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Zhang X, Wu L, Jia L, Hu X, Yao Y, Liu H, Ma J, Wang W, Li L, Chen K, Liu B. The implication of integrative multiple RNA modification-based subtypes in gastric cancer immunotherapy and prognosis. iScience 2024; 27:108897. [PMID: 38318382 PMCID: PMC10839690 DOI: 10.1016/j.isci.2024.108897] [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: 07/28/2023] [Revised: 10/28/2023] [Accepted: 01/09/2024] [Indexed: 02/07/2024] Open
Abstract
Previous studies have focused on the impact of individual RNA modifications on tumor development. This study comprehensively investigated the effects of multiple RNA modifications, including m6A, alternative polyadenylation, pseudouridine, adenosine-to-inosine editing, and uridylation, on gastric cancer (GC). By analyzing 1,946 GC samples from eleven independent cohorts, we identified distinct clusters of RNA modification genes with varying survival rates and immunological characteristics. We assessed the chromatin activity of these RNA modification clusters through regulon enrichment analysis. A prognostic model was developed using Stepwise Regression and Random Survival Forest algorithms and validated in ten independent datasets. Notably, the low-risk group showed a more favorable prognosis and positive response to immune checkpoint blockade therapy. Single-cell RNA sequencing confirmed the abundant expression of signature genes in B cells and plasma cells. Overall, our findings shed light on the potential significance of multiple RNA modifications in GC prognosis, stemness development, and chemotherapy resistance.
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Affiliation(s)
- Xiangnan Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Liuxing Wu
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Liqing Jia
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Xin Hu
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Yanxin Yao
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Huahuan Liu
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Junfu Ma
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Wei Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Lian Li
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Ben Liu
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
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Zheng L, Chen J, Ye W, Fan Q, Chen H, Yan H. An individualized stemness-related signature to predict prognosis and immunotherapy responses for gastric cancer using single-cell and bulk tissue transcriptomes. Cancer Med 2024; 13:e6908. [PMID: 38168907 PMCID: PMC10807574 DOI: 10.1002/cam4.6908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 12/01/2023] [Accepted: 12/22/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Currently, many stemness-related signatures have been developed for gastric cancer (GC) to predict prognosis and immunotherapy outcomes. However, due to batch effects, these signatures cannot accurately analyze patients one by one, rendering them impractical in real clinical scenarios. Therefore, we aimed to develop an individualized and clinically applicable signature based on GC stemness. METHODS Malignant epithelial cells from single-cell RNA-Seq data of GC were used to identify stemness-related signature genes based on the CytoTRACE score. Using two bulk tissue datasets as training data, the enrichment scores of the signature genes were applied to classify samples into two subtypes. Then, using the identified subtypes as criteria, we developed an individualized stemness-related signature based on the within-sample relative expression orderings of genes. RESULTS We identified 175 stemness-related signature genes, which exhibited significantly higher AUCell scores in poorly differentiated GCs compared to differentiated GCs. In training datasets, GC samples were classified into two subtypes with significantly different survival times and genomic characteristics. Utilizing the two subtypes, an individualized signature was constructed containing 47 gene pairs. In four independent testing datasets, GC samples classified as high risk exhibited significantly shorter survival times, higher infiltration of M2 macrophages, and lower immune responses compared to low-risk samples. Moreover, the potential therapeutic targets and corresponding drugs were identified for the high-risk group, such as CD248 targeted by ontuxizumab. CONCLUSIONS We developed an individualized stemness-related signature, which can accurately predict the prognosis and efficacy of immunotherapy for each GC sample.
