Suppressive stroma-immune prognostic signature impedes immunotherapy in ovarian cancer and can be reversed by PDGFRB inhibitors
Abstract Background As the most lethal gynecologic cancer, ovarian cancer (OV) holds the potential of being immunotherapy-responsive. However, only modest therapeutic effects have been achieved by immunotherapies such as immune checkpoint blockade. This study aims to propose a generalized stroma-imm...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-09-01
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| Series: | Journal of Translational Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12967-023-04422-x |
| _version_ | 1797451690846191616 |
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| author | Dong Yang Mei-Han Duan Qiu-Er Yuan Zhi-Ling Li Chuang-Hua Luo Lan-Yue Cui Li-Chao Li Ying Xiao Xian-Ying Zhu Hai-Liang Zhang Gong-Kan Feng Guo-Chen Liu Rong Deng Jun-Dong Li Xiao-Feng Zhu |
| author_facet | Dong Yang Mei-Han Duan Qiu-Er Yuan Zhi-Ling Li Chuang-Hua Luo Lan-Yue Cui Li-Chao Li Ying Xiao Xian-Ying Zhu Hai-Liang Zhang Gong-Kan Feng Guo-Chen Liu Rong Deng Jun-Dong Li Xiao-Feng Zhu |
| author_sort | Dong Yang |
| collection | DOAJ |
| description | Abstract Background As the most lethal gynecologic cancer, ovarian cancer (OV) holds the potential of being immunotherapy-responsive. However, only modest therapeutic effects have been achieved by immunotherapies such as immune checkpoint blockade. This study aims to propose a generalized stroma-immune prognostic signature (SIPS) to identify OV patients who may benefit from immunotherapy. Methods The 2097 OV patients included in the study were significant with high-grade serous ovarian cancer in the III/IV stage. The 470 immune-related signatures were collected and analyzed by the Cox regression and Lasso algorithm to generalize a credible SIPS. Correlations between the SIPS signature and tumor microenvironment were further analyzed. The critical immunosuppressive role of stroma indicated by the SIPS was further validated by targeting the major suppressive stroma component (CAFs, Cancer-associated fibroblasts) in vitro and in vivo. With four machine-learning methods predicting tumor immune subtypes, the stroma-immune signature was upgraded to a 23-gene signature. Results The SIPS effectively discriminated the high-risk individuals in the training and validating cohorts, where the high SIPS succeeded in predicting worse survival in several immunotherapy cohorts. The SIPS signature was positively correlated with stroma components, especially CAFs and immunosuppressive cells in the tumor microenvironment, indicating the critical suppressive stroma-immune network. The combination of CAFs’ marker PDGFRB inhibitors and frontline PARP inhibitors substantially inhibited tumor growth and promoted the survival of OV-bearing mice. The stroma-immune signature was upgraded to a 23-gene signature to improve clinical utility. Several drug types that suppress stroma-immune signatures, such as EGFR inhibitors, could be candidates for potential immunotherapeutic combinations in ovarian cancer. Conclusions The stroma-immune signature could efficiently predict the immunotherapeutic sensitivity of OV patients. Immunotherapy and auxiliary drugs targeting stroma could enhance immunotherapeutic efficacy in ovarian cancer. |
| first_indexed | 2024-03-09T14:58:10Z |
| format | Article |
| id | doaj.art-737309b875aa4eac9816f33c5500285a |
| institution | Directory Open Access Journal |
| issn | 1479-5876 |
| language | English |
| last_indexed | 2024-03-09T14:58:10Z |
