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Pytlarz M, Wojnicki K, Pilanc P, Kaminska B, Crimi A. Deep Learning Glioma Grading with the Tumor Microenvironment Analysis Protocol for Comprehensive Learning, Discovering, and Quantifying Microenvironmental Features. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024; 37:1711-1727. [PMID: 38413460 DOI: 10.1007/s10278-024-01008-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 12/17/2023] [Accepted: 12/21/2023] [Indexed: 02/29/2024]
Abstract
Gliomas are primary brain tumors that arise from neural stem cells, or glial precursors. Diagnosis of glioma is based on histological evaluation of pathological cell features and molecular markers. Gliomas are infiltrated by myeloid cells that accumulate preferentially in malignant tumors, and their abundance inversely correlates with survival, which is of interest for cancer immunotherapies. To avoid time-consuming and laborious manual examination of images, a deep learning approach for automatic multiclass classification of tumor grades was proposed. As an alternative way of investigating characteristics of brain tumor grades, we implemented a protocol for learning, discovering, and quantifying tumor microenvironment elements on our glioma dataset. Using only single-stained biopsies we derived characteristic differentiating tumor microenvironment phenotypic neighborhoods. The study was complicated by the small size of the available human leukocyte antigen stained on glioma tissue microarray dataset - 206 images of 5 classes - as well as imbalanced data distribution. This challenge was addressed by image augmentation for underrepresented classes. In practice, we considered two scenarios, a whole slide supervised learning classification, and an unsupervised cell-to-cell analysis looking for patterns of the microenvironment. In the supervised learning investigation, we evaluated 6 distinct model architectures. Experiments revealed that a DenseNet121 architecture surpasses the baseline's accuracy by a significant margin of 9% for the test set, achieving a score of 69%, increasing accuracy in discerning challenging WHO grade 2 and 3 cases. All experiments have been carried out in a cross-validation manner. The tumor microenvironment analysis suggested an important role for myeloid cells and their accumulation in the context of characterizing glioma grades. Those promising approaches can be used as an additional diagnostic tool to improve assessment during intraoperative examination or subtyping tissues for treatment selection, potentially easing the workflow of pathologists and oncologists.
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Affiliation(s)
- M Pytlarz
- Sano - Centre for Computational Personalised Medicine, Czarnowiejska 36, Kraków, 30-054, Poland.
| | - K Wojnicki
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 3 Pasteur Street, Warszawa, 02-093, Poland
| | - P Pilanc
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 3 Pasteur Street, Warszawa, 02-093, Poland
| | - B Kaminska
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 3 Pasteur Street, Warszawa, 02-093, Poland
| | - A Crimi
- Sano - Centre for Computational Personalised Medicine, Czarnowiejska 36, Kraków, 30-054, Poland
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Korte B, Mathios D. Innovation in Non-Invasive Diagnosis and Disease Monitoring for Meningiomas. Int J Mol Sci 2024; 25:4195. [PMID: 38673779 PMCID: PMC11050588 DOI: 10.3390/ijms25084195] [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: 02/19/2024] [Revised: 03/26/2024] [Accepted: 04/07/2024] [Indexed: 04/28/2024] Open
Abstract
Meningiomas are tumors of the central nervous system that vary in their presentation, ranging from benign and slow-growing to highly aggressive. The standard method for diagnosing and classifying meningiomas involves invasive surgery and can fail to provide accurate prognostic information. Liquid biopsy methods, which exploit circulating tumor biomarkers such as DNA, extracellular vesicles, micro-RNA, proteins, and more, offer a non-invasive and dynamic approach for tumor classification, prognostication, and evaluating treatment response. Currently, a clinically approved liquid biopsy test for meningiomas does not exist. This review provides a discussion of current research and the challenges of implementing liquid biopsy techniques for advancing meningioma patient care.
