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Sok CP, Polireddy K, Kooby DA. Molecular pathology and protein markers for pancreatic cancer: relevance in staging, in adjuvant therapy, in determination of minimal residual disease, and follow-up. Hepatobiliary Surg Nutr 2024; 13:56-70. [PMID: 38322203 PMCID: PMC10839718 DOI: 10.21037/hbsn-22-628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 05/10/2023] [Indexed: 02/08/2024]
Abstract
The diagnosis and monitoring of disease through the detection of circulating protein biomarkers is a growing field in the practice of oncology. The search for more effective protein biomarkers to aid in the diagnosis and treatment of patients with pancreatic ductal adenocarcinoma (PDAC) remains a valuable area of study, given the aggressive and often occult nature of this malignancy. Liquid biopsies are attractive, as they offer a minimally invasive and cost-effective approach when compared to traditional biopsy methods and imaging modalities used for diagnosis and surveillance. Carbohydrate antigen (CA) 19-9 is currently the most commonly used serum protein biomarker for the diagnosis and monitoring of patients with PDAC, but due to its sensitivity and specificity, its utility remains limited. In this review, we examine how circulating protein biomarkers are used in the diagnosis, prognostication, and surveillance of PDAC. We also highlight protein biomarkers that are currently under investigation that have the potential to enhance our ability to detect early-stage malignancies, predict response to therapy, and monitor for recurrence, but these markers require larger prospective validation studies before they can be widely implemented. Continued efforts to identify and validate novel biomarkers will be crucial for improving the management and outcomes of patients with this challenging disease.
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Affiliation(s)
- Caitlin P. Sok
- Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Karunesh Polireddy
- Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA
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2
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Álvarez-Hilario LG, Salmerón-Bárcenas EG, Ávila-López PA, Hernández-Montes G, Aréchaga-Ocampo E, Herrera-Goepfert R, Albores-Saavedra J, Manzano-Robleda MDC, Saldívar-Cerón HI, Martínez-Frías SP, Thompson-Bonilla MDR, Vargas M, Hernández-Rivas R. Circulating miRNAs as Noninvasive Biomarkers for PDAC Diagnosis and Prognosis in Mexico. Int J Mol Sci 2023; 24:15193. [PMID: 37894871 PMCID: PMC10607652 DOI: 10.3390/ijms242015193] [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: 08/09/2023] [Revised: 09/20/2023] [Accepted: 10/08/2023] [Indexed: 10/29/2023] Open
Abstract
Among malignant neoplasms, pancreatic ductal adenocarcinoma (PDAC) has one of the highest fatality rates due to its late detection. Therefore, it is essential to discover a noninvasive, early, specific, and sensitive diagnostic method. MicroRNAs (miRNAs) are attractive biomarkers because they are accessible, highly specific, and sensitive. It is crucial to find miRNAs that could be used as possible biomarkers because PDAC is the eighth most common cause of cancer death in Mexico. With the help of microRNA microarrays, differentially expressed miRNAs (DEmiRNAs) were found in PDAC tissues. The presence of these DEmiRNAs in the plasma of Mexican patients with PDAC was determined using RT-qPCR. Receiver operating characteristic curve analysis was performed to determine the diagnostic capacity of these DEmiRNAs. Gene Expression Omnibus datasets (GEO) were employed to verify our results. The Prisma V8 statistical analysis program was used. Four DEmiRNAs in plasma from PDAC patients and microarray tissues were found. Serum samples from patients with PDAC were used to validate their overexpression in GEO databases. We discovered a new panel of the two miRNAs miR-222-3p and miR-221-3p that could be used to diagnose PDAC, and when miR-221-3p and miR-222-3p were overexpressed, survival rates decreased. Therefore, miR-222-3p and miR-221-3p might be employed as noninvasive indicators for the diagnosis and survival of PDAC in Mexican patients.
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Affiliation(s)
- Lissuly Guadalupe Álvarez-Hilario
- Departamento de Biomedicina Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de Mexico C.P. 07360, Mexico; (L.G.Á.-H.); (E.G.S.-B.); (P.A.Á.-L.); (H.I.S.-C.); (M.V.)
| | - Eric Genaro Salmerón-Bárcenas
- Departamento de Biomedicina Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de Mexico C.P. 07360, Mexico; (L.G.Á.-H.); (E.G.S.-B.); (P.A.Á.-L.); (H.I.S.-C.); (M.V.)
| | - Pedro Antonio Ávila-López
- Departamento de Biomedicina Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de Mexico C.P. 07360, Mexico; (L.G.Á.-H.); (E.G.S.-B.); (P.A.Á.-L.); (H.I.S.-C.); (M.V.)
| | - Georgina Hernández-Montes
- Coordinación de la Investigación Científica, Red de Apoyo a la Investigación, Universidad Nacional Autónoma de México, Ciudad Universitaria, Ciudad de Mexico C.P. 14080, Mexico;
| | - Elena Aréchaga-Ocampo
- Departamento de Ciencias Naturales, Universidad Autónoma Metropolitana, Unidad Cuajimalpa, Ciudad de Mexico C.P. 05300, Mexico;
| | - Roberto Herrera-Goepfert
- Departamento de Patología, Instituto Nacional de Cancerología, Ciudad de Mexico C.P. 14080, Mexico;
| | - Jorge Albores-Saavedra
- Departamento de Patología, Medica Sur Clínica y Fundación, Ciudad de Mexico C.P. 14050, Mexico;
| | | | - Héctor Iván Saldívar-Cerón
- Departamento de Biomedicina Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de Mexico C.P. 07360, Mexico; (L.G.Á.-H.); (E.G.S.-B.); (P.A.Á.-L.); (H.I.S.-C.); (M.V.)
| | - Sandra Paola Martínez-Frías
- Departamento de Infectología, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (INCMNSZ), Avenida Vasco de Quiroga No.15, Colonia Belisario Domínguez Sección XVI, Ciudad de Mexico C.P. 14080, Mexico
| | | | - Miguel Vargas
- Departamento de Biomedicina Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de Mexico C.P. 07360, Mexico; (L.G.Á.-H.); (E.G.S.-B.); (P.A.Á.-L.); (H.I.S.-C.); (M.V.)
| | - Rosaura Hernández-Rivas
- Departamento de Biomedicina Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de Mexico C.P. 07360, Mexico; (L.G.Á.-H.); (E.G.S.-B.); (P.A.Á.-L.); (H.I.S.-C.); (M.V.)
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Marin AM, Batista M, Korte de Azevedo AL, Bombardelli Gomig TH, Soares Caldeira Brant R, Chammas R, Uno M, Dias Araújo D, Zanette DL, Nóbrega Aoki M. Screening of Exosome-Derived Proteins and Their Potential as Biomarkers in Diagnostic and Prognostic for Pancreatic Cancer. Int J Mol Sci 2023; 24:12604. [PMID: 37628784 PMCID: PMC10454563 DOI: 10.3390/ijms241612604] [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: 06/17/2023] [Revised: 07/11/2023] [Accepted: 07/18/2023] [Indexed: 08/27/2023] Open
Abstract
In the oncological area, pancreatic cancer is one of the most lethal diseases, with 5-year survival rising just 10% in high-development countries. This disease is genetically characterized by KRAS as a driven mutation followed by SMAD4, CDKN2, and TP53-associated mutations. In clinical aspects, pancreatic cancer presents unspecific clinical symptoms with the absence of screening and early plasmatic biomarker, being that CA19-9 is the unique plasmatic biomarker having specificity and sensitivity limitations. We analyzed the plasmatic exosome proteomic profile of 23 patients with pancreatic cancer and 10 healthy controls by using Nanoscale liquid chromatography coupled to tandem mass spectrometry (NanoLC-MS/MS). The pancreatic cancer patients were subdivided into IPMN and PDAC. Our findings show 33, 34, and 7 differentially expressed proteins when comparing the IPMN vs. control, PDAC-No treatment vs. control, and PDAC-No treatment vs. IPMN groups, highlighting proteins of the complement system and coagulation, such as C3, APOB, and SERPINA. Additionally, PDAC with no treatment showed 11 differentially expressed proteins when compared to Folfirinox neoadjuvant therapy or Gemcitabine adjuvant therapy. So here, we found plasmatic exosome-derived differentially expressed proteins among cancer patients (IPMN, PDAC) when comparing with healthy controls, which could represent alternative biomarkers for diagnostic and prognostic evaluation, supporting further scientific and clinical studies on pancreatic cancer.
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Affiliation(s)
- Anelis Maria Marin
- Laboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Curitiba 81350-010, Brazil; (A.M.M.); (M.B.); (D.L.Z.)
| | - Michel Batista
- Laboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Curitiba 81350-010, Brazil; (A.M.M.); (M.B.); (D.L.Z.)
- Mass Spectrometry Facility RPT02H, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Curitiba 81350-010, Brazil
| | - Alexandre Luiz Korte de Azevedo
- Laboratory of Human Cytogenetics and Oncogenetics, Genetic Department, University of Parana State (UFPR), Curitiba 80060-000, Brazil; (A.L.K.d.A.); (T.H.B.G.)
| | - Talita Helen Bombardelli Gomig
- Laboratory of Human Cytogenetics and Oncogenetics, Genetic Department, University of Parana State (UFPR), Curitiba 80060-000, Brazil; (A.L.K.d.A.); (T.H.B.G.)
| | - Rodrigo Soares Caldeira Brant
- Mass Spectrometry Facility RPT02H, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Curitiba 81350-010, Brazil
| | - Roger Chammas
- Center for Translational Research in Oncology (LIM24), Instituto do Cancer do Estado de Sao Paulo (ICESP), Hospital das Clinicas da Faculdade de Medicina da Universidade de Sao Paulo (HCFMUSP), Comprehensive Center for Precision Oncology (C2PO), Universidade de São Paulo, São Paulo 05508-220, Brazil; (R.C.); (M.U.); (D.D.A.)
| | - Miyuki Uno
- Center for Translational Research in Oncology (LIM24), Instituto do Cancer do Estado de Sao Paulo (ICESP), Hospital das Clinicas da Faculdade de Medicina da Universidade de Sao Paulo (HCFMUSP), Comprehensive Center for Precision Oncology (C2PO), Universidade de São Paulo, São Paulo 05508-220, Brazil; (R.C.); (M.U.); (D.D.A.)
| | - Diogo Dias Araújo
- Center for Translational Research in Oncology (LIM24), Instituto do Cancer do Estado de Sao Paulo (ICESP), Hospital das Clinicas da Faculdade de Medicina da Universidade de Sao Paulo (HCFMUSP), Comprehensive Center for Precision Oncology (C2PO), Universidade de São Paulo, São Paulo 05508-220, Brazil; (R.C.); (M.U.); (D.D.A.)
| | - Dalila Luciola Zanette
- Laboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Curitiba 81350-010, Brazil; (A.M.M.); (M.B.); (D.L.Z.)
| | - Mateus Nóbrega Aoki
- Laboratory for Applied Science and Technology in Health, Carlos Chagas Institute, Oswaldo Cruz Foundation (Fiocruz), Curitiba 81350-010, Brazil; (A.M.M.); (M.B.); (D.L.Z.)
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Mazer BL, Lee JW, Roberts NJ, Chu LC, Lennon AM, Klein AP, Eshleman JR, Fishman EK, Canto MI, Goggins MG, Hruban RH. Screening for pancreatic cancer has the potential to save lives, but is it practical? Expert Rev Gastroenterol Hepatol 2023; 17:555-574. [PMID: 37212770 PMCID: PMC10424088 DOI: 10.1080/17474124.2023.2217354] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 04/21/2023] [Accepted: 05/19/2023] [Indexed: 05/23/2023]
Abstract
INTRODUCTION Most patients with pancreatic cancer present with advanced stage, incurable disease. However, patients with high-grade precancerous lesions and many patients with low-stage disease can be cured with surgery, suggesting that early detection has the potential to improve survival. While serum CA19.9 has been a long-standing biomarker used for pancreatic cancer disease monitoring, its low sensitivity and poor specificity have driven investigators to hunt for better diagnostic markers. AREAS COVERED This review will cover recent advances in genetics, proteomics, imaging, and artificial intelligence, which offer opportunities for the early detection of curable pancreatic neoplasms. EXPERT OPINION From exosomes, to circulating tumor DNA, to subtle changes on imaging, we know much more now about the biology and clinical manifestations of early pancreatic neoplasia than we did just five years ago. The overriding challenge, however, remains the development of a practical approach to screen for a relatively rare, but deadly, disease that is often treated with complex surgery. It is our hope that future advances will bring us closer to an effective and financially sound approach for the early detection of pancreatic cancer and its precursors.
