1
|
Qiu C, Wang X, Batson SA, Wang B, Casiano CA, Francia G, Zhang JY. A Luminex Approach to Develop an Anti-Tumor-Associated Antigen Autoantibody Panel for the Detection of Prostate Cancer in Racially/Ethnically Diverse Populations. Cancers (Basel) 2023; 15:4064. [PMID: 37627091 PMCID: PMC10452333 DOI: 10.3390/cancers15164064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/07/2023] [Accepted: 08/09/2023] [Indexed: 08/27/2023] Open
Abstract
(1) Background: Autoantibodies to tumor-associated antigens (TAAs) have emerged as promising cancer biomarkers. Luminex technology offers a powerful approach for the simultaneous detection of multiple anti-TAA autoantibodies. (2) Methods: We aimed to utilize Luminex technology to evaluate and optimize a panel of anti-TAAs autoantibodies for detecting prostate cancer (PCa), which included autoantibodies to fourteen TAAs. A total of 163 serum samples (91 PCa, 72 normal controls) were screened to determine the levels of the autoantibodies using the Luminex assay. (3) Results: Twelve autoantibodies exhibited significantly high frequencies ranging from 19.8% to 51.6% in the PCa group. Receiver operating characteristic (ROC) curve analysis revealed area under the curve (AUC) values ranging from 0.609 to 0.868 for the twelve autoantibodies individually. We further confirmed the performance of the HSP60 autoantibody by using an enzyme-linked immunosorbent assay (ELISA) in a larger sample comprising 200 PCa sera, 20 benign prostatic hyperplasia (BPH) sera, and 137 normal control sera. The results obtained from the Luminex assay were consistent with the ELISA findings. We developed a panel consisting of three autoantibodies (p16, IMP2, and HSP60) which achieved an impressive AUC of 0.910 with a sensitivity of 71.4% and a specificity of 95.8%. The panel was also evaluated in PCa patients from different races/ethnicities with the best performance observed in distinguishing the Hispanic American patients with PCa from normal controls. (4) Conclusions: We developed an anti-TAA autoantibody panel for the detection of PCa that exhibits promising performance. This panel holds significant potential as a high-throughput tool to facilitate PCa detection.
Collapse
Affiliation(s)
- Cuipeng Qiu
- Department of Biological Sciences & NIH-Sponsored Border Biomedical Research Center, The University of Texas at El Paso, El Paso, TX 79968, USA; (C.Q.); (X.W.); (S.A.B.); (B.W.)
| | - Xiao Wang
- Department of Biological Sciences & NIH-Sponsored Border Biomedical Research Center, The University of Texas at El Paso, El Paso, TX 79968, USA; (C.Q.); (X.W.); (S.A.B.); (B.W.)
| | - Serina A. Batson
- Department of Biological Sciences & NIH-Sponsored Border Biomedical Research Center, The University of Texas at El Paso, El Paso, TX 79968, USA; (C.Q.); (X.W.); (S.A.B.); (B.W.)
| | - Bofei Wang
- Department of Biological Sciences & NIH-Sponsored Border Biomedical Research Center, The University of Texas at El Paso, El Paso, TX 79968, USA; (C.Q.); (X.W.); (S.A.B.); (B.W.)
| | - Carlos A. Casiano
- Center for Health Disparities and Molecular Medicine, Department of Basic Sciences, Loma Linda University School of Medicine, Loma Linda, CA 92354, USA;
| | - Giulio Francia
- Department of Biological Sciences & NIH-Sponsored Border Biomedical Research Center, The University of Texas at El Paso, El Paso, TX 79968, USA; (C.Q.); (X.W.); (S.A.B.); (B.W.)
| | - Jian-Ying Zhang
- Department of Biological Sciences & NIH-Sponsored Border Biomedical Research Center, The University of Texas at El Paso, El Paso, TX 79968, USA; (C.Q.); (X.W.); (S.A.B.); (B.W.)
| |
Collapse
|
2
|
Geng P, Chi Y, Yuan Y, Yang M, Zhao X, Liu Z, Liu G, Liu Y, Zhu L, Wang S. Novel chimeric antigen receptor T cell-based immunotherapy: a perspective for triple-negative breast cancer. Front Cell Dev Biol 2023; 11:1158539. [PMID: 37457288 PMCID: PMC10339351 DOI: 10.3389/fcell.2023.1158539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023] Open
Abstract
Triple-negative breast cancer (TNBC) is highly aggressive and does not express estrogen receptor (ER), progesterone (PR), or human epidermal growth factor receptor 2 (HER2). It has a poor prognosis, and traditional endocrine and anti-HER2 targeted therapies have low efficacy against it. In contrast, surgery, radiotherapy, and/or systemic chemotherapy are relatively effective at controlling TNBC. The resistance of TNBC to currently available clinical therapies has had a significantly negative impact on its treatment outcomes. Hence, new therapeutic options are urgently required. Chimeric antigen receptor T cell (CAR-T) therapy is a type of immunotherapy that integrates the antigen specificity of antibodies and the tumor-killing effect of T cells. CAR-T therapy has demonstrated excellent clinical efficacy against hematological cancers. However, its efficacy against solid tumors such as TNBC is inadequate. The present review aimed to investigate various aspects of CAR-T administration as TNBC therapy. We summarized the potential therapeutic targets of CAR-T that were identified in preclinical studies and clinical trials on TNBC. We addressed the limitations of using CAR-T in the treatment of TNBC in particular and solid tumors in general and explored key strategies to overcome these impediments. Finally, we comprehensively examined the advancement of CAR-T immunotherapy as well as countermeasures that could improve its efficacy as a TNBC treatment and the prognosis of patients with this type of cancer.
