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Vinayak S, Cecil DL, Disis ML. Vaccines for breast cancer prevention: Are we there yet? Mol Aspects Med 2024; 98:101292. [PMID: 38991631 DOI: 10.1016/j.mam.2024.101292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 06/10/2024] [Accepted: 06/30/2024] [Indexed: 07/13/2024]
Affiliation(s)
- Shaveta Vinayak
- University of Washington, Division of Oncology, Seattle, WA, USA; Fred Hutchinson Cancer Center, Seattle, WA, USA.
| | - Denise L Cecil
- University of Washington, Division of Oncology, Seattle, WA, USA
| | - Mary L Disis
- University of Washington, Division of Oncology, Seattle, WA, USA; Fred Hutchinson Cancer Center, Seattle, WA, USA
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2
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Javaid T, Bhattarai M, Venkataraghavan A, Held M, Faik A. Specific protein interactions between rice members of the GT43 and GT47 families form various central cores of putative xylan synthase complexes. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024; 118:856-878. [PMID: 38261531 DOI: 10.1111/tpj.16640] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 01/04/2024] [Accepted: 01/08/2024] [Indexed: 01/25/2024]
Abstract
Members of the glycosyltransferase (GT)43 and GT47 families have been associated with heteroxylan synthesis in both dicots and monocots and are thought to assemble into central cores of putative xylan synthase complexes (XSCs). Currently, it is unknown whether protein-protein interactions within these central cores are specific, how many such complexes exist, and whether these complexes are functionally redundant. Here, we used gene association network and co-expression approaches in rice to identify four OsGT43s and four OsGT47s that assemble into different GT43/GT47 complexes. Using two independent methods, we showed that (i) these GTs assemble into at least six unique complexes through specific protein-protein interactions and (ii) the proteins interact directly in vitro. Confocal microscopy showed that, when alone, all OsGT43s were retained in the endoplasmic reticulum (ER), while all OsGT47s were localized in the Golgi. co-expression of OsGT43s and OsGT47s displayed complexes that form in the ER but accumulate in Golgi. ER-to-Golgi trafficking appears to require interactions between OsGT43s and OsGT47s. Comparison of the central cores of the three putative rice OsXSCs to wheat, asparagus, and Arabidopsis XSCs, showed great variation in GT43/GT47 combinations, which makes the identification of orthologous central cores between grasses and dicots challenging. However, the emerging picture is that all central cores from these species seem to have at least one member of the IRX10/IRX10-L clade in the GT47 family in common, suggesting greater functional importance for this family in xylan synthesis. Our findings provide a new framework for future investigation of heteroxylan biosynthesis and function in monocots.
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Affiliation(s)
- Tasleem Javaid
- Department of Environmental and Plant Biology, Ohio University, Athens, Ohio, 45701, USA
| | - Matrika Bhattarai
- Department of Environmental and Plant Biology, Ohio University, Athens, Ohio, 45701, USA
| | | | - Michael Held
- Department of Chemistry and Biochemistry, Ohio University, Athens, Ohio, 45701, USA
| | - Ahmed Faik
- Department of Environmental and Plant Biology, Ohio University, Athens, Ohio, 45701, USA
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3
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Abdul Wahab MR, Palaniyandi T, Viswanathan S, Baskar G, Surendran H, Gangadharan SGD, Sugumaran A, Sivaji A, Kaliamoorthy S, Kumarasamy S. Biomarker-specific biosensors revolutionise breast cancer diagnosis. Clin Chim Acta 2024; 555:117792. [PMID: 38266968 DOI: 10.1016/j.cca.2024.117792] [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: 12/08/2023] [Revised: 01/19/2024] [Accepted: 01/19/2024] [Indexed: 01/26/2024]
Abstract
Breast cancer is the most common cancer among women across the globe. In order to treat breast cancer successfully, it is crucial to conduct a comprehensive assessment of the condition during its initial stages. Although mammogram screening has long been a common method of breast cancer screening, high rates of type I error and type II error results as well as radiation exposure have always been of concern. The outgrowth cancer mortality rate is primarily due to delayed diagnosis, which occurs most frequently in a metastatic III or IV stage, resulting in a poor prognosis after therapy. Traditional detection techniques require identifying carcinogenic properties of cells, such as DNA or RNA alterations, conformational changes and overexpression of certain proteins, and cell shape, which are referred to as biomarkers or analytes. These procedures are complex, long-drawn-out, and expensive. Biosensors have recently acquired appeal as low-cost, simple, and super sensitive detection methods for analysis. The biosensor approach requires the existence of biomarkers in the sample. Thus, the development of novel molecular markers for diverse forms of cancer is a rising complementary affair. These biosensor devices offer two major advantages: (1) a tiny amount of blood collected from the patient is sufficient for analysis, and (2) it could help clinicians swiftly select and decide on the best therapy routine for the individual. This review will include updates on prospective cancer markers and biosensors in cancer diagnosis, as well as the associated detection limitations, with a focus on biosensor development for marker detection.