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Affiliation(s)
- Benjamin L. Mazer
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jae W. Lee
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
| | - Nicholas J. Roberts
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Linda C. Chu
- Department of Radiology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anne Marie Lennon
- Department of Medicine, Division of Gastroenterology and Hepatology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alison P. Klein
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - James R. Eshleman
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Elliot K. Fishman
- Department of Radiology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marcia Irene Canto
- Department of Medicine, Division of Gastroenterology and Hepatology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Michael G. Goggins
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ralph H. Hruban
- The Sol Goldman Pancreatic Cancer Research Center, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pathology, the Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, MD, USA
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5
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Lee DH, Yoon W, Lee A, Han Y, Byun Y, Kang JS, Kim H, Kwon W, Suh YA, Choi Y, Namkung J, Han S, Yi SG, Heo JS, Han IW, Park JO, Park JK, Kim SC, Jun E, Kang CM, Lee WJ, Lee HK, Lee H, Lee S, Jeong SY, Lee KE, Han W, Park T, Jang JY. Multi-biomarker panel prediction model for diagnosis of pancreatic cancer. JOURNAL OF HEPATO-BILIARY-PANCREATIC SCIENCES 2023; 30:122-132. [PMID: 33991409 DOI: 10.1002/jhbp.986] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 03/02/2021] [Accepted: 05/02/2021] [Indexed: 01/17/2023]
Abstract
BACKGROUND/PURPOSE The current study aimed to develop a prediction model using a multi-marker panel as a diagnostic screening tool for pancreatic ductal adenocarcinoma. METHODS Multi-center cohort of 1991 blood samples were collected from January 2011 to September 2019, of which 609 were normal, 145 were other cancer (colorectal, thyroid, and breast cancer), 314 were pancreatic benign disease, and 923 were pancreatic ductal adenocarcinoma. The automated multi-biomarker Enzyme-Linked Immunosorbent Assay kit was developed using three potential biomarkers: LRG1, TTR, and CA 19-9. Using a logistic regression model on a training data set, the predicted values for pancreatic ductal adenocarcinoma were obtained, and the result was classification into one of the three risk groups: low, intermediate, and high. The five covariates used to create the model were sex, age, and three biomarkers. RESULTS Participants were categorized into four groups as normal (n = 609), other cancer (n = 145), pancreatic benign disease (n = 314), and pancreatic ductal adenocarcinoma (n = 923). The normal, other cancer, and pancreatic benign disease groups were clubbed into the non-pancreatic ductal adenocarcinoma group (n = 1068). The positive and negative predictive value, sensitivity, and specificity were 94.12, 90.40, 93.81, and 90.86, respectively. CONCLUSIONS This study demonstrates a significant diagnostic performance of the multi-marker panel in distinguishing pancreatic ductal adenocarcinoma from normal and benign pancreatic disease states, as well as patients with other cancers.
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Affiliation(s)
- Doo-Ho Lee
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
- Department of Surgery, Gachon university Gil medical center, Incheon, Korea
| | - Woongchang Yoon
- Bio-MAX/N-Bio Institute, Seoul National University, Seoul, Korea
| | - Areum Lee
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
| | - Youngmin Han
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
| | - Yoonhyeong Byun
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
| | - Jae Seung Kang
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
| | - Hongbeom Kim
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
| | - Wooil Kwon
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
| | - Young-Ah Suh
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
| | - Yonghwan Choi
- Immunodiagnostics R&D Team, IVD Business Unit 5, SK Telecom, Seoul, Korea
| | - Junghyun Namkung
- Immunodiagnostics R&D Team, IVD Business Unit 5, SK Telecom, Seoul, Korea
| | - Sangjo Han
- Immunodiagnostics R&D Team, IVD Business Unit 5, SK Telecom, Seoul, Korea
| | - Sung Gon Yi
- Immunodiagnostics R&D Team, IVD Business Unit 5, SK Telecom, Seoul, Korea
| | - Jin Seok Heo
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - In Woong Han
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Joon Oh Park
- Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Joo Kyung Park
- Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Song Cheol Kim
- Department of Surgery, University of Ulsan College of Medicine and Asan Medical Center, Seoul, Korea
| | - Eunsung Jun
- Department of Surgery, University of Ulsan College of Medicine and Asan Medical Center, Seoul, Korea
| | - Chang Moo Kang
- Department of Surgery, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Woo Jin Lee
- Center for Liver Cancer, National Cancer Center, Seoul, Korea
| | - Hyeon Kook Lee
- Department of Surgery, Ewha Womans University School of Medicine, Seoul, Korea
| | - Huisong Lee
- Department of Surgery, Ewha Womans University School of Medicine, Seoul, Korea
| | - Seungyeoun Lee
- Department of Mathematics and Statistics, Sejong University, Seoul, Korea
| | - Seung-Yong Jeong
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
| | - Kyu Eun Lee
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
| | - Wonshik Han
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
| | - Taesung Park
- Department of Statistics, Seoul National University, Seoul, Korea
| | - Jin-Young Jang
- Department of Surgery and Cancer Research Institute, College of Medicine, Seoul National University, Seoul, Korea
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Charles Jacob HK, Signorelli R, Charles Richard JL, Kashuv T, Lavania S, Middleton A, Gomez BA, Ferrantella A, Amirian H, Tao J, Ergonul AB, Boone MM, Hadisurya M, Tao WA, Iliuk A, Kashyap MK, Garcia-Buitrago M, Dawra R, Saluja AK. Identification of novel early pancreatic cancer biomarkers KIF5B and SFRP2 from “first contact” interactions in the tumor microenvironment. J Exp Clin Cancer Res 2022; 41:258. [PMID: 36002889 PMCID: PMC9400270 DOI: 10.1186/s13046-022-02425-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/23/2022] [Indexed: 12/27/2022] Open
Abstract
Abstract
Background
Pancreatic cancer is one of the most difficult cancers to detect early and most patients die from complications arising due to distant organ metastases. The lack of bona fide early biomarkers is one of the primary reasons for late diagnosis of pancreatic cancer. It is a multifactorial disease and warrants a novel approach to identify early biomarkers.