Collapse
Affiliation(s)
- Peizhen Geng
- School of Clinical Medicine, Affiliated Hospital of Weifang Medical University, Weifang Medical University, Weifang, Shandong, China
| | - Yuhua Chi
- Department of General Medicine, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China
| | - Yuan Yuan
- School of Clinical Medicine, Affiliated Hospital of Weifang Medical University, Weifang Medical University, Weifang, Shandong, China
| | - Maoquan Yang
- School of Clinical Medicine, Affiliated Hospital of Weifang Medical University, Weifang Medical University, Weifang, Shandong, China
| | - Xiaohua Zhao
- Department of Thoracic Surgery, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China
| | - Zhengchun Liu
- School of Clinical Medicine, Affiliated Hospital of Weifang Medical University, Weifang Medical University, Weifang, Shandong, China
| | - Guangwei Liu
- Key Laboratory of Precision Radiation Therapy for Tumors in Weifang City, Department of Radiotherapy, School of Medical Imaging, Affiliated Hospital of Weifang Medical University, Weifang Medical University, Weifang, Shandong, China
| | - Yihui Liu
- Key Laboratory of Precision Radiation Therapy for Tumors in Weifang City, Department of Radiotherapy, School of Medical Imaging, Affiliated Hospital of Weifang Medical University, Weifang Medical University, Weifang, Shandong, China
| | - Liang Zhu
- Clinical Research Center, Department of Endocrinology and Metabolism, Affiliated Hospital of Weifang Medical University, Weifang, Shandong, China
| | - Shuai Wang
- Key Laboratory of Precision Radiation Therapy for Tumors in Weifang City, Department of Radiotherapy, School of Medical Imaging, Affiliated Hospital of Weifang Medical University, Weifang Medical University, Weifang, Shandong, China
| |
Collapse
|
3
|
Autoantibodies to PAX5, PTCH1, and GNA11 as Serological Biomarkers in the Detection of Hepatocellular Carcinoma in Hispanic Americans. Int J Mol Sci 2023; 24:ijms24043721. [PMID: 36835134 PMCID: PMC9959316 DOI: 10.3390/ijms24043721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 02/07/2023] [Accepted: 02/10/2023] [Indexed: 02/16/2023] Open
Abstract
Studies have demonstrated that autoantibodies to tumor-associated antigens (TAAs) may be used as efficient biomarkers with low-cost and highly sensitive characteristics. In this study, an enzyme-linked immunosorbent assay (ELISA) was conducted to analyze autoantibodies to paired box protein Pax-5 (PAX5), protein patched homolog 1 (PTCH1), and guanine nucleotide-binding protein subunit alpha-11 (GNA11) in sera from Hispanic Americans including hepatocellular carcinoma (HCC) patients, patients with liver cirrhosis (LC), patients with chronic hepatitis (CH), as well as normal controls. Meanwhile, 33 serial sera from eight HCC patients before and after diagnosis were used to explore the potential of these three autoantibodies as early biomarkers. In addition, an independent non-Hispanic cohort was used to evaluate the specificity of these three autoantibodies. In the Hispanic cohort, at the 95.0% specificity for healthy controls, 52.0%, 44.0%, and 44.0% of HCC patients showed significantly elevated levels of autoantibodies to PAX5, PTCH1, and GNA11, respectively. Among patients with LC, the frequencies for autoantibodies to PAX5, PTCH1, and GNA11 were 32.1%, 35.7%, and 25.0%, respectively. The area under the ROC curves (AUCs) of autoantibodies to PAX5, PTCH1, and GNA11 for identifying HCC from healthy controls were 0.908, 0.924, and 0.913, respectively. When these three autoantibodies were combined as a panel, the sensitivity could be improved to 68%. The prevalence of PAX5, PTCH1, and GNA11 autoantibodies has already occurred in 62.5%, 62.5%, or 75.0% of patients before clinical diagnosis, respectively. In the non-Hispanic cohort, autoantibodies to PTCH1 showed no significant difference; however, autoantibodies to PAX5, PTCH1, and GNA11 showed potential value as biomarkers for early detection of HCC in the Hispanic population and they may monitor the transition of patients with high-risk (LC, CH) to HCC. Using a panel of the three anti-TAA autoantibodies may enhance the detection of HCC.
Collapse
|
4
|
Yang R, Han Y, Yi W, Long Q. Autoantibodies as biomarkers for breast cancer diagnosis and prognosis. Front Immunol 2022; 13:1035402. [PMID: 36451832 PMCID: PMC9701846 DOI: 10.3389/fimmu.2022.1035402] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 10/28/2022] [Indexed: 10/07/2023] Open
Abstract
Breast cancer is the most common cancer in women worldwide and is a substantial public health problem. Screening for breast cancer mainly relies on mammography, which leads to false positives and missed diagnoses and is especially non-sensitive for patients with small tumors and dense breasts. The prognosis of breast cancer is mainly classified by tumor, node, and metastasis (TNM) staging, but this method does not consider the molecular characteristics of the tumor. As the product of the immune response to tumor-associated antigens, autoantibodies can be detected in peripheral blood and can be used as noninvasive, presymptomatic, and low-cost biomarkers. Therefore, autoantibodies can provide a possible supplementary method for breast cancer screening and prognosis classification. This article introduces the methods used to detect peripheral blood autoantibodies and the research progress in the screening and prognosis of breast cancer made in recent years to provide a potential direction for the examination and treatment of breast cancer.
