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Cowzer D, Chou JF, Walch H, Keane F, Khalil D, Shia J, Do RKG, Yarmohammadi H, Erinjeri JP, El Dika I, Yaqubie A, Azhari H, Gambarin M, Hajj C, Crane C, Wei AC, Jarnagin W, Solit DB, Berger MF, O'Reilly EM, Schultz N, Chatila W, Capanu M, Abou-Alfa GK, Harding JJ. Clinicogenomic predictors of outcomes in patients with hepatocellular carcinoma treated with immunotherapy. Oncologist 2024:oyae110. [PMID: 38937977 DOI: 10.1093/oncolo/oyae110] [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: 03/08/2024] [Accepted: 04/26/2024] [Indexed: 06/29/2024] Open
Abstract
INTRODUCTION Immune checkpoint inhibitor (ICI) combinations extend overall survival (OS) while anti-PD-1/L1 monotherapy is non-inferior to sorafenib in treatment-naïve, patients with advanced hepatocellular carcinoma (HCC). Clinicogenomic features are posited to influence patient outcomes. METHODS The primary objective of this retrospective study was to define the clinical, pathologic, and genomic factors associated with outcomes to ICI therapy in patients with HCC. Patients with histologically confirmed advanced HCC treated with ICI at Memorial Sloan Kettering Cancer Center from 2012 to 2022 were included. Association between clinical, pathological, and genomic characteristics were assessed with univariable and multivariable Cox regression model for progression-free survival (PFS) and OS. RESULTS Two-hundred and forty-two patients were treated with ICI-based therapy. Patients were predominantly male (82%) with virally mediated HCC (53%) and Child Pugh A score (70%). Median follow-up was 28 months (0.5-78.4). Median PFS for those treated in 1st line, 2nd line and ≥ 3rd line was 4.9 (range: 2.9-6.2), 3.1 (2.3-4.0), and 2.5 (2.1-4.0) months, respectively. Median OS for those treated in 1st line, 2nd line, and ≥ 3rd line was 16 (11-22), 7.5 (6.4-11), and 6.4 (4.6-26) months, respectively. Poor liver function and performance status associated with worse PFS and OS, while viral hepatitis C was associated with favorable outcome. Genetic alterations were not associated with outcomes. CONCLUSION Clinicopathologic factors were the major determinates of outcomes for patients with advanced HCC treated with ICI. Molecular profiling did not aid in stratification of ICI outcomes. Future studies should explore alternative biomarkers such as the level of immune activation or the pretreatment composition of the immune tumor microenvironment.
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Affiliation(s)
- Darren Cowzer
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Joanne F Chou
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Henry Walch
- Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Fergus Keane
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Danny Khalil
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Weill Medical College of Cornell University, New York, NY, United States
| | - Jinru Shia
- Weill Medical College of Cornell University, New York, NY, United States
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Richard K G Do
- Weill Medical College of Cornell University, New York, NY, United States
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Hooman Yarmohammadi
- Weill Medical College of Cornell University, New York, NY, United States
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Joseph P Erinjeri
- Weill Medical College of Cornell University, New York, NY, United States
| | - Imane El Dika
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Weill Medical College of Cornell University, New York, NY, United States
| | - Amin Yaqubie
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Hassan Azhari
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Weill Medical College of Cornell University, New York, NY, United States
| | - Maya Gambarin
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Weill Medical College of Cornell University, New York, NY, United States
| | - Carla Hajj
- Weill Medical College of Cornell University, New York, NY, United States
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Christopher Crane
- Weill Medical College of Cornell University, New York, NY, United States
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Alice C Wei
- Weill Medical College of Cornell University, New York, NY, United States
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York, NY, United States
| | - William Jarnagin
- Weill Medical College of Cornell University, New York, NY, United States
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York, NY, United States
| | - David B Solit
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Weill Medical College of Cornell University, New York, NY, United States
| | - Michael F Berger
- Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Weill Medical College of Cornell University, New York, NY, United States
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Eileen M O'Reilly
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Weill Medical College of Cornell University, New York, NY, United States
| | - Nikolaus Schultz
- Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Weill Medical College of Cornell University, New York, NY, United States
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Walid Chatila
- Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Marinela Capanu
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Ghassan K Abou-Alfa
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Weill Medical College of Cornell University, New York, NY, United States
| | - James J Harding
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Weill Medical College of Cornell University, New York, NY, United States
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Li S, Xu Y, Hu X, Chen H, Xi X, Long F, Rong Y, Wang J, Yuan C, Liang C, Wang F. Crosstalk of non-apoptotic RCD panel in hepatocellular carcinoma reveals the prognostic and therapeutic optimization. iScience 2024; 27:109901. [PMID: 38799554 PMCID: PMC11126946 DOI: 10.1016/j.isci.2024.109901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 03/12/2024] [Accepted: 05/01/2024] [Indexed: 05/29/2024] Open
Abstract
Non-apoptotic regulated cell death (RCD) of tumor cells profoundly affects tumor progression and plays critical roles in determining response to immune checkpoint inhibitors (ICIs). Prognosis-distinctive HCC subtypes were identified by consensus cluster analysis based on the expressions of 507 non-apoptotic RCD genes obtained from databases and literature. Meanwhile, a set of bioinformatic tools was integrated to analyze the differences of the tumor immune microenvironment infiltration, genetic mutation, copy number variation, and epigenetics alternations within two subtypes. Finally, a non-apoptotic RCDRS signature was constructed and its reliability was evaluated in HCC patients' tissues. The high-RCDRS HCC subgroup showed a significantly lower overall survival and less sensitivity to ICIs compared to low-RCDRS subgroup, but higher sensitivity to cisplatin, paclitaxel, and sorafenib. Overall, we established an RCDRS panel consisting of four non-apoptotic RCD genes, which might be a promising predictor for evaluating HCC prognosis, guiding therapeutic decision-making, and ultimately improving patient outcomes.
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Affiliation(s)
- Shuo Li
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Yaqi Xu
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Xin Hu
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Hao Chen
- Department of Pathology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Xiaodan Xi
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Fei Long
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
| | - Yuan Rong
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Forensic Center of Justice, Zhongnan Hospital of Wuhan University, Wuhan China
| | - Jun Wang
- Department of Laboratory Medicine, Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430016, China
| | - Chunhui Yuan
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Department of Laboratory Medicine, Wuhan Children’s Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430016, China
| | - Chen Liang
- Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, No. 169 Donghu Road, Wuchang District, Wuhan 430071, China
| | - Fubing Wang
- Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Center for Single-Cell Omics and Tumor Liquid Biopsy, Zhongnan Hospital of Wuhan University, Wuhan 430071, China
- Wuhan Research Center for Infectious Diseases and Cancer, Chinese Academy of Medical Sciences, Wuhan, China
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Qin S, Xie B, Wang Q, Yang R, Sun J, Hu C, Liu S, Tao Y, Xiao D. New insights into immune cells in cancer immunotherapy: from epigenetic modification, metabolic modulation to cell communication. MedComm (Beijing) 2024; 5:e551. [PMID: 38783893 PMCID: PMC11112485 DOI: 10.1002/mco2.551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 03/24/2024] [Accepted: 04/02/2024] [Indexed: 05/25/2024] Open
Abstract
Cancer is one of the leading causes of death worldwide, and more effective ways of attacking cancer are being sought. Cancer immunotherapy is a new and effective therapeutic method after surgery, radiotherapy, chemotherapy, and targeted therapy. Cancer immunotherapy aims to kill tumor cells by stimulating or rebuilding the body's immune system, with specific efficiency and high safety. However, only few tumor patients respond to immunotherapy and due to the complex and variable characters of cancer immune escape, the behavior and regulatory mechanisms of immune cells need to be deeply explored from more dimensions. Epigenetic modifications, metabolic modulation, and cell-to-cell communication are key factors in immune cell adaptation and response to the complex tumor microenvironment. They collectively determine the state and function of immune cells through modulating gene expression, changing in energy and nutrient demands. In addition, immune cells engage in complex communication networks with other immune components, which are mediated by exosomes, cytokines, and chemokines, and are pivotal in shaping the tumor progression and therapeutic response. Understanding the interactions and combined effects of such multidimensions mechanisms in immune cell modulation is important for revealing the mechanisms of immunotherapy failure and developing new therapeutic targets and strategies.
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Affiliation(s)
- Sha Qin
- Department of PathologyXiangya HospitalCentral South UniversityChangshaHunanChina
- Department of PathologySchool of Basic Medical ScienceXiangya School of MedicineCentral South UniversityChangshaHunanChina
| | - Bin Xie
- Department of PathologyXiangya HospitalCentral South UniversityChangshaHunanChina
| | - Qingyi Wang
- Department of PathologyXiangya HospitalCentral South UniversityChangshaHunanChina
- Department of PathologySchool of Basic Medical ScienceXiangya School of MedicineCentral South UniversityChangshaHunanChina
| | - Rui Yang
- Department of PathologyXiangya HospitalCentral South UniversityChangshaHunanChina
- Department of PathologySchool of Basic Medical ScienceXiangya School of MedicineCentral South UniversityChangshaHunanChina
| | - Jingyue Sun
- Department of PathologyXiangya HospitalCentral South UniversityChangshaHunanChina
- Department of PathologySchool of Basic Medical ScienceXiangya School of MedicineCentral South UniversityChangshaHunanChina
| | - Chaotao Hu
- Regenerative Medicine, Medical SchoolUniversity of Chinese Academy of SciencesBeijingChina
| | - Shuang Liu
- Department of OncologyInstitute of Medical SciencesNational Clinical Research Center for Geriatric DisordersXiangya HospitalCentral South UniversityChangsha, Hunan, China. UniversityChangshaHunanChina
| | - Yongguang Tao
- Department of PathologyXiangya HospitalCentral South UniversityChangshaHunanChina
- NHC Key Laboratory of CarcinogenesisCancer Research Institute and School of Basic MedicineCentral South universityChangshaHunanChina
| | - Desheng Xiao
- Department of PathologyXiangya HospitalCentral South UniversityChangshaHunanChina
- Department of PathologySchool of Basic Medical ScienceXiangya School of MedicineCentral South UniversityChangshaHunanChina
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Zhang W, Song LN, You YF, Qi FN, Cui XH, Yi MX, Zhu G, Chang RA, Zhang HJ. Application of artificial intelligence in the prediction of immunotherapy efficacy in hepatocellular carcinoma: Current status and prospects. Artif Intell Gastroenterol 2024; 5:90096. [DOI: 10.35712/aig.v5.i1.90096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 01/28/2024] [Accepted: 03/12/2024] [Indexed: 04/29/2024] Open
Abstract
Artificial Intelligence (AI) has increased as a potent tool in medicine, with promising oncology applications. The emergence of immunotherapy has transformed the treatment terrain for hepatocellular carcinoma (HCC), offering new hope to patients with this challenging malignancy. This article examines the role and future of AI in forecasting the effectiveness of immunotherapy in HCC. We highlight the potential of AI to revolutionize the prediction of therapy response, thus improving patient selection and clinical outcomes. The article further outlines the challenges and future research directions in this emerging field.
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Affiliation(s)
- Wei Zhang
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Li-Ning Song
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Yun-Fei You
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Feng-Nan Qi
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Xiao-Hong Cui
- Department of General Surgery, Shanghai Electric Power Hospital, Shanghai 200050, China
| | - Ming-Xun Yi
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Guang Zhu
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Ren-An Chang
- Research Center of Clinical Medicine and Department of General Surgery, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
| | - Hai-Jian Zhang
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong, China
- Research Center of Clinical Medicine, The Affiliated Hospital of Nantong University, Nantong 226001, Jiangsu Province, China
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5
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Deng Z, Feng Q, Zhao D, Huang Z. A degradome-related signature for predicting the prognosis and immunotherapy benefit in stomach adenocarcinoma based on machine learning procedure. Medicine (Baltimore) 2024; 103:e37728. [PMID: 38608069 PMCID: PMC11018154 DOI: 10.1097/md.0000000000037728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 03/05/2024] [Indexed: 04/14/2024] Open
Abstract
Stomach adenocarcinoma (STAD) is one of the subtype of gastric cancer with high invasiveness, extreme heterogeneity, high morbidity, and high mortality. The degradome is the most abundant class of cellular enzymes that play an essential role in regulating cellular activity and carcinogenesis. An integrative machine learning procedure including 10 methods was performed to develop a prognostic degradome-based prognostic signature (DPS) in TCGA, GSE15459, GSE26253, and GSE62254 datasets. Investigations of the DPS concerning immune infiltration, immunotherapy benefits, and drug priority were orchestrated. The DPS developed by Enet [alpha = 0.3] method was regarded as the optimal prognostic model. The DPS had a stable and powerful performance in predicting the clinical outcome of STAD and served as an independent risk factor in training and testing cohorts. The C-index of DPS was higher than that of age, sex, and clinical stage. STAD patients with low DPS scores had a higher abundance of B cells, CD8+ T cells, higher cytolytic scores, and T cell co-stimulation scores. Moreover, low DPS score indicated a lower tumor immune dysfunction and exclusion score, lower T cell dysfunction and exclusion score, higher PD1&CTLA4 immunophenoscore, and higher tumor mutation burden score in STAD, demonstrating a better immunotherapy response. STAD patients with a high DPS score had a lower IC50 value of common chemotherapy and targeted therapy regimens (Cisplatin, Docetaxel, Gefitinib, etc). Our study developed an optimal DPS for STAD. The DPS could predict the prognosis, risk stratification and guide treatment for STAD patients.
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Affiliation(s)
- Ziqing Deng
- Department of General Surgery, Nanchang People’s Hospital, Nanchang, China
| | - Qian Feng
- Department of Emergency, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Dan Zhao
- Department of Critical Care Medicine, The Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, China
| | - Zhihao Huang
- Department of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China
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Liu Z, Han S, Luo Y, Zhao Z, Ni L, Chai L, Tang H. PERP May Affect the Prognosis of Lung Adenocarcinoma by Inhibiting Apoptosis. Cancer Manag Res 2024; 16:199-214. [PMID: 38525370 PMCID: PMC10961073 DOI: 10.2147/cmar.s443490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 02/29/2024] [Indexed: 03/26/2024] Open
Abstract
Background PERP, a member of the peripheral myelin protein gene family, is a new therapeutic target in cancer. The relationships between PERP and immune cell infiltration in lung cancer have not been studied. Therefore, the role of PERP in the tumour microenvironment (TME) of lung cancer needs to be further explored. Methods In this study, we explored the association between PERP expression and clinical characteristics by analysing data from the TCGA database. Cox regression and Kaplan‒Meier methods were used to investigate the relationship between the expression of PERP and overall survival in patients with lung adenocarcinoma (LUAD). The relationship between PERP expression and the degree of infiltration of specific immune cell subsets in LUAD was evaluated using the TIMER database and GEPIA. We also performed GO enrichment analysis and KEGG enrichment analysis to reveal genes coexpressed with PERP using the Coexpedia database. Finally, we verified the expression and function of PERP in LUAD tissues and the A549 cell line by RT‒PCR, Western blot, CCK-8, IHC, and wound healing assays. The mouse model was used to study the in vivo effects of PERP. Results According to our results, PERP expression was significantly higher in LUAD tissues and associated with the clinical characteristics of the disease. Survival was independently associated with PERP in LUAD patients. We further verified that PERP might regulate B-cell infiltration in LUAD to affect the prognosis of LUAD. To identify PERP-related signalling pathways in LUAD, we performed a genome-aggregation analysis (GSEA) between low and high PERP expression datasets. LUAD cells express higher levels of PERP than paracarcinoma cells, and PERP inhibits the proliferation and metastasis of A549 cells through apoptosis. Conclusion PERP may affect the prognosis of lung adenocarcinoma by inhibiting apoptosis and is associated with immune cell infiltration.
