1
|
Qin C, Fan X, Sai X, Yin B, Zhou S, Addeo A, Bian T, Yu H. Development and validation of a DNA damage repair-related gene-based prediction model for the prognosis of lung adenocarcinoma. J Thorac Dis 2023; 15:6928-6945. [PMID: 38249902 PMCID: PMC10797339 DOI: 10.21037/jtd-23-1746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 12/15/2023] [Indexed: 01/23/2024]
Abstract
Background Lung cancer is the leading cause of morbidity and mortality among all cancer types, with lung adenocarcinoma (LUAD) being the most prevalent subtype. DNA damage repair (DDR)-related genes are closely associated with cancer progression and treatment, with emerging evidence highlighting their correlation with tumor development. However, the relationship between LUAD prognosis and DDR-related genes remains unclear. Methods RNA sequencing (RNA-seq) data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. The GSE31210 dataset, utilized for external validation, was retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed DDR genes were identified, and a DDR-related prognostic model was established and validated using Kaplan-Meier (KM) survival analysis, time-dependent receiver operating characteristic (ROC) curves, gene set enrichment analysis (GSEA), tumor mutational burden (TMB) analysis, and immune cell infiltration. A P value of less than 0.05 was considered statistically significant. Results A total of 514 patients with LUAD from TCGA database were divided into distinct subtypes to characterize the diversity within the DDR pathway. DDR-activated and DDR-suppressed subgroups showed distinct clinical characteristics, molecular characteristics, and immune profiles. Nine genes were identified as hub DDR-related genes, including CASP14, DKK1, ECT2, FLNC, HMMR, IGFBP1, KRT6A, TYMS, and FCER2. By using the expression levels of these selected genes, the corresponding risk scores for each sample was predicted. In the training group, KM survival analysis revealed that the high-risk group exhibited significantly diminished overall survival (OS) [hazard ratio (HR) =3.341, P=1.38e-08]. The corresponding area under the curve (AUC) values for the 1-year follow-up periods was 0.767, respectively. Upon validation in the external cohort, patients with higher risk scores manifested significantly reduced OS (HR =2.372, P=1.87e-03). The AUC values of the ROC curves for the 1-year OS in the validation cohort was 0.87, respectively. Moreover, advanced DDR risk score was correlated with increased TMB scores, a heightened frequency of TP53 mutations, an increased abundance of cancer-testicular antigens (CTAs), and a lower tumor immune dysfunction and exclusion (TIDE) score in patients with LUAD (P<0.05). Conclusions A nine-gene risk signature associated with DDR in LUAD was effectively developed, demonstrating its potential as a robust and reliable classification tool for clinical practice. This model exhibited the capability to accurately predict the prognosis and survival outcomes of LUAD patients.
Collapse
Affiliation(s)
- Chu Qin
- Department of Respiratory Medicine, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China
| | - Xiaodong Fan
- Department of Respiratory Medicine, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China
| | - Xiaoyan Sai
- Department of Respiratory Medicine, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China
| | - Bo Yin
- Department of Respiratory Medicine, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China
| | - Shufang Zhou
- Department of Respiratory Medicine, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China
| | - Alfredo Addeo
- Oncology Department, Geneva University Hospital (CH), Geneva, Switzerland
| | - Tao Bian
- Department of Respiratory Medicine, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China
| | - Haoda Yu
- Department of Respiratory Medicine, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China
| |
Collapse
|
2
|
Celik S, Aktas T, Gokbayrak O, Erol A, Yorukoglu K, Yilmaz B, Sari H, Altun Z, Mungan MU, Celebi I, Aslan G, Aktas S. Genomic Alterations of Signaling and DNA Damage Repair Pathways in Non-Muscle Invasive Bladder Cancer. Cancer Invest 2023; 41:848-857. [PMID: 37997757 DOI: 10.1080/07357907.2023.2288640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 11/23/2023] [Indexed: 11/25/2023]
Abstract
The aim of the study was to demonstrate the most common genetic alterations and evaluate possible targets involving phosphatidylinositol-3-OH kinase (PIK3)/AKT/mammalian target of rapamycin (mTOR) signaling and DNA damage repair (DDR) pathways for personalized treatment in patients with non-muscle invasive bladder cancer (NMIBC). Alterations of these pathways were observed in 89.5% and 100% of patients, respectively. Among them, BARD1 was more frequently altered in low/intermediate-risk cases, but PARP4 was more frequently affected in intermediate/high-risk patients. The possible target feasibility of BARD1 and PARP4 alterations should be evaluated for personalized treatment using PARP-inhibitors in NMIBC. It is important to detect high tumor mutation burden (TMB) in patients in terms of immunotherapy.