Collapse
Affiliation(s)
| | | | | | - Qian Long
- Department of General Surgery, The Second Xiangya Hospital of Central South University, Changsha, China
| |
Collapse
|
5
|
Kathrikolly T, Nair SN, Mathew A, Saxena PPU, Nair S. Can serum autoantibodies be a potential early detection biomarker for breast cancer in women? A diagnostic test accuracy review and meta-analysis. Syst Rev 2022; 11:215. [PMID: 36210467 PMCID: PMC9549667 DOI: 10.1186/s13643-022-02088-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 09/28/2022] [Indexed: 12/01/2022] Open
Abstract
BACKGROUND The increasing incidence of breast cancer necessitates the need to explore alternate screening strategies that circumvent the setbacks of conventional techniques especially among population that report earlier age at diagnosis. Serum autoantibodies is one such potential area of interest. However, their ubiquitous presence across cancer types limits its applicability to any one specific type of cancer. This review was therefore carried out to explore and consolidate available evidence on autoantibodies for early detection of breast cancer and to identify those that demonstrated a higher sensitivity. METHODS A diagnostic test accuracy (DTA) review was carried out to ascertain serum autoantibodies that could be used for early detection of breast cancer among women. All relevant articles that investigated the role of autoantibodies in early detection of breast cancer were included for the review. MEDLINE, Scopus, ProQuest, Ovid SP, and Cochrane Library were searched extensively for eligible studies. Quality of the included studies was assessed using Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool. RevMan 5.3 was used for exploratory and MetaDTA 2019 for hierarchical analyses. The review helped identify the most frequently investigated autoantibodies and a meta-analysis further consolidated the findings. RESULTS A total of 53 articles were included for the final analysis that reported over a 100 autoantibodies that were studied for early detection of breast cancer in women. P53, MUC1, HER2, HSP60, P16, Cyclin B1, and c-Myc were the most frequently investigated autoantibodies. Of these P53, MUC1, HER2, and HSP60 exhibited higher summary sensitivity measures. While the individual pooled sensitivity estimates ranged between 10 and 56%, the panel sensitivity values reported across studies were higher with an estimated range of 60-87%. CONCLUSION Findings from the review indicate a higher sensitivity for an autoantibody panel in comparison to individual assays. A panel comprising of P53, MUC1, HER2, and HSP60 autoantibodies has the potential to be investigated as an early detection biomarker for breast cancer.
Collapse
Affiliation(s)
- Thejas Kathrikolly
- Department of Community Oncology, Sri Shankara Cancer Hospital and Research Centre, Bengaluru, India.,Department of Community Medicine, Kasturba Medical College, Manipal Academy of Higher Education (MAHE), Manipal, India
| | - Sreekumaran N Nair
- Department of Biostatistics, Jawaharlal Institute of Postgraduate Medical Education & Research (JIPMER), Puducherry, India
| | - Aju Mathew
- Department of Oncology, MOSC Medical College Kolenchery, Kerala, India.,Department of Internal Medicine, University of Kentucky Markey Cancer Center, Lexington, USA
| | - Prakash P U Saxena
- Department of Radiation Oncology, Kasturba Medical College, Mangalore, India
| | - Suma Nair
- Department of Community Medicine, Kasturba Medical College, Manipal Academy of Higher Education (MAHE), Manipal, India. .,School of Public Health, DY Patil Deemed to be University, Navi Mumbai, India.
| |
Collapse
|
6
|
Luo M, Wu S, Ma Y, Liang H, Luo Y, Gu W, Fan L, Hao Y, Li H, Xing L. Evaluating a Panel of Autoantibodies Against Tumor-Associated Antigens in Human Osteosarcoma. Front Genet 2022; 13:872253. [PMID: 35547257 PMCID: PMC9081566 DOI: 10.3389/fgene.2022.872253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 03/23/2022] [Indexed: 11/28/2022] Open
Abstract
Background: The aim of this study was to identify a panel of candidate autoantibodies against tumor-associated antigens in the detection of osteosarcoma (OS) so as to provide a theoretical basis for constructing a non-invasive serological diagnosis method in early immunodiagnosis of OS. Methods: The serological proteome analysis (SERPA) approach was used to select candidate anti-TAA autoantibodies. Then, indirect enzyme-linked immunosorbent assay (ELISA) was used to verify the expression levels of eight candidate autoantibodies in the serum of 51 OS cases, 28 osteochondroma (OC), and 51 normal human sera (NHS). The rank-sum test was used to compare the content of eight autoantibodies in the sera of three groups. The diagnostic value of each indicator for OS was analyzed by an ROC curve. Differential autoantibodies between OS and NHS were screened. Then, a binary logistic regression model was used to establish a prediction logistical regression model. Results: Through ELISA, the expression levels of seven autoantibodies (ENO1, GAPDH, HSP27, HSP60, PDLIM1, STMN1, and TPI1) in OS patients were identified higher than those in healthy patients (p < 0.05). By establishing a binary logistic regression predictive model, the optimal panel including three anti-TAAs (ENO1, GAPDH, and TPI1) autoantibodies was screened out. The sensitivity, specificity, Youden index, accuracy, and AUC of diagnosis of OS were 70.59%, 86.27%, 0.5686, 78.43%, and 0.798, respectively. Conclusion: The results proved that through establishing a predictive model, an optimal panel of autoantibodies could help detect OS from OC or NHS at an early stage, which could be used as a promising and powerful tool in clinical practice.
