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Sundell GN, Tao SC. Phage immunoprecipitation and sequencing-a versatile technique for mapping the antibody reactome. Mol Cell Proteomics 2024:100831. [PMID: 39168282 DOI: 10.1016/j.mcpro.2024.100831] [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: 04/10/2024] [Revised: 08/13/2024] [Accepted: 08/16/2024] [Indexed: 08/23/2024] Open
Abstract
Characterizing the antibody reactome for circulating antibodies provide insight into pathogen exposure, allergies and autoimmune diseases. This is important for biomarker discovery, clinical diagnosis, and prognosis of disease progression, as well as population-level insights into the immune system. The emerging technology phage display immunoprecipitation and sequencing (PhIP-seq) is a high-throughput method for identifying antigens/epitopes of the antibody reactome. In PhIP-seq, libraries with sequences of defined lengths and overlapping segments are bioinformatically designed using naturally occurring proteins and cloned into phage genomes to be displayed on the surface. These libraries are used in immunoprecipitation experiments of circulating antibodies. This can be done with parallel samples from multiple sources, and the DNA inserts from the bound phages are barcoded and subjected to next-generation sequencing for hit-determination. PhIP-seq is a powerful technique for characterizing the antibody reactome that has undergone rapid advances in recent years. In this review, we comprehensively describe the history of PhIP-seq and discuss recent advances in library design and applications.
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Affiliation(s)
- Gustav N Sundell
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - Sheng-Ce Tao
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China.
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2
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Xue Y, Zhang Y, Su Y, Zhao J, Yu D, Jo Y, Joo J, Lee HJ, Ryu D, Wei S. The implicated role of GDF15 in gastrointestinal cancer. Eur J Clin Invest 2024:e14290. [PMID: 39044314 DOI: 10.1111/eci.14290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 07/03/2024] [Indexed: 07/25/2024]
Abstract
BACKGROUND Growth differentiation factor 15 (GDF15), a stress-responsive cytokine from transforming growth factor superfamily, is highly expressed in mammalian tissues, including pancreas, stomach and intestine under pathological conditions. In particular, elevated levels of GDF15 might play an important role in the development and progression of various gastrointestinal cancers (GCs), suggesting its potential as a promising target for disease prediction and treatment. METHODS In this review, systematic reviews addressing the role of GDF15 in GCs were updated, along with the latest clinical trials focussing on the GDF15-associated digestive malignancies. RESULTS The multiple cellular pathways through which GDF15 is involved in the regulation of physiological and pathological conditions were first summarized. Then, GDF15 was also established as a valuable clinical index, functioning as a predictive marker in diverse GCs. Notably, latest clinical treatments targeting GDF15 were also highlighted, demonstrating its promising potential in mitigating and curing digestive malignancies. CONCLUSIONS This review unveils the pivotal roles of GDF15 and its potential as a promising target in the pathogenesis of GCs, which may provide insightful directions for future investigations.
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Affiliation(s)
- Yingqi Xue
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Korea
| | - Yan Zhang
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Korea
- Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon, Korea
| | - Yale Su
- Department of Cardiovascular Surgery, The Second Hospital of Jilin University, Changchun, China
| | - Jiangqi Zhao
- Department of Dermatology, The Second Hospital of Jilin University, Changchun, China
| | - Daoquan Yu
- Department of Hepatological Surgery, Shuangliao Center Hospital, Shuangliao, China
| | - Yunju Jo
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Korea
| | - Jongkil Joo
- Department of Obstetrics and Gynecology, Pusan National University Hospital, Busan, Korea
| | - Hyun Joo Lee
- Department of Obstetrics and Gynecology, Pusan National University Hospital, Busan, Korea
| | - Dongryeol Ryu
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Korea
| | - Shibo Wei
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Korea
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Zdravkova K, Mijanovic O, Brankovic A, Ilicheva PM, Jakovleva A, Karanovic J, Pualic M, Pualic D, Rubel AA, Savvateeva LV, Parodi A, Zamyatnin AA. Unveiling the Roles of Cysteine Proteinases F and W: From Structure to Pathological Implications and Therapeutic Targets. Cells 2024; 13:917. [PMID: 38891048 PMCID: PMC11171618 DOI: 10.3390/cells13110917] [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: 04/06/2024] [Revised: 05/22/2024] [Accepted: 05/23/2024] [Indexed: 06/20/2024] Open
Abstract
Cysteine cathepsins F and W are members of the papain-like cysteine protease family, which have distinct structural features and functional roles in various physiological and pathological processes. This review provides a comprehensive overview of the current understanding of the structure, biological functions, and pathological implications of cathepsins F and W. Beginning with an introduction to these proteases, we delve into their structural characteristics and elucidate their unique features that dictate their enzymatic activities and substrate specificity. We also explore the intricate involvement of cathepsins F and W in malignancies, highlighting their role as potential biomarkers and therapeutic targets in cancer progression. Furthermore, we discuss the emerging roles of these enzymes in immune response modulation and neurological disorders, shedding light on their implications in autoimmune and neurodegenerative diseases. Finally, we review the landscape of inhibitors targeting these proteases, highlighting their therapeutic potential and challenges in clinical translation. This review brings together the diverse facets of cysteine cathepsins F and W, providing insights into their roles in health and disease and guiding future investigations for therapeutic advances.
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Affiliation(s)
- Kristina Zdravkova
- AD Alkaloid Skopje, Boulevard Alexander the Great 12, 1000 Skopje, North Macedonia;
| | - Olja Mijanovic
- Dia-M, LCC, 7 b.3 Magadanskaya Str., 129345 Moscow, Russia;
| | - Ana Brankovic
- Department of Forensic Sciences, Faculty of Forensic Sciences and Engineering, University of Criminal Investigation and Police Studies, Cara Dusana 196, 11000 Belgrade, Serbia;
| | - Polina M. Ilicheva
- Institute of Chemistry, Saratov State University, Astrakhanskaya Street 83, 410012 Saratov, Russia;
| | | | - Jelena Karanovic
- Laboratory for Molecular Biology, Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Vojvode Stepe 444A, 11000 Belgrade, Serbia;
| | - Milena Pualic
- Institute Cardiovascular Diseases Dedinje, Heroja Milana Tepica 1, 11000 Belgrade, Serbia;
| | - Dusan Pualic
- Military Medical Academy, Crnotravska 17, 11000 Belgrade, Serbia;
| | - Aleksandr A. Rubel
- Laboratory of Amyloid Biology, St. Petersburg State University, 199034 St. Petersburg, Russia;
| | - Lyudmila V. Savvateeva
- Institute of Translational Medicine and Biotechnology, Sechenov First Moscow State Medical University, 119991 Moscow, Russia;
| | - Alessandro Parodi
- Research Center for Translational Medicine, Sirius University of Science and Technology, 354340 Sochi, Russia;
| | - Andrey A. Zamyatnin
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, 119234 Moscow, Russia
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, 119992 Moscow, Russia
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4
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Zhang J, Hao W, Liu X, Meng Y, Liu J, Wu L, Zhang Y, Hu X, Fan Y, Qin X. Proteome microarray identifies autoantibody biomarkers for diagnosis of hepatitis B-related hepatocellular carcinoma. Clin Chim Acta 2024; 554:117727. [PMID: 38123112 DOI: 10.1016/j.cca.2023.117727] [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: 09/19/2023] [Revised: 12/15/2023] [Accepted: 12/16/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND AND AIMS Hepatocellular carcinoma (HCC) has the highest mortality rate among malignant tumors worldwide. This study aimed to analyze the biological characteristics of serum proteins in hepatitis B (HBV)-related liver diseases, identify diagnostic biomarkers for HBV-infected HCC, and provide a scientific basis for its prevention and treatment. MATERIALS AND METHODS We used HuProt arrays to identify candidate biomarkers for HBV-related liver diseases and verified the differential biomarkers by using an HCC-focused array. The biological characteristics of serum proteins were analyzed via bioinformatics. Serum biomarkers levels were validated by ELISA. RESULTS We identified 547 differentially expressed proteins from HBV-infected HCC in a screening cohort. After analyzing the biological characteristics of serum proteins, we identified 10 potential differential autoantibodies against tumor-associated antigens (TAAbs) and a candidate biomarker panel (APEX2, RCSD1, and TP53) for the diagnosis of HBV-associated HCC with 61.9% sensitivity and 81.7% specificity in an HCC-focused array validation cohort. Finally, the protein levels and diagnostic capability of the biomarker panel were confirmed in a large-sample validation cohort, and this panel was found to be superior to alpha-fetoprotein, the standard hallmark for the diagnosis of HCC. CONCLUSION The APEX2, RCSD1, and TP53 biomarker panels could be used for the diagnosis of HBV-associated HCC, providing a scientific basis for clinical practice.
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Affiliation(s)
- Jin Zhang
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, No.36 Sanhao Street, Heping District, Shenyang 110004, China; Liaoning Clinical Research Center for Laboratory Medicine, No.36 Sanhao Street, Heping District, Shenyang 110004, China
| | - Wudi Hao
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, No.36 Sanhao Street, Heping District, Shenyang 110004, China; Liaoning Clinical Research Center for Laboratory Medicine, No.36 Sanhao Street, Heping District, Shenyang 110004, China
| | - Xinxin Liu
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, No.36 Sanhao Street, Heping District, Shenyang 110004, China; Department of Laboratory Medicine, Shandong Provincial Third Hospital, Shandong University, No.11 Wuyingshan Middle Road, Tianqiao District, Jinan 250031, China
| | - Yuan Meng
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, No.36 Sanhao Street, Heping District, Shenyang 110004, China; Liaoning Clinical Research Center for Laboratory Medicine, No.36 Sanhao Street, Heping District, Shenyang 110004, China
| | - Jianhua Liu
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, No.36 Sanhao Street, Heping District, Shenyang 110004, China; Liaoning Clinical Research Center for Laboratory Medicine, No.36 Sanhao Street, Heping District, Shenyang 110004, China
| | - Lina Wu
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, No.36 Sanhao Street, Heping District, Shenyang 110004, China; Liaoning Clinical Research Center for Laboratory Medicine, No.36 Sanhao Street, Heping District, Shenyang 110004, China
| | - Yue Zhang
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, No.36 Sanhao Street, Heping District, Shenyang 110004, China; Liaoning Clinical Research Center for Laboratory Medicine, No.36 Sanhao Street, Heping District, Shenyang 110004, China
| | - Xingwei Hu
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, No.36 Sanhao Street, Heping District, Shenyang 110004, China; Liaoning Clinical Research Center for Laboratory Medicine, No.36 Sanhao Street, Heping District, Shenyang 110004, China
| | - Yan Fan
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, No.36 Sanhao Street, Heping District, Shenyang 110004, China; Liaoning Clinical Research Center for Laboratory Medicine, No.36 Sanhao Street, Heping District, Shenyang 110004, China
| | - Xiaosong Qin
- Department of Laboratory Medicine, Shengjing Hospital of China Medical University, No.36 Sanhao Street, Heping District, Shenyang 110004, China; Liaoning Clinical Research Center for Laboratory Medicine, No.36 Sanhao Street, Heping District, Shenyang 110004, China.
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Sun G, Ye H, Liu H, Li T, Li J, Zhang X, Cheng Y, Wang K, Shi J, Dai L, Wang P. ZPR1 is an immunodiagnostic biomarker and promotes tumor progression in esophageal squamous cell carcinoma. Cancer Sci 2024; 115:70-82. [PMID: 37964506 PMCID: PMC10823283 DOI: 10.1111/cas.16004] [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: 06/11/2023] [Revised: 10/10/2023] [Accepted: 10/12/2023] [Indexed: 11/16/2023] Open
Abstract
To evaluate the potential of zinc finger protein 1 (ZPR1) as a diagnostic biomarker and explore the underlying role for esophageal squamous cell carcinoma (ESCC). A human proteome microarray was customized to identify anti-ZPR1 autoantibody, and enzyme-linked immunosorbent assay (ELISA) was adopted to assess the diagnostic performance of anti-ZPR1 autoantibody in 294 patients with ESCC and 294 normal controls. The expression of ZPR1 protein was measured by immunohistochemistry. The effect of ZPR1 on the proliferation, migration, and invasion of ESCC cells was investigated through CCK-8, wound healing, and Transwell assays. The expression level of anti-ZPR1 autoantibody (fold change = 2.77) in ESCC patients was higher than that in normal controls. The receiver operating characteristic (ROC) analysis manifested anti-ZPR1 autoantibody achieved area under the ROC curve (AUC) of 0.726 and 0.734 to distinguish ESCC from normal controls with sensitivity of 50.0% and 42.3%, and specificity of 91.0% and 92.0% in the test group and validation group, respectively. The positive rate of ZPR1 protein was significantly higher in ESCC tissues (75.5%, 80/106) than paracancerous tissues (9.4%, 5/53). Compared with the human normal esophageal cell line, the expression level of ZPR1 mRNA and protein in ESCC lines (KYSE150, Eca109, and TE1) had an increased trend. The knockdown or overexpression of ZPR1 reduced and enhanced the proliferation, migration, and invasion of ESCC cell, respectively. ZPR1 was a potential immunodiagnostic biomarker for noninvasive detection and could be a promotional factor in tumor progression of ESCC.
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Affiliation(s)
- Guiying Sun
- Department of Epidemiology and Statistics, College of Public HealthZhengzhou UniversityZhengzhouChina
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention and TreatmentZhengzhou UniversityZhengzhouChina
| | - Hua Ye
- Department of Epidemiology and Statistics, College of Public HealthZhengzhou UniversityZhengzhouChina
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention and TreatmentZhengzhou UniversityZhengzhouChina
| | - Huijuan Liu
- Scientific Research Department, The First Affiliated Hospital of Henan University of CMHenan University of Chinese MedicineZhengzhouChina
| | - Tiandong Li
- Department of Epidemiology and Statistics, College of Public HealthZhengzhou UniversityZhengzhouChina
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention and TreatmentZhengzhou UniversityZhengzhouChina
| | - Jiaxin Li
- Department of Epidemiology and Statistics, College of Public HealthZhengzhou UniversityZhengzhouChina
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention and TreatmentZhengzhou UniversityZhengzhouChina
| | - Xiaoyue Zhang
- Department of Epidemiology and Statistics, College of Public HealthZhengzhou UniversityZhengzhouChina
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention and TreatmentZhengzhou UniversityZhengzhouChina
| | - Yifan Cheng
- Department of Epidemiology and Statistics, College of Public HealthZhengzhou UniversityZhengzhouChina
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention and TreatmentZhengzhou UniversityZhengzhouChina
| | - Keyan Wang
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention and TreatmentZhengzhou UniversityZhengzhouChina
- Henan Institute of Medical and Pharmaceutical SciencesZhengzhou UniversityZhengzhouChina
| | - Jianxiang Shi
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention and TreatmentZhengzhou UniversityZhengzhouChina
- Henan Institute of Medical and Pharmaceutical SciencesZhengzhou UniversityZhengzhouChina
| | - Liping Dai
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention and TreatmentZhengzhou UniversityZhengzhouChina
- Henan Institute of Medical and Pharmaceutical SciencesZhengzhou UniversityZhengzhouChina
| | - Peng Wang
- Department of Epidemiology and Statistics, College of Public HealthZhengzhou UniversityZhengzhouChina
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention and TreatmentZhengzhou UniversityZhengzhouChina
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Repetto O, Vettori R, Steffan A, Cannizzaro R, De Re V. Circulating Proteins as Diagnostic Markers in Gastric Cancer. Int J Mol Sci 2023; 24:16931. [PMID: 38069253 PMCID: PMC10706891 DOI: 10.3390/ijms242316931] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 11/22/2023] [Accepted: 11/24/2023] [Indexed: 12/18/2023] Open
Abstract
Gastric cancer (GC) is a highly malignant disease affecting humans worldwide and has a poor prognosis. Most GC cases are detected at advanced stages due to the cancer lacking early detectable symptoms. Therefore, there is great interest in improving early diagnosis by implementing targeted prevention strategies. Markers are necessary for early detection and to guide clinicians to the best personalized treatment. The current semi-invasive endoscopic methods to detect GC are invasive, costly, and time-consuming. Recent advances in proteomics technologies have enabled the screening of many samples and the detection of novel biomarkers and disease-related signature signaling networks. These biomarkers include circulating proteins from different fluids (e.g., plasma, serum, urine, and saliva) and extracellular vesicles. We review relevant published studies on circulating protein biomarkers in GC and detail their application as potential biomarkers for GC diagnosis. Identifying highly sensitive and highly specific diagnostic markers for GC may improve patient survival rates and contribute to advancing precision/personalized medicine.
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Affiliation(s)
- Ombretta Repetto
- Facility of Bio-Proteomics, Immunopathology and Cancer Biomarkers, Centro di Riferimento Oncologico di Aviano (CRO), National Cancer Institute, IRCCS, 33081 Aviano, Italy
| | - Roberto Vettori
- Immunopathology and Cancer Biomarkers, Centro di Riferimento Oncologico di Aviano (CRO), National Cancer Institute, IRCCS, 33081 Aviano, Italy; (R.V.); (A.S.)
| | - Agostino Steffan
- Immunopathology and Cancer Biomarkers, Centro di Riferimento Oncologico di Aviano (CRO), National Cancer Institute, IRCCS, 33081 Aviano, Italy; (R.V.); (A.S.)
| | - Renato Cannizzaro
- Oncological Gastroenterology, Centro di Riferimento Oncologico di Aviano (CRO), National Cancer Institute, IRCCS, 33081 Aviano, Italy;
- Department of Medical, Surgical and Health Sciences, University of Trieste, 34127 Trieste, Italy
| | - Valli De Re
- Facility of Bio-Proteomics, Immunopathology and Cancer Biomarkers, Centro di Riferimento Oncologico di Aviano (CRO), National Cancer Institute, IRCCS, 33081 Aviano, Italy
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Sun G, Ye H, Yang Q, Zhu J, Qiu C, Shi J, Dai L, Wang K, Zhang J, Wang P. Using Proteome Microarray and Gene Expression Omnibus Database to Screen Tumour-Associated Antigens to Construct the Optimal Diagnostic Model of Oesophageal Squamous Cell Carcinoma. Clin Oncol (R Coll Radiol) 2023; 35:e582-e592. [PMID: 37433700 DOI: 10.1016/j.clon.2023.06.014] [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: 11/21/2022] [Revised: 05/09/2023] [Accepted: 06/30/2023] [Indexed: 07/13/2023]
Abstract
AIMS Autoantibodies against tumour-associated antigens (TAAs) are promising biomarkers for early immunodiagnosis of cancers. This study was designed to screen and verify autoantibodies against TAAs in sera as diagnostic biomarkers for oesophageal squamous cell carcinoma (ESCC). MATERIALS AND METHODS The customised proteome microarray based on cancer driver genes and the Gene Expression Omnibus database were used to identify potential TAAs. The expression levels of the corresponding autoantibodies in serum samples obtained from 243 ESCC patients and 243 healthy controls were investigated by enzyme-linked immunosorbent assay (ELISA). In total, 486 serum samples were randomly divided into the training set and the validation set in the ratio of 2:1. Logistic regression analysis, recursive partition analysis and support vector machine were performed to establish different diagnostic models. RESULTS Five and nine candidate TAAs were screened out by proteome microarray and bioinformatics analysis, respectively. Among these 14 anti-TAAs autoantibodies, the expression level of nine (p53, PTEN, GNA11, SRSF2, CXCL8, MMP1, MSH6, LAMC2 and SLC2A1) anti-TAAs autoantibodies in the cancer patient group was higher than that in the healthy control group based on the results from ELISA. In the three constructed models, a logistic regression model including four anti-TAA autoantibodies (p53, SLC2A1, GNA11 and MMP1) was considered to be the optimal diagnosis model. The sensitivity and specificity of the model in the training set and the validation set were 70.4%, 72.8% and 67.9%, 67.9%, respectively. The area under the receiver operating characteristic curve for detecting early patients in the training set and the validation set were 0.84 and 0.85, respectively. CONCLUSIONS This approach to screen novel TAAs is feasible, and the model including four autoantibodies could pave the way for the diagnosis of ESCC.
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Affiliation(s)
- G Sun
- Department of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China; Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China
| | - H Ye
- Department of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China; Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China
| | - Q Yang
- Department of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China; Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China
| | - J Zhu
- Department of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China; Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China
| | - C Qiu
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China
| | - J Shi
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China; Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan Province, China
| | - L Dai
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China; Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan Province, China
| | - K Wang
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China; Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan Province, China
| | - J Zhang
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China; Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, Henan Province, China
| | - P Wang
- Department of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China; Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China.
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Date M, Miyamoto A, Honjo T, Shiokawa T, Tada H, Okada N, Futami J. Hydrophobicity and molecular mass-based separation method for autoantibody discovery from mammalian total cellular proteins. Protein Sci 2023; 32:e4771. [PMID: 37638851 PMCID: PMC10503409 DOI: 10.1002/pro.4771] [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: 05/25/2023] [Revised: 08/23/2023] [Accepted: 08/25/2023] [Indexed: 08/29/2023]
Abstract
Serum autoantibody profiles are unique to individuals and reflect the level and history of autoimmunity and tumor immunity. The identification of autoantibody biomarkers is critical for the development of immune monitoring systems for immune-related disorders. Here, we present a practical method for large-scale autoantibody discovery using total cellular proteins from cultured mammalian cells. We found that nucleic acid-free and fully denatured water-soluble total cellular proteins from mammalian cells were superior, allowing precise separation by reversed-phase HPLC after preparing a large set of homogeneous total cellular proteins. After separating the proteins based on hydrophobicity, the fractionated samples were subjected to molecular mass analysis using conventional SDS-PAGE. The resulting two-dimensional gel electrophoresis was successfully employed for immune blotting and LC-MS/MS analysis. All procedures, including TRIzol-based total cellular protein extraction, solubilization of denatured proteins, reversed-phase HPLC separation, and SDS-PAGE, were highly reproducible and easily scalable. We propose this novel two-dimensional gel electrophoresis system as an alternative proteomics-based methodology suitable for large-scale autoantibody discovery.
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Affiliation(s)
- Mirei Date
- Graduate School of Interdisciplinary Science and Engineering in Health SystemsOkayama UniversityOkayamaJapan
| | - Ai Miyamoto
- Graduate School of Interdisciplinary Science and Engineering in Health SystemsOkayama UniversityOkayamaJapan
| | - Tomoko Honjo
- Graduate School of Interdisciplinary Science and Engineering in Health SystemsOkayama UniversityOkayamaJapan
| | - Tsugumi Shiokawa
- Division of Instrumental Analysis, Department of Instrumental Analysis and Cryogenics, Advanced Science Research CenterOkayama UniversityOkayamaJapan
| | - Hiroko Tada
- Division of Instrumental Analysis, Department of Instrumental Analysis and Cryogenics, Advanced Science Research CenterOkayama UniversityOkayamaJapan
| | - Nobuhiro Okada
- Graduate School of Interdisciplinary Science and Engineering in Health SystemsOkayama UniversityOkayamaJapan
| | - Junichiro Futami
- Graduate School of Interdisciplinary Science and Engineering in Health SystemsOkayama UniversityOkayamaJapan
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9
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Yao N, Pan J, Chen X, Li P, Li Y, Wang Z, Yao T, Qian L, Yi D, Wu Y. Discovery of potential biomarkers for lung cancer classification based on human proteome microarrays using Stochastic Gradient Boosting approach. J Cancer Res Clin Oncol 2023; 149:6803-6812. [PMID: 36807761 DOI: 10.1007/s00432-023-04643-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: 12/12/2022] [Accepted: 02/08/2023] [Indexed: 02/21/2023]
Abstract
PURPOSE Early identification of lung cancer (LC) will considerably facilitate the intervention and prevention of LC. The human proteome micro-arrays approach can be used as a "liquid biopsy" to diagnose LC to complement conventional diagnosis, which needs advanced bioinformatics methods such as feature selection (FS) and refined machine learning models. METHODS A two-stage FS methodology by infusing Pearson's Correlation (PC) with a univariate filter (SBF) or recursive feature elimination (RFE) was used to reduce the redundancy of the original dataset. The Stochastic Gradient Boosting (SGB), Random Forest (RF), and Support Vector Machine (SVM) techniques were applied to build ensemble classifiers based on four subsets. The synthetic minority oversampling technique (SMOTE) was used in the preprocessing of imbalanced data. RESULTS FS approach with SBF and RFE extracted 25 and 55 features, respectively, with 14 overlapped ones. All three ensemble models demonstrate superior accuracy (ranging from 0.867 to 0.967) and sensitivity (0.917 to 1.00) in the test datasets with SGB of SBF subset outperforming others. The SMOTE technique has improved the model performance in the training process. Three of the top selected candidate biomarkers (LGR4, CDC34, and GHRHR) were highly suggested to play a role in lung tumorigenesis. CONCLUSION A novel hybrid FS method with classical ensemble machine learning algorithms was first used in the classification of protein microarray data. The parsimony model constructed by the SGB algorithm with the appropriate FS and SMOTE approach performs well in the classification task with higher sensitivity and specificity. Standardization and innovation of bioinformatics approach for protein microarray analysis need further exploration and validation.
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Affiliation(s)
- Ning Yao
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, No.30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China
- Chongqing Center for Disease Control and Prevention, No.8 Changjiang 2nd Street, Yuzhong District, Chongqing, 400042, China
| | - Jianbo Pan
- Center for Novel Target and Therapeutic Intervention, Institute of Life Sciences, Chongqing Medical University, Chongqing, 400016, China
| | - Xicheng Chen
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, No.30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China
| | - Pengpeng Li
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, No.30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China
| | - Yang Li
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, No.30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China
| | - Zhenyan Wang
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, No.30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China
| | - Tianhua Yao
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, No.30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China
| | - Li Qian
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, No.30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China
| | - Dong Yi
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, No.30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China.
| | - Yazhou Wu
- Department of Health Statistics, College of Preventive Medicine, Army Medical University, No.30 Gaotanyan Street, Shapingba District, Chongqing, 400038, China.
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10
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Zhuang L, Huang C, Ning Z, Yang L, Zou W, Wang P, Cheng CS, Meng Z. Circulating tumor-associated autoantibodies as novel diagnostic biomarkers in pancreatic adenocarcinoma. Int J Cancer 2023; 152:1013-1024. [PMID: 36274627 DOI: 10.1002/ijc.34334] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 10/03/2022] [Accepted: 10/10/2022] [Indexed: 01/06/2023]
Abstract
To develop a superior diagnostic approach for pancreatic adenocarcinoma (PAAC), the present study prospectively included 338 PAAC patients, 294 normal healthy volunteers (NHV), 122 chronic pancreatitis (CP) patients and 100 patients with non-PAAC malignancies. In the identification phase, HuProt Human Proteome Microarray, comprising 21 065 proteins, was used to identify serum tumor-associated autoantibodies (TAAbs) candidates differentiating PAAC (n = 30) from NHV (n = 30). A PAAC-focused array containing 165 differentially expressed TAAbs identified was subsequently adopted in the validation phase (n = 712) for specificity and sensitivities. The multivariate TAAbs signature for differentiation PAAC from controls (NHV + CP) identified five candidates, namely the IgG-type TAAbs against CLDN17, KCNN3, SLAMF7, SLC22A11 and OR51F2. Multivariate logistic performance model of y = (22.893 × CA19-9 + 0.68 × CLDN17 - 4.012) showed a significant better diagnostic accuracy than that of CA19-9 and CLDN17 in differentiating PAAC from controls (NHV + CP) (AUC = 0.97, 0.92 and 0.82, respectively, P-value < .0001). We further tested the autoantigen level of CLDN17 by ELISA in 82 sera samples from PAAC (n = 42), CP (n = 24) and NHV (n = 16). Similarly, the model showed superior diagnostic performance than that of CA19-9 and CLDN17 (AUC = 0.93, 0.83 and 0.81, respectively, P-value < .0001) in differentiating PAAC from controls. In conclusion, our study is the first to characterize the circulating TAAbs signatures in PAAC. The results showed that CLDN17 combined with CA19-9 provided potentially clinical value and may serve as noninvasive novel biomarkers for PAAC diagnosis.
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Affiliation(s)
- Liping Zhuang
- Minimally Invasive Therapy Center, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Integrative Oncology, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Changjing Huang
- Minimally Invasive Therapy Center, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Integrative Oncology, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhouyu Ning
- Minimally Invasive Therapy Center, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Integrative Oncology, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lina Yang
- Minimally Invasive Therapy Center, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Integrative Oncology, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Shandong Province, China
| | - Wenbin Zou
- Department of Gastroenterology, Digestive Endoscopy Center, Changhai Hospital, the Second Military Medical University, Shanghai, China
| | - Peng Wang
- Minimally Invasive Therapy Center, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Integrative Oncology, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Chien-Shan Cheng
- Minimally Invasive Therapy Center, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Integrative Oncology, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Zhiqiang Meng
- Minimally Invasive Therapy Center, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Integrative Oncology, Shanghai Cancer Center, Fudan University, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
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11
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Chen G, Yang L, Liu G, Zhu Y, Yang F, Dong X, Xu F, Zhu F, Cao C, Zhong D, Li S, Zhang H, Li B. Research progress in protein microarrays: Focussing on cancer research. Proteomics Clin Appl 2023; 17:e2200036. [PMID: 36316278 DOI: 10.1002/prca.202200036] [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: 05/25/2022] [Revised: 09/10/2022] [Accepted: 09/27/2022] [Indexed: 01/22/2023]
Abstract
Although several effective treatment modalities have been developed for cancers, the morbidity and mortality associated with cancer continues to increase every year. As one of the most exciting emerging technologies, protein microarrays represent a powerful tool in the field of cancer research because of their advantages such as high throughput, small sample usage, more flexibility, high sensitivity and direct readout of results. In this review, we focus on the research progress in four types of protein microarrays (proteome microarray, antibody microarray, lectin microarray and reversed protein array) with emphasis on their application in cancer research. Finally, we discuss the current challenges faced by protein microarrays and directions for future developments. We firmly believe that this novel systems biology research tool holds immense potential in cancer research and will become an irreplaceable tool in this field.
