Jing Chen , Zi-Cheng Zhou , Yang Yan , Shu-Zhen Wu , Tao Ma , Han Xuan , Ruo-Chun Wang , Chi-Yu Gu , Yi-Heng Liu , Qing-Qing Liu , Si-Jia Ge , Wei Huang , Cui-Hua Lu
{"title":"从多组学分析中预测肝纤维化进展的聚集相关基因特征","authors":"Jing Chen , Zi-Cheng Zhou , Yang Yan , Shu-Zhen Wu , Tao Ma , Han Xuan , Ruo-Chun Wang , Chi-Yu Gu , Yi-Heng Liu , Qing-Qing Liu , Si-Jia Ge , Wei Huang , Cui-Hua Lu","doi":"10.1016/j.bmt.2023.04.001","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Liver fibrosis is recognized as a consequence of persistent liver damage. Hence, understanding the mechanisms of liver fibrosis could help patients reverse this process. Aggrephagy is a selective type of autophagy which is under study in various diseases. However, the investigation of aggrephagy in liver fibrosis has not been reported yet.</p></div><div><h3>Methods</h3><p>Five GEO databases were first batched into an integrated dataset by PCA analysis and facilitated for exploration of the aggrephagy-related genes. In addition, the diagnostic model under the aggrephagy-related genes was constructed by random forest. Then Western blot and immunofluorescence were employed in cells treated by autophagy-inhibitor Bafilomycin A1 to analyze whether the aggrephagy induced by liver fibrosis is necessary for aggregates degradation. Furthermore, the single cell data from GEO database and AUCell analysis functioned to detect the aggrephagy score. CellChat analysis compared the interaction strength and underlying receptor ligands between the different aggrephagy score groups. Furthermore, we used the monocle function to display the dynamic process from low aggrephagy score to high aggrephagy score groups. Finally, we used the consensus cluster to compare the clinical characteristics and underlying drug compounds under aggrephagy-score.</p></div><div><h3>Results</h3><p>First, we observed that aggrephagy score was much higher in the liver fibrosis group than in the normal group. Then our results showed that aggrephagy score was positively correlated with several metabolism pathways. In addition, aggrephagy related diagnostic model showed higher efficiency than other markers of liver fibrosis. Further experiments revealed that the removal of aggregates in liver fibrosis was depended on aggrephagy. We then observed that aggrephagy score and CFTR levels were dominantly located in hepatocytes from single-cell data. Moreover, the high aggrephagy-score group showed increased cell interaction strength, intercellular receptor-ligand signaling, and the transcription factor activity of HNF1B than the low aggrephagy-score groups. Hence, aggrephagy might be a promising target for liver fibrosis.</p></div><div><h3>Conclusions</h3><p>Our results showed that the aggrephagy score is a promising index for diagnosing liver fibrosis.</p></div>","PeriodicalId":100180,"journal":{"name":"Biomedical Technology","volume":"5 ","pages":"Pages 46-59"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Characterization of aggrephagy-related genes to predict the progression of liver fibrosis from multi-omics profiles\",\"authors\":\"Jing Chen , Zi-Cheng Zhou , Yang Yan , Shu-Zhen Wu , Tao Ma , Han Xuan , Ruo-Chun Wang , Chi-Yu Gu , Yi-Heng Liu , Qing-Qing Liu , Si-Jia Ge , Wei Huang , Cui-Hua Lu\",\"doi\":\"10.1016/j.bmt.2023.04.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Liver fibrosis is recognized as a consequence of persistent liver damage. Hence, understanding the mechanisms of liver fibrosis could help patients reverse this process. Aggrephagy is a selective type of autophagy which is under study in various diseases. However, the investigation of aggrephagy in liver fibrosis has not been reported yet.</p></div><div><h3>Methods</h3><p>Five GEO databases were first batched into an integrated dataset by PCA analysis and facilitated for exploration of the aggrephagy-related genes. In addition, the diagnostic model under the aggrephagy-related genes was constructed by random forest. Then Western blot and immunofluorescence were employed in cells treated by autophagy-inhibitor Bafilomycin A1 to analyze whether the aggrephagy induced by liver fibrosis is necessary for aggregates degradation. Furthermore, the single cell data from GEO database and AUCell analysis functioned to detect the aggrephagy score. CellChat analysis compared the interaction strength and underlying receptor ligands between the different aggrephagy score groups. Furthermore, we used the monocle function to display the dynamic process from low aggrephagy score to high aggrephagy score groups. Finally, we used the consensus cluster to compare the clinical characteristics and underlying drug compounds under aggrephagy-score.</p></div><div><h3>Results</h3><p>First, we observed that aggrephagy score was much higher in the liver fibrosis group than in the normal group. Then our results showed that aggrephagy score was positively correlated with several metabolism pathways. In addition, aggrephagy related diagnostic model showed higher efficiency than other markers of liver fibrosis. Further experiments revealed that the removal of aggregates in liver fibrosis was depended on aggrephagy. We then observed that aggrephagy score and CFTR levels were dominantly located in hepatocytes from single-cell data. Moreover, the high aggrephagy-score group showed increased cell interaction strength, intercellular receptor-ligand signaling, and the transcription factor activity of HNF1B than the low aggrephagy-score groups. 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Characterization of aggrephagy-related genes to predict the progression of liver fibrosis from multi-omics profiles
Background
Liver fibrosis is recognized as a consequence of persistent liver damage. Hence, understanding the mechanisms of liver fibrosis could help patients reverse this process. Aggrephagy is a selective type of autophagy which is under study in various diseases. However, the investigation of aggrephagy in liver fibrosis has not been reported yet.
Methods
Five GEO databases were first batched into an integrated dataset by PCA analysis and facilitated for exploration of the aggrephagy-related genes. In addition, the diagnostic model under the aggrephagy-related genes was constructed by random forest. Then Western blot and immunofluorescence were employed in cells treated by autophagy-inhibitor Bafilomycin A1 to analyze whether the aggrephagy induced by liver fibrosis is necessary for aggregates degradation. Furthermore, the single cell data from GEO database and AUCell analysis functioned to detect the aggrephagy score. CellChat analysis compared the interaction strength and underlying receptor ligands between the different aggrephagy score groups. Furthermore, we used the monocle function to display the dynamic process from low aggrephagy score to high aggrephagy score groups. Finally, we used the consensus cluster to compare the clinical characteristics and underlying drug compounds under aggrephagy-score.
Results
First, we observed that aggrephagy score was much higher in the liver fibrosis group than in the normal group. Then our results showed that aggrephagy score was positively correlated with several metabolism pathways. In addition, aggrephagy related diagnostic model showed higher efficiency than other markers of liver fibrosis. Further experiments revealed that the removal of aggregates in liver fibrosis was depended on aggrephagy. We then observed that aggrephagy score and CFTR levels were dominantly located in hepatocytes from single-cell data. Moreover, the high aggrephagy-score group showed increased cell interaction strength, intercellular receptor-ligand signaling, and the transcription factor activity of HNF1B than the low aggrephagy-score groups. Hence, aggrephagy might be a promising target for liver fibrosis.
Conclusions
Our results showed that the aggrephagy score is a promising index for diagnosing liver fibrosis.
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