Collapse
Affiliation(s)
- Manli Luo
- Luoyang Orthopedic Hospital of Henan Province (Orthopedic Hospital of Henan Province), Luoyang, China.,Henan Provincial Rehabilitation Hospital, Luoyang, China.,Henan University of Chinese Medicine, Zhengzhou, China
| | - Songmei Wu
- Luoyang Orthopedic Hospital of Henan Province (Orthopedic Hospital of Henan Province), Luoyang, China.,Henan University of Chinese Medicine, Zhengzhou, China
| | - Yan Ma
- Luoyang Orthopedic Hospital of Henan Province (Orthopedic Hospital of Henan Province), Luoyang, China
| | - Hong Liang
- Luoyang Orthopedic Hospital of Henan Province (Orthopedic Hospital of Henan Province), Luoyang, China
| | - Yage Luo
- Luoyang Orthopedic Hospital of Henan Province (Orthopedic Hospital of Henan Province), Luoyang, China
| | - Wentao Gu
- Luoyang Orthopedic Hospital of Henan Province (Orthopedic Hospital of Henan Province), Luoyang, China
| | - Lijuan Fan
- Luoyang Orthopedic Hospital of Henan Province (Orthopedic Hospital of Henan Province), Luoyang, China.,Henan University of Chinese Medicine, Zhengzhou, China
| | - Yang Hao
- Luoyang Orthopedic Hospital of Henan Province (Orthopedic Hospital of Henan Province), Luoyang, China.,Henan University of Chinese Medicine, Zhengzhou, China
| | - Haiting Li
- Luoyang Orthopedic Hospital of Henan Province (Orthopedic Hospital of Henan Province), Luoyang, China.,Henan University of Chinese Medicine, Zhengzhou, China
| | - Linbo Xing
- Luoyang Orthopedic Hospital of Henan Province (Orthopedic Hospital of Henan Province), Luoyang, China.,Henan University of Chinese Medicine, Zhengzhou, China
| |
Collapse
|
7
|
Zhang X, Li J, Wang Y, Liu M, Liu F, Zhang X, Pei L, Wang T, Jiang D, Wang X, Zhang J, Dai L. A Diagnostic Model With IgM Autoantibodies and Carcinoembryonic Antigen for Early Detection of Lung Adenocarcinoma. Front Immunol 2022; 12:728853. [PMID: 35140701 PMCID: PMC8818794 DOI: 10.3389/fimmu.2021.728853] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 12/28/2021] [Indexed: 12/19/2022] Open
Abstract
Immunoglobulin M (IgM) autoantibodies, as the early appearing antibodies in humoral immunity when stimulated by antigens, might be excellent biomarkers for the early detection of lung cancer (LC). We aimed to develop a multi-analyte integrative model combining IgM autoantibodies and a traditional tumor biomarker that could be a valuable and powerful auxiliary diagnostic tool and might improve the accuracy of early detection of lung adenocarcinoma (LUAD). A customized protein array based on cancer driver genes was constructed and applied in the discovery cohort consisting of 68 LUAD patients and 68 normal controls (NCs); 31 differentially expressed IgM autoantibodies were identified. The top 5 candidate IgM autoantibodies [based on the area under the receiver operating characteristic curve (AUC) ranking], namely, TSHR, ERBB2, survivin, PIK3CA, and JAK2, were validated in the validation cohort using enzyme-linked immunosorbent assay (ELISA), which included 147 LUAD samples, 72 lung squamous cell carcinoma (LUSC) samples, 44 small cell lung carcinoma (SCLC) samples, and 147 NCs. These indicators presented diagnostic capacity for LUAD, with AUCs of 0.599, 0.613, 0.579, 0.601, and 0.633, respectively (p < 0.05). However, none of them showed a significant difference between the SCLC and NC groups, and only the IgM autoantibody against JAK2 showed a higher expression in LUSC than in NC (p = 0.046). Through logistic regression analysis, with the five IgM autoantibodies and carcinoembryonic antigen (CEA), one diagnostic model was constructed for LUAD. The model yielded an AUC of 0.827 (sensitivity = 56.63%, specificity = 93.98%). The diagnostic efficiency was superior to that of either CEA (AUC = 0.692) or IgM autoantibodies alone (AUC = 0.698). Notably, the accuracy of this model in early-stage LUAD reached 83.02%. In conclusion, we discovered and identified five novel IgM indicators and developed a multi-analyte model combining IgM autoantibodies and CEA, which could be a valuable and powerful auxiliary diagnostic tool and might improve the accuracy of early detection of LUAD.