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Affiliation(s)
- Guang Chen
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Lina Yang
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Guoxiang Liu
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Yunfan Zhu
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Fanghao Yang
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Xiaolei Dong
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Fenghua Xu
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Feng Zhu
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Can Cao
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Di Zhong
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Shuang Li
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Huhu Zhang
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Bing Li
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China.,Department of Hematology, The Affiliated Hospital of Qingdao University, Qingdao, China
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12
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Yang Q, Ye H, Sun G, Wang K, Dai L, Qiu C, Shi J, Zhu J, Wang X, Wang P. Human Proteome Microarray identifies autoantibodies to tumor-associated antigens as serological biomarkers for the diagnosis of hepatocellular carcinoma. Mol Oncol 2023; 17:887-900. [PMID: 36587394 PMCID: PMC10158779 DOI: 10.1002/1878-0261.13371] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 11/14/2022] [Accepted: 12/30/2022] [Indexed: 01/02/2023] Open
Abstract
The identification of the high-efficiency and non-invasive biomarkers for hepatocellular carcinoma (HCC) detection is urgently needed. This study aims to screen out potential autoantibodies to tumor-associated antigens (TAAbs) and to assess their diagnostic value for HCC. Fifteen potential TAAbs were screened out from the Human Proteome Microarray by 30 HCC sera and 22 normal control sera, of which eight passed multiple-stage validations by ELISA with a total of 1625 human serum samples from normal controls (NCs) and patients with HCC, liver cirrhosis, chronic hepatitis B, gastric cancer, esophageal cancer, and colorectal cancer. Finally, an immunodiagnostic model including six TAAbs (RAD23A, CAST, RUNX1T1, PAIP1, SARS, PRKCZ) was constructed by logistic regression, and yielded the area under curve (AUC) of 0.835 and 0.788 in training and validation sets, respectively. The serial serum samples from HCC model mice were tested to explore the change in TAAbs during HCC formation, and an increasing level of autoantibodies was observed. In conclusion, the panel of six TAAbs can provide potential value for HCC detection, and the strategy to identify novel serological biomarkers can also provide new clues in understanding immunodiagnostic biomarkers.
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Affiliation(s)
- Qian Yang
- The State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, China.,Department of Prenatal Diagnosis Center, The Third Affiliated Hospital of Zhengzhou University, China
| | - Hua Ye
- The State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, China.,Department of Epidemiology and Health Statistics and Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, China
| | - Guiying Sun
- The State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, China.,Department of Epidemiology and Health Statistics and Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, China
| | - Keyan Wang
- The State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, China.,Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, China
| | - Liping Dai
- The State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, China.,Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, China
| | - Cuipeng Qiu
- The State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, China.,Department of Epidemiology and Health Statistics and Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, China
| | - Jianxiang Shi
- The State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, China.,Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, China
| | - Jicun Zhu
- The State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, China.,Department of Epidemiology and Health Statistics and Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, China
| | - Xiao Wang
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, China
| | - Peng Wang
- The State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, China.,Department of Epidemiology and Health Statistics and Henan Key Laboratory of Tumor Epidemiology, College of Public Health, Zhengzhou University, China
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13
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Lou N, Zheng C, Wang Y, Liang C, Tan Q, Luo R, Zhang L, Xie T, Shi Y, Han X. Identification of novel serological autoantibodies in Chinese prostate cancer patients using high-throughput protein arrays. Cancer Immunol Immunother 2023; 72:235-247. [PMID: 35831618 DOI: 10.1007/s00262-022-03242-0] [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: 11/21/2021] [Accepted: 06/13/2022] [Indexed: 01/07/2023]
Abstract
Autoantibody (AAb) has a prominent role in prostate cancer (PCa), with few studies profiling the AAb landscape in Chinese patients. Therefore, the AAb landscape in Chinese patients was characterized using protein arrays. First, in the discovery phase, Huprot arrays outlined autoimmune profiles against ~ 21,888 proteins from 57 samples. In the verification phase, the PCa-focused arrays detected 25 AAbs selected from the discovery phase within 178 samples. Then, PCa was detected using a backpropagation artificial neural network (BPANN) model. In the validation phase, an enzyme-linked immunosorbent assay (ELISA) was used to validate four AAb biomarkers from 196 samples. Huprot arrays profiled distinct PCa, benign prostate diseases (BPD), and health AAb landscapes. PCa-focused array depicted that IFIT5 and CPOX AAbs could distinguish PCa from health with an area under curve (AUC) of 0.71 and 0.70, respectively. PAH and FCER2 AAbs had AUCs of 0.86 and 0.88 in discriminating PCa from BPD. Particularly, PAH AAb detected patients in the prostate-specific antigen (PSA) gray zone with an AUC of 0.86. Meanwhile, the BPANN model of 4-AAb (IFIT5, PAH, FCER2, CPOX) panel attained AUC of 0.83 among the two cohorts for detecting patients with gray-zone PSA. In the validation cohort, the IFIT5 AAb was upregulated in PCa compared to health (p < 0.001). Compared with BPD, PAH and FCER2 AAbs were significantly elevated in PCa (p = 0.012 and 0.039). We have demonstrated the first extensive profiling of autoantibodies in Chinese PCa patients, identifying novel diagnostic AAb biomarkers, especially for identification of gray-zone-PSA patients.
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Affiliation(s)
- Ning Lou
- Department of Clinical Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.,Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Cuiling Zheng
- Department of Clinical Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Yanrong Wang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Caixia Liang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Qiaoyun Tan
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Rongrong Luo
- Department of Clinical Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Lei Zhang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Tongji Xie
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China
| | - Yuankai Shi
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing Key Laboratory of Clinical Study On Anticancer Molecular Targeted Drugs, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.
| | - Xiaohong Han
- Clinical Pharmacology Research Center, Peking Union Medical College Hospital, State Key Laboratory of Complex Severe and Rare Diseases, NMPA Key Laboratory for Clinical Research and Evaluation of Drug, Beijing Key Laboratory of Clinical PK and PD Investigation for Innovative Drugs, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuaifuyuan, Dongcheng District, Beijing, 100730, China.
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14
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Duan H, Hu K, Zheng D, Cheng Y, Zhang Z, Wang Y, Liang L, Hu J, Luo T. Recognition and release of uridine and hCNT3: From multivariate interactions to molecular design. Int J Biol Macromol 2022; 223:1562-1577. [PMID: 36402394 DOI: 10.1016/j.ijbiomac.2022.11.145] [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: 09/29/2022] [Revised: 11/09/2022] [Accepted: 11/14/2022] [Indexed: 11/18/2022]
Abstract
As a vital target for the development of novel anti-cancer drugs, human concentrative nucleoside transporter 3 (hCNT3) has been widely concerned. Nevertheless, the lack of a comprehensive understanding of molecular interactions and motion mechanism has greatly hindered the development of novel inhibitors against hCNT3. In this paper, molecular recognition of hCNT3 with uridine was investigated with molecular docking, conventional molecular dynamics (CMD) simulations and adaptive steered molecular dynamics (ASMD) simulations; and then, the uridine derivatives with possibly highly inhibitory activity were designed. The result of CMD showed that more water-mediated H-bonds and lower binding free energy both explained higher recognition ability and transported efficiency of hCNT3. While during the ASMD simulation, nucleoside transport process involved the significant side-chain flip of residues F321 and Q142, a typical substrate-induced conformational change. By considering electronegativity, atomic radius, functional group and key H-bonds factors, 25 novel uridine derivatives were constructed. Subsequently, the receptor-ligand binding free energy was predicted by solvated interaction energy (SIE) method to determine the inhibitor c8 with the best potential performance. This work not only revealed molecular recognition and release mechanism of uridine with hCNT3, but also designed a series of uridine derivatives to obtain lead compounds with potential high activity.
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Affiliation(s)
- Huaichuan Duan
- Department of Head, Neck and Mammary Gland Oncology, Cancer Center, Clinical Research Center for Breast, West China Hospital, Sichuan University, Chengdu, China
| | - Kaixuan Hu
- School of Pharmaceutical Sciences, Jishou University, Jishou, China
| | - Dan Zheng
- Department of Head, Neck and Mammary Gland Oncology, Cancer Center, Clinical Research Center for Breast, West China Hospital, Sichuan University, Chengdu, China
| | - Yan Cheng
- Department of Head, Neck and Mammary Gland Oncology, Cancer Center, Clinical Research Center for Breast, West China Hospital, Sichuan University, Chengdu, China
| | - Zelan Zhang
- Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu, China
| | - Yueteng Wang
- Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu, China
| | - Li Liang
- Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu, China
| | - Jianping Hu
- Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu, China
| | - Ting Luo
- Department of Head, Neck and Mammary Gland Oncology, Cancer Center, Clinical Research Center for Breast, West China Hospital, Sichuan University, Chengdu, China.
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15
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Sun Y, Liu C, Zhong H, Wang C, Xu H, Chen W. Screening of autoantibodies as biomarkers in the serum of renal cancer patients based on human proteome microarray. Acta Biochim Biophys Sin (Shanghai) 2022; 54:1909-1916. [PMID: 36789694 PMCID: PMC10157637 DOI: 10.3724/abbs.2022189] [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: 03/02/2022] [Accepted: 06/10/2022] [Indexed: 12/13/2022] Open
Abstract
The autoantibody in patients' serum can act as a biomarker for diagnosing cancer, and the differences in autoantibodies are significantly correlated with the changes in their target proteins. In this study, 16 renal cancer (RC) patients were assigned to the disease group, and 16 healthy people were assigned to the healthy control (HC) group. The human proteome microarray consisting of>19,500 proteins was used to examine the differences in IgG and IgM autoantibodies in sera between RC and HC. The comparative analysis of the microarray results shows that 101 types of IgG and 25 types of IgM autoantibodies are significantly higher in RC than in HC. Highly responsive autoantibodies can be candidate biomarkers (e.g., anti-KCNAB2 IgG and anti-RCN1 IgM). Extensive enzyme-linked immunosorbent assay (ELISA) was performed to screen sera in 72 RC patients and 66 healthy volunteers to verify the effectiveness of the new autoantibodies. The AUCs of anti-KCNAB2 IgG and anti-GAPDH IgG were 0.833 and 0.753, respectively. KCNAB2 achieves high protein expression, and its high mRNA level is confirmed to be an unfavorable prognostic marker in clear cell renal cell carcinoma (ccRCC) tissues. This study suggests that the high-throughput human proteome microarray can effectively screen autoantibodies in serum as candidate biomarkers, and their corresponding target proteins can lay a basis for the in-depth investigation into renal cancer.
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Affiliation(s)
- Yangyang Sun
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- Department of Urology, Shenzhen Second People’s Hospital, the First Affiliated Hospital of Shenzhen University, International Cancer Center, Shenzhen University School of Medicine, Shenzhen 518039, China
| | - Chengxi Liu
- State Key Laboratory of Chemical Biology and Drug Discovery, Food Safety and Technology Research Centre and Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hong Kong 999077, China
| | - Huidong Zhong
- Department of Medicinal ChemistryShantou University Medical CollegeShantou515041China
| | - Chenguang Wang
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Haibo Xu
- Department of Urology, Shenzhen Second People’s Hospital, the First Affiliated Hospital of Shenzhen University, International Cancer Center, Shenzhen University School of Medicine, Shenzhen 518039, China
| | - Wei Chen
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- Department of Urology, Shenzhen Second People’s Hospital, the First Affiliated Hospital of Shenzhen University, International Cancer Center, Shenzhen University School of Medicine, Shenzhen 518039, China
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16
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Ren J, Wang H, Wei C, Yang X, Yu X. Development of a protein microarray for profiling circulating autoantibodies in human diseases. Proteomics Clin Appl 2022; 16:e2100132. [PMID: 36006834 DOI: 10.1002/prca.202100132] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 08/19/2022] [Accepted: 08/22/2022] [Indexed: 12/30/2022]
Abstract
PURPOSE To develop a robust microarray platform to detect thousands of serological autoantibodies (AAbs) simultaneously in different diseases. EXPERIMENTAL DESIGN An AAbMap microarray was prepared by printing a total of 4032 purified His-tagged human proteins and peptide probes on a chemically-modified slide. The sensitivity, dynamic range, and the inter- and intra-array reproducibility of the AAb microarray were then systematically tested and optimized. Finally, the large-scale profiling of AAbs in the serum of patients with different human diseases using the AAbMap microarray was demonstrated. RESULTS The dynamic range of antibody (Ab) detection was 2 to 3 orders of magnitude with the lowest limit of detection (LOD) of 68 pg/mL. The intra-array (r) correlation of duplicate spots was 1.00, whereas the inter-array correlations between different arrays and batches were 0.99 and 0.97 to 0.98, respectively. Notably, 132, 266, 171, and 84 AAbs were detected in pooled serum from healthy controls (HCs) or patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), or lung cancer (LC), respectively. These AAbs included antibodies that target well-known disease biomarkers, such as anti-cyclic citrullinated peptide, anti-ribonucleoprotein, and anti-nucleosome. CONCLUSIONS AND CLINICAL RELEVANCE We developed a microarray platform to measure thousands of serological AAbs simultaneously with high sensitivity and reproducibility. The array can help study autoimmunity and complement genomics, proteomics, and metabolomics data for systematic investigations of human diseases.
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Affiliation(s)
- Jing Ren
- School of Basic Medicine Sciences, Anhui Medical University, Hefei, Anhui, PR China
| | - Hongye Wang
- National Center for Protein Sciences Beijing (PHOENIX Center), State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, PR China
| | - Chundi Wei
- National Center for Protein Sciences Beijing (PHOENIX Center), State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, PR China
| | - Xiaoming Yang
- School of Basic Medicine Sciences, Anhui Medical University, Hefei, Anhui, PR China.,National Center for Protein Sciences Beijing (PHOENIX Center), State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, PR China
| | - Xiaobo Yu
- National Center for Protein Sciences Beijing (PHOENIX Center), State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing, PR China
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17
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Qi H, Xue JB, Lai DY, Li A, Tao SC. Current advances in antibody-based serum biomarker studies: From protein microarray to phage display. Proteomics Clin Appl 2022; 16:e2100098. [PMID: 36071670 DOI: 10.1002/prca.202100098] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 08/16/2022] [Accepted: 09/05/2022] [Indexed: 12/30/2022]
Abstract
PURPOSE This review aims to summarize the technological advances in the field of antibody-based biomarker studies by proteome microarray and phage display. In addition, the possible development directions of this field are also discussed. EXPERIMENTAL DESIGN We have focused on the antibody profiling by proteome microarray and phage display, including the technological advances, the tools/resources constructed, and the characteristics of both platforms. RESULTS With the help of tools/resources and technological advances in proteome microarray and phage display, the efficiency of profiling antibody-based biomarkers in serum samples has been greatly improved. CONCLUSIONS In the past few years, proteome microarray and phage display, especially the latter one, have already demonstrated their capacity and efficiency for biomarker identification. In the near future, we believe that more antibody-based biomarkers could be identified, and some of them could eventually be developed into real clinical applications.