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Affiliation(s)
- Brianna Korte
- Department of Neurosurgery, Washington University Medical Campus, St. Louis, MO 63110, USA
| | - Dimitrios Mathios
- Department of Neurosurgery, Washington University Medical Campus, St. Louis, MO 63110, USA
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Kino S, Kanamori M, Shimoda Y, Niizuma K, Endo H, Matsuura Y. Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation. BMC Cancer 2024; 24:222. [PMID: 38365669 PMCID: PMC10870484 DOI: 10.1186/s12885-024-11970-y] [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] [Received: 12/04/2023] [Accepted: 02/06/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Glioma is a primary brain tumor and the assessment of its molecular profile in a minimally invasive manner is important in determining treatment strategies. Among the molecular abnormalities of gliomas, mutations in the isocitrate dehydrogenase (IDH) gene are strong predictors of treatment sensitivity and prognosis. In this study, we attempted to non-invasively diagnose glioma development and the presence of IDH mutations using multivariate analysis of the plasma mid-infrared absorption spectra for a comprehensive and sensitive view of changes in blood components associated with the disease and genetic mutations. These component changes are discussed in terms of absorption wavenumbers that contribute to differentiation. METHODS Plasma samples were collected at our institutes from 84 patients with glioma (13 oligodendrogliomas, 17 IDH-mutant astrocytoma, 7 IDH wild-type diffuse glioma, and 47 glioblastomas) before treatment initiation and 72 healthy participants. FTIR-ATR spectra were obtained for each plasma sample, and PLS discriminant analysis was performed using the absorbance of each wavenumber in the fingerprint region of biomolecules as the explanatory variable. This data was used to distinguish patients with glioma from healthy participants and diagnose the presence of IDH mutations. RESULTS The derived classification algorithm distinguished the patients with glioma from healthy participants with 83% accuracy (area under the curve (AUC) in receiver operating characteristic (ROC) = 0.908) and diagnosed the presence of IDH mutation with 75% accuracy (AUC = 0.752 in ROC) in cross-validation using 30% of the total test data. The characteristic changes in the absorption spectra suggest an increase in the ratio of β-sheet structures in the conformational composition of blood proteins of patients with glioma. Furthermore, these changes were more pronounced in patients with IDH-mutant gliomas. CONCLUSIONS The plasma infrared absorption spectra could be used to diagnose gliomas and the presence of IDH mutations in gliomas with a high degree of accuracy. The spectral shape of the protein absorption band showed that the ratio of β-sheet structures in blood proteins was significantly higher in patients with glioma than in healthy participants, and protein aggregation was a distinct feature in patients with glioma with IDH mutations.
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Affiliation(s)
- Saiko Kino
- Graduate School of Biomedical Engineering, Tohoku University, 6-6-05, Aza-Aoba, Aramaki, Aoba, Sendai City, 980-8579, Miyagi Prefecture, Japan
| | - Masayuki Kanamori
- Department of Neurosurgery, Tohoku University Graduate School of Medicine, 980-8574 Seiryo 1-1, Aoba, Sendai City, Miyagi Prefecture, Japan
| | - Yoshiteru Shimoda
- Department of Neurosurgery, Tohoku University Graduate School of Medicine, 980-8574 Seiryo 1-1, Aoba, Sendai City, Miyagi Prefecture, Japan
| | - Kuniyasu Niizuma
- Department of Neurosurgical Engineering and Translational Neuroscience, Graduate School of Biomedical Engineering, Tohoku University, Seiryo 2-1, Aoba, Sendai City, 980-8575, Miyagi Prefecture, Japan
- Department of Neurosurgical Engineering and Translational Neuroscience, Tohoku University Graduate School of Medicine, 980-8575 Seiryo 2-1, Aoba, Sendai City, Miyagi Prefecture, Japan
| | - Hidenori Endo
- Department of Neurosurgery, Tohoku University Graduate School of Medicine, 980-8574 Seiryo 1-1, Aoba, Sendai City, Miyagi Prefecture, Japan
| | - Yuji Matsuura
- Graduate School of Biomedical Engineering, Tohoku University, 6-6-05, Aza-Aoba, Aramaki, Aoba, Sendai City, 980-8579, Miyagi Prefecture, Japan.
