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Chen HJC, Hu SX, Tu CW. Multiple oxidative modifications on hemoglobin are elevated in breast cancer patients as measured by nanoflow liquid chromatography-tandem mass spectrometry. J Pharm Biomed Anal 2024; 252:116477. [PMID: 39321489 DOI: 10.1016/j.jpba.2024.116477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2024] [Revised: 09/14/2024] [Accepted: 09/15/2024] [Indexed: 09/27/2024]
Abstract
Breast cancer is strongly connected with elevated oxidative stress. Oxidative modifications of hemoglobin can serve as biomarkers for monitoring oxidative stress status in vivo. The structure of hemoglobin modifications derived from malondialdehyde (MDA) in human blood hemoglobin exists as N-propenal and dihydropyridine (DHP). This study reports the simultaneous quantification of eleven modified peptides in hemoglobin derived from MDA and advanced histidine oxidation in 16 breast cancer patients and 16 healthy women using nanoflow liquid chromatography nanoelectrospray ionization tandem mass spectrometry. The results reveal statistically significant increases in the formation of MDA-derived N-propenal and DHP of lysine and advanced oxidation of histidine in hemoglobin of breast cancer patients with the Mann-Whitney U-test p values < 0.0001 and the AUC of ROC between 0.9277 and 1.0. Furthermore, the elevation in modified peptides is significant in patients with early stages of breast cancer. By measuring these oxidative modifications in hemoglobin from a drop of blood, the role of lipid peroxidation and oxidative stress in breast cancer can be assessed using this sensitive assay.
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Affiliation(s)
- Hauh-Jyun Candy Chen
- Department of Chemistry and Biochemistry, National Chung Cheng University, 168 University Road, Ming-Hsiung, Chiayi 62142, Taiwan.
| | - Shun-Xiang Hu
- Department of Chemistry and Biochemistry, National Chung Cheng University, 168 University Road, Ming-Hsiung, Chiayi 62142, Taiwan
| | - Chi-Wen Tu
- Department of Surgery, Ditmanson Medical Foundation Chia‑Yi Christian Hospital, Chiayi 60002, Taiwan
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2
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Tsai KL, Chang CC, Chang YS, Lu YY, Tsai IJ, Chen JH, Lin SH, Tai CC, Lin YF, Chang HW, Lin CY, Su ECY. Isotypes of autoantibodies against novel differential 4-hydroxy-2-nonenal-modified peptide adducts in serum is associated with rheumatoid arthritis in Taiwanese women. BMC Med Inform Decis Mak 2021; 21:49. [PMID: 33568149 PMCID: PMC7874460 DOI: 10.1186/s12911-020-01380-y] [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: 02/26/2020] [Accepted: 12/21/2020] [Indexed: 01/03/2023] Open
Abstract
Background Rheumatoid arthritis (RA) is an autoimmune disorder with systemic inflammation and may be induced by oxidative stress that affects an inflamed joint. Our objectives were to examine isotypes of autoantibodies against 4-hydroxy-2-nonenal (HNE) modifications in RA and associate them with increased levels of autoantibodies in RA patients. Methods Serum samples from 155 female patients [60 with RA, 35 with osteoarthritis (OA), and 60 healthy controls (HCs)] were obtained. Four novel differential HNE-modified peptide adducts, complement factor H (CFAH)1211–1230, haptoglobin (HPT)78–108, immunoglobulin (Ig) kappa chain C region (IGKC)2–19, and prothrombin (THRB)328–345, were re-analyzed using tandem mass spectrometric (MS/MS) spectra (ProteomeXchange: PXD004546) from RA patients vs. HCs. Further, we determined serum protein levels of CFAH, HPT, IGKC and THRB, HNE-protein adducts, and autoantibodies against unmodified and HNE-modified peptides. Significant correlations and odds ratios (ORs) were calculated. Results Levels of HPT in RA patients were greatly higher than the levels in HCs. Levels of HNE-protein adducts and autoantibodies in RA patients were significantly greater than those of HCs. IgM anti-HPT78−108 HNE, IgM anti-IGKC2−19, and IgM anti-IGKC2−19 HNE may be considered as diagnostic biomarkers for RA. Importantly, elevated levels of IgM anti-HPT78−108 HNE, IgM anti-IGKC2−19, and IgG anti-THRB328−345 were positively correlated with the disease activity score in 28 joints for C-reactive protein (DAS28-CRP). Further, the ORs of RA development through IgM anti-HPT78−108 HNE (OR 5.235, p < 0.001), IgM anti-IGKC2−19 (OR 12.655, p < 0.001), and IgG anti-THRB328−345 (OR 5.761, p < 0.001) showed an increased risk. Lastly, we incorporated three machine learning models to differentiate RA from HC and OA, and performed feature selection to determine discriminative features. Experimental results showed that our proposed method achieved an area under the receiver operating characteristic curve of 0.92, which demonstrated that our selected autoantibodies combined with machine learning can efficiently detect RA.