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Affiliation(s)
- Huan Qi
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Jun-Biao Xue
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Dan-Yun Lai
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Ang Li
- College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Sheng-Ce Tao
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
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18
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Pan Y, Zheng Y, Yang J, Wei Y, Wu H, Liu S, Yin A, Hu J, Zeng Y. A new biomarker for the early diagnosis of gastric cancer: gastric juice- and serum-derived SNCG. Future Oncol 2022; 18:3179-3190. [PMID: 35947016 DOI: 10.2217/fon-2022-0253] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: To explore the possibility of gastric juice (GJ)- and serum-derived SNCG as a potential biomarker for the early diagnosis of gastric cancer (GC). Materials & methods: GJ and serum samples were collected from 87 patients with GC, 38 patients with gastric precancerous lesions and 44 healthy volunteers. The levels of SNCG in GJ and serum samples were detected by ELISA. Results: The levels of SNCG in GJ and serum were significantly higher in the GC group when compared with the GPL group or the control group. The expression of SNCG in GJ and serum was associated with tumor node metastasis stage, lymph node metastasis, tumor size and drinking, and it is important for the diagnosis and prognosis of GC (p < 0.05). Conclusion: The findings highlight the significance of SNCG in GC diagnosis and prognosis and implicate SNCG as a promising candidate for GC treatment.
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Affiliation(s)
- Yangyang Pan
- Precision Clinical Laboratory, Central People's Hospital of Zhanjiang, Zhanjiang, Guangdong, China.,Key Laboratory of Xinjiang Endemic & Ethnic Disease, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Yi Zheng
- Department of Gastroenterology, First Affiliated Hospital, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Jie Yang
- Department of Laboratory, The First Affiliated Hospital, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Yi Wei
- School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Hanrui Wu
- School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Shuo Liu
- School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Aihua Yin
- School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Jinfeng Hu
- School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Yan Zeng
- Precision Clinical Laboratory, Central People's Hospital of Zhanjiang, Zhanjiang, Guangdong, China
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19
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Zhang J, Guo X, Jin B, Zhu Q. Editorial: Tumor-associated antigens and their autoantibodies, from discovering to clinical utilization. Front Oncol 2022; 12:970623. [PMID: 35936692 PMCID: PMC9346231 DOI: 10.3389/fonc.2022.970623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 07/07/2022] [Indexed: 11/30/2022] Open
Affiliation(s)
- Jianying Zhang
- Department of Biological Sciences, The University of Texas at El Paso, El Paso, TX, United States
- *Correspondence: Jianying Zhang, ; Xiangqian Guo,
| | - Xiangqian Guo
- Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Basic Medical Sciences, Academy for Advanced Interdisciplinary Studies, Henan University, Kaifeng, China
- *Correspondence: Jianying Zhang, ; Xiangqian Guo,
| | - Bilian Jin
- Cancer Center, Dalian Medical University, Dalian, China
| | - Qing Zhu
- West China Hospital, Sichuan University, Chengdu, China
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20
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Novel serological biomarker panel using protein microarray can distinguish active TB from latent TB infection. Microbes Infect 2022; 24:105002. [DOI: 10.1016/j.micinf.2022.105002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 11/22/2022]
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21
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Koopaie M, Ghafourian M, Manifar S, Younespour S, Davoudi M, Kolahdooz S, Shirkhoda M. Evaluation of CSTB and DMBT1 expression in saliva of gastric cancer patients and controls. BMC Cancer 2022; 22:473. [PMID: 35488257 PMCID: PMC9055774 DOI: 10.1186/s12885-022-09570-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 04/19/2022] [Indexed: 01/07/2023] Open
Abstract
Background Gastric cancer (GC) is the fifth most common cancer and the third cause of cancer deaths globally, with late diagnosis, low survival rate, and poor prognosis. This case-control study aimed to evaluate the expression of cystatin B (CSTB) and deleted in malignant brain tumor 1 (DMBT1) in the saliva of GC patients with healthy individuals to construct diagnostic algorithms using statistical analysis and machine learning methods. Methods Demographic data, clinical characteristics, and food intake habits of the case and control group were gathered through a standard checklist. Unstimulated whole saliva samples were taken from 31 healthy individuals and 31 GC patients. Through ELISA test and statistical analysis, the expression of salivary CSTB and DMBT1 proteins was evaluated. To construct diagnostic algorithms, we used the machine learning method. Results The mean salivary expression of CSTB in GC patients was significantly lower (115.55 ± 7.06, p = 0.001), and the mean salivary expression of DMBT1 in GC patients was significantly higher (171.88 ± 39.67, p = 0.002) than the control. Multiple linear regression analysis demonstrated that GC was significantly correlated with high levels of DMBT1 after controlling the effects of age of participants (R2 = 0.20, p < 0.001). Considering salivary CSTB greater than 119.06 ng/mL as an optimal cut-off value, the sensitivity and specificity of CSTB in the diagnosis of GC were 83.87 and 70.97%, respectively. The area under the ROC curve was calculated as 0.728. The optimal cut-off value of DMBT1 for differentiating GC patients from controls was greater than 146.33 ng/mL (sensitivity = 80.65% and specificity = 64.52%). The area under the ROC curve was up to 0.741. As a result of the machine learning method, the area under the receiver-operating characteristic curve for the diagnostic ability of CSTB, DMBT1, demographic data, clinical characteristics, and food intake habits was 0.95. The machine learning model’s sensitivity, specificity, and accuracy were 100, 70.8, and 80.5%, respectively. Conclusion Salivary levels of DMBT1 and CSTB may be accurate in diagnosing GCs. Machine learning analyses using salivary biomarkers, demographic, clinical, and nutrition habits data simultaneously could provide affordability models with acceptable accuracy for differentiation of GC by a cost-effective and non-invasive method.
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Affiliation(s)
- Maryam Koopaie
- Department of Oral Medicine, School of Dentistry, Tehran University of Medical Sciences, Tehran, Iran
| | - Marjan Ghafourian
- Department of Oral Medicine, School of Dentistry, Tehran University of Medical Sciences, Tehran, Iran
| | - Soheila Manifar
- Department of Oral Medicine, Imam Khomeini Hospital, Tehran University of Medical Sciences, North Kargar St, P.O.Box:14395-433, Tehran, 14399-55991, Iran.
| | - Shima Younespour
- Dentistry Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mansour Davoudi
- Department of Computer Science and Engineering and IT, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran
| | - Sajad Kolahdooz
- Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Mohammad Shirkhoda
- Department of General Oncology, Cancer Research Center, Cancer Institute of Iran, Tehran University of Medical Sciences, Tehran, Iran
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22
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Liu XY, Zhang TQ, Zhang Q, Guo J, Zhang P, Mao T, Tian ZB, Zhang CP, Li XY. Differential Long Non-Coding RNA Expression Analysis in Chronic Non-Atrophic Gastritis, Gastric Mucosal Intraepithelial Neoplasia, and Gastric Cancer Tissues. Front Genet 2022; 13:833857. [PMID: 35571069 PMCID: PMC9091194 DOI: 10.3389/fgene.2022.833857] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 03/25/2022] [Indexed: 11/13/2022] Open
Abstract
Gastric cancer (GC) has a high incidence worldwide, and when detected, the majority of patients have already progressed to advanced stages. Long non-coding RNAs (lncRNAs) have a wide range of biological functions and affect tumor occurrence and development. However, the potential role of lncRNAs in GC diagnosis remains unclear. We selected five high-quality samples from each group of chronic non-atrophic gastritis, gastric mucosal intraepithelial neoplasia, and GC tissues for analysis. RNA-seq was used to screen the differentially expressed lncRNAs, and we identified 666 differentially expressed lncRNAs between the chronic non-atrophic gastritis and GC groups, 13 differentially expressed lncRNAs between the gastric mucosal intraepithelial neoplasia and GC groups, and 507 differentially expressed lncRNAs between the chronic non-atrophic gastritis and gastric mucosal intraepithelial neoplasia groups. We also identified six lncRNAs (lncRNA H19, LINC00895, lnc-SRGAP2C-16, lnc-HLA-C-2, lnc-APOC1-1, and lnc-B3GALT2-1) which not only differentially expressed between the chronic non-atrophic gastritis and GC groups, but also differentially expressed between the gastric mucosal intraepithelial neoplasia and GC groups. Furthermore, RT-qPCR was used to verify the differentially co-expressed lncRNAs. LncSEA was used to conduct a functional analysis of differentially expressed lncRNAs. We also predicted the target mRNAs of the differentially expressed lncRNAs through bioinformatics analysis and analyzed targeting correlations between three differentially co-expressed lncRNAs and mRNAs (lncRNA H19, LINC00895, and lnc-SRGAP2C-16). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases were used to explore the functions of target mRNAs of differentially expressed lncRNAs. In conclusion, our study provides a novel perspective on the potential functions of differentially expressed lncRNAs in GC occurrence and development, indicating that the differentially expressed lncRNAs might be new biomarkers for early GC diagnosis.
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Affiliation(s)
- Xin-Yuan Liu
- Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Tian-Qi Zhang
- Department of Gastroenterology, Qingdao Women and Children’s Hospital, Qingdao, China
| | - Qi Zhang
- Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Jing Guo
- Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Peng Zhang
- Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Tao Mao
- Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Zi-Bin Tian
- Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Cui-Ping Zhang
- Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiao-Yu Li
- Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China
- *Correspondence: Xiao-Yu Li,
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23
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Temporal reproducibility of IgG and IgM autoantibodies in serum from healthy women. Sci Rep 2022; 12:6192. [PMID: 35418192 PMCID: PMC9008031 DOI: 10.1038/s41598-022-10174-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 03/30/2022] [Indexed: 11/09/2022] Open
Abstract
Autoantibodies are present in healthy individuals and altered in chronic diseases. We used repeated samples collected from participants in the NYU Women's Health Study to assess autoantibody reproducibility and repertoire stability over a one-year period using the HuProt array. We included two samples collected one year apart from each of 46 healthy women (92 samples). We also included eight blinded replicate samples to assess laboratory reproducibility. A total of 21,211 IgG and IgM autoantibodies were interrogated. Of those, 86% of IgG (n = 18,303) and 34% of IgM (n = 7,242) autoantibodies showed adequate lab reproducibility (coefficient of variation [CV] < 20%). Intraclass correlation coefficients (ICCs) were estimated to assess temporal reproducibility. A high proportion of both IgG and IgM autoantibodies with CV < 20% (76% and 98%, respectively) showed excellent temporal reproducibility (ICC > 0.8). Temporal reproducibility was lower after using quantile normalization suggesting that batch variability was not an important source of error, and that normalization removed some informative biological information. To our knowledge this study is the largest in terms of sample size and autoantibody numbers to assess autoantibody reproducibility in healthy women. The results suggest that for many autoantibodies a single measurement may be used to rank individuals in studies of autoantibodies as etiologic markers of disease.
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24
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Zha Q, Wu X, Zhang J, Xu T, Shi Y, Sun Y, Fang Y, Gu Y, Ma P, Shu Y, Tian S. Hsa_circ_0007967 promotes gastric cancer proliferation through the miR-411-5p/MAML3 axis. Cell Death Dis 2022; 8:144. [PMID: 35354791 PMCID: PMC8969178 DOI: 10.1038/s41420-022-00954-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 03/10/2022] [Accepted: 03/17/2022] [Indexed: 01/30/2023]
Abstract
Circular RNAs are an important kind of noncoding RNAs and involved in cancerogenesis, but the specific mechanism between gastric cancer and circRNAs needs further study. Hsa_circ_0007967 was selected by RNA sequencing. Here, hsa_circ_0007967 was highly expressed in gastric cancer tissues than adjacent normal tissues. Overexpressing hsa_circ_0007967 promoted gastric cancer cell proliferation in vitro and in vivo, while suppression of hsa_circ_0007967 inhibited gastric cancer cell proliferation in vitro and in vivo. Mechanistically, hsa_circ_0007967 sponged miR-411-5p to increase MAML3 expression. Overall, hsa_circ_0007967 is a promising biomarker for gastric cancer diagnosis and a potential molecule for gastric cancer treatment.
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Affiliation(s)
- Quanbin Zha
- Department of Oncology, Jintan Hospital, Jiangsu University, Changzhou, 213200, People's Republic of China
| | - Xi Wu
- Department of Oncology, the First Affifiliated Hospital of Nanjing Medical University, Nanjing, 210029, People's Republic of China
| | - Jingxin Zhang
- Department of General Surgery, the Affifiliated People's Hospital of Jiangsu University, Zhenjiang Clinic School of Nanjing Medical University, Zhenjiang, 212002, People's Republic of China
| | - Tingting Xu
- Department of Oncology, the First Affifiliated Hospital of Nanjing Medical University, Nanjing, 210029, People's Republic of China
| | - YongKang Shi
- Department of Oncology, Jintan Hospital, Jiangsu University, Changzhou, 213200, People's Republic of China
| | - Yayun Sun
- Department of Neurology, Jintan Hospital, Jiangsu University, Changzhou, 213200, People's Republic of China
| | - Yuan Fang
- Department of Oncology, the First Affifiliated Hospital of Nanjing Medical University, Nanjing, 210029, People's Republic of China
| | - Yunru Gu
- Department of Oncology, the First Affifiliated Hospital of Nanjing Medical University, Nanjing, 210029, People's Republic of China
| | - Pei Ma
- Department of Oncology, Jintan Hospital, Jiangsu University, Changzhou, 213200, People's Republic of China. .,Department of Oncology, the First Affifiliated Hospital of Nanjing Medical University, Nanjing, 210029, People's Republic of China.
| | - Yongqian Shu
- Department of Oncology, Jintan Hospital, Jiangsu University, Changzhou, 213200, People's Republic of China. .,Department of Oncology, the First Affifiliated Hospital of Nanjing Medical University, Nanjing, 210029, People's Republic of China. .,Department of Oncology, Sir Run Run Hospital, Nanjing Medical University, Nanjing, 210029, People's Republic of China. .,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, 210029, People's Republic of China.
| | - Shengwang Tian
- Department of Oncology, Jintan Hospital, Jiangsu University, Changzhou, 213200, People's Republic of China.
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25
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Du W, Zhang R, Muhammad B, Pei D. Targeting the COP9 signalosome for cancer therapy. Cancer Biol Med 2022; 19:j.issn.2095-3941.2021.0605. [PMID: 35315259 PMCID: PMC9196064 DOI: 10.20892/j.issn.2095-3941.2021.0605] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 01/18/2022] [Indexed: 11/24/2022] Open
Abstract
The COP9 signalosome (CSN) is a highly conserved protein complex composed of 8 subunits (CSN1 to CSN8). The individual subunits of the CSN play essential roles in cell proliferation, tumorigenesis, cell cycle regulation, DNA damage repair, angiogenesis, and microenvironmental homeostasis. The CSN complex has an intrinsic metalloprotease that removes the ubiquitin-like activator NEDD8 from cullin-RING ligases (CRLs). Binding of neddylated CRLs to CSN is sensed by CSN4 and communicated to CSN5 with the assistance of CSN6, thus leading to the activation of deneddylase. Therefore, CSN is a crucial regulator at the intersection between neddylation and ubiquitination in cancer progression. Here, we summarize current understanding of the roles of individual CSN subunits in cancer progression. Furthermore, we explain how the CSN affects tumorigenesis through regulating transcription factors and the cell cycle. Finally, we discuss individual CSN subunits as potential therapeutic targets to provide new directions and strategies for cancer therapy.
