Deciphering the role of apoptosis signature on the immune dynamics and therapeutic prognosis in breast cancer: Implication for immunotherapy Article Swipe
Yunfang Yu
,
Xueyuan Jia
,
Sunyu Chen
,
Zijia Lai
,
Heran Deng
,
Yuqian Mo
,
Xinxin Xie
,
Zehua Wang
,
Ruichong Lin
,
Wenhao Ouyang
,
Herui Yao
,
Jiannan Wu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3389/fgene.2024.1332935
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3389/fgene.2024.1332935
Background: In breast cancer oncogenesis, the precise role of cell apoptosis holds untapped potential for prognostic and therapeutic insights. Thus, it is important to develop a model predicated for breast cancer patients’ prognosis and immunotherapy response based on apoptosis-related signature. Methods: Our approach involved leveraging a training dataset from The Cancer Genome Atlas (TCGA) to construct an apoptosis-related gene prognostic model. The model’s validity was then tested across several cohorts, including METABRIC, Sun Yat-sen Memorial Hospital Sun Yat-sen University (SYSMH), and IMvigor210, to ensure its applicability and robustness across different patient demographics and treatment scenarios. Furthermore, we utilized Quantitative Polymerase Chain Reaction (qPCR) analysis to explore the expression patterns of these model genes in breast cancer cell lines compared to immortalized mammary epithelial cell lines, aiming to confirm their differential expression and underline their significance in the context of breast cancer. Results: Through the development and validation of our prognostic model based on seven apoptosis-related genes, we have demonstrated its substantial predictive power for the survival outcomes of breast cancer patients. The model effectively stratified patients into high and low-risk categories, with high-risk patients showing significantly poorer overall survival in the training cohort and across all validation cohorts. Importantly, qPCR analysis confirmed that the genes constituting our model indeed exhibit differential expression in breast cancer cell lines when contrasted with immortalized mammary epithelial cell lines. Conclusion: Our study establishes a groundbreaking prognostic model using apoptosis-related genes to enhance the precision of breast cancer prognosis and treatment, particularly in predicting immunotherapy response.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/fgene.2024.1332935
- OA Status
- gold
- Cited By
- 1
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4396583206
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4396583206Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3389/fgene.2024.1332935Digital Object Identifier
- Title
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Deciphering the role of apoptosis signature on the immune dynamics and therapeutic prognosis in breast cancer: Implication for immunotherapyWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-05-02Full publication date if available
- Authors
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Yunfang Yu, Xueyuan Jia, Sunyu Chen, Zijia Lai, Heran Deng, Yuqian Mo, Xinxin Xie, Zehua Wang, Ruichong Lin, Wenhao Ouyang, Herui Yao, Jiannan WuList of authors in order
- Landing page
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https://doi.org/10.3389/fgene.2024.1332935Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.3389/fgene.2024.1332935Direct OA link when available
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Breast cancer, Oncology, Immunotherapy, Carcinogenesis, Medicine, Cancer, Cancer research, Context (archaeology), Internal medicine, Biology, Bioinformatics, PaleontologyTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.scenarios. | 94 |
| abstract_inverted_index.signature. | 39 |
| abstract_inverted_index.stratified | 174 |
| abstract_inverted_index.treatment, | 245 |
| abstract_inverted_index.validation | 146, 196 |
| abstract_inverted_index.Background: | 0 |
| abstract_inverted_index.Conclusion: | 225 |
| abstract_inverted_index.IMvigor210, | 81 |
| abstract_inverted_index.categories, | 180 |
| abstract_inverted_index.development | 144 |
| abstract_inverted_index.effectively | 173 |
| abstract_inverted_index.establishes | 228 |
| abstract_inverted_index.patients’ | 31 |
| abstract_inverted_index.substantial | 160 |
| abstract_inverted_index.therapeutic | 17 |
| abstract_inverted_index.Furthermore, | 95 |
| abstract_inverted_index.Importantly, | 198 |
| abstract_inverted_index.Quantitative | 98 |
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| abstract_inverted_index.demographics | 91 |
| abstract_inverted_index.demonstrated | 158 |
| abstract_inverted_index.differential | 129, 210 |
| abstract_inverted_index.immortalized | 120, 220 |
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| abstract_inverted_index.significantly | 185 |
| abstract_inverted_index.groundbreaking | 230 |
| abstract_inverted_index.apoptosis-related | 38, 57, 154, 234 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 12 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/1 |
| sustainable_development_goals[0].score | 0.6899999976158142 |
| sustainable_development_goals[0].display_name | No poverty |
| citation_normalized_percentile.value | 0.66244256 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |