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Zhang L, Zhang X, Guan M, Zeng J, Yu F, Lai F. Identification of a novel ADCC-related gene signature for predicting the prognosis and therapy response in lung adenocarcinoma. Inflamm Res 2024; 73:841-866. [PMID: 38507067 DOI: 10.1007/s00011-024-01871-y] [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: 12/15/2023] [Revised: 03/03/2024] [Accepted: 03/05/2024] [Indexed: 03/22/2024] Open
Abstract
BACKGROUND Previous studies have largely neglected the role of ADCC in LUAD, and no study has systematically compiled ADCC-associated genes to create prognostic signatures. METHODS In this study, 1564 LUAD patients, 2057 NSCLC patients, and more than 5000 patients with various cancer types from diverse cohorts were included. R package ConsensusClusterPlus was utilized to classify patients into different subtypes. A number of machine-learning algorithms were used to construct the ADCCRS. GSVA and ClusterProfiler were used for enrichment analyses, and IOBR was used to quantify immune cell infiltration level. GISTIC2.0 and maftools were used to analyze the CNV and SNV data. The Oncopredict package was used to predict drug information based on the GDSC1. Three immunotherapy cohorts were used to evaluate patient response to immunotherapy. The Seurat package was used to process single-cell data, the AUCell package was used to calculate cells' geneset activity scores, and the Scissor algorithm was used to identify ADCCRS-associated cells. RESULTS Through unsupervised clustering, two distinct subtypes of LUAD were identified, each exhibiting distinct clinical characteristics. The ADCCRS, consisted of 16 genes, was constructed by integrated machine-learning methods. The prognostic power of ADCCRS was validated in 28 independent datasets. Further, ADCCRS shows better predictive abilities than 102 previously published signatures in predicting LUAD patients' survival. A nomogram incorporating ADCCRS and clinical features was constructed, demonstrating high predictive performance. ADCCRS positively correlates with patients' gene mutation, and integrated analysis of bulk and single-cell transcriptome data revealed the association of ADCCRS with TME modulators. Cells representing high-ADCCRS phenotype exhibited more malignant features. LUAD patients with high ADCCRS levels exhibited sensitivity to chemotherapy and targeted therapy, while displaying resistance to immunotherapy. In pan-cancer analysis, ADCCRS still exhibited significant prognostic value and was found to be a risk factor for most cancer patients. CONCLUSIONS ADCCRS offers a critical prognostic insight for patients with LUAD, shedding light on the tumor microenvironment and forecasting treatment responsiveness.
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Affiliation(s)
- Liangyu Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Thoracic Surgery, National Regional Medical Center, Binhai Campus of the Fitst Affiliated Hospiral, Fujian Medical University, Fuzhou, 350212, China
| | - Xun Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Thoracic Surgery, National Regional Medical Center, Binhai Campus of the Fitst Affiliated Hospiral, Fujian Medical University, Fuzhou, 350212, China
| | - Maohao Guan
- Department of Thoracic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Thoracic Surgery, National Regional Medical Center, Binhai Campus of the Fitst Affiliated Hospiral, Fujian Medical University, Fuzhou, 350212, China
| | - Jianshen Zeng
- Department of Thoracic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Thoracic Surgery, National Regional Medical Center, Binhai Campus of the Fitst Affiliated Hospiral, Fujian Medical University, Fuzhou, 350212, China
| | - Fengqiang Yu
- Department of Thoracic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China.
- Department of Thoracic Surgery, National Regional Medical Center, Binhai Campus of the Fitst Affiliated Hospiral, Fujian Medical University, Fuzhou, 350212, China.
| | - Fancai Lai
- Department of Thoracic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China.
- Department of Thoracic Surgery, National Regional Medical Center, Binhai Campus of the Fitst Affiliated Hospiral, Fujian Medical University, Fuzhou, 350212, China.
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Ding H, Teng Y, Gao P, Zhang Q, Wang M, Yu Y, Fan Y, Zhu L. Construction of a prognostic model for lung adenocarcinoma based on m6A/m5C/m1A genes. Hum Mol Genet 2024; 33:563-582. [PMID: 38142284 DOI: 10.1093/hmg/ddad208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 11/15/2023] [Accepted: 12/07/2023] [Indexed: 12/25/2023] Open
Abstract
BACKGROUND Developing a prognostic model for lung adenocarcinoma (LUAD) that utilizes m6A/m5C/m1A genes holds immense importance in providing precise prognosis predictions for individuals. METHODS This study mined m6A/m5C/m1A-related differential genes in LUAD based on public databases, identified LUAD tumor subtypes based on these genes, and further built a risk prognostic model grounded in differential genes between subtypes. The immune status between high- and low-risk groups was investigated, and the distribution of feature genes in tumor immune cells was analyzed using single-cell analysis. Based on the expression levels of feature genes, a projection of chemotherapeutic and targeted drugs was made for individuals identified as high-risk. Ultimately, cell experiments were further verified. RESULTS The 6-gene risk prognosis model based on differential genes between tumor subtypes had good predictive performance. Individuals classified as low-risk exhibited a higher (P < 0.05) abundance of infiltrating immune cells. Feature genes were mainly distributed in tumor immune cells like CD4+T cells, CD8+T cells, and regulatory T cells. Four drugs with relatively low IC50 values were found in the high-risk group: Elesclomol, Pyrimethamine, Saracatinib, and Temsirolimus. In addition, four drugs with significant positive correlation (P < 0.001) between IC50 values and feature gene expression were found, including Alectinib, Estramustine, Brigatinib, and Elesclomol. The low expression of key gene NTSR1 reduced the IC50 value of irinotecan. CONCLUSION Based on the m6A/m5C/m1A-related genes in LUAD, LUAD patients were divided into 2 subtypes, and a m6A/m5C/m1A-related LUAD prognostic model was constructed to provide a reference for the prognosis prediction of LUAD.