Methods
In order to characterize the proteome, Extracellular vesicles (EVs) isolated from different in vitro conditions mimicking tumor-microenvironment interactions between pancreatic cancer epithelial and stromal cells were analyzed using high throughput mass spectrometry. The biological activity of the secreted EVome was analyzed by investigating changes in distant organ metastases and associated early changes in the microbiome. Candidate biomarkers (KIF5B, SFRP2, LOXL2, and MMP3) were selected and validated on a mouse-human hybrid Tissue Microarray (TMA) that was specifically generated for this study. Additionally, a human TMA was used to analyze the expression of KIF5B and SFRP2 in progressive stages of pancreatic cancer.
Results
The EVome of co-cultured epithelial and stromal cells is different from individual cells with distinct protein compositions. EVs secreted from stromal and cancer cells cultures could not induce significant changes in Pre-Metastatic Niche (PMN) modulation, which was assessed by changes in the distant organ metastases. However, they did induce significant changes in the early microbiome, as indicated by differences in α and β-diversities. KIF5B and SFRP2 show promise for early detection and investigation in progressive pancreatic cancer. These markers are expressed in all stages of pancreatic cancer such as low grade PanINs, advanced cancer, and in liver and soft tissue metastases.
Conclusions
Proteomic characterization of EVs derived from mimicking conditions of epithelial and stromal cells in the tumor-microenvironment resulted in the identification of several proteins, some for the first time in EVs. These secreted EVs cannot induce changes in distant organ metastases in in vivo models of EV education, but modulate changes in the early murine microbiome. Among all the proteins that were analyzed (MMP3, KIF5B, SFRP2, and LOXL2), KIF5B and SFRP2 show promise as bona fide early pancreatic cancer biomarkers expressed in progressive stages of pancreatic cancer.
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7
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Vellan CJ, Jayapalan JJ, Yoong BK, Abdul-Aziz A, Mat-Junit S, Subramanian P. Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review. Int J Mol Sci 2022; 23:2093. [PMID: 35216204 PMCID: PMC8879036 DOI: 10.3390/ijms23042093] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/07/2022] [Accepted: 01/09/2022] [Indexed: 12/12/2022] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC), a highly aggressive malignancy with a poor prognosis is usually detected at the advanced stage of the disease. The only US Food and Drug Administration-approved biomarker that is available for PDAC, CA 19-9, is most useful in monitoring treatment response among PDAC patients rather than for early detection. Moreover, when CA 19-9 is solely used for diagnostic purposes, it has only a recorded sensitivity of 79% and specificity of 82% in symptomatic individuals. Therefore, there is an urgent need to identify reliable biomarkers for diagnosis (specifically for the early diagnosis), ascertain prognosis as well as to monitor treatment response and tumour recurrence of PDAC. In recent years, proteomic technologies are growing exponentially at an accelerated rate for a wide range of applications in cancer research. In this review, we discussed the current status of biomarker research for PDAC using various proteomic technologies. This review will explore the potential perspective for understanding and identifying the unique alterations in protein expressions that could prove beneficial in discovering new robust biomarkers to detect PDAC at an early stage, ascertain prognosis of patients with the disease in addition to monitoring treatment response and tumour recurrence of patients.
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Affiliation(s)
- Christina Jane Vellan
- Department of Molecular Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia; (C.J.V.); (A.A.-A.); (S.M.-J.)
| | - Jaime Jacqueline Jayapalan
- Department of Molecular Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia; (C.J.V.); (A.A.-A.); (S.M.-J.)
- University of Malaya Centre for Proteomics Research (UMCPR), Universiti Malaya, Kuala Lumpur 50603, Malaysia
| | - Boon-Koon Yoong
- Department of Surgery, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia;
| | - Azlina Abdul-Aziz
- Department of Molecular Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia; (C.J.V.); (A.A.-A.); (S.M.-J.)
| | - Sarni Mat-Junit
- Department of Molecular Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia; (C.J.V.); (A.A.-A.); (S.M.-J.)
| | - Perumal Subramanian
- Department of Biochemistry and Biotechnology, Annamalai University, Chidambaram 608002, Tamil Nadu, India;
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8
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Camilli C, Hoeh AE, De Rossi G, Moss SE, Greenwood J. LRG1: an emerging player in disease pathogenesis. J Biomed Sci 2022; 29:6. [PMID: 35062948 PMCID: PMC8781713 DOI: 10.1186/s12929-022-00790-6] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 01/11/2022] [Indexed: 12/15/2022] Open
Abstract
The secreted glycoprotein leucine-rich α-2 glycoprotein 1 (LRG1) was first described as a key player in pathogenic ocular neovascularization almost a decade ago. Since then, an increasing number of publications have reported the involvement of LRG1 in multiple human conditions including cancer, diabetes, cardiovascular disease, neurological disease, and inflammatory disorders. The purpose of this review is to provide, for the first time, a comprehensive overview of the LRG1 literature considering its role in health and disease. Although LRG1 is constitutively expressed by hepatocytes and neutrophils, Lrg1-/- mice show no overt phenotypic abnormality suggesting that LRG1 is essentially redundant in development and homeostasis. However, emerging data are challenging this view by suggesting a novel role for LRG1 in innate immunity and preservation of tissue integrity. While our understanding of beneficial LRG1 functions in physiology remains limited, a consistent body of evidence shows that, in response to various inflammatory stimuli, LRG1 expression is induced and directly contributes to disease pathogenesis. Its potential role as a biomarker for the diagnosis, prognosis and monitoring of multiple conditions is widely discussed while dissecting the mechanisms underlying LRG1 pathogenic functions. Emphasis is given to the role that LRG1 plays as a vasculopathic factor where it disrupts the cellular interactions normally required for the formation and maintenance of mature vessels, thereby indirectly contributing to the establishment of a highly hypoxic and immunosuppressive microenvironment. In addition, LRG1 has also been reported to affect other cell types (including epithelial, immune, mesenchymal and cancer cells) mostly by modulating the TGFβ signalling pathway in a context-dependent manner. Crucially, animal studies have shown that LRG1 inhibition, through gene deletion or a function-blocking antibody, is sufficient to attenuate disease progression. In view of this, and taking into consideration its role as an upstream modifier of TGFβ signalling, LRG1 is suggested as a potentially important therapeutic target. While further investigations are needed to fill gaps in our current understanding of LRG1 function, the studies reviewed here confirm LRG1 as a pleiotropic and pathogenic signalling molecule providing a strong rationale for its use in the clinic as a biomarker and therapeutic target.