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Affiliation(s)
- Linyong Zheng
- Fujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, School of Medical Technology and EngineeringFujian Medical UniversityFuzhouChina
| | - Jingyan Chen
- Fujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, School of Medical Technology and EngineeringFujian Medical UniversityFuzhouChina
| | - Wenhai Ye
- Fujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, School of Medical Technology and EngineeringFujian Medical UniversityFuzhouChina
| | - Qi Fan
- Fujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, School of Medical Technology and EngineeringFujian Medical UniversityFuzhouChina
| | - Haifeng Chen
- Department of Gastrointestinal SurgeryFuzhou Second HospitalFuzhouChina
| | - Haidan Yan
- Fujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, School of Medical Technology and EngineeringFujian Medical UniversityFuzhouChina
- Key Laboratory of Ministry of Education for Gastrointestinal Cancer, The School of Basic Medical SciencesFujian Medical UniversityFuzhouChina
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Yuan Q, Lu X, Guo H, Sun J, Yang M, Liu Q, Tong M. Low-density lipoprotein receptor promotes crosstalk between cell stemness and tumor immune microenvironment in breast cancer: a large data-based multi-omics study. J Transl Med 2023; 21:871. [PMID: 38037058 PMCID: PMC10691045 DOI: 10.1186/s12967-023-04699-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: 07/15/2023] [Accepted: 11/03/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND Tumor cells with stemness in breast cancer might facilitate the immune microenvironment's suppression process and led to anti-tumor immune effects. The primary objective of this study was to identify potential targets to disrupt the communication between cancer cell stemness and the immune microenvironment. METHODS In this study, we initially isolated tumor cells with varying degrees of stemness using a spheroid formation assay. Subsequently, we employed RNA-seq and proteomic analyses to identify genes associated with stemness through gene trend analysis. These stemness-related genes were then subjected to pan-cancer analysis to elucidate their functional roles in a broader spectrum of cancer types. RNA-seq data of 3132 patients with breast cancer with clinical data were obtained from public databases. Using the identified stemness genes, we constructed two distinct stemness subtypes, denoted as C1 and C2. We subsequently conducted a comprehensive analysis of the differences between these subtypes using pathway enrichment methodology and immune infiltration algorithms. Furthermore, we identified key immune-related stemness genes by employing lasso regression analysis and a Cox survival regression model. We conducted in vitro experiments to ascertain the regulatory impact of the key gene on cell stemness. Additionally, we utilized immune infiltration analysis and pan-cancer analysis to delineate the functions attributed to this key gene. Lastly, single-cell RNA sequencing (scRNA-seq) was employed to conduct a more comprehensive examination of the key gene's role within the microenvironment. RESULTS In our study, we initially identified a set of 65 stemness-related genes in breast cancer cells displaying varying stemness capabilities. Subsequently, through survival analysis, we pinpointed 41 of these stemness genes that held prognostic significance. We observed that the C2 subtype exhibited a higher stemness capacity compared to the C1 subtype and displayed a more aggressive malignancy profile. Further analysis using Lasso-Cox algorithm identified LDLR as a pivotal immune-related stemness gene. It became evident that LDLR played a crucial role in shaping the immune microenvironment. In vitro experiments demonstrated that LDLR regulated the cell stemness of breast cancer. Immune infiltration analysis and pan-cancer analysis determined that LDLR inhibited the proliferation of immune cells and might promote tumor cell progression. Lastly, in our scRNA-seq analysis, we discovered that LDLR exhibited associations with stemness marker genes within breast cancer tissues. Moreover, LDLR demonstrated higher expression levels in tumor cells compared to immune cells, further emphasizing its relevance in the context of breast cancer. CONCLUSION LDLR is an important immune stemness gene that regulates cell stemness and enhances the crosstalk between breast cancer cancer cell stemness and tumor immune microenvironment.
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Affiliation(s)
- Qihang Yuan
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Xiaona Lu
- Institute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian, China
| | - Hui Guo
- Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Jiaao Sun
- Department of Urology, First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Mengying Yang
- Institute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian, China
| | - Quentin Liu
- Institute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian, China.
- State Key Laboratory of Oncology in South China, Cancer Center, Sun Yat-sen University, Guangzhou, China.
| | - Mengying Tong
- Institute of Cancer Stem Cell, Cancer Center, Dalian Medical University, Dalian, China.
- Department of Ultrasound, First Affiliated Hospital of Dalian Medical University, Dalian, China.