| publishDate | 2023-09-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj.art-737309b875aa4eac9816f33c5500285a2023-11-26T14:04:37ZengBMCJournal of Translational Medicine1479-58762023-09-0121111610.1186/s12967-023-04422-xSuppressive stroma-immune prognostic signature impedes immunotherapy in ovarian cancer and can be reversed by PDGFRB inhibitorsDong Yang0Mei-Han Duan1Qiu-Er Yuan2Zhi-Ling Li3Chuang-Hua Luo4Lan-Yue Cui5Li-Chao Li6Ying Xiao7Xian-Ying Zhu8Hai-Liang Zhang9Gong-Kan Feng10Guo-Chen Liu11Rong Deng12Jun-Dong Li13Xiao-Feng Zhu14State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterDepartment of Gynecological Oncology, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterDepartment of Gynecological Oncology, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer CenterAbstract Background As the most lethal gynecologic cancer, ovarian cancer (OV) holds the potential of being immunotherapy-responsive. However, only modest therapeutic effects have been achieved by immunotherapies such as immune checkpoint blockade. This study aims to propose a generalized stroma-immune prognostic signature (SIPS) to identify OV patients who may benefit from immunotherapy. Methods The 2097 OV patients included in the study were significant with high-grade serous ovarian cancer in the III/IV stage. The 470 immune-related signatures were collected and analyzed by the Cox regression and Lasso algorithm to generalize a credible SIPS. Correlations between the SIPS signature and tumor microenvironment were further analyzed. The critical immunosuppressive role of stroma indicated by the SIPS was further validated by targeting the major suppressive stroma component (CAFs, Cancer-associated fibroblasts) in vitro and in vivo. With four machine-learning methods predicting tumor immune subtypes, the stroma-immune signature was upgraded to a 23-gene signature. Results The SIPS effectively discriminated the high-risk individuals in the training and validating cohorts, where the high SIPS succeeded in predicting worse survival in several immunotherapy cohorts. The SIPS signature was positively correlated with stroma components, especially CAFs and immunosuppressive cells in the tumor microenvironment, indicating the critical suppressive stroma-immune network. The combination of CAFs’ marker PDGFRB inhibitors and frontline PARP inhibitors substantially inhibited tumor growth and promoted the survival of OV-bearing mice. The stroma-immune signature was upgraded to a 23-gene signature to improve clinical utility. Several drug types that suppress stroma-immune signatures, such as EGFR inhibitors, could be candidates for potential immunotherapeutic combinations in ovarian cancer. Conclusions The stroma-immune signature could efficiently predict the immunotherapeutic sensitivity of OV patients. Immunotherapy and auxiliary drugs targeting stroma could enhance immunotherapeutic efficacy in ovarian cancer.https://doi.org/10.1186/s12967-023-04422-xOvarian cancerImmunotherapyStromaPrognostic signature |
| spellingShingle | Dong Yang Mei-Han Duan Qiu-Er Yuan Zhi-Ling Li Chuang-Hua Luo Lan-Yue Cui Li-Chao Li Ying Xiao Xian-Ying Zhu Hai-Liang Zhang Gong-Kan Feng Guo-Chen Liu Rong Deng Jun-Dong Li Xiao-Feng Zhu Suppressive stroma-immune prognostic signature impedes immunotherapy in ovarian cancer and can be reversed by PDGFRB inhibitors Journal of Translational Medicine Ovarian cancer Immunotherapy Stroma Prognostic signature |
| title | Suppressive stroma-immune prognostic signature impedes immunotherapy in ovarian cancer and can be reversed by PDGFRB inhibitors |
| title_full | Suppressive stroma-immune prognostic signature impedes immunotherapy in ovarian cancer and can be reversed by PDGFRB inhibitors |
| title_fullStr | Suppressive stroma-immune prognostic signature impedes immunotherapy in ovarian cancer and can be reversed by PDGFRB inhibitors |
| title_full_unstemmed | Suppressive stroma-immune prognostic signature impedes immunotherapy in ovarian cancer and can be reversed by PDGFRB inhibitors |
| title_short | Suppressive stroma-immune prognostic signature impedes immunotherapy in ovarian cancer and can be reversed by PDGFRB inhibitors |
| title_sort | suppressive stroma immune prognostic signature impedes immunotherapy in ovarian cancer and can be reversed by pdgfrb inhibitors |
| topic | Ovarian cancer Immunotherapy Stroma Prognostic signature |
| url | https://doi.org/10.1186/s12967-023-04422-x |
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