Functional Gene Expression Signatures from On-Treatment Tumor Specimens Predict Anti-PD1 Blockade Response in Metastatic Melanoma
Functional gene expression signatures (FGES) from pretreatment biopsy samples have been used to predict the responses of metastatic melanoma to immune checkpoint blockade (ICB) therapies. However, there are no predictive FGE signatures from patients receiving treatment. Here, using the Elastic Net R...
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MDPI AG
2022-12-01
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| Online Access: | https://www.mdpi.com/2218-273X/13/1/58 |
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| author | Shuzhao Chen Limei Zhang Haocheng Lin Yang Liang Yun Wang |
| author_facet | Shuzhao Chen Limei Zhang Haocheng Lin Yang Liang Yun Wang |
| author_sort | Shuzhao Chen |
| collection | DOAJ |
| description | Functional gene expression signatures (FGES) from pretreatment biopsy samples have been used to predict the responses of metastatic melanoma to immune checkpoint blockade (ICB) therapies. However, there are no predictive FGE signatures from patients receiving treatment. Here, using the Elastic Net Regression (ENLR) algorithm, we analyzed transcriptomic and matching clinical data from a dataset of patients with metastatic melanoma treated with ICB therapies and produced an FGE signature for pretreatment (FGES-PRE) and on-treatment (FGES-ON). Both the FGES-PRE and FGES-ON signatures are validated in three independent datasets of metastatic melanoma as the validation set, achieving area under the curve (AUC) values of 0.44–0.81 and 0.82–0.83, respectively. Then, we combined all test samples and obtained AUCs of 0.71 and 0.82 for the FGES-PRE and FGES-ON signatures, respectively. The FGES-ON signatures had a higher predictive value for prognosis than the FGES-PRE signatures. The FGES-PRE and FGES-ON signatures were divided into high- and low-risk scores using the signature score mean value. Patients with a high FGE signature score had better survival outcomes than those with low scores. Overall, we determined that the FGES-ON signature is an effective biomarker for metastatic melanoma patients receiving ICB therapy. This work would provide an important theoretical basis for applying FGE signatures derived from on-treatment tumor samples to predict patients’ therapeutic response to ICB therapies. |
| first_indexed | 2024-03-09T13:27:26Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2218-273X |
| language | English |
| last_indexed | 2024-03-09T13:27:26Z |
| publishDate | 2022-12-01 |
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| spelling | doaj.art-9678c6be233b493d8ffc3699f2555e5f2023-11-30T21:22:08ZengMDPI AGBiomolecules2218-273X2022-12-011315810.3390/biom13010058Functional Gene Expression Signatures from On-Treatment Tumor Specimens Predict Anti-PD1 Blockade Response in Metastatic MelanomaShuzhao Chen0Limei Zhang1Haocheng Lin2Yang Liang3Yun Wang4Department of Hematologic Oncology, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, ChinaDepartment of Hematologic Oncology, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, ChinaDepartment of Oncology, The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen 518033, ChinaDepartment of Hematologic Oncology, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, ChinaDepartment of Hematologic Oncology, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, ChinaFunctional gene expression signatures (FGES) from pretreatment biopsy samples have been used to predict the responses of metastatic melanoma to immune checkpoint blockade (ICB) therapies. However, there are no predictive FGE signatures from patients receiving treatment. Here, using the Elastic Net Regression (ENLR) algorithm, we analyzed transcriptomic and matching clinical data from a dataset of patients with metastatic melanoma treated with ICB therapies and produced an FGE signature for pretreatment (FGES-PRE) and on-treatment (FGES-ON). Both the FGES-PRE and FGES-ON signatures are validated in three independent datasets of metastatic melanoma as the validation set, achieving area under the curve (AUC) values of 0.44–0.81 and 0.82–0.83, respectively. Then, we combined all test samples and obtained AUCs of 0.71 and 0.82 for the FGES-PRE and FGES-ON signatures, respectively. The FGES-ON signatures had a higher predictive value for prognosis than the FGES-PRE signatures. The FGES-PRE and FGES-ON signatures were divided into high- and low-risk scores using the signature score mean value. Patients with a high FGE signature score had better survival outcomes than those with low scores. Overall, we determined that the FGES-ON signature is an effective biomarker for metastatic melanoma patients receiving ICB therapy. This work would provide an important theoretical basis for applying FGE signatures derived from on-treatment tumor samples to predict patients’ therapeutic response to ICB therapies.https://www.mdpi.com/2218-273X/13/1/58functional gene expression signatureson-treatment tumor specimensanti-PD1 blockade responsemetastatic melanoma |
| spellingShingle | Shuzhao Chen Limei Zhang Haocheng Lin Yang Liang Yun Wang Functional Gene Expression Signatures from On-Treatment Tumor Specimens Predict Anti-PD1 Blockade Response in Metastatic Melanoma Biomolecules functional gene expression signatures on-treatment tumor specimens anti-PD1 blockade response metastatic melanoma |
| title | Functional Gene Expression Signatures from On-Treatment Tumor Specimens Predict Anti-PD1 Blockade Response in Metastatic Melanoma |
| title_full | Functional Gene Expression Signatures from On-Treatment Tumor Specimens Predict Anti-PD1 Blockade Response in Metastatic Melanoma |
| title_fullStr | Functional Gene Expression Signatures from On-Treatment Tumor Specimens Predict Anti-PD1 Blockade Response in Metastatic Melanoma |
| title_full_unstemmed | Functional Gene Expression Signatures from On-Treatment Tumor Specimens Predict Anti-PD1 Blockade Response in Metastatic Melanoma |
| title_short | Functional Gene Expression Signatures from On-Treatment Tumor Specimens Predict Anti-PD1 Blockade Response in Metastatic Melanoma |
| title_sort | functional gene expression signatures from on treatment tumor specimens predict anti pd1 blockade response in metastatic melanoma |
| topic | functional gene expression signatures on-treatment tumor specimens anti-PD1 blockade response metastatic melanoma |
| url | https://www.mdpi.com/2218-273X/13/1/58 |
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