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Affiliation(s)
- Zhongxiang Liu
- Department of Pulmonary and Critical Care Medicine, the Yancheng Clinical College of Xuzhou Medical University, The First People’s Hospital of Yancheng, the First Affiliated Hospital of Jiangsu Vocational College of Medicine, Yancheng, 224000, People’s Republic of China
| | - Shuhua Han
- Department of Respiratory and Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210009, People’s Republic of China
| | - Yuhong Luo
- College of Life Science and Technology, Guangxi University, Nanning, 530004, People’s Republic of China
| | - Zhangyan Zhao
- Department of Respiratory and Critical Care Medicine, Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, People’s Republic of China
| | - Lingyu Ni
- China School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210046, People’s Republic of China
| | - Linlin Chai
- Department of Pathology, The Yancheng Clinical College of Xuzhou Medical University, The First People’s Hospital of Yancheng, The First Affiliated Hospital of Jiangsu Vocational College of Medicine, Yancheng, 224000, People’s Republic of China
| | - Haicheng Tang
- Department of Respiratory and Critical Care Medicine, Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, People’s Republic of China
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7
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Chen R, Zheng Y, Fei C, Ye J, Fei H. Machine learning developed a CD8 + exhausted T cells signature for predicting prognosis, immune infiltration and drug sensitivity in ovarian cancer. Sci Rep 2024; 14:5794. [PMID: 38461331 PMCID: PMC10925064 DOI: 10.1038/s41598-024-55919-4] [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: 01/02/2024] [Accepted: 02/28/2024] [Indexed: 03/11/2024] Open
Abstract
CD8+ exhausted T cells (CD8+ Tex) played a vital role in the progression and therapeutic response of cancer. However, few studies have fully clarified the characters of CD8+ Tex related genes in ovarian cancer (OC). The CD8+ Tex related prognostic signature (TRPS) was constructed with integrative machine learning procedure including 10 methods using TCGA, GSE14764, GSE26193, GSE26712, GSE63885 and GSE140082 dataset. Several immunotherapy benefits indicators, including Tumor Immune Dysfunction and Exclusion (TIDE) score, immunophenoscore (IPS), TMB score and tumor escape score, were used to explore performance of TRPS in predicting immunotherapy benefits of OC. The TRPS constructed by Enet (alpha = 0.3) method acted as an independent risk factor for OC and showed stable and powerful performance in predicting clinical outcome of patients. The C-index of the TRPS was higher than that of tumor grade, clinical stage, and many developed signatures. Low TRPS score indicated a higher level of CD8+ T cell, B cell, macrophage M1, and NK cells, representing a relative immunoactivated ecosystem in OC. OC patients with low risk score had a higher PD1&CTLA4 immunophenoscore, higher TMB score, lower TIDE score and lower tumor escape score, suggesting a better immunotherapy response. Moreover, higher TRPS score indicated a higher score of cancer-related hallmarks, including angiogenesis, EMT, hypoxia, glycolysis, and notch signaling. Vitro experiment showed that ARL6IP5 was downregulated in OC tissues and inhibited tumor cell proliferation. The current study constructed a novel TRPS for OC, which could serve as an indicator for predicting the prognosis, immune infiltration and immunotherapy benefits for OC patients.
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Affiliation(s)
- Rujun Chen
- Department of Obstetrics and Gynecology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, China
| | - Yicai Zheng
- Department of Stomatology,Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, China
| | - Chen Fei
- Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jun Ye
- Department of Obstetrics and Gynecology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, China.
| | - He Fei
- Department of Obstetrics and Gynecology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, 200240, China.
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8
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Lehrich BM, Zhang J, Monga SP, Dhanasekaran R. Battle of the biopsies: Role of tissue and liquid biopsy in hepatocellular carcinoma. J Hepatol 2024; 80:515-530. [PMID: 38104635 PMCID: PMC10923008 DOI: 10.1016/j.jhep.2023.11.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 10/27/2023] [Accepted: 11/27/2023] [Indexed: 12/19/2023]
Abstract
The diagnosis and management of hepatocellular carcinoma (HCC) have improved significantly in recent years. With the introduction of immunotherapy-based combination therapy, there has been a notable expansion in treatment options for patients with unresectable HCC. Simultaneously, innovative molecular tests for early detection and management of HCC are emerging. This progress prompts a key question: as liquid biopsy techniques rise in prominence, will they replace traditional tissue biopsies, or will both techniques remain relevant? Given the ongoing challenges of early HCC detection, including issues with ultrasound sensitivity, accessibility, and patient adherence to surveillance, the evolution of diagnostic techniques is more relevant than ever. Furthermore, the accurate stratification of HCC is limited by the absence of reliable biomarkers which can predict response to therapies. While the advantages of molecular diagnostics are evident, their potential has not yet been fully harnessed, largely because tissue biopsies are not routinely performed for HCC. Liquid biopsies, analysing components such as circulating tumour cells, DNA, and extracellular vesicles, provide a promising alternative, though they are still associated with challenges related to sensitivity, cost, and accessibility. The early results from multi-analyte liquid biopsy panels are promising and suggest they could play a transformative role in HCC detection and management; however, comprehensive clinical validation is still ongoing. In this review, we explore the challenges and potential of both tissue and liquid biopsy, highlighting that these diagnostic methods, while distinct in their approaches, are set to jointly reshape the future of HCC management.
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Affiliation(s)
- Brandon M Lehrich
- Department of Pathology and Pittsburgh Liver Institute, University of Pittsburgh, School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Josephine Zhang
- Division of Gastroenterology and Hepatology, Department of Medicine, Stanford University, Staford, CA, 94303, USA
| | - Satdarshan P Monga
- Department of Pathology and Pittsburgh Liver Institute, University of Pittsburgh, School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
| | - Renumathy Dhanasekaran
- Division of Gastroenterology and Hepatology, Department of Medicine, Stanford University, Staford, CA, 94303, USA.
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Sheng Y, Wang Q, Liu H, Wang Q, Chen W, Xing W. Prognostic nomogram model for selecting between transarterial chemoembolization plus lenvatinib, with and without PD-1 inhibitor in unresectable hepatocellular carcinoma. Br J Radiol 2024; 97:668-679. [PMID: 38303541 PMCID: PMC11027259 DOI: 10.1093/bjr/tqae018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 12/11/2023] [Accepted: 01/13/2024] [Indexed: 02/03/2024] Open
Abstract
OBJECTIVES To establish and verify a prognostic nomogram model for selecting in unresectable hepatocellular carcinoma (uHCC) treated by transarterial chemoembolization plus lenvatinib (TACE-L) with or without PD-1 inhibitor. METHODS Data of 241 uHCC patients who underwent TACE-L (n = 128) and TACE-L plus PD-1 inhibitor (TACE-L-P, n = 113) were retrospectively reviewed. The differences in tumour responses, progression-free survival (PFS), overall survival (OS), and adverse events (AEs) between two groups were compared, and a prognostic nomogram model was established based on independent clinical-radiologic factors and confirmed by Cox regression analysis for predicting PFS and OS. The treatment selection for uHCC patients was stratified by the nomogram score. RESULTS Compared to TACE-L, TACE-L-P presented prolonged PFS (14.0 vs. 9.0 months, P < .001), longer OS (24.0 vs. 15.0 months, P < .001), and a better overall objective response rate (54.0% vs. 32.8%, P = .001). There was no significant difference between the rate of AEs in the TACE-L-P and the TACE-L (56.64% vs. 46.09%, P = .102) and the rate of grade ≥ 3 AEs (11.50% vs. 9.38%, P = .588), respectively. The nomogram model presented good discrimination, with a C-index of 0.790 for predicting PFS and 0.749 for predicting OS. Patients who underwent TACE-L and obtained a nomogram score >9 demonstrated improved 2-year PFS when transferred to TACE-L-P, and those with a nomogram ≤25 had better 2-year OS when transferred to TACE-L-P. CONCLUSIONS TACE-L-P showed significant improvements in efficiency and safety for uHCC patients compared with TACE-L. The nomogram was useful for stratifying treatment decisions and selecting a suitable population for uHCC patients. ADVANCES IN KNOWLEDGE Prognostic nomogram model is of great value in predicting individualized survival benefits for uHCC patients after TACE-L or/and TACE-L-P. And the nomogram was helpful for selection between TACE-L-P and TACE-L among uHCC patients.
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Affiliation(s)
- Ye Sheng
- Department of Interventional Radiology, Third Affiliated Hospital of Soochow University & Changzhou First People’s Hospital, Juqian street NO.185, Tianning district, Changzhou, Jiangsu, 213003, China
| | - Qing Wang
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou & Changzhou First People’s Hospital, Juqian street NO.185, Tianning district, Changzhou, Jiangsu, 213003, China
| | - HaiFeng Liu
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou & Changzhou First People’s Hospital, Juqian street NO.185, Tianning district, Changzhou, Jiangsu, 213003, China
| | - Qi Wang
- Department of Interventional Radiology, Third Affiliated Hospital of Soochow University & Changzhou First People’s Hospital, Juqian street NO.185, Tianning district, Changzhou, Jiangsu, 213003, China
| | - WenHua Chen
- Department of Interventional Radiology, Third Affiliated Hospital of Soochow University & Changzhou First People’s Hospital, Juqian street NO.185, Tianning district, Changzhou, Jiangsu, 213003, China
| | - Wei Xing
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou & Changzhou First People’s Hospital, Juqian street NO.185, Tianning district, Changzhou, Jiangsu, 213003, China
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Wang RY, Yang JL, Xu N, Xu J, Yang SH, Liang DM, Li JZ, Zhu H. Lipid metabolism-related long noncoding RNA RP11-817I4.1 promotes fatty acid synthesis and tumor progression in hepatocellular carcinoma. World J Gastroenterol 2024; 30:919-942. [PMID: 38516243 PMCID: PMC10950635 DOI: 10.3748/wjg.v30.i8.919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/24/2023] [Accepted: 01/27/2024] [Indexed: 02/26/2024] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is one of the most common types of tumors. The influence of lipid metabolism disruption on the development of HCC has been demonstrated in published studies. AIM To establish an HCC prognostic model for lipid metabolism-related long non-coding RNAs (LMR-lncRNAs) and conduct in-depth research on the specific role of novel LMR-lncRNAs in HCC. METHODS Correlation and differential expression analyses of The Cancer Genome Atlas data were used to identify differentially expressed LMR-lncRNAs. Quantitative real-time polymerase chain reaction analysis was used to evaluate the expression of LMR-lncRNAs. Nile red staining was employed to observe intracellular lipid levels. The interaction between RP11-817I4.1, miR-3120-3p, and ATP citrate lyase (ACLY) was validated through the performance of dual-luciferase reporter gene and RIP assays. RESULTS Three LMR-lncRNAs (negative regulator of antiviral response, RNA transmembrane and coiled-coil domain family 1 antisense RNA 1, and RP11-817I4.1) were identified as predictive markers for HCC patients and were utilized in the construction of risk models. Additionally, proliferation, migration, and invasion were reduced by RP11-817I4.1 knockdown. An increase in lipid levels in HCC cells was significantly induced by RP11-817I4.1 through the miR-3120-3p/ACLY axis. CONCLUSION LMR-lncRNAs have the capacity to predict the clinical characteristics and prognoses of HCC patients, and the discovery of a novel LMR-lncRNAs, RP11-817I4.1, revealed its role in promoting lipid accumulation, thereby accelerating the onset and progression of HCC.
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Affiliation(s)
- Ren-Yong Wang
- Second Affiliated Hospital of Kunming Medical University, Kunming 650106, Yunnan Province, China
| | - Jia-Ling Yang
- School of Basic Medical Sciences, Nanjing Medical University, Nanjing 211166, Jiangsu Province, China
| | - Ning Xu
- Second Affiliated Hospital of Kunming Medical University, Kunming 650106, Yunnan Province, China
| | - Jia Xu
- Wuhan Blood Center, Wuhan 430030, Hubei Province, China
| | - Shao-Hua Yang
- Second Affiliated Hospital of Kunming Medical University, Kunming 650106, Yunnan Province, China
| | - Dao-Ming Liang
- Second Affiliated Hospital of Kunming Medical University, Kunming 650106, Yunnan Province, China
| | - Jin-Ze Li
- Department of Gastrointestinal Surgery, The Third People's Hospital of Hubei Province, Wuhan 430071, Hubei Province, China
| | - Hong Zhu
- Second Affiliated Hospital of Kunming Medical University, Kunming 650106, Yunnan Province, China
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11
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Zhang Y, Pei L. Machine learning constructs a T cell-related signature for predicting prognosis and drug sensitivity in ovarian cancer. Aging (Albany NY) 2024; 16:3332-3349. [PMID: 38345575 PMCID: PMC10929824 DOI: 10.18632/aging.205536] [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: 07/20/2023] [Accepted: 12/07/2023] [Indexed: 03/06/2024]
Abstract
BACKGROUND The leading cause of death related to gynecologic cancer is ovarian cancer, which typically has a poor prognosis. T cells are referred to as key mediators of immunosurveillance and tumor eradication, and unbalanced regulation or lack of T cells in tumors result in immunotherapy resistance. METHODS The identification of T cell related markers depended on single-cell RNA-seq analysis. Using data from multiple datasets, including TCGA, GSE14764, GSE26193, GSE26712, and GSE140082, we constructed a prognostic signature called TRS (T cell-related signature) using 10 different machine learning algorithms. The correlation between TRS and drug sensitivity were analyzed using the data from GSE91061 and IMvigor210 dataset. RESULTS PlsRcox method based TRS was as a risk factor for the clinical outcome of ovarian cancer patients. In comparison with stage, grade and many prognostic signatures, the performance of our TRS in evaluating the clinical outcome was better in ovarian cancer. TRS-based risk score showed distinct association with the level of ESTIMATE score, immune-related function score and immune cells. Moreover, TRS could be used to predict the immunotherapy response and chemotherapy response in ovarian cancer. CONCLUSION In conclusion, we constructed a powerful TRS in ovarian cancer, which could accurately predict the clinical outcome of patients and be used to predict the immunotherapy response and chemotherapy response.
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Affiliation(s)
- Yunzheng Zhang
- Department of Obstetrics and Gynecology, General Hospital of Northern Theater Command, Shenyang 110015, China
| | - Lipeng Pei
- Department of Obstetrics and Gynecology, General Hospital of Northern Theater Command, Shenyang 110015, China
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12
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Liu Y, Tang R, Meng QC, Shi S, Xu J, Yu XJ, Zhang B, Wang W. NUSAP1 promotes pancreatic ductal adenocarcinoma progression by drives the epithelial-mesenchymal transition and reduces AMPK phosphorylation. BMC Cancer 2024; 24:87. [PMID: 38229038 PMCID: PMC10790387 DOI: 10.1186/s12885-024-11842-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 01/04/2024] [Indexed: 01/18/2024] Open
Abstract
BACKGROUND Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, and its molecular mechanisms are unclear. Nucleolar and spindle-associated protein 1 (NUSAP1), an indispensable mitotic regulator, has been reported to be involved in the development of several types of tumors. The biological function and molecular mechanism of NUSAP1 in PDAC remain controversial. This study explored the effects and mechanism of NUSAP1 in PDAC. METHODS Differentially expressed genes (DEGs) were screened. A protein‒protein interaction (PPI) network was constructed to identify hub genes. Experimental studies and tissue microarray (TMA) analysis were performed to investigate the effects of NUSAP1 in PDAC and explore its mechanism. RESULTS Network analysis revealed that NUSAP1 is an essential hub gene in the PDAC transcriptome. Genome heterogeneity analysis revealed that NUSAP1 is related to tumor mutation burden (TMB), loss of heterozygosity (LOH) and homologous recombination deficiency (HRD) in PDAC. NUSAP1 is correlated with the levels of infiltrating immune cells, such as B cells and CD8 T cells. High NUSAP1 expression was found in PDAC tissues and was associated with a poor patient prognosis. NUSAP1 promoted cancer cell proliferation, migration and invasion, drives the epithelial-mesenchymal transition and reduces AMPK phosphorylation. CONCLUSIONS NUSAP1 is an essential hub gene that promotes PDAC progression and leads to a dismal prognosis by drives the epithelial-mesenchymal transition and reduces AMPK phosphorylation.