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Wan Q, Ren X, Tang J, Ma K, Deng YP. Cross talk between tumor stemness and microenvironment for prognosis and immunotherapy of uveal melanoma. J Cancer Res Clin Oncol 2023; 149:11951-11968. [PMID: 37420017 DOI: 10.1007/s00432-023-05061-x] [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: 06/02/2023] [Accepted: 06/28/2023] [Indexed: 07/09/2023]
Abstract
PURPOSE Tumor stem cells have emerged as a crucial focus of investigation and a therapeutic target in the context of cancer metastasis and drug resistance. They represent a promising novel approach to address the treatment of uveal melanoma (UVM). METHODS According to the one-class logistic regression (OCLR) approach, we first estimated two stemness indices (mDNAsi and mRNAsi) in a cohort of UVM (n = 80). The prognostic value of stemness indices among four subtypes of UVM (subtype A-D) was investigated. Moreover, univariate Cox regression and Lasso-penalized algorithms were conducted to identify a stemness-associated signature and verify in several independent cohorts. Besides, UVM patients classified into subgroups based on the stemness-associated signature. The differences in clinical outcomes, tumor microenvironment, and probability of immunotherapeutic response were investigated further. RESULTS We observed that mDNAsi was significantly linked with overall survival (OS) time of UVM, but no association was discovered between mRNAsi and OS. Stratification analysis indicated that the prognostic value of mDNAsi was only limited in subtype D of UVM. Besides, we established and verified a prognostic stemness-associated gene signature which can classify UVM patients into subgroups with distinct clinical outcomes, tumor mutation, immune microenvironment, and molecular pathways. The high risk of UVM is more sensitive to immunotherapy. Finally, a well-performed nomogram was constructed to predict the mortality of UVM patients. CONCLUSIONS This study offers a comprehensive examination of UVM stemness characteristics. We discovered mDNAsi-associated signatures improved the prediction capacity of individualized UVM prognosis and indicated prospective targets for stemness-regulated immunotherapy. Analysis of the interaction between stemness and tumor microenvironment may shed light on combinational treatment that targets both stem cell and the tumor microenvironment.
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Affiliation(s)
- Qi Wan
- Department of Ophthalmology, West China Hospital, Sichuan University, Chengdu City, Sichuan Province, China
| | - Xiang Ren
- Department of Ophthalmology, West China Hospital, Sichuan University, Chengdu City, Sichuan Province, China
| | - Jing Tang
- Department of Ophthalmology, West China Hospital, Sichuan University, Chengdu City, Sichuan Province, China
| | - Ke Ma
- Department of Ophthalmology, West China Hospital, Sichuan University, Chengdu City, Sichuan Province, China.
| | - Ying-Ping Deng
- Department of Ophthalmology, West China Hospital, Sichuan University, Chengdu City, Sichuan Province, 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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Mao D, Zhou Z, Chen H, Liu X, Li D, Chen X, He Y, Liu M, Zhang C. Pleckstrin-2 promotes tumour immune escape from NK cells by activating the MT1-MMP-MICA signalling axis in gastric cancer. Cancer Lett 2023; 572:216351. [PMID: 37591356 DOI: 10.1016/j.canlet.2023.216351] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 08/08/2023] [Accepted: 08/13/2023] [Indexed: 08/19/2023]
Abstract
Immune escape is a major challenge in tumour immunotherapy. Pleckstrin-2(PLEK2) plays a critical role in tumour progression, but its role in immune escape in gastric cancer (GC) remains uncharacterized. RNA sequencing was used to explore the differentially expressed genes in a GC cell line that was resistant to the antitumor effect of Natural killer (NK) cells. Apoptosis and the expression of IFN-γ and TNF-α were detected by flow cytometry (FCM). PLEK2 expression was examined by Western blotting and immunohistochemistry (IHC). PLEK2 was upregulated in MGC803R cells that were resistant to the antitumor effect of NK cells. PLEK2 knockout increased the sensitivity of GC cells to NK cell killing. PLEK2 expression was negatively correlated with MICA and positively correlated with MT1-MMP expression both in vitro and in vivo. PLEK2 promoted Sp1 phosphorylation through the PI3K-AKT pathway, thereby upregulating MT1-MMP expression, which ultimately led to MICA shedding. In mouse xenograft models, PLEK2 knockout inhibited intraperitoneal metastasis of GC cells and promoted NK cell infiltration. In summary, PLEK2 suppressed NK cell immune surveillance by promoting MICA shedding, which serves as a potential therapeutic target for GC.
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Affiliation(s)
- Deli Mao
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China
| | - Zhijun Zhou
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China; Department of Medicine, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, United States
| | - Hengxing Chen
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China
| | - Xinran Liu
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China
| | - Dongsheng Li
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China
| | - Xiancong Chen
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China
| | - Yulong He
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China; Department of Gastrointestinal Surgery of the First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan 2nd Road, Guangzhou, 510080, Guangdong, China
| | - Mingyang Liu
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, China.
| | - Changhua Zhang
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China; Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, No. 628 Zhenyuan Road, Shenzhen, 518107, Guangdong, China.
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Tu Y, Mao Z. Identification and Validation of Molecular Subtype and Prognostic Signature for Bladder Cancer Based on Neutrophil Extracellular Traps. Cancer Invest 2023; 41:354-368. [PMID: 36762827 DOI: 10.1080/07357907.2023.2179063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
Neutrophil extracellular traps (NETs) could promote tumor growth and distant metastases. Molecular subtypes of bladder cancer were identified with consensus cluster analysis. A NETs-related prognostic signature was constructed with LASSO cox regression analysis. As a result, we identified three subtypes of bladder cancer, which had a distinct difference in prognosis, immune microenvironment, TIDE score, mRNAsi score and IC50 score. We also developed a prognostic signature based on 5 NETs-related genes, which had a good performance in clinical outcome prediction of bladder cancer. These results may provide more data about the vital role of NETs in bladder cancer.
