Impact of disulfidptosis-associated clusters on breast cancer survival rates and guiding personalized treatment
BackgroundBreast cancer (BC) poses a serious threat to human health. Disulfidptosis is a recently discovered form of cell death associated with cancer prognosis and progression. However, the relationship between BC and disulfidptosis remains unclear.MethodsWe integrated single-cell sequencing and tr...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-12-01
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| Series: | Frontiers in Endocrinology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2023.1256132/full |
| _version_ | 1797404550171197440 |
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| author | Xiong Chen Guohuang Hu Qianle Yu |
| author_facet | Xiong Chen Guohuang Hu Qianle Yu |
| author_sort | Xiong Chen |
| collection | DOAJ |
| description | BackgroundBreast cancer (BC) poses a serious threat to human health. Disulfidptosis is a recently discovered form of cell death associated with cancer prognosis and progression. However, the relationship between BC and disulfidptosis remains unclear.MethodsWe integrated single-cell sequencing and transcriptome sequencing in BC to assess the abundance and mutation status of disulfidptosis-associated genes (DAGs). Subsequently, we clustered the samples based on DAGs and constructed a prognostic model associated with disulfidptosis. Additionally, we performed pathway enrichment, immune response, and drug sensitivity analyses on the model. Finally, we validated the prognostic genes through Immunohistochemistry (IHC).ResultsThe single-cell analysis identified 21 cell clusters and 8 cell types. By evaluating the abundance of DAGs in different cell types, we found specific expression of the disulfidoptosis core gene SLC7A11 in mesenchymal stem cells (MSCs). Through unsupervised clustering of DAGs, we identified two clusters. Utilizing differentially expressed genes from these clusters, we selected 7 genes (AFF4, SLC7A11, IGKC, IL6ST, LIMD2, MAT2B, and SCAND1) through Cox and Lasso regression to construct a prognostic model. External validation demonstrated good prognostic prediction of our model. BC patients were stratified into two groups based on riskscore, with the high-risk group corresponding to a worse prognosis. Immune response analysis revealed higher TMB and lower TIDE scores in the high-risk group, while the low-risk group exhibited higher CTLA4/PD-1 expression. This suggests that both groups may respond to immunotherapy, necessitating further research to elucidate potential mechanisms. Drug sensitivity analysis indicated that dasatinib, docetaxel, lapatinib, methotrexate, paclitaxel, and sunitinib may have better efficacy in the low-risk group. Finally, Immunohistochemistry (IHC) validated the expression of prognostic genes, demonstrating higher levels in tumor tissue compared to normal tissue.ConclusionOur study has developed an effective disulfidptosis-related prognostic prediction tool for BC and provides personalized guidance for the clinical management and immunotherapy selection of BC patients. |
| first_indexed | 2024-03-09T02:56:38Z |
| format | Article |
| id | doaj.art-f95294a8776942efb6fd9dffb68fcb78 |
| institution | Directory Open Access Journal |
| issn | 1664-2392 |
| language | English |
| last_indexed | 2024-03-09T02:56:38Z |
| publishDate | 2023-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Endocrinology |
| spelling | doaj.art-f95294a8776942efb6fd9dffb68fcb782023-12-05T04:42:36ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922023-12-011410.3389/fendo.2023.12561321256132Impact of disulfidptosis-associated clusters on breast cancer survival rates and guiding personalized treatmentXiong ChenGuohuang HuQianle YuBackgroundBreast cancer (BC) poses a serious threat to human health. Disulfidptosis is a recently discovered form of cell death associated with cancer prognosis and progression. However, the relationship between BC and disulfidptosis remains unclear.MethodsWe integrated single-cell sequencing and transcriptome sequencing in BC to assess the abundance and mutation status of disulfidptosis-associated genes (DAGs). Subsequently, we clustered the samples based on DAGs and constructed a prognostic model associated with disulfidptosis. Additionally, we performed pathway enrichment, immune response, and drug sensitivity analyses on the model. Finally, we validated the prognostic genes through Immunohistochemistry (IHC).ResultsThe single-cell analysis identified 21 cell clusters and 8 cell types. By evaluating the abundance of DAGs in different cell types, we found specific expression of the disulfidoptosis core gene SLC7A11 in mesenchymal stem cells (MSCs). Through unsupervised clustering of DAGs, we identified two clusters. Utilizing differentially expressed genes from these clusters, we selected 7 genes (AFF4, SLC7A11, IGKC, IL6ST, LIMD2, MAT2B, and SCAND1) through Cox and Lasso regression to construct a prognostic model. External validation demonstrated good prognostic prediction of our model. BC patients were stratified into two groups based on riskscore, with the high-risk group corresponding to a worse prognosis. Immune response analysis revealed higher TMB and lower TIDE scores in the high-risk group, while the low-risk group exhibited higher CTLA4/PD-1 expression. This suggests that both groups may respond to immunotherapy, necessitating further research to elucidate potential mechanisms. Drug sensitivity analysis indicated that dasatinib, docetaxel, lapatinib, methotrexate, paclitaxel, and sunitinib may have better efficacy in the low-risk group. Finally, Immunohistochemistry (IHC) validated the expression of prognostic genes, demonstrating higher levels in tumor tissue compared to normal tissue.ConclusionOur study has developed an effective disulfidptosis-related prognostic prediction tool for BC and provides personalized guidance for the clinical management and immunotherapy selection of BC patients.https://www.frontiersin.org/articles/10.3389/fendo.2023.1256132/fullbreast cancerdisulfidptosissingle-cellimmunotherapyprognosis |
| spellingShingle | Xiong Chen Guohuang Hu Qianle Yu Impact of disulfidptosis-associated clusters on breast cancer survival rates and guiding personalized treatment Frontiers in Endocrinology breast cancer disulfidptosis single-cell immunotherapy prognosis |
| title | Impact of disulfidptosis-associated clusters on breast cancer survival rates and guiding personalized treatment |
| title_full | Impact of disulfidptosis-associated clusters on breast cancer survival rates and guiding personalized treatment |
| title_fullStr | Impact of disulfidptosis-associated clusters on breast cancer survival rates and guiding personalized treatment |
| title_full_unstemmed | Impact of disulfidptosis-associated clusters on breast cancer survival rates and guiding personalized treatment |
| title_short | Impact of disulfidptosis-associated clusters on breast cancer survival rates and guiding personalized treatment |
| title_sort | impact of disulfidptosis associated clusters on breast cancer survival rates and guiding personalized treatment |
| topic | breast cancer disulfidptosis single-cell immunotherapy prognosis |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2023.1256132/full |
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