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Affiliation(s)
- Yuan Liu
- Department of Endoscopy, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Pancreatic Cancer Institute, No.270 Dong'An Road, Shanghai, 200032, China
| | - Rong Tang
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Pancreatic Cancer Institute, No.270 Dong'An Road, Shanghai, 200032, China
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Qing-Cai Meng
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Pancreatic Cancer Institute, No.270 Dong'An Road, Shanghai, 200032, China
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Si Shi
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Pancreatic Cancer Institute, No.270 Dong'An Road, Shanghai, 200032, China
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Jin Xu
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Pancreatic Cancer Institute, No.270 Dong'An Road, Shanghai, 200032, China
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Xian-Jun Yu
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Shanghai Pancreatic Cancer Institute, No.270 Dong'An Road, Shanghai, 200032, China
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Bo Zhang
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
- Shanghai Pancreatic Cancer Institute, No.270 Dong'An Road, Shanghai, 200032, China.
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
| | - Wei Wang
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
- Shanghai Pancreatic Cancer Institute, No.270 Dong'An Road, Shanghai, 200032, China.
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
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13
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Pourbagheri-Sigaroodi A, Fallah F, Bashash D, Karimi A. Unleashing the potential of gene signatures as prognostic and predictive tools: A step closer to personalized medicine in hepatocellular carcinoma (HCC). Cell Biochem Funct 2024; 42:e3913. [PMID: 38269520 DOI: 10.1002/cbf.3913] [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: 11/16/2023] [Revised: 12/14/2023] [Accepted: 12/17/2023] [Indexed: 01/26/2024]
Abstract
Hepatocellular carcinoma (HCC) is one of the growing malignancies globally, affecting a myriad of people and causing numerous cancer-related deaths. Despite therapeutic improvements in treatment strategies over the past decades, HCC still remains one of the leading causes of person-years of life lost. Numerous studies have been conducted to assess the characteristics of HCC with the aim of predicting its prognosis and responsiveness to treatment. However, the identified biomarkers have shown limited sensitivity, and the translation of these findings into clinical practice has faced challenges. The development of sequencing techniques has facilitated the exploration of a wide range of genes, leading to the emergence of gene signatures. Although several studies assessed differentially expressed genes in normal and HCC tissues to find the unique gene signature with prognostic value, to date, no study has reviewed the task, and to the best of our knowledge, this review represents the first comprehensive analysis of relevant studies in HCC. Most gene signatures focused on immune-related genes, while others investigated genes related to metabolism, autophagy, and apoptosis. Even though no identical gene signatures were found, NDRG1, SPP1, BIRC5, and NR0B1 were the most extensively studied genes with prognostic value. Finally, despite challenges such as the lack of consistent patterns in gene signatures, we believe that comprehensive analysis of pertinent gene signatures will bring us a step closer to personalized medicine in HCC, where treatment strategies can be tailored to individual patients based on their unique molecular profiles.
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Affiliation(s)
- Atieh Pourbagheri-Sigaroodi
- Pediatric Infections Research Center, Research Institute for Children's Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fatemeh Fallah
- Pediatric Infections Research Center, Research Institute for Children's Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Davood Bashash
- Department of Hematology and Blood Banking, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Abdollah Karimi
- Pediatric Infections Research Center, Research Institute for Children's Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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14
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Li JP, Liu YJ, Yin Y, Li RN, Huang W, Zou X. Stroma-associated FSTL3 is a factor of calcium channel-derived tumor fibrosis. Sci Rep 2023; 13:21317. [PMID: 38044354 PMCID: PMC10694158 DOI: 10.1038/s41598-023-48574-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/28/2023] [Indexed: 12/05/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the most widespread histological form of primary liver cancer, and it faces great diagnostic and therapeutic difficulties owing to its tumor diversity. Herein, we aim to establish a unique prognostic molecular subtype (MST) and based on this to find potential therapeutic targets to develop new immunotherapeutic strategies. Using calcium channel molecules expression-based consensus clustering, we screened 371 HCC patients from The Cancer Genome Atlas to screen for possible MSTs. We distinguished core differential gene modules between varying MSTs, and Tumor Immune Dysfunction and Exclusion scores were employed for the reliable assessment of HCC patient immunotherapeutic response rate. Immunohistochemistry and Immunofluorescence staining were used for validation of predicted immunotherapy outcomes and underlying biological mechanisms, respectively. We identified two MSTs with different clinical characteristics and prognoses. Based on the significant differences between the two MSTs, we further identified Follistatin-like 3 (FSTL3) as a potential indicator of immunotherapy resistance and validated this result in our own cohort. Finally, we found that FSTL3 is predominantly expressed in HCC stromal components and that it is a factor in enhancing fibroblast-M2 macrophage signaling crosstalk, the function of which is relevant to the pathogenesis of HCC. The presence of two MSTs associated with the calcium channel phenotype in HCC patients may provide promising directions for overcoming immunotherapy resistance in HCC, and the promotion of FSTL3 expressed in stromal components for HCC hyperfibrosis may be responsible for the poor response rate to immunotherapy in Cluster 2 (C2) patients.
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Affiliation(s)
- Jie-Pin Li
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, Jiangsu, China
- Key Laboratory of Tumor System Biology of Traditional Chinese Medicine, Nanjing, 210029, Jiangsu, China
- No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China
| | - Yuan-Jie Liu
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, Jiangsu, China
- No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China
| | - Yi Yin
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, Jiangsu, China
- No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China
| | - Ruo-Nan Li
- Shihezi Labor Personnel Dispute Arbitration Committee, Shihezi, 832000, China
| | - Wei Huang
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, Jiangsu, China.
- No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China.
| | - Xi Zou
- Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, 210029, Jiangsu, China.
- No. 1 Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, 210023, Jiangsu, China.
- Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor, Nanjing, 210023, China.
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15
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Wang J, Wang S, Wang J, Huang J, Lu H, Pan B, Pan H, Song Y, Deng Q, Jin X, Shi G. Comprehensive analysis of clinical prognosis and biological significance of CNIH4 in cervical cancer. Cancer Med 2023; 12:22381-22394. [PMID: 38087815 PMCID: PMC10757085 DOI: 10.1002/cam4.6734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 09/27/2023] [Accepted: 11/07/2023] [Indexed: 12/31/2023] Open
Abstract
BACKGROUND Cornichon homolog 4 (CNIH4) belongs to the CNIH family. It functions as an oncogene in many tumors. However, CNIH4's significance in the immune landscape and its predictive potential in cervical cancer (CESC) is unexplored. METHODS CNIH4 levels and its effect on the survival of patients with CESC were evaluated using data retrieved from The Cancer Genome Atlas (TCGA). The oncogenic effect of CNIH4 in CESC was determined using small interfering RNA-mediated transfected cell lines and tumorigenesis experiments in animal models. RESULTS Higher expression of CNIH4 was found in advanced tumor and pathological stages, as well as lymph node metastasis. CNIH4 expression correlated positively with the infiltration of macrophages M2 and resting dendritic cells into the affected tissue. Additionally, functional enrichment of RNA-sequencing of CNIH4-knocked down CESC cell lines showed the association of CNIH4 to the PI3K-Akt signaling pathway. Single-sample gene set enrichment analysis highlighted several immune pathways that were elevated in the CESC samples with enhanced levels of CNIH4, including Type-I and Type-II IFN-response pathways. The impact of CNIH4 on drug sensitivity was further assessed using the GDSC database. As CNIH4 is linked to the immune landscape in CESC, this study determined a four-gene risk prediction signature utilizing CNIH4-related immunomodulators. The risk score quantified from the prediction signature was an independent predictive indicator in CESC. Receiver operating characteristic curve analysis verified the good predictive ability of the four-gene signature in TCGA-CESC cohort. Thus, the CNIH4-related model showed potential as an auxiliary TNM staging system tool. CONCLUSION CNIH4 may be an effective predictive biomarker for patients with cervical cancer, thus providing new ideas and research directions for CESC.
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Affiliation(s)
- Jiajia Wang
- Department of Obstetrics and GynecologyThe Affiliated Hospital of Youjiang Medical University for NationalitiesBaiseChina
- Industrial College of Biomedicine and Health IndustryYoujiang Medical University for NationalitiesBaiseChina
| | - Shudan Wang
- School of MedicineNingbo UniversityNingboChina
| | - Junli Wang
- Industrial College of Biomedicine and Health IndustryYoujiang Medical University for NationalitiesBaiseChina
- School of Medical LaboratoryYoujiang Medical University for NationalitiesBaiseChina
| | - Jingjing Huang
- Department of Obstetrics and GynecologyThe Affiliated Hospital of Youjiang Medical University for NationalitiesBaiseChina
| | - Haishan Lu
- Clinical Pathological Diagnosis & Research CentraThe Affiliated Hospital of Youjiang Medical University for NationalitiesBaiseChina
| | - Bin Pan
- Department of Laboratory Animal CenterYoujiang Medical University for NationalitiesBaiseChina
| | - Hanyi Pan
- Department of Obstetrics and GynecologyThe Affiliated Hospital of Youjiang Medical University for NationalitiesBaiseChina
| | - Yanlun Song
- Industrial College of Biomedicine and Health IndustryYoujiang Medical University for NationalitiesBaiseChina
- School of Medical LaboratoryYoujiang Medical University for NationalitiesBaiseChina
| | - Qianqian Deng
- Industrial College of Biomedicine and Health IndustryYoujiang Medical University for NationalitiesBaiseChina
- School of Medical LaboratoryYoujiang Medical University for NationalitiesBaiseChina
| | - Xiaojun Jin
- School of MedicineNingbo UniversityNingboChina
| | - Guiling Shi
- Department of Obstetrics and GynecologyThe Affiliated Hospital of Youjiang Medical University for NationalitiesBaiseChina
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16
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Pan B, Luo Y, Ye D, Qiu J, Zhang X, Wu X, Yao Y, Wang X, Tang N. A modified immune cell infiltration score achieves ideal stratification for CD8 + T cell efficacy and immunotherapy benefit in hepatocellular carcinoma. Cancer Immunol Immunother 2023; 72:4103-4119. [PMID: 37755466 DOI: 10.1007/s00262-023-03546-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 09/09/2023] [Indexed: 09/28/2023]
Abstract
Immunotherapy, which aims to enhance the function of T cells, has emerged as a novel therapeutic approach for hepatocellular carcinoma (HCC). Nevertheless, the clinical utility of using flow cytometry to assess immune cell infiltration (ICI) is hindered by its cumbersome procedures, prompting the need for more accessible methods. Here, we acquired gene expression profiles and survival data of HCC from TCGA and GSE10186 datasets. The patients were categorized into two clusters of ICI, and a set of 11 characteristic genes responsible for the differentiation performance of these ICI clusters were identified. Subsequently, we successfully developed a modified ICI score (mICIS) by utilizing the expression levels of these genes. The efficacy of our mICIS was confirmed via mass cytometry, flow cytometry, and immunohistochemistry. Our research indicated that the favorable overall survival (OS) rate could be attributed to the improved function of anti-tumor leukocytes rather than their infiltration. Furthermore, we observed that the low score group exhibited lower expression levels of T-cell exhaustion-associated genes, which was confirmed in both HCC tissues from patients and mice, which demonstrated that the benefits of the low scores were due to enhanced active/cytotoxic CD8+ T cells and reduced exhausted CD8+ T cells. Additionally, our mICIS stratified the benefits derived from immunotherapies. Lastly, we observed a misalignment between CD8+ T-cell infiltration and function in HCC. In summary, our mICIS demonstrated proficiency in assessing the OS rate of HCC and offering significant stratified data pertaining to distinct responses to immunotherapy.
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Affiliation(s)
- Banglun Pan
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Yue Luo
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Dongjie Ye
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Jiacheng Qiu
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Xiaoxia Zhang
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Xiaoxuan Wu
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Yuxin Yao
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Xiaoqian Wang
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China
| | - Nanhong Tang
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
- Cancer Center of Fujian Medical University, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, Fuzhou, 350122, China.
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Zhao C, Zhou J, Xing J, Yin Q. ASF1B acted as a prognostic biomarker for stomach adenocarcinoma. Medicine (Baltimore) 2023; 102:e35408. [PMID: 38050219 PMCID: PMC10695504 DOI: 10.1097/md.0000000000035408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Accepted: 09/05/2023] [Indexed: 12/06/2023] Open
Abstract
Stomach adenocarcinoma (STAD) has a high mortality rate due to the lack of highly sensitive biomarkers. Therefore, the search for potential tumor markers is of great value. ASF1B is a prognostic marker for a variety of tumors, while the prognostic value and immune microenvironment of ASF1B in STAD remain unclear, and to be determined. Kaplan-Meier analysis was performed to analyze the prognostic role of ASF1B in STAD. Functional enrichment of ASF1B was explored with GO and KEGG pathway analysis. We also explored the correlation between ASF1B expression and immune infiltration in STAD. ASF1B was significantly upregulated in STAD tissues and high expression of ASF1B indicated a poor overall survival, progression-free survival, and first progression rate in STAD. The functional enrichment analysis of ASF1B and related genes showed high enrichment in the cell cycle and DNA repair, and the ASF1B high expression group was also mainly enriched in pathways such as the cell cycle. Analysis of tumor immune infiltration showed that ASF1B expression was significantly associated with the majority of immune cell infiltration in STAD. Moreover, STAD patients with high ASF1B expression had a higher tumor mutation burden score, microsatellite instability score, PD-1 immunophenoscore, and immune checkpoint expression. Our results suggest that ASF1B was an independent prognostic factor for STAD as well as a potential target for immunotherapy.
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Affiliation(s)
- Cailing Zhao
- Department of Oncology, The First Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Jianghao Zhou
- Department of Gastrointestinal Tumor Surgery, The First Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Jianwei Xing
- Department of General Surgery, Sanya Central Hospital, the Third People’s Hospital of Hainan Province, Sanya, China
| | - Qiushi Yin
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Hainan Medical University, Haikou, China
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18
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Zhang YJ, Yi DH. CDK1-SRC Interaction-Dependent Transcriptional Activation of HSP90AB1 Promotes Antitumor Immunity in Hepatocellular Carcinoma. J Proteome Res 2023; 22:3714-3729. [PMID: 37949475 DOI: 10.1021/acs.jproteome.3c00379] [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] [Indexed: 11/12/2023]
Abstract
This study aimed to analyze multiomics data and construct a regulatory network involving kinases, transcription factors, and immune genes in hepatocellular carcinoma (HCC) prognosis. The researchers used transcriptomic, proteomic, and clinical data from TCGA and GEO databases to identify immune genes associated with HCC. Statistical analysis, meta-analysis, and protein-protein interaction analyses were performed to identify key immune genes and their relationships. In vitro and in vivo experiments validated the CDK1-SRC-HSP90AB1 network's effects on HCC progression and antitumor immunity. A prognostic risk model was developed using clinicopathological features and immune infiltration. The immune genes LPA, BIRC5, HSP90AB1, ROBO1, and CCL20 were identified as the key prognostic factors. The CDK1-SRC-HSP90AB1 network promoted HCC cell proliferation and migration, with HSP90AB1 being transcriptionally activated by the CDK1-SRC interaction. Manipulating SRC or HSP90AB1 reversed the effects of CDK1 and SRC on HCC. The CDK1-SRC-HSP90AB1 network also influenced HCC tumor formation and antitumor immunity. Overall, this study highlights the importance of the CDK1-SRC-HSP90AB1 network as a crucial immune-regulatory network in the HCC prognosis.
