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Saito K, Goda R, Arai K, Asahina K, Kawabata M, Uchiyama H, Andou T, Shimizu H, Takahara K, Kakehi M, Yamauchi S, Nitta SI, Suga T, Fujita H, Ishikawa R, Saito Y. Interlaboratory evaluation of LC-MS-based biomarker assays. Bioanalysis 2024; 16:389-402. [PMID: 38334082 DOI: 10.4155/bio-2023-0173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024] Open
Abstract
Validation of biomarker assays is crucial for effective drug development and clinical applications. Interlaboratory reproducibility is vital for reliable comparison and combination of data from different centers. This review summarizes interlaboratory studies of quantitative LC-MS-based biomarker assays using reference standards for calibration curves. The following points are discussed: trends in reports, reference and internal standards, evaluation of analytical validation parameters, study sample analysis and normalization of biomarker assay data. Full evaluation of these parameters in interlaboratory studies is limited, necessitating further research. Some reports suggest methods to address variations in biomarker assay data among laboratories, facilitating organized studies and data combination. Method validation across laboratories is crucial for reducing interlaboratory differences and reflecting target biomarker responses.
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Affiliation(s)
- Kosuke Saito
- National Institute of Health Sciences, Kanagawa, Japan
| | - Ryoya Goda
- Daiichi Sankyo Company Ltd, Tokyo, Japan
| | - Koji Arai
- LSI Medience Corporation, Tokyo, Japan
| | | | | | | | | | | | | | | | | | | | | | | | - Rika Ishikawa
- National Institute of Health Sciences, Kanagawa, Japan
| | - Yoshiro Saito
- National Institute of Health Sciences, Kanagawa, Japan
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2
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Safari F, Kehelpannala C, Safarchi A, Batarseh AM, Vafaee F. Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis. Cancers (Basel) 2023; 15:2780. [PMID: 37345117 DOI: 10.3390/cancers15102780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 05/02/2023] [Accepted: 05/10/2023] [Indexed: 06/23/2023] Open
Abstract
Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.
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Affiliation(s)
- Fatemeh Safari
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
| | - Cheka Kehelpannala
- BCAL Diagnostics Ltd., Suite 506, 50 Clarence St, Sydney, NSW 2000, Australia
- BCAL Dx, The University of Sydney, Sydney Knowledge Hub, Merewether Building, Sydney, NSW 2006, Australia
| | - Azadeh Safarchi
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- Microbiomes for One Systems Health, Health and Biosecurity, CSIRO, Westmead, NSW 2145, Australia
| | - Amani M Batarseh
- BCAL Diagnostics Ltd., Suite 506, 50 Clarence St, Sydney, NSW 2000, Australia
- BCAL Dx, The University of Sydney, Sydney Knowledge Hub, Merewether Building, Sydney, NSW 2006, Australia
| | - Fatemeh Vafaee
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- UNSW Data Science Hub (uDASH), University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- OmniOmics.ai Pty Ltd., Sydney, NSW 2035, Australia
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3
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Barker AD, Alba MM, Mallick P, Agus DB, Lee JSH. An Inflection Point in Cancer Protein Biomarkers: What Was and What's Next. Mol Cell Proteomics 2023:100569. [PMID: 37196763 PMCID: PMC10388583 DOI: 10.1016/j.mcpro.2023.100569] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 04/26/2023] [Accepted: 05/08/2023] [Indexed: 05/19/2023] Open
Abstract
Biomarkers remain the highest value proposition in cancer medicine today - especially protein biomarkers. Yet despite decades of evolving regulatory frameworks to facilitate the review of emerging technologies, biomarkers have been mostly about promise with very little to show for improvements in human health. Cancer is an emergent property of a complex system and deconvoluting the integrative and dynamic nature of the overall system through biomarkers is a daunting proposition. The last two decades have seen an explosion of multi-omics profiling and a range of advanced technologies for precision medicine, including the emergence of liquid biopsy, exciting advances in single cell analysis, artificial intelligence (machine and deep learning) for data analysis and many other advanced technologies that promise to transform biomarker discovery. Combining multiple omics modalities to acquire a more comprehensive landscape of the disease state, we are increasingly developing biomarkers to support therapy selection and patient monitoring. Furthering precision medicine, especially in oncology, necessitates moving away from the lens of reductionist thinking towards viewing and understanding that complex diseases are, in fact, complex adaptive systems. As such, we believe it is necessary to re-define biomarkers as representations of biological system states at different hierarchical levels of biological order. This definition could include traditional molecular, histologic, radiographic, or physiological characteristics, as well as emerging classes of digital markers and complex algorithms. To succeed in the future, we must move past purely observational individual studies and instead start building a mechanistic framework to enable integrative analysis of new studies within the context of prior studies. Identifying information in complex systems and applying theoretical constructs, such as information theory, to study cancer as a disease of dysregulated communication could prove to be "game changing" for the clinical outcome of cancer patients.
