Bulk and single-cell sequencing identified a prognostic model based on the macrophage and lipid metabolism related signatures for osteosarcoma patients
The introduction of multidrug combination chemotherapy has significantly advanced the long-term survival prospects for osteosarcoma (OS) patients over the past decades. However, the escalating prevalence of chemoresistance has emerged as a substantial impediment to further advancements, necessitatin...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-02-01
|
| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024021224 |
| _version_ | 1797267722822746112 |
|---|---|
| author | Zili Lin Ziyi Wu Wei Luo |
| author_facet | Zili Lin Ziyi Wu Wei Luo |
| author_sort | Zili Lin |
| collection | DOAJ |
| description | The introduction of multidrug combination chemotherapy has significantly advanced the long-term survival prospects for osteosarcoma (OS) patients over the past decades. However, the escalating prevalence of chemoresistance has emerged as a substantial impediment to further advancements, necessitating the formulation of innovative strategies. Our present study leveraged sophisticated bulk and single-cell sequencing techniques to scrutinize the OS immune microenvironment, unveiling a potential association between the differentiation state of macrophages and the efficacy of OS chemotherapy. Notably, we observed that a heightened presence of lipid metabolism genes and pathways in predifferentiated macrophages, constituting the major cluster of OS patients exhibiting a less favorable response to chemotherapy. Subsequently, we developed a robust Macrophage and Lipid Metabolism (MLMR) risk model and a nomogram, both of which demonstrated commendable prognostic predictive performance. Furthermore, a comprehensive investigation into the underlying mechanisms of the risk model revealed intricate associations with variations in the immune response among OS patients. Finally, our meticulous drug sensitivity analysis identified a spectrum of potential therapeutic agents for OS, including AZD2014, Sapitinib, Buparlisib, Afuresertib, MIRA-1, and BIBR-1532. These findings significantly augment the therapeutic arsenal available to clinicians managing OS, presenting a promising avenue for elevating treatment outcomes. |
| first_indexed | 2024-04-25T01:21:06Z |
| format | Article |
| id | doaj.art-2808522a9fc0491cbc0a132928a83f35 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-25T01:21:06Z |
| publishDate | 2024-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-2808522a9fc0491cbc0a132928a83f352024-03-09T09:27:10ZengElsevierHeliyon2405-84402024-02-01104e26091Bulk and single-cell sequencing identified a prognostic model based on the macrophage and lipid metabolism related signatures for osteosarcoma patientsZili Lin0Ziyi Wu1Wei Luo2Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, PR ChinaDepartment of Orthopaedics, the Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, PR ChinaDepartment of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, PR China; National Clinical Research Center for Geriatric Disorders,Xiangya Hospital, Changsha, Hunan, 410008, PR China; Corresponding author. Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, PR China.The introduction of multidrug combination chemotherapy has significantly advanced the long-term survival prospects for osteosarcoma (OS) patients over the past decades. However, the escalating prevalence of chemoresistance has emerged as a substantial impediment to further advancements, necessitating the formulation of innovative strategies. Our present study leveraged sophisticated bulk and single-cell sequencing techniques to scrutinize the OS immune microenvironment, unveiling a potential association between the differentiation state of macrophages and the efficacy of OS chemotherapy. Notably, we observed that a heightened presence of lipid metabolism genes and pathways in predifferentiated macrophages, constituting the major cluster of OS patients exhibiting a less favorable response to chemotherapy. Subsequently, we developed a robust Macrophage and Lipid Metabolism (MLMR) risk model and a nomogram, both of which demonstrated commendable prognostic predictive performance. Furthermore, a comprehensive investigation into the underlying mechanisms of the risk model revealed intricate associations with variations in the immune response among OS patients. Finally, our meticulous drug sensitivity analysis identified a spectrum of potential therapeutic agents for OS, including AZD2014, Sapitinib, Buparlisib, Afuresertib, MIRA-1, and BIBR-1532. These findings significantly augment the therapeutic arsenal available to clinicians managing OS, presenting a promising avenue for elevating treatment outcomes.http://www.sciencedirect.com/science/article/pii/S2405844024021224OsteosarcomaMacrophageLipid metabolismChemoresistanceImmune infiltration |
| spellingShingle | Zili Lin Ziyi Wu Wei Luo Bulk and single-cell sequencing identified a prognostic model based on the macrophage and lipid metabolism related signatures for osteosarcoma patients Heliyon Osteosarcoma Macrophage Lipid metabolism Chemoresistance Immune infiltration |
| title | Bulk and single-cell sequencing identified a prognostic model based on the macrophage and lipid metabolism related signatures for osteosarcoma patients |
| title_full | Bulk and single-cell sequencing identified a prognostic model based on the macrophage and lipid metabolism related signatures for osteosarcoma patients |
| title_fullStr | Bulk and single-cell sequencing identified a prognostic model based on the macrophage and lipid metabolism related signatures for osteosarcoma patients |
| title_full_unstemmed | Bulk and single-cell sequencing identified a prognostic model based on the macrophage and lipid metabolism related signatures for osteosarcoma patients |
| title_short | Bulk and single-cell sequencing identified a prognostic model based on the macrophage and lipid metabolism related signatures for osteosarcoma patients |
| title_sort | bulk and single cell sequencing identified a prognostic model based on the macrophage and lipid metabolism related signatures for osteosarcoma patients |
| topic | Osteosarcoma Macrophage Lipid metabolism Chemoresistance Immune infiltration |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024021224 |
| work_keys_str_mv | AT zililin bulkandsinglecellsequencingidentifiedaprognosticmodelbasedonthemacrophageandlipidmetabolismrelatedsignaturesforosteosarcomapatients AT ziyiwu bulkandsinglecellsequencingidentifiedaprognosticmodelbasedonthemacrophageandlipidmetabolismrelatedsignaturesforosteosarcomapatients AT weiluo bulkandsinglecellsequencingidentifiedaprognosticmodelbasedonthemacrophageandlipidmetabolismrelatedsignaturesforosteosarcomapatients |