1
|
Li MT, Zheng KF, Qiu YE. Identification of immune cell-related prognostic genes characterized by a distinct microenvironment in hepatocellular carcinoma. World J Clin Oncol 2024; 15:243-270. [PMID: 38455128 PMCID: PMC10915937 DOI: 10.5306/wjco.v15.i2.243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 12/04/2023] [Accepted: 01/11/2024] [Indexed: 02/20/2024] Open
Abstract
BACKGROUND The development and progression of hepatocellular carcinoma (HCC) have been reported to be associated with immune-related genes and the tumor microenvironment. Nevertheless, there are not enough prognostic biomarkers and models available for clinical use. Based on seven prognostic genes, this study calculated overall survival in patients with HCC using a prognostic survival model and revealed the immune status of the tumor microenvironment (TME). AIM To develop a novel immune cell-related prognostic model of HCC and depict the basic profile of the immune response in HCC. METHODS We obtained clinical information and gene expression data of HCC from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. TCGA and ICGC datasets were used for screening prognostic genes along with developing and validating a seven-gene prognostic survival model by weighted gene coexpression network analysis and least absolute shrinkage and selection operator regression with Cox regression. The relative analysis of tumor mutation burden (TMB), TME cell infiltration, immune checkpoints, immune therapy, and functional pathways was also performed based on prognostic genes. RESULTS Seven prognostic genes were identified for signature construction. Survival receiver operating characteristic curve analysis showed the good performance of survival prediction. TMB could be regarded as an independent factor in HCC survival prediction. There was a significant difference in stromal score, immune score, and estimate score between the high-risk and low-risk groups stratified based on the risk score derived from the seven-gene prognostic model. Several immune checkpoints, including VTCN1 and TNFSF9, were found to be associated with the seven prognostic genes and risk score. Different combinations of checkpoint blockade targeting inhibitory CTLA4 and PD1 receptors and potential chemotherapy drugs hold great promise for specific HCC therapies. Potential pathways, such as cell cycle regulation and metabolism of some amino acids, were also identified and analyzed. CONCLUSION The novel seven-gene (CYTH3, ENG, HTRA3, PDZD4, SAMD14, PGF, and PLN) prognostic model showed high predictive efficiency. The TMB analysis based on the seven genes could depict the basic profile of the immune response in HCC, which might be worthy of clinical application.
Collapse
Affiliation(s)
- Meng-Ting Li
- Department of Gastroenterology, The Affiliated People's Hospital of Ningbo University, Ningbo 315000, Zhejiang Province, China
| | - Kai-Feng Zheng
- Department of Gastroenterology, The Affiliated People's Hospital of Ningbo University, Ningbo 315000, Zhejiang Province, China
| | - Yi-Er Qiu
- Department of Gastroenterology, The Affiliated People's Hospital of Ningbo University, Ningbo 315000, Zhejiang Province, China
| |
Collapse
|
2
|
Li C, Yang X, Cheng Y, Wang J. LGR5, a prognostic stem cell target, promotes endometrial cancer proliferation through autophagy activation. Transl Oncol 2024; 40:101853. [PMID: 38134843 PMCID: PMC10776661 DOI: 10.1016/j.tranon.2023.101853] [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: 08/10/2023] [Revised: 11/01/2023] [Accepted: 11/29/2023] [Indexed: 12/24/2023] Open
Abstract
Endometrial cancer (EC) is a common malignant tumor in women worldwide. Although early EC has a good prognosis, advanced endometrial cancer is still associated with the risk of drug resistance and recurrence. Cancer stem cells (CSCs), a category closely related to drug resistance and recurrence, are rarely studied at present. Here, we constructed a risk model containing ten stemness-related prognostic genes. Compared with patients in the low-risk group, patients in the high-risk group had a shorter overall survival time. The accuracy of this model was verified by ROC in the TCGA (AUC = 0.779) and Peking University People's Hospital (PKUPH, AUC = 0.864) cohorts. The risk score and stage were independent risk factors in the multivariate regression analysis, which was subsequently used to construct the nomogram and verified in the TCGA cohort. LGR5 was significantly correlated with overall survival and involvement in the Wnt signaling pathway. In addition, LGR5 was highly expressed in EC tissues and was related to age, stage, histological type, and menopause status in the TCGA database. Overexpression of LGR5 accelerated the proliferation rate of EC cells, which may be related to autophagy activation. Taken together, our study established a prognostic model based on transcription sequencing data from the TCGA database and verified it in the PKUPH cohort, which has prospective clinical implications for the prognostic evaluation of EC. We systematically studied the code gene LGR5 in EC, which may help clinicians make personalized prognostic assessments and effective clinical decisions for EC.