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Affiliation(s)
- Wenqi Du
- Department of Pathology, Xuzhou Medical University, Xuzhou 221004, China
- Department of Human Anatomy, Xuzhou Medical University, Xuzhou 221004, China
| | - Ruicheng Zhang
- Department of Neurology, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221006, China
| | - Bilal Muhammad
- Department of Neurology, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221006, China
| | - Dongsheng Pei
- Department of Pathology, Xuzhou Medical University, Xuzhou 221004, China
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26
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Autoantibody to GNAS in Early Detection of Hepatocellular Carcinoma: A Large-Scale Sample Study Combined with Verification in Serial Sera from HCC Patients. Biomedicines 2022; 10:biomedicines10010097. [PMID: 35052777 PMCID: PMC8773227 DOI: 10.3390/biomedicines10010097] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 12/29/2021] [Accepted: 12/30/2021] [Indexed: 11/16/2022] Open
Abstract
The aim of this study was to explore the value of autoantibody to GNAS in the early detection of hepatocellular carcinoma (HCC). In a large-scale sample set of 912 participants (228 cases in each of HCC, liver cirrhosis (LC), chronic hepatitis B (CHB), and normal controls (NCs) groups), autoantibody to GNAS was detected with a positive result in 47.8% of HCC patients, which was significantly higher than that in patients with LC (35.1%), CHB (19.7%), and NCs (19.7%). Further analysis showed that the frequency of autoantibody to GNAS started increasing in compensated cirrhosis patients (37.0%) with a jump in decompensated cirrhosis patients (53.2%) and reached a peak in early HCC patients (62.4%). The increasing autoantibody response to GNAS in patients at different stages was closely associated with the progression of chronic liver lesions. The result from 44 human serial sera demonstrated that 5 of 11 (45.5%) HCC patients had elevated autoantibody to GNAS before and/or at diagnosis of HCC. Moreover, 46.1% and 62.4% of high positive rates in alpha-fetoprotein (AFP) negative and early-stage HCC patients can supplement AFP in early detection of HCC. These findings suggest that autoantibody to GNAS could be used as a potential biomarker for the early detection of HCC.
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27
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Li X, Zheng NR, Wang LH, Li ZW, Liu ZC, Fan H, Wang Y, Dai J, Ni XT, Wei X, Liu MW, Li K, Li ZX, Zhou T, Zhang Y, Zhang JY, Kadeerhan G, Huang S, Wu WH, Liu WD, Wu XZ, Zhang LF, Xu JM, Gerhard M, You WC, Pan KF, Li WQ, Qin J. Proteomic profiling identifies signatures associated with progression of precancerous gastric lesions and risk of early gastric cancer. EBioMedicine 2021; 74:103714. [PMID: 34818622 PMCID: PMC8617343 DOI: 10.1016/j.ebiom.2021.103714] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 11/09/2021] [Accepted: 11/09/2021] [Indexed: 12/21/2022] Open
Abstract
Background Molecular features underlining the multistage progression of gastric lesions and development of early gastric cancer (GC) are poorly understood, restricting the ability to GC prevention and management. Methods We portrayed proteomic landscape and explored proteomic signatures associated with progression of gastric lesions and risk of early GC. Tissue proteomic profiling was conducted for a total of 324 subjects. A case-control study was performed in the discovery stage (n=169) based on populations from Linqu, a known high-risk area for GC in China. We then conducted two-stage validation, including a cohort study from Linqu (n = 56), with prospective follow-up for progression of gastric lesions (280–473 days), and an independent case-control study from Beijing (n = 99). Findings There was a clear distinction in proteomic features for precancerous gastric lesions and GC. We derived four molecular subtypes of gastric lesions and identified subtype-S4 with the highest progression risk. We found 104 positively-associated and 113 inversely-associated proteins for early GC, with APOA1BP, PGC, HPX and DDT associated with the risk of gastric lesion progression. Integrating these proteomic signatures, the ability to predict progression of gastric lesions was significantly strengthened (areas-under-the-curve=0.88 (95%CI: 0.78–0.99) vs. 0.56 (0.36–0.76), Delong's P = 0.002). Immunohistochemistry assays and examination at mRNA level validated the findings for four proteins. Interpretation We defined proteomic signatures for progression of gastric lesions and risk of early GC, which may have translational significance for identifying particularly high-risk population and detecting GC at an early stage, improving potential for targeted GC prevention. Funding The funders are listed in the Acknowledgement.
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Affiliation(s)
- Xue Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Nai-Ren Zheng
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Lin-Heng Wang
- Department of Gastroenterology, Second Clinical Medical College of Beijing University of Chinese Medicine (Dongfang Hospital), Beijing 100078, China
| | - Zhong-Wu Li
- Department of Pathology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Zong-Chao Liu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Hua Fan
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Yi Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Jin Dai
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Xiao-Tian Ni
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Xin Wei
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Ming-Wei Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Kai Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Zhe-Xuan Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Tong Zhou
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Yang Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Jing-Ying Zhang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Gaohaer Kadeerhan
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Sha Huang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Wen-Hui Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Wei-Dong Liu
- Linqu County Public Health Bureau, Shandong 262600, China
| | - Xiu-Zhen Wu
- Linqu County People's Hospital, Shandong 262600, China
| | - Lan-Fu Zhang
- Linqu County People's Hospital, Shandong 262600, China
| | - Jian-Ming Xu
- Department of Gastrointestinal Oncology, The Fifth Medical Center, General Hospital of PLA, Beijing 100071, China
| | - Markus Gerhard
- PYLOTUM Key joint laboratory for upper GI cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich/Beijing, Germany/ China
| | - Wei-Cheng You
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China; PYLOTUM Key joint laboratory for upper GI cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich/Beijing, Germany/ China
| | - Kai-Feng Pan
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China; PYLOTUM Key joint laboratory for upper GI cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich/Beijing, Germany/ China.
| | - Wen-Qing Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Cancer Epidemiology, Peking University Cancer Hospital & Institute, Beijing 100142, China; PYLOTUM Key joint laboratory for upper GI cancer, Technische Universität München/Peking University Cancer Hospital & Institute, Munich/Beijing, Germany/ China.
| | - Jun Qin
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China.
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28
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Lei Q, Yu CZ, Li Y, Hou HY, Xu ZW, Yao ZJ, Zhang YD, Lai DY, Ndzouboukou JLB, Zhang B, Chen H, Ouyang ZQ, Xue JB, Lin XS, Zheng YX, Wang XN, Jiang HW, Zhang HN, Qi H, Guo SJ, He MA, Sun ZY, Wang F, Tao SC, Fan XL. Anti-SARS-CoV-2 IgG responses are powerful predicting signatures for the outcome of COVID-19 patients. J Adv Res 2021; 36:133-145. [PMID: 35116173 PMCID: PMC8641215 DOI: 10.1016/j.jare.2021.11.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 11/10/2021] [Accepted: 11/23/2021] [Indexed: 12/14/2022] Open
Affiliation(s)
- Qing Lei
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Division of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Cai-zheng Yu
- Department of Public Health, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Li
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - Hong-yan Hou
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhao-wei Xu
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zong-jie Yao
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan-di Zhang
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Dan-yun Lai
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jo-Lewis Banga Ndzouboukou
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bo Zhang
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hong Chen
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zhu-qing Ouyang
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jun-biao Xue
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - Xiao-song Lin
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yun-xiao Zheng
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - Xue-ning Wang
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - He-wei Jiang
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - Hai-nan Zhang
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - Huan Qi
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - Shu-juan Guo
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
| | - Mei-an He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental and Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zi-yong Sun
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Feng Wang
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Corresponding authors at: No.13, Hangkong Rd., Wuhan 430030, China (X. Fan).
| | - Sheng-ce Tao
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
- Corresponding authors at: No.13, Hangkong Rd., Wuhan 430030, China (X. Fan).
| | - Xiong-lin Fan
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Corresponding authors at: No.13, Hangkong Rd., Wuhan 430030, China (X. Fan).
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Zhou H, Sun W, Zou J. Analysis of expression profiles and prognostic value of COP9 signalosome subunits for patients with head and neck squamous cell carcinoma. Oncol Lett 2021; 22:803. [PMID: 34630710 PMCID: PMC8477071 DOI: 10.3892/ol.2021.13064] [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: 05/14/2021] [Accepted: 07/14/2021] [Indexed: 11/25/2022] Open
Abstract
Head and neck squamous cell carcinoma (HNSCC) has been associated with poor prognosis, due to its strong invasive ability and resistance to chemotherapy. Thus, there is an urgent requirement to identify effective biomarkers for the early diagnosis and prognostic evaluation of HNSCC. COP9 signalosome (COPS) regulates numerous cancer-associated biological processes in various malignancies. The aim of the present study was to investigate the association between COPS and HNSCC. The mRNA expression profiles of COPS in HNSCC were analyzed using UALCAN, Oncomine and UCSC Xena databases. The association between overall survival time in patients with HNSCC and the COPS genes was investigated using the Kaplan-Meier plotter database. The CERES score was obtained and evaluated to determine the importance of the COPS genes for survival of the HNSCC cell lines. Functional analysis for Gene Ontology and Gene Set Enrichment Analysis (GSEA) was performed using The Database for Annotation, Visualization and Integrated Discovery and GSEA software, respectively. After knocking down COPS5 and COPS6, cell Counting Kit-8 and wound healing assays were used to detect cell growth and migration of the CAL27 and SCC25 cell lines, respectively. Among the 10 COPS genes examined, most COPS subunits were upregulated in HNSCC samples compared with that in normal tissues, except for COPS9. Increased mRNA expression level of COPS5, COPS6, COPS7B, COPS8 and COPS9 was associated with TNM stage in patients with HNSCC. High mRNA expression level of COPS2, COPS5, COPS6, COPS7A, COPS7B, COPS8 and COPS9 had prognostic significance of patients with HNSCC. Knockdown of COPS5 and COPS6 inhibited cell growth and migration of the CAL27 and SCC25 cell lines. The results from the present study suggested that COPS subunits could be potential biomarkers in patients with HNSCC. COPS5 and COPS6 were important for cell survival and migration of the HNSCC cells.
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Affiliation(s)
- Hao Zhou
- Department of Oral and Maxillofacial Surgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430000, P.R. China
| | - Wei Sun
- Department of Oral and Maxillofacial Surgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430000, P.R. China
| | - Jiaruan Zou
- Department of Oral and Maxillofacial Surgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430000, P.R. China
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30
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Prediction of Blood miRNA-mRNA Regulatory Network in Gastric Cancer. Rep Biochem Mol Biol 2021; 10:243-256. [PMID: 34604414 DOI: 10.52547/rbmb.10.2.243] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 10/13/2020] [Indexed: 01/15/2023]
Abstract
Background The aim of the study was to suggest a high specific and sensitive blood biomarker for early GC diagnosis. Methods the expression data of miRNAs and mRNAs were collected from the blood samples of the GC patients based on literature mining. Bioinformatics tools and databases (PANTHER, TargetScan, miRTarBase, miRDB, STRING, and Cytoscape) were used to predict the regulatory relationship. Subsequently, expression level of the selected miRNA was evaluated in the blood samples of gastritis patients to recognize the common miRNA between the GC and gastritis patients. Results Analysis of 40 target genes by MCODE (installed in Cytoscape software) indicated 4 hub genes (WWP1, SKP2, KLHL42, and FBXO11) as a significant cluster in the PPI network related to miR-21, with Node Score Cutoff: 0.2, Degree Cutoff: 2 and K-Core: 2. In addition, the miRNA RT-qPCR results showed that, the expression level of miR-21 was significantly higher in gastritis group compared to the healthy group (p< 0.05). Conclusion the present study clearly demonstrated the increasing level of blood miR-21 among the gastritis patients infected by H. pylori. Therefore, the altered miRNAs, especially overexpression of onco-miRs, may identify a potential link between miRNAs and pathogenesis of the H. pylori-related complications.
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31
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Wang H, Yang X, Sun G, Yang Q, Cui C, Wang X, Ye H, Dai L, Shi J, Zhang J, Wang P. Identification and Evaluation of Autoantibody to a Novel Tumor-Associated Antigen GNA11 as a Biomarker in Esophageal Squamous Cell Carcinoma. Front Oncol 2021; 11:661043. [PMID: 34568004 PMCID: PMC8462091 DOI: 10.3389/fonc.2021.661043] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 08/18/2021] [Indexed: 12/15/2022] Open
Abstract
The study aims to explore the diagnostic value of anti-GNA11 autoantibody in esophageal squamous cell carcinoma (ESCC) from multiple levels. Autoantibody against GNA11 with the highest diagnostic performance was screened out from the customized protein microarray. A total of 486 subjects including ESCC patients and matched normal controls were recruited in the verification and validation phases by using enzyme-linked immunosorbent assay (ELISA). Western blotting analysis was used to verify the ELISA results. Immunohistochemistry (IHC) was used to evaluate GNA11 expression in ESCC tissues and para-tumor tissues. In addition, a bioinformatics approach was adopted to investigate the mRNA expression of GNA11 in ESCC. Results indicated that the level of anti-GNA11 autoantibody in ESCC patients was significantly higher than that in the normal controls, and it can be used to distinguish ESCC patients from normal individuals in clinical subgroups (p < 0.05), as revealed by both ELISA and Western blotting. The receiver operating characteristic (ROC) curve analysis showed that anti-GNA11 autoantibody could distinguish ESCC patients from normal controls with an area under the ROC curve (AUC) of 0.653, sensitivity of 10.96%, and specificity of 98.63% in the verification cohort and with an AUC of 0.751, sensitivity of 38.24%, and specificity of 88.82% in the validation cohort. IHC manifested that the expression of GNA11 can differentiate ESCC tissues with para-tumor tissues (p < 0.05), but it cannot be used to differentiate different pathological grades and clinical stages (p > 0.05). The mRNA expression of GNA11 in ESCC patients and normal controls was different with a bioinformatics mining with The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) data in Gene Expression Profiling Interactive Analysis (GEPIA). In summary, anti-GNA11 autoantibody has the potential to be a new serological marker in the diagnosis of ESCC.