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Affiliation(s)
- Yi-Jie Zhang
- Department of Hepatobiliary and Organ Transplantation, The First Affiliated Hospital of China Medical University, Shenyang 110001, P. R. China
- The Key Laboratory of Organ Transplantation of Liaoning Province, The First Affiliated Hospital of China Medical University, Shenyang 110001, P. R. China
| | - De-Hui Yi
- Department of Hepatobiliary and Organ Transplantation, The First Affiliated Hospital of China Medical University, Shenyang 110001, P. R. China
- The Key Laboratory of Organ Transplantation of Liaoning Province, The First Affiliated Hospital of China Medical University, Shenyang 110001, P. R. China
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Cheng M, Zheng X, Wei J, Liu M. Current state and challenges of emerging biomarkers for immunotherapy in hepatocellular carcinoma (Review). Exp Ther Med 2023; 26:586. [PMID: 38023367 PMCID: PMC10665984 DOI: 10.3892/etm.2023.12285] [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: 03/22/2023] [Accepted: 08/29/2023] [Indexed: 12/01/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer. According to the American Cancer Society, among patients diagnosed with advanced liver cancer, HCC has the sixth-highest incident rate, resulting in a poor prognosis. Surgery, radiofrequency ablation, transcatheter arterial chemoembolization, radiation, chemotherapy, targeted therapy and immunotherapy are the current treatment options available. Immunotherapy, which has emerged as an innovative treatment strategy over the past decade, is serving a vital role in the treatment of advanced liver cancer. Since only a small number of individuals can benefit from immunotherapy, biomarkers are required to help clinicians identify the target populations for this precision medicine. These biomarkers, such as PD-1/PD-L1, tumor mutational burden and circulating tumor DNA, can be used to investigate interactions between immune checkpoint inhibitors and tumors. The present review summarizes information on the currently available biomarkers used for immunotherapy and the challenges that are present.
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Affiliation(s)
- Mo Cheng
- Department of Medical Oncology, Gastric Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China
| | - Xiufeng Zheng
- Department of Medical Oncology, Gastric Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China
| | - Jing Wei
- Department of Medical Oncology, Gastric Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China
| | - Ming Liu
- Department of Medical Oncology, Gastric Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China
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Tian L, Wang Y, Zhang Z, Feng X, Xiao F, Zong M. CD72, a new immune checkpoint molecule, is a novel prognostic biomarker for kidney renal clear cell carcinoma. Eur J Med Res 2023; 28:531. [PMID: 37980541 PMCID: PMC10656955 DOI: 10.1186/s40001-023-01487-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 10/30/2023] [Indexed: 11/20/2023] Open
Abstract
BACKGROUND The incidence and mortality of clear cell carcinoma of the kidney increases yearly. There are limited screening methods and advances in treating kidney renal clear cell carcinoma (KIRC). It is important to find new biomarkers to screen, diagnose and predict the prognosis of KIRC. Some studies have shown that CD72 influences the development and progression of colorectal cancer, nasopharyngeal cancer, and acute lymphoid leukemia. However, there is a lack of research on the role of CD72 in the pathogenesis of KIRC. This study aimed to determine whether CD72 is associated with the prognosis and immune infiltration of KIRC, providing an essential molecular basis for the early non-invasive diagnosis and immunotherapy of KIRC. METHODS Using TCGA, GTE, GEO, and ImmPort databases, we obtained the differentially expressed mRNA (DEmRNA) associated with the prognosis and immunity of KIRC patients. We used the Kruskal-Wallis test to identify clinicopathological parameters associated with target gene expression. We performed univariate and multivariate COX regression analyses to determine the effect of target gene expression and clinicopathological parameters on survival. We analyzed the target genes' relevant functions and signaling pathways through enrichment analysis. Finally, the correlation of target genes with tumor immune infiltration was explored by ssGSEA and Spearman correlation analysis. RESULTS The results revealed that patients with KIRC with higher expression of CD72 have a poorer prognosis. CD72 was associated with the Pathologic T stage, Pathologic stage, Pathologic M stage, Pathologic N stage, Histologic grade in KIRC patients, Laterality, and OS event. It was an independent predictor of the overall survival of KIRC patients. Functional enrichment analysis showed that CD72 was significantly enriched in oncogenic and immune-related pathways. According to ssGSEA and Spearman correlation analysis, CD72 expression was significantly associated with tumor immune cells and immune checkpoints. CONCLUSION Our study suggests that CD72 is associated with tumor immunity and may be a biomarker relevant to the diagnosis and prognosis of KIRC patients.
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Affiliation(s)
- Lv Tian
- Department of Rehabilitation, China-Japan Union Hospital of Jilin University, Changchun, 130033, China
- School of Nursing, Jilin University, Changchun, China
| | - Yiming Wang
- School of Nursing, Jilin University, Changchun, China
| | - Zhiyuan Zhang
- School of Nursing, Jilin University, Changchun, China
| | - Xuechao Feng
- School of Life Sciences, Northeast Normal University, Changchun, China
| | - Fengjun Xiao
- Beijing Institute of Radiation Medicine, Beijing, 100850, China.
| | - Minru Zong
- Department of Rehabilitation, China-Japan Union Hospital of Jilin University, Changchun, 130033, China.
- School of Nursing, Jilin University, Changchun, China.
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Lu Y, Wang S, Chi T, Zhao Y, Guo H, Wang H, Feng L. DNA damage repair-related gene signature for identifying the immune status and predicting the prognosis of hepatocellular carcinoma. Sci Rep 2023; 13:18978. [PMID: 37923899 PMCID: PMC10624694 DOI: 10.1038/s41598-023-45999-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/26/2023] [Indexed: 11/06/2023] Open
Abstract
The heterogeneity of hepatocellular carcinoma (HCC) poses a challenge for accurate prognosis prediction. DNA damage repair genes (DDRGs) have an impact on a wide range of malignancies. However, the relevance of these genes in HCC prognosis has received little attention. In this study, we aimed to develop a prognostic signature to identify novel therapy options for HCC. We acquired mRNA expression profiles and clinical data for HCC patients from The Cancer Genome Atlas (TCGA) database. A polygenic prognostic model for HCC was constructed using selection operator Cox analysis and least absolute shrinkage. The model was validated using International Cancer Genome Consortium (ICGC) data. Overall survival (OS) between the high-risk and low-risk groups was compared using Kaplan‒Meier analysis. Independent predictors of OS were identified through both univariate and multivariate Cox analyses. To determine immune cell infiltration scores and activity in immune-related pathways, a single-sample gene set enrichment analysis was performed. The protein and mRNA expression levels of the prognostic genes between HCC and normal liver tissues were also examined by immunohistochemistry (IHC), immunofluorescence (IF) and quantitative real-time PCR (qRT-PCR). A novel ten-gene signature (CHD1L, HDAC1, KPNA2, MUTYH, PPP2R5B, NEIL3, POLR2L, RAD54B, RUVBL1 and SPP1) was established for HCC prognosis prediction. Patients in the high-risk group had worse OS than those in the low-risk group. Receiver operating characteristic curve analysis confirmed the predictive ability of this prognostic gene signature. Multivariate Cox analysis showed that the risk score was an independent predictor of OS. Functional analysis revealed a strong association with cell cycle and antigen binding pathways, and the risk score was highly correlated with tumor grade, tumor stage, and types of immune infiltrate. High expression levels of the prognostic genes were significantly correlated with increased sensitivity of cancer cells to antitumor drugs. IHC, IF and qRT-PCR all indicated that the prognostic genes were highly expressed in HCC relative to normal liver tissue, consistent with the results of bioinformatics analysis. Ten DDRGs were utilized to create a new signature for identifying the immunological state of HCC and predicting prognosis. In addition, blocking these genes could represent a promising treatment.
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Affiliation(s)
- Yongpan Lu
- Department of Plastic Surgery, Shandong University of Traditional Chinese Medicine, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qian Foshan Hospital, Jingshi Road, Jinan, 250014, Shandong, China
| | - Sen Wang
- Department of Medical Ultrasound, Shandong Medicine and Health Key Laboratory of Abdominal Medical Imaging, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qian Foshan Hospital, Shandong First Medical University, No. 16766, Jingshi Road, Jinan, 250014, Shandong, China
| | - Tingting Chi
- Department of Acupuncture and Rehabilitation, The Affiliated Qingdao Hai Ci Hospital of Qingdao University (West Hospital Area), Qingdao, 266000, Shandong, China
| | - Yuli Zhao
- Department of Medical Ultrasound, Shandong Medicine and Health Key Laboratory of Abdominal Medical Imaging, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qian Foshan Hospital, Shandong First Medical University, No. 16766, Jingshi Road, Jinan, 250014, Shandong, China
| | - Huimin Guo
- Department of Medical Ultrasound, Shandong Medicine and Health Key Laboratory of Abdominal Medical Imaging, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qian Foshan Hospital, Jining Medical College, No. 16766, Jingshi Road, Jinan, 250014, Shandong, China
| | - Haizheng Wang
- Department of Medical Ultrasound, Shandong Medicine and Health Key Laboratory of Abdominal Medical Imaging, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qian Foshan Hospital, Shandong First Medical University, No. 16766, Jingshi Road, Jinan, 250014, Shandong, China
| | - Li Feng
- Department of Medical Ultrasound, Shandong Medicine and Health Key Laboratory of Abdominal Medical Imaging, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qian Foshan Hospital, Shandong First Medical University, No. 16766, Jingshi Road, Jinan, 250014, Shandong, China.
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Li Z, Guo M, Lin W, Huang P. Machine Learning-Based Integration Develops a Macrophage-Related Index for Predicting Prognosis and Immunotherapy Response in Lung Adenocarcinoma. Arch Med Res 2023; 54:102897. [PMID: 37865004 DOI: 10.1016/j.arcmed.2023.102897] [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: 03/16/2023] [Revised: 08/06/2023] [Accepted: 10/06/2023] [Indexed: 10/23/2023]
Abstract
BACKGROUND Macrophages play a critical role in tumor immune microenvironment (TIME) formation and cancer progression in lung adenocarcinoma (LUAD). However, few studies have comprehensively and systematically described the characteristics of macrophages in LUAD. METHODS This study identified macrophage-related markers with single-cell RNA sequencing data from the GSE189487 dataset. An integrative machine learning-based procedure based on 10 algorithms was developed to construct a macrophage-related index (MRI) in The Cancer Genome Atlas (TCGA), GSE30219, GSE31210, and GSE72094 datasets. Several algorithms were used to evaluate the associations of MRI with TIME and immunotherapy-related biomarkers. The role of MRI in predicting the immunotherapy response was evaluated with the GSE91061 dataset. RESULTS The optimal MRI constructed by the combination of the Lasso algorithm and plsRCox was an independent risk factor in LUAD and showed a stable and powerful performance in predicting the overall survival rate of patients with LUAD. Those with low MRI scores had a higher TIME score, a higher level of immune cells, a higher immunophenoscore, and a lower Tumor Immune Dysfunction and Exclusion (TIDE) score, indicating a better response to immunotherapy. The IC50 value of common drugs for chemotherapy and target therapy with low MRI scores was higher compared to high MRI scores. Moreover, the survival prediction nomogram, developed from MRI, had good potential for clinical application in predicting the 1-, 3-, and 5-year overall survival rate of LUAD. CONCLUSION Our study constructed for the first time a consensus MRI for LUAD with 10 machine learning algorithms. The MRI could be helpful for risk stratification, prognosis, and selection of treatment approach in LUAD.
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Affiliation(s)
- Zuwei Li
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China
| | - Minzhang Guo
- Department of Thoracic Surgery and Institute of Thoracic Oncology, West China Hospital, Sichuan University, Chengdu, China
| | - Wanli Lin
- Department of Thoracic Surgery, Gaozhou People's Hospital, Maoming, China
| | - Peiyuan Huang
- Department of Pharmacy, Gaozhou People's Hospital, Maoming, China.
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23
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Han X, Yang L, Tian H, Ji Y. Machine learning developed a PI3K/Akt pathway-related signature for predicting prognosis and drug sensitivity in ovarian cancer. Aging (Albany NY) 2023; 15:11162-11183. [PMID: 37851341 PMCID: PMC10637788 DOI: 10.18632/aging.205119] [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: 08/01/2023] [Accepted: 09/18/2023] [Indexed: 10/19/2023]
Abstract
BACKGROUND Ovarian cancer is one of the deadliest malignancies among females, generally having a poor prognosis. The PI3K/Akt pathway plays a vital role in the oncogenesis and progression of many types of cancer. Limited studies have fully clarified the role of PI3K/Akt pathway in the prognosis of ovarian cancer and its correlation with drug sensitivity. METHODS A prognostic PI3K/Akt pathway related signature (PRS) was constructed with 10 machine learning algorithms using TCGA, GSE14764, GSE26193, GSE26712, GSE63885 and GSE140082 datasets. Gaussian mixture and logistic regression were performed to identify the optimal models for classifying lymphatic and venous invasion. RESULTS The optimal prognostic PRS developed by Lasso + survivalSVM algorithm acted as an independent risk factor for overall survival (OS) of ovarian cancer patients and had a good performance in evaluating OS rate of ovarian cancer patients. Significant correlation was obtained between PRS-based risk score and Immune score, ESTIMATE score, immune cells and cancer-related hallmarks. Low risk score indicated a lower immune escape score, TIDE score, and higher PD1&CTLA4 immunophenoscore in ovarian cancer. Moreover, PRS-based risk score acted as an indicator for drug sensitivity in the immunotherapy and chemotherapy of ovarian cancer patients. CONCLUSIONS All in all, our study developed a prognostic PRS showing powerful and good performance in predicting clinical outcome of ovarian cancer patients. PRS could serve as an indicator for drug sensitivity in the chemotherapy and immunotherapy.
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Affiliation(s)
- Xiaofang Han
- Core Laboratory, Shanxi Provincial People's Hospital (Fifth Hospital) of Shanxi Medical University, Taiyuan 030012, China
| | - Liu Yang
- Core Laboratory, Shanxi Provincial People's Hospital (Fifth Hospital) of Shanxi Medical University, Taiyuan 030012, China
| | - Hui Tian
- Core Laboratory, Shanxi Provincial People's Hospital (Fifth Hospital) of Shanxi Medical University, Taiyuan 030012, China
| | - Yuanyuan Ji
- Core Laboratory, Shanxi Provincial People's Hospital (Fifth Hospital) of Shanxi Medical University, Taiyuan 030012, China
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24
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Wang L, Chen X, Song L, Zou H. Machine Learning Developed a Programmed Cell Death Signature for Predicting Prognosis, Ecosystem, and Drug Sensitivity in Ovarian Cancer. Anal Cell Pathol (Amst) 2023; 2023:7365503. [PMID: 37868825 PMCID: PMC10586435 DOI: 10.1155/2023/7365503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 08/14/2023] [Accepted: 09/07/2023] [Indexed: 10/24/2023] Open
Abstract
Background Ovarian cancer (OC) is the leading cause of gynecological cancer death and the fifth most common cause of cancer-related death in women in America. Programmed cell death played a vital role in tumor progression and immunotherapy response in cancer. Methods The prognostic cell death signature (CDS) was constructed with an integrative machine learning procedure, including 10 methods, using TCGA, GSE14764, GSE26193, GSE26712, GSE63885, and GSE140082 datasets. Several methods and single-cell analysis were used to explore the correlation between CDS and the ecosystem and therapy response of OC patients. Results The prognostic CDS constructed by the combination of StepCox (n = both) + Enet (alpha = 0.2) acted as an independent risk factor for the overall survival (OS) of OC patients and showed stable and powerful performance in predicting the OS rate of OC patients. Compared with tumor grade, clinical stage, and many developed signatures, the CDS had a higher C-index. OC patients with low CDS score had a higher level of CD8+ cytotoxic T, B cell, and M1-like macrophage, representing a related immunoactivated ecosystem. A low CDS score indicated a higher PD1 and CTLA4 immunophenoscore, higher tumor mutation burden score, lower tumor immune dysfunction and exclusion score, and lower tumor escape score in OC, demonstrating a better immunotherapy response. OC patients with high CDS score had a higher gene set score of cancer-related hallmarks, including angiogenesis, epithelial-mesenchymal transition, hypoxia, glycolysis, and notch signaling. Conclusion The current study constructed a novel CDS for OC, which could serve as an indicator for predicting the prognosis, ecosystem, and immunotherapy benefits of OC patients.