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Cameron JM, Sala A, Antoniou G, Brennan PM, Butler HJ, Conn JJA, Connal S, Curran T, Hegarty MG, McHardy RG, Orringer D, Palmer DS, Smith BR, Baker MJ. A spectroscopic liquid biopsy for the earlier detection of multiple cancer types. Br J Cancer 2023; 129:1658-1666. [PMID: 37717120 PMCID: PMC10645969 DOI: 10.1038/s41416-023-02423-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 08/24/2023] [Accepted: 08/31/2023] [Indexed: 09/18/2023] Open
Abstract
BACKGROUND A rapid, low-cost blood test that can be applied to reliably detect multiple different cancer types would be transformational. METHODS In this large-scale discovery study (n = 2092 patients) we applied the Dxcover® Cancer Liquid Biopsy to examine eight different cancers. The test uses Fourier transform infrared (FTIR) spectroscopy and machine-learning algorithms to detect cancer. RESULTS Area under the receiver operating characteristic curve (ROC) values were calculated for eight cancer types versus symptomatic non-cancer controls: brain (0.90), breast (0.76), colorectal (0.91), kidney (0.91), lung (0.91), ovarian (0.86), pancreatic (0.84) and prostate (0.86). We assessed the test performance when all eight cancer types were pooled to classify 'any cancer' against non-cancer patients. The cancer versus asymptomatic non-cancer classification detected 64% of Stage I cancers when specificity was 99% (overall sensitivity 57%). When tuned for higher sensitivity, this model identified 99% of Stage I cancers (with specificity 59%). CONCLUSIONS This spectroscopic blood test can effectively detect early-stage disease and can be fine-tuned to maximise either sensitivity or specificity depending on the requirements from different healthcare systems and cancer diagnostic pathways. This low-cost strategy could facilitate the requisite earlier diagnosis, when cancer treatment can be more effective, or less toxic. STATEMENT OF TRANSLATIONAL RELEVANCE The earlier diagnosis of cancer is of paramount importance to improve patient survival. Current liquid biopsies are mainly focused on single tumour-derived biomarkers, which limits test sensitivity, especially for early-stage cancers that do not shed enough genetic material. This pan-omic liquid biopsy analyses the full complement of tumour and immune-derived markers present within blood derivatives and could facilitate the earlier detection of multiple cancer types. There is a low barrier to integrating this blood test into existing diagnostic pathways since the technology is rapid, simple to use, only minute sample volumes are required, and sample preparation is minimal. In addition, the spectroscopic liquid biopsy described in this study has the potential to be combined with other orthogonal tests, such as cell-free DNA, which could provide an efficient route to diagnosis. Cancer treatment can be more effective when given earlier, and this low-cost strategy has the potential to improve patient prognosis.
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Affiliation(s)
- James M Cameron
- Dxcover Ltd., Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Alexandra Sala
- Dxcover Ltd., Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Georgios Antoniou
- Dxcover Ltd., Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Paul M Brennan
- Translational Neurosurgery, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Holly J Butler
- Dxcover Ltd., Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Justin J A Conn
- Dxcover Ltd., Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Siobhan Connal
- Dxcover Ltd., Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, 295 Cathedral Street, Glasgow, G11XL, UK
| | - Tom Curran
- Children's Mercy Research Institute, Children's Mercy Kansas City, 2401 Gillham Rd, Kansas City, 64108, MO, USA
| | - Mark G Hegarty
- Dxcover Ltd., Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Rose G McHardy
- Dxcover Ltd., Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
- Translational Neurosurgery, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Daniel Orringer
- Department of Neurosurgery, New York University Grossman School of Medicine, New York, NY, 10018, USA
| | - David S Palmer
- Dxcover Ltd., Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
- Translational Neurosurgery, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Benjamin R Smith
- Dxcover Ltd., Royal College Building, 204 George Street, Glasgow, G1 1XW, UK
| | - Matthew J Baker
- Dxcover Ltd., Royal College Building, 204 George Street, Glasgow, G1 1XW, UK.
- School of Medicine, Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK.
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Sala A, Cameron JM, Brennan PM, Crosbie EJ, Curran T, Gray E, Martin-Hirsch P, Palmer DS, Rehman IU, Rattray NJW, Baker MJ. Global serum profiling: an opportunity for earlier cancer detection. J Exp Clin Cancer Res 2023; 42:207. [PMID: 37580713 PMCID: PMC10426107 DOI: 10.1186/s13046-023-02786-y] [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] [Received: 06/03/2023] [Accepted: 07/30/2023] [Indexed: 08/16/2023] Open
Abstract
The advances in cancer research achieved in the last 50 years have been remarkable and have provided a deeper knowledge of this disease in many of its conceptual and biochemical aspects. From viewing a tumor as a 'simple' aggregate of mutant cells and focusing on detecting key cell changes leading to the tumorigenesis, the understanding of cancer has broadened to consider it as a complex organ interacting with its close and far surroundings through tumor and non-tumor cells, metabolic mechanisms, and immune processes. Metabolism and the immune system have been linked to tumorigenesis and malignancy progression along with cancer-specific genetic mutations. However, most technologies developed to overcome the barriers to earlier detection are focused solely on genetic information. The concept of cancer as a complex organ has led to research on other analytical techniques, with the quest of finding a more sensitive and cost-effective comprehensive approach. Furthermore, artificial intelligence has gained broader consensus in the oncology community as a powerful tool with the potential to revolutionize cancer diagnosis for physicians. We herein explore the relevance of the concept of cancer as a complex organ interacting with the bodily surroundings, and focus on promising emerging technologies seeking to diagnose cancer earlier, such as liquid biopsies. We highlight the importance of a comprehensive approach to encompass all the tumor and non-tumor derived information salient to earlier cancer detection.
