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Wang F, Wang ZR, Ding XS, Yang H, Guo Y, Su H, Wan XR, Wang LJ, Jiang XY, Xu YH, Chen F, Cui W, Feng FZ. Combining serum peptide signatures with International Federation of Gynecology and Obstetrics (FIGO) risk score to predict the outcomes of patients with gestational trophoblastic neoplasia (GTN) after first-line chemotherapy. Front Oncol 2022; 12:982806. [PMID: 36338720 PMCID: PMC9634134 DOI: 10.3389/fonc.2022.982806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 10/06/2022] [Indexed: 11/21/2022] Open
Abstract
Background Gestational trophoblastic neoplasia (GTN) is a group of clinically rare tumors that develop in the uterus from placental tissue. Currently, its satisfactory curability derives from the timely and accurately classification and refined management for patients. This study aimed to discover biomarkers that could predict the outcomes of GTN patients after first-line chemotherapy. Methods A total of 65 GTN patients were included in the study. Patients were divided into the good or poor outcome group and the clinical characteristics of the patients in the two groups were compared. Furthermore, the serum peptide profiles of all patients were uncovered by using weak cation exchange magnetic beads and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Feature peaks were identified by three machine learning algorithms and then models were constructed and compared using five machine learning methods. Additionally, liquid chromatography mass spectrometry was used to identify the feature peptides. Results Multivariate logistic regression analysis showed that the International Federation of Gynecology and Obstetrics (FIGO) risk score was associated with poor outcomes. Eight feature peaks (m/z =1287, 2042, 2862, 2932, 2950, 3240, 3277 and 6626) were selected for model construction and validation by the three algorithms. Based on the panel combining FIGO risk score and peptide serum signatures, the neural network (nnet) model showed promising performance in both the training (AUC=0.9635) and validation (AUC=0.8788) cohorts. Peaks at m/z 2042, 2862, 2932, 3240 were identified as the partial sequences of transthyretin, fibrinogen alpha chain (FGA), beta-globin and FGA, respectively. Conclusion We combined FIGO risk score and serum peptide signatures using the nnet method to construct the model which can accurately predict outcome of GTN patients after first-line chemotherapy. With this model, patients can be further classified and managed, and those with poor predicted outcomes can be given more attention for developing treatment failure.
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Affiliation(s)
- Fei Wang
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Zi-ran Wang
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xue-song Ding
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hua Yang
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Ye Guo
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hao Su
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xi-run Wan
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Li-juan Wang
- Department of Gynecological Oncology, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xiang-yang Jiang
- Department of Obstetrics and Gynecology, Shanxi Provincial People’s Hospital, Xian, China
| | - Yan-hua Xu
- Department of Obstetrics and Gynecology, Jinan Maternity and Child Health Care Hospital, Jinan, China
| | - Feng Chen
- Department of Clinical Laboratory, State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei Cui
- Department of Clinical Laboratory, State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- *Correspondence: Wei Cui, ; Feng-zhi Feng,
| | - Feng-zhi Feng
- Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetric & Gynecologic Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- *Correspondence: Wei Cui, ; Feng-zhi Feng,
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Jia B, Zhao X, Wu D, Dong Z, Chi Y, Zhao J, Wu M, An T, Wang Y, Zhuo M, Li J, Chen X, Tian G, Long J, Yang X, Chen H, Wang J, Zhai X, Li S, Li J, Ma M, He Y, Kong L, Brcic L, Fang J, Wang Z. Identification of serum biomarkers to predict pemetrexed/platinum chemotherapy efficacy for advanced lung adenocarcinoma patients by data-independent acquisition (DIA) mass spectrometry analysis with parallel reaction monitoring (PRM) verification. Transl Lung Cancer Res 2021; 10:981-994. [PMID: 33718037 PMCID: PMC7947410 DOI: 10.21037/tlcr-21-153] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Background Pemetrexed/platinum chemotherapy has been the standard chemotherapy regimen for lung adenocarcinoma patients, but the efficacy varies considerably. Methods To discover new serum biomarkers to predict the efficacy of pemetrexed/platinum chemotherapy, we analyzed 20 serum samples from advanced lung adenocarcinoma patients who received pemetrexed/platinum chemotherapy with the data-independent acquisition (DIA) quantitative mass spectrometry (MS). Results The 20 patients were categorized as “good response” [12 patients achieving partial response (PR)] and “poor response” [8 patients with progressive disease (PD)] groups. Altogether 23 significantly different expressed proteins were identified, which had relative ratios higher than 1.2 or lower than –0.83, with 7 proteins having an area under the curve (AUC) above 0.8. To further validate the DIA results, we used the parallel reaction monitoring (PRM) method to examine 16 candidate serum biomarkers in the study cohort of 20 patients and another cohort of 22 advanced lung adenocarcinoma patients (16 PR and 6 PD). Quantitative validation using PRM correlated well with the DIA results, and 10 promising proteins exhibited a similar up- or downregulation. It is worth noting that glutathione peroxidase 3 (GPX3) exhibits significant upregulation in the poor response group compared with the good response group, which was validated by both DIA and PRM methods. Conclusions Our study confirmed that combined DIA MS and PRM approaches were effective in identifying serum predictive biomarkers for advanced lung adenocarcinoma patients. Further studies are needed to explore the potential biological mechanism underlying these biomarkers.