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Affiliation(s)
| | - Thirunavukkarasu Palaniyandi
- Department of Biotechnology, Dr. M.G.R. Educational and Research Institute, Chennai, India; Department of Anatomy, Biomedical Research Unit and Laboratory Animal Centre, Saveetha Dental College and Hospital, SIMATS, Saveetha University, Chennai, India.
| | - Sandhiya Viswanathan
- Department of Biotechnology, Dr. M.G.R. Educational and Research Institute, Chennai, India
| | - Gomathy Baskar
- Department of Biotechnology, Dr. M.G.R. Educational and Research Institute, Chennai, India
| | - Hemapreethi Surendran
- Department of Biotechnology, Dr. M.G.R. Educational and Research Institute, Chennai, India
| | - S G D Gangadharan
- Department of Medical Oncology, Madras Medical College, R. G. G. G. H., Chennai, Tamil Nadu, India
| | - Abimanyu Sugumaran
- Department of Pharmaceutical Sciences, Assam University, (A Central University), Silchar, Assam, India
| | - Asha Sivaji
- Department of Biochemistry, DKM College for Women, Vellore, India
| | - Senthilkumar Kaliamoorthy
- Department of Electronics and Communication Engineering, Dr. M.G.R Educational and Research Institute, Chennai, Tamil Nadu, India
| | - Saravanan Kumarasamy
- Department of Electrical and Electronics Engineering, Dr. M.G.R Educational and Research Institute, Chennai, Tamil Nadu, India
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4
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Wani S, Humaira, Farooq I, Ali S, Rehman MU, Arafah A. Proteomic profiling and its applications in cancer research. Proteomics 2023. [DOI: 10.1016/b978-0-323-95072-5.00015-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
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5
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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.
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Affiliation(s)
| | | | | | - Qian Long
- Department of General Surgery, The Second Xiangya Hospital of Central South University, Changsha, China
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6
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Khan H, Shah MR, Barek J, Malik MI. Cancer biomarkers and their biosensors: A comprehensive review. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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7
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Cao Z, Delfino K, Tiwari V, Wang X, Hannan A, Zaidi F, McClintock A, Robinson K, Zhu Y, Gao J, Cao D, Rao K. AKR1B10 as a Potential Novel Serum Biomarker for Breast Cancer: A Pilot Study. Front Oncol 2022; 12:727505. [PMID: 35280770 PMCID: PMC8908957 DOI: 10.3389/fonc.2022.727505] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 01/17/2022] [Indexed: 12/11/2022] Open
Abstract
Background Aldo-keto reductase 1B10 (AKR1B10) is a secretory protein that is upregulated in breast cancer. Objective This case-controlled pilot study evaluated the serum level of AKR1B10 in healthy women and patients with a localized or metastatic breast cancer. Methods AKR1B10 levels were measured by ELISA and IHC in several patient cohorts. Results Our data showed that serum AKR1B10 was significantly elevated in patients with localized (6.72 ± 0.92 ng/ml) or metastatic (7.79 ± 1.13 ng/ml) disease compared to cancer-free healthy women (1.69 ± 0.17 ng/ml) (p<0.001); the serum AKR1B10 was correlated with its expression in tumor tissues, but not with the tumor burden, molecular subtypes or histological stages. After surgical removal of primary tumors, the serum AKR1B10 was rapidly decreased within 3 days and plateaued at a level similar to that of healthy controls in most patients. ROC curve analysis suggested the optimal diagnostic cut-off value of serum AKR1B10 at 3.456 ng/ml with AUC 0.9045 ± 0.0337 (95% CI 0.8384 - 0.9706), sensitivity 84.75% (95% CI 73.01% to 92.78%), and specificity 93.88% (95% CI 83.13% to 98.72%). Conclusions These data indicate the potential value of serum AKR1B10 as a biomarker of breast cancer.