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Affiliation(s)
| | | | - Paul M Brennan
- Translational Neurosurgery, Department of Clinical Neurosciences, Royal Infirmary of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Emma J Crosbie
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
- Division of Gynecology, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, M13 9WL, UK
| | - Tom Curran
- Children's Mercy Research Institute, Children's Mercy Kansas City, Kansas City, MO, 64108, USA
| | - Ewan Gray
- Independent Health Economics Consultant, Edinburgh, UK
| | - Pierre Martin-Hirsch
- Gynecological Oncology, Clinical Research Facility, Lancashire Teaching Hospitals, Preston, PR2 9HT, UK
| | - David S Palmer
- Dxcover Limited, Glasgow, G1 1XW, UK
- Department of Pure and Applied Chemistry, Thomas Graham Building, University of Strathclyde, Glasgow, G1 1XL, UK
| | - Ihtesham U Rehman
- School of Medicine, Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK
| | - Nicholas J W Rattray
- Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), University of Strathclyde, Glasgow, G4 0RE, UK
| | - Matthew J Baker
- Dxcover Limited, Glasgow, G1 1XW, UK.
- Department of Pure and Applied Chemistry, Thomas Graham Building, University of Strathclyde, Glasgow, G1 1XL, UK.
- School of Medicine, Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK.
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Theakstone AG, Brennan PM, Jenkinson MD, Goodacre R, Baker MJ. Investigating centrifugal filtration of serum-based FTIR spectroscopy for the stratification of brain tumours. PLoS One 2023; 18:e0279669. [PMID: 36800340 PMCID: PMC9937474 DOI: 10.1371/journal.pone.0279669] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 01/31/2023] [Indexed: 02/18/2023] Open
Abstract
Discrimination of brain cancer versus non-cancer patients using serum-based attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy diagnostics was first developed by Hands et al with a reported sensitivity of 92.8% and specificity of 91.5%. Cameron et al. then went on to stratifying between specific brain tumour types: glioblastoma multiforme (GBM) vs. primary cerebral lymphoma with a sensitivity of 90.1% and specificity of 86.3%. Expanding on these studies, 30 GBM, 30 lymphoma and 30 non-cancer patients were selected to investigate the influence on test performance by focusing on specific molecular weight regions of the patient serum. Membrane filters with molecular weight cut offs of 100 kDa, 50 kDa, 30 kDa, 10 kDa and 3 kDa were purchased in order to remove the most abundant high molecular weight components. Three groups were classified using both partial least squares-discriminate analysis (PLS-DA) and random forest (RF) machine learning algorithms; GBM versus non-cancer, lymphoma versus non-cancer and GBM versus lymphoma. For all groups, once the serum was filtered the sensitivity, specificity and overall balanced accuracies decreased. This illustrates that the high molecular weight components are required for discrimination between cancer and non-cancer as well as between tumour types. From a clinical application point of view, this is preferable as less sample preparation is required.
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Affiliation(s)
- Ashton G. Theakstone
- Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, United Kingdom
| | - Paul M. Brennan
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael D. Jenkinson
- The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
- Department of Pharmacology & Therapeutics, University of Liverpool, Liverpool, United Kingdom
| | - Royston Goodacre
- Department of Biochemistry and Systems Biology, University of Liverpool, Liverpool, United Kingdom
| | - Matthew J. Baker
- Dxcover Limited, Glasgow, United Kingdom
- Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston, United Kingdom
- * E-mail: ,
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Zhang C, Zhou W, Tan Y, Tian D, Zhong C. 5-Hydroxymethylcytosines in circulating cell-free DNA reveal a diagnostic biomarker for glioma. Heliyon 2022; 8:e11022. [PMID: 36281400 PMCID: PMC9587273 DOI: 10.1016/j.heliyon.2022.e11022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/12/2022] [Accepted: 10/06/2022] [Indexed: 11/06/2022] Open
Abstract
Gliomas typically have unfavorable prognosis, due to late detection and interventions. However, effective biomarkers for early glioma diagnosis based on 5-hydroxymethylcytosines (5 hm C) in circulating cell-free DNA (cfDNA) are not currently available. 5 hm C profiles in GSE132118 set were subjected for establishment of diagnostic model using the LASSO (least absolute shrinkage and selection operator) algorithm. The 5 hm C-based models demonstrated great potency in differentiating healthy subjects from gliomas, with area under the curves (AUCs) > 0.91 in the training and validation sets. Moreover, the indicator performed well in combination with clinicopathological characteristics to differentiate glioblastomas (GBMs) from lower grade glioma (LGGs). Enrichment analysis on 5 hm C profiles displayed great correlation with glioma pathophysiology. The 5 hm C-derived biomarker might act as an effective and non-invasive measure in glioma screening.
