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Lv Q, Shi J, Miao D, Tan D, Zhao C, Xiong Z, Zhang X. miR-1182-mediated ALDH3A2 inhibition affects lipid metabolism and progression in ccRCC by activating the PI3K-AKT pathway. Transl Oncol 2024; 40:101835. [PMID: 38039946 PMCID: PMC10730858 DOI: 10.1016/j.tranon.2023.101835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 11/02/2023] [Accepted: 11/13/2023] [Indexed: 12/03/2023] Open
Abstract
In clear cell renal cell carcinoma (ccRCC), dysregulated lipid metabolism plays a pivotal role in tumor initiation and progression. This study delves into the unexplored landscape of Dysregulated Aldehyde Dehydrogenase 3 Family Member A2 (ALDH3A2) in ccRCC. Using a combination of "fatty acid metabolism" dataset analysis and differentially expressed genes (DEGs) derived from Gene Expression Omnibus (GEO) database, potential metabolic regulators in ccRCC were identified. Subsequent investigations utilizing public databases, clinical samples, and in vitro experiments revealed that ALDH3A2 was down-regulated in ccRCC, mediated by miR-1182, highlighting its role as an independent prognostic factor for patient survival. Functionally, ALDH3A2 exhibited tumor-suppressive properties, impacting ccRCC cell phenotypes and influencing epithelial-mesenchymal transition. Mechanistically, silencing ALDH3A2 promoted lipid accumulation in ccRCC cells by activating the PI3K-AKT pathway, thereby promoting tumor progression. These findings shed light on the critical role of the miR-1182/ALDH3A2 axis in ccRCC tumorigenesis, emphasizing the potential for targeting lipid metabolism as a promising anti-cancer strategy.
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Affiliation(s)
- Qingyang Lv
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China; Institute of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
| | - Jian Shi
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China; Institute of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
| | - Daojia Miao
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China; Institute of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
| | - Diaoyi Tan
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China; Institute of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
| | - Chuanyi Zhao
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China; Institute of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
| | - Zhiyong Xiong
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China; Institute of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China.
| | - Xiaoping Zhang
- Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China; Institute of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, PR China.
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Chang J, Wu H, Wu J, Liu M, Zhang W, Hu Y, Zhang X, Xu J, Li L, Yu P, Zhu J. Constructing a novel mitochondrial-related gene signature for evaluating the tumor immune microenvironment and predicting survival in stomach adenocarcinoma. J Transl Med 2023; 21:191. [PMID: 36915111 PMCID: PMC10012538 DOI: 10.1186/s12967-023-04033-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/03/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND The incidence and mortality of gastric cancer ranks fifth and fourth worldwide among all malignancies, respectively. Accumulating evidences have revealed the close relationship between mitochondrial dysfunction and the initiation and progression of stomach cancer. However, rare prognostic models for mitochondrial-related gene risk have been built up in stomach cancer. METHODS In current study, the expression and prognostic value of mitochondrial-related genes in stomach adenocarcinoma (STAD) patients were systematically analyzed to establish a mitochondrial-related risk model based on available TCGA and GEO databases. The tumor microenvironment (TME), immune cell infiltration, tumor mutation burden, and drug sensitivity of gastric adenocarcinoma patients were also investigated using R language, GraphPad Prism 8 and online databases. RESULTS We established a mitochondrial-related risk prognostic model including NOX4, ALDH3A2, FKBP10 and MAOA and validated its predictive power. This risk model indicated that the immune cell infiltration in high-risk group was significantly different from that in the low-risk group. Besides, the risk score was closely related to TME signature genes and immune checkpoint molecules, suggesting that the immunosuppressive tumor microenvironment might lead to poor prognosis in high-risk groups. Moreover, TIDE analysis demonstrated that combined analysis of risk score and immune score, or stromal score, or microsatellite status could more effectively predict the benefit of immunotherapy in STAD patients with different stratifications. Finally, rapamycin, PD-0325901 and dasatinib were found to be more effective for patients in the high-risk group, whereas AZD7762, CEP-701 and methotrexate were predicted to be more effective for patients in the low-risk group. CONCLUSIONS Our results suggest that the mitochondrial-related risk model could be a reliable prognostic biomarker for personalized treatment of STAD patients.