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Affiliation(s)
- Zhe Cao
- Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China.,Department of Medical Microbiology, Immunology and Cell Biology, Simmons Cancer Institute, Southern Illinois University School of Medicine, Springfield, IL, United States
| | - Kristin Delfino
- Center for Clinical Research, Southern Illinois University School of Medicine, Springfield, IL, United States
| | - Vivek Tiwari
- Dartmouth Hitchcock Medical Center, Lebanon, NH, United States
| | - Xin Wang
- Department of Medical Microbiology, Immunology and Cell Biology, Simmons Cancer Institute, Southern Illinois University School of Medicine, Springfield, IL, United States
| | - Abdul Hannan
- Division of Hematology/Medical Oncology, Department of Internal Medicine and Simmons Cancer Institute, Southern Illinois University School of Medicine, Springfield, IL, United States
| | - Fawwad Zaidi
- Division of Hematology/Medical Oncology, Department of Internal Medicine and Simmons Cancer Institute, Southern Illinois University School of Medicine, Springfield, IL, United States
| | - Andrew McClintock
- Southern Illinois University School of Medicine, Springfield, IL, United States
| | - Kathy Robinson
- Dartmouth Hitchcock Medical Center, Lebanon, NH, United States
| | - Yun Zhu
- Department of Medical Microbiology, Immunology and Cell Biology, Simmons Cancer Institute, Southern Illinois University School of Medicine, Springfield, IL, United States
| | - John Gao
- Department of Pathology, Memorial Medical Center, Springfield, IL, United States
| | - Deliang Cao
- Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China.,Department of Medical Microbiology, Immunology and Cell Biology, Simmons Cancer Institute, Southern Illinois University School of Medicine, Springfield, IL, United States
| | - Krishna Rao
- Dartmouth Hitchcock Medical Center, Lebanon, NH, United States
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8
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Current advances in prognostic and diagnostic biomarkers for solid cancers: Detection techniques and future challenges. Biomed Pharmacother 2021; 146:112488. [PMID: 34894516 DOI: 10.1016/j.biopha.2021.112488] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 11/19/2021] [Accepted: 11/30/2021] [Indexed: 12/20/2022] Open
Abstract
Solid cancers are one of the leading causes of cancer related deaths, characterized by rapid growth of tumour, and local and distant metastases. Current advances on multimodality care have substantially improved local control and metastasis-free survival of patients by resection of primary tumour. The major concern in disease prognosis is the timely detection of resectable or metastatic tumour, thus reinforcing the need for identification of biomarkers for premalignant lesions of solid cancer. This ultimately improves the outcome for the patients. Therefore, the purpose of this review is to update the recent advancements on prognostic and diagnostic biomarkers to enhance early detection of common solid cancers including, breast, lung, colorectal, prostate and stomach cancer. We also provide an insight into Food and Drug Administration (FDA)-approved solid cancers biomarkers; various conventional techniques used for detection of prognostic and diagnostic biomarkers and discuss approaches to turn challenges in this field into opportunities.
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9
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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.
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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
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10
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Lázár J, Kovács A, Tornyi I, Takács L, Kurucz I. Detection of leucine-rich alpha-2-glycoprotein 1-containing immunocomplexes in the plasma of lung cancer patients with epitope-specific mAbs. Cancer Biomark 2021; 34:113-122. [PMID: 34744074 DOI: 10.3233/cbm-210164] [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: 11/15/2022]
Abstract
BACKGROUND Lung cancer is the leading cause of cancer-related deaths worldwide. With the expectation of improved survival, tremendous efforts and resources have been invested in the discovery of specific biomarkers for early detection of the disease. Several investigators have reported the presence of cancer-associated autoantibodies in the plasma or serum of lung cancer patients. Previously, we used a monoclonal-antibody proteomics technology platform for the discovery of novel lung cancer-associated proteins. OBJECTIVE The identification of specific protein epitopes associated with various cancers is a promising method in biomarker discovery. Here, in a preliminary study, we aimed to detect autoantibody-leucine-rich alpha-2-glycoprotein 1 (LRG1) immunocomplexes using epitope-specific monoclonal antibodies (mAbs). METHODS We performed sandwich ELISA assays using the LRG1 epitope-specific capture mAbs, Bsi0352 and Bsi0392, and an IgG-specific polyclonal antibody coupled to a reporter system as the detection reagent. We tested the plasma of lung-cancer patients and apparently healthy controls. RESULTS Depending on the epitope specificity of the capture monoclonal mAb, we were either unable to distinguish the control from LC-groups or showed a higher level of LRG1 and IgG autoantibody containing immunocomplexes in the plasma of non-small cell lung cancer and small cell lung cancer subgroups of lung cancer patients than in the plasma of control subjects. CONCLUSIONS Our findings underline the importance of protein epitope-specific antibody targeted approaches in biomarker research, as this may increase the accuracy of previously described tests, which will need further validation in large clinical cohorts.