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Affiliation(s)
- Anna D Barker
- Lawrence J. Ellison Institute for Transformative Medicine, Los Angeles, CA; Complex Adaptive Systems Initiative and School of Life Sciences, Arizona State University, Tempe, Arizona
| | - Mario M Alba
- Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA
| | - Parag Mallick
- Canary Center at Stanford for Cancer Early Detection, Stanford University, Stanford, CA; Department of Radiology, Stanford University, Stanford, CA
| | - David B Agus
- Lawrence J. Ellison Institute for Transformative Medicine, Los Angeles, CA; Keck School of Medicine, University of Southern California, Los Angeles, CA; Viterbi School of Engineering, University of Southern California, Los Angeles, CA
| | - Jerry S H Lee
- Lawrence J. Ellison Institute for Transformative Medicine, Los Angeles, CA; Keck School of Medicine, University of Southern California, Los Angeles, CA; Viterbi School of Engineering, University of Southern California, Los Angeles, CA
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Wong YL, Ramanathan A, Yuen KM, Mustafa WMW, Abraham MT, Tay KK, Rahman ZAA, Chen Y. Comparative sera proteomics analysis of differentially expressed proteins in oral squamous cell carcinoma. PeerJ 2021; 9:e11548. [PMID: 34178453 PMCID: PMC8199918 DOI: 10.7717/peerj.11548] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 05/11/2021] [Indexed: 11/20/2022] Open
Abstract
Background Oral squamous cell carcinoma (OSCC) has increased in incidence from 1990 to 2017, especially in South and Southeast Asia. It is often diagnosed at an advanced stage with a poor prognosis. Therefore, early detection of OSCC is essential to improve the prognosis of OSCC. This study aims to identify the differentially expressed serum proteins as potential biomarkers for oral squamous cell carcinoma (OSCC). Methods Comparative proteomics profiling of serum samples from OSCC patients, oral potentially malignant disorder (OPMD) patients, and healthy individuals were performed using two-dimensional gel electrophoresis (2-DE) coupled with mass spectrometry (MS) (n = 60) and bioinformatics analysis. The enzyme-linked immunosorbent assay (ELISA) (n = 120) and immunohistochemistry (IHC) (n = 70) were used to confirm our findings. Results The 2-DE analysis revealed that 20 differentially expressed proteins were detected in OPMD and OSCC (p < 0.05). Bioinformatics analysis indicated that the activation of classical complement, liver X receptor/retinoid X receptor (LXR/RXR) activation, and acute phase response signaling pathway are associated with the development and progression of OSCC. Most of the detected proteins are acute-phase proteins and were related to inflammation and immune responses, including apolipoprotein A-I (APOA1), complement C3 (C3), clusterin (CLU), and haptoglobin (HP). The expression levels of CLU and HP in ELISA are consistent with the findings from the 2-DE analysis, except for the mean serum level of HP in OPMD, whereby it was slightly higher than that in control. IHC results demonstrated that CLU and HP are significantly decreased in OSCC tissues. Conclusion Decreased expression of CLU and HP could serve as complementary biomarkers of OSCC. These proteins may assist in predicting the outcomes of OSCC patients. However, a larger cohort is needed for further investigation.
