Development and validation of a genomic mutation signature to predict response to PD-1 inhibitors in non-squamous NSCLC: a multicohort study
Background Genetic variations of some driver genes in non-small cell lung cancer (NSCLC) had shown potential impact on immune microenvironment and associated with response or resistance to programmed cell death protein 1 (PD-1) blockade immunotherapy. We therefore undertook an exploratory analysis t...
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BMJ Publishing Group
2020-05-01
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| Series: | Journal for ImmunoTherapy of Cancer |
| Online Access: | https://jitc.bmj.com/content/8/1/e000381.full |
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| author | Jian Wang Yi-Long Wu Xue Bai De-Hua Wu Si-Cong Ma Xin-Ran Tang Shuai Kang Qiang John Fu Chuan-Hui Cao He-San Luo Yu-Han Chen Hong-Bo Zhu Hong-Hong Yan Zhong-Yi Dong |
| author_facet | Jian Wang Yi-Long Wu Xue Bai De-Hua Wu Si-Cong Ma Xin-Ran Tang Shuai Kang Qiang John Fu Chuan-Hui Cao He-San Luo Yu-Han Chen Hong-Bo Zhu Hong-Hong Yan Zhong-Yi Dong |
| author_sort | Jian Wang |
| collection | DOAJ |
| description | Background Genetic variations of some driver genes in non-small cell lung cancer (NSCLC) had shown potential impact on immune microenvironment and associated with response or resistance to programmed cell death protein 1 (PD-1) blockade immunotherapy. We therefore undertook an exploratory analysis to develop a genomic mutation signature (GMS) and predict the response to anti-PD-(L)1 therapy.Methods In this multicohort analysis, 316 patients with non-squamous NSCLC treated with anti-PD-(L)1 from three independent cohorts were included in our study. Tumor samples from the patients were molecularly profiled by MSK-IMPACT or whole exome sequencing. We developed a risk model named GMS based on the MSK training cohort (n=123). The predictive model was first validated in the separate internal MSK cohort (n=82) and then validated in an external cohort containing 111 patients from previously published clinical trials.Results A GMS risk model consisting of eight genes (TP53, KRAS, STK11, EGFR, PTPRD, KMT2C, SMAD4, and HGF) was generated to classify patients into high and low GMS groups in the training cohort. Patients with high GMS in the training cohort had longer progression-free survival (hazard ratio (HR) 0.41, 0.28–0.61, p<0.0001) and overall survival (HR 0.53, 0.32–0.89, p=0.0275) compared with low GMS. We noted equivalent findings in the internal validation cohort and in the external validation cohort. The GMS was demonstrated as an independent predictive factor for anti-PD-(L)1 therapy comparing with tumor mutational burden. Meanwhile, GMS showed undifferentiated predictive value in patients with different clinicopathological features. Notably, both GMS and PD-L1 were independent predictors and demonstrated poorly correlated; inclusion of PD-L1 with GMS further improved the predictive capacity for PD-1 blockade immunotherapy.Conclusions Our study highlights the potential predictive value of GMS for immunotherapeutic benefit in non-squamous NSCLC. Besides, the combination of GMS and PD-L1 may serve as an optimal partner in guiding treatment decisions for anti-PD-(L)1 based therapy. |
| format | Article |
| id | doaj-art-2daf1a4f2e834ec6869612616cff4cc8 |
| institution | Kabale University |
| issn | 2051-1426 |
| language | English |
| publishDate | 2020-05-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | Journal for ImmunoTherapy of Cancer |
| spelling | doaj-art-2daf1a4f2e834ec6869612616cff4cc82024-11-09T13:55:11ZengBMJ Publishing GroupJournal for ImmunoTherapy of Cancer2051-14262020-05-018110.1136/jitc-2019-000381Development and validation of a genomic mutation signature to predict response to PD-1 inhibitors in non-squamous NSCLC: a multicohort studyJian Wang0Yi-Long Wu1Xue Bai2De-Hua Wu3Si-Cong Ma4Xin-Ran Tang5Shuai Kang6Qiang John Fu7Chuan-Hui Cao8He-San Luo9Yu-Han Chen10Hong-Bo Zhu11Hong-Hong Yan12Zhong-Yi Dong13Department of Pain Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaGuangdong Lung Cancer Institute, Guangdong Provincial People`s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China2University of Missouri School of Medicine, Columbia, MO, USA1 Department of Radiation Oncology, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, China1 Department of Radiation Oncology, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, China1 