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Affiliation(s)
- Huimin Wang
- Henan Institute of Medical and Pharmaceutical Sciences in Academy of Medical Science, Zhengzhou University, Zhengzhou, China.,School of Basic Medical Sciences, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.,College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiaoang Yang
- Henan Institute of Medical and Pharmaceutical Sciences in Academy of Medical Science, Zhengzhou University, Zhengzhou, China
| | - Guiying Sun
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.,College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Qian Yang
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.,College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Chi Cui
- Henan Institute of Medical and Pharmaceutical Sciences in Academy of Medical Science, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Xiao Wang
- Henan Institute of Medical and Pharmaceutical Sciences in Academy of Medical Science, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Hua Ye
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.,College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Liping Dai
- Henan Institute of Medical and Pharmaceutical Sciences in Academy of Medical Science, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Jianxiang Shi
- Henan Institute of Medical and Pharmaceutical Sciences in Academy of Medical Science, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Jianying Zhang
- Henan Institute of Medical and Pharmaceutical Sciences in Academy of Medical Science, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Peng Wang
- Henan Institute of Medical and Pharmaceutical Sciences in Academy of Medical Science, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.,College of Public Health, Zhengzhou University, Zhengzhou, China
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32
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Wang D, Deng L, Xu X, Ji Y, Jiao Z. Elevated SYNC Expression Is Associated with Gastric Tumorigenesis and Infiltration of M2-Polarized Macrophages in the Gastric Tumor Immune Microenvironment. Genet Test Mol Biomarkers 2021; 25:236-246. [PMID: 33734892 DOI: 10.1089/gtmb.2020.0131] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Aims: To assess the expression and epigenetic regulation of Syncoilin, intermediate filament protein (SYNC) in gastric cancer tissues, and to determine its associations with clinicopathological features; immune infiltration of macrophages in tumors; and patient survival. Materials and Methods: Clinicopathological features, expression profiles, and methylation data of the SYNC gene were obtained from multi-institutional real-world public datasets. A total of 1601 samples from patients with gastric cancer were examined. The associations between clinicopathological features and SYNC expression levels were assessed by the chi-square test; survival was assessed using the Kaplan-Meier analysis. The infiltration levels of M1, 2-polarized tumor-associated macrophages (TAMs) in a gastric tumor immune microenvironment were quantified using deconvolution, and the correlation between SYNC expression level and M1, 2-polarized macrophages' infiltration was examined using the Pearson correlation test. SYNC gene methylation data were analyzed to investigate epigenetic control of its expression. Results: SYNC expression was elevated in gastric cancer tissues (p < 0.01), and was associated with a poorer overall survival (p < 0.01) and poorer postprogression survival (p = 0.01). Higher SYNC levels were significantly associated with more aggressive clinicopathological features in gastric cancer patients (p < 0.05). SYNC was also associated with the infiltration of M2-polarized TAMs in the gastric tumor immune microenvironment (p < 0.001). Hypomethylation was shown to be associated with SYNC's upregulation (p < 0.05). Conclusion: SYNC is highly expressed in gastric cancer tissues and has the potential to be a therapeutic target and to serve as a prognostic marker.
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Affiliation(s)
- Dazhi Wang
- Department of Medicinal Chemistry, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.,Department of Pharmacy, Center for Precision Cancer Medicine, Clinical Oncology Pharmacist Training Bases (National Health Commission), Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lihua Deng
- Department of Oncology, Center for Precision Cancer Medicine, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xiaona Xu
- Department of Central Laboratories, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yinghui Ji
- Department of Pharmacy, Affiliated Hospital of Weifang Medical University, Weifang, China
| | - Zheng Jiao
- Department of Pharmacy, Center for Precision Cancer Medicine, Clinical Oncology Pharmacist Training Bases (National Health Commission), Qingdao Municipal Hospital, Qingdao University, Qingdao, China
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Li Z, Hu J, Liu P, Cui D, Di H, Wu S. Microarray-based selection of a serum biomarker panel that can discriminate between latent and active pulmonary TB. Sci Rep 2021; 11:14516. [PMID: 34267288 PMCID: PMC8282789 DOI: 10.1038/s41598-021-93893-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 06/11/2021] [Indexed: 12/14/2022] Open
Abstract
Bacterial culture of M. tuberculosis (MTB), the causative agent of tuberculosis (TB), from clinical specimens is the gold standard for laboratory diagnosis of TB, but is slow and culture-negative TB cases are common. Alternative immune-based and molecular approaches have been developed, but cannot discriminate between active TB (ATB) and latent TB (LTBI). Here, to identify biomarkers that can discriminate between ATB and LTBI/healthy individuals (HC), we profiled 116 serum samples (HC, LTBI and ATB) using a protein microarray containing 257 MTB secreted proteins, identifying 23 antibodies against MTB antigens that were present at significantly higher levels in patients with ATB than in those with LTBI and HC (Fold change > 1.2; p < 0.05). A 4-protein biomarker panel (Rv0934, Rv3881c, Rv1860 and Rv1827), optimized using SAM and ROC analysis, had a sensitivity of 67.3% and specificity of 91.2% for distinguishing ATB from LTBI, and 71.2% sensitivity and 96.3% specificity for distinguishing ATB from HC. Validation of the four candidate biomarkers in ELISA assays using 440 serum samples gave consistent results. The promising sensitivity and specificity of this biomarker panel suggest it merits further investigation for its potential as a diagnostic for discriminating between latent and active TB.
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Affiliation(s)
- Zhihui Li
- Hebei Chest Hospital, Shijiazhuang, 050041, China
| | - Jianjun Hu
- Hebei Chest Hospital, Shijiazhuang, 050041, China
| | | | - Dan Cui
- Hebei Chest Hospital, Shijiazhuang, 050041, China
| | - Hongqin Di
- Hebei Chest Hospital, Shijiazhuang, 050041, China
| | - Shucai Wu
- Hebei Chest Hospital, Shijiazhuang, 050041, China.
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McGregor R, Tay ML, Carlton LH, Hanson-Manful P, Raynes JM, Forsyth WO, Brewster DT, Middleditch MJ, Bennett J, Martin WJ, Wilson N, Atatoa Carr P, Baker MG, Moreland NJ. Mapping Autoantibodies in Children With Acute Rheumatic Fever. Front Immunol 2021; 12:702877. [PMID: 34335616 PMCID: PMC8320770 DOI: 10.3389/fimmu.2021.702877] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 07/02/2021] [Indexed: 01/16/2023] Open
Abstract
Background Acute rheumatic fever (ARF) is a serious sequela of Group A Streptococcus (GAS) infection associated with significant global mortality. Pathogenesis remains poorly understood, with the current prevailing hypothesis based on molecular mimicry and the notion that antibodies generated in response to GAS infection cross-react with cardiac proteins such as myosin. Contemporary investigations of the broader autoantibody response in ARF are needed to both inform pathogenesis models and identify new biomarkers for the disease. Methods This study has utilised a multi-platform approach to profile circulating autoantibodies in ARF. Sera from patients with ARF, matched healthy controls and patients with uncomplicated GAS pharyngitis were initially analysed for autoreactivity using high content protein arrays (Protoarray, 9000 autoantigens), and further explored using a second protein array platform (HuProt Array, 16,000 autoantigens) and 2-D gel electrophoresis of heart tissue combined with mass spectrometry. Selected autoantigens were orthogonally validated using conventional immunoassays with sera from an ARF case-control study (n=79 cases and n=89 matched healthy controls) and a related study of GAS pharyngitis (n=39) conducted in New Zealand. Results Global analysis of the protein array data showed an increase in total autoantigen reactivity in ARF patients compared with controls, as well as marked heterogeneity in the autoantibody profiles between ARF patients. Autoantigens previously implicated in ARF pathogenesis, such as myosin and collagens were detected, as were novel candidates. Disease pathway analysis revealed several autoantigens within pathways linked to arthritic and myocardial disease. Orthogonal validation of three novel autoantigens (PTPN2, DMD and ANXA6) showed significant elevation of serum antibodies in ARF (p < 0.05), and further highlighted heterogeneity with patients reactive to different combinations of the three antigens. Conclusions The broad yet heterogenous elevation of autoantibodies observed suggests epitope spreading, and an expansion of the autoantibody repertoire, likely plays a key role in ARF pathogenesis and disease progression. Multiple autoantigens may be needed as diagnostic biomarkers to capture this heterogeneity.
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Affiliation(s)
- Reuben McGregor
- School of Medical Sciences, The University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
| | - Mei Lin Tay
- School of Medical Sciences, The University of Auckland, Auckland, New Zealand
| | - Lauren H. Carlton
- School of Medical Sciences, The University of Auckland, Auckland, New Zealand
| | | | - Jeremy M. Raynes
- School of Medical Sciences, The University of Auckland, Auckland, New Zealand
| | - Wasan O. Forsyth
- School of Medical Sciences, The University of Auckland, Auckland, New Zealand
| | | | | | - Julie Bennett
- Department of Public Health, University of Otago, Wellington, New Zealand
| | - William John Martin
- Science for Technological Innovation Science Challenge, Callaghan Innovation, Wellington, New Zealand
| | - Nigel Wilson
- Starship Children’s Hospital, Auckland, New Zealand
| | - Polly Atatoa Carr
- Waikato District Health Board and Waikato University, Hamilton, New Zealand
| | - Michael G. Baker
- Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
- Department of Public Health, University of Otago, Wellington, New Zealand
| | - Nicole J. Moreland
- School of Medical Sciences, The University of Auckland, Auckland, New Zealand
- Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
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35
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Comprehending the Proteomic Landscape of Ovarian Cancer: A Road to the Discovery of Disease Biomarkers. Proteomes 2021; 9:proteomes9020025. [PMID: 34070600 PMCID: PMC8163166 DOI: 10.3390/proteomes9020025] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/20/2021] [Accepted: 05/21/2021] [Indexed: 12/28/2022] Open
Abstract
Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for personalized therapy and management of drug resistance. Here, we review single and multiple marker panels that have been identified through proteomic investigations of patient sera, effusions, and other biospecimens. We discuss their clinical utility and implementation into clinical practice.
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36
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Abstract
Epidemiological studies have reported an inverse correlation between cancer and neurodegenerative disorders, and increasing evidence shows that similar genes and pathways are dysregulated in both diseases but in a contrasting manner. Given the genetic convergence of the neuronal ceroid lipofuscinoses (NCLs), a family of rare neurodegenerative disorders commonly known as Batten disease, and other neurodegenerative diseases, we sought to explore the relationship between cancer and the NCLs. In this review, we survey data from The Cancer Genome Atlas and available literature on the roles of NCL genes in different oncogenic processes to reveal links between all the NCL genes and cancer-related processes. We also discuss the potential contributions of NCL genes to cancer immunology. Based on our findings, we propose that further research on the relationship between cancer and the NCLs may help shed light on the roles of NCL genes in both diseases and possibly guide therapy development.
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37
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Circulating lncRNA DANCR as a potential auxillary biomarker for the diagnosis and prognostic prediction of colorectal cancer. Biosci Rep 2021; 40:222327. [PMID: 32159208 PMCID: PMC7103578 DOI: 10.1042/bsr20191481] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 02/11/2020] [Accepted: 03/03/2020] [Indexed: 12/13/2022] Open
Abstract
Studies have shown that long non-coding RNAs (lncRNAs) play vital roles in the development of cancer, including colorectal cancer (CRC). Our purpose is to validate the diagnostic value of serum differentiation antagonizing non-protein coding RNA (DANCR) in CRC by focusing on its expression and clinical application. lncRNA expression profiles of CRC patients were obtained and analyzed by repurposing the publically available microarray data. Tissue or serum specimens were obtained from 40 patients with primary CRC, 10 patients with recurrent CRC, 40 patients with colorectal polyps, and 40 healthy controls. It was found that DANCR level in the CRC tissue and serum was significantly increased, and serum DANCR expression was decreased in post-operative patients as compared with that in pre-treatment patients and recurrent patients. In addition, serum DANCR expression was significantly correlated with different TNM stages. Correlation analysis of DANCR and other diagnostic indicators showed that the serum DANCR expression level was significantly correlated with CA199 but not with CEA in CRC patients. As for diagnostic efficiency by ROC analysis, the area under the curve (AUC) of serum DANCR was higher than that of CEA and CA199 in CRC group vs. colorectal polyp group. Simultaneous detection of DANCR, CEA and CA199 yielded the highest sensitivity and AUC as compared with either of them alone. Taken together, serum DANCR was up-regulated in CRC patients and high expression of DANCR may prove to be a potential biomarker for the diagnosis of CRC.
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38
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Li Y, Lai DY, Lei Q, Xu ZW, Wang F, Hou H, Chen L, Wu J, Ren Y, Ma ML, Zhang B, Chen H, Yu C, Xue JB, Zheng YX, Wang XN, Jiang HW, Zhang HN, Qi H, Guo SJ, Zhang Y, Lin X, Yao Z, Pang P, Shi D, Wang W, Yang X, Zhou J, Sheng H, Sun Z, Shan H, Fan X, Tao SC. Systematic evaluation of IgG responses to SARS-CoV-2 spike protein-derived peptides for monitoring COVID-19 patients. Cell Mol Immunol 2021; 18:621-631. [PMID: 33483707 PMCID: PMC7821179 DOI: 10.1038/s41423-020-00612-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 11/30/2020] [Indexed: 02/07/2023] Open
Abstract
Serological tests play an essential role in monitoring and combating the COVID-19 pandemic. Recombinant spike protein (S protein), especially the S1 protein, is one of the major reagents used for serological tests. However, the high cost of S protein production and possible cross-reactivity with other human coronaviruses pose unavoidable challenges. By taking advantage of a peptide microarray with full spike protein coverage, we analyzed 2,434 sera from 858 COVID-19 patients, 63 asymptomatic patients and 610 controls collected from multiple clinical centers. Based on the results, we identified several S protein-derived 12-mer peptides that have high diagnostic performance. In particular, for monitoring the IgG response, one peptide (aa 1148-1159 or S2-78) exhibited a sensitivity (95.5%, 95% CI 93.7-96.9%) and specificity (96.7%, 95% CI 94.8-98.0%) comparable to those of the S1 protein for the detection of both symptomatic and asymptomatic COVID-19 cases. Furthermore, the diagnostic performance of the S2-78 (aa 1148-1159) IgG was successfully validated by ELISA in an independent sample cohort. A panel of four peptides, S1-93 (aa 553-564), S1-97 (aa 577-588), S1-101 (aa 601-612) and S1-105 (aa 625-636), that likely will avoid potential cross-reactivity with sera from patients infected by other coronaviruses was constructed. The peptides identified in this study may be applied independently or in combination with the S1 protein for accurate, affordable, and accessible COVID-19 diagnosis.
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Affiliation(s)
- Yang Li
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Dan-Yun Lai
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Qing Lei
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhao-Wei Xu
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China
| | - Feng Wang
- Department of Clinical Laboratory, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongyan Hou
- Department of Clinical Laboratory, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lingyun Chen
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, 518083, China
| | - Jiaoxiang Wu
- Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan Ren
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Ming-Liang Ma
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Bo Zhang
- Department of Clinical Laboratory, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hong Chen
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Caizheng Yu
- Department of Public Health, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jun-Biao Xue
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Yun-Xiao Zheng
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Xue-Ning Wang
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - He-Wei Jiang
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Hai-Nan Zhang
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Huan Qi
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Shu-Juan Guo
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Yandi Zhang
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaosong Lin
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zongjie Yao
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Pengfei Pang
- Center for Interventional Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, 519000, China
| | - Dawei Shi
- National Institutes for Food and Drug Control, Beijing, 100050, China
| | - Wei Wang
- Foshan Fourth People's Hospital, Foshan, 528000, China
| | - Xiao Yang
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jie Zhou
- Foshan Fourth People's Hospital, Foshan, 528000, China
| | - Huiming Sheng
- Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ziyong Sun
- Department of Clinical Laboratory, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hong Shan
- Center for Interventional Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, 519000, China.
| | - Xionglin Fan
- Department of Pathogen Biology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Sheng-Ce Tao
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China.