Conclusions This study discovered that some IgG- and IgM-NAAs and anti-HNE M-NAAs may be correlated with inflammation and disease activity in RA. Moreover, our findings suggested that IgM anti-HPT78−108 HNE, IgM anti-IGKC2−19, and IgG anti-THRB328−345 may play heavy roles in RA development.
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Affiliation(s)
- Kai-Leun Tsai
- Division of Allergy, Immunology and Rheumatology, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, 23561, Taiwan.,Division of Allergy, Immunology and Rheumatology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, 11031, Taiwan
| | - Che-Chang Chang
- Graduate Institute of Translational Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan
| | - Yu-Sheng Chang
- Division of Allergy, Immunology and Rheumatology, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, 23561, Taiwan.,Division of Allergy, Immunology and Rheumatology, Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, 11031, Taiwan
| | - Yi-Ying Lu
- School of Medical Laboratory Science and Biotechnology, College of Medical Science and Technology, Taipei Medical University, 250 Wuxing Street, Taipei, 11031, Taiwan
| | - I-Jung Tsai
- School of Medical Laboratory Science and Biotechnology, College of Medical Science and Technology, Taipei Medical University, 250 Wuxing Street, Taipei, 11031, Taiwan
| | - Jin-Hua Chen
- Graduate Institute of Data Science, College of Management, Taipei Medical University, Taipei, 11031, Taiwan.,Research Center of Biostatistics, College of Management, Taipei Medical University, Taipei, 11031, Taiwan
| | - Sheng-Hong Lin
- Division of Allergy, Immunology and Rheumatology, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, 23561, Taiwan
| | - Chih-Chun Tai
- Department of Laboratory Medicine, Taipei Medical University-Shuang-Ho Hospital, Taipei Medical University, New Taipei City, 23561, Taiwan
| | - Yi-Fang Lin
- Department of Laboratory Medicine, Taipei Medical University-Shuang-Ho Hospital, Taipei Medical University, New Taipei City, 23561, Taiwan
| | - Hui-Wen Chang
- Department of Medical Laboratory, Taipei Medical University Hospital, Taipei, 11031, Taiwan.,PhD Program in Medical Biotechnology, College of Medical Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan
| | - Ching-Yu Lin
- School of Medical Laboratory Science and Biotechnology, College of Medical Science and Technology, Taipei Medical University, 250 Wuxing Street, Taipei, 11031, Taiwan. .,PhD Program in Medical Biotechnology, College of Medical Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan. .,Department of Biotechnology and Animal Science, National Ilan University, Ilan, 26047, Taiwan.
| | - Emily Chia-Yu Su
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, 11031, Taiwan. .,Clinical Big Data Research Center, Taipei Medical University Hospital, Taipei, 11031, Taiwan.
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3
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Moi SH, Lee YC, Chuang LY, Yuan SSF, Ou-Yang F, Hou MF, Yang CH, Chang HW. Cumulative receiver operating characteristics for analyzing interaction between tissue visfatin and clinicopathologic factors in breast cancer progression. Cancer Cell Int 2018; 18:19. [PMID: 29449787 PMCID: PMC5807850 DOI: 10.1186/s12935-018-0517-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Accepted: 01/31/2018] [Indexed: 01/16/2023] Open
Abstract
Background Visfatin has been reported to be associated with breast cancer progression, but the interaction between the visfatin and clinicopathologic factors in breast cancer progression status requires further investigation. To address this problem, it is better to simultaneously consider multiple factors in sensitivity and specificity assays. Methods In this study, a dataset for 105 breast cancer patients (84 disease-free and 21 progressing) were chosen. Individual and cumulative receiver operating characteristics (ROC) were used to analyze the impact of each factor along with interaction effects. Results In individual ROC analysis, only 3 of 13 factors showed better performance for area under curve (AUC), i.e., AUC > 7 for hormone therapy (HT), tissue visfatin, and lymph node (LN) metastasis. Under our proposed scoring system, the cumulative ROC analysis provides higher AUC performance (0.746–0.886) than individual ROC analysis in predicting breast cancer progression. Considering the interaction between these factors, a minimum of six factors, including HT, tissue visfatin, LN metastasis, tumor stage, age, and tumor size, were identified as being highly interactive and associated with breast cancer progression, providing potential and optimal discriminators for predicting breast cancer progression. Conclusion Taken together, the cumulative ROC analysis provides better prediction for breast cancer progression than individual ROC analysis. Electronic supplementary material The online version of this article (10.1186/s12935-018-0517-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sin-Hua Moi
- 1Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan
| | - Yi-Chen Lee
- Translational Research Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,3Department of Anatomy, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Li-Yeh Chuang
- 4Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan
| | - Shyng-Shiou F Yuan
- Translational Research Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Cancer Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Fu Ou-Yang
- Cancer Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,6Division of Breast Surgery and Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Ming-Feng Hou
- Cancer Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,7Institute of Clinical Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.,8Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Cheng-Hong Yang