Collapse
Affiliation(s)
- Serdar Celik
- Department of Urology, Izmir Faculty of Medicine, Health Sciences University, Izmir Bozyaka Education and Research Hospital, Izmir, Turkey
- Department of Basic Oncology, Institute of Oncology, Dokuz Eylul University, Izmir, Turkey
| | - Tekincan Aktas
- Department of Basic Oncology, Institute of Oncology, Dokuz Eylul University, Izmir, Turkey
| | - Ozde Gokbayrak
- Department of Basic Oncology, Institute of Oncology, Dokuz Eylul University, Izmir, Turkey
| | - Aylin Erol
- Department of Basic Oncology, Institute of Oncology, Dokuz Eylul University, Izmir, Turkey
| | - Kutsal Yorukoglu
- Department of Pathology, School of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Batuhan Yilmaz
- Department of Urology, School of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Hilmi Sari
- Department of Urology, School of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Zekiye Altun
- Department of Basic Oncology, Institute of Oncology, Dokuz Eylul University, Izmir, Turkey
| | - Mehmet Ugur Mungan
- Department of Urology, School of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Ilhan Celebi
- Department of Urology, School of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Guven Aslan
- Department of Urology, School of Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Safiye Aktas
- Department of Basic Oncology, Institute of Oncology, Dokuz Eylul University, Izmir, Turkey
| |
Collapse
|
3
|
Wang J, Wu J, Wang Y, Wang Y, Jiang C, Zou M, Jin X, Sun X, Zhang Y, Ma S, Wang G, Zhu X, Lu H, Xu C, Wang W, Li L, Han Y, Cai S, Li H. A DNA Damage Response Related Signature to Predict Prognosis in Patients with Acute Myeloid Leukemia. Cancer Invest 2023; 41:1-13. [PMID: 36629468 DOI: 10.1080/07357907.2023.2167209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 12/26/2022] [Accepted: 01/08/2023] [Indexed: 01/12/2023]
Abstract
The prognosis of acute myeloid leukemia (AML) is disappointing in most subtypes and varies widely. DNA damage response (DDR) is associated with prognosis and immunotherapy in multiple cancers. Here, we identify a signature of eight DDR-related genes associated with overall survival, which stratifies AML patients into high- and low-risk groups. Patients in low-risk group were more likely to respond to sorafenib. The signature could be an independent prognostic predictor for patients treated with ADE and ADE plus gemtuzumab ozogamicin. Therefore, this DDR prognostic signature might be applied to prognostic stratification and treatment selection in AML patients, which warrants further studies.
Collapse
Affiliation(s)
- Jun Wang
- School of Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Jiafei Wu
- School of Clinical Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yijing Wang
- School of Clinical Medicine, Chengdu Medical College, Chengdu, China
| | - Yu Wang
- Department of Hematology, Dong Li Hospital, Chengdu, China
| | - Chuanyan Jiang
- Department of Hematology, Chengdu Second People's Hospital, Chengdu, China
| | - Mengying Zou
- Department of Hematology, Chengdu BOE Hospital, Chengdu, China
| | | | | | - Yu Zhang
- Burning Rock Biotech, Guangzhou, China
| | - Sijia Ma
- Burning Rock Biotech, Guangzhou, China
| | | | - Xin Zhu
- Burning Rock Biotech, Guangzhou, China
| | - Huafei Lu
- Burning Rock Biotech, Guangzhou, China
| | - Chunwei Xu
- Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | - Wenxian Wang
- Department of Clinical Trial, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China
| | - Leo Li
- Burning Rock Biotech, Guangzhou, China
| | | | | | - Hui Li
- Department of Hematology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
| |
Collapse
|
4
|
Zhu S, Kong W, Zhu J, Huang L, Wang S, Bi S, Xie Z. The genetic algorithm-aided three-stage ensemble learning method identified a robust survival risk score in patients with glioma. Brief Bioinform 2022; 23:6694808. [DOI: 10.1093/bib/bbac344] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 07/14/2022] [Accepted: 07/25/2022] [Indexed: 02/07/2023] Open
Abstract
Abstract
Ensemble learning is a kind of machine learning method which can integrate multiple basic learners together and achieve higher accuracy. Recently, single machine learning methods have been established to predict survival for patients with cancer. However, it still lacked a robust ensemble learning model with high accuracy to pick out patients with high risks. To achieve this, we proposed a novel genetic algorithm-aided three-stage ensemble learning method (3S score) for survival prediction. During the process of constructing the 3S score, double training sets were used to avoid over-fitting; the gene-pairing method was applied to reduce batch effect; a genetic algorithm was employed to select the best basic learner combination. When used to predict the survival state of glioma patients, this model achieved the highest C-index (0.697) as well as area under the receiver operating characteristic curve (ROC-AUCs) (first year = 0.705, third year = 0.825 and fifth year = 0.839) in the combined test set (n = 1191), compared with 12 other baseline models. Furthermore, the 3S score can distinguish survival significantly in eight cohorts among the total of nine independent test cohorts (P < 0.05), achieving significant improvement of ROC-AUCs. Notably, ablation experiments demonstrated that the gene-pairing method, double training sets and genetic algorithm make sure the robustness and effectiveness of the 3S score. The performance exploration on pan-cancer showed that the 3S score has excellent ability on survival prediction in five kinds of cancers, which was verified by Cox regression, survival curves and ROC curves together. To enable its clinical adoption, we implemented the 3S score and other two clinical factors as an easy-to-use web tool for risk scoring and therapy stratification in glioma patients.
Collapse
Affiliation(s)
- Sujie Zhu
- Institute of Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University , Qingdao, China
| | - Weikaixin Kong
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki , Finland
- Institute Sanqu Technology (Hangzhou) Co., Ltd. , Hangzhou, China
| | - Jie Zhu
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki , Finland
| | - Liting Huang
- Institute of Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University , Qingdao, China
| | - Shixin Wang
- Institute of Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University , Qingdao, China
| | - Suzhen Bi
- Institute of Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University , Qingdao, China
| | - Zhengwei Xie
- Peking University International Cancer Institute and Department of Pharmacology, School of Basic Medical Sciences, Peking University , Beijing, China
| |
Collapse
|