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Affiliation(s)
- Carlotta Camilli
- Institute of Ophthalmology, University College London, London, UK.
| | - Alexandra E Hoeh
- Institute of Ophthalmology, University College London, London, UK
| | - Giulia De Rossi
- Institute of Ophthalmology, University College London, London, UK
| | - Stephen E Moss
- Institute of Ophthalmology, University College London, London, UK
| | - John Greenwood
- Institute of Ophthalmology, University College London, London, UK
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9
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Yang M, Zhang CY. Diagnostic biomarkers for pancreatic cancer: An update. World J Gastroenterol 2021; 27:7862-7865. [PMID: 34963749 PMCID: PMC8661384 DOI: 10.3748/wjg.v27.i45.7862] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 08/10/2021] [Accepted: 11/25/2021] [Indexed: 02/06/2023] Open
Abstract
Pancreatic ductal adenocarcinoma accounts for the primary type of pancreatic cancer (PC) with a 5-year survival rate of only about 10% in the United States. Early diagnosis will improve chances for curative treatment. To date, a broadly used serum marker for PC diagnosis is carbohydrate antigen 19-9, which is the only approved biomarker currently by the United States Food and Drug Administration. However, it has low specificity; therefore, development of novel biomarkers is urgently needed. Clinical trials are ongoing to evaluate candidate biomarkers for PC diagnosis, and the use of a multi-biomarker panel with current PC diagnostic biomarkers appears promising.
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Affiliation(s)
- Ming Yang
- Department of Surgery, University of Missouri, Columbia, MO 65212, United States
| | - Chun-Ye Zhang
- Department of Veterinary Pathobiology, University of Missouri, Columbia, MO 65212, United States
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10
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Kapszewicz M, Małecka-Wojciesko E. Simple Serum Pancreatic Ductal Adenocarcinoma (PDAC) Protein Biomarkers-Is There Anything in Sight? J Clin Med 2021; 10:jcm10225463. [PMID: 34830745 PMCID: PMC8619303 DOI: 10.3390/jcm10225463] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 11/07/2021] [Accepted: 11/20/2021] [Indexed: 01/04/2023] Open
Abstract
A poor PDAC prognosis is due to a lack of effective treatment and late diagnosis. The early detection of PDAC could significantly decrease mortality and save lives. Idealbiomarkers for PDAC should be cost-effective, detectable in easily accessible biological material, and present in sufficient concentration in the earliest possible phase of the disease. This review addresses newly selected, simple protein biomarkers—new ones such as thrombospondin-2, insulin-linked binding protein 2, lysophosphatidic acid, and autotaxin and conventional ones such as Ca19-9, inflammatory factors, and coagulation factors. Their possible use in the early detection of PDAC, differentiation from benign diseases, prognosis, and treatment response prediction is discussed. We also address the usefulness of possible combinations of biomarkers in diagnostic panels.
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11
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Non-Invasive Biomarkers for Earlier Detection of Pancreatic Cancer-A Comprehensive Review. Cancers (Basel) 2021; 13:cancers13112722. [PMID: 34072842 PMCID: PMC8198035 DOI: 10.3390/cancers13112722] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 05/20/2021] [Accepted: 05/27/2021] [Indexed: 12/24/2022] Open
Abstract
Simple Summary Pancreatic ductal adenocarcinoma (PDAC), which represents approximately 90% of all pancreatic cancers, is an extremely aggressive and lethal disease. It is considered a silent killer due to a largely asymptomatic course and late clinical presentation. Earlier detection of the disease would likely have a great impact on changing the currently poor survival figures for this malignancy. In this comprehensive review, we assessed over 4000 reports on non-invasive PDAC biomarkers in the last decade. Applying the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool, we selected and reviewed in more detail 49 relevant studies reporting on the most promising candidate biomarkers. In addition, we also highlight the present challenges and complexities of translating novel biomarkers into clinical use. Abstract Pancreatic ductal adenocarcinoma (PDAC) carries a deadly diagnosis, due in large part to delayed presentation when the disease is already at an advanced stage. CA19-9 is currently the most commonly utilized biomarker for PDAC; however, it lacks the necessary accuracy to detect precursor lesions or stage I PDAC. Novel biomarkers that could detect this malignancy with improved sensitivity (SN) and specificity (SP) would likely result in more curative resections and more effective therapeutic interventions, changing thus the present dismal survival figures. The aim of this study was to systematically and comprehensively review the scientific literature on non-invasive biomarkers in biofluids such as blood, urine and saliva that were attempting earlier PDAC detection. The search performed covered a period of 10 years (January 2010—August 2020). Data were extracted using keywords search in the three databases: MEDLINE, Web of Science and Embase. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied for study selection based on establishing the risk of bias and applicability concerns in Patient Selection, Index test (biomarker assay) and Reference Standard (standard-of-care diagnostic test). Out of initially over 4000 published reports, 49 relevant studies were selected and reviewed in more detail. In addition, we discuss the present challenges and complexities in the path of translating the discovered biomarkers into the clinical setting. Our systematic review highlighted several promising biomarkers that could, either alone or in combination with CA19-9, potentially improve earlier detection of PDAC. Overall, reviewed biomarker studies should aim to improve methodological and reporting quality, and novel candidate biomarkers should be investigated further in order to demonstrate their clinical usefulness. However, challenges and complexities in the path of translating the discovered biomarkers from the research laboratory to the clinical setting remain and would have to be addressed before a more realistic breakthrough in earlier detection of PDAC is achieved.