Collapse
Affiliation(s)
- Xue Zhang
- Henan Institute of Medical and Pharmaceutical Sciences & School of Basic Medical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, China
| | - Jiaqi Li
- Henan Institute of Medical and Pharmaceutical Sciences & School of Basic Medical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, China
| | - Yulin Wang
- Henan Institute of Medical and Pharmaceutical Sciences & School of Basic Medical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, China
| | - Man Liu
- Henan Institute of Medical and Pharmaceutical Sciences & School of Basic Medical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, China
| | - Fenghui Liu
- Department of Respiratory and Sleep Medicine in the First Affiliated Hospital, Zhengzhou University, Zhengzhou, China
| | - Xiuzhi Zhang
- Department of Pathology, Henan Medical College, Zhengzhou, China
| | - Lu Pei
- Department of Clinical Laboratory, Zhengzhou Hospital of Traditional Chinese Medicine, Zhengzhou, China
| | - Tingting Wang
- Department of Clinical Laboratory, Fuwai Central China Cardiovascular Hospital, Zhengzhou, China
| | - Di Jiang
- Henan Institute of Medical and Pharmaceutical Sciences & School of Basic Medical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, China
| | - Xiao Wang
- Henan Institute of Medical and Pharmaceutical Sciences & School of Basic Medical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, China
| | - Jianying Zhang
- Henan Institute of Medical and Pharmaceutical Sciences & School of Basic Medical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, China
| | - Liping Dai
- Henan Institute of Medical and Pharmaceutical Sciences & School of Basic Medical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China
- Henan Key Laboratory of Tumor Epidemiology & Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, China
- *Correspondence: Liping Dai,
| |
Collapse
|
8
|
Luo R, Zheng C, Song W, Tan Q, Shi Y, Han X. High-throughput and multi-phases identification of autoantibodies in diagnosing early-stage breast cancer and subtypes. Cancer Sci 2021; 113:770-783. [PMID: 34843149 PMCID: PMC8819333 DOI: 10.1111/cas.15227] [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: 07/07/2021] [Revised: 11/12/2021] [Accepted: 11/21/2021] [Indexed: 12/12/2022] Open
Abstract
Autoantibodies (AAbs) targeted tumor‐associated antigens (TAAs) have the potential for early detection of breast cancer. Here, 574 early‐stage breast cancer (ES‐BC) patients containing 4 subtypes (Luminal A, Luminal B, HER2+, TN), 126 benign breast disease (BBD) patients, and 199 normal healthy controls (NHC) were separated into three‐phases to discover, verify, and validate AAbs. In discovery phase using high‐throughput protein microarray, 37 AAbs with sensitivity of 31.25%‐86.25% and specificity over 73% in ES‐BC, and 40 AAbs with different positive rates between subtypes were identified as candidates. In verification phase, 18 AAbs were significantly increased compared with the Control (BBD and NHC) in focused array. Ten out of 18 AAbs exhibited a significant difference between subtypes (P < .05). In ELISA validation phase, 5 novel AAbs (anti‐KJ901215, ‐FAM49B, ‐HYI, ‐GARS, ‐CRLF3) exhibited significantly higher levels in ES‐BC compared with BBD/NHC (P < .05). The sensitivities of individual AAb and a 5‐AAbs panel were 20.41%‐28.57% and 38.78%, whereas the specificities were over 90% and 85.94%. Simultaneously, 4 AAbs except anti‐GARS differed significantly between TN and non‐TN subtype (P < .05). We constructed 3 random forest classifier models based on AAbs to discriminant ES‐BC from Control or BBD, and to discern TN subtype, which yielded an area under the curve of 0.870, 0.860, and 0.875, respectively. Biological interaction analysis revealed 4 TAAs, except for KJ901215, that were associated with well known proteins of BC. This study discovered and stepwise validated 5 novel AAbs with the potential to diagnose ES‐BC and discern TN subtype, indicating easy‐to‐detect and minimally invasive diagnostic value of serum AAbs ahead of biopsy for future application.
Collapse
Affiliation(s)
- Rongrong Luo
- Department of Clinical Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Cuiling Zheng
- Department of Clinical Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Wenya Song
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Qiaoyun Tan
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yuankai Shi
- Department of Medical Oncology, Beijing Key Laboratory of Clinical Study on Anticancer Molecular Targeted Drugs, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 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 & PD Investigation for Innovative Drugs, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| |
Collapse
|
9
|
Wu J, Wang P, Han Z, Li T, Yi C, Qiu C, Yang Q, Sun G, Dai L, Shi J, Wang K, Ye H. A novel immunodiagnosis panel for hepatocellular carcinoma based on bioinformatics and the autoantibody-antigen system. Cancer Sci 2021; 113:411-422. [PMID: 34821436 PMCID: PMC8819288 DOI: 10.1111/cas.15217] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 10/26/2021] [Accepted: 11/08/2021] [Indexed: 12/11/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is a malignancy with a dismal survival rate. The novel autoantibodies panel may provide new insights for the diagnosis of HCC. Biomarkers screened by two methods (bioinformatics and the antigen‐antibody system) were taken as candidate tumor‐associated antigens (TAAs). Enzyme‐linked immunosorbent assay was used to detect the corresponding autoantibodies in 888 samples of verification and validation cohorts. The verification cohort was used to verify the autoantibodies. Samples in the validation cohort were randomly divided into a train set and a test set with the ratio of 6:4. A diagnostic model was established by support vector machines within the train set. The test set further verified the model. Eleven TAAs were selected (AAGAB, C17orf75, CDC37L1, DUSP6, EID3, PDIA2, RGS20, PCNA, TAF7L, TBC1D13, and ZIC2). The titer of six autoantibodies (PCNA, AAGAB, CDC37L1, TAF7L, DUSP6, and ZIC2) had a significant difference in any of the pairwise comparisons among the HCC, liver cirrhosis, and normal control groups. The titer of these autoantibodies had an increasing tendency. Finally, an optimum diagnostic model was constructed with the six autoantibodies. The AUCs were 0.826 in the train set and 0.773 in the test set. The area under the curve (AUC) of this panel for diagnosing early HCC was 0.889. The diagnostic ability of the panel reduced with the progress of HCC. The positive rate of the panel in diagnosing alpha‐fetoprotein (AFP)‐negative patients was 75.6%. For early HCC, the sensitivity of the combination of AFP with the panel was 90.9% and superior to 53.2% of AFP alone. The novel immunodiagnosis panel combining AFP may be a new approach for the diagnosis of HCC, especially for early‐HCC cases.
