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Wang Y, Han Y, Jin L, Ji L, Liu Y, Lin M, Zhou S, Yang R. A novel prognostic signature based on cancer stemness and metabolism-related genes for cervical squamous cell carcinoma and endocervical adenocarcinoma. Aging (Albany NY) 2024; 16:7293-7310. [PMID: 38656879 PMCID: PMC11087133 DOI: 10.18632/aging.205757] [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: 10/11/2023] [Accepted: 03/28/2024] [Indexed: 04/26/2024]
Abstract
BACKGROUND CESC is the second most commonly diagnosed gynecological malignancy. Given the pivotal involvement of metabolism-related genes (MRGs) in the etiology of multiple tumors, our investigation aims to devise a prognostic risk signature rooted in cancer stemness and metabolism. METHODS The stemness index based on mRNA expression (mRNAsi) of samples from the TCGA dataset was computed using the One-class logistic regression (OCLR) algorithm. Furthermore, potential metabolism-related genes related to mRNAsi were identified through weighted gene co-expression network analysis (WGCNA). We construct a stemness-related metabolic gene signature through shrinkage estimation and univariate analysis, thereby calculating the corresponding risk scores. Moreover, we selected corresponding DEGs between groups with high- and low-risk score and conducted routine bioinformatic analyses. Furthermore, we validated the expression of four hub genes at the protein level through immunohistochemistry (IHC) in samples obtained from our patient cohort. RESULTS According to the findings, it was found that six genes-AKR1B10, GNA15, ALDH1B1, PLOD2, LPCAT1, and GPX8- were differentially expressed in both TCGA-CSEC and GEO datasets among 23 differentially expressed metabolism-related genes (DEMRGs). mRNAsi exhibited a notable association with the extent of key oncogene mutation. The results showed that the AUC values for forecasting survival at 1, 3, and 5 years are 0.715, 0.689, and 0.748, individually. We observed a notable association between the risk score and different immune cell populations, along with enrichment in crucial signaling pathways in CESC. Four genes differentially expressed between different risk score groups were validated by IHC to be highly expressed in the CESC samples at the protein level. CONCLUSION The current investigation indicated that a 3-gene signature based on stemness-related metabolic and 4 hub genes with differential expression between high and low-risk score subgroups may serve as valuable prognostic markers and potential therapeutic targets in CESC.
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Affiliation(s)
- Yaokai Wang
- Department of Gynecology and Obstetrics, The University of Hong Kong-Shenzhen Hospital, Shenzhen 518053, Guangdong, China
| | - Yuanyuan Han
- Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Yunnan Key Laboratory of Vaccine Research and Development on Severe Infectious Diseases, Kunming, Yunnan, China
| | - Liangzi Jin
- Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Yunnan Key Laboratory of Vaccine Research and Development on Severe Infectious Diseases, Kunming, Yunnan, China
| | - Lulu Ji
- Department of Gynecology and Obstetrics, The University of Hong Kong-Shenzhen Hospital, Shenzhen 518053, Guangdong, China
| | - Yanxiang Liu
- Yantian District Maternal and Child Health Hospital, Shenzhen, Guangdong, China
| | - Min Lin
- Department of Gynecology and Obstetrics, The University of Hong Kong-Shenzhen Hospital, Shenzhen 518053, Guangdong, China
| | - Sitong Zhou
- Department of Dermatology, The First People’s Hospital of Foshan, Foshan, Guangdong, China
| | - Ronghua Yang
- Department of Burn and Plastic Surgery, Guangzhou First People’s Hospital, South China University of Technology, Guangzhou, Guangdong, China
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Wan R, Chen Y, Feng X, Luo Z, Peng Z, Qi B, Qin H, Lin J, Chen S, Xu L, Tang J, Zhang T. Exercise potentially prevents colorectal cancer liver metastases by suppressing tumor epithelial cell stemness via RPS4X downregulation. Heliyon 2024; 10:e26604. [PMID: 38439884 PMCID: PMC10909670 DOI: 10.1016/j.heliyon.2024.e26604] [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: 02/05/2024] [Accepted: 02/15/2024] [Indexed: 03/06/2024] Open
Abstract
Background Colorectal cancer (CRC) is the third most prevalent tumor globally. The liver is the most common site for CRC metastasis, and the involvement of the liver is a common cause of death in patients with late-stage CRC. Consequently, mitigating CRC liver metastasis (CRLM) is key to improving CRC prognosis and increasing survival. Exercise has been shown to be an effective method of improving the prognosis of many tumor types. However, the ability of exercise to inhibit CRLM is yet to be thoroughly investigated. Methods The GSE157600 and GSE97084 datasets were used for analysis. A pan-cancer dataset which was uniformly normalized was downloaded and analyzed from the UCSC database: TCGA, TARGET, GTEx (PANCAN, n = 19,131, G = 60,499). Several advanced bioinformatics analyses were conducted, including single-cell sequencing analysis, correlation algorithm, and prognostic screen. CRC tumor microarray (TMA) as well as cell/animal experiments are used to further validate the results of the analysis. Results The greatest variability was found in epithelial cells from the tumor group. RPS4X was generally upregulated in all types of CRC, while exercise downregulated RPS4X expression. A lowered expression of RPS4X may prolong tumor survival and reduce CRC metastasis. RPS4X and tumor stemness marker-CD44 were highly positively correlated and knockdown of RPS4X expression reduced tumor stemness both in vitro and in vivo. Conclusion RPS4X upregulation may enhance CRC stemness and increase the odds of metastasis. Exercise may reduce CRC metastasis through the regulation of RPS4X.