Collapse
Affiliation(s)
- Chengcheng Li
- Department of Obstetrics and Gynecology, Peking University People's Hospital, No. 11, Xizhimen South Street, Xicheng District, Beijing 100044, China
| | - Xiao Yang
- Department of Obstetrics and Gynecology, Peking University People's Hospital, No. 11, Xizhimen South Street, Xicheng District, Beijing 100044, China
| | - Yuan Cheng
- Department of Obstetrics and Gynecology, Peking University People's Hospital, No. 11, Xizhimen South Street, Xicheng District, Beijing 100044, China
| | - Jianliu Wang
- Department of Obstetrics and Gynecology, Peking University People's Hospital, No. 11, Xizhimen South Street, Xicheng District, Beijing 100044, China.
| |
Collapse
|
3
|
Yang Y, Zhao W, Wang Y, Du J. Prognostic impact of MICALL1 and associates with immune infiltration in liver hepatocellular carcinoma patients. Cancer Biomark 2023:CBM220370. [PMID: 37248888 DOI: 10.3233/cbm-220370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
BACKGROUND Liver hepatocellular carcinoma (LIHC) is one of the most malignancy over the world. Previous studies have proven that Molecules Interacting with CasL-Like 1 (MICALL1) participated in cellular trafficking cascades, while there has no study to explore the function and carcinogenic mechanism MICALL1 in LIHC. METHODS We aimed to investigate the relationship between MICALL1 mRNA expression and LIHC using TCGA database. The expression of MICALL1 protein in clinic samples were examined by UALCAN database. Kaplan-Meier method was used for survival analysis. Logistic regression and Cox regression were performed to evaluate the prognostic significance of MICALL1. The MICALL1-binding protein were built by the STRING tool. Enrichment analysis by GO, KEGG and GSEA was used to explore possible function of MICALL1. The ssGSEA method was used to investigate the association between MICALL1 expression and the immune infiltration level in LIHC. RESULTS The expression and prognostic value of different MICAL family members in LIHC were evaluated. The expression of MICALL1 was significantly increased at both the transcript and protein levels in LIHC tissues. Further, the LIHC patients with high MICALL1 levels showed a worse OS, DSS and PFI. Some clinicopathologic features were identified to be related to MICALL1 expression in LIHC included clinical T stage, pathologic stage, histologic grade and AFP concentration. Univariate and multivariate survival analysis showed that MICALL1 was an independent prognostic marker for OS and DSS. Further enrichment analysis revealed that the K-RAS, TNFα/NF-κB and inflammatory response were significantly enriched in the high MICALL1 expression group. Immune infiltration analysis showed that high MICALL1 expression was correlated with infiltration level of macrophage cells, Th2 cells and some other immune cell types, including TFH. CONCLUSIONS MICALL1 expression was significantly associated with immune cell infiltration and may regarded as a promising prognostic biomarker for LIHC patients.
