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Yang H, Lin Z, Wu B, Xu J, Tao SC, Zhou S. Deciphering disease through glycan codes: leveraging lectin microarrays for clinical insights. Acta Biochim Biophys Sin (Shanghai) 2024; 56:1145-1155. [PMID: 39099413 DOI: 10.3724/abbs.2024123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/06/2024] Open
Abstract
Glycosylation, a crucial posttranslational modification, plays a significant role in numerous physiological and pathological processes. Lectin microarrays, which leverage the high specificity of lectins for sugar binding, are ideally suited for profiling the glycan spectra of diverse and complex biological samples. In this review, we explore the evolution of lectin detection technologies, as well as the applications and challenges of lectin microarrays in analyzing the glycome profiles of various clinical samples, including serum, saliva, tissues, sperm, and urine. This review not only emphasizes significant advancements in the high-throughput analysis of polysaccharides but also provides insight into the potential of lectin microarrays for diagnosing and managing diseases such as tumors, autoimmune diseases, and chronic inflammation. We aim to provide a clear, concise, and comprehensive overview of the use of lectin microarrays in clinical settings, thereby assisting researchers in conducting clinical studies in glycobiology.
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Affiliation(s)
- Hangzhou Yang
- Department of General Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Zihan Lin
- Department of General Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Bo Wu
- Department of General Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Jun Xu
- Department of Orthopaedic Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Sheng-Ce Tao
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
| | - Shumin Zhou
- Institute of Microsurgery on Extremities, Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai 200233, China
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Li X, Xiao Y, Chen X, Zhu Y, Du H, Shu J, Yu H, Ren X, Zhang F, Dang J, Zhang C, Su S, Li Z. Machine Learning Reveals Serum Glycopatterns as Potential Biomarkers for the Diagnosis of Nonalcoholic Fatty Liver Disease (NAFLD). J Proteome Res 2024. [PMID: 38698681 DOI: 10.1021/acs.jproteome.4c00204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Nonalcoholic fatty liver disease (NAFLD) has emerged as the predominant chronic liver condition globally, and underdiagnosis is common, particularly in mild cases, attributed to the asymptomatic nature and traditional ultrasonography's limited sensitivity to detect early-stage steatosis. Consequently, patients may experience progressive liver pathology. The objective of this research is to ascertain the efficacy of serum glycan glycopatterns as a potential diagnostic biomarker, with a particular focus on the disease's early stages. We collected a total of 170 serum samples from volunteers with mild-NAFLD (Mild), severe-NAFLD (Severe), and non-NAFLD (None). Examination via lectin microarrays has uncovered pronounced disparities in serum glycopatterns identified by 19 distinct lectins. Following this, we employed four distinct machine learning algorithms to categorize the None, Mild, and Severe groups, drawing on the alterations observed in serum glycopatterns. The gradient boosting decision tree (GBDT) algorithm outperformed other models in diagnostic accuracy within the validation set, achieving an accuracy rate of 95% in differentiating the None group from the Mild group. Our research indicates that employing lectin microarrays to identify alterations in serum glycopatterns, when integrated with advanced machine learning algorithms, could constitute a promising approach for the diagnosis of NAFLD, with a special emphasis on its early detection.