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Affiliation(s)
- Renwen Wan
- Department of Sports Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Yisheng Chen
- Department of Sports Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Xinting Feng
- Department of Sports Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Zhiwen Luo
- Department of Sports Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Zhen Peng
- Department of Sports Medicine, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Beijie Qi
- Department of Orthopedics, Shanghai Pudong Hospital, Fudan University Affiliated Pudong Medical Center, Shanghai 201399, China
| | - Haocheng Qin
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Jinrong Lin
- Department of Sports Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Shiyi Chen
- Department of Sports Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Liangfeng Xu
- Department of Gastroenterology, Sheyang County People's Hospital, Yancheng 224300, Jiangsu, China
| | - Jiayin Tang
- Department of Gastrointestinal Surgery, Renji Hospital, Shanghai 200127, China
| | - Ting Zhang
- Department of Integrative Medicine, Huashan Hospital, Fudan University, Shanghai, China
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Wang R, Huang Y, He J, Jin S, Li X, Tan K, Xia W. The endoplasmic reticulum stress-related genes and molecular typing predicts prognosis and reveals characterization of tumor immune microenvironment in lung squamous cell carcinoma. Discov Oncol 2024; 15:37. [PMID: 38363409 PMCID: PMC10873263 DOI: 10.1007/s12672-024-00887-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 02/07/2024] [Indexed: 02/17/2024] Open
Abstract
BACKGROUND Endoplasmic reticulum stress (ERS) acts critical roles on cell growth, proliferation, and metastasis in various cancers. However, the relationship between ERs and lung squamous cell carcinoma (LUSC) prognoses still remains unclear. METHODS The consensus clustering analysis of ERS-related genes and the differential expression analysis between clusters were investigated in LUSC based on TCGA database. Furthermore, ERS-related prognostic risk models were constructed by LASSO regression and Cox regression analyses. Then, the predictive effect of the risk model was evaluated by Kaplan-Meier, Cox regression, and ROC Curve analyses, as well as validated in the GEO cohort. According to the optimal threshold, patients with LUSC were divided into high- and low- risk groups, and somatic mutations, immune cell infiltration, chemotherapy response and immunotherapy effect were systematically analyzed. RESULTS Two ERS-related clusters were identified in patients with LUSC that had distinct patterns of immune cell infiltration. A 5-genes ERS-related prognostic risk model and nomogram were constructed and validated. Kaplan-Meier curves and Cox regression analysis showed that ERS risk score was an independent prognostic factor (p < 0.001, HR = 1.317, 95% CI = 1.159-1.496). Patients with low-risk scores presented significantly lower TIDE scores and significantly lower IC50 values for common chemotherapy drugs such as cisplatin and gemcitabine. CONCLUSION ERS-related risk signature has certain prognostic value and may be a potential therapeutic target and prognostic biomarker for LUSC patients.
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Affiliation(s)
- Ruolan Wang
- College of Pharmacy, Dali University, Dali, 671000, Yunnan, China
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Yanhua Huang
- Department of Procurement Management, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Juan He
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Shan Jin
- College of Pharmacy, Dali University, Dali, 671000, Yunnan, China
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Xin Li
- College of Pharmacy, Dali University, Dali, 671000, Yunnan, China
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Kun Tan
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China
| | - Wei Xia
- Department of Pharmacy, 920th Hospital of Joint Logistics Support Force of People's Liberation Army, Kunming, 650032, Yunnan, China.
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Liu J, Miao X, Yao J, Wan Z, Yang X, Tian W. Investigating the clinical role and prognostic value of genes related to insulin-like growth factor signaling pathway in thyroid cancer. Aging (Albany NY) 2024; 16:2934-2952. [PMID: 38329437 PMCID: PMC10911384 DOI: 10.18632/aging.205524] [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: 09/25/2023] [Accepted: 12/27/2023] [Indexed: 02/09/2024]
Abstract
BACKGROUND Thyroid cancer (THCA) is the most common endocrine malignancy having a female predominance. The insulin-like growth factor (IGF) pathway contributed to the unregulated cell proliferation in multiple malignancies. We aimed to explore the IGF-related signature for THCA prognosis. METHOD The TCGA-THCA dataset was collected from the Cancer Genome Atlas (TCGA) for screening of key prognostic genes. The limma R package was applied for differentially expressed genes (DEGs) and the clusterProfiler R package was used for the Gene Ontology (GO) and KEGG analysis of DEGs. Then, the un/multivariate and least absolute shrinkage and selection operator (Lasso) Cox regression analysis was used for the establishment of RiskScore model. Receiver Operating Characteristic (ROC) analysis was used to verify the model's predictive performance. CIBERSORT and MCP-counter algorithms were applied for immune infiltration analysis. Finally, we analyzed the mutation features and the correlation between the RiskScore and cancer hallmark pathway by using the GSEA. RESULT We obtained 5 key RiskScore model genes for patient's risk stratification from the 721 DEGs. ROC analysis indicated that our model is an ideal classifier, the high-risk patients are associated with the poor prognosis, immune infiltration, high tumor mutation burden (TMB), stronger cancer stemness and stronger correlation with the typical cancer-activation pathways. A nomogram combined with multiple clinical features was developed and exhibited excellent performance upon long-term survival quantitative prediction. CONCLUSIONS We constructed an excellent prognostic model RiskScore based on IGF-related signature and concluded that the IGF signal pathway may become a reliable prognostic phenotype in THCA intervention.