Collapse
Affiliation(s)
- Jinyu Wu
- College of Public Health, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Peng Wang
- College of Public Health, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Zhuo Han
- College of Public Health, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Tiandong Li
- College of Public Health, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Chuncheng Yi
- College of Public Health, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Cuipeng Qiu
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.,Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
| | - Qian Yang
- College of Public Health, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Guiying Sun
- College of Public Health, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| | - Liping Dai
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.,Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
| | - Jianxiang Shi
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.,Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
| | - Keyan Wang
- Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China.,Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China
| | - Hua Ye
- College of Public Health, Zhengzhou University, Zhengzhou, China.,Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China
| |
Collapse
|
10
|
Qiu C, Wang B, Wang P, Wang X, Ma Y, Dai L, Shi J, Wang K, Sun G, Ye H, Zhang J. Identification of novel autoantibody signatures and evaluation of a panel of autoantibodies in breast cancer. Cancer Sci 2021; 112:3388-3400. [PMID: 34115421 PMCID: PMC8353906 DOI: 10.1111/cas.15021] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 06/06/2021] [Accepted: 06/08/2021] [Indexed: 12/24/2022] Open
Abstract
Tumor-associated autoantibodies (TAAb) could be serological tumor markers. This study aims to discover novel TAAb signatures for breast cancer (BC) detection. The protein microarray was used to identify candidate TAAb, which were further validated in 1197 sera from BC, benign breast diseases (BD), and healthy controls (HC) by enzyme-linked immunosorbent assay. In addition, 319 preoperative and postoperative sera were evaluated. A panel was determined using four different classifiers. Twelve TAAb were identified with frequencies of 15.8%-59.2%; their levels were significantly decreased in postoperative sera compared to those in preoperative sera (P < .05). A panel with six TAAb was developed and evaluated. The area under the curve (AUC) was 0.879 (74.3% sensitivity, 91.9% specificity) and 0.865 (69.7% sensitivity, 91.7% specificity) for distinguishing BC from HC in the training set and test set, respectively. The panel had an AUC of .884 (71.2% sensitivity, 90.5% specificity) for discriminating BC from BD. For identifying BC from all controls (HC+BD), the AUC was .916 (78.9% sensitivity, 90.2% specificity). The AUC of the panel was .920 and .934 for distinguishing stage I-II and age < 50 BC from HC, respectively. These identified TAAb have the potential to provide a non-invasive approach to detect BC.
Collapse
Affiliation(s)
- Cuipeng Qiu
- BGI College & Henan Academy of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory of Tumor Epidemiology, Zhengzhou, China.,Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Bofei Wang
- State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory of Tumor Epidemiology, Zhengzhou, China
| | - Peng Wang
- State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory of Tumor Epidemiology, Zhengzhou, China.,Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiao Wang
- BGI College & Henan Academy of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory of Tumor Epidemiology, Zhengzhou, China
| | - Yan Ma
- State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory of Tumor Epidemiology, Zhengzhou, China.,Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Liping Dai
- BGI College & Henan Academy of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory of Tumor Epidemiology, Zhengzhou, China
| | - Jianxiang Shi
- BGI College & Henan Academy of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory of Tumor Epidemiology, Zhengzhou, China
| | - Keyan Wang
- BGI College & Henan Academy of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory of Tumor Epidemiology, Zhengzhou, China
| | - Guiying Sun
- State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory of Tumor Epidemiology, Zhengzhou, China.,Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Hua Ye
- State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory of Tumor Epidemiology, Zhengzhou, China.,Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Jianying Zhang
- BGI College & Henan Academy of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China.,State Key Laboratory of Esophageal Cancer Prevention and Treatment and Henan Key Laboratory of Tumor Epidemiology, Zhengzhou, China.,Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| |
Collapse
|
11
|
Oh Y, Kwon OS, Min SS, Shin YB, Oh MK, Kim M. Olfactory Detection of Toluene by Detection Rats for Potential Screening of Lung Cancer. SENSORS 2021; 21:s21092967. [PMID: 33922694 PMCID: PMC8123061 DOI: 10.3390/s21092967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 04/21/2021] [Accepted: 04/22/2021] [Indexed: 12/02/2022]
Abstract
Early detection is critical to successfully eradicating a variety of cancers, so the development of a new cancer primary screening system is essential. Herein, we report an animal nose sensor system for the potential primary screening of lung cancer. To establish this, we developed an odor discrimination training device based on operant conditioning paradigms for detection of toluene, an odor indicator component of lung cancer. The rats (N = 15) were trained to jump onto a floating ledge in response to toluene-spiked breath samples. Twelve rats among 15 trained rats reached performance criterion in 12 consecutive successful tests within a given set, or over 12 sets, with a success rate of over 90%. Through a total of 1934 tests, the trained rats (N = 3) showed excellent performance for toluene detection with 82% accuracy, 83% sensitivity, 81% specificity, 80% positive predictive value (PPV) and 83% negative predictive value (NPV). The animals also acquired considerable performance for odor discrimination even in rigorous tests, validating odor specificity. Since environmental and long-term stability are important factors that can influence the sensing results, the performance of the trained rats was studied under specified temperature (20, 25, and 30 °C) and humidity (30%, 45%, and 60% RH) conditions, and monitored over a period of 45 days. At given conditions of temperature and humidity, the animal sensors showed an average accuracy within a deviation range of ±10%, indicating the excellent environmental stability of the detection rats. Surprisingly, the trained rats did not differ in retention of last odor discrimination when tested 45 days after training, denoting that the rats’ memory for trained odor is still available over a long period of time. When taken together, these results indicate that our odor discrimination training system can be useful for non-invasive breath testing and potential primary screening of lung cancer.