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Affiliation(s)
- Jingjia Chang
- Department of Cell Biology and Medical Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Hao Wu
- Department of Cell Biology and Medical Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Jin Wu
- Department of Pathology, Laboratory of Translational Medicine Research, Deyang People's Hospital, Deyang, China.,Key Laboratory of Tumor Molecular Research of Deyang, Deyang, China.,Department of Molecular and Cellular Biology, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14263, USA
| | - Ming Liu
- Department of Cell Biology and Medical Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Wentao Zhang
- Department of Cell Biology and Medical Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Yanfen Hu
- Department of Cell Biology and Medical Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Xintong Zhang
- Department of Cell Biology and Medical Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Jing Xu
- Department of Cell Biology and Medical Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Li Li
- Department of Cell Biology and Medical Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China
| | - Pengfei Yu
- Department of Gastrointestinal Surgery, Xijing Hospital, Air Force Military Medical University, Xi'an, 710032, Shaanxi, China.
| | - Jianjun Zhu
- Department of Cell Biology and Medical Genetics, School of Basic Medical Science, Shanxi Medical University, Taiyuan, 030001, China.
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Wang L, Shen J, Wang Y, Bi J. Identification of fatty acid metabolism-based molecular subtypes and prognostic signature to predict immune landscape and guide clinical drug treatment in renal clear cell carcinoma. Int Immunopharmacol 2023; 116:109735. [PMID: 36716517 DOI: 10.1016/j.intimp.2023.109735] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 01/04/2023] [Accepted: 01/11/2023] [Indexed: 01/29/2023]
Abstract
Three subtypes of samples were generated based on genes involved in fatty acid metabolism in The Cancer Genome Atlas (TCGA)-RCC patients using a non-negative matrix factorization (NMF) algorithm. 32 co-expressed modules were identified using WCGNA. We constructed a four-gene signature in our training set using least absolute shrinkage selection operator regression analysis and verified it in our testing and overall sets. A relevant study analysis in clinical trials was conducted, which showed the model had good stability and potential application value for predicting outcomes. We analyzed the immune microenvironment using MCPcounter, CIBERSORT, quanTIseq, TIMER and ESTIMATE algorithms, and the result indicated risk was positively related to T cells, B-lineage, and fibroblasts and negatively correlated with monocytic lineage, myeloid dendritic cells, neutrophils, and endothelial cells, and CPT1B was positively related to T cells, CD8 + T cells, Cytotoxic lymphocytes and NK cells, and negatively correlated with myeloid dendritic cells, fibroblasts, endothelial cells. Tumor mutation burden was positively related to risk score and the expression of CPT1B using the R packages corrplot, circlize. Through the R package pRRophetic, drug sensitivity tests showed that the low-risk score group would benefit more from sunitinib and less from pazopanib, sorafenib, temsirolimus, gemcitabine and doxorubicin than the high-risk score group. We performed the relevant basic assay validation for CPT1B, and the proliferation ability of RCC cells was inhibited after the knockdown of protein expression of CPT1B. In conclusion, we established a four-gene model that can predict outcomes of RCC with potential applications in diagnosis and treatment.
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Affiliation(s)
- Linhui Wang
- Department of Urology, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Junlin Shen
- Department of Urology, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Yutao Wang
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianbin Bi
- Department of Urology, The First Hospital of China Medical University, Shenyang, Liaoning, China.