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Cui C, Duan Y, Qiu C, Wang P, Sun G, Ye H, Dai L, Han Z, Song C, Wang K, Shi J, Zhang J. Identification of Novel Autoantibodies Based on the Human Proteomic Chips and Evaluation of Their Performance in the Detection of Gastric Cancer. Front Oncol 2021; 11:637871. [PMID: 33718231 PMCID: PMC7953047 DOI: 10.3389/fonc.2021.637871] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 01/27/2021] [Indexed: 12/24/2022] Open
Abstract
Autoantibodies against tumor-associated antigens (TAAbs) can be used as potential biomarkers in the detection of cancer. Our study aims to identify novel TAAbs for gastric cancer (GC) based on human proteomic chips and construct a diagnostic model to distinguish GC from healthy controls (HCs) based on serum TAAbs. The human proteomic chips were used to screen the candidate TAAbs. Enzyme-linked immunosorbent assay (ELISA) was used to verify and validate the titer of the candidate TAAbs in the verification cohort (80 GC cases and 80 HCs) and validation cohort (192 GC cases, 128 benign gastric disease cases, and 192 HCs), respectively. Then, the diagnostic model was established by Logistic regression analysis based on OD values of candidate autoantibodies with diagnostic value. Eleven candidate TAAbs were identified, including autoantibodies against INPP5A, F8, NRAS, MFGE8, PTP4A1, RRAS2, RGS4, RHOG, SRARP, RAC1, and TMEM243 by proteomic chips. The titer of autoantibodies against INPP5A, F8, NRAS, MFGE8, PTP4A1, and RRAS2 were significantly higher in GC cases while the titer of autoantibodies against RGS4, RHOG, SRARP, RAC1, and TMEM243 showed no difference in the verification group. Next, six potential TAAbs were validated in the validation cohort. The titer of autoantibodies against F8, NRAS, MFGE8, RRAS2, and PTP4A1 was significantly higher in GC cases. Finally, an optimal prediction model with four TAAbs (anti-NRAS, anti-MFGE8, anti-PTP4A1, and anti-RRAS2) showed an optimal diagnostic performance of GC with AUC of 0.87 in the training group and 0.83 in the testing group. The proteomic chip approach is a feasible method to identify TAAbs for the detection of cancer. Moreover, the panel consisting of anti-NRAS, anti-MFGE8, anti-PTP4A1, and anti-RRAS2 may be useful to distinguish GC cases from HCs.
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Affiliation(s)
- Chi Cui
- BGI College & Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
| | - Yaru Duan
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- School of Basic Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Cuipeng Qiu
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Peng Wang
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- College of Public Health, Zhengzhou University, Zhengzhou, China
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Guiying Sun
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Hua Ye
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- College of Public Health, Zhengzhou University, Zhengzhou, China
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Liping Dai
- BGI College & Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Zhuo Han
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Chunhua Song
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Kaijuan Wang
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Jianxiang Shi
- BGI College & Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- College of Public Health, Zhengzhou University, Zhengzhou, China
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Jianying Zhang
- BGI College & Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- College of Public Health, Zhengzhou University, Zhengzhou, China
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
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Zheng GD, Xu ZY, Hu C, Lv H, Xie HX, Huang T, Zhang YQ, Chen GP, Fu YF, Cheng XD. Exosomal miR-590-5p in Serum as a Biomarker for the Diagnosis and Prognosis of Gastric Cancer. Front Mol Biosci 2021; 8:636566. [PMID: 33681295 PMCID: PMC7928302 DOI: 10.3389/fmolb.2021.636566] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 01/06/2021] [Indexed: 12/20/2022] Open
Abstract
The purpose of this study is to explore the expression of miRNA-590-5p, an exosome of gastric cancer (GC), and to evaluate the suitability of miR-590-5p, an exosome with its own clinical characteristics. Serum samples from 168 gastric cancer patients and 50 matched controls were collected and exosomal RNAs were extracted. After that, miR-590-5p is analyzed by quantitative polymerase chain reaction (qRT-PCR), which is more related to clinical and pathological parameters and patient monitoring data. MGC-803 and HGC-27 cells were treated by miR-590-5p mimics, and then the changes of cell fluidity and invasiveness were monitored. The results showed that the expression level of miR-590-5p in exosomes of healthy observation group, early (I and II) stage group, and late stage (III) group was 30.34 ± 6.35, 6.19 ± 0.81, and 2.9 ± 0.19, respectively (all p < 0.05). ROC (receiver-operating characteristic curve) showed that the AUC (area under the curve) of exosomal miR-590-5p was 0.810 with 63.7% sensitivity and 86% specificity. The expression of exosomal miR-590-5p in serum was related to clinical stage (p = 0.008), infiltration depth, and the expression level of ki-67 (p < 0.001). In addition, Kaplan-Meier analysis showed that the decrease of explicit level of exosomal miR-590-5p was related to the decrease of overall survival rate (p < 0.001). Cox regression analysis showed that miR-590-5p can be used as an independent predictor. Furthermore, upregulation of miR-590-5p inhibited cell migration and invasion in MGC-803 cells and HGC-27 cells. The serum expression level of exosomal miR-590-5p may be a biomarker, which is potentially useful and noninvasive for early detection and prediction of GC. In addition, miR-590-5p can play a role in eliminating carcinogens by actively regulating the malignant potential of gastric cancer.
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Affiliation(s)
- Guo-Dian Zheng
- Department of Hepatobiliary Surgery, Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, China
| | - Zhi-Yuan Xu
- Department of Gastric Surgery, Institute of Cancer Research and Basic Medical Sciences of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, China
| | - Can Hu
- The 2nd Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Hang Lv
- Laboratory of Digestive Pathophysiology of Zhejiang Province, Institute of Cancer Research, First Affiliated Hospital, Zhejiang Chinese Medical University, Hangzhou, China
| | - Hua-Xia Xie
- Department of General Surgery, Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, China
| | - Ting Huang
- Department of Gastroenterological Surgery, Zhejiang Integrated Traditional and Western Medicine Hospital, Hangzhou, China
| | - Yan-Qiang Zhang
- Department of Gastric Surgery, Institute of Cancer Research and Basic Medical Sciences of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, China
| | - Gui-Ping Chen
- Department of Hepatobiliary Surgery, Zhejiang Provincial Hospital of Traditional Chinese Medicine, Hangzhou, China
| | - Yu-Fei Fu
- Laboratory of Digestive Pathophysiology of Zhejiang Province, Institute of Cancer Research, First Affiliated Hospital, Zhejiang Chinese Medical University, Hangzhou, China
| | - Xiang-Dong Cheng
- Department of Gastric Surgery, Institute of Cancer Research and Basic Medical Sciences of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, China
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Wen X, Song G, Hu C, Pan J, Wu Z, Li L, Liu C, Tian X, Zhang F, Qian J, Zhu H, Li Y. Identification of Novel Serological Autoantibodies in Takayasu Arteritis Patients Using HuProt Arrays. Mol Cell Proteomics 2021; 20:100036. [PMID: 33545363 PMCID: PMC7995655 DOI: 10.1074/mcp.ra120.002119] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 08/27/2020] [Accepted: 12/17/2020] [Indexed: 02/05/2023] Open
Abstract
To identify novel autoantibodies of Takayasu arteritis (TAK) using HuProt array-based approach, a two-phase approach was adopted. In Phase I, serum samples collected from 40 TAK patients, 15 autoimmune disease patients, and 20 healthy subjects were screened to identify TAK-specific autoantibodies using human protein (HuProt) arrays. In phase II, the identified candidate autoantibodies were validated with TAK-focused arrays using an additional cohort comprised of 109 TAK patients, 110 autoimmune disease patients, and 96 healthy subjects. Subsequently, the TAK-specific autoantibodies validated in phase II were further confirmed using western blot analysis. We identified and validated eight autoantibodies as potential TAK-specific diagnostic biomarkers, including anti-SPATA7, -QDPR, -SLC25A2, -PRH2, -DIXDC1, -IL17RB, -ZFAND4, and -NOLC1 antibodies, with AUC of 0.803, 0.801, 0.780, 0.696, 0.695, 0.678, 0.635, and 0.613, respectively. SPATA7 could distinguish TAK from healthy and disease controls with 73.4% sensitivity at 85.4% specificity, while QDPR showed 71.6% sensitivity at 86.4% specificity. SLC25A22 showed the highest sensitivity of 80.7%, but at lower specificity of 67.0%. In addition, PRH2, IL17RB, and NOLC1 showed good specificities of 88.3%, 85.9%, and 86.9%, respectively, but at lower sensitivities (<50%). Finally, DIXDC1 and ZFAND4 showed moderate performance as compared with the other autoantibodies. Using a decision tree model, we could reach a specificity of 94.2% with AUC of 0.843, a significantly improved performance as compared with that by each individual biomarker. The performances of three autoantibodies, namely anti-SPATA7, -QDPR, and -PRH2, were successfully confirmed with western blot analysis. Using this two-phase strategy, we identified and validated eight novel autoantibodies as TAK-specific biomarker candidates, three of which could be readily adopted in a clinical setting.
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Affiliation(s)
- Xiaoting Wen
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China; Department of Rheumatology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Taiyuan, Shanxi, China
| | - Guang Song
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Chaojun Hu
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China
| | - Jianbo Pan
- Department of Ophthalmology, Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Ziyan Wu
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China
| | - Liubing Li
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chenxi Liu
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xinping Tian
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China
| | - Fengchun Zhang
- Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, China
| | - Jiang Qian
- Department of Ophthalmology, Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Heng Zhu
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
| | - Yongzhe Li
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China; State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China.
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42
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Ding J, Shi F, Xie G, Zhu Y. Long Non-coding RNA LINC01503 Promotes Gastric Cancer Cell Proliferation and Invasion by Regulating Wnt Signaling. Dig Dis Sci 2021; 66:452-459. [PMID: 32207034 DOI: 10.1007/s10620-020-06215-4] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 03/16/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND Previous studies have indicated that the dysregulation of long non-coding RNAs plays an important role in tumors. LINC01503 is a newly discovered lncRNA that promotes development of various tumor types. However, the function of LINC01503 in gastric cancer has not been reported yet. AIMS To explore the function of LINC01503 in gastric cancer development and the underlying molecular biological regulatory mechanisms. METHODS LINC01503 expression in tissues and cell lines of gastric cancer were determined through qRT-PCR. Transwell assay and cell number counting experiments were employed to detect the cell invasion and proliferation. C-myc, cyclin D1, and β-catenin expressions were analyzed through Western blot and qRT-PCR. RESULTS LINC01503 was highly expressed in gastric cancer tissues and cell lines, which was correlated with poor prognosis. Knockdown of LINC01503 suppressed gastric cancer cell proliferation and invasion, whereas overexpression of LINC01503 showed a reverse trend. Silencing LINC01503 significantly inhibited the expression of c-myc, cyclin D1, and β-catenin. Overexpressing β-catenin rescued the inhibitory effects, induced by LINC01503 silencing, on gastric cancer cell proliferation and metastasis. CONCLUSIONS This research reported that the elevated expression of LINC01503 could promote proliferation and metastasis of gastric cancer through positively regulating the Wnt/β-catenin pathway.
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Affiliation(s)
- Jian Ding
- The Affiliated Hospital of Shandong University of TCM, No. 16369, Jingshi Road, Jinan, 250014, Shandong, China
| | - Feng Shi
- The Affiliated Hospital of Shandong University of TCM, No. 16369, Jingshi Road, Jinan, 250014, Shandong, China
| | - Guangdong Xie
- Shandong University of Traditional Chinese Medicine, No. 21, Shanshi East Road, Lixia District, Jinan, 250014, Shandong, China
| | - Yong Zhu
- The Affiliated Hospital of Shandong University of TCM, No. 16369, Jingshi Road, Jinan, 250014, Shandong, China.
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You H, Dang G, Lu B, Zhang S, Li C, Wang L, Hu Y, Chen H, Zhang J, He W. Serum Sp17 Autoantibody Serves as a Potential Specific Biomarker in Patients with SAPHO Syndrome. J Clin Immunol 2021; 41:565-575. [PMID: 33392854 PMCID: PMC7921076 DOI: 10.1007/s10875-020-00937-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 11/30/2020] [Indexed: 11/30/2022]
Abstract
SAPHO (synovitis, acne, pustulosis, hyperostosis, and osteitis) syndrome shows a wide variability in musculoskeletal and cutaneous manifestations, and it is therefore underrecognized and misdiagnosed in the clinic due to a lack of specific markers. In this study, we aimed to identify specific biomarkers by screening serum autoantibodies in SAPHO patients with a 17K human whole-proteome microarray. The serum anti-Sp17 autoantibody was identified and verified to be a specific biomarker in patients with SAPHO syndrome. Indeed, the level of the anti-Sp17 autoantibody was significantly increased in patients with active SAPHO compared to patients with an inactive disease and healthy controls (P < 0.05). Additionally, serum anti-Sp17 autoantibody levels correlated with those of serum hypersensitive C-reactive protein (hsCRP), the erythrocyte sedimentation rate (ESR), and β-crosslaps (β-CTx) in patients with active SAPHO disease. Moreover, anti-Sp17 autoantibody levels were markedly decreased after anti-inflammatory treatment with pamidronate disodium, which downregulated levels of hsCRP and ESR in patients with active SAPHO. Thus, serum levels of the anti-Sp17 autoantibody might serve as a specific biomarker for the diagnosis of SAPHO syndrome or for monitoring the disease status.
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Affiliation(s)
- Hongqin You
- Department of Immunology, Key Laboratory of T Cell Mediated Cancer Immunotherapy, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, State Key Laboratory of Medical Molecular Biology, Peking Union Medical College, Beijing, China
- Department of Immunotherapy, Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou, Henan, China
| | - Guanglei Dang
- Department of Immunology, Key Laboratory of T Cell Mediated Cancer Immunotherapy, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, State Key Laboratory of Medical Molecular Biology, Peking Union Medical College, Beijing, China
| | - Bichao Lu
- Department of Immunology, Key Laboratory of T Cell Mediated Cancer Immunotherapy, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, State Key Laboratory of Medical Molecular Biology, Peking Union Medical College, Beijing, China
| | - Siya Zhang
- Department of Immunology, Key Laboratory of T Cell Mediated Cancer Immunotherapy, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, State Key Laboratory of Medical Molecular Biology, Peking Union Medical College, Beijing, China
| | - Chen Li
- Department of Traditional Chinese Medicine, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
| | - Lun Wang
- Institute of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yu Hu
- Department of Immunology, Key Laboratory of T Cell Mediated Cancer Immunotherapy, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, State Key Laboratory of Medical Molecular Biology, Peking Union Medical College, Beijing, China
| | - Hui Chen
- Department of Immunology, Key Laboratory of T Cell Mediated Cancer Immunotherapy, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, State Key Laboratory of Medical Molecular Biology, Peking Union Medical College, Beijing, China.
| | - Jianmin Zhang
- Department of Immunology, Key Laboratory of T Cell Mediated Cancer Immunotherapy, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, State Key Laboratory of Medical Molecular Biology, Peking Union Medical College, Beijing, China.
| | - Wei He
- Department of Immunology, Key Laboratory of T Cell Mediated Cancer Immunotherapy, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, State Key Laboratory of Medical Molecular Biology, Peking Union Medical College, Beijing, China.