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Affiliation(s)
- Junyan Liu
- Department of General Surgery, The First Medical Center, Chinese People’s Liberation Army (PLA) General Hospital, Beijing 100853, China
| | - Xin Miao
- Department of General Surgery, The First Medical Center, Chinese People’s Liberation Army (PLA) General Hospital, Beijing 100853, China
| | - Jing Yao
- Department of General Surgery, The First Medical Center, Chinese People’s Liberation Army (PLA) General Hospital, Beijing 100853, China
| | - Zheng Wan
- Department of General Surgery, The First Medical Center, Chinese People’s Liberation Army (PLA) General Hospital, Beijing 100853, China
| | - Xiaodong Yang
- Department of General Surgery, The First Medical Center, Chinese People’s Liberation Army (PLA) General Hospital, Beijing 100853, China
| | - Wen Tian
- Department of General Surgery, The First Medical Center, Chinese People’s Liberation Army (PLA) General Hospital, Beijing 100853, China
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Xia Y, Wang C, Li X, Gao M, Hogg HDJ, Tunthanathip T, Hulsen T, Tian X, Zhao Q. Development and validation of a novel stemness-related prognostic model for neuroblastoma using integrated machine learning and bioinformatics analyses. Transl Pediatr 2024; 13:91-109. [PMID: 38323183 PMCID: PMC10839279 DOI: 10.21037/tp-23-582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 01/05/2024] [Indexed: 02/08/2024] Open
Abstract
Background Neuroblastoma (NB) is a common solid tumor in children, with a dismal prognosis in high-risk cases. Despite advancements in NB treatment, the clinical need for precise prognostic models remains critical, particularly to address the heterogeneity of cancer stemness which plays a pivotal role in tumor aggressiveness and patient outcomes. By utilizing machine learning (ML) techniques, we aimed to explore the cancer stemness features in NB and identify stemness-related hub genes for future investigation and potential targeted therapy. Methods The public dataset GSE49710 was employed as the training set for acquire gene expression data and NB sample information, including age, stage, and MYCN amplification status and survival. The messenger RNA (mRNA) expression-based stemness index (mRNAsi) was calculated and patients were grouped according to their mRNAsi value. Stemness-related hub genes were identified from the differentially expressed genes (DEGs) to construct a gene signature. This was followed by evaluating the relationship between cancer stemness and the NB immune microenvironment, and the development of a predictive nomogram. We assessed the prognostic outcomes including overall survival (OS) and event-free survival, employing machine learning methods to measure predictive accuracy through concordance indices and validation in an independent cohort E-MTAB-8248. Results Based on mRNAsi, we categorized NB patients into two groups to explore the association between varying levels of stemness and their clinical outcomes. High mRNAsi was linked to the advanced International Neuroblastoma Staging System (INSS) stage, amplified MYCN, and elder age. High mRNAsi patients had a significantly poorer prognosis than low mRNAsi cases. According to the multivariate Cox analysis, the mRNAsi was an independent risk factor of prognosis in NB patients. After least absolute shrinkage and selection operator (LASSO) regression analysis, four key genes (ERCC6L, DUXAP10, NCAN, DIRAS3) most related to mRNAsi scores were discovered and a risk model was built. Our model demonstrated a significant prognostic capacity with hazard ratios (HR) ranging from 18.96 to 41.20, P values below 0.0001, and area under the receiver operating characteristic curve (AUC) values of 0.918 in the training set, suggesting high predictive accuracy which was further confirmed by external verification. Individuals with a low four-gene signature score had a favorable outcome and better immune responses. Finally, a nomogram for clinical practice was constructed by integrating the four-gene signature and INSS stage. Conclusions Our findings confirm the influence of CSC features in NB prognosis. The newly developed NB stemness-related four-gene signature prognostic signature could facilitate the prognostic prediction, and the identified hub genes may serve as promising targets for individualized treatments.
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Affiliation(s)
- Yuren Xia
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China
- Department of General Surgery, Tianjin Cancer Hospital Airport Hospital, Tianjin, China
| | - Chaoyu Wang
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China
| | - Xin Li
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China
- Department of Pathology, Tianjin Cancer Hospital Airport Hospital, Tianjin, China
| | - Mingyou Gao
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China
| | - Henry David Jeffry Hogg
- Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK
| | - Thara Tunthanathip
- Division of Neurosurgery, Department of Surgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand
| | - Tim Hulsen
- Data Science & AI Engineering, Philips, Eindhoven, The Netherlands
| | - Xiangdong Tian
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China
| | - Qiang Zhao
- National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China
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Dong Y, Yu X, Song H, Chen Q, Zheng B, Ji X, Xu M, Liu J, Sun X, Wang Q, Ren R, Lu H. Identification of molecular subtypes and prognostic model to reveal immune infiltration and predict prognosis based on immunogenic cell death-related genes in lung adenocarcinoma. Cell Cycle 2023; 22:2566-2583. [PMID: 38164943 PMCID: PMC10936658 DOI: 10.1080/15384101.2023.2300591] [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: 04/13/2023] [Accepted: 12/25/2023] [Indexed: 01/03/2024] Open
Abstract
Immunogenic cell death (ICD) has been increasingly indicated to be related to caners. However, ICD's role in Lung adenocarcinoma (LUAD) is still not well investigated. Clinical data along with associated mRNA expression profiles from LUAD cases were collected in TCGA and GEO databases. 13 ICD-related genes were identified. Relations of ICD-related genes expression with prognosis of patients, tumor immune microenvironment (TIME) was analyzed. Then, candidate genes were identified and the prognostic signature were constructed. Afterwards, one nomogram incorporating those chosen clinical data together with risk scores were built. Finally, the effect of HSP90AA1, one gene of the prognostic signature, on LUAD cell were analyzed. Two clusters were identified, which were designated as the ICD-high or -low subtype according to ICD-related genes levels. ICD-high subgroup showed good prognosis, high immune cell infiltration degrees, and enhanced immune response signaling activity compared with ICD-low subtype. Moreover, we established and verified the risk signature based on ICD-related genes. High risk group predicted poor prognosis of LUAD independently and presented negative association with immune score and immune status. Furthermore, nomogram contributed to the accurate prediction of LUAD prognostic outcome. Finally, HSP90AA1 levels were remarkably elevated within tumor cells in comparison with healthy pulmonary epithelial cells. HSP90α, HSP90AA1 protein product, promoted growth, migration, and invasion of LUAD cells. Molecular subtypes and prognostic model were identified by incorporating ICD-related genes, and it was related to TIME and might be adopted for the accurate prediction of LUAD prognosis.
