Single-cell RNA sequencing and AlphaFold 3 insights into cytokine signaling and its role in uveal melanoma
BackgroundUveal melanoma (UVM) is a form of eye cancer with a poor prognosis, particularly in metastatic patients. This study aimed to elucidate the cellular heterogeneity within UVM and identify prognostic biomarkers.MethodsWe performed single-cell RNA sequencing (scRNA-seq) on primary and metastat...
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-01-01
|
| Series: | Frontiers in Immunology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1458041/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832590858953687040 |
|---|---|
| author | Hongyan Sun Cunzi Li Zuhui Pu Zuhui Pu Ying Lu Ying Lu Zijing Wu Zijing Wu Lan Zhou Lan Zhou Hongzhan Lin Yumo Wang Tao Zi Lisha Mou Lisha Mou Ming-ming Yang |
| author_facet | Hongyan Sun Cunzi Li Zuhui Pu Zuhui Pu Ying Lu Ying Lu Zijing Wu Zijing Wu Lan Zhou Lan Zhou Hongzhan Lin Yumo Wang Tao Zi Lisha Mou Lisha Mou Ming-ming Yang |
| author_sort | Hongyan Sun |
| collection | DOAJ |
| description | BackgroundUveal melanoma (UVM) is a form of eye cancer with a poor prognosis, particularly in metastatic patients. This study aimed to elucidate the cellular heterogeneity within UVM and identify prognostic biomarkers.MethodsWe performed single-cell RNA sequencing (scRNA-seq) on primary and metastatic UVM samples. A UVM-specific gene signature was constructed using LASSO regression and validated via ROC curve analysis in the TCGA-UVM and GSE84976 cohorts. AlphaFold 3 was used to predict the 3D structures of key proteins. T-cell populations were analyzed using pseudotime trajectory mapping and interaction network visualization. CRISPR-Cas9 screening analysis was conducted to identify hub genes and cytokine pathways that may serve as therapeutic targets. Additionally, we constructed the Dictionary of Immune Responses to Cytokines at single-cell resolution to evaluate cytokine signatures.ResultsScRNA-seq revealed five major cell types within UVMs and subdivided them into seven distinct subtypes. Cytokine signaling analysis revealed differential expression of cytokine signaling in immune-related genes (CSIRGs) across these subtypes in primary and metastatic tumors. The UVM-specific gene signature demonstrated high predictive accuracy in ROC curve analysis and was associated with overall survival in Kaplan–Meier survival analyses. Additionally, AlphaFold 3 predicted the 3D structures of key proteins with high confidence. T-cell population analysis revealed complex developmental pathways and interaction networks in UVM. Myeloid-derived suppressor cells (MDSCs) were found to be increased in metastatic UVM, correlating with the enrichment of GM-CSF. CRISPR-Cas9 screening analysis identified hub genes and cytokine pathways with low gene effect scores across cell lines, indicating their potential importance in UVM.ConclusionThis study identified critical cellular subtypes and prognostic biomarkers in UVM, shedding light on targeted therapies. The insights into cytokine signaling and T-cell dynamics within the UVM microenvironment provide a foundation for developing personalized therapeutic strategies to improve patient outcomes. |
| format | Article |
| id | doaj-art-026253cd3d2d4f099ca69f1c7251c256 |
| institution | Kabale University |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj-art-026253cd3d2d4f099ca69f1c7251c2562025-01-23T06:56:14ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-01-011510.3389/fimmu.2024.14580411458041Single-cell RNA sequencing and AlphaFold 3 insights into cytokine signaling and its role in uveal melanomaHongyan Sun0Cunzi Li1Zuhui Pu2Zuhui Pu3Ying Lu4Ying Lu5Zijing Wu6Zijing Wu7Lan Zhou8Lan Zhou9Hongzhan Lin10Yumo Wang11Tao Zi12Lisha Mou13Lisha Mou14Ming-ming Yang15Department of Ophthalmology, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, ChinaDepartment of Ophthalmology, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, ChinaImaging Department, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, ChinaMetaLife Center, Shenzhen Institute of Translational Medicine, Shenzhen, Guangdong, ChinaImaging Department, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, ChinaMetaLife Center, Shenzhen Institute of Translational Medicine, Shenzhen, Guangdong, ChinaImaging Department, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, ChinaMetaLife Center, Shenzhen Institute of Translational Medicine, Shenzhen, Guangdong, ChinaDepartment of Ophthalmology, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, ChinaPost-doctoral Scientific Research Station of Basic Medicine, Jinan University, Guangzhou, ChinaDepartment of Ophthalmology, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, ChinaDepartment of Ophthalmology, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, ChinaDepartment of Ophthalmology, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, ChinaImaging Department, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, ChinaMetaLife Center, Shenzhen