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Affiliation(s)
- Le Wang
- Department of Blood Transfusion, The Second Affiliated Hospital of Nanchang University, Nanchang 330000, China
| | - Xi Chen
- Department of Emergency, The Second Affiliated Hospital of Nanchang University, Nanchang 330000, China
| | - Lei Song
- Department of General Practice, The Second Affiliated Hospital of Nanchang University, Nanchang 330000, China
| | - Hua Zou
- Department of Organ Transplantation, The Second Affiliated Hospital of Nanchang University, Nanchang 330000, China
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25
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Zhao B, Pei L. A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning. BMC Med Genomics 2023; 16:230. [PMID: 37784081 PMCID: PMC10544447 DOI: 10.1186/s12920-023-01671-z] [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: 04/18/2023] [Accepted: 09/22/2023] [Indexed: 10/04/2023] Open
Abstract
BACKGROUND Ovarian cancer ranks the leading cause of gynecologic cancer-related death in the United States and the fifth most common cause of cancer-related mortality among American women. Increasing evidences have highlighted the vital role of macrophages M2/M1 proportion in tumor progression, prognosis and immunotherapy. METHODS Weighted gene co-expression network analysis (WGCNA) was performed to identify macrophages related markers. Integrative procedure including 10 machine learning algorithms were performed to develop a prognostic macrophage related signature (MRS) with TCGA, GSE14764, GSE140082 datasets. The role of MRS in tumor microenvironment (TME) and therapy response was evaluated with the data of CIBERSORT, MCPcounter, QUANTISEQ, XCELL, CIBERSORT-ABS, TIMER and EPIC, GSE91061 and IMvigor210 dataset. RESULTS The optimal MRS developed by the combination of CoxBoost and StepCox[forward] algorithm served as an independent risk factor in ovarian cancer. Compared with stage, grade and other established prognostic signatures, the current MRS had a better performance in predicting the overall survival rate of ovarian cancer patients. Low risk score indicated a higher TME score, higher level of immune cells, higher immunophenoscore, higher tumor mutational burden, lower TIDE score and lower IC50 value in ovarian cancer. The survival prediction nomogram had a good potential for clinical application in predicting the 1-, 3-, and 5-year overall survival rate of ovarian cancer patients. CONCLUSION All in all, the current study constructed a powerful prognostic MRS for ovarian cancer patients using 10 machine learning algorithms. This MRS could predict the prognosis and drug sensitivity in ovarian cancer.
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Affiliation(s)
- Bo Zhao
- Department of Obstetrics and Gynecology, General Hospital of Northern Theater Command, Shenyang, 110016, China
| | - Lipeng Pei
- Department of Obstetrics and Gynecology, General Hospital of Northern Theater Command, Shenyang, 110016, China.
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Yang X, Su X, Wang Z, Yu Y, Wu Z, Zhang D. ULBP2 is a biomarker related to prognosis and immunity in colon cancer. Mol Cell Biochem 2023; 478:2207-2219. [PMID: 36633827 DOI: 10.1007/s11010-022-04647-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 12/17/2022] [Indexed: 01/13/2023]
Abstract
The study aimed to determine whether ULBP2 was associated with prognosis and immune infiltration in colon cancer (CC) and provided important molecular basis in order to early non-invasive diagnosis and immunotherapy of CC. Using The Cancer Genome Atlas database (TCGA) and ImmPort database, we extracted messenger RNA (mRNA) data of CC and immune-related genes, then we used "limma" package, "survival" package, and Venn overlap analysis to obtain the differentially expressed mRNA (DEmRNA) associated with prognosis and immunity of CC patients. "pROC" package was used to analyze receiver operating characteristics (ROC) of target gene. We used chi-square test and two-class logistics model to identify clinicopathological parameters that correlated with target gene expression. In order to determine the effects of target gene expression and clinicopathological parameters on survival, univariate and multivariate cox regression analyses were performed. We analyzed the related functions and signaling pathways of target gene by enrichment analysis. Finally, the correlation between target gene and tumor immune infiltrating was explored by ssGSEA and spearman correlation analysis. Results showed that ULBP2 was a target gene associated with immunity and prognosis in CC patients. CC patients with higher ULBP2 expression had poor outcomes. In terms of ROC, ULBP2 had an area under the curve (AUC) of 0.984. ULBP2 was associated with T stage, N stage, and pathologic stage of CC patients, and served as an independent predictor of overall survival in CC patients. Functional enrichment analysis revealed ULBP2 was obviously enriched in pathways connected with carcinogenesis and immunosuppression. The expression of ULBP2 was significantly associated with tumor immune cells and immune checkpoints according to ssGSEA and spearman correlation analysis. To conclude, our study suggested that ULBP2 was associated with tumor immunity, and might be a biomarker associated with the diagnosis and prognosis of CC patients, and a potential target of CC immunotherapy.
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Affiliation(s)
- Xiaoping Yang
- Key Laboratory of Digestive Diseases of Gansu Province, Lanzhou University Second Hospital, Lanzhou, 730030, China
- The Second Clinical Medical College, Lanzhou University, Lanzhou, 730030, China
| | - Xiaolu Su
- Department of Pathology, Lanzhou University Second Hospital, Lanzhou, 730030, China
| | - Zirui Wang
- The Second Clinical Medical College, Lanzhou University, Lanzhou, 730030, China
| | - Yi Yu
- Department of Gastroenterology, Lanzhou University Second Hospital, Lanzhou, 730030, China
| | - Zhiping Wu
- Department of Gastroenterology, Lanzhou University Second Hospital, Lanzhou, 730030, China
| | - Dekui Zhang
- Key Laboratory of Digestive Diseases of Gansu Province, Lanzhou University Second Hospital, Lanzhou, 730030, China.
- Department of Gastroenterology, Lanzhou University Second Hospital, Lanzhou, 730030, China.
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Li S, Yang M, Teng S, Lin K, Wang Y, Zhang Y, Guo W, Wang D. Chromatin accessibility dynamics in colorectal cancer liver metastasis: Uncovering the liver tropism at single cell resolution. Pharmacol Res 2023; 195:106896. [PMID: 37633511 DOI: 10.1016/j.phrs.2023.106896] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 08/18/2023] [Accepted: 08/23/2023] [Indexed: 08/28/2023]
Abstract
Tumor metastasis causes over 90% of cancer related death and no currently available therapies target it. However, there is limited understanding regarding the epigenetic regulation of genes during this complex process. Here by integrating single-cell ATAC-seq (scATAC-seq), single-cell RNA-seq (scRNA-seq), microarray, bulk RNA-seq, immunohistochemistry (IHC) staining, as well as proteomics datasets from paired primary and liver metastatic colorectal cancer (CRC) patient-derived xenograft (PDX) model and patients, we discovered that liver metastatic CRC cells lose their colon-specific chromatin accessible sites yet gain liver-specific ones. Importantly, we observed elevated accessibility of HNF4A, a liver-specific transcription factor, in liver metastatic CRC cells. Subsequently, we performed clustering analysis of liver metastatic CRC cells together with cells involved in liver development, revealing significant heterogeneity among the liver metastatic CRC cells. Over 50% of the liver metastatic CRC cells exhibited characteristics similar to those of erythroid progenitors and hepatocytes, showing increased expression of genes involved in oxidative phosphorylation and glycolysis. Moreover, our discovery further revealed that the MHC and IFN response genes in these cells exhibit moderate epigenetic activity, which is significantly associated with the low objective response rates in checkpoint blockade immunotherapy. Our findings uncovered the critical roles of HNF4A and the cell populations within liver metastatic CRC cells might serve as crucial therapeutic targets for addressing liver metastasis and improving the immunotherapy response in patients with CRC.
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Affiliation(s)
- Shasha Li
- Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, Medical Center for Comprehensive Weight Control, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China.
| | - Ming Yang
- Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Shuaishuai Teng
- Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Kequan Lin
- Department of Cardiology of The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China
| | - Yumei Wang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Yanmei Zhang
- Biomanufacturing Center, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China
| | - Wei Guo
- Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Haining 314400, China; Institute of Hematology, the First Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310029, China
| | - Dong Wang
- State Key Laboratory of Southwestern Chinese Medicine Resources, School of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
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Sun Z, Chen X, Huang X, Wu Y, Shao L, Zhou S, Zheng Z, Lin Y, Chen S. Cuproptosis and Immune-Related Gene Signature Predicts Immunotherapy Response and Prognosis in Lung Adenocarcinoma. Life (Basel) 2023; 13:1583. [PMID: 37511958 PMCID: PMC10381686 DOI: 10.3390/life13071583] [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: 05/06/2023] [Revised: 07/07/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
Cuproptosis and associated immune-related genes (IRG) have been implicated in tumorigenesis and tumor progression. However, their effects on lung adenocarcinoma (LUAD) have not been elucidated. Therefore, we investigated the impact of cuproptosis-associated IRGs on the immunotherapy response and prognosis of LUAD using a bioinformatical approach and in vitro experiments analyzing clinical samples. Using the cuproptosis-associated IRG signature, we classified LUAD into two subtypes, cluster 1 and cluster 2, and identified three key cuproptosis-associated IRGs, NRAS, TRAV38-2DV8, and SORT1. These three genes were employed to establish a risk model and nomogram, and to classify the LUAD cohort into low- and high-risk subgroups. Biofunctional annotation revealed that cluster 2, remarkably downregulating epigenetic, stemness, and proliferation pathways activity, had a higher overall survival (OS) and immunoinfiltration abundance compared to cluster 1. Real-time quantitative PCR (RT-qPCR) validated the differential expression of these three genes in both subgroups. scRNA-seq demonstrated elevated expression of NRAS and SORT1 in macrophages. Immunity and oncogenic and stromal activation pathways were dramatically enriched in the low-risk subgroup, and patients in this subgroup responded better to immunotherapy. Our data suggest that the cuproptosis-associated IRG signature can be used to effectively predict the immunotherapy response and prognosis in LUAD. Our work provides enlightenment for immunotherapy response assessment, prognosis prediction, and the development of potential prognostic biomarkers for LUAD patients.
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Affiliation(s)
- Zihao Sun
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Xiujing Chen
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Xiaoning Huang
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Yanfen Wu
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Lijuan Shao
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Key Laboratory of Cancer Immunotherapy of Guangdong Higher Education Institutes, Guangzhou 510080, China
| | - Suna Zhou
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Zhu Zheng
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
| | - Yiguang Lin
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Key Laboratory of Cancer Immunotherapy of Guangdong Higher Education Institutes, Guangzhou 510080, China
- Research & Development Division, Guangzhou Anjie Biomedical Technology Co., Ltd., Guangzhou 510535, China
| | - Size Chen
- Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Guangdong Provincial Engineering Research Center for Esophageal Cancer Precision Therapy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou 510080, China
- Key Laboratory of Cancer Immunotherapy of Guangdong Higher Education Institutes, Guangzhou 510080, China
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Shi H, Huang J, Wang X, Li R, Shen Y, Jiang B, Ran J, Cai R, Guo F, Wang Y, Ren G. Development and validation of a copper-related gene prognostic signature in hepatocellular carcinoma. Front Cell Dev Biol 2023; 11:1157841. [PMID: 37534104 PMCID: PMC10393034 DOI: 10.3389/fcell.2023.1157841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 07/03/2023] [Indexed: 08/04/2023] Open
Abstract
Introduction: Reliable biomarkers are in need to predict the prognosis of hepatocellular carcinoma (HCC). Whilst recent evidence has established the critical role of copper homeostasis in tumor growth and progression, no previous studies have dealt with the copper-related genes (CRGs) signature with prognostic potential in HCC. Methods: To develop and validate a CRGs prognostic signature for HCC, we retrospectively included 353 and 142 patients as the development and validation cohort, respectively. Copper-related Prognostic Signature (Copper-PSHC) was developed using differentially expressed CRGs with prognostic value. The hazard ratio (HR) and the area under the time-dependent receiver operating characteristic curve (AUC) during 3-year follow-up were utilized to evaluate the performance. Additionally, the Copper-PSHC was combined with age, sex, and cancer stage to construct a Copper-clinical-related Prognostic Signature (Copper-CPSHC), by multivariate Cox regression. We further explored the underlying mechanism of Copper-PSHC by analyzing the somatic mutation, functional enrichment, and tumor microenvironment. Potential drugs for the high-risk group were screened. Results: The Copper-PSHC was constructed with nine CRGs. Patients in the high-risk group demonstrated a significantly reduced overall survival (OS) (adjusted HR, 2.65 [95% CI, 1.83-3.84] and 3.30, [95% CI, 1.27-8.60] in the development and validation cohort, respectively). The Copper-PSHC achieved a 3-year AUC of 0.74 [95% CI, 0.67-0.82] and 0.71 [95% CI, 0.56-0.86] for OS in the development and validation cohort, respectively. Copper-CPSHC yield a 3-year AUC of 0.73 [95% CI, 0.66-0.80] and 0.72 [95% CI, 0.56-0.87] for OS in the development and validation cohort, respectively. Higher tumor mutation burden, downregulated metabolic processes, hypoxia status and infiltrated stroma cells were found for the high-risk group. Six small molecular drugs were screened for the treatment of the high-risk group. Conclusion: Copper-PSHC services as a promising tool to identify HCC with poor prognosis and to improve disease outcomes by providing potential clinical decision support in treatment.
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Affiliation(s)
- Haoting Shi
- Department of Radiation Therapy, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingxuan Huang
- Department of Clinical Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xue Wang
- Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Runchuan Li
- Department of Clinical Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiqing Shen
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, United States
| | - Bowen Jiang
- College of Biophotonics, South China Normal University, Guangzhou, China
| | - Jinjun Ran
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rong Cai
- Department of Radiation Therapy, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fang Guo
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Yufei Wang
- Department of Clinical Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Gang Ren
- Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Li C, Wirth U, Schardey J, Ehrlich-Treuenstätt VV, Bazhin AV, Werner J, Kühn F. An immune-related gene prognostic index for predicting prognosis in patients with colorectal cancer. Front Immunol 2023; 14:1156488. [PMID: 37483596 PMCID: PMC10358773 DOI: 10.3389/fimmu.2023.1156488] [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: 02/01/2023] [Accepted: 06/13/2023] [Indexed: 07/25/2023] Open
Abstract
Background Colorectal cancer (CRC) is one of the most common solid malignant burdens worldwide. Cancer immunology and immunotherapy have become fundamental areas in CRC research and treatment. Currently, the method of generating Immune-Related Gene Prognostic Indices (IRGPIs) has been found to predict patient prognosis as an immune-related prognostic biomarker in a variety of tumors. However, their role in patients with CRC remains mostly unknown. Therefore, we aimed to establish an IRGPI for prognosis evaluation in CRC. Methods RNA-sequencing data and clinical information of CRC patients were retrieved from The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO) databases as training and validation sets, respectively. Immune-related gene data was obtained from the ImmPort and InnateDB databases. The weighted gene co-expression network analysis (WGCNA) was used to identify hub immune-related genes. An IRGPI was then constructed using Cox regression methods. Based on the median risk score of IRGPI, patients could be divided into high-risk and low-risk groups. To further investigate the immunologic differences, Gene set variation analysis (GSVA) studies were conducted. In addition, immune cell infiltration and related functional analysis were used to identify the differential immune cell subsets and related functional pathways. Results We identified 49 immune-related genes associated with the prognosis of CRC, 17 of which were selected for an IRGPI. The IRGPI model significantly differentiates the survival rates of CRC patients in the different groups. The IRGPI as an independent prognostic factor significantly correlates with clinico-pathological factors such as age and tumor stage. Furthermore, we developed a nomogram to improve the clinical utility of the IRGPI score. Immuno-correlation analysis in different IRGPI groups revealed distinct immune cell infiltration (CD4+ T cells resting memory) and associated pathways (macrophages, Type I IFNs responses, iDCs.), providing new insights into the tumor microenvironment. At last, drug sensitivity analysis revealed that the high-risk IRGPI group was sensitive to 11 and resistant to 15 drugs. Conclusion Our study established a promising immune-related risk model for predicting survival in CRC patients. This could help to better understand the correlation between immunity and the prognosis of CRC providing a new perspective for personalized treatment of CRC.