Department of Radiation Oncology, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Beijing, China3 Department of Epidemiology and Biostatistics, Saint Louis University College for Public Health and Social Justice, Saint Louis, Missouri, USA1 Department of Radiation Oncology, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, China1 Department of Radiation Oncology, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, China1 Department of Radiation Oncology, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, China2 Hepatology Unit and Department of Infectious Diseases, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, ChinaGuangdong Lung Cancer Institute, Guangdong Provincial People`s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China1 Department of Radiation Oncology, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, ChinaBackground Genetic variations of some driver genes in non-small cell lung cancer (NSCLC) had shown potential impact on immune microenvironment and associated with response or resistance to programmed cell death protein 1 (PD-1) blockade immunotherapy. We therefore undertook an exploratory analysis to develop a genomic mutation signature (GMS) and predict the response to anti-PD-(L)1 therapy.Methods In this multicohort analysis, 316 patients with non-squamous NSCLC treated with anti-PD-(L)1 from three independent cohorts were included in our study. Tumor samples from the patients were molecularly profiled by MSK-IMPACT or whole exome sequencing. We developed a risk model named GMS based on the MSK training cohort (n=123). The predictive model was first validated in the separate internal MSK cohort (n=82) and then validated in an external cohort containing 111 patients from previously published clinical trials.Results A GMS risk model consisting of eight genes (TP53, KRAS, STK11, EGFR, PTPRD, KMT2C, SMAD4, and HGF) was generated to classify patients into high and low GMS groups in the training cohort. Patients with high GMS in the training cohort had longer progression-free survival (hazard ratio (HR) 0.41, 0.28–0.61, p<0.0001) and overall survival (HR 0.53, 0.32–0.89, p=0.0275) compared with low GMS. We noted equivalent findings in the internal validation cohort and in the external validation cohort. The GMS was demonstrated as an independent predictive factor for anti-PD-(L)1 therapy comparing with tumor mutational burden. Meanwhile, GMS showed undifferentiated predictive value in patients with different clinicopathological features. Notably, both GMS and PD-L1 were independent predictors and demonstrated poorly correlated; inclusion of PD-L1 with GMS further improved the predictive capacity for PD-1 blockade immunotherapy.Conclusions Our study highlights the potential predictive value of GMS for immunotherapeutic benefit in non-squamous NSCLC. Besides, the combination of GMS and PD-L1 may serve as an optimal partner in guiding treatment decisions for anti-PD-(L)1 based therapy.https://jitc.bmj.com/content/8/1/e000381.full |
| spellingShingle | Jian Wang Yi-Long Wu Xue Bai De-Hua Wu Si-Cong Ma Xin-Ran Tang Shuai Kang Qiang John Fu Chuan-Hui Cao He-San Luo Yu-Han Chen Hong-Bo Zhu Hong-Hong Yan Zhong-Yi Dong Development and validation of a genomic mutation signature to predict response to PD-1 inhibitors in non-squamous NSCLC: a multicohort study Journal for ImmunoTherapy of Cancer |
| title | Development and validation of a genomic mutation signature to predict response to PD-1 inhibitors in non-squamous NSCLC: a multicohort study |
| title_full | Development and validation of a genomic mutation signature to predict response to PD-1 inhibitors in non-squamous NSCLC: a multicohort study |
| title_fullStr | Development and validation of a genomic mutation signature to predict response to PD-1 inhibitors in non-squamous NSCLC: a multicohort study |
| title_full_unstemmed | Development and validation of a genomic mutation signature to predict response to PD-1 inhibitors in non-squamous NSCLC: a multicohort study |
| title_short | Development and validation of a genomic mutation signature to predict response to PD-1 inhibitors in non-squamous NSCLC: a multicohort study |
| title_sort | development and validation of a genomic mutation signature to predict response to pd 1 inhibitors in non squamous nsclc a multicohort study |
| url | https://jitc.bmj.com/content/8/1/e000381.full |
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