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Affiliation(s)
- Bo Jia
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Xinghui Zhao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Di Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology II, Peking University Cancer Hospital & Institute, Beijing, China
| | - Zhi Dong
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of GI Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Yujia Chi
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Jun Zhao
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Meina Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Tongtong An
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Yuyan Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Minglei Zhuo
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Jianjie Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Xiaoling Chen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology II, Peking University Cancer Hospital & Institute, Beijing, China
| | - Guangming Tian
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology II, Peking University Cancer Hospital & Institute, Beijing, China
| | - Jieran Long
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology II, Peking University Cancer Hospital & Institute, Beijing, China
| | - Xue Yang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Hanxiao Chen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Jingjing Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Xiaoyu Zhai
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Sheng Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Junfeng Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Menglei Ma
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Yuling He
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Lingdong Kong
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
| | - Luka Brcic
- Diagnostic and Research Institute of Pathology, Medical University of Graz, Graz, Austria
| | - Jian Fang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Oncology II, Peking University Cancer Hospital & Institute, Beijing, China
| | - Ziping Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China
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Ciocan-Cartita CA, Jurj A, Buse M, Gulei D, Braicu C, Raduly L, Cojocneanu R, Pruteanu LL, Iuga CA, Coza O, Berindan-Neagoe I. The Relevance of Mass Spectrometry Analysis for Personalized Medicine through Its Successful Application in Cancer "Omics". Int J Mol Sci 2019; 20:ijms20102576. [PMID: 31130665 PMCID: PMC6567119 DOI: 10.3390/ijms20102576] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 05/21/2019] [Accepted: 05/24/2019] [Indexed: 01/06/2023] Open
Abstract
Mass spectrometry (MS) is an essential analytical technology on which the emerging omics domains; such as genomics; transcriptomics; proteomics and metabolomics; are based. This quantifiable technique allows for the identification of thousands of proteins from cell culture; bodily fluids or tissue using either global or targeted strategies; or detection of biologically active metabolites in ultra amounts. The routine performance of MS technology in the oncological field provides a better understanding of human diseases in terms of pathophysiology; prevention; diagnosis and treatment; as well as development of new biomarkers; drugs targets and therapies. In this review; we argue that the recent; successful advances in MS technologies towards cancer omics studies provides a strong rationale for its implementation in biomedicine as a whole.
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Affiliation(s)
- Cristina Alexandra Ciocan-Cartita
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
| | - Ancuța Jurj
- Research Center for Functional Genomics, Biomedicine and Translational Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy.
| | - Mihail Buse
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
| | - Diana Gulei
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
| | - Cornelia Braicu
- Research Center for Functional Genomics, Biomedicine and Translational Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy.
| | - Lajos Raduly
- Research Center for Functional Genomics, Biomedicine and Translational Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy.
| | - Roxana Cojocneanu
- Research Center for Functional Genomics, Biomedicine and Translational Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy.
| | - Lavinia Lorena Pruteanu
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
| | - Cristina Adela Iuga
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
- Department of Pharmaceutical Analysis, Faculty of Pharmacy, "Iuliu Hațieganu" University of Medicine and Pharmacy, 6 Louis Pasteur Street, 400349 Cluj-Napoca.
| | - Ovidiu Coza
- Department of Oncology, "Iuliu Hațieganu" University of Medicine and Pharmacy, 34-36 Republicii Street, 400015 Cluj-Napoca, Romania.
- Department of Radiotherapy with High Energies and Brachytherapy, Oncology Institute "Prof. Dr. Ion Chiricuta", 34-36 Republicii Street, 400015 Cluj-Napoca.
| | - Ioana Berindan-Neagoe
- MEDFUTURE -Research Center for Advanced Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy, 4-6 Louis Pasteur Street, 400349 Cluj-Napoca, Romania.
- Research Center for Functional Genomics, Biomedicine and Translational Medicine," Iuliu Hațieganu" University of Medicine and Pharmacy.
- Department of Functional Genomics and Experimental Pathology, Ion Chiricuțǎ Oncology Institute, 34-36 Republicii Street, 400015 Cluj-Napoca.
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