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Affiliation(s)
- Yin-Ling Wong
- Department of Oral & Craniofacial Sciences, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia
| | - Anand Ramanathan
- Department of Oral & Maxillofacial Clinical Sciences, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia.,Oral Cancer Research & Coordinating Centre, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia
| | - Kar Mun Yuen
- Oral Health Program, Ministry of Health, Federal Government Administrative Centre, Putrajaya, Malaysia
| | | | - Mannil Thomas Abraham
- Oral Health Program, Ministry of Health, Federal Government Administrative Centre, Putrajaya, Malaysia
| | - Keng Kiong Tay
- Oral Health Program, Ministry of Health, Federal Government Administrative Centre, Putrajaya, Malaysia
| | - Zainal Ariff Abdul Rahman
- Department of Oral & Maxillofacial Clinical Sciences, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia.,Oral Cancer Research & Coordinating Centre, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia
| | - Yeng Chen
- Department of Oral & Craniofacial Sciences, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia.,Oral Cancer Research & Coordinating Centre, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia
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Oshima M, Hara A, Toyama T, Jun M, Pollock C, Jardine M, Harrap S, Poulter N, Cooper ME, Woodward M, Chalmers J, Perkovic V, Wong MG, Wada T. Comparison of Circulating Biomarkers in Predicting Diabetic Kidney Disease Progression With Autoantibodies to Erythropoietin Receptor. Kidney Int Rep 2020; 6:284-295. [PMID: 33615053 PMCID: PMC7879109 DOI: 10.1016/j.ekir.2020.10.039] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 10/03/2020] [Accepted: 10/27/2020] [Indexed: 01/21/2023] Open
Abstract
Introduction Several circulating markers, including autoantibodies to erythropoietin receptor (anti-EPOR antibodies), have been identified as useful biomarkers in predicting diabetic kidney disease progression. However, a direct comparison of their utility is lacking. We aimed to validate and to compare the prognostic value of anti-EPOR antibodies with that of other known biomarkers, using the ADVANCE trial and its long-term follow-up, ADVANCE-ON, cohorts. Methods In this nested case-control study from the ADVANCE trial cohort, we included 165 case participants who had the composite kidney outcome (renal replacement therapy, renal death, or doubling of serum creatinine to ≥200 μmol/l) and 330 matched controls. We compared the associations of baseline plasma levels of anti-EPOR antibodies, tumor necrosis factor receptor (TNFR)-1 and -2, and bone morphogenetic protein (BMP)-7 with kidney outcomes. Results Cases had higher baseline plasma levels of anti-EPOR antibodies than controls (median 1.7 vs. 0.6 enzyme-linked immunosorbent assay unit, P < 0.001). Higher levels of anti-EPOR antibodies were associated with an increased risk of kidney outcome (odds ratio 2.16 [95% confidence interval 1.51, 3.08], per 1 SD of log-transformed levels) after adjusting for conventional markers. Elevated circulating TNFR1 and TNFR2 levels, and lower BMP-7 levels at baseline, were associated with poor kidney outcome (odds ratios 2.06 [1.29, 3.30], 1.66 [1.13, 2.43], and 0.45 [0.32, 0.65], respectively). The addition of anti-EPOR antibodies into the model improved the prediction of kidney outcome, regardless of other biomarkers. Conclusion Anti-EPOR antibodies provide a promising biomarker, as with TNFR1, TNFR2, and BMP-7, in predicting kidney disease progression in people with type 2 diabetes mellitus.