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Affiliation(s)
- József Lázár
- Biosystems International Kft., Debrecen, Hungary
| | | | - Ilona Tornyi
- Biosystems International Kft., Debrecen, Hungary.,Department of Human Genetics, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - László Takács
- Biosystems International Kft., Debrecen, Hungary.,Department of Human Genetics, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
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11
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Wu HJ, Chu PY. Recent Discoveries of Macromolecule- and Cell-Based Biomarkers and Therapeutic Implications in Breast Cancer. Int J Mol Sci 2021; 22:ijms22020636. [PMID: 33435254 PMCID: PMC7827149 DOI: 10.3390/ijms22020636] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 12/31/2020] [Accepted: 01/08/2021] [Indexed: 12/13/2022] Open
Abstract
Breast cancer is the most commonly diagnosed cancer type and the leading cause of cancer-related mortality in women worldwide. Breast cancer is fairly heterogeneous and reveals six molecular subtypes: luminal A, luminal B, HER2+, basal-like subtype (ER−, PR−, and HER2−), normal breast-like, and claudin-low. Breast cancer screening and early diagnosis play critical roles in improving therapeutic outcomes and prognosis. Mammography is currently the main commercially available detection method for breast cancer; however, it has numerous limitations. Therefore, reliable noninvasive diagnostic and prognostic biomarkers are required. Biomarkers used in cancer range from macromolecules, such as DNA, RNA, and proteins, to whole cells. Biomarkers for cancer risk, diagnosis, proliferation, metastasis, drug resistance, and prognosis have been identified in breast cancer. In addition, there is currently a greater demand for personalized or precise treatments; moreover, the identification of novel biomarkers to further the development of new drugs is urgently needed. In this review, we summarize and focus on the recent discoveries of promising macromolecules and cell-based biomarkers for the diagnosis and prognosis of breast cancer and provide implications for therapeutic strategies.
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Affiliation(s)
- Hsing-Ju Wu
- Department of Biology, National Changhua University of Education, Changhua 500, Taiwan;
- Research Assistant Center, Show Chwan Memorial Hospital, Changhua 500, Taiwan
- Department of Medical Research, Chang Bing Show Chwan Memorial Hospital, Lukang Town, Changhua County 505, Taiwan
| | - Pei-Yi Chu
- School of Medicine, College of Medicine, Fu Jen Catholic University, New Taipei City 231, Taiwan
- Department of Pathology, Show Chwan Memorial Hospital, No. 542, Sec. 1 Chung-Shan Rd., Changhua 500, Taiwan
- Department of Health Food, Chung Chou University of Science and Technology, Changhua 510, Taiwan
- National Institute of Cancer Research, National Health Research Institutes, Tainan 704, Taiwan
- Correspondence: ; Tel.: +886-975-611-855; Fax: +886-4-7227-116
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12
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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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Li J, Guan X, Fan Z, Ching LM, Li Y, Wang X, Cao WM, Liu DX. Non-Invasive Biomarkers for Early Detection of Breast Cancer. Cancers (Basel) 2020; 12:E2767. [PMID: 32992445 PMCID: PMC7601650 DOI: 10.3390/cancers12102767] [Citation(s) in RCA: 85] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 09/23/2020] [Accepted: 09/24/2020] [Indexed: 12/24/2022] Open
Abstract
Breast cancer is the most common cancer in women worldwide. Accurate early diagnosis of breast cancer is critical in the management of the disease. Although mammogram screening has been widely used for breast cancer screening, high false-positive and false-negative rates and radiation from mammography have always been a concern. Over the last 20 years, the emergence of "omics" strategies has resulted in significant advances in the search for non-invasive biomarkers for breast cancer diagnosis at an early stage. Circulating carcinoma antigens, circulating tumor cells, circulating cell-free tumor nucleic acids (DNA or RNA), circulating microRNAs, and circulating extracellular vesicles in the peripheral blood, nipple aspirate fluid, sweat, urine, and tears, as well as volatile organic compounds in the breath, have emerged as potential non-invasive diagnostic biomarkers to supplement current clinical approaches to earlier detection of breast cancer. In this review, we summarize the current progress of research in these areas.