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Affiliation(s)
- Yaofen Tu
- Department of Urology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China
| | - Zujie Mao
- Department of Urology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, China
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Zhou Z, Saluja AK, Houchen CW, Li M. Replication stress identifies novel molecular classification associated with treatment outcomes in pancreatic cancer. Pancreatology 2023; 23:82-89. [PMID: 36435734 DOI: 10.1016/j.pan.2022.11.008] [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: 10/12/2022] [Revised: 11/17/2022] [Accepted: 11/19/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND Replication stress is a prominent hallmark of tumor cells, which is crucial for maintaining genomic integrity. However, it remains poorly understood whether replication stress can serve as a surrogate biomarker to indicate prognosis and treatment response of pancreatic cancer. METHODS Transcriptomic and clinical data were obtained from The Cancer Genome Atlas and literature. An integrated signature of 18 replication-stress associated genes (termed as REST18) was established using the cox proportional hazards regression analysis. Tumors were sorted into REST18-low and REST18-high groups. Survival analysis, gene set enrichment analysis and composition of immune cells were compared between these tumors. RESULTS Patients with REST18-high tumors showed worse prognoses than those with REST18-low tumors in the TCGA database and the finding is validated in an independent cohort of pancreatic cancer. Comparison of REST18 model and other molecular classifications showed that REST18-high tumors are positively correlated to basal-like or squamous phenotypes, which have higher metastasis potential. DNA repair pathway is enriched in the REST18-high tumors. Analysis of tumor immune microenvironment found that REST18-high tumors are characterized with "immune-cold" features. Univariate and multivariate analysis show that REST18 is an independent risk factor for overall survival and predicts outcomes of chemotherapy in pancreatic cancer. CONCLUSION REST18 is a novel biomarker to indicate prognosis and treatment response of chemotherapy in pancreatic cancer.
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Affiliation(s)
- Zhijun Zhou
- Department of Medicine, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Anuj K Saluja
- Department of Medicine, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Courtney W Houchen
- Department of Medicine, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
| | - Min Li
- Department of Medicine, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
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Ji D, Yang Y, Zhou F, Li C. A nine–consensus–prognostic –gene–based prognostic signature, recognizing the dichotomized subgroups of gastric cancer patients with different clinical outcomes and therapeutic strategies. Front Genet 2022; 13:909175. [PMID: 36226177 PMCID: PMC9550166 DOI: 10.3389/fgene.2022.909175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 08/10/2022] [Indexed: 12/24/2022] Open
Abstract
Background: The increasing prevalence and mortality of gastric cancer (GC) has promoted the urgent need for prognostic signatures to predict the long-term risk and search for therapeutic biomarkers. Methods and materials: A total of 921 GC patients from three GEO cohorts were enrolled in the current study. The GSE15459 and GSE62254 cohorts were used to select the top prognostic gene via the evaluation of the area under the receiver operating characteristic (ROC) curve (AUC) values. The GSE84437 cohort was used as the external validation cohort. Least absolute shrinkage and selector operation (LASSO) regression analysis was applied to reduce the feature dimension and construct the prognostic signature. Furthermore, a nomogram was constructed by integrating the independent prognostic analysis and validated by calibration plot, decision curve analysis and clinical impact curve. The molecular features and response to chemo-/immunotherapy among risk subgroups were evaluated by the “MOVICS” and “ESTAMATE” R packages and the SubMap algorithm. Lauren classification and ACRG molecular subtype were obtained to compare with the risk model. Results: Forty-four prognosis-associated genes were identified with a preset cutoff AUC value of 0.65 in both the GSE62254 and GSE15459 cohorts. With the 10-fold cross validation analysis of LASSO, nine genes were selected to construct the nine-consensus-prognostic-gene signature. The signature showed good prognostic value in the GSE62254 (p < 0.001, HR: 3.81, 95% CI: 2.44–5.956) and GSE15459 (p < 0.001, HR: 2.65, 95% CI: 1.892–3.709) cohorts and the external validation GSE84437 cohort (p < 0.001, HR: 2.06, 95% CI: 1.554–2.735). The nomogram constructed based on two independent predictive factors, tumor stage and the signature, predicted events tightly consistent with the actual (Hosmer–Lemeshow p value: 1-year, 0.624; 3-years, 0.795; 5-years, 0.824). For the molecular features, we observed the activation of apical junction, epithelial mesenchymal transition, and immune pathways in the high-risk group, while in the low-risk group, cell cycle associated G2M, E2F and MYC target pathways were activated. Based on the results we obtained, we indicated that gastric patients in the low-risk group are more suitable for 5-fluorouracil therapy, while high-risk group patients are more suitable for anti-CTLA4 immunotherapy, these results need more support in the further studies. After compare with proposed molecular subtypes, we realized that the nine-consensus prognostic gene signature is a powerful addition to identify the gastric patients with poor prognosis. Conclusion: In summary, we constructed a robust nine-consensus-prognostic-gene signature for the prediction of GC prognosis, which can also predict the personalized treatment of GC patients.