Institute of Translational Medicine, Shenzhen, Guangdong, ChinaDepartment of Ophthalmology, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, ChinaBackgroundUveal melanoma (UVM) is a form of eye cancer with a poor prognosis, particularly in metastatic patients. This study aimed to elucidate the cellular heterogeneity within UVM and identify prognostic biomarkers.MethodsWe performed single-cell RNA sequencing (scRNA-seq) on primary and metastatic UVM samples. A UVM-specific gene signature was constructed using LASSO regression and validated via ROC curve analysis in the TCGA-UVM and GSE84976 cohorts. AlphaFold 3 was used to predict the 3D structures of key proteins. T-cell populations were analyzed using pseudotime trajectory mapping and interaction network visualization. CRISPR-Cas9 screening analysis was conducted to identify hub genes and cytokine pathways that may serve as therapeutic targets. Additionally, we constructed the Dictionary of Immune Responses to Cytokines at single-cell resolution to evaluate cytokine signatures.ResultsScRNA-seq revealed five major cell types within UVMs and subdivided them into seven distinct subtypes. Cytokine signaling analysis revealed differential expression of cytokine signaling in immune-related genes (CSIRGs) across these subtypes in primary and metastatic tumors. The UVM-specific gene signature demonstrated high predictive accuracy in ROC curve analysis and was associated with overall survival in Kaplan–Meier survival analyses. Additionally, AlphaFold 3 predicted the 3D structures of key proteins with high confidence. T-cell population analysis revealed complex developmental pathways and interaction networks in UVM. Myeloid-derived suppressor cells (MDSCs) were found to be increased in metastatic UVM, correlating with the enrichment of GM-CSF. CRISPR-Cas9 screening analysis identified hub genes and cytokine pathways with low gene effect scores across cell lines, indicating their potential importance in UVM.ConclusionThis study identified critical cellular subtypes and prognostic biomarkers in UVM, shedding light on targeted therapies. The insights into cytokine signaling and T-cell dynamics within the UVM microenvironment provide a foundation for developing personalized therapeutic strategies to improve patient outcomes.https://www.frontiersin.org/articles/10.3389/fimmu.2024.1458041/fulluveal melanomasingle-cell RNA sequencingcytokine signalingT cellAlphaFold 3Dictionary of Immune Responses to Cytokines |
| spellingShingle | Hongyan Sun Cunzi Li Zuhui Pu Zuhui Pu Ying Lu Ying Lu Zijing Wu Zijing Wu Lan Zhou Lan Zhou Hongzhan Lin Yumo Wang Tao Zi Lisha Mou Lisha Mou Ming-ming Yang Single-cell RNA sequencing and AlphaFold 3 insights into cytokine signaling and its role in uveal melanoma Frontiers in Immunology uveal melanoma single-cell RNA sequencing cytokine signaling T cell AlphaFold 3 Dictionary of Immune Responses to Cytokines |
| title | Single-cell RNA sequencing and AlphaFold 3 insights into cytokine signaling and its role in uveal melanoma |
| title_full | Single-cell RNA sequencing and AlphaFold 3 insights into cytokine signaling and its role in uveal melanoma |
| title_fullStr | Single-cell RNA sequencing and AlphaFold 3 insights into cytokine signaling and its role in uveal melanoma |
| title_full_unstemmed | Single-cell RNA sequencing and AlphaFold 3 insights into cytokine signaling and its role in uveal melanoma |
| title_short | Single-cell RNA sequencing and AlphaFold 3 insights into cytokine signaling and its role in uveal melanoma |
| title_sort | single cell rna sequencing and alphafold 3 insights into cytokine signaling and its role in uveal melanoma |
| topic | uveal melanoma single-cell RNA sequencing cytokine signaling T cell AlphaFold 3 Dictionary of Immune Responses to Cytokines |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1458041/full |
| work_keys_str_mv | AT hongyansun singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT cunzili singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT zuhuipu singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT zuhuipu singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT yinglu singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT yinglu singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT zijingwu singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT zijingwu singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT lanzhou singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT lanzhou singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT hongzhanlin singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT yumowang singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT taozi singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT lishamou singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT lishamou singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma AT mingmingyang singlecellrnasequencingandalphafold3insightsintocytokinesignalinganditsroleinuvealmelanoma |