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Affiliation(s)
- Xiaocheng Li
- Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Yaqing Xiao
- Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Xinhuan Chen
- Department of Health Science Center, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - Yayun Zhu
- Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Haoqi Du
- Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi'an 710069, China
- School of Medicine, Faculty of Life Sciences and Medicine, Northwest University, Xi'an 710069, China
| | - Jian Shu
- Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi'an 710069, China
- School of Medicine, Faculty of Life Sciences and Medicine, Northwest University, Xi'an 710069, China
| | - Hanjie Yu
- Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Xiameng Ren
- Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Fan Zhang
- Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Jing Dang
- Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Chen Zhang
- Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi'an 710069, China
| | - Shi Su
- Department of Health Science Center, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - Zheng Li
- Laboratory for Functional Glycomics, College of Life Sciences, Northwest University, Xi'an 710069, China
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Hu W, Ge W, Xia P, Chen Y, Du J, Hu G, Wu Z, Zhang X, Yang C, Jiang J, Yang S, Xia J. Diagnostic Potential of Serum Glycome Analysis in Lung Cancer: A Glycopattern Study. J Proteome Res 2024; 23:500-509. [PMID: 38097511 DOI: 10.1021/acs.jproteome.3c00645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Abstract
Lung cancer is the leading cause of cancer-related death, with high morbidity and mortality rates due to the lack of reliable methods for diagnosing lung cancer at an early stage. Low-dose computed tomography can help detect abnormal areas in the lungs, but only 16% of cases are diagnosed early. Tests for lung cancer markers are often employed to determine genetic expression or mutations in lung carcinogenesis. Serum glycome analysis is a promising new method for early lung cancer diagnosis as glycopatterns exhibit significant differences in lung cancer patients. In this study, we employed a solid-phase chemoenzymatic method to systematically compare glycopatterns in benign cases, adenocarcinoma before and after surgery, and advanced stages of adenocarcinoma. Our findings indicate that serum high-mannose levels are elevated in both benign cases and adenocarcinoma, while complex N-glycans, including fucose and 2,6-linked sialic acid, are downregulated in the serum. Subsequently, we developed an algorithm that utilizes 16 altered N-glycans, 7 upregulated and 9 downregulated, to generate a score based on their intensity. This score can predict the stages of cancer progression in patients through glycan characterization. This methodology offers a potential means of diagnosing lung cancer through serum glycome analysis.
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Affiliation(s)
- Wenhua Hu
- Center for Clinical Mass Spectrometry, College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu 215123, China
| | - Wei Ge
- Center for Clinical Mass Spectrometry, College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu 215123, China
- Department of Respiratory Medicine, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, Jiangsu 215123, China
| | - Peng Xia
- Laboratory Medicine Center, Department of Clinical Laboratory, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang 310014, China
| | - Yan Chen
- Center for Clinical Mass Spectrometry, College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu 215123, China
| | - Jing Du
- Laboratory Medicine Center, Department of Clinical Laboratory, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang 310014, China
| | - Guangxu Hu
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Zhen Wu
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Xumin Zhang
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Chuanlai Yang
- Health Examination Center, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215004, China
| | - Junhong Jiang
- Department of Respiratory Medicine, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, Jiangsu 215123, China
| | - Shuang Yang
- Center for Clinical Mass Spectrometry, College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu 215123, China
- Health Examination Center, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu 215004, China
| | - Jun Xia
- Laboratory Medicine Center, Department of Clinical Laboratory, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang 310014, China
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Li C, Xiao J, Wu S, Liu L, Zeng X, Zhao Q, Zhang Z. Clinical application of serum-based proteomics technology in human tumor research. Anal Biochem 2023; 663:115031. [PMID: 36580994 DOI: 10.1016/j.ab.2022.115031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 12/20/2022] [Accepted: 12/24/2022] [Indexed: 12/27/2022]
Abstract
The rapid development of proteomics technology in the past decades has led to further human understanding of tumor research, and in some ways, the technology plays a very important supporting role in the early detection of tumors. Human serum has been shown to contain a variety of proteins closely related to life activities, and the dynamic change in proteins can often reflect the physiological and pathological conditions of the body. Serum has the advantage of easy extraction, so the application of proteomics technology in serum has become a hot spot and frontier area for the study of malignant tumors. However, there are still many difficulties in the standardized use of proteomic technologies, which inevitably limit the clinical application of proteomic technologies due to the heterogeneity of human proteins leading to incomplete whole proteome populations, in addition to most serum protein markers being now not highly specific in aiding the early detection of tumors. Nevertheless, further development of proteomics technologies will greatly increase our understanding of tumor biology and help discover more new tumor biomarkers with specificity that will enable medical technology.
