1 may be correlated with aberrant LUAD immune infiltration, prompting a worse survival outcome. CONCLUSIONS Results showed that low UPB1 is correlated with a worse prognosis of LUAD and may be a valuable prognostic indicator for LUAD.
Collapse
Affiliation(s)
- Libin Zhang
- Department of Thoracic Surgery, Yan'an Hospital affiliated to Kunming Medical University, Yunnan Province, China
| | - Jun Liu
- Department of Thoracic Surgery, The First People'sHospital of Yunnan Province, Yunnan Province, China
| | - Han Wang
- Department of Thoracic Surgery, The First People'sHospital of Yunnan Province, Yunnan Province, China
| | - Zheyuan Xu
- Department of Thoracic Surgery, The First People'sHospital of Yunnan Province, Yunnan Province, China
| | - Yang Wang
- Department of Thoracic Surgery, The First People'sHospital of Yunnan Province, Yunnan Province, China
| | - Yun Chen
- Department of Thoracic Surgery, The First People'sHospital of Yunnan Province, Yunnan Province, China
| | - Hao Peng
- Department of Thoracic Surgery, The First People'sHospital of Yunnan Province, Yunnan Province, China
| |
Collapse
|
2
|
Yue Y, Tao J, An D, Shi L. Three molecular subtypes and a five-gene signature for hepatocellular carcinoma based on m7G-related classification. J Gene Med 2024; 26:e3611. [PMID: 37847055 DOI: 10.1002/jgm.3611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 09/14/2023] [Accepted: 09/23/2023] [Indexed: 10/18/2023] Open
Abstract
BACKGROUND The current research investigated the heterogeneity of hepatocellular carcinoma (HCC) based on the expression of N7-methylguanosine (m7G)-related genes as a classification model and developed a risk model predictive of HCC prognosis, key pathological behaviors and molecular events of HCC. METHODS The RNA sequencing data of HCC were extracted from The Cancer Genome Atlas (TCGA)-live cancer (LIHC) database, hepatocellular carcinoman database (HCCDB) and Gene Expression Omnibus database, respectively. According to the expression level of 29 m7G-related genes, a consensus clustering analysis was conducted. The least absolute shrinkage and selection operator (LASSO) regression analysis and COX regression algorithm were applied to create a risk prediction model based on normalized expression of five characteristic genes weighted by coefficients. Tumor microenvironment (TME) analysis was performed using the MCP-Counter, TIMER, CIBERSORT and ESTIMATE algorithms. The Tumor Immune Dysfunction and Exclusion algorithm was applied to assess the responses to immunotherapy in different clusters and risk groups. In addition, patient sensitivity to common chemotherapeutic drugs was determined by the biochemical half-maximal inhibitory concentration using the R package pRRophetic. RESULTS Three molecular subtypes of HCC were defined based on the expression level of m7G-associated genes, each of which had its specific survival rate, genomic variation status, TME status and immunotherapy response. In addition, drug sensitivity analysis showed that the C1 subtype was more sensitive to a number of conventional oncolytic drugs (including paclitaxel, imatinib, CGP-082996, pyrimethamine, salubrinal and vinorelbine). The current five-gene risk prediction model accurately predicted HCC prognosis and revealed the degree of somatic mutations, immune microenvironment status and specific biological events. CONCLUSION In this study, three heterogeneous molecular subtypes of HCC were defined based on m7G-related genes as a classification model, and a five-gene risk prediction model was created for predicting HCC prognosis, providing a potential assessment tool for understanding the genomic variation, immune microenvironment status and key pathological mechanisms during HCC development.
Collapse
Affiliation(s)
- Yuan Yue
- Department of Pharmacy, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Jie Tao
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Dan An
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Lei Shi
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| |
Collapse
|
3
|
Zhong S, Chen S, Lin H, Luo Y, He J. Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their putative diagnostic and prognostic role. BMC Urol 2023; 23:186. [PMID: 37968670 PMCID: PMC10652602 DOI: 10.1186/s12894-023-01357-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 11/01/2023] [Indexed: 11/17/2023] Open
Abstract
BACKGROUND Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. This study aims to develop new biomarkers for KIRC and explore the impact of biomarkers on the immunotherapeutic efficacy for KIRC, providing a theoretical basis for the treatment of KIRC patients. METHODS Transcriptome data for KIRC was obtained from the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Weighted gene co-expression network analysis identified KIRC-related modules of long noncoding RNAs (lncRNAs). Intersection analysis was performed differentially expressed lncRNAs between KIRC and normal control samples, and lncRNAs associated with N(7)-methylguanosine (m7G), resulting in differentially expressed m7G-associated lncRNAs in KIRC patients (DE-m7G-lncRNAs). Machine Learning was employed to select biomarkers for KIRC. The prognostic value of biomarkers and clinical features was evaluated using Kaplan-Meier (K-M) survival analysis, univariate and multivariate Cox regression analysis. A nomogram was constructed based on biomarkers and clinical features, and its efficacy was evaluated using calibration curves and decision curves. Functional enrichment analysis was performed to investigate the functional enrichment of biomarkers. Correlation analysis was conducted to explore the relationship between biomarkers and immune cell infiltration levels and common immune checkpoint in KIRC samples. RESULTS By intersecting 575 KIRC-related module lncRNAs, 1773 differentially expressed lncRNAs, and 62 m7G-related lncRNAs, we identified 42 DE-m7G-lncRNAs. Using XGBoost and Boruta algorithms, 8 biomarkers for KIRC were selected. Kaplan-Meier survival analysis showed significant survival differences in KIRC patients with high and low expression of the PTCSC3 and RP11-321G12.1. Univariate and multivariate Cox regression analyses showed that AP000696.2, PTCSC3 and clinical characteristics were independent prognostic factors for patients with KIRC. A nomogram based on these prognostic factors accurately predicted the prognosis of KIRC patients. The biomarkers showed associations with clinical features of KIRC patients, mainly localized in the cytoplasm and related to cytokine-mediated immune response. Furthermore, immune feature analysis demonstrated a significant decrease in immune cell infiltration levels in KIRC samples compared to normal samples, with a negative correlation observed between the biomarkers and most differentially infiltrating immune cells and common immune checkpoints. CONCLUSION In summary, this study discovered eight prognostic biomarkers associated with KIRC patients. These biomarkers showed significant correlations with clinical features, immune cell infiltration, and immune checkpoint expression in KIRC patients, laying a theoretical foundation for the diagnosis and treatment of KIRC.
