Establishment of a lysosome-related prognostic signature in breast cancer to predict immune infiltration and therapy response
BackgroundLysosomes are instrumental in intracellular degradation and recycling, with their functional alterations holding significance in tumor growth. Nevertheless, the precise role of lysosome-related genes (LRGs) in breast cancer (BC) remains elucidated. This study aimed to establish a prognosti...
| Main Authors: | , , , , , , , , , , |
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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 Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2023.1325452/full |
| _version_ | 1797391177623797760 |
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| author | Hairong Su Hairong Su Ying Chen Ying Chen Fengye Lin Wanhua Li Xiangyu Gu Weijie Zeng Weijie Zeng Dan Liu Dan Liu Man Li Man Li Shaowen Zhong Shaowen Zhong Qianjun Chen Qianjun Chen Qubo Chen Qubo Chen |
| author_facet | Hairong Su Hairong Su Ying Chen Ying Chen Fengye Lin Wanhua Li Xiangyu Gu Weijie Zeng Weijie Zeng Dan Liu Dan Liu Man Li Man Li Shaowen Zhong Shaowen Zhong Qianjun Chen Qianjun Chen Qubo Chen Qubo Chen |
| author_sort | Hairong Su |
| collection | DOAJ |
| description | BackgroundLysosomes are instrumental in intracellular degradation and recycling, with their functional alterations holding significance in tumor growth. Nevertheless, the precise role of lysosome-related genes (LRGs) in breast cancer (BC) remains elucidated. This study aimed to establish a prognostic model for BC based on LRGs.MethodsEmploying The Cancer Genome Atlas (TCGA) BC cohort as a training dataset, this study identified differentially expressed lysosome-related genes (DLRGs) through intersecting LRGs with differential expression genes (DEGs) between tumor and normal samples. A prognostic model of BC was subsequently developed using Cox regression analysis and validated within two Gene Expression Omnibus (GEO) external validation sets. Further analyses explored functional pathways, the immune microenvironment, immunotherapeutic responses, and sensitivity to chemotherapeutic drugs in different risk groups. Additionally, the mRNA and protein expression levels of genes within the risk model were examined by utilizing the Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases. Clinical tissue specimens obtained from patients were gathered to validate the expression of the model genes via Real-Time Polymerase Chain Reaction (RT-PCR).ResultsWe developed a risk model of BC based on five specific genes (ATP6AP1, SLC7A5, EPDR1, SDC1, and PIGR). The model was validated for overall survival (OS) in two GEO validation sets (p=0.00034 for GSE20685 and p=0.0095 for GSE58812). In addition, the nomogram incorporating clinical factors showed better predictive performance. Compared to the low-risk group, the high-risk group had a higher level of certain immune cell infiltration, including regulatory T cells (Tregs) and type 2 T helper cells (Th2). The high-risk patients appeared to respond less well to general immunotherapy and chemotherapeutic drugs, according to the Tumor Immune Dysfunction and Exclusion (TIDE), Immunophenotype Score (IPS), and drug sensitivity scores. The RT-PCR results validated the expression trends of some prognostic-related genes in agreement with the previous differential expression analysis.ConclusionOur innovative lysosome-associated signature can predict the prognosis for BC patients, offering insights for guiding subsequent immunotherapeutic and chemotherapeutic interventions. Furthermore, it has the potential to provide a scientific foundation for identifying prospective therapeutic targets. |
| first_indexed | 2024-03-08T23:29:14Z |
| format | Article |
| id | doaj.art-ce38bbdfb091442b97731840631be339 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-03-08T23:29:14Z |
| publishDate | 2023-12-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Oncology |
| spelling | doaj.art-ce38bbdfb091442b97731840631be3392023-12-14T16:49:11ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2023-12-011310.3389/fonc.2023.13254521325452Establishment of a lysosome-related prognostic signature in breast cancer to predict immune infiltration and therapy responseHairong Su0Hairong Su1Ying Chen2Ying Chen3Fengye Lin4Wanhua Li5Xiangyu Gu6Weijie Zeng7Weijie Zeng8Dan Liu9Dan Liu10Man Li11Man Li12Shaowen Zhong13Shaowen Zhong14Qianjun Chen15Qianjun Chen16Qubo Chen17Qubo Chen18Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, ChinaState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, ChinaSecond Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, ChinaState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, ChinaSecond Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, ChinaSecond Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, ChinaSecond Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, ChinaSecond Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, ChinaDepartment