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Affiliation(s)
- Dan Ji
- Department of Basic Medicine, Anhui Medical College, Hefei, Anhui, China
| | - Yang Yang
- Huangshan Health Vocational College, Huangshan, Anhui, China
| | - Fei Zhou
- Department of Basic Medicine, Anhui Medical College, Hefei, Anhui, China
| | - Chao Li
- Department of General Surgery, Hefei First People’s Hospital, Hefei, China
- *Correspondence: Chao Li,
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10
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Zheng H, Liu H, Li H, Dou W, Wang J, Zhang J, Liu T, Wu Y, Liu Y, Wang X. Characterization of stem cell landscape and identification of stemness-relevant prognostic gene signature to aid immunotherapy in colorectal cancer. Stem Cell Res Ther 2022; 13:244. [PMID: 35681225 PMCID: PMC9185878 DOI: 10.1186/s13287-022-02913-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 02/22/2022] [Indexed: 02/08/2023] Open
Abstract
Background It is generally accepted that colorectal cancer (CRC) originates from cancer stem cells (CSCs), which are responsible for CRC progression, metastasis and therapy resistance. The high heterogeneity of CSCs has precluded clinical application of CSC-targeting therapy. Here, we aimed to characterize the stemness landscapes and screen for certain patients more responsive to immunotherapy. Methods Twenty-six stem cell gene sets were acquired from StemChecker database. Consensus clustering algorithm was applied for stemness subtypes identification on 1,467 CRC samples from TCGA and GEO databases. The differences in prognosis, tumor microenvironment (TME) components, therapy responses were evaluated among subtypes. Then, the stemness-risk model was constructed by weighted gene correlation network analysis (WGCNA), Cox regression and random survival forest analyses, and the most important marker was experimentally verified. Results Based on single-sample gene set enrichment analysis (ssGSEA) enrichments scores, CRC patients were classified into three subtypes (C1, C2 and C3). C3 subtype exhibited the worst prognosis, highest macrophages M0 and M2 infiltrations, immune and stromal scores, and minimum sensitivity to immunotherapies, but was more sensitive to drugs like Bosutinib, Docetaxel, Elesclomol, Gefitinib, Lenalidomide, Methotrexate and Sunitinib. The turquoise module was identified by WGCNA that it was most positively correlated with C3 but most negatively with C2, and five hub genes in turquoise module were identified for stemness model construction. CRC patients with higher stemness scores exhibited worse prognosis, more immunosuppressive components in TME and lower immunotherapeutic responses. Additionally, the model’s immunotherapeutic prediction efficacy was further confirmed from two immunotherapy cohorts (anti-PD-L1 in IMvigor210 cohort and anti-PD-1 in GSE78220 cohort). Mechanistically, Gene Set Enrichment Analysis (GSEA) results revealed high stemness score group was enriched in interferon gamma response, interferon alpha response, P53 pathway, coagulation, apoptosis, KRAS signaling upregulation, complement, epithelial–mesenchymal transition (EMT) and IL6-mediated JAK-STAT signaling gene sets. Conclusions Our study characterized three stemness-related subtypes with distinct prognosis and TME patterns in CRC patients, and a 5-gene stemness-risk model was constructed by comprehensive bioinformatic analyses. We suggest our stemness model has prospective clinical implications for prognosis evaluation and might facilitate physicians selecting prospective responders for preferential use of current immune checkpoint inhibitors. Supplementary Information The online version contains supplementary material available at 10.1186/s13287-022-02913-0.