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Affiliation(s)
- Chao Li
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Ulrich Wirth
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Josefine Schardey
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | | | - Alexandr V. Bazhin
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - Jens Werner
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - Florian Kühn
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
- German Cancer Consortium (DKTK), Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
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Tang H, Qiao C, Guo Z, Geng R, Sun Z, Wang Y, Bai C. Necroptosis-related signatures identify two distinct hepatocellular carcinoma subtypes: Implications for predicting drug sensitivity and prognosis. Heliyon 2023; 9:e18136. [PMID: 37519654 PMCID: PMC10372238 DOI: 10.1016/j.heliyon.2023.e18136] [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: 02/09/2023] [Revised: 07/03/2023] [Accepted: 07/08/2023] [Indexed: 08/01/2023] Open
Abstract
Background Necroptosis is associated with oncogenesis, tumor immunity and progression. This research aims to investigate the association of necroptosis-related genes with drug sensitivity and prognosis in hepatocellular carcinoma (HCC). Methods Based on necroptosis-related signatures, HCC patients retrieved from the TCGA database were categorized. Survival outcomes, mutation profile, immune microenvironment, and drug sensitivity between HCC subtypes were further compared. Then, LASSO analysis was performed to construct a necroptosis-related prognostic signature, which was further evaluated using another independent cohort. Results A total of 371 patients with HCC could be categorized into two necroptosis-related subtypes. About 36% of patients were allocated to subtype A, with worse survival, more mutant TP53, and a lower likelihood of immunotherapy response. In contrast, patients in subtype B had a favorable prognosis, with lower expression of immunosuppressive signatures but a lower abundance of B and CD8+ T-cell infiltration. The prognostic risk score calculated using the expression levels of nine genes involved in the necroptosis pathway (MLKL, FADD, XIAP, USP22, UHRF1, CASP8, RIPK3, ZBP1, and FAS) showed a significant association with tumor stage, histologic grade, and Child‒Pugh score. Additionally, the risk score model was proven to be accurate in both the training and independent external validation cohorts and performed better than the TNM staging system and three well-recognized risk score models. Conclusions Based on necroptosis-related signatures, we identified two HCC subtypes with distinctive immune microenvironments, mutation profiles, drug sensitivities, and survival outcomes. A novel well-performing prognostic model was further constructed.
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Affiliation(s)
- Hui Tang
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Caixia Qiao
- Department of Medical Oncology, Liaocheng Third People's Hospital, Liaocheng, China
| | - Zhenwei Guo
- Department of Clinical Laboratory, Liaocheng Third People's Hospital, Liaocheng, China
| | - Ruixuan Geng
- Department of International Medical Services, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Zhao Sun
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yingyi Wang
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chunmei Bai
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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Hu D, Messadi DV. Immune-Related Long Non-Coding RNA Signatures for Tongue Squamous Cell Carcinoma. Curr Oncol 2023; 30:4817-4832. [PMID: 37232821 DOI: 10.3390/curroncol30050363] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/27/2023] [Accepted: 05/04/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND Tongue squamous cell carcinoma (TSCC) represents one of the major subsets of head and neck cancer, which is characterized by unfavorable prognosis, frequent lymph node metastasis, and high mortality rate. The molecular events regulating tongue tumorigenesis remain elusive. In this study, we aimed to identify and evaluate immune-related long non-coding RNAs (lncRNAs) as prognostic biomarkers in TSCC. METHODS The lncRNA expression data for TSCC were obtained from The Cancer Genome Atlas (TCGA) and the immune-related genes were downloaded from the Immunology Database and Analysis Portal (ImmPort). Pearson correlation analysis was performed to identify immune-related lncRNAs. The TCGA TSCC patient cohort was randomly divided into training and testing cohorts. In the training cohort, univariate and multivariate Cox regression analyses were used to determining key immune-related lncRNAs, which were then validated through Cox regression analysis, principal component analysis (PCA), and receiver operating characteristic (ROC) analysis in the testing cohort. RESULTS Six immune-related signature lncRNAs (MIR4713HG, AC104088.1, LINC00534, NAALADL2-AS2, AC083967.1, FNDC1-IT1) were found to have prognostic value in TSCC. Multivariate and univariate cox regression analyses showed that the risk score based on our six-lncRNA model, when compared to other clinicopathological factors (age, gender, stage, N, T), was an important indicator of survival rate. In addition, Kaplan-Meier survival analysis demonstrated significantly higher overall survival in the low-risk patient group than the high-risk patient group within both training and testing cohorts. The ROC analysis indicated that the AUCs for 5-year overall survival were 0.790, 0.691, and 0.721, respectively, for training, testing, and entire cohorts. Finally, PCA analysis demonstrated that the high-risk and low-risk patient groups presented significant deviation regarding their immune status. CONCLUSIONS A prognostic model based on six immune-related signature lncRNAs was established. This six-lncRNA prognostic model has clinical significance and may be helpful in the development of personalized immunotherapy strategies.
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Affiliation(s)
- Daniel Hu
- School of Dentistry, University of California, Los Angeles, CA 90095-1668, USA
| | - Diana V Messadi
- School of Dentistry, University of California, Los Angeles, CA 90095-1668, USA
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA 90095-1668, USA
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Zhang Z, Zhang E. Conversion therapy for advanced hepatocellular carcinoma with vascular invasion: a comprehensive review. Front Immunol 2023; 14:1073531. [PMID: 37180144 PMCID: PMC10169581 DOI: 10.3389/fimmu.2023.1073531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 04/12/2023] [Indexed: 05/15/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common type of liver cancer and has a high mortality rate worldwide. The percentage of HCC patients with vascular invasion at the time of initial HCC diagnosis is 10%-40%. According to most guidelines, HCC with vascular invasion is classified as advanced stage, and resection is only suggested for a minority of such patients. Recently, advances in systemic and locoregional treatments for such patients have resulted in amazing response rates. Therefore, a "conversion therapy" strategy including systemic and locoregional treatments is proposed to select patients from an initially unresectable state to eventually undergo R0 resection. Recently, many studies have proven that conversion therapy followed by subsequent surgery is achievable in well-selected advanced HCC patients and can provide prolonged long-term outcomes. Based on published research, this review has summarized the clinical experience and evidence of conversion treatment in HCC patients with vascular invasion.
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Affiliation(s)
| | - Erlei Zhang
- Research Laboratory and Hepatic Surgery Center, Department of Hepatic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Ji JH, Ha SY, Lee D, Sankar K, Koltsova EK, Abou-Alfa GK, Yang JD. Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma. Int J Mol Sci 2023; 24:7640. [PMID: 37108802 PMCID: PMC10144688 DOI: 10.3390/ijms24087640] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 04/15/2023] [Accepted: 04/18/2023] [Indexed: 04/29/2023] Open
Abstract
Hepatocellular carcinoma (HCC) has one of the highest mortality rates among solid cancers. Late diagnosis and a lack of efficacious treatment options contribute to the dismal prognosis of HCC. Immune checkpoint inhibitor (ICI)-based immunotherapy has presented a new milestone in the treatment of cancer. Immunotherapy has yielded remarkable treatment responses in a range of cancer types including HCC. Based on the therapeutic effect of ICI alone (programmed cell death (PD)-1/programmed death-ligand1 (PD-L)1 antibody), investigators have developed combined ICI therapies including ICI + ICI, ICI + tyrosine kinase inhibitor (TKI), and ICI + locoregional treatment or novel immunotherapy. Although these regimens have demonstrated increasing treatment efficacy with the addition of novel drugs, the development of biomarkers to predict toxicity and treatment response in patients receiving ICI is in urgent need. PD-L1 expression in tumor cells received the most attention in early studies among various predictive biomarkers. However, PD-L1 expression alone has limited utility as a predictive biomarker in HCC. Accordingly, subsequent studies have evaluated the utility of tumor mutational burden (TMB), gene signatures, and multiplex immunohistochemistry (IHC) as predictive biomarkers. In this review, we aim to discuss the current state of immunotherapy for HCC, the results of the predictive biomarker studies, and future direction.
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Affiliation(s)
- Jun Ho Ji
- Division of Hematology and Oncology, Department of Internal Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon 51353, Republic of Korea
- Karsh Division of Gastroenterology and Hepatology, Comprehensive Transplant Center, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Sang Yun Ha
- Karsh Division of Gastroenterology and Hepatology, Comprehensive Transplant Center, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 03181, Republic of Korea
| | - Danbi Lee
- Karsh Division of Gastroenterology and Hepatology, Comprehensive Transplant Center, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Department of Gastroenterology, Liver Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Republic of Korea
| | - Kamya Sankar
- Division of Medical Oncology, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Ekaterina K. Koltsova
- Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Ghassan K. Abou-Alfa
- Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
- Weil Cornell Medicine, Cornell University, New York, NY 14853, USA
| | - Ju Dong Yang
- Karsh Division of Gastroenterology and Hepatology, Comprehensive Transplant Center, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
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Yao N, Jiang W, Wang Y, Song Q, Cao X, Zheng W, Zhang J. An immune-related signature for optimizing prognosis prediction and treatment decision of hepatocellular carcinoma. Eur J Med Res 2023; 28:123. [PMID: 36918943 PMCID: PMC10015788 DOI: 10.1186/s40001-023-01091-w] [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: 07/29/2022] [Accepted: 03/06/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND An immune-related gene signature (IGS) was established for discriminating prognosis, predicting benefit of immunotherapy, and exploring therapeutic options in hepatocellular carcinoma (HCC). METHODS Based on Immune-related hub genes and The Cancer Genome Atlas (TCGA) LIHC dataset (n = 363), an immune-related gene signature (IGS) was established by least absolute shrinkage and selection operator (LASSO) analysis. The prognostic significance and clinical implications of IGS were verified in International Cancer Genome Consortium (ICGC) and Chinese HCC (CHCC) cohorts. The molecular and immune characteristics and the benefit of immune checkpoint inhibitor (ICI) therapy in IGS-defined subgroups were analyzed. In addition, by leveraging the Cancer Therapeutics Response Portal (CTRP) and PRISM Repurposing datasets, we determined the potential therapeutic agents for high IGS-risk patients. RESULTS The IGS was constructed based on 8 immune-related hub genes with individual coefficients. The IGS risk model could robustly predict the survival of HCC patients in TCGA, ICGC, and CHCC cohorts. Compared with 4 previous established immune genes-based signatures, IGS exhibited superior performance in survival prediction. Additionally, for immunological characteristics and enriched pathways, a low-IGS score was correlated with IL-6/JAK/STAT3 signaling, inflammatory response and interferon α/γ response pathways, low TP53 mutation rate, high infiltration level, and more benefit from ICI therapy. In contrast, high IGS score manifested an immunosuppressive microenvironment and activated aggressive pathways. Finally, by in silico screening potential compounds, vindesine, ispinesib and dasatinib were identified as potential therapeutic agents for high-IGS risk patients. CONCLUSIONS This study developed a robust IGS model for survival prediction of HCC patients, providing new insights into integrating tailored risk stratification with precise immunotherapy and screening potentially targeted agents.
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Affiliation(s)
- Ninghua Yao
- Department of Oncology, Affiliated Hospital of Nantong University, Nantong, 226001, People's Republic of China.,Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, 226001, People's Republic of China
| | - Wei Jiang
- Department of Neurology, Affiliated Wuxi No.2 People's Hospital of Nanjing Medical University, Wuxi, People's Republic of China
| | - Yilang Wang
- Department of Oncology, Affiliated Tumor Hospital of Nantong University, Nantong, People's Republic of China
| | - Qianqian Song
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, USA
| | - Xiaolei Cao
- School of Medicine, Nantong University, Nantong, 226001, Jiangsu, China.
| | - Wenjie Zheng
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, 226001, People's Republic of China.
| | - Jie Zhang
- Department of Oncology, Affiliated Hospital of Nantong University, Nantong, 226001, People's Republic of China.
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Liu J, Liu B. CircTNPO3 promotes hepatocellular carcinoma progression by sponging miR-199b-5p and regulating STRN expression. Kaohsiung J Med Sci 2023; 39:221-233. [PMID: 36524450 DOI: 10.1002/kjm2.12631] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 10/12/2022] [Accepted: 11/13/2022] [Indexed: 12/23/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common primary liver tumor, which seriously threatens human health. CircTNPO3 was up-regulated in HCC tissues. However, the regulatory mechanism of circTNPO3 in HCC was still unclear. We aimed to investigate the circTNPO3 function in the development of HCC. qRT-PCR and Western blot examined gene and protein levels. CCK8, EdU, flow cytometry, and Transwell assays were used to detect cell viability, proliferation, apoptosis, and invasion abilities. Dual-luciferase reporter and RIP assays determined the relationship between circTNPO3, miR-199b-5p, and striatin (STRN). The effect of CircTNPO3 on HCC progress was investigated in vivo. CircTNPO3 and STRN were significantly increased, while miR-199b-5p was repressed in HCC tissues or cells. Afterward, miR-199b-5p was negatively correlated with STRN. circTNPO3 was positively correlated with STRN. Knockdown of circTNPO3 inhibited cell viability, proliferation, invasion, and promoted apoptosis, while circTNPO3 overexpression had the opposite results. Furthermore, miR-199b-5p inhibition could eliminate the regulatory effect of sh-circTNPO3 on the proliferation and apoptosis in HCC cells. CircTNPO3 positively regulated STRN expression by targeting miR-199b-5p. MiR-199b-5p suppressed HCC progression by inhibiting STRN expression. Tumor formation in nude mice showed that knockdown of circTNPO3 significantly inhibited tumor growth and suppressed ki-67 levels. CircTNPO3 promoted HCC progression through regulating STRN expression by sponging miR-199b-5p, which provided a strategy for HCC treatment.
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Affiliation(s)
- Jing Liu
- Department of Infection Disease, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - BingJie Liu
- Department of Infection Disease, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
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Licata L, Mariani M, Rossari F, Viale G, Notini G, Naldini MM, Bosi C, Piras M, Dugo M, Bianchini G. Tissue- and liquid biopsy-based biomarkers for immunotherapy in breast cancer. Breast 2023; 69:330-341. [PMID: 37003065 PMCID: PMC10070181 DOI: 10.1016/j.breast.2023.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 03/23/2023] [Accepted: 03/25/2023] [Indexed: 03/29/2023] Open
Abstract
Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy and now represent the mainstay of treatment for many tumor types, including triple-negative breast cancer and two agnostic registrations. However, despite impressive durable responses suggestive of an even curative potential in some cases, most patients receiving ICIs do not derive a substantial benefit, highlighting the need for more precise patient selection and stratification. The identification of predictive biomarkers of response to ICIs may play a pivotal role in optimizing the therapeutic use of such compounds. In this Review, we describe the current landscape of tissue and blood biomarkers that could serve as predictive factors for ICI treatment in breast cancer. The integration of these biomarkers in a "holistic" perspective aimed at developing comprehensive panels of multiple predictive factors will be a major step forward towards precision immune-oncology.
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Affiliation(s)
- Luca Licata
- Department of Medical Oncology, San Raffaele Hospital, Milan, Italy; School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy
| | - Marco Mariani
- Department of Medical Oncology, San Raffaele Hospital, Milan, Italy; School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy
| | - Federico Rossari
- Department of Medical Oncology, San Raffaele Hospital, Milan, Italy; School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy; San Raffaele Telethon Institute for Gene Therapy (SR-Tiget), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Giulia Viale
- Department of Medical Oncology, San Raffaele Hospital, Milan, Italy; School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy
| | - Giulia Notini
- Department of Medical Oncology, San Raffaele Hospital, Milan, Italy; School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy
| | - Matteo Maria Naldini
- Department of Medical Oncology, San Raffaele Hospital, Milan, Italy; School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy; San Raffaele Telethon Institute for Gene Therapy (SR-Tiget), IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Carlo Bosi
- Department of Medical Oncology, San Raffaele Hospital, Milan, Italy; School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy
| | - Marta Piras
- Department of Medical Oncology, San Raffaele Hospital, Milan, Italy
| | - Matteo Dugo
- Department of Medical Oncology, San Raffaele Hospital, Milan, Italy; School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy
| | - Giampaolo Bianchini
- Department of Medical Oncology, San Raffaele Hospital, Milan, Italy; School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy.