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Affiliation(s)
- Yinying Dong
- Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiao Yu
- Department of Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Hao Song
- Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Qingfeng Chen
- Breast Disease Diagnosis and Treatment Center, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Bin Zheng
- Department of Neurosurgery, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, China
| | - Xiaomeng Ji
- Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Mingjin Xu
- Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Jian Liu
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiangyin Sun
- Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Qiuxiao Wang
- Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Ruimei Ren
- Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Haijun Lu
- Department of Radiation Oncology, The Affiliated Hospital of Qingdao University, Qingdao, China
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Wu R, Ma R, Duan X, Zhang J, Li K, Yu L, Zhang M, Liu P, Wang C. Identification of specific prognostic markers for lung squamous cell carcinoma based on tumor progression, immune infiltration, and stem index. Front Immunol 2023; 14:1236444. [PMID: 37841237 PMCID: PMC10570622 DOI: 10.3389/fimmu.2023.1236444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 09/12/2023] [Indexed: 10/17/2023] Open
Abstract
Introduction Lung squamous cell carcinoma (LUSC) is a unique subform of nonsmall cell lung cancer (NSCLC). The lack of specific driver genes as therapeutic targets leads to worse prognoses in patients with LUSC, even with chemotherapy, radiotherapy, or immune checkpoint inhibitors. Furthermore, research on the LUSC-specific prognosis genes is lacking. This study aimed to develop a comprehensive LUSC-specific differentially expressed genes (DEGs) signature for prognosis correlated with tumor progression, immune infiltration,and stem index. Methods RNA sequencing data for LUSC and lung adenocarcinoma (LUAD) were extracted from The Cancer Genome Atlas (TCGA) data portal, and DEGs analyses were conducted in TCGA-LUSC and TCGA-LUAD cohorts to identify specific DEGs associated with LUSC. Functional analysis and protein-protein interaction network were performed to annotate the roles of LUSC-specific DEGs and select the top 100 LUSC-specific DEGs. Univariate Cox regression and least absolute shrinkage and selection operator regression analyses were performed to select prognosis-related DEGs. Results Overall, 1,604 LUSC-specific DEGs were obtained, and a validated seven-gene signature was constructed comprising FGG, C3, FGA, JUN, CST3, CPSF4, and HIST1H2BH. FGG, C3, FGA, JUN, and CST3 were correlated with poor LUSC prognosis, whereas CPSF4 and HIST1H2BH were potential positive prognosis markers in patients with LUSC. Receiver operating characteristic analysis further confirmed that the genetic profile could accurately estimate the overall survival of LUSC patients. Analysis of immune infiltration demonstrated that the high risk (HR) LUSC patients exhibited accelerated tumor infiltration, relative to low risk (LR) LUSC patients. Molecular expressions of immune checkpoint genes differed significantly between the HR and LR cohorts. A ceRNA network containing 19 lncRNAs, 50 miRNAs, and 7 prognostic DEGs was constructed to demonstrate the prognostic value of novel biomarkers of LUSC-specific DEGs based on tumor progression, stemindex, and immune infiltration. In vitro experimental models confirmed that LUSC-specific DEG FGG expression was significantly higher in tumor cells and correlated with immune tumor progression, immune infiltration, and stem index. In vitro experimental models confirmed that LUSC-specific DEG FGG expression was significantly higher in tumor cells and correlated with immune tumor progression, immune infiltration, and stem index. Conclusion Our study demonstrated the potential clinical implication of the 7- DEGs signature for prognosis prediction of LUSC patients based on tumor progression, immune infiltration, and stem index. And the FGG could be an independent prognostic biomarker of LUSC promoting cell proliferation, migration, invasion, THP-1 cell infiltration, and stem cell maintenance.