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Affiliation(s)
- Jiawei Li
- The Centre for Biomedical and Chemical Sciences, School of Science, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland 1010, New Zealand; (J.L.); (X.G.); (Y.L.)
| | - Xin Guan
- The Centre for Biomedical and Chemical Sciences, School of Science, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland 1010, New Zealand; (J.L.); (X.G.); (Y.L.)
- Department of Breast Surgery, the First Hospital of Jilin University, Jilin University, Changchun 130021, China;
| | - Zhimin Fan
- Department of Breast Surgery, the First Hospital of Jilin University, Jilin University, Changchun 130021, China;
| | - Lai-Ming Ching
- Auckland Cancer Society Research Centre, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand;
| | - Yan Li
- The Centre for Biomedical and Chemical Sciences, School of Science, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland 1010, New Zealand; (J.L.); (X.G.); (Y.L.)
| | - Xiaojia Wang
- Department of Breast Medical Oncology, Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital & Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China;
| | - Wen-Ming Cao
- Department of Breast Medical Oncology, Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital & Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China;
| | - Dong-Xu Liu
- The Centre for Biomedical and Chemical Sciences, School of Science, Faculty of Health and Environmental Sciences, Auckland University of Technology, Auckland 1010, New Zealand; (J.L.); (X.G.); (Y.L.)
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Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer. Cancers (Basel) 2020; 12:cancers12092428. [PMID: 32867043 PMCID: PMC7564506 DOI: 10.3390/cancers12092428] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 08/23/2020] [Accepted: 08/25/2020] [Indexed: 12/12/2022] Open
Abstract
Simple Summary The traditional approach in identifying cancer related protein biomarkers has focused on evaluation of a single peptide/protein in tissue or circulation. At best, this approach has had limited success for clinical applications, since multiple pathological tumor pathways may be involved during initiation or progression of cancer which diminishes the significance of a single candidate protein/peptide. Emerging sensitive proteomic based technologies like liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics can provide a platform for evaluating serial serum or plasma samples to interrogate secreted products of tumor–host interactions, thereby revealing a more “complete” repertoire of biological variables encompassing heterogeneous tumor biology. However, several challenges need to be met for successful application of serum/plasma based proteomics. These include uniform pre-analyte processing of specimens, sensitive and specific proteomic analytical platforms and adequate attention to study design during discovery phase followed by validation of discovery-level signatures for prognostic, predictive, and diagnostic cancer biomarker applications. Abstract Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.
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Why the Gold Standard Approach by Mammography Demands Extension by Multiomics? Application of Liquid Biopsy miRNA Profiles to Breast Cancer Disease Management. Int J Mol Sci 2019; 20:ijms20122878. [PMID: 31200461 PMCID: PMC6627787 DOI: 10.3390/ijms20122878] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 06/07/2019] [Accepted: 06/11/2019] [Indexed: 02/06/2023] Open
Abstract
In the global context, the epidemic of breast cancer (BC) is evident for the early 21st century. Evidence shows that national mammography screening programs have sufficiently reduced BC related mortality. Therefore, the great utility of the mammography-based screening is not an issue. However, both false positive and false negative BC diagnosis, excessive biopsies, and irradiation linked to mammography application, as well as sub-optimal mammography-based screening, such as in the case of high-dense breast tissue in young females, altogether increase awareness among the experts regarding the limitations of mammography-based screening. Severe concerns regarding the mammography as the “golden standard” approach demanding complementary tools to cover the evident deficits led the authors to present innovative strategies, which would sufficiently improve the quality of the BC management and services to the patient. Contextually, this article provides insights into mammography deficits and current clinical data demonstrating the great potential of non-invasive diagnostic tools utilizing circulating miRNA profiles as an adjunct to conventional mammography for the population screening and personalization of BC management.
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Wang D. Systematic Glycolytic Enzyme Activity Analysis from Human Serum with PEP Technology. Methods Mol Biol 2019; 1871:69-81. [PMID: 30276732 DOI: 10.1007/978-1-4939-8814-3_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
A functional proteomics technology was used to systematically monitor metabolic enzyme activities from resolved serum proteins produced by a modified 2-D gel separation and subsequent Protein Elution Plate, a method collectively called PEP. Both qualitative and quantitative differences in the metabolic enzyme activity could be detected between cancer patient and control group, providing excellent biomarker candidates for cancer diagnosis and drug development. This technology has a wide range of applications; it can be used for rapid functional protein purification and characterization as well as drug target identification and validation. The ability for the PEP technology to efficiently separate and recover functional proteins makes it useful for the analysis of any proteins and its variants; this is especially advantageous for enzyme families with large number of enzymes such as protein kinases, phosphatases, proteases, and metabolic enzymes.
