Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancer
The tumor microenvironment (TME) plays a crucial role in tumor progression and immunoregulation. Major histocompatibility complex class II (MHC-II) is essential for immune surveillance within the TME. While MHC-II genes are typically expressed by professional antigen-presenting cells, they are also...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-11-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1497251/full |
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| author | Yang Cui Weihang Zhang Xin Zeng Yitao Yang Sung-Joon Park Kenta Nakai Kenta Nakai |
| author_facet | Yang Cui Weihang Zhang Xin Zeng Yitao Yang Sung-Joon Park Kenta Nakai Kenta Nakai |
| author_sort | Yang Cui |
| collection | DOAJ |
| description | The tumor microenvironment (TME) plays a crucial role in tumor progression and immunoregulation. Major histocompatibility complex class II (MHC-II) is essential for immune surveillance within the TME. While MHC-II genes are typically expressed by professional antigen-presenting cells, they are also expressed in tumor cells, potentially facilitating antitumor immune responses. To understand the role of MHC-II-expressing tumor cells, we analyzed triple-negative breast cancer (TNBC), an aggressive subtype with poor prognosis and limited treatment options, using public bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics datasets. Our analysis revealed a distinct tumor subpopulation that upregulates MHC-II genes and actively interacts with immune cells. We implicated that this subpopulation is preferentially present in proximity to regions in immune infiltration of TNBC patient cohorts with a better prognosis, suggesting the functional importance of MHC-II-expressing tumor cells in modulating the immune landscape and influencing patient survival outcomes. Remarkably, we identified a prognostic signature comprising 40 significant genes in the MHC-II-expressing tumors in which machine leaning models with the signature successfully predicted patient survival outcomes and the degree of immune infiltration. This study advances our understanding of the immunological basis of cancer progression and suggests promising new directions for therapeutic strategies. |
| format | Article |
| id | doaj-art-cb09e89bbe7f4e75982285fbd8bcbce3 |
| institution | Kabale University |
| issn | 1664-3224 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj-art-cb09e89bbe7f4e75982285fbd8bcbce32024-11-27T06:33:09ZengFrontiers Media S.A.Frontiers in Immunology1664-32242024-11-011510.3389/fimmu.2024.14972511497251Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancerYang Cui0Weihang Zhang1Xin Zeng2Yitao Yang3Sung-Joon Park4Kenta Nakai5Kenta Nakai6Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, JapanDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, JapanDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, JapanDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, JapanHuman Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, JapanDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, JapanHuman Genome Center, Institute of Medical Science, University of Tokyo, Tokyo, JapanThe tumor microenvironment (TME) plays a crucial role in tumor progression and immunoregulation. Major histocompatibility complex class II (MHC-II) is essential for immune surveillance within the TME. While MHC-II genes are typically expressed by professional antigen-presenting cells, they are also expressed in tumor cells, potentially facilitating antitumor immune responses. To understand the role of MHC-II-expressing tumor cells, we analyzed triple-negative breast cancer (TNBC), an aggressive subtype with poor prognosis and limited treatment options, using public bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics datasets. Our analysis revealed a distinct tumor subpopulation that upregulates MHC-II genes and actively interacts with immune cells. We implicated that this subpopulation is preferentially present in proximity to regions in immune infiltration of TNBC patient cohorts with a better prognosis, suggesting the functional importance of MHC-II-expressing tumor cells in modulating the immune landscape and influencing patient survival outcomes. Remarkably, we identified a prognostic signature comprising 40 significant genes in the MHC-II-expressing tumors in which machine leaning models with the signature successfully predicted patient survival outcomes and the degree of immune infiltration. This study advances our understanding of the immunological basis of cancer progression and suggests promising new directions for therapeutic strategies.https://www.frontiersin.org/articles/10.3389/fimmu.2024.1497251/fullbreast cancermachine learningMHC-II pathwaymulti-omics data integrationtumor microenvironment |
| spellingShingle | Yang Cui Weihang Zhang Xin Zeng Yitao Yang Sung-Joon Park Kenta Nakai Kenta Nakai Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancer Frontiers in Immunology breast cancer machine learning MHC-II pathway multi-omics data integration tumor microenvironment |
| title | Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancer |
| title_full | Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancer |
| title_fullStr | Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancer |
| title_full_unstemmed | Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancer |
| title_short | Computational analysis of the functional impact of MHC-II-expressing triple-negative breast cancer |
| title_sort | computational analysis of the functional impact of mhc ii expressing triple negative breast cancer |
| topic | breast cancer machine learning MHC-II pathway multi-omics data integration tumor microenvironment |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1497251/full |
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