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12
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Lindgaard SC, Sztupinszki Z, Maag E, Chen IM, Johansen AZ, Jensen BV, Bojesen SE, Nielsen DL, Hansen CP, Hasselby JP, Nielsen KR, Szallasi Z, Johansen JS. Circulating Protein Biomarkers for Use in Pancreatic Ductal Adenocarcinoma Identification. Clin Cancer Res 2021; 27:2592-2603. [PMID: 33737308 DOI: 10.1158/1078-0432.ccr-20-4215] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 01/07/2021] [Accepted: 03/03/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal solid tumors. Most patients are diagnosed at an advanced stage where curative surgery is not an option. The aim of this study was to identify a panel of circulating proteins that could distinguish patients with PDAC from non-PDAC individuals. EXPERIMENTAL DESIGN We investigated 92 proteins known to be involved in inflammation, development, and progression of PDAC using the Olink immuno-oncology panel in serum samples from 701 patients with PDAC (stage I-IV), 102 patients with nonmalignant pancreatic diseases, and 180 healthy blood donors. Patients were included prospectively between 2008 and 2018. Plasma carbohydrate antigen 19-9 (CA19-9) was measured in all samples. The protein panels with the best diagnostic performances were developed by two bioinformaticians working independently, using LASSO and Ridge regression models. RESULTS Two panels of proteins (index I, containing 9 proteins + CA19-9, and index II, containing 23 proteins + CA19-9) were identified. Index I was able to discriminate patients with PDAC from all patients with non-PDAC, with a ROC AUC value of 0.92 [95% confidence interval (CI), 0.89-0.96] in the discovery cohort and 0.92 (95% CI, 0.87-0.97) in the replication cohort. For index II, the AUC value was 0.96 (95% CI, 0.95-0.98) in the discovery cohort and 0.93 (95% CI, 0.90-0.96) in the replication cohort. All nine serum proteins of index I were found in index II. CONCLUSIONS This study identified two circulating protein indices with the potential to discriminate between individuals with and without PDAC.
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Affiliation(s)
- Sidsel C Lindgaard
- Department of Oncology, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.
| | | | | | - Inna M Chen
- Department of Oncology, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Astrid Z Johansen
- Department of Oncology, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Benny V Jensen
- Department of Oncology, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Stig E Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Dorte L Nielsen
- Department of Oncology, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Carsten P Hansen
- Department of Surgery, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Jane P Hasselby
- Department of Pathology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Kaspar R Nielsen
- Department of Clinical Immunology, Aalborg University Hospital, Aalborg, Denmark
| | - Zoltan Szallasi
- Danish Cancer Society Research Center, Copenhagen, Denmark
- Computational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Julia S Johansen
- Department of Oncology, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Medicine, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
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13
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Clinical Perspective on Proteomic and Glycomic Biomarkers for Diagnosis, Prognosis, and Prediction of Pancreatic Cancer. Int J Mol Sci 2021; 22:ijms22052655. [PMID: 33800786 PMCID: PMC7961509 DOI: 10.3390/ijms22052655] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 02/26/2021] [Accepted: 03/02/2021] [Indexed: 02/07/2023] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is known as a highly aggressive malignant disease. Prognosis for patients is notoriously poor, despite improvements in surgical techniques and new (neo)adjuvant chemotherapy regimens. Early detection of PDAC may increase the overall survival. It is furthermore foreseen that precision medicine will provide improved prognostic stratification and prediction of therapeutic response. In this review, omics-based discovery efforts are presented that aim for novel diagnostic and prognostic biomarkers of PDAC. For this purpose, we systematically evaluated the literature published between 1999 and 2020 with a focus on protein- and protein-glycosylation biomarkers in pancreatic cancer patients. Besides genomic and transcriptomic approaches, mass spectrometry (MS)-based proteomics and glycomics of blood- and tissue-derived samples from PDAC patients have yielded new candidates with biomarker potential. However, for reasons discussed in this review, the validation and clinical translation of these candidate markers has not been successful. Consequently, there has been a change of mindset from initial efforts to identify new unimarkers into the current hypothesis that a combination of biomarkers better suits a diagnostic or prognostic panel. With continuing development of current research methods and available techniques combined with careful study designs, new biomarkers could contribute to improved detection, prognosis, and prediction of pancreatic cancer.
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14
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Choi YJ, Yoon W, Lee A, Han Y, Byun Y, Kang JS, Kim H, Kwon W, Suh YA, Kim Y, Lee S, Namkung J, Han S, Choi Y, Heo JS, Park JO, Park JK, Kim SC, Kang CM, Lee WJ, Park T, Jang JY. Diagnostic model for pancreatic cancer using a multi-biomarker panel. Ann Surg Treat Res 2021; 100:144-153. [PMID: 33748028 PMCID: PMC7943279 DOI: 10.4174/astr.2021.100.3.144] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 12/06/2020] [Accepted: 12/11/2020] [Indexed: 12/28/2022] Open
Abstract
Purpose Diagnostic biomarkers of pancreatic ductal adenocarcinoma (PDAC) have been used for early detection to reduce its dismal survival rate. However, clinically feasible biomarkers are still rare. Therefore, in this study, we developed an automated multi-marker enzyme-linked immunosorbent assay (ELISA) kit using 3 biomarkers (leucine-rich alpha-2-glycoprotein [LRG1], transthyretin [TTR], and CA 19-9) that were previously discovered and proposed a diagnostic model for PDAC based on this kit for clinical usage. Methods Individual LRG1, TTR, and CA 19-9 panels were combined into a single automated ELISA panel and tested on 728 plasma samples, including PDAC (n = 381) and normal samples (n = 347). The consistency between individual panels of 3 biomarkers and the automated multi-panel ELISA kit were accessed by correlation. The diagnostic model was developed using logistic regression according to the automated ELISA kit to predict the risk of pancreatic cancer (high-, intermediate-, and low-risk groups). Results The Pearson correlation coefficient of predicted values between the triple-marker automated ELISA panel and the former individual ELISA was 0.865. The proposed model provided reliable prediction results with a positive predictive value of 92.05%, negative predictive value of 90.69%, specificity of 90.69%, and sensitivity of 92.05%, which all simultaneously exceed 90% cutoff value. Conclusion This diagnostic model based on the triple ELISA kit showed better diagnostic performance than previous markers for PDAC. In the future, it needs external validation to be used in the clinic.