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Affiliation(s)
- Chen Li
- Department of Pathology, The First Affiliated Hospital of University of South China, Hunan, Hengyang, 421001, Hunan Province, China
| | - Juan Xiao
- Department of Otorhinolaryngology, The Second Affiliated Hospital of University of South China, Hunan, Hengyang, 421001, Hunan Province, China
| | - Shihua Wu
- Department of Pathology, The Second Hospital of Shaoyang College, Hunan, Shaoyang, 422000, Hunan Province, China
| | - Lu Liu
- Department of Pathology, The First Affiliated Hospital of University of South China, Hunan, Hengyang, 421001, Hunan Province, China
| | - Xuemei Zeng
- Cancer Research Institute of Hengyang Medical College, University of South China, Key Laboratory of Cancer Cellular and Molecular Pathology in Hunan Province, Hunan, Hengyang, 421001, China
| | - Qiang Zhao
- Department of Pathology, The First Affiliated Hospital of University of South China, Hunan, Hengyang, 421001, Hunan Province, China.
| | - Zhiwei Zhang
- Department of Pathology, The First Affiliated Hospital of University of South China, Hunan, Hengyang, 421001, Hunan Province, China; Cancer Research Institute of Hengyang Medical College, University of South China, Key Laboratory of Cancer Cellular and Molecular Pathology in Hunan Province, Hunan, Hengyang, 421001, China.
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Yang H, Tian Z. Sialic acid linkage-specific quantitative N-glycoproteomics using selective alkylamidation and multiplex TMT-labeling. Anal Chim Acta 2022; 1230:340391. [DOI: 10.1016/j.aca.2022.340391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 09/07/2022] [Accepted: 09/10/2022] [Indexed: 11/25/2022]
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Zhao Y, He L, Huang B, Zhang W, Hu A, Li B, Liao S, Wang N. Identification of a novel DNA aptamer that selectively targets lung cancer serum. RSC Adv 2021; 11:33759-33769. [PMID: 35497520 PMCID: PMC9042271 DOI: 10.1039/d1ra06233f] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/09/2021] [Indexed: 11/21/2022] Open
Abstract
Lung cancer is the leading cause of cancer-related deaths worldwide. Early diagnosis and treatment is critical to improving the 5 year survival rate of lung cancer. The identification of new options for early-stage diagnosis and therapy of lung cancer still represents a crucial challenge. Therefore, a new diagnostic method is urgently needed. In this study, we used a new modified SELEX, called serum-SELEX, to isolate aptamers that can specifically bind lung cancer serum, without any prior knowledge of their target. Among the obtained candidate aptamer sequences, Ap-LC-19 was identified as the optimal aptamer probe with the lowest dissociation constant (K d) value of 15 ± 8.6 nM and higher affinity assessed by qPCR. Furthermore, this molecule could be a suitable aptamer for lung cancer serum and could be used as a recognition element in aptamer-based biosensors for efficient early diagnosis of lung cancer or as an innovative tool for targeted therapy. In addition, we performed MALDI-TOF MS followed by secondary peptide sequencing MS analysis for the identification of the aptamer targeted proteins. CLEC3B could be useful biomarkers for early detection of lung cancer and in monitoring its evolution.
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Affiliation(s)
- Yunwang Zhao
- The First Hospital of Qinhuangdao Qinhuangdao 066000 China +86-0335-590-8439
| | - Lei He
- Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen 518055 China
| | - Baihai Huang
- Key Laboratory of Molecular and Cellular Systems Biology, College of Life Sciences, Tianjin Normal University Tianjin 300387 China
| | - Weidong Zhang
- The First Hospital of Qinhuangdao Qinhuangdao 066000 China +86-0335-590-8439
| | - Ailing Hu
- The First Hospital of Qinhuangdao Qinhuangdao 066000 China +86-0335-590-8439
| | - Baolin Li
- The First Hospital of Qinhuangdao Qinhuangdao 066000 China +86-0335-590-8439
| | - Shiqi Liao
- College of Life Sciences, Lanzhou University Lanzhou 730000 China
| | - Na Wang
- The First Hospital of Qinhuangdao Qinhuangdao 066000 China +86-0335-590-8439
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