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Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy. J Clin Med 2023; 12:jcm12041279. [PMID: 36835813 PMCID: PMC9968102 DOI: 10.3390/jcm12041279] [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: 12/17/2022] [Revised: 01/28/2023] [Accepted: 02/01/2023] [Indexed: 02/08/2023] Open
Abstract
The emergence of immunotherapy has dramatically changed the cancer treatment paradigm and generated tremendous promise in precision medicine. However, cancer immunotherapy is greatly limited by its low response rates and immune-related adverse events. Transcriptomics technology is a promising tool for deciphering the molecular underpinnings of immunotherapy response and therapeutic toxicity. In particular, applying single-cell RNA-seq (scRNA-seq) has deepened our understanding of tumor heterogeneity and the microenvironment, providing powerful help for developing new immunotherapy strategies. Artificial intelligence (AI) technology in transcriptome analysis meets the need for efficient handling and robust results. Specifically, it further extends the application scope of transcriptomic technologies in cancer research. AI-assisted transcriptomic analysis has performed well in exploring the underlying mechanisms of drug resistance and immunotherapy toxicity and predicting therapeutic response, with profound significance in cancer treatment. In this review, we summarized emerging AI-assisted transcriptomic technologies. We then highlighted new insights into cancer immunotherapy based on AI-assisted transcriptomic analysis, focusing on tumor heterogeneity, the tumor microenvironment, immune-related adverse event pathogenesis, drug resistance, and new target discovery. This review summarizes solid evidence for immunotherapy research, which might help the cancer research community overcome the challenges faced by immunotherapy.
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Wang R, Xu H, Chen W, Jin L, Ma Z, Wen L, Wang H, Cao K, Du X, Li M. Gadoxetic acid-enhanced MRI with a focus on LI-RADS v2018 imaging features predicts the prognosis after radiofrequency ablation in small hepatocellular carcinoma. Front Oncol 2023; 13:975216. [PMID: 36816925 PMCID: PMC9932892 DOI: 10.3389/fonc.2023.975216] [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: 06/22/2022] [Accepted: 01/12/2023] [Indexed: 02/05/2023] Open
Abstract
Introduction Gadoxetic acid-enhanced magnetic resonance imaging (MRI) contributes to evaluating the prognosis of small hepatocellular carcinoma (sHCC) following treatment. We have investigated the potential role of gadoxetic acid-enhanced MRI based on LI-RADS (Liver Imaging Reporting and Data System) v2018 imaging features in the prognosis prediction of patients with sHCC treated with radiofrequency ablation (RFA) as the first-line treatment and formulated a predictive nomogram. Methods A total of 204 patients with sHCC who all received RFA as the first-line therapy were enrolled. All patients had undergone gadoxetic acid-enhanced MRI examinations before RFA. Uni- and multivariable analyses for RFS were assessing using a Cox proportional hazards model. A novel nomogram was further constructed for predicting RFS. The clinical capacity of the model was validated according to calibration curves, the concordance index (C-index), and decision curve analyses. Results Alpha fetoprotein (AFP) > 100 ng/ml (HR, 2.006; 95% CI, 1.111-3.621; P = 0.021), rim arterial phase hyperenhancement (APHE) (HR, 2.751; 95% CI, 1.511-5.011; P = 0.001), and targetoid restriction on diffusion-weighted imaging (DWI) (HR, 3.289; 95% CI, 1.832-5.906; P < 0.001) were considered as the independent risk features for recurrence in patients with sHCC treated with RFA. The calibration curves and C-indexes (C-index values of 0.758 and 0.807) showed the superior predictive performance of the integrated nomogram in both the training and validation groups. Discussion The gadoxetic acid-enhanced MRI features based on LI-RADS v2018, including rim APHE, targetoid restriction on DWI, and the AFP level, are the independent risk factors of recurrence in patients with sHCC treated with RFA as the first-line therapy. The predictive clinical-radiological nomogram model was constructed for clinicians to develop individualized treatment and surveillance strategies.
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Affiliation(s)
- Ruizhi Wang
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China
| | - Hengtian Xu
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Wufei Chen
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China
| | - Liang Jin
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China
| | - Zhuangxuan Ma
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China
| | - Lei Wen
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Hongwei Wang
- Department of General Surgery, Huadong Hospital, Fudan University, Shanghai, China
| | - Kun Cao
- Department of Hepatobiliary Surgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Xia Du
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China,*Correspondence: Xia Du, ; Ming Li,
| | - Ming Li
- Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China,*Correspondence: Xia Du, ; Ming Li,
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Sun P, Zhang H, Shi J, Xu M, Cheng T, Lu B, Yang L, Zhang X, Huang J. KRTCAP2 as an immunological and prognostic biomarker of hepatocellular carcinoma. Colloids Surf B Biointerfaces 2023; 222:113124. [PMID: 36634487 DOI: 10.1016/j.colsurfb.2023.113124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/27/2022] [Accepted: 01/01/2023] [Indexed: 01/04/2023]
Abstract
Alterations in protein glycosylation affect tumor progression and immune responses in the tumor microenvironment. Keratinocyte-associated protein 2 (KRTCAP2) encodes the corresponding proteins involved in N-glycosylation. The clinical predictive significance and immune role of KRTCAP2 in hepatocellular carcinoma (HCC) largely remain elusive. Combining bioinformatics tools and multiplex immunohistochemistry analysis, we evaluated the KRTCAP2 expression in the HCC tumor microenvironment. The results showed that KRTCAP2 mRNA and protein expression were markedly increased in HCC tissues. Furthermore, high KRTCAP2 expression was an independent predictive factor of unfavorable prognosis in HCC. Moreover, high KRTCAP2 protein expression was associated with a lower proportion of CD8+ T cells and CD68+ macrophages in the stroma region. There was also a lower proportion of CD8+ T cells in the tumor region with high KRTCAP2 protein expression. Specifically, KRTCAP2 expression showed an inverse relationship with programmed cell death ligand-1 in HCC. Analysis of immunophenoscore showed that the low KRTCAP2 expression group had a stronger ability to predict response to immune checkpoint inhibitors. In conclusion, KRTCAP2 had a significant prognostic value for HCC and was correlated with the immune microenvironment. Our findings suggest that KRTCAP2 is a prognostic marker for HCC patients with potential clinical implications for predicting immunotherapeutic responsiveness.
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Affiliation(s)
- Pingping Sun
- Department of Clinical Biobank, Affiliated Hospital of Nantong University & Medical School of Nantong University, Nantong, Jiangsu 226001, China
| | - Hui Zhang
- Department of Clinical Biobank, Affiliated Hospital of Nantong University & Medical School of Nantong University, Nantong, Jiangsu 226001, China
| | - Jiawen Shi
- Department of Clinical Biobank, Affiliated Hospital of Nantong University & Medical School of Nantong University, Nantong, Jiangsu 226001, China
| | - Manyu Xu
- Department of Clinical Biobank, Affiliated Hospital of Nantong University & Medical School of Nantong University, Nantong, Jiangsu 226001, China
| | - Tong Cheng
- Department of Clinical Biobank, Affiliated Hospital of Nantong University & Medical School of Nantong University, Nantong, Jiangsu 226001, China
| | - Bing Lu
- Department of Clinical Biobank, Affiliated Hospital of Nantong University & Medical School of Nantong University, Nantong, Jiangsu 226001, China
| | - Lei Yang
- Department of Clinical Biobank, Affiliated Hospital of Nantong University & Medical School of Nantong University, Nantong, Jiangsu 226001, China
| | - Xiaojing Zhang
- Department of Clinical Biobank, Affiliated Hospital of Nantong University & Medical School of Nantong University, Nantong, Jiangsu 226001, China
| | - Jianfei Huang
- Department of Clinical Biobank, Affiliated Hospital of Nantong University & Medical School of Nantong University, Nantong, Jiangsu 226001, China.
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Mou L, Pu Z, Luo Y, Quan R, So Y, Jiang H. Construction of a lipid metabolism-related risk model for hepatocellular carcinoma by single cell and machine learning analysis. Front Immunol 2023; 14:1036562. [PMID: 36936948 PMCID: PMC10014552 DOI: 10.3389/fimmu.2023.1036562] [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: 09/04/2022] [Accepted: 02/15/2023] [Indexed: 03/05/2023] Open
Abstract
One of the most common cancers is hepatocellular carcinoma (HCC). Numerous studies have shown the relationship between abnormal lipid metabolism-related genes (LMRGs) and malignancies. In most studies, the single LMRG was studied and has limited clinical application value. This study aims to develop a novel LMRG prognostic model for HCC patients and to study its utility for predictive, preventive, and personalized medicine. We used the single-cell RNA sequencing (scRNA-seq) dataset and TCGA dataset of HCC samples and discovered differentially expressed LMRGs between primary and metastatic HCC patients. By using the least absolute selection and shrinkage operator (LASSO) regression machine learning algorithm, we constructed a risk prognosis model with six LMRGs (AKR1C1, CYP27A1, CYP2C9, GLB1, HMGCS2, and PLPP1). The risk prognosis model was further validated in an external cohort of ICGC. We also constructed a nomogram that could accurately predict overall survival in HCC patients based on cancer status and LMRGs. Further investigation of the association between the LMRG model and somatic tumor mutational burden (TMB), tumor immune infiltration, and biological function was performed. We found that the most frequent somatic mutations in the LMRG high-risk group were CTNNB1, TTN, TP53, ALB, MUC16, and PCLO. Moreover, naïve CD8+ T cells, common myeloid progenitors, endothelial cells, granulocyte-monocyte progenitors, hematopoietic stem cells, M2 macrophages, and plasmacytoid dendritic cells were significantly correlated with the LMRG high-risk group. Finally, gene set enrichment analysis showed that RNA degradation, spliceosome, and lysosome pathways were associated with the LMRG high-risk group. For the first time, we used scRNA-seq and bulk RNA-seq to construct an LMRG-related risk score model, which may provide insights into more effective treatment strategies for predictive, preventive, and personalized medicine of HCC patients.
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Affiliation(s)
- Lisha Mou
- Imaging Department, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, China
- MetaLife Center, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, China
| | - Zuhui Pu
- Imaging Department, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, China
| | - Yongxiang Luo
- Department of General Surgery, The First People's Hospital of Qinzhou/The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, Guangxi, China
| | - Ryan Quan
- MetaLife Center, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, China
| | - Yunhu So
- MetaLife Center, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, China
| | - Hui Jiang
- Department of General Surgery, The First People's Hospital of Qinzhou/The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou, Guangxi, China
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Role of immune-related lncRNAs--PRKCQ-AS1 and EGOT in the regulation of IL-1β, IL-6 and IL-8 expression in human gingival fibroblasts with TNF-α stimulation. J Dent Sci 2023; 18:184-190. [PMID: 36643260 PMCID: PMC9831783 DOI: 10.1016/j.jds.2022.06.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 06/13/2022] [Indexed: 01/18/2023] Open
Abstract
Background/purpose It was reported that lncRNAs have an effect on immune-related diseases, however, their roles in periodontitis remain to be investigated. The aim of this study was to look for immune-related lncRNAs in periodontitis, and to preliminarily explore their function in vitro. Materials and methods CIBERSORT was used to analyze abundance of immune cell in the periodontal tissue. Correlation between the expression profile of lncRNAs and abundance of immune cell was calculated and immune-related lncRNAs were identified. The expressions of immune-related lncRNAs identified were validated by RT-qPCR with 15 periodontitis and 15 healthy gingival tissues. The expressions of PRKCQ-AS1 and EGOT in HGFs were detected under the stimulation of different concentrations of TNF-α (0, 10, 15, 20, 30 ng/mL) and different duration (0, 12, 24 and 48 h). Then, siRNA was used to silence PRKCQ-AS1 and EGOT in HGFs. The expression level of IL-1β, IL-6, IL-8 of the HGFs after stimulated by 15 ng/mL TNF-α, and the activation of NF-κB pathway was observed. Results PRKCQ-AS1 and EGOT were identified as top 2 immune-related lncRNAs in periodontal tissues. The expressions of PRKCQ-AS1 and EGOT were significantly up-regulated in inflamed periodontal tissue and in HGFs under TNF-α stimulation. After knock-down of PRKCQ-AS1 and EGOT, expression level of IL-1β, IL-6, and IL-8 in HGFs with TNF-α stimulation were decreased, and activation of NF-κB pathway was inhibited. Conclusion PRKCQ-AS1 and EGOT were firstly identified as immune-related lncRNAs in periodontal tissue, and they regulate the expression of IL-1β, IL-6, and IL-8 of HGFs through the NF-κB pathway.
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Che B, Zhang W, Li W, Tang K, Yin J, Liu M, Xu S, Huang T, Yu Y, Huang K, Peng Z, Zha C. Bacterial lipopolysaccharide-related genes are involved in the invasion and recurrence of prostate cancer and are related to immune escape based on bioinformatics analysis. Front Oncol 2023; 13:1141191. [PMID: 37188204 PMCID: PMC10175693 DOI: 10.3389/fonc.2023.1141191] [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: 01/10/2023] [Accepted: 04/13/2023] [Indexed: 05/17/2023] Open
Abstract
Background The composition of the tumor microbial microenvironment participates in the whole process of tumor disease. However, due to the limitations of the current technical level, the depth and breadth of the impact of microorganisms on tumors have not been fully recognized, especially in prostate cancer (PCa). Therefore, the purpose of this study is to explore the role and mechanism of the prostate microbiome in PCa based on bacterial lipopolysaccharide (LPS)-related genes by means of bioinformatics. Methods The Comparative Toxicogenomics Database (CTD) was used to find bacterial LPS- related genes. PCa expression profile data and clinical data were acquired from TCGA, GTEx, and GEO. The differentially expressed LPS-related hub genes (LRHG) were obtained by Venn diagram, and gene set enrichment analysis (GSEA) was used to investigate the putative molecular mechanism of LRHG. The immune infiltration score of malignancies was investigated using single-sample gene set enrichment analysis (ssGSEA). Using univariate and multivariate Cox regression analysis, a prognostic risk score model and nomogram were developed. Results 6 LRHG were screened. LRHG were involved in functional phenotypes such as tumor invasion, fat metabolism, sex hormone response, DNA repair, apoptosis, and immunoregulation. And it can regulate the immune microenvironment in the tumor by influencing the antigen presentation of immune cells in the tumor. And a prognostic risk score and the nomogram, which were based on LRHG, showed that the low-risk score has a protective effect on patients. Conclusion Microorganisms in the PCa microenvironment may use complex mechanism and networks to regulate the occurrence and development of PCa. Bacterial lipopolysaccharide-related genes can help build a reliable prognostic model and predict progression-free survival in patients with prostate cancer.