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Affiliation(s)
- Rihan Wu
- School of Life Science, Inner Mongolia University, Hohhot, China
- The Department of Oncology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China
| | - Ru Ma
- School of Life Science, Inner Mongolia University, Hohhot, China
| | - Xiaojun Duan
- School of Life Science, Inner Mongolia University, Hohhot, China
- School of Basic Medicine, Inner Mongolia Medical University, Hohhot, China
| | - Jiandong Zhang
- School of Life Science, Inner Mongolia University, Hohhot, China
| | - Kexin Li
- School of Life Science, Inner Mongolia University, Hohhot, China
| | - Lei Yu
- School of Life Science, Inner Mongolia University, Hohhot, China
| | - Mingyang Zhang
- School of Life Science, Inner Mongolia University, Hohhot, China
| | - Pengxia Liu
- School of Life Science, Inner Mongolia University, Hohhot, China
| | - Changshan Wang
- School of Life Science, Inner Mongolia University, Hohhot, China
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Mogenet A, Finetti P, Denicolai E, Greillier L, Boudou-Rouquette P, Goldwasser F, Lumet G, Ceccarelli M, Birnbaum D, Bedognetti D, Mamessier E, Barlesi F, Bertucci F, Tomasini P. Immunologic constant of rejection as a predictive biomarker of immune checkpoint inhibitors efficacy in non-small cell lung cancer. J Transl Med 2023; 21:637. [PMID: 37726776 PMCID: PMC10507965 DOI: 10.1186/s12967-023-04463-2] [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: 07/24/2023] [Accepted: 08/22/2023] [Indexed: 09/21/2023] Open
Abstract
BACKGROUND Anti-PD1/PDL1 immune checkpoint inhibitors (ICI) transformed the prognosis of patients with advanced non-small cell lung cancer (NSCLC). However, the response rate remains disappointing and toxicity may be life-threatening, making urgent identification of biomarkers predictive for efficacy. Immunologic Constant of Rejection signature (ICR) is a 20-gene expression signature of cytotoxic immune response with prognostic value in some solid cancers. Our objective was to assess its predictive value for benefit from anti-PD1/PDL1 in patients with advanced NSCLC. METHODS We retrospectively profiled 44 primary tumors derived from NSCLC patients treated with ICI as single-agent in at least the second-line metastatic setting. Transcriptomic analysis was performed using the nCounter® analysis system and the PanCancer Immune Profiling Panel. We then pooled our data with clinico-biological data from four public gene expression data sets, leading to a total of 162 NSCLC patients treated with single-agent anti-PD1/PDL1. ICR was applied to all samples and correlation was searched between ICR classes and the Durable Clinical Benefit (DCB), defined as stable disease or objective response according to RECIST 1.1 for a minimum of 6 months after the start of ICI. RESULTS The DCB rate was 29%; 22% of samples were classified as ICR1, 30% ICR2, 22% ICR3, and 26% ICR4. These classes were not associated with the clinico-pathological variables, but showed enrichment from ICR1 to ICR4 in quantitative/qualitative markers of immune response. ICR2-4 class was associated with a 5.65-fold DCB rate when compared with ICR1 class. In multivariate analysis, ICR classification remained associated with DCB, independently from PDL1 expression and other predictive immune signatures. By contrast, it was not associated with disease-free survival in 556 NSCLC TCGA patients untreated with ICI. CONCLUSION The 20-gene ICR signature was independently associated with benefit from anti-PD1/PDL1 ICI in patients with advanced NSCLC. Validation in larger retrospective and prospective series is warranted.
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Affiliation(s)
- Alice Mogenet
- Multidisciplinary Oncology and Therapeutic Innovations Department, Aix Marseille Univ, APHM, INSERM, CNRS, CRCM, Hôpital Nord, Marseille, France
| | - Pascal Finetti
- Centre de Recherche en Cancérologie de Marseille (CRCM), INSERM UMR1068, CNRS UMR725, Laboratoire d'Oncologie Prédictive, Aix Marseille Univ, Marseille, France
| | - Emilie Denicolai
- Centre de Recherche en Cancérologie de Marseille (CRCM), INSERM UMR1068, CNRS UMR725, Laboratoire d'Oncologie Prédictive, Aix Marseille Univ, Marseille, France
| | - Laurent Greillier
- Multidisciplinary Oncology and Therapeutic Innovations Department, Aix Marseille Univ, APHM, INSERM, CNRS, CRCM, Hôpital Nord, Marseille, France
| | - Pascaline Boudou-Rouquette
- Department of Medical Oncology, Cochin Hospital, AP-HP, Paris, France-University of Paris Descartes, ARIANE, CARPEM, Paris, France
| | - François Goldwasser
- Department of Medical Oncology, Cochin Hospital, AP-HP, Paris, France-University of Paris Descartes, ARIANE, CARPEM, Paris, France
| | - Gwenael Lumet
- Centre de Recherche en Cancérologie de Marseille (CRCM), INSERM UMR1068, CNRS UMR725, Laboratoire d'Oncologie Prédictive, Aix Marseille Univ, Marseille, France
| | - Michele Ceccarelli
- Sylvester Comprehensive Cancer Center, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Daniel Birnbaum
- Centre de Recherche en Cancérologie de Marseille (CRCM), INSERM UMR1068, CNRS UMR725, Laboratoire d'Oncologie Prédictive, Aix Marseille Univ, Marseille, France
| | - Davide Bedognetti
- Division of Translational Medicine, Research Branch, Sidra Medicine, Doha, Qatar
- Department of Internal Medicine and Medical Specialties, University of Genoa, Genoa, Italy
| | - Emilie Mamessier
- Centre de Recherche en Cancérologie de Marseille (CRCM), INSERM UMR1068, CNRS UMR725, Laboratoire d'Oncologie Prédictive, Aix Marseille Univ, Marseille, France
| | - Fabrice Barlesi
- Paris-Saclay University and Medical Oncology, Gustave Roussy, Cancer Campus, Villejuif, France
| | - François Bertucci
- Centre de Recherche en Cancérologie de Marseille (CRCM), INSERM UMR1068, CNRS UMR725, Laboratoire d'Oncologie Prédictive, Aix Marseille Univ, Marseille, France.