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Affiliation(s)
- Yoo Jin Choi
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Woongchang Yoon
- Bio-MAX/N-Bio Institute, Seoul National University, Seoul, Korea
| | - Areum Lee
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Youngmin Han
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Yoonhyeong Byun
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Jae Seung Kang
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Hongbeom Kim
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Wooil Kwon
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Young-Ah Suh
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
| | - Yongkang Kim
- Department of Statistics, Seoul National University, Seoul, Korea
| | - Seungyeoun Lee
- Department of Applied Mathematics, Sejong University, Seoul, Korea
| | | | - Sangjo Han
- Data Labs, AI Center, SK Telecom, Seoul, Korea
| | | | - Jin Seok Heo
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Joon Oh Park
- Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Joo Kyung Park
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Suwon, Korea.,Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea
| | - Song Cheol Kim
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Korea
| | - Chang Moo Kang
- Department of Surgery, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Woo Jin Lee
- Center for Liver Cancer, National Cancer Center, Seoul, Korea
| | - Taesung Park
- Department of Statistics, Seoul National University, Seoul, Korea
| | - Jin-Young Jang
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea
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15
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Son M, Kim H, Han D, Kim Y, Huh I, Han Y, Hong SM, Kwon W, Kim H, Jang JY, Kim Y. A Clinically Applicable 24-Protein Model for Classifying Risk Subgroups in Pancreatic Ductal Adenocarcinomas using Multiple Reaction Monitoring-Mass Spectrometry. Clin Cancer Res 2021; 27:3370-3382. [PMID: 33593883 DOI: 10.1158/1078-0432.ccr-20-3513] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 01/12/2021] [Accepted: 02/12/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE Pancreatic ductal adenocarcinoma (PDAC) subtypes have been identified using various methodologies. However, it is a challenge to develop classification system applicable to routine clinical evaluation. We aimed to identify risk subgroups based on molecular features and develop a classification model that was more suited for clinical applications. EXPERIMENTAL DESIGN We collected whole dissected specimens from 225 patients who underwent surgery at Seoul National University Hospital [Seoul, Republic of Korea (South)], between October 2009 and February 2018. Target proteins with potential relevance to tumor progression or prognosis were quantified with robust quality controls. We used hierarchical clustering analysis to identify risk subgroups. A random forest classification model was developed to predict the identified risk subgroups, and the model was validated using transcriptomic datasets from external cohorts (N = 700), with survival analysis. RESULTS We identified 24 protein features that could classify the four risk subgroups associated with patient outcomes: stable, exocrine-like; activated, and extracellular matrix (ECM) remodeling. The "stable" risk subgroup was characterized by proteins that were associated with differentiation and tumor suppressors. "Exocrine-like" tumors highly expressed pancreatic enzymes. Two high-risk subgroups, "activated" and "ECM remodeling," were enriched in terms such as cell cycle, angiogenesis, immunocompetence, tumor invasion metastasis, and metabolic reprogramming. The classification model that included these features made prognoses with relative accuracy and precision in multiple cohorts. CONCLUSIONS We proposed PDAC risk subgroups and developed a classification model that may potentially be useful for routine clinical implementations, at the individual level. This clinical system may improve the accuracy of risk prediction and treatment guidelines.See related commentary by Thakur and Singh, p. 3272.
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Affiliation(s)
- Minsoo Son
- Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Hongbeom Kim
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Dohyun Han
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea (South)
| | - Yoseop Kim
- Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Iksoo Huh
- College of Nursing and Research Institute of Nursing Science, Seoul National University, Seoul, Republic of Korea (South)
| | - Youngmin Han
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Seung-Mo Hong
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea (South)
| | - Wooil Kwon
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Haeryoung Kim
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea (South)
| | - Jin-Young Jang
- Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea (South).
| | - Youngsoo Kim
- Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Republic of Korea (South).
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16
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Kim Y, Yeo I, Huh I, Kim J, Han D, Jang JY, Kim Y. Development and Multiple Validation of the Protein Multi-marker Panel for Diagnosis of Pancreatic Cancer. Clin Cancer Res 2021; 27:2236-2245. [PMID: 33504556 DOI: 10.1158/1078-0432.ccr-20-3929] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 12/22/2020] [Accepted: 01/21/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE To develop and validate a protein-based, multi-marker panel that provides superior pancreatic ductal adenocarcinoma (PDAC) detection abilities with sufficient diagnostic performance. EXPERIMENTAL DESIGN A total of 959 plasma samples from patients at multiple medical centers were used. To construct an optimal, diagnostic, multi-marker panel, we applied data preprocessing procedure to biomarker candidates. The multi-marker panel was developed using a training set comprised of 261 PDAC cases and 290 controls. Subsequent evaluations were performed in a validation set comprised of 65 PDAC cases and 72 controls. Further validation was performed in an independent set comprised of 75 PDAC cases and 47 controls. RESULTS A multi-marker panel containing 14 proteins was developed. The multi-marker panel achieved AUCs of 0.977 and 0.953 for the training set and validation set, respectively. In an independent validation set, the multi-marker panel yielded an AUC of 0.928. The diagnostic performance of the multi-marker panel showed significant improvements compared with carbohydrate antigen (CA) 19-9 alone (training set AUC = 0.977 vs. 0.872, P < 0.001; validation set AUC = 0.953 vs. 0.832, P < 0.01; independent validation set AUC = 0.928 vs. 0.771, P < 0.001). When the multi-marker panel and CA 19-9 were combined, the diagnostic performance of the combined panel was improved for all sets. CONCLUSIONS This multi-marker panel and the combined panel showed statistically significant improvements in diagnostic performance compared with CA 19-9 alone and has the potential to complement CA 19-9 as a diagnostic marker in clinical practice.
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Affiliation(s)
- Yoseop Kim
- Interdisciplinary Program in Bioengineering, Seoul National University, College of Engineering, Seoul, Republic of South Korea
| | - Injoon Yeo
- Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University College of Medicine, Seoul, Republic of South Korea
| | - Iksoo Huh
- College of Nursing and Research Institute of Nursing Science, Seoul National University, Seoul, Republic of South Korea
| | - Jaenyeon Kim
- Interdisciplinary Program in Bioengineering, Seoul National University, College of Engineering, Seoul, Republic of South Korea
| | - Dohyun Han
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of South Korea
| | - Jin-Young Jang
- Department of Surgery, Seoul National University College of Medicine, Seoul, Republic of South Korea.