Collapse
Affiliation(s)
- Yunkwang Oh
- Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea; (Y.O.); (Y.-B.S.)
- Department of Chemical and Biological Engineering, Korea University, 145 Anam-ro, Sungbuk-gu, Seoul 02841, Korea
| | - Oh-Seok Kwon
- Infectious Disease Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea;
| | - Sun-Seek Min
- Department of Physiology and Biophysics, Eulji University School of Medicine, 77 Gyeryong-ro, Jung-gu, Daejeon 34824, Korea;
| | - Yong-Beom Shin
- Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea; (Y.O.); (Y.-B.S.)
- KRIBB School, Korea University of Science and Technology (UST), 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, Korea
| | - Min-Kyu Oh
- Department of Chemical and Biological Engineering, Korea University, 145 Anam-ro, Sungbuk-gu, Seoul 02841, Korea
- Correspondence: (M.-K.O.); (M.K.); Tel.: +82-2-3290-3308 (M.-K.O.); +82-42-8798447 (M.K.); Fax: +82-2-926-6102 (M.-K.O.); +82-42-879-8594 (M.K.)
| | - Moonil Kim
- Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea; (Y.O.); (Y.-B.S.)
- KRIBB School, Korea University of Science and Technology (UST), 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, Korea
- Correspondence: (M.-K.O.); (M.K.); Tel.: +82-2-3290-3308 (M.-K.O.); +82-42-8798447 (M.K.); Fax: +82-2-926-6102 (M.-K.O.); +82-42-879-8594 (M.K.)
| |
Collapse
|
12
|
Anti-glycan antibodies: roles in human disease. Biochem J 2021; 478:1485-1509. [PMID: 33881487 DOI: 10.1042/bcj20200610] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 03/23/2021] [Accepted: 03/26/2021] [Indexed: 02/07/2023]
Abstract
Carbohydrate-binding antibodies play diverse and critical roles in human health. Endogenous carbohydrate-binding antibodies that recognize bacterial, fungal, and other microbial carbohydrates prevent systemic infections and help maintain microbiome homeostasis. Anti-glycan antibodies can have both beneficial and detrimental effects. For example, alloantibodies to ABO blood group carbohydrates can help reduce the spread of some infectious diseases, but they also impose limitations for blood transfusions. Antibodies that recognize self-glycans can contribute to autoimmune diseases, such as Guillain-Barre syndrome. In addition to endogenous antibodies that arise through natural processes, a variety of vaccines induce anti-glycan antibodies as a primary mechanism of protection. Some examples of approved carbohydrate-based vaccines that have had a major impact on human health are against pneumococcus, Haemophilus influeanza type b, and Neisseria meningitidis. Monoclonal antibodies specifically targeting pathogen associated or tumor associated carbohydrate antigens (TACAs) are used clinically for both diagnostic and therapeutic purposes. This review aims to highlight some of the well-studied and critically important applications of anti-carbohydrate antibodies.
Collapse
|
13
|
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.
Collapse
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
| |
Collapse
|
14
|
de Jonge H, Iamele L, Maggi M, Pessino G, Scotti C. Anti-Cancer Auto-Antibodies: Roles, Applications and Open Issues. Cancers (Basel) 2021; 13:813. [PMID: 33672007 PMCID: PMC7919283 DOI: 10.3390/cancers13040813] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 02/05/2021] [Accepted: 02/10/2021] [Indexed: 12/11/2022] Open
Abstract
Auto-antibodies are classically associated with autoimmune diseases, where they are an integral part of diagnostic panels. However, recent evidence is accumulating on the presence of auto-antibodies against single or selected panels of auto-antigens in many types of cancer. Auto-antibodies might initially represent an epiphenomenon derived from the inflammatory environment induced by the tumor. However, their effect on tumor evolution can be crucial, as is discussed in this paper. It has been demonstrated that some of these auto-antibodies can be used for early detection and cancer staging, as well as for monitoring of cancer regression during treatment and follow up. Interestingly, certain auto-antibodies were found to promote cancer progression and metastasis, while others contribute to the body's defense against it. Moreover, auto-antibodies are of a polyclonal nature, which means that often several antibodies are involved in the response to a single tumor antigen. Dissection of these antibody specificities is now possible, allowing their identification at the genetic, structural, and epitope levels. In this review, we report the evidence available on the presence of auto-antibodies in the main cancer types and discuss some of the open issues that still need to be addressed by the research community.
Collapse
Affiliation(s)
| | | | | | | | - Claudia Scotti
- Unit of Immunology and General Pathology, Department of Molecular Medicine, University of Pavia, 27100 Pavia, Italy; (H.d.J.); (L.I.); (M.M.); (G.P.)