- 1Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan.,9Graduate Institute of Clinical Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Hsueh-Wei Chang
- Cancer Center, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,10Institute of Medical Science and Technology, National Sun Yat-sen University, Kaohsiung, Taiwan.,11Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.,12Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan
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Interaction of MRE11 and Clinicopathologic Characteristics in Recurrence of Breast Cancer: Individual and Cumulated Receiver Operating Characteristic Analyses. BIOMED RESEARCH INTERNATIONAL 2017; 2017:2563910. [PMID: 28133604 PMCID: PMC5241446 DOI: 10.1155/2017/2563910] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Accepted: 11/28/2016] [Indexed: 12/28/2022]
Abstract
The interaction between the meiotic recombination 11 homolog A (MRE11) oncoprotein and breast cancer recurrence status remains unclear. The aim of this study was to assess the interaction between MRE11 and clinicopathologic variables in breast cancer. A dataset for 254 subjects with breast cancer (220 nonrecurrent and 34 recurrent) was used in individual and cumulated receiver operating characteristic (ROC) analyses of MRE11 and 12 clinicopathologic variables for predicting breast cancer recurrence. In individual ROC analysis, the area under curve (AUC) for each predictor of breast cancer recurrence was smaller than 0.7. In cumulated ROC analysis, however, the AUC value for each predictor improved. Ten relevant variables in breast cancer recurrence were used to find the optimal prognostic indicators. The presence of any six of the following ten variables had a high (79%) sensitivity and a high (70%) specificity for predicting breast cancer recurrence: tumor size ≥ 2.4 cm, tumor stage II/III, therapy other than hormone therapy, age ≥ 52 years, MRE11 positive cells > 50%, body mass index ≥ 24, lymph node metastasis, positivity for progesterone receptor, positivity for epidermal growth factor receptor, and negativity for estrogen receptor. In conclusion, this study revealed that these 10 clinicopathologic variables are the minimum discriminators needed for optimal discriminant effectiveness in predicting breast cancer recurrence.
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Ewaisha R, Gawryletz CD, Anderson KS. Crucial considerations for pipelines to validate circulating biomarkers for breast cancer. Expert Rev Proteomics 2016; 13:201-11. [PMID: 26653344 DOI: 10.1586/14789450.2016.1132170] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Despite decades of progress in breast imaging, breast cancer remains the second most common cause of cancer mortality in women. The rapidly proliferative breast cancers that are associated with high relapse rates and mortality frequently present in younger women, in unscreened individuals, or in the intervals between screening mammography. Biomarkers exist for monitoring metastatic disease, such as CEA, CA27.29 and CA15-3, but there are no circulating biomarkers clinically available for early detection, prognosis, or monitoring for clinical relapse. There has been significant progress in the discovery of potential circulating biomarkers, including proteins, autoantibodies, nucleic acids, exosomes, and circulating tumor cells, but the vast majority of these biomarkers have not progressed beyond initial research discovery, and none have yet been approved for clinical use in early stage disease. Here, the authors review the crucial considerations of developing pipelines for the rapid evaluation of circulating biomarkers for breast cancer.
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Affiliation(s)
- Radwa Ewaisha
- a Center for Personalized Diagnostics, Biodesign Institute , Arizona State University , Tempe , AZ , USA
| | - Chelsea D Gawryletz
- b Department of Medical Oncology , Mayo Clinic Arizona , Scottsdale , AZ , USA
| | - Karen S Anderson
- a Center for Personalized Diagnostics, Biodesign Institute , Arizona State University , Tempe , AZ , USA.,b Department of Medical Oncology , Mayo Clinic Arizona , Scottsdale , AZ , USA
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Schaur RJ, Siems W, Bresgen N, Eckl PM. 4-Hydroxy-nonenal-A Bioactive Lipid Peroxidation Product. Biomolecules 2015; 5:2247-337. [PMID: 26437435 PMCID: PMC4693237 DOI: 10.3390/biom5042247] [Citation(s) in RCA: 141] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2015] [Revised: 07/24/2015] [Accepted: 07/29/2015] [Indexed: 12/23/2022] Open
Abstract
This review on recent research advances of the lipid peroxidation product 4-hydroxy-nonenal (HNE) has four major topics: I. the formation of HNE in various organs and tissues, II. the diverse biochemical reactions with Michael adduct formation as the most prominent one, III. the endogenous targets of HNE, primarily peptides and proteins (here the mechanisms of covalent adduct formation are described and the (patho-) physiological consequences discussed), and IV. the metabolism of HNE leading to a great number of degradation products, some of which are excreted in urine and may serve as non-invasive biomarkers of oxidative stress.
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Affiliation(s)
- Rudolf J Schaur
- Institute of Molecular Biosciences, University of Graz, Heinrichstrasse 33a, 8010 Graz, Austria.
| | - Werner Siems
- Institute for Medical Education, KortexMed GmbH, Hindenburgring 12a, 38667 Bad Harzburg, Germany.
| | - Nikolaus Bresgen
- Division of Genetics, Department of Cell Biology, University of Salzburg, Hellbrunnerstasse 34, 5020 Salzburg, Austria.
| | - Peter M Eckl
- Division of Genetics, Department of Cell Biology, University of Salzburg, Hellbrunnerstasse 34, 5020 Salzburg, Austria.
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