Collapse
Affiliation(s)
- Yixing Yang
- The First Clinical Medical College, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Weizhen Zhao
- Department of Physiology, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yueyuan Wang
- The Laboratory Center for Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jun Du
- Department of Physiology, Nanjing Medical University, Nanjing, Jiangsu, China
| |
Collapse
|
4
|
Chen J, Jin H, Zhou H, Hei X, Liu K. Research into the characteristic molecules significantly affecting liver cancer immunotherapy. Front Immunol 2023; 14:1029427. [PMID: 36860864 PMCID: PMC9968832 DOI: 10.3389/fimmu.2023.1029427] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 02/01/2023] [Indexed: 02/15/2023] Open
Abstract
Background The past decade has witnessed unprecedented scientific breakthroughs, including immunotherapy, which has great potential in clinical applications for liver cancer. Methods Public data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases and analyzed with R software. Results The LASSO and SVM-RFE machine learning algorithms identified 16 differentially expressed genes (DEGs) related to immunotherapy, namely, GNG8, MYH1, CHRNA3, DPEP1, PRSS35, CKMT1B, CNKSR1, C14orf180, POU3F1, SAG, POU2AF1, IGFBPL1, CDCA7, ZNF492, ZDHHC22, and SFRP2. Moreover, a logistic model (CombinedScore) was established based on these DEGs, showing an excellent prediction performance for liver cancer immunotherapy. Patients with a low CombinedScore might respond better to immunotherapy. Gene Set Enrichment Analysis showed that many metabolism pathways were activated in patients with a high CombinedScore, including butanoate metabolism, bile acid metabolism, fatty acid metabolism, glycine serine and threonine metabolism, and propanoate metabolism. Our comprehensive analysis showed that the CombinedScore was negatively correlated with the levels of most tumor-infiltrating immune cells and the activities of key steps of cancer immunity cycles. Continually, the CombinedScore was negatively associated with the expression of most immune checkpoints and immunotherapy response-related pathways. Moreover, patients with a high and a low CombinedScore exhibited diverse genomic features. Furthermore, we found that CDCA7 was significantly correlated with patient survival. Further analysis showed that CDCA7 was positively associated with M0 macrophages and negatively associated with M2 macrophages, suggesting that CDCA7 could influence the progression of liver cancer cells by affecting macrophage polarization. Next, single-cell analysis showed that CDCA7 was mainly expressed in prolif T cells. Immunohistochemical results confirmed that the staining intensity of CDCA7 was prominently increased in the nucleus in primary liver cancer tissues compared to adjacent non-tumor tissues. Conclusions Our results provide novel insights into the DEGs and factors affecting liver cancer immunotherapy. Meanwhile, CDCA7 was identified as a potential therapeutic target in this patient population.
Collapse
Affiliation(s)
- Junhong Chen
- Department of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China
| | - Hengwei Jin
- Department of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China
| | - Hao Zhou
- Department of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China
| | - Xufei Hei
- Department of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China
| | - Kai Liu
- Department of Hepatobiliary and Pancreatic Surgery II, General Surgery Center, The First Hospital of Jilin University, Changchun, China
| |
Collapse
|
5
|
Yue Q, Zhou Z, Zhang X, Xu X, Liu Y, Wang K, Liu Q, Wang J, Zhao Y, Yin Y. Contrast-enhanced CT findings-based model to predict MVI in patients with hepatocellular carcinoma. BMC Gastroenterol 2022; 22:544. [PMID: 36577952 PMCID: PMC9798548 DOI: 10.1186/s12876-022-02586-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 11/16/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Microvascular invasion (MVI) is important in early recurrence and leads to poor overall survival (OS) in hepatocellular carcinoma (HCC). A number of studies have reported independent risk factors for MVI. In this retrospective study, we designed to develop a preoperative model for predicting the presence of MVI in HCC patients to help surgeons in their surgical decision-making and improve patient management. PATIENTS AND METHODS We developed a predictive model based on a nomogram in a training cohort of 225 HCC patients. We analyzed patients' clinical information, laboratory examinations, and imaging features from contrast-enhanced CT. Mann-Whitney U test and multiple logistic regression analysis were used to confirm independent risk factors and develop the predictive model. Internal and external validation was performed on 75 and 77 HCC patients, respectively. Moreover, the diagnostic performance of our model was evaluated using receiver operating characteristic (ROC) curves. RESULTS In the training cohort, maximum tumor diameter (> 50 mm), tumor margin, direct bilirubin (> 2.7 µmol/L), and AFP (> 360.7 ng/mL) were confirmed as independent risk factors for MVI. In the internal and external validation cohort, the developed nomogram model demonstrated good diagnostic ability for MVI with an area under the curve (AUC) of 0.723 and 0.829, respectively. CONCLUSION Based on routine clinical examinations, which may be helpful for clinical decision-making, we have developed a nomogram model that can successfully assess the risk of MVI in HCC patients preoperatively. When predicting HCC patients with a high risk of MVI, the surgeons may perform an anatomical or wide-margin hepatectomy on the patient.