Collapse
Affiliation(s)
- Shuangze Zhong
- Guangdong Medical University, Zhanjiang City, 524023, Guangdong Province, China
| | - Shangjin Chen
- Guangdong Medical University, Zhanjiang City, 524023, Guangdong Province, China
| | - Hansheng Lin
- Guangdong Medical University, Zhanjiang City, 524023, Guangdong Province, China
- Department of Urology, Yangjiang People's Hospital affiliated to Guangdong Medical University, Yangjiang, 42 Dongshan Road, Jiangcheng District, Guangdong Province, 529500, China
| | - Yuancheng Luo
- Guangdong Medical University, Zhanjiang City, 524023, Guangdong Province, China
| | - Jingwei He
- Department of Urology, Yangjiang People's Hospital affiliated to Guangdong Medical University, Yangjiang, 42 Dongshan Road, Jiangcheng District, Guangdong Province, 529500, China.
| |
Collapse
|
4
|
Han WY, Wang J, Zhao J, Zheng YM, Chai XQ, Gao C, Cai JB, Ke AW, Fan J, Gao PT, Sun HX. WDR4/TRIM28 is a novel molecular target linked to lenvatinib resistance that helps retain the stem characteristics in hepatocellular carcinomas. Cancer Lett 2023:216259. [PMID: 37279851 DOI: 10.1016/j.canlet.2023.216259] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 05/29/2023] [Accepted: 05/31/2023] [Indexed: 06/08/2023]
Abstract
Hepatocellular carcinoma (HCC) is an aggressive malignancy with few effective treatment options. Lenvatinib is the first-line therapy for HCC but has only limited clinical benefit. Here, we explored the role and mechanism of the WD repeat domain 4 (WDR4) in lenvatinib resistance to improve clinical benefit. We found that lenvatinib-resistant HCC tissues/cells exhibited increased the N7-methylguanosine (m7G) modification and WDR4 expression. By a gain/loss of function experiment, we showed that WDR4 promoted HCC lenvatinib resistance and tumor progress both in vitro and in vivo. By proteomics analysis and RNA immunoprecipitation PCR, we found that tripartite motif protein 28 (trim28) was an important WDR4 target gene. WDR4 promoted TRIM28 expression, further affected target genes expression, and thus increased cell-acquired stemness and lenvatinib resistance. Clinical tissue data showed that TRIM28 expression was correlated with WDR4 levels, and the expression of both was positively correlated with poor prognosis. Our study provides new insight into the role of WDR4, suggesting a potential therapeutic target to enhance the lenvatinib sensitivity of HCC.
Collapse
Affiliation(s)
- Wei-Yu Han
- Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion of the Ministry of Education, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Jie Wang
- Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion of the Ministry of Education, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Jing Zhao
- Department of Pathology, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China
| | - Yi-Min Zheng
- Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion of the Ministry of Education, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Xiao-Qiang Chai
- Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion of the Ministry of Education, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Chao Gao
- Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion of the Ministry of Education, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Jia-Bin Cai
- Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion of the Ministry of Education, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Ai-Wu Ke
- Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion of the Ministry of Education, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Jia Fan
- Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion of the Ministry of Education, Key Laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Fudan University, Shanghai, China.
| | - Ping-Ting Gao
- Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Zhongshan Hospital, Fudan University, Shanghai, China; Endoscopy Center and Endoscopy Research Institute, Fudan University, Shanghai, China.
| | - Hai-Xiang Sun
- Liver Cancer Institute, Zhongshan Hospital, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Zhongshan Hospital, Fudan University, Shanghai, China.
| |
Collapse
|