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Affiliation(s)
- David Wang
- University of Iowa School of Medicine, Iowa City, IA, USA.
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Núñez C. Blood-based protein biomarkers in breast cancer. Clin Chim Acta 2018; 490:113-127. [PMID: 30597138 DOI: 10.1016/j.cca.2018.12.028] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Revised: 12/26/2018] [Accepted: 12/27/2018] [Indexed: 02/07/2023]
Abstract
Breast cancer (BCa) is a significant healthcare problem on women worldwide. Thus, early detection is very important to reduce mortality. Furthermore, better BCa prognosis could improve selection of patients eligible for adjuvant therapy. New markers for early diagnosis, accurate prognosis and prediction of response to treatment are necessary to improve BCa care. The present review summarizes important aspects of the potential usefulness of modern technologies, strategies, and scientific findings in proteomic research for discovery of breast cancer-associated blood-based protein biomarkers in the clinic.
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Affiliation(s)
- Cristina Núñez
- Research Unit, Hospital Universitario Lucus Augusti (HULA), Servizo Galego de Saúde (SERGAS), 27002 Lugo, Spain.
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Henderson MC, Silver M, Tran Q, Letsios EE, Mulpuri R, Reese DE, Lourenco AP, LaBaer J, Anderson KS, Alpers J, Costantini C, Rohatgi N, Ali H, Baker K, Northfelt DW, Ghosh K, Grobmyer SR, Polen W, Wolf JK. A Noninvasive Blood-based Combinatorial Proteomic Biomarker Assay to Detect Breast Cancer in Women over age 50 with BI-RADS 3, 4, or 5 Assessment. Clin Cancer Res 2018; 25:142-149. [DOI: 10.1158/1078-0432.ccr-18-0843] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Revised: 05/22/2018] [Accepted: 08/30/2018] [Indexed: 11/16/2022]
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Henderson MC, Silver M, Borman S, Tran Q, Letsios E, Mulpuri R, Reese DE, Wolf JK. A Combinatorial Proteomic Biomarker Assay to Detect Ovarian Cancer in Women. BIOMARKERS IN CANCER 2018; 10:1179299X18756646. [PMID: 35237085 PMCID: PMC8842374 DOI: 10.1177/1179299x18756646] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Accepted: 01/10/2018] [Indexed: 11/16/2022]
Abstract
Ovarian cancer is often fatal and incidence in the general population is low, underscoring the necessity (and the challenges) for advancements in screening and early detection. The goal of this study was to design a serum-based biomarker panel and corresponding multivariate algorithm that can be used to accurately detect ovarian cancer. A combinatorial protein biomarker assay (CPBA) that uses CA125, HE4, and 3 tumor-associated autoantibodies resulted in an area under the curve of 0.98. The CPBA Ov algorithm was trained using subjects who were suspected to have gynecological cancer and were scheduled for surgery. As a surgical rule-out test, the clinical performance achieves 100% sensitivity and 83.7% specificity. Although sample size (n = 60) is a limiting factor, the CPBA Ov algorithm performed better than either CA-125 alone or the Risk of Ovarian Malignancy Algorithm.
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Yu X, Song L, Petritis B, Bian X, Wang H, Viloria J, Park J, Bui H, Li H, Wang J, Liu L, Yang L, Duan H, McMurray DN, Achkar JM, Magee M, Qiu J, LaBaer J. Multiplexed Nucleic Acid Programmable Protein Arrays. Theranostics 2017; 7:4057-4070. [PMID: 29109798 PMCID: PMC5667425 DOI: 10.7150/thno.20151] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2017] [Accepted: 08/03/2017] [Indexed: 12/13/2022] Open
Abstract
Rationale: Cell-free protein microarrays display naturally-folded proteins based on just-in-time in situ synthesis, and have made important contributions to basic and translational research. However, the risk of spot-to-spot cross-talk from protein diffusion during expression has limited the feature density of these arrays. Methods: In this work, we developed the Multiplexed Nucleic Acid Programmable Protein Array (M-NAPPA), which significantly increases the number of displayed proteins by multiplexing as many as five different gene plasmids within a printed spot. Results: Even when proteins of different sizes were displayed within the same feature, they were readily detected using protein-specific antibodies. Protein-protein interactions and serological antibody assays using human viral proteome microarrays demonstrated that comparable hits were detected by M-NAPPA and non-multiplexed NAPPA arrays. An ultra-high density proteome microarray displaying > 16k proteins on a single microscope slide was produced by combining M-NAPPA with a photolithography-based silicon nano-well platform. Finally, four new tuberculosis-related antigens in guinea pigs vaccinated with Bacillus Calmette-Guerin (BCG) were identified with M-NAPPA and validated with ELISA. Conclusion: All data demonstrate that multiplexing features on a protein microarray offer a cost-effective fabrication approach and have the potential to facilitate high throughput translational research.