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Ma X, Sun L. Construction and Validation of Protein Expression-related Prognostic Models in Clear Cell Renal Cell Carcinoma. J Cancer 2023; 14:793-808. [PMID: 37056387 PMCID: PMC10088890 DOI: 10.7150/jca.81915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 02/19/2023] [Indexed: 04/15/2023] Open
Abstract
Objective: To construct a prognostic evaluation model for clear cell renal cell carcinoma (ccRCC) patients using bioinformatics method and to screen potential drugs for ccRCC. Methods: ccRCC RNA sequencing data, clinical data, and protein expression data were downloaded from the TCGA database. Univariate Cox and Lasso regression analyses were performed on the combined data to screen out the proteins related to the prognosis, and they were included in a multivariate Cox proportional hazard model. The patients were divided into high and low-risk groups for a survival difference analysis. The predictive power of the model was evaluated on the basis of overall survival, progression-free survival, independent prognostic, clinically relevant receiver operating characteristic (ROC) curve, C-index, principal component, and clinical data statistics analyses. GSEA enrichment and immune function correlation analyses were performed. The samples were divided into different subtypes based on the expression of the risk proteins, and survival analysis of the subtypes was performed. The risk-related protein and RNA sequencing data were analyzed to screen out sensitive drugs with significant differences between the high and low-risk groups. Results: A total of 469 ccRCC-related proteins were screened, of which 13 proteins with independent prognostic significance were screened by univariate Cox, Lasso, and multivariate Cox regression analyses to construct the prognostic model. The sensitivity and accuracy of the model in predicting the survival of patients with ccRCC were high (1 year: 0.811, 3 years: 0.783, 5 years: 0.777). The 13 proteins were closely related to immunity, and the model proteins were different between kidney and tumor tissues according to the HPA database. The samples were divided into three subtypes, and there were obvious clinical characteristics of the three subtypes in the grade and T, N and M stages. According to the IC50 values, CGP-60474, vinorelbine, doxorubicin, etoposide, FTI-277, JQ12, OSU-03012, pyrimethamine, and other drugs were more sensitive in the high-risk group. Conclusions: A prognostic model of protein expression in ccRCC was successfully constructed, which had good predictive ability for the prognosis of ccRCC patients. The ccRCC-related proteins in the model can be used as targets for studying the pathogenesis and targeted therapy.
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Affiliation(s)
| | - Libin Sun
- ✉ Corresponding author: Libin Sun, Department of Urology, Affiliated First Hospital of Shanxi Medical University, 85 South Jiefang Rd, Taiyuan, Shanxi Province, 030001, China. Tel: +86-15698579398; Email address:
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Ding R, Wei H, Jiang X, Wei L, Deng M, Yuan H. Prognosis and pain dissection of novel signatures in kidney renal clear cell carcinoma based on fatty acid metabolism-related genes. Front Oncol 2022; 12:1094657. [PMID: 36568252 PMCID: PMC9780486 DOI: 10.3389/fonc.2022.1094657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 11/23/2022] [Indexed: 12/13/2022] Open
Abstract
Renal cell carcinoma (RCC) is a malignant tumor that is characterized by the accumulation of intracellular lipid droplets. The prognostic value of fatty acid metabolism-related genes (FMGs) in RCC remains unclear. Alongside this insight, we collected data from three RCC cohorts, namely, The Cancer Genome Atlas (TCGA), E-MTAB-1980, and GSE22541 cohorts, and identified a total of 309 FMGs that could be associated with RCC prognosis. First, we determined the copy number variation and expression levels of these FMGs, and identified 52 overall survival (OS)-related FMGs of the TCGA-KIRC and the E-MTAB-1980 cohort data. Next, 10 of these genes-FASN, ACOT9, MID1IP1, CYP2C9, ABCD1, CPT2, CRAT, TP53INP2, FAAH2, and PTPRG-were identified as pivotal OS-related FMGs based on least absolute shrinkage and selection operator and Cox regression analyses. The expression of some of these genes was confirmed in patients with RCC by immunohistochemical analyses. Kaplan-Meier analysis showed that the identified FMGs were effective in predicting the prognosis of RCC. Moreover, an optimal nomogram was constructed based on FMG-based risk scores and clinical factors, and its robustness was verified by time-dependent receiver operating characteristic analysis, calibration curve analysis, and decision curve analysis. We have also described the biological processes and the tumor immune microenvironment based on FMG-based risk score classification. Given the close association between fatty acid metabolism and cancer-related pain, our 10-FMG signature may also serve as a potential therapeutic target with dual effects on ccRCC prognosis and cancer pain and, therefore, warrants further investigation.