of Breast, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, ChinaSecond Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, ChinaDepartment of Breast, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, ChinaSecond Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, ChinaState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, ChinaSecond Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, ChinaDepartment of Breast, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, ChinaSecond Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, ChinaDepartment of Breast, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, ChinaSecond Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, ChinaState Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, ChinaBackgroundLysosomes are instrumental in intracellular degradation and recycling, with their functional alterations holding significance in tumor growth. Nevertheless, the precise role of lysosome-related genes (LRGs) in breast cancer (BC) remains elucidated. This study aimed to establish a prognostic model for BC based on LRGs.MethodsEmploying The Cancer Genome Atlas (TCGA) BC cohort as a training dataset, this study identified differentially expressed lysosome-related genes (DLRGs) through intersecting LRGs with differential expression genes (DEGs) between tumor and normal samples. A prognostic model of BC was subsequently developed using Cox regression analysis and validated within two Gene Expression Omnibus (GEO) external validation sets. Further analyses explored functional pathways, the immune microenvironment, immunotherapeutic responses, and sensitivity to chemotherapeutic drugs in different risk groups. Additionally, the mRNA and protein expression levels of genes within the risk model were examined by utilizing the Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases. Clinical tissue specimens obtained from patients were gathered to validate the expression of the model genes via Real-Time Polymerase Chain Reaction (RT-PCR).ResultsWe developed a risk model of BC based on five specific genes (ATP6AP1, SLC7A5, EPDR1, SDC1, and PIGR). The model was validated for overall survival (OS) in two GEO validation sets (p=0.00034 for GSE20685 and p=0.0095 for GSE58812). In addition, the nomogram incorporating clinical factors showed better predictive performance. Compared to the low-risk group, the high-risk group had a higher level of certain immune cell infiltration, including regulatory T cells (Tregs) and type 2 T helper cells (Th2). The high-risk patients appeared to respond less well to general immunotherapy and chemotherapeutic drugs, according to the Tumor Immune Dysfunction and Exclusion (TIDE), Immunophenotype Score (IPS), and drug sensitivity scores. The RT-PCR results validated the expression trends of some prognostic-related genes in agreement with the previous differential expression analysis.ConclusionOur innovative lysosome-associated signature can predict the prognosis for BC patients, offering insights for guiding subsequent immunotherapeutic and chemotherapeutic interventions. Furthermore, it has the potential to provide a scientific foundation for identifying prospective therapeutic targets.https://www.frontiersin.org/articles/10.3389/fonc.2023.1325452/fulllysosomebreast cancerprognosisimmune infiltrationimmunotherapychemotherapeutic drug sensitivity |
| spellingShingle | Hairong Su Hairong Su Ying Chen Ying Chen Fengye Lin Wanhua Li Xiangyu Gu Weijie Zeng Weijie Zeng Dan Liu Dan Liu Man Li Man Li Shaowen Zhong Shaowen Zhong Qianjun Chen Qianjun Chen Qubo Chen Qubo Chen Establishment of a lysosome-related prognostic signature in breast cancer to predict immune infiltration and therapy response Frontiers in Oncology lysosome breast cancer prognosis immune infiltration immunotherapy chemotherapeutic drug sensitivity |
| title | Establishment of a lysosome-related prognostic signature in breast cancer to predict immune infiltration and therapy response |
| title_full | Establishment of a lysosome-related prognostic signature in breast cancer to predict immune infiltration and therapy response |
| title_fullStr | Establishment of a lysosome-related prognostic signature in breast cancer to predict immune infiltration and therapy response |
| title_full_unstemmed | Establishment of a lysosome-related prognostic signature in breast cancer to predict immune infiltration and therapy response |
| title_short | Establishment of a lysosome-related prognostic signature in breast cancer to predict immune infiltration and therapy response |
| title_sort | establishment of a lysosome related prognostic signature in breast cancer to predict immune infiltration and therapy response |
| topic | lysosome breast cancer prognosis immune infiltration immunotherapy chemotherapeutic drug sensitivity |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2023.1325452/full |
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