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Poulsen TBG, Karamehmedovic A, Aboo C, Jørgensen MM, Yu X, Fang X, Blackburn JM, Nielsen CH, Kragstrup TW, Stensballe A. Protein array-based companion diagnostics in precision medicine. Expert Rev Mol Diagn 2020; 20:1183-1198. [PMID: 33315478 DOI: 10.1080/14737159.2020.1857734] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
INTRODUCTION The development of companion diagnostics (CDx) will increase efficacy and cost-benefit markedly, compared to the currently prevailing trial-and-error approach for treatment. Recent improvements in high-throughput protein technology have resulted in large amounts of predictive biomarkers that are potentially useful components of future CDx assays. Current high multiplex protein arrays are suitable for discovery-based approaches, while low-density and more simple arrays are suitable for use in point-of-care facilities. AREA COVERED This review discusses the technical platforms available for protein array focused CDx, explains the technical details of the platforms and provide examples of clinical use, ranging from multiplex arrays to low-density clinically applicable arrays. We thereafter highlight recent predictive biomarkers within different disease areas, such as oncology and autoimmune diseases. Lastly, we discuss some of the challenges connected to the implementation of CDx assays as point-of-care tests. EXPERT OPINION Recent advances in the field of protein arrays have enabled high-density arrays permitting large biomarker discovery studies, which are beneficial for future CDx assays. The density of protein arrays range from a single protein to proteome-wide arrays, allowing the discovery of protein signatures that may correlate with drug response. Protein arrays will undoubtedly play a key role in future CDx assays.
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Affiliation(s)
- Thomas B G Poulsen
- Department of Health Science and Technology, Aalborg University , Aalborg, Denmark.,Sino-Danish Center for Education and Research, University of Chinese Academy of Sciences , China
| | - Azra Karamehmedovic
- Department of Health Science and Technology, Aalborg University , Aalborg, Denmark.,Sino-Danish Center for Education and Research, University of Chinese Academy of Sciences , China
| | - Christopher Aboo
- Department of Health Science and Technology, Aalborg University , Aalborg, Denmark.,Sino-Danish Center for Education and Research, University of Chinese Academy of Sciences , China
| | - Malene Møller Jørgensen
- Department of Clinical Immunology, Aalborg University Hospital , Aalborg, Denmark.,Department of Clinical Medicine, Aalborg University , Aalborg, Denmark
| | - Xiaobo Yu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics , Beijing, China
| | - Xiangdong Fang
- Sino-Danish Center for Education and Research, University of Chinese Academy of Sciences , China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences , China
| | - Jonathan M Blackburn
- Department of Integrative Biomedical Sciences & Institute of Infectious Disease and Molecular Medicine, University of Cape Town , Cape Town, South Africa.,Sengenics Corporation Pte Ltd , Singapore
| | - Claus H Nielsen
- Institute for Inflammation Research, Center for Rheumatology and Spine Diseases, Copenhagen University Hospital Rigshospitalet , Copenhagen, Denmark
| | - Tue W Kragstrup
- Department of Biomedicine, Aarhus University , Aarhus, Denmark.,Department of Rheumatology, Aarhus University Hospital , Aarhus, Denmark
| | - Allan Stensballe
- Department of Health Science and Technology, Aalborg University , Aalborg, Denmark
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High ELK3 expression is associated with the VEGF-C/VEGFR-3 axis and gastric tumorigenesis and enhances infiltration of M2 macrophages. Future Med Chem 2020; 12:2209-2224. [PMID: 33191789 DOI: 10.4155/fmc-2019-0337] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Aim: To assess the expression and effect of ELK3 in gastric cancer, along with its associations with the VEGF-C/VEGFR-3 axis, IC50 of the VEGFR-3 inhibitor axitinib and immune infiltration of M2-polarized macrophages in gastric cancer, and to analyze the possible epigenetic regulation mechanism. Materials & methods: Expression profiles and methylation data from 1645 samples were obtained and examined from multi-institutional public datasets. The associations were assessed by multiple analysis methods. Results: Elevated ELK3 is associated with the VEGF-C/VEGFR-3 axis and tumorigenesis, reduces the effect of axitinib in vitro, enhances immune infiltration of M2 macrophages and affects clinical outcomes. Hypomethylation contributes to the upregulation of ELK3 in gastric cancer. Conclusions: ELK3 is a potential therapeutic target which reduces the effect of axitinib and enhances infiltration of M2-polarized macrophages.
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Rauf F, Anderson KS, LaBaer J. Autoantibodies in Early Detection of Breast Cancer. Cancer Epidemiol Biomarkers Prev 2020; 29:2475-2485. [PMID: 32994341 PMCID: PMC7710604 DOI: 10.1158/1055-9965.epi-20-0331] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 07/14/2020] [Accepted: 09/24/2020] [Indexed: 02/06/2023] Open
Abstract
In spite of the progress made in treatment and early diagnosis, breast cancer remains a major public health issue worldwide. Although modern image-based screening modalities have significantly improved early diagnosis, around 15% to 20% of breast cancers still go undetected. In underdeveloped countries, lack of resources and cost concerns prevent implementing mammography for routine screening. Noninvasive, low-cost, blood-based markers for early breast cancer diagnosis would be an invaluable alternative that would complement mammography screening. Tumor-specific autoantibodies are excellent biosensors that could be exploited to monitor disease-specific changes years before disease onset. Although clinically informative autoantibody markers for early breast cancer screening have yet to emerge, progress has been made in the development of tools to discover and validate promising autoantibody signatures. This review focuses on the current progress toward the development of autoantibody-based early screening markers for breast cancer.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."
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Affiliation(s)
- Femina Rauf
- Virginia G. Piper Biodesign Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona
| | - Karen S Anderson
- Virginia G. Piper Biodesign Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona
| | - Joshua LaBaer
- Virginia G. Piper Biodesign Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona.
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Sun G, Ye H, Wang X, Cheng L, Ren P, Shi J, Dai L, Wang P, Zhang J. Identification of novel autoantibodies based on the protein chip encoded by cancer-driving genes in detection of esophageal squamous cell carcinoma. Oncoimmunology 2020; 9:1814515. [PMID: 33457096 PMCID: PMC7781740 DOI: 10.1080/2162402x.2020.1814515] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 08/03/2020] [Accepted: 08/20/2020] [Indexed: 01/22/2023] Open
Abstract
The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAbs) and explore the optimal diagnosis model based on the protein chip for detecting esophageal squamous cell carcinoma (ESCC). The human protein chip based on cancer-driving genes was customized to discover candidate TAAbs. Enzyme-linked immunosorbent assay was applied to verify and validate the expression levels of candidate TAAbs in the training cohort (130 ESCC and 130 normal controls) and the validation cohort (125 ESCC and 125 normal controls). Logistic regression analysis was adopted to construct the diagnostic model based on the expression levels of autoantibodies with diagnostic value. Twelve candidate autoantibodies were identified based on the protein chip according to the corresponding statistical methods. In both the training cohort and validation cohort, the expression levels of 10 TAAbs (GNA11, PTEN, P53, SRSF2, GNAS, ACVR1B, CASP8, DAXX, PDGFRA, and MEN1) in ESCC patients were higher than that in normal controls. The panel consisting of GNA11, ACVR1B and P53 demonstrated favorable diagnostic power. The sensitivity, specificity and accuracy of the model in the train cohort and the validation cohort were 71.5%, 93.8%, 79.6% and 77.6%, 81.6%, 70.8%, respectively. In either cohort, there was no correlation between positive rate of the autoantibody panel and clinicopathologic features for ESCC patients. Protein chip technology is an effective method to identify novel TAAbs, and the panel of 3 TAAbs (GNA11, ACVR1B, and P53) is promising for distinguishing ESCC patients from normal individuals.
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Affiliation(s)
- Guiying Sun
- College of Public Health, Zhengzhou University, Zhengzhou, China
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
| | - Hua Ye
- College of Public Health, Zhengzhou University, Zhengzhou, China
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
| | - Xiao Wang
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
| | - Lin Cheng
- College of Life Science, Xinyang Normal University, Xinyang, China
| | - Pengfei Ren
- Department of Molecular Pathology& Henan Key Laboratory of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
| | - Jianxiang Shi
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
| | - Liping Dai
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
| | - Peng Wang
- College of Public Health, Zhengzhou University, Zhengzhou, China
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
| | - Jianying Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, China
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Henan Key Laboratory of Tumor Epidemiology, Zhengzhou University, Zhengzhou, China
- Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
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Ling HZ, Xu SZ, Leng RX, Wu J, Pan HF, Fan YG, Wang B, Xia YR, Huang Q, Shuai ZW, Ye DQ. Discovery of new serum biomarker panels for systemic lupus erythematosus diagnosis. Rheumatology (Oxford) 2020; 59:1416-1425. [PMID: 31899518 DOI: 10.1093/rheumatology/kez634] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 11/26/2019] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE Clinical diagnosis of SLE is currently challenging due to its heterogeneity. Many autoantibodies are associated with SLE and are considered potential diagnostic markers, but systematic screening and validation of such autoantibodies is lacking. This study aimed to systematically discover new autoantibodies that may be good biomarkers for use in SLE diagnosis. METHODS Sera from 15 SLE patients and 5 healthy volunteers were analysed using human proteome microarrays to identify candidate SLE-related autoantibodies. The results were validated by screening of sera from 107 SLE patients, 94 healthy volunteers and 60 disease controls using focussed arrays comprised of autoantigens corresponding to the identified candidate antibodies. Logistic regression was used to derive and validate autoantibody panels that can discriminate SLE disease. Extensive ELISA screening of sera from 294 SLE patients and 461 controls was performed to validate one of the newly discovered autoantibodies. RESULTS A total of 31, 11 and 18 autoantibodies were identified to be expressed at significantly higher levels in the SLE group than in the healthy volunteers, disease controls and healthy volunteers plus disease control groups, respectively, with 25, 7 and 13 of these differentially expressed autoantibodies being previously unreported. Diagnostic panels comprising anti-RPLP2, anti-SNRPC and anti-PARP1, and anti-RPLP2, anti-PARP1, anti-MAK16 and anti- RPL7A were selected. Performance of the newly discovered anti-MAK16 autoantibody was confirmed by ELISA. Some associations were seen with clinical characteristics of SLE patients, such as disease activity with the level of anti-PARP1 and rash with the level of anti-RPLP2, anti-MAK16 and anti- RPL7A. CONCLUSION The combined autoantibody panels identified here show promise for the diagnosis of SLE and for differential diagnosis of other major rheumatic immune diseases.
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Affiliation(s)
- Hua-Zhi Ling
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical UniversityHefei, Anhui, China.,Department of Clinical Laboratory, the First Affiliated Hospital of Anhui Medical UniversityHefei, Anhui, China.,Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Shu-Zhen Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical UniversityHefei, Anhui, China.,Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Rui-Xue Leng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical UniversityHefei, Anhui, China.,Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Jun Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical UniversityHefei, Anhui, China
| | - Hai-Feng Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical UniversityHefei, Anhui, China.,Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Yin-Guang Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical UniversityHefei, Anhui, China
| | - Bin Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical UniversityHefei, Anhui, China
| | - Yuan-Rui Xia
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical UniversityHefei, Anhui, China
| | - Qian Huang
- Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
| | - Zong-Wen Shuai
- Department of Rheumatology and Immunology, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Dong-Qing Ye
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical UniversityHefei, Anhui, China.,Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, China
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Zhang S, Liu Y, Chen J, Shu H, Shen S, Li Y, Lu X, Cao X, Dong L, Shi J, Cao Y, Wang X, Zhou J, Liu Y, Chen L, Fan J, Ding G, Gao Q. Autoantibody signature in hepatocellular carcinoma using seromics. J Hematol Oncol 2020; 13:85. [PMID: 32616055 PMCID: PMC7330948 DOI: 10.1186/s13045-020-00918-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 06/16/2020] [Indexed: 02/07/2023] Open
Abstract
Background Alpha-fetoprotein (AFP) is a widely used biomarker for hepatocellular carcinoma (HCC) early detection. However, low sensitivity and false negativity of AFP raise the requirement of more effective early diagnostic approaches for HCC. Methods We employed a three-phase strategy to identify serum autoantibody (AAb) signature for HCC early diagnosis using protein array-based approach. A total of 1253 serum samples from HCC, liver cirrhosis, and healthy controls were prospectively collected from three liver cancer centers in China. The Human Proteome Microarray, comprising 21,154 unique proteins, was first applied to identify AAb candidates in discovery phase (n = 100) and to further fabricate HCC-focused arrays. Then, an artificial neural network (ANN) model was used to discover AAbs for HCC detection in a test phase (n = 576) and a validation phase (n = 577), respectively. Results Using HCC-focused array, we identified and validated a novel 7-AAb panel containing CIAPIN1, EGFR, MAS1, SLC44A3, ASAH1, UBL7, and ZNF428 for effective HCC detection. The ANN model of this panel showed improvement of sensitivity (61.6–77.7%) compared to AFP (cutoff 400 ng/mL, 28.4–30.7%). Notably, it was able to detect AFP-negative HCC with AUC values of 0.841–0.948. For early-stage HCC (BCLC 0/A) detection, it outperformed AFP (cutoff 400 ng/mL) with approximately 10% increase in AUC. Conclusions The 7-AAb panel provides potentially clinical value for non-invasive early detection of HCC, and brings new clues on understanding the immune response against hepatocarcinogenesis.
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Affiliation(s)
- Shu Zhang
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, 200032, China
| | - Yuming Liu
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, 200032, China
| | - Jing Chen
- The International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, 200438, China
| | - Hong Shu
- Department of Clinical Laboratory, Cancer Hospital of Guangxi Medical University, Nanning, 530021, China
| | - Siyun Shen
- The International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, 200438, China
| | - Yin Li
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Xinyuan Lu
- The Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, 200438, China
| | - Xinyi Cao
- Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China
| | - Liangqing Dong
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, 200032, China
| | - Jieyi Shi
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, 200032, China
| | - Ya Cao
- Key Laboratory of Carcinogenesis and Invasion, Chinese Ministry of Education, Xiangya Hospital and Cancer Research Institute, Xiangya School of Medicine, Central South University, Changsha, 410078, China
| | - Xiaoying Wang
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, 200032, China
| | - Jian Zhou
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, 200032, China
| | - Yinkun Liu
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, 200032, China.,Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China
| | - Lei Chen
- The International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, 200438, China
| | - Jia Fan
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, 200032, China.,Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China
| | - Guangyu Ding
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, 200032, China.
| | - Qiang Gao
- Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, 200032, China. .,Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China.
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50
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Syu GD, Dunn J, Zhu H. Developments and Applications of Functional Protein Microarrays. Mol Cell Proteomics 2020; 19:916-927. [PMID: 32303587 PMCID: PMC7261817 DOI: 10.1074/mcp.r120.001936] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 03/24/2020] [Indexed: 12/19/2022] Open
Abstract
Protein microarrays are crucial tools in the study of proteins in an unbiased, high-throughput manner, as they allow for characterization of up to thousands of individually purified proteins in parallel. The adaptability of this technology has enabled its use in a wide variety of applications, including the study of proteome-wide molecular interactions, analysis of post-translational modifications, identification of novel drug targets, and examination of pathogen-host interactions. In addition, the technology has also been shown to be useful in profiling antibody specificity, as well as in the discovery of novel biomarkers, especially for autoimmune diseases and cancers. In this review, we will summarize the developments that have been made in protein microarray technology in both in basic and translational research over the past decade. We will also introduce a novel membrane protein array, the GPCR-VirD array, and discuss the future directions of functional protein microarrays.
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Affiliation(s)
- Guan-Da Syu
- Department of Biotechnology and Bioindustry Sciences, National Cheng Kung University, Tainan 701, Taiwan R.O.C..
| | - Jessica Dunn
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
| | - Heng Zhu
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205; Center for High-Throughput Biology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205; Viral Oncology Program, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21231.
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