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Affiliation(s)
- Ruifeng Ding
- Department of Anesthesiology, Changzheng Hospital, Second Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Huawei Wei
- Department of Anesthesiology, Changzheng Hospital, Second Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Xin Jiang
- Department of Anesthesiology, Changzheng Hospital, Second Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Liangtian Wei
- Jiangsu Province Key Laboratory of Anesthesiology, Xuzhou Medical University, Xuzhou, China
| | - Mengqiu Deng
- Department of Anesthesiology, Changzheng Hospital, Second Affiliated Hospital of Naval Medical University, Shanghai, China
| | - Hongbin Yuan
- Department of Anesthesiology, Changzheng Hospital, Second Affiliated Hospital of Naval Medical University, Shanghai, China,*Correspondence: Hongbin Yuan,
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A Potential Fatty Acid Metabolism-Related Gene Signature for Prognosis in Clear Cell Renal Cell Carcinoma. Cancers (Basel) 2022; 14:cancers14194943. [PMID: 36230866 PMCID: PMC9564311 DOI: 10.3390/cancers14194943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 09/22/2022] [Accepted: 09/28/2022] [Indexed: 12/04/2022] Open
Abstract
Simple Summary Clear Cell Renal Cell Carcinoma (ccRCC) is the most common and aggressive subtype of renal cancer. Abnormal fatty acid metabolism (FAM) is reported to be strongly associated with multiple malignancies, yet there is limited research in ccRCC. In this manuscript, we reported the significant role of abnormal FAM in predicting the prognosis of ccRCC. Three independent clinical cohorts (TCGA, EMTAB and our clinical cohorts with prognostic profiles and gene expression data, including RNA-seq, microarray and RT-qPCR) were applied as training and two external validation cohorts. As a result, we successfully constructed and validated a novel FAM-related gene signature (FAMGS) and nomogram for the overall survival of patients with ccRCC. Additionally, our study further elucidated the potential immune relevance and molecular mechanisms of abnormal FAM and the signature. In conclusion, the novel FAMGS constructed in this study offered a promising prognostic tool in clinic and potential therapeutic targets for ccRCC patients. Abstract This study aims to explore the role of abnormal fatty acid metabolism (FAM) in ccRCC and construct a novel fatty acid metabolism-related gene signature (FAMGS) for prognosis. Three independent ccRCC cohorts, including The Cancer Genome Atlas, E-MTAB-1980 and our clinical cohort (including RNA-seq, microarray and RT-qPCR data), were applied as training and two independent validation cohorts. Firstly, FAM levels were found to be significantly decreased in ccRCC and correlated with degrees of malignancy, confirming the pivotal role of FAM in ccRCC. Applying the least absolute shrinkage and selection operator cox regression, we established a novel FAMGS for overall survival (OS). The FAMGS divided patients into low or high-risk groups in the training cohort and were successfully validated in both the EMTAB and our clinical validation cohorts. Additionally, the FAMGS serves as an independent risk factor for OS of ccRCC. Results of the immune cell abundance identifier (ImmuCellAI) algorithm and gene set variation analysis (GSVA) revealed that patients in the high-risk group have comprehensively impaired metabolism, including lipids, amino acids and tricarboxylic acid cycle-related pathways and a more immunosuppressive tumor microenvironment. In conclusion, our study constructed and validated a novel FAMGS, which may improve the risk stratification optimization and personalized management of ccRCC.
