Data Sheet 1_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.docx
Background<p>Regulatory B cells (Bregs) are a distinct subset of B cells that play a crucial role in regulating immune responses and maintaining immune tolerance in cancerous environments. However, their function in lung adenocarcinoma (LUAD) remains largely underexplored. This study seeks to...
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2025
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| _version_ | 1852018099085115392 |
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| author | Liangyu Zhang (8947964) |
| author2 | Jianshen Zeng (18557484) Xun Zhang (113378) Menglong Zhang (4743870) Yilin Lin (6235856) Fancai Lai (11616127) |
| author2_role | author author author author author |
| author_facet | Liangyu Zhang (8947964) Jianshen Zeng (18557484) Xun Zhang (113378) Menglong Zhang (4743870) Yilin Lin (6235856) Fancai Lai (11616127) |
| author_role | author |
| dc.creator.none.fl_str_mv | Liangyu Zhang (8947964) Jianshen Zeng (18557484) Xun Zhang (113378) Menglong Zhang (4743870) Yilin Lin (6235856) Fancai Lai (11616127) |
| dc.date.none.fl_str_mv | 2025-07-30T05:25:54Z |
| dc.identifier.none.fl_str_mv | 10.3389/fimmu.2025.1595408.s001 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Data_Sheet_1_Comprehensive_analysis_of_regulatory_B_Cell_related_genes_in_prognosis_and_therapeutic_response_in_lung_adenocarcinoma_docx/29671904 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Genetic Immunology Breg LUAD artificial intelligence prognostic model immune |
| dc.title.none.fl_str_mv | Data Sheet 1_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.docx |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | Background<p>Regulatory B cells (Bregs) are a distinct subset of B cells that play a crucial role in regulating immune responses and maintaining immune tolerance in cancerous environments. However, their function in lung adenocarcinoma (LUAD) remains largely underexplored. This study seeks to investigate the roles of Breg-associated genes in the context of LUAD.</p>Methods<p>ConsensusClusterPlus package was used to characterize LUAD patients into two clusters. Differentially expressed genes between the two clusters were then used to construct the BREGI using 32 algorithms, including traditional regression, machine learning, deep learning, and 274 different combinations. The training set, TCGA-LUAD, along with SNV and CNV data, was obtained from the TCGA database. Seven external validation sets and one single-cell RNA sequencing set were downloaded from GEO. Data from the TIDE, TCIA, and TIGER websites were curated to assess the effectiveness of immunotherapy.</p>Results<p>LUAD patients were divided into two clusters based on 27 Breg-related genes. Patients in Cluster C1 exhibited better prognosis, along with higher immune cell infiltration and immune molecule expression levels, displaying characteristics of a “hot immune” phenotype. The BREGI demonstrated robust predictive power for LUAD patient prognosis across various cohorts. Patients with high BREGI were associated with poor prognosis, higher gene mutation frequencies, a “cold immune” phenotype, and potential resistance to immunotherapy.</p>Conclusions<p>Breg-related genes significantly characterize LUAD patients into distinct clusters, and the BREGI demonstrated strong prognostic value, providing new insights for future research on Bregs.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_b7730a45a3bc2b4a5f4e71ba2bfeadd6 |
| identifier_str_mv | 10.3389/fimmu.2025.1595408.s001 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29671904 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Data Sheet 1_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.docxLiangyu Zhang (8947964)Jianshen Zeng (18557484)Xun Zhang (113378)Menglong Zhang (4743870)Yilin Lin (6235856)Fancai Lai (11616127)Genetic ImmunologyBregLUADartificial intelligenceprognostic modelimmuneBackground<p>Regulatory B cells (Bregs) are a distinct subset of B cells that play a crucial role in regulating immune responses and maintaining immune tolerance in cancerous environments. However, their function in lung adenocarcinoma (LUAD) remains largely underexplored. This study seeks to investigate the roles of Breg-associated genes in the context of LUAD.</p>Methods<p>ConsensusClusterPlus package was used to characterize LUAD patients into two clusters. Differentially expressed genes between the two clusters were then used to construct the BREGI using 32 algorithms, including traditional regression, machine learning, deep learning, and 274 different combinations. The training set, TCGA-LUAD, along with SNV and CNV data, was obtained from the TCGA database. Seven external validation sets and one single-cell RNA sequencing set were downloaded from GEO. Data from the TIDE, TCIA, and TIGER websites were curated to assess the effectiveness of immunotherapy.</p>Results<p>LUAD patients were divided into two clusters based on 27 Breg-related genes. Patients in Cluster C1 exhibited better prognosis, along with higher immune cell infiltration and immune molecule expression levels, displaying characteristics of a “hot immune” phenotype. The BREGI demonstrated robust predictive power for LUAD patient prognosis across various cohorts. Patients with high BREGI were associated with poor prognosis, higher gene mutation frequencies, a “cold immune” phenotype, and potential resistance to immunotherapy.</p>Conclusions<p>Breg-related genes significantly characterize LUAD patients into distinct clusters, and the BREGI demonstrated strong prognostic value, providing new insights for future research on Bregs.</p>2025-07-30T05:25:54ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.3389/fimmu.2025.1595408.s001https://figshare.com/articles/dataset/Data_Sheet_1_Comprehensive_analysis_of_regulatory_B_Cell_related_genes_in_prognosis_and_therapeutic_response_in_lung_adenocarcinoma_docx/29671904CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/296719042025-07-30T05:25:54Z |
| spellingShingle | Data Sheet 1_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.docx Liangyu Zhang (8947964) Genetic Immunology Breg LUAD artificial intelligence prognostic model immune |
| status_str | publishedVersion |
| title | Data Sheet 1_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.docx |
| title_full | Data Sheet 1_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.docx |
| title_fullStr | Data Sheet 1_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.docx |
| title_full_unstemmed | Data Sheet 1_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.docx |
| title_short | Data Sheet 1_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.docx |
| title_sort | Data Sheet 1_Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma.docx |
| topic | Genetic Immunology Breg LUAD artificial intelligence prognostic model immune |