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Affiliation(s)
- Xiaobo Yu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (PHOENIX Center, Beijing), Beijing Institute of Radiation Medicine, Beijing, 102206, China
| | - Lusheng Song
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Brianne Petritis
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Xiaofang Bian
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Haoyu Wang
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Jennifer Viloria
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Jin Park
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Hoang Bui
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Han Li
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Jie Wang
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Lei Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (PHOENIX Center, Beijing), Beijing Institute of Radiation Medicine, Beijing, 102206, China
| | - Liuhui Yang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (PHOENIX Center, Beijing), Beijing Institute of Radiation Medicine, Beijing, 102206, China
| | - Hu Duan
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (PHOENIX Center, Beijing), Beijing Institute of Radiation Medicine, Beijing, 102206, China
| | - David N. McMurray
- Department of Microbial Pathogenesis and Immunology, College of Medicine, Texas A&M Health Science Center, College Station, TX 77843, USA
| | - Jacqueline M. Achkar
- Department of Medicine, Albert Einstein College of Medicine, NY 10461, USA; Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Mitch Magee
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Ji Qiu
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Joshua LaBaer
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
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Huang R, Chen Z, He L, He N, Xi Z, Li Z, Deng Y, Zeng X. Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application. Theranostics 2017; 7:3559-3572. [PMID: 28912895 PMCID: PMC5596443 DOI: 10.7150/thno.20797] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2017] [Accepted: 07/12/2017] [Indexed: 12/13/2022] Open
Abstract
There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.
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Affiliation(s)
- Rongrong Huang
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Zhongsi Chen
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Lei He
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
| | - Nongyue He
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
- Economical Forest Cultivation and Utilization of 2011 Collaborative Innovation Center in Hunan Province, Hunan Key Laboratory of Green Chemistry and Application of Biological Nanotechnology; Hunan University of Technology, Zhuzhou 412007, China
| | - Zhijiang Xi
- School of Medicine, Yangtze University, Jingzhou 434023, China
| | - Zhiyang Li
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
- Department of Clinical Laboratory, the Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Yan Deng
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China
- Economical Forest Cultivation and Utilization of 2011 Collaborative Innovation Center in Hunan Province, Hunan Key Laboratory of Green Chemistry and Application of Biological Nanotechnology; Hunan University of Technology, Zhuzhou 412007, China
| | - Xin Zeng
- Nanjing Maternity and Child Health Medical Institute, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing 210004, China
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A Noninvasive Blood-based Combinatorial Proteomic Biomarker Assay to Detect Breast Cancer in Women Under the Age of 50 Years. Clin Breast Cancer 2017. [PMID: 28624156 DOI: 10.1016/j.clbc.2017.05.004] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Despite significant advances in breast imaging, the ability to detect breast cancer (BC) remains a challenge. To address the unmet needs of the current BC detection paradigm, 2 prospective clinical trials were conducted to develop a blood-based combinatorial proteomic biomarker assay (Videssa Breast) to accurately detect BC and reduce false positives (FPs) from suspicious imaging findings. PATIENTS AND METHODS Provista-001 and Provista-002 (cohort one) enrolled Breast Imaging Reporting and Data System 3 or 4 women aged under 50 years. Serum was evaluated for 11 serum protein biomarkers and 33 tumor-associated autoantibodies. Individual biomarker expression, demographics, and clinical characteristics data from Provista-001 were combined to develop a logistic regression model to detect BC. The performance was tested using Provista-002 cohort one (validation set). RESULTS The training model had a sensitivity and specificity of 92.3% and 85.3% (BC prevalence, 7.7%), respectively. In the validation set (BC prevalence, 2.9%), the sensitivity and specificity were 66.7% and 81.5%, respectively. The negative predictive value was high in both sets (99.3% and 98.8%, respectively). Videssa Breast performance in the combined training and validation set was 99.1% negative predictive value, 87.5% sensitivity, 83.8% specificity, and 25.2% positive predictive value (BC prevalence, 5.87%). Overall, imaging resulted in 341 participants receiving follow-up procedures to detect 30 cancers (90.6% FP rate). Videssa Breast would have recommended 111 participants for follow-up, a 67% reduction in FPs (P < .00001). CONCLUSIONS Videssa Breast can effectively detect BC when used in conjunction with imaging and can substantially reduce unnecessary medical procedures, as well as provide assurance to women that they likely do not have BC.