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Affiliation(s)
- Bangwei Che
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Wenjun Zhang
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Wei Li
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Kaifa Tang
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
- Department of Urology, The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, China
- *Correspondence: Kaifa Tang,
| | - Jingju Yin
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Miao Liu
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Shenghan Xu
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Tao Huang
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Ying Yu
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Kunyuan Huang
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Zheng Peng
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
| | - Cheng Zha
- School of Clinical Medicine, Guizhou Medical University, Guiyang, China
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Identification of an Immune-Related Gene Signature Associated with Prognosis and Tumor Microenvironment in Esophageal Cancer. BIOMED RESEARCH INTERNATIONAL 2022; 2022:7413535. [PMID: 36588538 PMCID: PMC9803573 DOI: 10.1155/2022/7413535] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/30/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022]
Abstract
Background Esophageal cancer (EC) is a common malignant tumor of the digestive system with high mortality and morbidity. Current evidence suggests that immune cells and molecules regulate the initiation and progression of EC. Accordingly, it is necessary to identify immune-related genes (IRGs) affecting the biological behaviors and microenvironmental characteristics of EC. Methods Bioinformatics methods, including differential expression analysis, Cox regression, and immune infiltration prediction, were conducted using R software to analyze the Gene Expression Omnibus (GEO) dataset. The Cancer Genome Atlas (TCGA) cohort was used to validate the prognostic signature. Patients were stratified into high- and low-risk groups for further analyses, including functional enrichment, immune infiltration, checkpoint relevance, clinicopathological characteristics, and therapeutic sensitivity analyses. Results A prognostic signature was established based on 21 IRGs (S100A7, S100A7A, LCN1, CR2, STAT4, GAST, ANGPTL5, TRAV39, F2RL2, PGLYRP3, KLRD1, TRIM36, PDGFA, SLPI, PCSK2, APLN, TICAM1, ITPR3, MAPK9, GATA4, and PLAU). Compared with high-risk patients, better overall survival rates and clinicopathological characteristics were found in low-risk patients. The areas under the curve of the two cohorts were 0.885 and 0.718, respectively. Higher proportions of resting CD4+ memory T lymphocytes, M2 macrophages, and resting dendritic cells and lower proportions of follicular helper T lymphocytes, plasma cells, and neutrophils were found in the high-risk tumors. Moreover, the high-risk group showed higher expression of CD44 and TNFSF4, lower expression of PDCD1 and CD40, and higher TIDE scores, suggesting they may respond poorly to immunotherapy. High-risk patients responded better to chemotherapeutic agents such as docetaxel, doxorubicin, and gemcitabine. Furthermore, IRGs associated with tumor progression, including PDGFA, ITPR3, SLPI, TICAM1, and GATA4, were identified. Conclusion Our immune-related signature yielded reliable value in evaluating the prognosis, microenvironmental characteristics, and therapeutic sensitivity of EC and may help with the precise treatment of this patient population.
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Wan Y, He Y, Yang Q, Cheng Y, Li Y, Zhang X, Zhang W, Dai H, Yu Y, Li T, Xiong Z, Wan H. Construction of a prognostic assessment model for colon cancer patients based on immune-related genes and exploration of related immune characteristics. Front Cell Dev Biol 2022; 10:993580. [PMID: 36589748 PMCID: PMC9800979 DOI: 10.3389/fcell.2022.993580] [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: 07/13/2022] [Accepted: 11/15/2022] [Indexed: 12/23/2022] Open
Abstract
Objectives: To establish a novel risk score model that could predict the survival and immune response of patients with colon cancer. Methods: We used The Cancer Genome Atlas (TCGA) database to get mRNA expression profile data, corresponding clinical information and somatic mutation data of patients with colon cancer. Limma R software package and univariate Cox regression were performed to screen out immune-related prognostic genes. GO (Gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) were used for gene function enrichment analysis. The risk scoring model was established by Lasso regression and multivariate Cox regression. CIBERSORT was conducted to estimate 22 types of tumor-infiltrating immune cells and immune cell functions in tumors. Correlation analysis was used to demonstrate the relationship between the risk score and immune escape potential. Results: 679 immune-related genes were selected from 7846 differentially expressed genes (DEGs). GO and KEGG analysis found that immune-related DEGs were mainly enriched in immune response, complement activation, cytokine-cytokine receptor interaction and so on. Finally, we established a 3 immune-related genes risk scoring model, which was the accurate independent predictor of overall survival (OS) in colon cancer. Correlation analysis indicated that there were significant differences in T cell exclusion potential in low-risk and high-risk groups. Conclusion: The immune-related gene risk scoring model could contribute to predicting the clinical outcome of patients with colon cancer.
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Affiliation(s)
- Yanhua Wan
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China,Department of General Surgery, The First People’s Hospital of Jiujiang, Jiujiang, China
| | - Yingcheng He
- Queen Mary College of Nanchang University, Nanchang, China
| | - Qijun Yang
- Queen Mary College of Nanchang University, Nanchang, China
| | - Yunqi Cheng
- Queen Mary College of Nanchang University, Nanchang, China
| | - Yuqiu Li
- Queen Mary College of Nanchang University, Nanchang, China
| | - Xue Zhang
- Queen Mary College of Nanchang University, Nanchang, China
| | - Wenyige Zhang
- Queen Mary College of Nanchang University, Nanchang, China
| | - Hua Dai
- Department of Pathology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yanqing Yu
- Department of Pathology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Taiyuan Li
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China,*Correspondence: Taiyuan Li, ; Zhenfang Xiong, ; Hongping Wan,
| | - Zhenfang Xiong
- Department of Pathology, The First Affiliated Hospital of Nanchang University, Nanchang, China,*Correspondence: Taiyuan Li, ; Zhenfang Xiong, ; Hongping Wan,
| | - Hongping Wan
- Department of Pathology, The First Affiliated Hospital of Nanchang University, Nanchang, China,*Correspondence: Taiyuan Li, ; Zhenfang Xiong, ; Hongping Wan,
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Li X, Sun W, Ding X, Li W, Chen J. Prognostic model of immune checkpoint inhibitors combined with anti-angiogenic agents in unresectable hepatocellular carcinoma. Front Immunol 2022; 13:1060051. [PMID: 36532029 PMCID: PMC9751696 DOI: 10.3389/fimmu.2022.1060051] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 11/21/2022] [Indexed: 12/03/2022] Open
Abstract
Background The combination of immune checkpoint inhibitors (ICIs) and anti-angiogenic agents has shown promising efficacy in unresectable hepatocellular carcinoma (HCC), but until now no clinical prognostic models or predictive biomarkers have been established. Methods From 2016 to 2021, a total of 258 HCCs treated with ICIs and tyrosine kinase inhibitors (TKIs) were retrospectively enrolled, as the study cohort. Patients' baseline data was extracted by least absolute and shrinkage selection operator (LASSO) and Cox regression. Finally, a prognostic model in the form of nomogram was developed. Model performance was assessed in terms of discrimination, calibration, and clinical utility. A 5-fold cross-validation was used to evaluate the internal repeatability of the model. In addition, the patient cohort was divided into three subgroups according to nomogram scores. Their survivals were estimated by Kaplan-Meier methods and the differences were analyzed using log-rank tests. Results Seven clinical parameters were selected: Eastern Cooperative Oncology Group performance status (ECOG PS), combination of transarterial chemoembolization (TACE), extrahepatic metastasis (EHM), platelet to lymphocyte ratio (PLR), alanine aminotransferase (ALT), alpha-fetoprotein (AFP), and Child-Pugh score. The model had an area under the curve (AUC) of 0.777 at 1 year and 0.772 at 2 years. Receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) showed that the discrimination, consistency and applicability of the model were good. In addition, cross-validation validated the discrimination of the model, and the C index value of the model is 0.7405. The median overall survival (OS) of the high-, medium- and low-risk subgroups was 7.58, 17.50 and 53.17 months, respectively, with a significant difference between the groups (P < 0.0001). Conclusion We developed a comprehensive and simple prognostic model for the combination of ICIs plus TKIs. And it may predict the efficacy of the combination regimen for unresectable HCC.
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Affiliation(s)
| | | | | | - Wei Li
- *Correspondence: Jinglong Chen, ; Wei Li,
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Zhao L, Teng Q, Liu Y, Chen H, Chong W, Du F, Xiao K, Sang Y, Ma C, Cui J, Shang L, Zhang R. Machine learning-based identification of a novel prognosis-related long noncoding RNA signature for gastric cancer. Front Cell Dev Biol 2022; 10:1017767. [PMID: 36438557 PMCID: PMC9691877 DOI: 10.3389/fcell.2022.1017767] [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: 08/12/2022] [Accepted: 10/26/2022] [Indexed: 08/30/2023] Open
Abstract
Gastric cancer (GC) is one of the most common malignancies with a poor prognosis. Immunotherapy has attracted much attention as a treatment for a wide range of cancers, including GC. However, not all patients respond to immunotherapy. New models are urgently needed to accurately predict the prognosis and the efficacy of immunotherapy in patients with GC. Long noncoding RNAs (lncRNAs) play crucial roles in the occurrence and progression of cancers. Recent studies have identified a variety of prognosis-related lncRNA signatures in multiple cancers. However, these studies have some limitations. In the present study, we developed an integrative analysis to screen risk prediction models using various feature selection methods, such as univariate and multivariate Cox regression, least absolute shrinkage and selection operator (LASSO), stepwise selection techniques, subset selection, and a combination of the aforementioned methods. We constructed a 9-lncRNA signature for predicting the prognosis of GC patients in The Cancer Genome Atlas (TCGA) cohort using a machine learning algorithm. After obtaining a risk model from the training cohort, we further validated the model for predicting the prognosis in the test cohort, the entire dataset and two external GEO datasets. Then we explored the roles of the risk model in predicting immune cell infiltration, immunotherapeutic responses and genomic mutations. The results revealed that this risk model held promise for predicting the prognostic outcomes and immunotherapeutic responses of GC patients. Our findings provide ideas for integrating multiple screening methods for risk modeling through machine learning algorithms.
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Affiliation(s)
- Linli Zhao
- Department of Ultrasound, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Qiong Teng
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Yuan Liu
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Hao Chen
- Clinical Epidemiology Unit, Clinical Research Center of Shandong University, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Wei Chong
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Key Laboratory of Engineering of Shandong Province, Shandong Provincial Hospital, Jinan, Shandong, China
- Medical Science and Technology Innovation Center, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Fengying Du
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Kun Xiao
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Yaodong Sang
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Chenghao Ma
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
| | - Jian Cui
- BioGeniusCloud, Shanghai BioGenius Biotechnology Center, Shanghai, China
| | - Liang Shang
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Ronghua Zhang
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
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Pu D, Liu D, Li C, Chen C, Che Y, Lv J, Yang Y, Wang X. A novel ten-gene prognostic signature for cervical cancer based on CD79B-related immunomodulators. Front Genet 2022; 13:933798. [PMID: 36406115 PMCID: PMC9666757 DOI: 10.3389/fgene.2022.933798] [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: 05/05/2022] [Accepted: 09/09/2022] [Indexed: 01/25/2023] Open
Abstract
The identification of immune-related prognostic biomarkers opens up the possibility of developing new immunotherapy strategies against tumors. In this study, we investigated immune-related biomarkers in the tumor microenvironment to predict the prognosis of cervical cancer (CC) patients. ESTIMATE and CIBERSORT algorithms were used to calculate the abundance of tumor-infiltrating immune cells (TICs) and the amount of immune and stromal components in cervical samples (n = 309) from The Cancer Genome Atlas. Ten immune-related differentially expressed genes associated with CC survival were identified via intersection analyses of multivariate Cox regression and protein-protein interactions. CD79B was chosen for further study, and its prognostic value and role in anti-CC immune functions were analyzed. Differential expression analysis and qRT-PCR validation both revealed that CD79B expression was down-regulated in CC tissues. Survival analysis suggested that a high level of CD79B expression was associated with good prognosis. In the clinical correlation analysis, CD79B expression was found to be related to primary therapy outcome, race, histological type, degree of cell differentiation, disease-specific survival, and progression-free interval. GSEA showed that the function and pathway of CD79B were mainly related to immune activities. Meanwhile, CD79B expression was correlated with 10 types of TICs. Based on CD79B-associated immunomodulators, a novel immune prognostic signature consisting of 10 genes (CD96, LAG3, PDCD1, TIGIT, CD27, KLRK1, LTA, PVR, TNFRSF13C, and TNFRSF17) was established and validated as possessing good independent prognostic value for CC patients. Finally, a nomogram to predict personalized 3- and 5-year overall survival probabilities in CC patients was built and validated. In summary, our findings demonstrated that CD79B might be a potential prognostic biomarker for CC. The 10-gene prognostic signature independently predicted the overall survival of patients with CC, which could improve individualized treatment and aid clinical decision-making.
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Affiliation(s)
- Dan Pu
- Department of Microbiology and Parasitology, College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Dan Liu
- Department of Microbiology and Parasitology, College of Basic Medical Sciences, China Medical University, Shenyang, China,Department of Gynecology, The Fourth Affiliated Hospital of China Medical University, Shenyang, China
| | - Can Li
- Department of Microbiology and Parasitology, College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Chunyan Chen
- Department of Microbiology and Parasitology, College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Yuxin Che
- Department of Microbiology and Parasitology, College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Jiaoyan Lv
- Department of Microbiology and Parasitology, College of Basic Medical Sciences, China Medical University, Shenyang, China
| | - Yang Yang
- Department of Medical Basic Experimental Teaching Center, China Medical University, Shenyang, China,*Correspondence: Yang Yang, ; Xuelian Wang,
| | - Xuelian Wang
- Department of Microbiology and Parasitology, College of Basic Medical Sciences, China Medical University, Shenyang, China,*Correspondence: Yang Yang, ; Xuelian Wang,
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Trans-Arterial Chemoembolization Plus Systemic Treatments for Hepatocellular Carcinoma: An Update. J Pers Med 2022; 12:jpm12111788. [PMID: 36579504 PMCID: PMC9697413 DOI: 10.3390/jpm12111788] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 10/23/2022] [Accepted: 10/25/2022] [Indexed: 02/01/2023] Open
Abstract
Recent years have seen the advent of novel treatment options for hepatocellular carcinoma (HCC). Given a strong biological rationale supporting this strategy, multiple studies have explored the role of combination treatments including locoregional plus systemic therapies to produce a synergistic effect and enhance antitumor activity. Among locoregional therapies, several clinical trials assessing trans-arterial chemoembolization (TACE) have been recently presented and published. In the current paper, we discuss available evidence and current and future research on combined TACE and systemic treatments, including antiangiogenic agents, immune checkpoint inhibitors, and immune-based combinations for HCC patients.
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Long M, Zhou Z, Wei X, Lin Q, Qiu M, Zhou Y, Chen P, Jiang Y, Wen Q, Liu Y, Li R, Zhou X, Yu H. A novel risk score based on immune-related genes for hepatocellular carcinoma as a reliable prognostic biomarker and correlated with immune infiltration. Front Immunol 2022; 13:1023349. [PMID: 36353638 PMCID: PMC9637590 DOI: 10.3389/fimmu.2022.1023349] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 09/15/2022] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND Immunological-related genes (IRGs) play a critical role in the immune microenvironment of tumors. Our study aimed to develop an IRG-based survival prediction model for hepatocellular carcinoma (HCC) patients and to investigate the impact of IRGs on the immune microenvironment. METHODS Differentially expressed IRGs were obtained from The Genomic Data Commons Data Portal (TCGA) and the immunology database and analysis portal (ImmPort). The univariate Cox regression was used to identify the IRGs linked to overall survival (OS), and a Lasso-regularized Cox proportional hazard model was constructed. The International Cancer Genome Consortium (ICGC) database was used to verify the prediction model. ESTIMATE and CIBERSORT were used to estimate immune cell infiltration in the tumor immune microenvironment (TIME). RNA sequencing was performed on HCC tissue specimens to confirm mRNA expression. RESULTS A total of 401 differentially expressed IRGs were identified, and 63 IRGs were found related to OS on the 237 up-regulated IRGs by univariate Cox regression analyses. Finally, five IRGs were selected by the LASSO Cox model, including SPP1, BIRC5, STC2, GLP1R, and RAET1E. This prognostic model demonstrated satisfactory predictive value in the ICGC dataset. The risk score was an independent predictive predictor for OS in HCC patients. Immune-related analysis showed that the immune infiltration level in the high-risk group was higher, suggesting that the 5-IRG signature may play an important role in mediating immune escape and immune resistance in the TIME of HCC. Finally, we confirmed the 5-IRG signature is highly expressed in 65 HCC patients with good predictive power. CONCLUSION We established and verified a new prognosis model for HCC patients based on survival-related IRGs, and the signature could provide new insights into the prognosis of HCC.
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Affiliation(s)
- Meiying Long
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Zihan Zhou
- Department of Cancer Prevention and Control, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Xueyan Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Qiuling Lin
- Department of Clinical Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Moqin Qiu
- Department of Respiratory Oncology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Yunxiang Zhou
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Peiqin Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Yanji Jiang
- Scientific Research Department, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Qiuping Wen
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Yingchun Liu
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Runwei Li
- Department of Environmental and Occupational Health, School of Public Health, Indiana University, Bloomington, IN, United States
| | - Xianguo Zhou
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Hongping Yu
- Department of Experimental Research, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
- Key Laboratory of Early Prevention and Treatment for Regional High-Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi, China
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