Bioinformatics-based analysis of fatty acid metabolic reprogramming in hepatocellular carcinoma: cellular heterogeneity, therapeutic targets, and drug discovery
Fatty acid (FA) reprogramming has a significant role in liver cancer. However, the contribution of FA metabolism reprogramming to the heterogeneity of hepatocellular carcinoma (HCC) has not been established. Bioinformatics analysis using single-cell sequencing, a non-negative matrix factorization (N...
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| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Compuscript Ltd
2024-11-01
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| Series: | Acta Materia Medica |
| Online Access: | https://www.scienceopen.com/hosted-document?doi=10.15212/AMM-2024-0057 |
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| author | Yingying Guo Run Shi Yu Xu William C. Cho Jun Yang You Yeon Choi Jing Sun Yan Ma Olga Pozharitskaya Alexander Shikov Hongliang Li Minglun Li Zhenpeng Qiu Woong Mo Yang Pierre Duez Hongxi Xu Xuanbin Wang |
| author_facet | Yingying Guo Run Shi Yu Xu William C. Cho Jun Yang You Yeon Choi Jing Sun Yan Ma Olga Pozharitskaya Alexander Shikov Hongliang Li Minglun Li Zhenpeng Qiu Woong Mo Yang Pierre Duez Hongxi Xu Xuanbin Wang |
| author_sort | Yingying Guo |
| collection | DOAJ |
| description | Fatty acid (FA) reprogramming has a significant role in liver cancer. However, the contribution of FA metabolism reprogramming to the heterogeneity of hepatocellular carcinoma (HCC) has not been established. Bioinformatics analysis using single-cell sequencing, a non-negative matrix factorization (NMF) algorithm, and survival analyses were used to investigate FA metabolism reprogramming in HCC patients. Molecular targets and the progress of drug discovery were also analyzed and discussed. Among 13 types of HCC cells, epithelial cells exhibited the highest score for FA metabolic aberrance, while certain lymphocytes, such as B cells, CD8Tcm cells, and Treg cells, exhibited the lowest score. Furthermore, epithelial cells displayed significant diversity in FA metabolism with a wide distribution range (−0.2 to 0.8). Additionally, a low level of FA metabolism was associated with poor prognosis in HCC patients (log-rank test, P =0.0089). Higher oxidase expression was correlated with a lower risk of oncogenesis and higher overall survival. However, enzymes involved in synthesis, oxidation, storage, and release exhibited considerable phenotypic diversity in HCC. FA metabolism reprograming was shown to be significantly correlated with the heterogeneity of HCC, which is characterized by a diversity of cancerous cells and enzymes. |
| format | Article |
| id | doaj-art-56cc9cd5a27a4175a8d714244b687725 |
| institution | Kabale University |
| issn | 2737-7946 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Compuscript Ltd |
| record_format | Article |
| series | Acta Materia Medica |
| spelling | doaj-art-56cc9cd5a27a4175a8d714244b6877252025-08-20T03:27:17ZengCompuscript LtdActa Materia Medica2737-79462024-11-013447750810.15212/AMM-2024-0057Bioinformatics-based analysis of fatty acid metabolic reprogramming in hepatocellular carcinoma: cellular heterogeneity, therapeutic targets, and drug discoveryYingying GuoRun ShiYu XuWilliam C. ChoJun YangYou Yeon ChoiJing SunYan MaOlga PozharitskayaAlexander ShikovHongliang LiMinglun LiZhenpeng QiuWoong Mo YangPierre DuezHongxi XuXuanbin WangFatty acid (FA) reprogramming has a significant role in liver cancer. However, the contribution of FA metabolism reprogramming to the heterogeneity of hepatocellular carcinoma (HCC) has not been established. Bioinformatics analysis using single-cell sequencing, a non-negative matrix factorization (NMF) algorithm, and survival analyses were used to investigate FA metabolism reprogramming in HCC patients. Molecular targets and the progress of drug discovery were also analyzed and discussed. Among 13 types of HCC cells, epithelial cells exhibited the highest score for FA metabolic aberrance, while certain lymphocytes, such as B cells, CD8Tcm cells, and Treg cells, exhibited the lowest score. Furthermore, epithelial cells displayed significant diversity in FA metabolism with a wide distribution range (−0.2 to 0.8). Additionally, a low level of FA metabolism was associated with poor prognosis in HCC patients (log-rank test, P =0.0089). Higher oxidase expression was correlated with a lower risk of oncogenesis and higher overall survival. However, enzymes involved in synthesis, oxidation, storage, and release exhibited considerable phenotypic diversity in HCC. FA metabolism reprograming was shown to be significantly correlated with the heterogeneity of HCC, which is characterized by a diversity of cancerous cells and enzymes.https://www.scienceopen.com/hosted-document?doi=10.15212/AMM-2024-0057 |
| spellingShingle | Yingying Guo Run Shi Yu Xu William C. Cho Jun Yang You Yeon Choi Jing Sun Yan Ma Olga Pozharitskaya Alexander Shikov Hongliang Li Minglun Li Zhenpeng Qiu Woong Mo Yang Pierre Duez Hongxi Xu Xuanbin Wang Bioinformatics-based analysis of fatty acid metabolic reprogramming in hepatocellular carcinoma: cellular heterogeneity, therapeutic targets, and drug discovery Acta Materia Medica |
| title | Bioinformatics-based analysis of fatty acid metabolic reprogramming in hepatocellular carcinoma: cellular heterogeneity, therapeutic targets, and drug discovery |
| title_full | Bioinformatics-based analysis of fatty acid metabolic reprogramming in hepatocellular carcinoma: cellular heterogeneity, therapeutic targets, and drug discovery |
| title_fullStr | Bioinformatics-based analysis of fatty acid metabolic reprogramming in hepatocellular carcinoma: cellular heterogeneity, therapeutic targets, and drug discovery |
| title_full_unstemmed | Bioinformatics-based analysis of fatty acid metabolic reprogramming in hepatocellular carcinoma: cellular heterogeneity, therapeutic targets, and drug discovery |
| title_short | Bioinformatics-based analysis of fatty acid metabolic reprogramming in hepatocellular carcinoma: cellular heterogeneity, therapeutic targets, and drug discovery |
| title_sort | bioinformatics based analysis of fatty acid metabolic reprogramming in hepatocellular carcinoma cellular heterogeneity therapeutic targets and drug discovery |
| url | https://www.scienceopen.com/hosted-document?doi=10.15212/AMM-2024-0057 |
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