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Zhou L, Fang H, Yin M, Long H, Weng G. Novel immune-related signature based on immune cells for predicting prognosis and immunotherapy response in clear cell renal cell carcinoma. J Clin Lab Anal 2022; 36:e24409. [PMID: 35441741 PMCID: PMC9169179 DOI: 10.1002/jcla.24409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 03/21/2022] [Accepted: 03/22/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Clear cell renal cell carcinoma (ccRCC) is the most common malignant tumor of the kidney and is characterized by poor prognosis. We sought to build an immune-related prognostic signature and investigate its relationship with immunotherapy response in ccRCC. METHODS Immune-related genes were identified by ssGSEA and WGCNA. The prognostic signature was conducted via univariate, least absolute shrinkage and selection operator, and multivariable Cox regression analyses. Kaplan-Meier analysis, PCA, t-SNE, and ROC were used to evaluate the risk model. RESULTS A total of 119 immune-related genes associated with prognosis were screened out. Six immune-related genes (CSF1, CD5L, AIM2, TIMP3, IRF6, and HHLA2) were applied to construct a prognostic signature for KIRC. Kaplan-Meier analysis showed that patients in high-risk group had a poorer survival outcome than in low-risk group. The 1-, 3- and 5-year AUC of the prognostic signature was 0.754, 0.715, and 0.739, respectively. Univariate and multivariate Cox regression models demonstrated that the risk signature was an independent prognostic factor for KIRC survival. GSEA analysis suggested that the high-risk group was concentrated on immune-related pathways. The high-risk group with more regulatory T-cell infiltration showed a higher expression of immune negative regulation genes. The risk score had positively relationship with TIDE score and negatively with the response of immunotherapy. The IC50 values of axitinib, sunitinib, sorafenib, and temsirolimus were lower in the high-risk group. CONCLUSION Our study defined a robust signature that may be promising for predicting clinical outcomes and immunotherapy and targeted therapy response in ccRCC patients.
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Affiliation(s)
- Libin Zhou
- Department of UrologyThe Affiliated Lihuili HospitalNingbo UniversityNingboChina
- Department of UrologyNingbo Medical Centre Lihuili HospitalNingboChina
| | - Hualong Fang
- The First Affiliated Hospital of NanchangNanchangChina
| | - Min Yin
- Department of UrologyNingbo Medical Centre Lihuili HospitalNingboChina
| | - Huimin Long
- Department of UrologyNingbo Medical Centre Lihuili HospitalNingboChina
| | - Guobin Weng
- Department of UrologyThe Affiliated Yinzhou No 2 Hospital, Ningbo UniversityNingboChina
- Department of UrologyNingbo Yinzhou No 2 HospitalNingboChina
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Zhou Z, Wang T, Du Y, Deng J, Gao G, Zhang J. Identification of a Novel Glycosyltransferase Prognostic Signature in Hepatocellular Carcinoma Based on LASSO Algorithm. Front Genet 2022; 13:823728. [PMID: 35356430 PMCID: PMC8959637 DOI: 10.3389/fgene.2022.823728] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 02/23/2022] [Indexed: 01/10/2023] Open
Abstract
Although many prognostic models have been developed to help determine personalized prognoses and treatments, the predictive efficiency of these prognostic models in hepatocellular carcinoma (HCC), which is a highly heterogeneous malignancy, is less than ideal. Recently, aberrant glycosylation has been demonstrated to universally participate in tumour initiation and progression, suggesting that dysregulation of glycosyltransferases can serve as novel cancer biomarkers. In this study, a total of 568 RNA-sequencing datasets of HCC from the TCGA database and ICGC database were analysed and integrated via bioinformatic methods. LASSO regression analysis was applied to construct a prognostic signature. Kaplan-Meier survival, ROC curve, nomogram, and univariate and multivariate Cox regression analyses were performed to assess the predictive efficiency of the prognostic signature. GSEA and the "CIBERSORT" R package were utilized to further discover the potential biological mechanism of the prognostic signature. Meanwhile, the differential expression of the prognostic signature was verified by western blot, qRT-PCR and immunohistochemical staining derived from the HPA. Ultimately, we constructed a prognostic signature in HCC based on a combination of six glycosyltransferases, whose prognostic value was evaluated and validated successfully in the testing cohort and the validation cohort. The prognostic signature was identified as an independent unfavourable prognostic factor for OS, and a nomogram including the risk score was established and showed the good performance in predicting OS. Further analysis of the underlying mechanism revealed that the prognostic signature may be potentially associated with metabolic disorders and tumour-infiltrating immune cells.
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Affiliation(s)
- Zhiyang Zhou
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Tao Wang
- Department of Day Ward, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yao Du
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Junping Deng
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Ge Gao
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Jiangnan Zhang
- Department of General Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China
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