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Affiliation(s)
- Hang Zheng
- Department of General Surgery, Peking University First Hospital, Peking University, Beijing, People's Republic of China
| | - Heshu Liu
- Department of Oncology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Huayu Li
- Department of General Surgery, Peking University First Hospital, Peking University, Beijing, People's Republic of China
| | - Weidong Dou
- Department of General Surgery, Peking University First Hospital, Peking University, Beijing, People's Republic of China
| | - Jingui Wang
- Department of General Surgery, Peking University First Hospital, Peking University, Beijing, People's Republic of China
| | - Junling Zhang
- Department of General Surgery, Peking University First Hospital, Peking University, Beijing, People's Republic of China
| | - Tao Liu
- Department of General Surgery, Peking University First Hospital, Peking University, Beijing, People's Republic of China
| | - Yingchao Wu
- Department of General Surgery, Peking University First Hospital, Peking University, Beijing, People's Republic of China
| | - Yucun Liu
- Department of General Surgery, Peking University First Hospital, Peking University, Beijing, People's Republic of China
| | - Xin Wang
- Department of General Surgery, Peking University First Hospital, Peking University, Beijing, People's Republic of China.
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11
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Nie C, Zhai J, Wang Q, Zhu X, Xiang G, Liu C, Liu T, Wang W, Wang Y, Zhao Y, Tian W, Xue Y, Zhou H. Comprehensive Analysis of an Individualized Immune-Related lncRNA Pair Signature in Gastric Cancer. Front Cell Dev Biol 2022; 10:805623. [PMID: 35273959 PMCID: PMC8902466 DOI: 10.3389/fcell.2022.805623] [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: 10/30/2021] [Accepted: 02/02/2022] [Indexed: 12/26/2022] Open
Abstract
Long noncoding RNAs (lncRNAs) have diverse functions, including immune regulation. Increasing studies have reported immune-related lncRNAs in the prognosis of multiple cancers. In this study, we developed an individualized signature containing 13 immune-related lncRNA pairs (IRLPs) which could predict the overall survival, disease-free survival, progression-free survival, and disease-specific survival of gastric cancer (GC) patients in The Cancer Genome Atlas (TCGA) cohort, and internal and external validations, signature comparisons, and subgroup analyses further confirmed its superiority, stability, and generalizability. Notably, this signature also showed good applicability in discriminating the prognosis of pan-cancer patients. Then, we constructed and validated a nomogram for overall survival based on the signature and clinical factors, which allowed more accurate predictions of GC prognosis. In addition, we revealed that the low survival rate of patients with high-risk scores may be due to their aggressive clinical features, enriched cancer-related signaling pathways, the infiltration of specific immunosuppressive cells, and low tumor mutation burden. We further predicted obviously worse immunotherapeutic responses in the high-risk groups and identified some candidate compounds targeting GC risk group differentiation. This signature based on the IRLPs may be promising for predicting the survival outcomes and immunotherapeutic responses of GC patients in clinical practice.
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Affiliation(s)
- Chuang Nie
- Department of Epidemiology, College of Public Health, Harbin Medical University, Harbin, China
| | - Jiabao Zhai
- Department of Epidemiology, College of Public Health, Harbin Medical University, Harbin, China
| | - Qi Wang
- Department of Epidemiology, College of Public Health, Harbin Medical University, Harbin, China
| | - Xiaojie Zhu
- Department of Epidemiology, College of Public Health, Harbin Medical University, Harbin, China
| | - Guanghui Xiang
- Department of Epidemiology, College of Public Health, Harbin Medical University, Harbin, China
| | - Chang Liu
- Department of Epidemiology, College of Public Health, Harbin Medical University, Harbin, China
| | - Tianyu Liu
- Department of Epidemiology, College of Public Health, Harbin Medical University, Harbin, China
| | - Wanyu Wang
- Department of Epidemiology, College of Public Health, Harbin Medical University, Harbin, China
| | - Yimin Wang
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Yashuang Zhao
- Department of Epidemiology, College of Public Health, Harbin Medical University, Harbin, China
| | - Wenjing Tian
- Department of Epidemiology, College of Public Health, Harbin Medical University, Harbin, China
| | - Yingwei Xue
- Department of Gastroenterological Surgery, Harbin Medical University Cancer Hospital, Harbin, China
| | - Haibo Zhou
- Department of Epidemiology, College of Public Health, Harbin Medical University, Harbin, China
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12
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Jia X, Chen B, Li Z, Huang S, Chen S, Zhou R, Feng W, Zhu H, Zhu X. Identification of a Four-Gene-Based SERM Signature for Prognostic and Drug Sensitivity Prediction in Gastric Cancer. Front Oncol 2022; 11:799223. [PMID: 35096599 PMCID: PMC8790320 DOI: 10.3389/fonc.2021.799223] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/14/2021] [Indexed: 12/17/2022] Open