- Department of Medical Oncology, Institut Paoli-Calmettes, Aix Marseille Univ, 232, Bd de Sainte-Marguerite, 13009, Marseille, France.
| | - Pascale Tomasini
- Multidisciplinary Oncology and Therapeutic Innovations Department, Aix Marseille Univ, APHM, INSERM, CNRS, CRCM, Hôpital Nord, Marseille, France
- Centre de Recherche en Cancérologie de Marseille (CRCM), INSERM UMR1068, CNRS UMR725, Laboratoire d'Oncologie Prédictive, Aix Marseille Univ, Marseille, France
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9
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Hong Y, Xia Z, Sun Y, Lan Y, Di T, Yang J, Sun J, Qiu M, Luo Q, Yang D. A Comprehensive Pan-Cancer Analysis of the Regulation and Prognostic Effect of Coat Complex Subunit Zeta 1. Genes (Basel) 2023; 14:genes14040889. [PMID: 37107648 PMCID: PMC10137353 DOI: 10.3390/genes14040889] [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: 02/14/2023] [Revised: 03/26/2023] [Accepted: 04/08/2023] [Indexed: 04/29/2023] Open
Abstract
The Coatomer protein complex Zeta 1 (COPZ1) has been reported to play an essential role in maintaining the survival of some types of tumors. In this study, we sought to explore the molecular characteristics of COPZ1 and its clinical prognostic value through a pan-cancers bioinformatic analysis. We found that COPZ1 was extremely prevalent in a variety of cancer types, and high expression of COPZ1 was linked to poor overall survival in many cancers, while low expression in LAML and PADC was correlated with tumorigenesis. Besides, the CRISPR Achilles' knockout analysis revealed that COPZ1 was vital for many tumor cells' survival. We further demonstrated that the high expression level of COPZ1 in tumors was regulated in multi-aspects, including abnormal CNV, DNA-methylation, transcription factor and microRNAs. As for the functional exploration of COPZ1, we found a positive relationship between COPZ1's expression and stemness and hypoxia signature, especially the contribution of COPZ1 on EMT ability in SARC. GSEA analysis revealed that COPZ1 was associated with many immune response pathways. Further investigation demonstrated that COPZ expression was negatively correlated with immune score and stromal score, and low expression of COPZ1 has been associated to more antitumor immune cell infiltration and pro-inflammatory cytokines. The further analysis of COPZ1 expression and anti-inflammatory M2 cells showed a consistent result. Finally, we verified the expression of COPZ1 in HCC cells, and proved its ability of sustaining tumor growth and invasion with biological experiments. Our study provides a multi-dimensional pan-cancer analysis of COPZ and demonstrates that COPZ1 can serve as both a prospective target for the treatment of cancer and a prognostic marker for a variety of cancer types.
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Affiliation(s)
- Ye Hong
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
- Department of Pediatric Oncology, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China
| | - Zengfei Xia
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
- Department of Experimental Research, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China
| | - Yuting Sun
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
- Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China
| | - Yingxia Lan
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
- Department of Pediatric Oncology, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China
| | - Tian Di
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
- Department of Experimental Research, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China
| | - Jing Yang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
- Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China
| | - Jian Sun
- Department of Clinical Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510060, China
| | - Miaozhen Qiu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
- Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China
| | - Qiuyun Luo
- Department of Cancer Research, The Eighth Affiliated Hospital of Sun Yat-Sen University, Shenzhen 518033, China
| | - Dajun Yang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
- Department of Experimental Research, Sun Yat-Sen University Cancer Center, Guangzhou 510060, China
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10
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Li Z, Jin C, Lu X, Zhang Y, Zhang Y, Wen J, Liu Y, Liu X, Li J. Construction of a novel mRNAsi-related risk model for predicting prognosis and immunotherapy response in osteosarcoma. ANNALS OF TRANSLATIONAL MEDICINE 2023; 11:61. [PMID: 36819514 PMCID: PMC9929782 DOI: 10.21037/atm-22-6011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 01/06/2023] [Indexed: 01/31/2023]
Abstract
Background Targeting cancer stem cells (CSC) may represent a future therapeutic direction for osteosarcoma (OS), which mainly relies on the identification of CSC markers. This study aimed to classify OS based on messenger ribonucleic acid (mRNA) stemness indices (mRNAsi) and construct a mRNAsi-related risk model to predict the prognosis of OS. Methods The one-class logistic regression (OCLR) algorithm was applied to the RNA- sequencing (seq) data of human embryonic stem cells (hESC) and induced pluripotent stem cell (iPSC) lines to calculate mRNAsi. Weighted gene co-expression network analysis (WGCNA) was performed on data obtained from the TARGET database to screen the mRNAsi-related genes. Univariate Cox regression analysis was implemented to screen mRNAsi-related genes with prognostic significance for consensus clustering of OS. The least absolute shrinkage and selection operator (LASSO) and COX regression analysis were conducted to construct a risk model based on mRNAsi-related genes. Results Six gene modules were identified in the TARGET database. The yellow module showed the strongest negative correlation with mRNAsi and the strongest significant positive correlation with the immune score and stromal score. OS was divided into three molecular subtypes with significant survival differences based on 73 mRNAsi-related genes with prognostic value for OS. The survival rate was ranked as C3 < C1 < C2 from low to high. The levels of immune components in C2 was significantly higher than those in C1 and C3. HSD11B2, GBP1, RNF130, APBB1IP, and NPC2 in the yellow module were used as variables for building the mRNAsi-related risk model. The survival rate of the high-risk group (as defined by this model) was significantly higher than that of the low-risk group, and it had significant survival prediction ability in 28 types of cancer. In addition, the mRNAsi-related risk model was superior to the Tumor Immune Dysfunction and Exclusion (TIDE) model in predicting the prognosis and immunotherapy response in all three immunotherapy cohorts. Conclusions This study classified OS and constructed a mRNAsi-related risk model based on mRNAsi-related genes, which provides a potential tool for more accurate risk stratification of OS and prediction of immunotherapy response.