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Affiliation(s)
- Megumi Oshima
- Department of Renal and Metabolic, The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia.,Department of Nephrology and Laboratory Medicine, Kanazawa University, Kanazawa, Japan.,Renal Department, Kolling Institute of Medical Research, Sydney Medical School, University of Sydney, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Akinori Hara
- Department of Nephrology and Laboratory Medicine, Kanazawa University, Kanazawa, Japan
| | - Tadashi Toyama
- Department of Nephrology and Laboratory Medicine, Kanazawa University, Kanazawa, Japan
| | - Min Jun
- Department of Renal and Metabolic, The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Carol Pollock
- Renal Department, Kolling Institute of Medical Research, Sydney Medical School, University of Sydney, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Meg Jardine
- Department of Renal and Metabolic, The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia.,Nephrology Unit, Concord Repatriation General Hospital, Sydney, New South Wales, Australia
| | - Stephen Harrap
- Department of Physiology, Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia
| | - Neil Poulter
- International Center for Circulatory Health, Imperial College, London, UK
| | - Mark E Cooper
- Departiment of Diabetes, Baker IDI Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Mark Woodward
- Department of Renal and Metabolic, The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia.,The George Institute for Global Health, University of Oxford, Oxford, UK.,Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - John Chalmers
- Department of Renal and Metabolic, The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Vlado Perkovic
- Department of Renal and Metabolic, The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Muh Geot Wong
- Department of Renal and Metabolic, The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia.,Renal Department, Kolling Institute of Medical Research, Sydney Medical School, University of Sydney, Royal North Shore Hospital, Sydney, New South Wales, Australia
| | - Takashi Wada
- Department of Nephrology and Laboratory Medicine, Kanazawa University, Kanazawa, Japan
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Coll-de la Rubia E, Martinez-Garcia E, Dittmar G, Gil-Moreno A, Cabrera S, Colas E. Prognostic Biomarkers in Endometrial Cancer: A Systematic Review and Meta-Analysis. J Clin Med 2020; 9:E1900. [PMID: 32560580 PMCID: PMC7356541 DOI: 10.3390/jcm9061900] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Revised: 06/12/2020] [Accepted: 06/15/2020] [Indexed: 12/23/2022] Open
Abstract
Endometrial cancer (EC) is the sixth most common cancer in women worldwide and its mortality is directly associated with the presence of poor prognostic factors driving tumor recurrence. Stratification systems are based on few molecular, and mostly clinical and pathological parameters, but these systems remain inaccurate. Therefore, identifying prognostic EC biomarkers is crucial for improving risk assessment pre- and postoperatively and to guide treatment decisions. This systematic review gathers all protein biomarkers associated with clinical prognostic factors of EC, recurrence and survival. Relevant studies were identified by searching the PubMed database from 1991 to February 2020. A total number of 398 studies matched our criteria, which compiled 255 proteins associated with the prognosis of EC. MUC16, ESR1, PGR, TP53, WFDC2, MKI67, ERBB2, L1CAM, CDH1, PTEN and MMR proteins are the most validated biomarkers. On the basis of our meta-analysis ESR1, TP53 and WFDC2 showed potential usefulness for predicting overall survival in EC. Limitations of the published studies in terms of appropriate study design, lack of high-throughput measurements, and statistical deficiencies are highlighted, and new approaches and perspectives for the identification and validation of clinically valuable EC prognostic biomarkers are discussed.
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Affiliation(s)
- Eva Coll-de la Rubia
- Biomedical Research Group in Gynecology, Vall Hebron Institute of Research, Universitat Autònoma de Barcelona, CIBERONC, 08035 Barcelona, Spain;
| | - Elena Martinez-Garcia
- Quantitative Biology Unit, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg; (E.M.-G.); (G.D.)
| | - Gunnar Dittmar
- Quantitative Biology Unit, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg; (E.M.-G.); (G.D.)
| | - Antonio Gil-Moreno
- Biomedical Research Group in Gynecology, Vall Hebron Institute of Research, Universitat Autònoma de Barcelona, CIBERONC, 08035 Barcelona, Spain;
- Gynecological Department, Vall Hebron University Hospital, CIBERONC, 08035 Barcelona, Spain
| | - Silvia Cabrera
- Biomedical Research Group in Gynecology, Vall Hebron Institute of Research, Universitat Autònoma de Barcelona, CIBERONC, 08035 Barcelona, Spain;
- Gynecological Department, Vall Hebron University Hospital, CIBERONC, 08035 Barcelona, Spain
| | - Eva Colas
- Biomedical Research Group in Gynecology, Vall Hebron Institute of Research, Universitat Autònoma de Barcelona, CIBERONC, 08035 Barcelona, Spain;
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