| |
Collapse
|
15
|
Yang SH, Liu CT, Hong CQ, Huang ZY, Wang HZ, Wei LF, Lin YW, Guo HP, Peng YH, Xu YW. Autoantibodies against p53, MMP-7, and Hsp70 as Potential Biomarkers for Detection of Nonmelanoma Skin Cancers. DISEASE MARKERS 2021; 2021:5592693. [PMID: 34336006 PMCID: PMC8289574 DOI: 10.1155/2021/5592693] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 05/31/2021] [Indexed: 02/05/2023]
Abstract
Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are two predominant histological types of nonmelanoma skin cancer (NMSC), lacking effective early diagnostic markers. In this study, we assessed the diagnostic value of autoantibodies against p53, MMP-7, and Hsp70 in skin SCC and BCC. ELISA was performed to detect levels of autoantibodies in sera from 101 NMSC patients and 102 normal controls, who were recruited from the Cancer Hospital of Shantou University Medical College. A receiver operator characteristic curve was used to evaluate the diagnostic value. The serum levels of autoantibodies against p53, MMP-7, and Hsp70 were higher in NMSCs than those in the normal controls (all P < 0.01). The AUC of the three-autoantibody panel was 0.841 (95% CI: 0.788-0.894) with the sensitivity and specificity of 60.40% and 91.20% when differentiating NMSCs from normal controls. Furthermore, measurement of this panel could differentiate early-stage skin cancer patients from normal controls (AUC: 0.851; 95% CI: 0.793-0.908). Data from Oncomine showed that the level of p53 mRNA was elevated in BCC (P < 0.05), and the Hsp70 mRNA was upregulated in SCC (P < 0.001). This serum three-autoantibody panel might function in assisting the early diagnosis of NMSC.
Collapse
Affiliation(s)
- Shi-Han Yang
- Department of Dermatology and Venereology, Affiliated Shantou Hospital of Sun Yat-sen University, 114 Waima Road, Shantou 515041, China
| | - Can-Tong Liu
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, 7 Raoping Road, Shantou 515041, China
- Precision Medicine Research Center, Shantou University Medical College, 22 Xinling Road, Shantou 515041, China
| | - Chao-Qun Hong
- Department of Oncological Laboratory Research, The Cancer Hospital of Shantou University Medical College, 7 Raoping Road, Shantou 515041, China
| | - Ze-Yuan Huang
- Department of Dermatology and Venereology, Affiliated Shantou Hospital of Sun Yat-sen University, 114 Waima Road, Shantou 515041, China
| | - Huan-Zhu Wang
- Department of Dermatology and Venereology, Affiliated Shantou Hospital of Sun Yat-sen University, 114 Waima Road, Shantou 515041, China
| | - Lai-Feng Wei
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, 7 Raoping Road, Shantou 515041, China
- Precision Medicine Research Center, Shantou University Medical College, 22 Xinling Road, Shantou 515041, China
| | - Yi-Wei Lin
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, 7 Raoping Road, Shantou 515041, China
- Precision Medicine Research Center, Shantou University Medical College, 22 Xinling Road, Shantou 515041, China
| | - Hai-Peng Guo
- Department of Head and Neck Surgery, The Cancer Hospital of Shantou University Medical College, 7 Raoping Road, Shantou 515041, China
| | - Yu-Hui Peng
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, 7 Raoping Road, Shantou 515041, China
- Precision Medicine Research Center, Shantou University Medical College, 22 Xinling Road, Shantou 515041, China
- Guangdong Esophageal Cancer Research Institute, Shantou University Medical College, 22 Xinling Road, Shantou 515041, China
| | - Yi-Wei Xu
- Department of Clinical Laboratory Medicine, The Cancer Hospital of Shantou University Medical College, 7 Raoping Road, Shantou 515041, China
- Precision Medicine Research Center, Shantou University Medical College, 22 Xinling Road, Shantou 515041, China
- Guangdong Esophageal Cancer Research Institute, Shantou University Medical College, 22 Xinling Road, Shantou 515041, China
| |
Collapse
|
16
|
Discovery and Validation of Serum Autoantibodies Against Tumor-Associated Antigens as Biomarkers in Gastric Adenocarcinoma Based on the Focused Protein Arrays. Clin Transl Gastroenterol 2020; 12:e00284. [PMID: 33346593 PMCID: PMC7752677 DOI: 10.14309/ctg.0000000000000284] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 11/03/2020] [Indexed: 12/27/2022] Open
Abstract
INTRODUCTION: Previous studies have demonstrated that autoantibodies against tumor-associated antigens (TAAs) in patients with cancer can be used as sensitive immunodiagnostic biomarkers for the detection of cancer. Most of these TAAs are involved in the tumorigenesis pathway. Cancer driver genes with intragenic mutations can promote tumorigenesis. This study aims to identify autoantibodies against TAAs encoded by cancer driver genes in sera as potential immunodiagnostic biomarkers for gastric adenocarcinoma (GAC). METHODS: Protein arrays based on cancer driver genes were customized for screening candidate TAAs in 100 GAC sera and 50 normal control (NC) sera. Autoantibodies against candidate TAAs were assessed by enzyme-linked immunosorbent assay in both training group (205 GAC sera and 205 NC sera) and independent validation group (126 GAC sera and 126 NC sera). Moreover, the immunodiagnostic models were respectively established and validated in the training group and validation group. RESULTS: A panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti–serine/arginine-rich splicing factor 2, and anti-SMARCB1 was selected by the Fisher linear discriminant analysis model with an areas under receiver operating characteristic curve (AUC) of 0.928 (95% confidence interval [CI]: 0.888–0.967) in the training cohort and an AUC of 0.885 (95% CI: 0.852–0.918) in the validation cohort. Besides, the panel with 5 autoantibodies including anti-TP53, anti-COPB1, anti-GNAS, anti-PBRM1, and anti-ACVR1B which were selected by the binary logistic regression model showed an AUC of 0.885 (95% CI: 0.852–0.919) in the training cohort and 0.884 (95% CI: 0.842–0.925) in the validation cohort. DISCUSSION: Two panels which were selected in this study could boost the detection of anti-TAA autoantibodies in sera as biomarkers for the detection of GAC.
Collapse
|