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Affiliation(s)
- Zhe Li
- Department of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chi Jin
- Department of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xinchang Lu
- Department of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yan Zhang
- Department of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yi Zhang
- Department of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jia Wen
- Department of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yongkui Liu
- Department of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoting Liu
- Department of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jiazhen Li
- Department of Orthopaedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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11
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Zuo Y, Leng G, Leng P. Identification and validation of molecular subtype and prognostic signature for lung adenocarcinoma based on neutrophil extracellular traps. Pathol Oncol Res 2023; 29:1610899. [PMID: 37143472 PMCID: PMC10151567 DOI: 10.3389/pore.2023.1610899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 03/27/2023] [Indexed: 05/06/2023]
Abstract
Background: Neutrophil Extracellular Traps (NETs) are fibrous networks made of DNA-histone complexes and proteins protruded from activated neutrophils. Accumulating evidences have highlighted the vital role of NETs in tumor progression and diffusion. However, limited systematic studies regarding the role of NETs in LUAD have been performed. Methods: Differentially expressed NETs-related genes and their mutation landscape were identified with TCGA database. Consensus clustering analysis was performed to determine the NETs-related subtypes of LUAD. LASSO algorithm was employed to construct a prognostic signature. Moreover, GSE30219 and GSE31210 were used as independent validation. We also constructed a lncRNA-miRNA-mRNA regulatory axis with several miRNA and lncRNA databases. Results: Consensus clustering identified two NETs-related clusters in LUAD. High NETs score was correlated with a favorable overall survival, abundant immune cell infiltration, and high activity of immune response signal pathways. Six NET-related genes (G0S2, KCNJ15, S100A12, AKT2, CTSG, and HMGB1) with significant prognostic value were screened to develop a prognostic signature. LUAD patients with low-risk had a significantly favorable overall survival both in the training set and validation set. Moreover, NETs-related risk score and clinical stage could act as an independent prognostic factor for LUAD patients. Significant correlation was obtained between risk score and tumor immune microenvironment. We also identified lncRNA BCYRN1/miR-3664-5p/CTSG regulatory axis that may be involved in the progression of LUAD. Conclusion: We developed two molecular subtypes and a prognostic signature for LUAD based on NETs-related genes. This stratification could provide more evidences for estimating the prognosis and immunotherapy of LAUD patients.
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Affiliation(s)
- Yanhua Zuo
- Department of Pharmacy, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Guangyi Leng
- Laboratory of Drug Metabolism and Pharmacokinetics, Shenyang Pharmaceutical University, Shenyang, China
| | - Ping Leng
- Department of Pharmacy, The Affiliated Hospital of Qingdao University, Qingdao, China
- *Correspondence: Ping Leng,
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12
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Zhang J, Jin H, Pan S, Han C, Sun Q, Han X. Immune checkpoints expression patterns in early-stage triple-negative breast cancer predict prognosis and remodel the tumor immune microenvironment. Front Immunol 2023; 14:1073550. [PMID: 36814908 PMCID: PMC9939840 DOI: 10.3389/fimmu.2023.1073550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 01/16/2023] [Indexed: 02/08/2023] Open
Abstract
Background Currently, targeting immune checkpoint molecules holds great promise for triple-negative breast cancer (TNBC). However, the expression landscape of immune checkpoint genes (ICGs) in TNBC remains largely unknown. Method Herein, we systematically investigated the ICGs expression patterns in 422 TNBC samples. We evaluated the ICGs molecular typing based on the ICGs expression profile and explored the associations between ICGs molecular subtypes and tumor immune characteristics, clinical significance, and response to immune checkpoint inhibitors (ICIs). Results Two ICGs clusters and two ICGs-related gene clusters were determined, which were involved in different survival outcomes, biological roles and infiltration levels of immune cells. We established a quantification system ICGs riskscore (named IRS) to assess the ICGs expression patterns for individuals. TNBC patients with lower IRS were characterized by increased immune cell infiltration, favorable clinical outcomes and high sensitivity to ICIs therapy. We also developed a nomogram model combining clinicopathological variables to predict overall survival in TNBC. Genomic feature analysis revealed that high IRS group presented an increased tumor mutation burden compared with the low IRS group. Conclusion Collectively, dissecting the ICGs expression patterns not only provides a new insight into TNBC subtypes but also deepens the understanding of ICGs in the tumor immune microenvironment.