Collapse
Affiliation(s)
- Qi Yue
- grid.428392.60000 0004 1800 1685Department of Hepatobiliary Surgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China ,grid.428392.60000 0004 1800 1685Department of Hepatobiliary Surgery, Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing, China
| | - Zheyu Zhou
- grid.428392.60000 0004 1800 1685Department of Hepatobiliary Surgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China ,grid.428392.60000 0004 1800 1685Department of General Surgery, Nanjing Drum Tower Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Graduate School of Peking Union Medical College, Nanjing, China
| | - Xudong Zhang
- grid.89957.3a0000 0000 9255 8984Department of Hepato-Biliary-Pancreatic Surgery, The Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University, Changzhou, China
| | - Xiaoliang Xu
- grid.428392.60000 0004 1800 1685Department of Hepatobiliary Surgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Yang Liu
- grid.428392.60000 0004 1800 1685Department of Hepatobiliary Surgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Kun Wang
- grid.428392.60000 0004 1800 1685Department of Hepatobiliary Surgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Qiaoyu Liu
- grid.428392.60000 0004 1800 1685Department of Hepatobiliary Surgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Jincheng Wang
- grid.428392.60000 0004 1800 1685Department of Hepatobiliary Surgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Yu Zhao
- grid.89957.3a0000 0000 9255 8984Department of Medical Imaging, School of Medical Imaging, Nanjing Medical University, Jiangning, Nanjing, China
| | - Yin Yin
- grid.428392.60000 0004 1800 1685Department of Hepatobiliary Surgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| |
Collapse
|
6
|
Kong W, Huang W, Peng C, Zhang B, Duan G, Ma W, Huang Z. Multiple machine learning methods aided virtual screening of Na V 1.5 inhibitors. J Cell Mol Med 2022; 27:266-276. [PMID: 36573431 PMCID: PMC9843531 DOI: 10.1111/jcmm.17652] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 10/30/2022] [Accepted: 12/06/2022] [Indexed: 12/28/2022] Open
Abstract
Nav 1.5 sodium channels contribute to the generation of the rapid upstroke of the myocardial action potential and thereby play a central role in the excitability of myocardial cells. At present, the patch clamp method is the gold standard for ion channel inhibitor screening. However, this method has disadvantages such as high technical difficulty, high cost and low speed. In this study, novel machine learning models to screen chemical blockers were developed to overcome the above shortage. The data from the ChEMBL Database were employed to establish the machine learning models. Firstly, six molecular fingerprints together with five machine learning algorithms were used to develop 30 classification models to predict effective inhibitors. A validation and a test set were used to evaluate the performance of the models. Subsequently, the privileged substructures tightly associated with the inhibition of the Nav 1.5 ion channel were extracted using the bioalerts Python package. In the validation set, the RF-Graph model performed best. Similarly, RF-Graph produced the best result in the test set in which the Prediction Accuracy (Q) was 0.9309 and Matthew's correlation coefficient was 0.8627, further indicating the model had high classification ability. The results of the privileged substructures indicated Sulfa structures and fragments with large Steric hindrance tend to block Nav 1.5. In the unsupervised learning task of identifying sulfa drugs, MACCS and Graph fingerprints had good results. In summary, effective machine learning models have been constructed which help to screen potential inhibitors of the Nav 1.5 ion channel and key privileged substructures with high affinity were also extracted.