Abstract
Background Gastric cancer (GC) is a highly molecular heterogeneous tumor with poor prognosis. Epithelial-mesenchymal transition (EMT) process and cancer stem cells (CSCs) are reported to share common signaling pathways and cause poor prognosis in GC. Considering about the close relationship between these two processes, we aimed to establish a gene signature based on both processes to achieve better prognostic prediction in GC. Methods The gene signature was constructed by univariate Cox and the least absolute shrinkage and selection operator (LASSO) Cox regression analyses by using The Cancer Genome Atlas (TCGA) GC cohort. We performed enrichment analyses to explore the potential mechanisms of the gene signature. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) curves were implemented to assess its prognostic value in TCGA cohort. The prognostic value of gene signature on overall survival (OS), disease-free survival (DFS), and drug sensitivity was validated in different cohorts. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) validation of the prognostic value of gene signature for OS and DFS prediction was performed in the Fudan cohort. Results A prognostic signature including SERPINE1, EDIL3, RGS4, and MATN3 (SERM signature) was constructed to predict OS, DFS, and drug sensitivity in GC. Enrichment analyses illustrated that the gene signature has tight connection with the CSC and EMT processes in GC. Patients were divided into two groups based on the risk score obtained from the formula. The Kaplan-Meier analyses indicated high-risk group yielded significantly poor prognosis compared with low-risk group. Pearson’s correlation analysis indicated that the risk score was positively correlated with carboplatin and 5-fluorouracil IC50 of GC cell lines. Multivariate Cox regression analyses showed that the gene signature was an independent prognostic factor for predicting GC patients’ OS, DFS, and susceptibility to adjuvant chemotherapy. Conclusions Our SERM prognostic signature is of great value for OS, DFS, and drug sensitivity prediction in GC, which may give guidance to the development of targeted therapy for CSC- and EMT-related gene in the future.
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Affiliation(s)
- Xiya Jia
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Bing Chen
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Ziteng Li
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Shenglin Huang
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Siyuan Chen
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Runye Zhou
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Wanjing Feng
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Hui Zhu
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
| | - Xiaodong Zhu
- Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College of Fudan University, Shanghai, China
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13
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Mao D, Xu R, Chen H, Chen X, Li D, Song S, He Y, Wei Z, Zhang C. Cross-Talk of Focal Adhesion-Related Gene Defines Prognosis and the Immune Microenvironment in Gastric Cancer. Front Cell Dev Biol 2021; 9:716461. [PMID: 34660578 PMCID: PMC8517448 DOI: 10.3389/fcell.2021.716461] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 09/14/2021] [Indexed: 12/11/2022] Open
Abstract
Background: Focal adhesion, as the intermediary between tumor cells and extracellular matrix communication, plays a variety of roles in tumor invasion, migration, and drug resistance. However, the potential role of focal adhesion-related genes in the microenvironment, immune cell infiltration, and drug sensitivity of gastric cancer (GC) has not yet been revealed. Methods: The genetic and transcriptional perspectives of focal adhesion-related genes were systematically analyzed. From a genetic perspective, the focal adhesion index (FAI) was constructed based on 18 prognosis-related focus adhesion-related genes to evaluate the immune microenvironment and drug sensitivity. Then three prognosis-related genes were used for consistent clustering to identify GC subtypes. Finally, use FLT1, EGF, COL5A2, and M2 macrophages to develop risk signatures, and establish a nomogram together with clinicopathological characteristics. Results: Mutations in the focal adhesion-related gene affect the survival time and clinical characteristics of GC patients. FAI has been associated with a shorter survival time, immune signaling pathways, M2 macrophage infiltration, epithelial-mesenchymal transition (EMT) signaling, and diffuse type of GC. FAI recognizes ALK, cell cycle, and BMX signaling pathways inhibitors as sensitive agents for the treatment of GC. FLT1, EGF, and COL5A2 may distinguish GC subtypes. The established risk signature is of great significance to the prognostic evaluation of GC based on FLT1, EGF, and COL5A2 and M2 macrophage expression. Conclusion: The focal adhesion-related gene is a potential biomarker for the evaluation of the immune microenvironment and prognosis. This work emphasizes the potential impact of the focal adhesion pathway in GC therapy and highlights its guiding role in prognostic evaluation.