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Affiliation(s)
- Jinguo Zhang
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China.,Department of Medical Oncology, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, China
| | - Hongwei Jin
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China.,Department of Medical Oncology, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, China.,School of Medical Oncology, Anhui Medical University, Hefei, China
| | - Shuaikang Pan
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China.,School of Medical Oncology, Wan Nan Medical College, Wuhu, China
| | - Chaoqiang Han
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China
| | - Qingqing Sun
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China.,Department of Medical Oncology, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, China.,School of Medical Oncology, Anhui Medical University, Hefei, China
| | - Xinghua Han
- Department of Medical Oncology, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei, China.,Department of Medical Oncology, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, China.,School of Medical Oncology, Anhui Medical University, Hefei, China
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13
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Zhan X, Feng S, Zhou X, Liao W, Zhao B, Yang Q, Tan Q, Shen J. Immunotherapy response and microenvironment provide biomarkers of immunotherapy options for patients with lung adenocarcinoma. Front Genet 2022; 13:1047435. [PMID: 36386793 PMCID: PMC9640754 DOI: 10.3389/fgene.2022.1047435] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 10/17/2022] [Indexed: 11/30/2022] Open
Abstract
Background: Immunotherapy has been a promising approach option for lung cancer. Method: All the open-accessed data was obtained from the Cancer Genome Atlas (TCGA) database. All the analysis was conducted using the R software analysis. Results: Firstly, the genes differentially expressed in lung cancer immunotherapy responders and non-responders were identified. Then, the lung adenocarcinoma immunotherapy-related genes were determined by LASSO logistic regression and SVM-RFE, respectively. A total of 18 immunotherapy response-related genes were included in our investigation. Subsequently, we constructed the logistics score model. Patients with high logistics score had a better clinical effect on immunotherapy, with 63.2% of patients responding to immunotherapy, while only 12.1% of patients in the low logistics score group responded to immunotherapy. Moreover, we found that pathways related to immunotherapy were mainly enriched in metabolic pathways such as fatty acid metabolism, bile acid metabolism, oxidative phosphorylation, and carcinogenic pathways such as KRAS signaling. Logistics score was positively correlated with NK cells activated, Mast cells resting, Monocytes, Macrophages M2, dendritic cells resting, dendritic cells activated and eosinophils, while was negatively related to Tregs, macrophages M0, macrophages M1, and mast cells activated. In addition, ERVH48-1 was screened for single-cell exploration. The expression of ERVH48-1 increased in patients with distant metastasis, and ERVH48-1 was associated with pathways such as pancreas beta cells, spermatogenesis, G2M checkpoints and KRAS signaling. The result of quantitative real-time PCR showed that ERVH48-1 was upregulated in lung cancer cells. Conclusion: Our study developed an effective signature to predict the immunotherapy response of lung cancer patients.
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Affiliation(s)
- Xue Zhan
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Shihan Feng
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Xutao Zhou
- Department of Oncology, Jiulongpo Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Wei Liao
- Department of Oncology, Jiulongpo Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Bin Zhao
- Department of Oncology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China
| | - Qian Yang
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Qi Tan
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
| | - Jian Shen
- Chongqing Key Laboratory of Traditional Chinese Medicine for Prevention and Cure of Metabolic Diseases, College of Traditional Chinese Medicine, Chongqing Medical University, Chongqing, China
- *Correspondence: Jian Shen,
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14
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Hou S, Xu H, Liu S, Yang B, Li L, Zhao H, Jiang C. Integrated Bioinformatics Analysis Identifies a New Stemness Index-Related Survival Model for Prognostic Prediction in Lung Adenocarcinoma. Front Genet 2022; 13:860268. [PMID: 35464867 PMCID: PMC9026767 DOI: 10.3389/fgene.2022.860268] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 03/07/2022] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Lung adenocarcinoma (LUAD) is one of the most lethal malignancies and is currently lacking in effective biomarkers to assist in diagnosis and therapy. The aim of this study is to investigate hub genes and develop a risk signature for predicting prognosis of LUAD patients. METHODS RNA-sequencing data and relevant clinical data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was performed to identify hub genes associated with mRNA expression-based stemness indices (mRNAsi) in TCGA. We utilized LASSO Cox regression to assemble our predictive model. To validate our predictive model, me applied it to an external cohort. RESULTS mRNAsi index was significantly associated with the tissue type of LUAD, and high mRNAsi scores may have a protective influence on survival outcomes seen in LUAD patients. WGCNA indicated that the turquoise module was significantly correlated with the mRNAsi. We identified a 9-gene signature (CENPW, MCM2, STIL, RACGAP1, ASPM, KIF14, ANLN, CDCA8, and PLK1) from the turquoise module that could effectively identify a high-risk subset of these patients. Using the Kaplan-Meier survival curve, as well as the time-dependent receiver operating characteristic (tdROC) analysis, we determined that this gene signature had a strong predictive ability (AUC = 0.716). By combining the 9-gene signature with clinicopathological features, we were able to design a predictive nomogram. Finally, we additionally validated the 9-gene signature using two external cohorts from GEO and the model proved to be of high value. CONCLUSION Our study shows that the 9-gene mRNAsi-related signature can predict the prognosis of LUAD patient and contribute to decisions in the treatment and prevention of LUAD patients.
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Affiliation(s)
- Shaohui Hou
- Department of Thoracic Surgery, Tianjin Union Medical Center, Nankai University, Tianjin, China
| | - Hongrui Xu
- Department of Thoracic Surgery, Tianjin Union Medical Center, Nankai University, Tianjin, China
| | - Shuzhong Liu
- Department of Thoracic Surgery, Tianjin Union Medical Center, Nankai University, Tianjin, China
| | - Bingjun Yang
- Department of Thoracic Surgery, Tianjin Union Medical Center, Nankai University, Tianjin, China
| | - Li Li
- Department of Thoracic Surgery, Tianjin Union Medical Center, Nankai University, Tianjin, China
| | - Hui Zhao
- Department of Thoracic Surgery, Tianjin Union Medical Center, Nankai University, Tianjin, China
| | - Chunyang Jiang
- Department of Thoracic Surgery, Tianjin Union Medical Center, Nankai University, Tianjin, China
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