Collapse
Affiliation(s)
- Weikaixin Kong
- Department of Molecular and Cellular Pharmacology, School of Pharmaceutical SciencesPeking University Health Science CenterBeijingChina,Institute for Molecular Medicine Finland (FIMM)HiLIFE, University of HelsinkiHelsinkiFinland,Institute Sanqu Technology (Hangzhou) Co., Ltd.HangzhouChina
| | - Weiran Huang
- Department of Molecular and Cellular Pharmacology, School of Pharmaceutical SciencesPeking University Health Science CenterBeijingChina
| | - Chao Peng
- Department of Molecular and Cellular Pharmacology, School of Pharmaceutical SciencesPeking University Health Science CenterBeijingChina
| | - Bowen Zhang
- ComMedX (Computational Medicine Beijing Co., Ltd.)BeijingChina
| | - Guifang Duan
- Department of Molecular and Cellular Pharmacology, School of Pharmaceutical SciencesPeking University Health Science CenterBeijingChina
| | - Weining Ma
- Department of NeurologyShengjing Hospital affiliated to China Medical UniversityShenyangChina
| | - Zhuo Huang
- Department of Molecular and Cellular Pharmacology, School of Pharmaceutical SciencesPeking University Health Science CenterBeijingChina,State Key Laboratory of Natural and Biomimetic Drugs, Department of Molecular and Cellular Pharmacology, School of Pharmaceutical SciencesPeking University Health Science CenterBeijingChina
| |
Collapse
|
7
|
Mao S, Yu X, Yang Y, Shan Y, Mugaanyi J, Wu S, Lu C. Preoperative nomogram for microvascular invasion prediction based on clinical database in hepatocellular carcinoma. Sci Rep 2021; 11:13999. [PMID: 34234239 PMCID: PMC8263707 DOI: 10.1038/s41598-021-93528-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 06/25/2021] [Indexed: 01/27/2023] Open
Abstract
The presence of microvascular invasion (MVI) is a critical determinant of early hepatocellular carcinoma (HCC) recurrence and prognosis. We developed a nomogram model integrating clinical laboratory examinations and radiological imaging results from our clinical database to predict microvascular invasion presence at preoperation in HCC patients. 242 patients with pathologically confirmed HCC at the Ningbo Medical Centre Lihuili Hospital from September 2015 to January 2021 were included in this study. Baseline clinical laboratory examinations and radiological imaging results were collected from our clinical database. LASSO regression analysis model was used to construct data dimensionality reduction and elements selection. Multivariate logistic regression analysis was performed to identify the independent risk factors associated with MVI and finally a nomogram for predicting MVI presence of HCC was established. Nomogram performance was assessed via internal validation and calibration curve statistics. Decision curve analysis (DCA) was conducted to determine the clinical usefulness of the nomogram model by quantifying the net benefits along with the increase in threshold probabilities. Survival analysis indicated that the probability of overall survival (OS) and recurrence-free survival (RFS) were significantly different between patients with MVI and without MVI (P < 0.05). Histopathologically identified MVI was found in 117 of 242 patients (48.3%). The preoperative factors associated with MVI were large tumor diameter (OR = 1.271, 95%CI: 1.137–1.420, P < 0.001), AFP level greater than 20 ng/mL (20–400 vs. ≤ 20, OR = 2.025, 95%CI: 1.056–3.885, P = 0.034; > 400 vs. ≤ 20, OR = 3.281, 95%CI: 1.661–6.480, P = 0.001), total bilirubin level greater than 23 umol/l (OR = 2.247, 95%CI: 1.037–4.868, P = 0.040). Incorporating tumor diameter, AFP and TB, the nomogram achieved a better concordance index of 0.725 (95%CI: 0.661–0.788) in predicting MVI presence. Nomogram analysis showed that the total factor score ranged from 0 to 160, and the corresponding risk rate ranged from 0.20 to 0.90. The DCA showed that if the threshold probability was > 5%, using the nomogram to diagnose MVI could acquire much more benefit. And the net benefit of the nomogram model was higher than single variable within 0.3–0.8 of threshold probability. In summary, the presence of MVI is an independent prognostic risk factor for RFS. The nomogram detailed here can preoperatively predict MVI presence in HCC patients. Using the nomogram model may constitute a usefully clinical tool to guide a rational and personalized subsequent therapeutic choice.