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Wang DL, Xiao C, Fu G, Wang X, Li L. Identification of potential serum biomarkers for breast cancer using a functional proteomics technology. Biomark Res 2017; 5:11. [PMID: 28293426 PMCID: PMC5348793 DOI: 10.1186/s40364-017-0092-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Accepted: 03/06/2017] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Cancer is a genetic disease; its development and metastasis depend on the function of many proteins. Human serum contains thousands of proteins; it is a window for the homeostasis of individual's health. Many of the proteins found in the human serum could be potential biomarkers for cancer early detection and drug efficacy evaluation. METHODS In this study, a functional proteomics technology was used to systematically monitor metabolic enzyme and protease activities from resolved serum proteins produced by a modified 2-D gel separation and subsequent Protein Elution Plate, a method collectively called PEP. All the experiments were repeated at least twice to ensure the validity of the findings. RESULTS For the first time, significant differences were found between breast cancer patient serum and normal serum in two families of enzymes known to be involved in cancer development and metastasis: metabolic enzymes and proteases. Multiple enzyme species were identified in the serum assayed directly or after enrichment. Both qualitative and quantitative differences in the metabolic enzyme and protease activity were detected between breast cancer patient and control group, providing excellent biomarker candidates for breast cancer diagnosis and drug development. CONCLUSIONS This study identified several potential functional protein biomarkers from breast cancer patient serum. It also demonstrated that the functional proteomics technology, PEP, can be applied to the analysis of any functional proteins in human serum which contains thousands of proteins. The study indicated that the functional domain of the human serum could be unlocked with the PEP technology, pointing to a novel alternative for the development of diagnosis biomarkers for breast cancer and other diseases.
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Affiliation(s)
- David L. Wang
- Department of Biology, Vanderbilt University, Nashville, TN USA
| | | | - Guofeng Fu
- Array Bridge Inc., 4320 Forest Park Ave, Suite 303, St. Louis, MO 63108 USA
| | - Xing Wang
- Array Bridge Inc., 4320 Forest Park Ave, Suite 303, St. Louis, MO 63108 USA
| | - Liang Li
- Zibo Central Hospital, Zibo, China
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Wang D, Yang L, Zhang P, LaBaer J, Hermjakob H, Li D, Yu X. AAgAtlas 1.0: a human autoantigen database. Nucleic Acids Res 2016; 45:D769-D776. [PMID: 27924021 PMCID: PMC5210642 DOI: 10.1093/nar/gkw946] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2016] [Revised: 09/22/2016] [Accepted: 10/11/2016] [Indexed: 12/25/2022] Open
Abstract
Autoantibodies refer to antibodies that target self-antigens, which can play pivotal roles in maintaining homeostasis, distinguishing normal from tumor tissue and trigger autoimmune diseases. In the last three decades, tremendous efforts have been devoted to elucidate the generation, evolution and functions of autoantibodies, as well as their target autoantigens. However, reports of these countless previously identified autoantigens are randomly dispersed in the literature. Here, we constructed an AAgAtlas database 1.0 using text-mining and manual curation. We extracted 45 830 autoantigen-related abstracts and 94 313 sentences from PubMed using the keywords of either ‘autoantigen’ or ‘autoantibody’ or their lexical variants, which were further refined to 25 520 abstracts, 43 253 sentences and 3984 candidates by our bio-entity recognizer based on the Protein Ontology. Finally, we identified 1126 genes as human autoantigens and 1071 related human diseases, with which we constructed a human autoantigen database (AAgAtlas database 1.0). The database provides a user-friendly interface to conveniently browse, retrieve and download human autoantigens as well as their associated diseases. The database is freely accessible at http://biokb.ncpsb.org/aagatlas/. We believe this database will be a valuable resource to track and understand human autoantigens as well as to investigate their functions in basic and translational research.
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Affiliation(s)
- Dan Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Radiation Medicine, Beijing 102206, China
| | - Liuhui Yang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Radiation Medicine, Beijing 102206, China
| | - Ping Zhang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Radiation Medicine, Beijing 102206, China
| | - Joshua LaBaer
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA
| | - Henning Hermjakob
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Radiation Medicine, Beijing 102206, China .,European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Dong Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Radiation Medicine, Beijing 102206, China
| | - Xiaobo Yu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Radiation Medicine, Beijing 102206, China
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