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Affiliation(s)
- Chunyu Zhang
- Department of Neurosurgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200120, China,Department of Neurosurgery, Huzhou Central Hospital, Huzhou 313099, Zhejiang Province, China
| | - Wei Zhou
- Department of Anesthesiology, Huzhou Central Hospital, Huzhou 313099, Zhejiang Province, China
| | - Yinqiu Tan
- Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430060, Hubei Province, China
| | - Daofeng Tian
- Department of Neurosurgery, Wuhan University, Renmin Hospital, Wuhan 430060, Hubei Province, China,Corresponding author.
| | - Chunlong Zhong
- Department of Neurosurgery, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200120, China,Corresponding author.
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Sala A, Cameron JM, Jenkins CA, Barr H, Christie L, Conn JJA, Evans TRJ, Harris DA, Palmer DS, Rinaldi C, Theakstone AG, Baker MJ. Liquid Biopsy for Pancreatic Cancer Detection Using Infrared Spectroscopy. Cancers (Basel) 2022; 14:3048. [PMID: 35804820 PMCID: PMC9264892 DOI: 10.3390/cancers14133048] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 06/16/2022] [Accepted: 06/20/2022] [Indexed: 12/04/2022] Open
Abstract
Pancreatic cancer claims over 460,000 victims per year. The carbohydrate antigen (CA) 19-9 test is the blood test used for pancreatic cancer's detection; however, its levels can be raised in symptomatic patients with other non-malignant diseases, or with other tumors in the surrounding area. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy has demonstrated exceptional potential in cancer diagnostics, and its clinical implementation could represent a significant step towards early detection. This proof-of-concept study, investigating the use of ATR-FTIR spectroscopy on dried blood serum, focused on the discrimination of both cancer versus healthy control samples, and cancer versus symptomatic non-malignant control samples, as a novel liquid biopsy approach for pancreatic cancer diagnosis. Machine learning algorithms were applied, achieving results of up to 92% sensitivity and 88% specificity when discriminating between cancers (n = 100) and healthy controls (n = 100). An area under the curve (AUC) of 0.95 was obtained through receiver operating characteristic (ROC) analysis. Balanced sensitivity and specificity over 75%, with an AUC of 0.83, were achieved with cancers (n = 35) versus symptomatic controls (n = 35). Herein, we present these results as demonstration that our liquid biopsy approach could become a simple, minimally invasive, and reliable diagnostic test for pancreatic cancer detection.
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Affiliation(s)
- Alexandra Sala
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, Glasgow G1 1XL, UK; (A.S.); (L.C.); (D.S.P.)
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - James M. Cameron
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - Cerys A. Jenkins
- Swansea University Medical School, Swansea University, Swansea SA2 8PP, UK;
| | - Hugh Barr
- Gloucestershire Hospitals NHS Foundation Trust, Gloucester GL1 2EL, UK;
| | - Loren Christie
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, Glasgow G1 1XL, UK; (A.S.); (L.C.); (D.S.P.)
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - Justin J. A. Conn
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | | | - Dean A. Harris
- Singleton Hospital, Swansea Bay University Local Health Board, Swansea SA2 8QA, UK;
| | - David S. Palmer
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, Glasgow G1 1XL, UK; (A.S.); (L.C.); (D.S.P.)
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - Christopher Rinaldi
- Department of Pure and Applied Chemistry, University of Strathclyde, The Technology and Innovation Centre, Glasgow G1 1RD, UK; (C.R.); (A.G.T.)
| | - Ashton G. Theakstone
- Department of Pure and Applied Chemistry, University of Strathclyde, The Technology and Innovation Centre, Glasgow G1 1RD, UK; (C.R.); (A.G.T.)
| | - Matthew J. Baker
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
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