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Affiliation(s)
- Deli Mao
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.,Department of Gastrointestinal Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Rui Xu
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.,Department of Gastrointestinal Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Hengxing Chen
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Xiancong Chen
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Dongsheng Li
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Shenglei Song
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Yulong He
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Zhewei Wei
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Changhua Zhang
- Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.,Guangdong Provincial Key Laboratory of Digestive Cancer Research, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
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14
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Jiang Q, Chen L, Chen H, Tang Z, Liu F, Sun Y. Integrated Analysis of Stemness-Related LncRNAs Helps Predict the Immunotherapy Responsiveness of Gastric Cancer Patients. Front Cell Dev Biol 2021; 9:739509. [PMID: 34589496 PMCID: PMC8473797 DOI: 10.3389/fcell.2021.739509] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Accepted: 08/16/2021] [Indexed: 12/24/2022] Open
Abstract
The immune microenvironment plays a critical role in tumor biology. As a critical feature of cancers, stemness is acknowledged as a contributor to the development of drug resistance in gastric cancers (GCs). Long non-coding RNAs (lncRNAs) have been revealed to participate in this process. In this study, we aimed to develop a stemness-related lncRNA signature (SRLncSig) with guiding significance for immunotherapy. Three cohorts (TCGA, Zhongshan, and IMvigor210) were enrolled for analysis. A list of stemness-related lncRNAs (SRlncRNAs) was collected by co-expression strategy under the threshold of coefficient value >0.35 and p-value < 0.05. Cox and Lasso regression analysis was further applied to find out the SRlncRNAs with prognosis-predictive value to establish the SRLncSig in the TCGA cohort. IPS and TIDE algorithms were further applied to predict the efficacy of SRLncSig in TCGA and Zhongshan cohorts. IMvigor210 was composed of patients with clinical outcomes of immunotherapy. The results indicated that SRLncSig not only was confirmed as an independent risk factor for GCs but also identified as a robust indicator for immunotherapy. The patient with a lower SRLncSig score was more likely to benefit from immunotherapy, and the results were highly consistent in three cohorts. In conclusion, our study not only could clarify the correlations between stemness and immunotherapy in GC patients but also provided a model to guide the applications of immunotherapy in clinical practice.
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Affiliation(s)
- Quan Jiang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.,Human Phenome Institute, Fudan University, Shanghai, China
| | - Lingli Chen
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hao Chen
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhaoqing Tang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Fenglin Liu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yihong Sun
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
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15
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Wei R, Quan J, Li S, Liu H, Guan X, Jiang Z, Wang X. Integrative Analysis of Biomarkers Through Machine Learning Identifies Stemness Features in Colorectal Cancer. Front Cell Dev Biol 2021; 9:724860. [PMID: 34568334 PMCID: PMC8456021 DOI: 10.3389/fcell.2021.724860] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 08/12/2021] [Indexed: 01/06/2023] Open
Abstract
Background: Cancer stem cells (CSCs), which are characterized by self-renewal and plasticity, are highly correlated with tumor metastasis and drug resistance. To fully understand the role of CSCs in colorectal cancer (CRC), we evaluated the stemness traits and prognostic value of stemness-related genes in CRC. Methods: In this study, the data from 616 CRC patients from The Cancer Genome Atlas (TCGA) were assessed and subtyped based on the mRNA expression-based stemness index (mRNAsi). The correlations of cancer stemness with the immune microenvironment, tumor mutational burden (TMB), and N6-methyladenosine (m6A) RNA methylation regulators were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify the crucial stemness-related genes and modules. Furthermore, a prognostic expression signature was constructed using the Lasso-penalized Cox regression analysis. The signature was validated via multiplex immunofluorescence staining of tissue samples in an independent cohort of 48 CRC patients. Results: This study suggests that high-mRNAsi scores are associated with poor overall survival in stage IV CRC patients. Moreover, the levels of TMB and m6A RNA methylation regulators were positively correlated with mRNAsi scores, and low-mRNAsi scores were characterized by increased immune activity in CRC. The analysis identified 34 key genes as candidate prognosis biomarkers. Finally, a three-gene prognostic signature (PARPBP, KNSTRN, and KIF2C) was explored together with specific clinical features to construct a nomogram, which was successfully validated in an external cohort. Conclusion: There is a unique correlation between CSCs and the prognosis of CRC patients, and the novel biomarkers related to cell stemness could accurately predict the clinical outcomes of these patients.
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Affiliation(s)
- Ran Wei
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jichuan Quan
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shuofeng Li
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hengchang Liu
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xu Guan
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zheng Jiang
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xishan Wang
- Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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