A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma
Background: Immunotherapy has changed the treatment landscape for lung cancer. This study aims to construct a tumor mutation-related model that combines long non-coding RNA (lncRNA) expression levels and tumor mutation levels in tumor genomes to detect the possibilities of the lncRNA signature as an...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-04-01
|
| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024047017 |
| _version_ | 1797234060965183488 |
|---|---|
| author | Wenjie Chen Chen Liao Xudong Xiang Heng Li Qiang Wu Wen Li Qianli Ma Nan Chen Benchao Chen Gaofeng Li |
| author_facet | Wenjie Chen Chen Liao Xudong Xiang Heng Li Qiang Wu Wen Li Qianli Ma Nan Chen Benchao Chen Gaofeng Li |
| author_sort | Wenjie Chen |
| collection | DOAJ |
| description | Background: Immunotherapy has changed the treatment landscape for lung cancer. This study aims to construct a tumor mutation-related model that combines long non-coding RNA (lncRNA) expression levels and tumor mutation levels in tumor genomes to detect the possibilities of the lncRNA signature as an indicator for predicting the prognosis and response to immunotherapy in lung adenocarcinoma (LUAD). Methods: We downloaded the tumor mutation profiles and RNA-seq expression database of LUAD from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were extracted based on the cumulative number of mutations. Cox regression analyses were used to identify the prognostic lncRNA signature, and the prognostic value of the five selected lncRNAs was validated by using survival analysis and the receiver operating characteristic (ROC) curve. We used qPCR to validate the expression of five selected lncRNAs between human lung epithelial and human lung adenocarcinoma cell lines. The ImmuCellAI, immunophenoscore (IPS) scores and Tumor Immune Dysfunction and Exclusion (TIDE) analyses were used to predict the response to immunotherapy for this mutation related lncRNA signature. Results: A total of 162 lncRNAs were detected among the differentially expressed lncRNAs between the Tumor mutational burden (TMB)-high group and the TMB-low group. Then, five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as tumor mutation-related candidates for constructing the prognostic prediction model. Kaplan‒Meier curves showed that the overall survival of the low-risk group was significantly better than that of the high-risk group, and the results of the GSE50081 set were consistent. The expression levels of PD1, PD-L1 and CTLA4 in the low-risk group were higher than those in the high-risk group. The IPS scores and TIDE scores of patients in the low-risk group were significantly higher than those in the high-risk group. Conclusion: Our findings demonstrated that the five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as candidates for constructing the tumor mutation-related model which may serve as an indicator of tumor mutation levels and have important implications for predicting the response to immunotherapy in LUAD. |
| first_indexed | 2024-04-24T16:26:04Z |
| format | Article |
| id | doaj.art-ad716cff40d44224acaa04696d221746 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-24T16:26:04Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-ad716cff40d44224acaa04696d2217462024-03-31T04:37:38ZengElsevierHeliyon2405-84402024-04-01107e28670A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinomaWenjie Chen0Chen Liao1Xudong Xiang2Heng Li3Qiang Wu4Wen Li5Qianli Ma6Nan Chen7Benchao Chen8Gaofeng Li9Department of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, ChinaDepartment of Gastroenterology, The Second Affiliated Hospital of Kunming Medical University, Kunming, ChinaDepartment of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, ChinaDepartment of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, ChinaLung Cancer Center, West China Hospital, Sichuan University, Chengdu, ChinaLung Cancer Center, West China Hospital, Sichuan University, Chengdu, ChinaDepartment of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, ChinaDepartment of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, ChinaDepartment of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, ChinaDepartment of Thoracic Surgery, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, China; Corresponding author.Background: Immunotherapy has changed the treatment landscape for lung cancer. This study aims to construct a tumor mutation-related model that combines long non-coding RNA (lncRNA) expression levels and tumor mutation levels in tumor genomes to detect the possibilities of the lncRNA signature as an indicator for predicting the prognosis and response to immunotherapy in lung adenocarcinoma (LUAD). Methods: We downloaded the tumor mutation profiles and RNA-seq expression database of LUAD from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were extracted based on the cumulative number of mutations. Cox regression analyses were used to identify the prognostic lncRNA signature, and the prognostic value of the five selected lncRNAs was validated by using survival analysis and the receiver operating characteristic (ROC) curve. We used qPCR to validate the expression of five selected lncRNAs between human lung epithelial and human lung adenocarcinoma cell lines. The ImmuCellAI, immunophenoscore (IPS) scores and Tumor Immune Dysfunction and Exclusion (TIDE) analyses were used to predict the response to immunotherapy for this mutation related lncRNA signature. Results: A total of 162 lncRNAs were detected among the differentially expressed lncRNAs between the Tumor mutational burden (TMB)-high group and the TMB-low group. Then, five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as tumor mutation-related candidates for constructing the prognostic prediction model. Kaplan‒Meier curves showed that the overall survival of the low-risk group was significantly better than that of the high-risk group, and the results of the GSE50081 set were consistent. The expression levels of PD1, PD-L1 and CTLA4 in the low-risk group were higher than those in the high-risk group. The IPS scores and TIDE scores of patients in the low-risk group were significantly higher than those in the high-risk group. Conclusion: Our findings demonstrated that the five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as candidates for constructing the tumor mutation-related model which may serve as an indicator of tumor mutation levels and have important implications for predicting the response to immunotherapy in LUAD.http://www.sciencedirect.com/science/article/pii/S2405844024047017Tumor mutationImmune checkpoint inhibitorPrognosisLong non-coding RNALung adenocarcinoma |
| spellingShingle | Wenjie Chen Chen Liao Xudong Xiang Heng Li Qiang Wu Wen Li Qianli Ma Nan Chen Benchao Chen Gaofeng Li A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma Heliyon Tumor mutation Immune checkpoint inhibitor Prognosis Long non-coding RNA Lung adenocarcinoma |
| title | A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma |
| title_full | A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma |
| title_fullStr | A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma |
| title_full_unstemmed | A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma |
| title_short | A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma |
| title_sort | novel tumor mutation related long non coding rna signature for predicting overall survival and immunotherapy response in lung adenocarcinoma |
| topic | Tumor mutation Immune checkpoint inhibitor Prognosis Long non-coding RNA Lung adenocarcinoma |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024047017 |
| work_keys_str_mv | AT wenjiechen anoveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT chenliao anoveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT xudongxiang anoveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT hengli anoveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT qiangwu anoveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT wenli anoveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT qianlima anoveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT nanchen anoveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT benchaochen anoveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT gaofengli anoveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT wenjiechen noveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT chenliao noveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT xudongxiang noveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT hengli noveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT qiangwu noveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT wenli noveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT qianlima noveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT nanchen noveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT benchaochen noveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma AT gaofengli noveltumormutationrelatedlongnoncodingrnasignatureforpredictingoverallsurvivalandimmunotherapyresponseinlungadenocarcinoma |