Collapse
Affiliation(s)
- Shuqi Mao
- Department of Hepatopancreatobiliary Surgery, Ningbo Medical Centre Lihuili Hospital, Ningbo University, Ningbo, 315040, Zhejiang, China
| | - Xi Yu
- Department of Hepatopancreatobiliary Surgery, Ningbo Medical Centre Lihuili Hospital, Ningbo University, Ningbo, 315040, Zhejiang, China
| | - Yong Yang
- Department of Hepatopancreatobiliary Surgery, Ningbo Medical Centre Lihuili Hospital, Ningbo University, Ningbo, 315040, Zhejiang, China
| | - Yuying Shan
- Department of Hepatopancreatobiliary Surgery, Ningbo Medical Centre Lihuili Hospital, Ningbo University, Ningbo, 315040, Zhejiang, China
| | - Joseph Mugaanyi
- Department of Hepatopancreatobiliary Surgery, Ningbo Medical Centre Lihuili Hospital, Ningbo University, Ningbo, 315040, Zhejiang, China
| | - Shengdong Wu
- Department of Hepatopancreatobiliary Surgery, Ningbo Medical Centre Lihuili Hospital, Ningbo University, Ningbo, 315040, Zhejiang, China.
| | - Caide Lu
- Department of Hepatopancreatobiliary Surgery, Ningbo Medical Centre Lihuili Hospital, Ningbo University, Ningbo, 315040, Zhejiang, China.
| |
Collapse
|
8
|
Chen G, Yin Y, Lin Z, Wen H, Chen J, Luo W. Transcriptome profile analysis reveals KLHL30 as an essential regulator for myoblast differentiation. Biochem Biophys Res Commun 2021; 559:84-91. [PMID: 33933993 DOI: 10.1016/j.bbrc.2021.04.086] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 04/20/2021] [Indexed: 11/29/2022]
Abstract
Skeletal muscle development is a sophisticated multistep process orchestrated by diverse myogenic transcription factors. Recent studies have suggested that Kelch-like genes play vital roles in muscle disease and myogenesis. However, it is still unclear how Kelch-like genes impact myoblast physiology. Here, through integrative analysis of the mRNA expression profile during chicken primary myoblast and C2C12 differentiation, many differentially expressed genes were found and suggested to be enriched in myoblast differentiation and muscle development. Interestingly, a little-known Kelch-like gene KLHL30 was screened as skeletal muscle-specific gene with essential roles in myogenic differentiation. Transcriptomic data and quantitative PCR analysis indicated that the expression of KLHL30 is upregulated under myoblast differentiation state. KLHL30 overexpression upregulated the protein expression of myogenic transcription factors (MYOD, MYOG, MEF2C) and induced myoblast differentiation and myotube formation, while knockdown of KLHL30 caused the opposite effect. Furthermore, KLHL30 was found to significantly decrease the numbers of cells in the S stage and thereby depress myoblast proliferation. Collectively, this study highlights that KLHL30 as a muscle-specific regulator plays essential roles in myoblast proliferation and differentiation.
Collapse
Affiliation(s)
- Genghua Chen
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, 510642, Guangdong Province, China; Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, 510642, China
| | - Yunqian Yin
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, 510642, Guangdong Province, China; Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, 510642, China
| | - Zetong Lin
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, 510642, Guangdong Province, China; Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, 510642, China
| | - Huaqiang Wen
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, 510642, Guangdong Province, China; Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, 510642, China
| | - Jiahui Chen
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, 510642, Guangdong Province, China; Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, 510642, China
| | - Wen Luo
- Department of Animal Genetics, Breeding and Reproduction, College of Animal Science, South China Agricultural University, Guangzhou, 510642, Guangdong Province, China; Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, and Key Laboratory of Chicken Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affair, South China Agricultural University, Guangzhou, 510642, China.
| |
Collapse
|