Circadian rhythm related genes signature in glioma for drug resistance prediction: a comprehensive analysis integrating transcriptomics and machine learning
Abstract Background Gliomas, 24% of all primary brain tumors, have diverse histology and poor survival rates, with about 70% recurring due to acquired or de novo resistance. Insomnia in patients is correlated strongly with circadian rhythm disruptions. The correlation between circadian rhythm disord...
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| Format: | Article |
| Language: | English |
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Springer
2025-02-01
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| Series: | Discover Oncology |
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| Online Access: | https://doi.org/10.1007/s12672-025-01863-2 |
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| _version_ | 1823861778296078336 |
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| author | Junbo Liao Yingxing Duan Xiangwang Xu Yaxue Liu Chaohong Zhan Gelei Xiao |
| author_facet | Junbo Liao Yingxing Duan Xiangwang Xu Yaxue Liu Chaohong Zhan Gelei Xiao |
| author_sort | Junbo Liao |
| collection | DOAJ |
| description | Abstract Background Gliomas, 24% of all primary brain tumors, have diverse histology and poor survival rates, with about 70% recurring due to acquired or de novo resistance. Insomnia in patients is correlated strongly with circadian rhythm disruptions. The correlation between circadian rhythm disorders and drug resistance of some tumors has been proved. However, the precise mechanism underlying the relationship between glioma and circadian rhythm disorders has not been elucidated. Methods Circadian rhythm-related genes (CRRGs) were identified using the least absolute shrinkage and selection operator (LASSO) regression, and stochastic gradient descent (SGD) was performed to form a circadian rhythm-related score (CRRS) model. The studies of immune cell infiltration, genetic variations, differential gene expression pattern, and single cell analysis were performed for exploring the mechanisms of chemotherapy resistance in glioma. The relationship between CRRGs and chemosensitivity was also confirmed by IC 50 (half maximal inhibitory concentration) analysis. Result Signatures of 16 CRRGs were screened out and identified. Based on the CRRS model, an optimal comprehensive nomogram was created, exhibiting a favorable potential for predicting drug resistance in samples. Immune infiltration, cell–cell communication, and single cell analysis all indicated that high CRRS group was closely related to innate immune cells. IC50 analysis showed that CRRG knockdown enhanced the chemosensitivity of glioma. Conclusion A significant correlation between CRRGs, drug resistance of glioma, and innate immune cells was found, which might hold a significant role in the drug resistance of glioma. |
| format | Article |
| id | doaj-art-08de6fe9b2e6442cb2838b553617101f |
| institution | Kabale University |
| issn | 2730-6011 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Oncology |
| spelling | doaj-art-08de6fe9b2e6442cb2838b553617101f2025-02-09T12:43:32ZengSpringerDiscover Oncology2730-60112025-02-0116112310.1007/s12672-025-01863-2Circadian rhythm related genes signature in glioma for drug resistance prediction: a comprehensive analysis integrating transcriptomics and machine learningJunbo Liao0Yingxing Duan1Xiangwang Xu2Yaxue Liu3Chaohong Zhan4Gelei Xiao5Department of Neurosurgery, Xiangya Hospital, Central South UniversityDepartment of Radiology, Xiangya Hospital, Central South UniversityDepartment of Neurosurgery, Xiangya Hospital, Central South UniversityDepartment of Neurosurgery, Xiangya Hospital, Central South UniversityDepartment of Neurosurgery, Xiangya Hospital, Central South UniversityDepartment of Neurosurgery, Xiangya Hospital, Central South UniversityAbstract Background Gliomas, 24% of all primary brain tumors, have diverse histology and poor survival rates, with about 70% recurring due to acquired or de novo resistance. Insomnia in patients is correlated strongly with circadian rhythm disruptions. The correlation between circadian rhythm disorders and drug resistance of some tumors has been proved. However, the precise mechanism underlying the relationship between glioma and circadian rhythm disorders has not been elucidated. Methods Circadian rhythm-related genes (CRRGs) were identified using the least absolute shrinkage and selection operator (LASSO) regression, and stochastic gradient descent (SGD) was performed to form a circadian rhythm-related score (CRRS) model. The studies of immune cell infiltration, genetic variations, differential gene expression pattern, and single cell analysis were performed for exploring the mechanisms of chemotherapy resistance in glioma. The relationship between CRRGs and chemosensitivity was also confirmed by IC 50 (half maximal inhibitory concentration) analysis. Result Signatures of 16 CRRGs were screened out and identified. Based on the CRRS model, an optimal comprehensive nomogram was created, exhibiting a favorable potential for predicting drug resistance in samples. Immune infiltration, cell–cell communication, and single cell analysis all indicated that high CRRS group was closely related to innate immune cells. IC50 analysis showed that CRRG knockdown enhanced the chemosensitivity of glioma. Conclusion A significant correlation between CRRGs, drug resistance of glioma, and innate immune cells was found, which might hold a significant role in the drug resistance of glioma.https://doi.org/10.1007/s12672-025-01863-2GliomaCircadian rhythmChemotherapyDrug resistanceInnate immune |
| spellingShingle | Junbo Liao Yingxing Duan Xiangwang Xu Yaxue Liu Chaohong Zhan Gelei Xiao Circadian rhythm related genes signature in glioma for drug resistance prediction: a comprehensive analysis integrating transcriptomics and machine learning Discover Oncology Glioma Circadian rhythm Chemotherapy Drug resistance Innate immune |
| title | Circadian rhythm related genes signature in glioma for drug resistance prediction: a comprehensive analysis integrating transcriptomics and machine learning |
| title_full | Circadian rhythm related genes signature in glioma for drug resistance prediction: a comprehensive analysis integrating transcriptomics and machine learning |
| title_fullStr | Circadian rhythm related genes signature in glioma for drug resistance prediction: a comprehensive analysis integrating transcriptomics and machine learning |
| title_full_unstemmed | Circadian rhythm related genes signature in glioma for drug resistance prediction: a comprehensive analysis integrating transcriptomics and machine learning |
| title_short | Circadian rhythm related genes signature in glioma for drug resistance prediction: a comprehensive analysis integrating transcriptomics and machine learning |
| title_sort | circadian rhythm related genes signature in glioma for drug resistance prediction a comprehensive analysis integrating transcriptomics and machine learning |
| topic | Glioma Circadian rhythm Chemotherapy Drug resistance Innate immune |
| url | https://doi.org/10.1007/s12672-025-01863-2 |
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