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Affiliation(s)
- Hao Ding
- Department of Respiratory Disease, Affiliated People's Hospital of Jiangsu University, NO. 8 Dianli Road, Runzhou District, Zhenjiang City, Jiangsu Province 212002, China
| | - Yuanyuan Teng
- Department of Respiratory Disease, Affiliated People's Hospital of Jiangsu University, NO. 8 Dianli Road, Runzhou District, Zhenjiang City, Jiangsu Province 212002, China
| | - Ping Gao
- Department of Respiratory Disease, Affiliated People's Hospital of Jiangsu University, NO. 8 Dianli Road, Runzhou District, Zhenjiang City, Jiangsu Province 212002, China
| | - Qi Zhang
- Department of Respiratory Disease, Affiliated People's Hospital of Jiangsu University, NO. 8 Dianli Road, Runzhou District, Zhenjiang City, Jiangsu Province 212002, China
| | - Mengdi Wang
- Department of Respiratory Disease, Affiliated People's Hospital of Jiangsu University, NO. 8 Dianli Road, Runzhou District, Zhenjiang City, Jiangsu Province 212002, China
| | - Yi Yu
- Department of General Practice, Jiankang Road Community Health Service Center, NO. 239 Zhongshan East Road, Jingkou District, Zhenjiang City, Jiangsu Province 212008, China
| | - Yueping Fan
- Department of Respiratory, Jurong Branch Hospital, Affiliated Hospital of Jiangsu University, NO. 8 Huayang South Road, Jurong City, Zhenjiang City, Jiangsu Province 212400, China
| | - Li Zhu
- Department of Nephrology, Affiliated People's Hospital of Jiangsu University, NO. 8 Dianli Road, Runzhou District, Zhenjiang City, Jiangsu Province 212002, China
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Zheng J, Jiang S, Lin X, Wang H, Liu L, Cai X, Sun Y. Comprehensive analyses of mitophagy-related genes and mitophagy-related lncRNAs for patients with ovarian cancer. BMC Womens Health 2024; 24:37. [PMID: 38218807 PMCID: PMC10788026 DOI: 10.1186/s12905-023-02864-5] [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: 04/03/2023] [Accepted: 12/24/2023] [Indexed: 01/15/2024] Open
Abstract
BACKGROUND Both mitophagy and long non-coding RNAs (lncRNAs) play crucial roles in ovarian cancer (OC). We sought to explore the characteristics of mitophagy-related gene (MRG) and mitophagy-related lncRNAs (MRL) to facilitate treatment and prognosis of OC. METHODS The processed data were extracted from public databases (TCGA, GTEx, GEO and GeneCards). The highly synergistic lncRNA modules and MRLs were identified using weighted gene co-expression network analysis. Using LASSO Cox regression analysis, the MRL-model was first established based on TCGA and then validated with four external GEO datasets. The independent prognostic value of the MRL-model was evaluated by Multivariate Cox regression analysis. Characteristics of functional pathways, somatic mutations, immunity features, and anti-tumor therapy related to the MRL-model were evaluated using abundant algorithms, such as GSEA, ssGSEA, GSVA, maftools, CIBERSORT, xCELL, MCPcounter, ESTIMATE, TIDE, pRRophetic and so on. RESULTS We found 52 differentially expressed MRGs and 22 prognostic MRGs in OC. Enrichment analysis revealed that MRGs were involved in mitophagy. Nine prognostic MRLs were identified and eight optimal MRLs combinations were screened to establish the MRL-model. The MRL-model stratified patients into high- and low-risk groups and remained a prognostic factor (P < 0.05) with independent value (P < 0.05) in TCGA and GEO. We observed that OC patients in the high-risk group also had the unfavorable survival in consideration of clinicopathological parameters. The Nomogram was plotted to make the prediction results more intuitive and readable. The two risk groups were enriched in discrepant functional pathways (such as Wnt signaling pathway) and immunity features. Besides, patients in the low-risk group may be more sensitive to immunotherapy (P = 0.01). Several chemotherapeutic drugs (Paclitaxel, Veliparib, Rucaparib, Axitinib, Linsitinib, Saracatinib, Motesanib, Ponatinib, Imatinib and so on) were found with variant sensitivity between the two risk groups. The established ceRNA network indicated the underlying mechanisms of MRLs. CONCLUSIONS Our study revealed the roles of MRLs and MRL-model in expression, prognosis, chemotherapy, immunotherapy, and molecular mechanism of OC. Our findings were able to stratify OC patients with high risk, unfavorable prognosis and variant treatment sensitivity, thus improving clinical outcomes for OC patients.
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Affiliation(s)
- Jianfeng Zheng
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Shan Jiang
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Xuefen Lin
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Huihui Wang
- Department of Anesthesiology, The Central hospital of Wenzhou City, 32 Dajian Lane, Wenzhou, 325000, China
| | - Li Liu
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Xintong Cai
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Yang Sun
- Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China.
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