| | - Youngsoo Kim
- Interdisciplinary Program in Bioengineering, Seoul National University, College of Engineering, Seoul, Republic of South Korea. .,Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University College of Medicine, Seoul, Republic of South Korea.,Institute of Bioengineering, Seoul National University, Seoul, Republic of South Korea
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17
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Zhang WH, Wang WQ, Han X, Gao HL, Li TJ, Xu SS, Li S, Xu HX, Li H, Ye LY, Lin X, Wu CT, Long J, Yu XJ, Liu L. Advances on diagnostic biomarkers of pancreatic ductal adenocarcinoma: A systems biology perspective. Comput Struct Biotechnol J 2020; 18:3606-3614. [PMID: 33304458 PMCID: PMC7710502 DOI: 10.1016/j.csbj.2020.11.018] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 11/08/2020] [Accepted: 11/10/2020] [Indexed: 12/26/2022] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy that is usually diagnosed at an advanced stage when curative surgery is no longer an option. Robust diagnostic biomarkers with high sensitivity and specificity for early detection are urgently needed. Systems biology provides a powerful tool for understanding diseases and solving challenging biological problems, allowing biomarkers to be identified and quantified with increasing accuracy, sensitivity, and comprehensiveness. Here, we present a comprehensive overview of efforts to identify biomarkers of PDAC using genomics, transcriptomics, proteomics, metabonomics, and bioinformatics. Systems biology perspective provides a crucial “network” to integrate multi-omics approaches to biomarker identification, shedding additional light on early PDAC detection.
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Affiliation(s)
- Wu-Hu Zhang
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Wen-Quan Wang
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Xuan Han
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - He-Li Gao
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Tian-Jiao Li
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Shuai-Shuai Xu
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Shuo Li
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Hua-Xiang Xu
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Hao Li
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Long-Yun Ye
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Xuan Lin
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Chun-Tao Wu
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Jiang Long
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Xian-Jun Yu
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
| | - Liang Liu
- Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.,Shanghai Pancreatic Cancer Institute, Shanghai, China.,Pancreatic Cancer Institute, Fudan University, Shanghai, China
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18
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O'Rourke MB, Sahni S, Samra J, Mittal A, Molloy MP. Data independent acquisition of plasma biomarkers of response to neoadjuvant chemotherapy in pancreatic ductal adenocarcinoma. J Proteomics 2020; 231:103998. [PMID: 33027703 DOI: 10.1016/j.jprot.2020.103998] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 08/18/2020] [Accepted: 09/29/2020] [Indexed: 02/07/2023]
Abstract
The detection of disease-related plasma biomarkers has challenged the proteomic community for years. Attractive features for plasma proteomics includes the ease of collection and small volume needed for analysis, but on the other hand, the presence of highly abundant proteins complicates sample preparation procedures and reduces dynamic range. Data independent acquisition label free quantitation (DIA-LFQ) by mass spectrometry partly overcomes the dynamic range issue; however, generating the peptide spectral reference libraries that allow extensive analysis of the plasma proteome can be a slow and expensive task which is unattainable for many laboratories. We investigated the re-purposing of publically available plasma proteome datasets and the impact on peptide/protein detection for DIA-LFQ. We carried out these studies in the context of identifying putative biomarkers of response to neoadjuvant chemotherapy (NAC) for pancreatic ductal adenocarcinoma, as no useful plasma biomarkers have been clinically adopted. We demonstrated the benefit in searching DIA data against multiple spectral libraries to show that complement proteins were linked to NAC response in PDAC patients, confirming previous observations of the prognostic utility of complement following adjuvant chemotherapy. Our workflow demonstrates that DIA-LFQ can be readily applied in the oncology setting for the putative assignment of clinically relevant plasma biomarkers. STATEMENT OF SIGNIFICANCE: The proteomic mass spectrometry analysis of undepleted, unfractionated human plasma has benefits for sample throughput but remains challenging to obtain deep coverage. This work evaluated the re-purposing of open source peptide mass spectrometry data from human plasma to create spectral reference libraries for use in Data independent acquisition (DIA). We showed how seeding in locally acquired data to integrate iRT peptides into spectral libraries increased identification confidence by facilitating querying of multiple libraries. This workflow was applied to the discovery of putative plasma biomarkers for response to neoadjuvant chemotherapy (NAC) in pancreatic ductal adenocarcinoma patients. There is a paucity of prior information in the literature on this topic and we show that good responder patients have reduced levels of complement proteins.
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Affiliation(s)
- Matthew B O'Rourke
- Bowel Cancer and Biomarker Laboratory, Kolling Institute, Royal North Shore Hospital, The University of Sydney, Australia
| | - Sumit Sahni
- Bill Walsh Translational Cancer Laboratory, Kolling Institute, Royal North Shore Hospital, The University of Sydney, Australia
| | - Jaswinder Samra
- Upper GI Surgical Unit, Royal North Shore Hospital, Sydney, Australia
| | - Anubhav Mittal
- Upper GI Surgical Unit, Royal North Shore Hospital, Sydney, Australia
| | - Mark P Molloy
- Bowel Cancer and Biomarker Laboratory, Kolling Institute, Royal North Shore Hospital, The University of Sydney, Australia.
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19
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Ma J, Sun S, Song C, Li N, Li N, Xu L, Yang T, Lan Y, Li M. Screening potential microRNAs associated with pancreatic cancer: Data mining based on RNA sequencing and microarrays. Exp Ther Med 2020; 20:2705-2715. [PMID: 32765765 PMCID: PMC7401655 DOI: 10.3892/etm.2020.8991] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 01/17/2020] [Indexed: 02/07/2023] Open
Abstract
Pancreatic cancer is a malignant tumor of the digestive tract, rendering it difficult to make an accurate diagnosis. The 5 year survival rate for pancreatic cancer is <1%, and surgical resection rarely proves to be effective. Therefore, the identification of more effective methods for the early detection of pancreatic cancer is an urgent requirement. The present study aimed to explore key genes and microRNAs (miRNAs) associated with the pathogenesis of pancreatic cancer. Public databases were searched, and the data were integrated from The Cancer Genome Atlas and Gene Expression Omnibus databases, leading to the identification of 23 differentially expressed miRNAs (DE-miRNAs). A total of four of the DE-miRNAs were upregulated (hsa-miR-892b, hsa-miR-194-2, hsa-miR-200a and hsa-miR-194-1), whereas 19 downregulated DE-miRNAs (hsa-miR-424, hsa-miR-191, hsa-miR-484, hsa-miR-142, hsa-miR-15b, hsa-miR-450a-1, hsa-miR-423, hsa-miR-126, hsa-miR-505, hsa-miR-16-1, hsa-miR-342, hsa-miR-130a, hsa-miR-3613, hsa-miR-450a-2, hsa-miR-26b, hsa-miR-451, hsa-miR-19b-2, hsa-miR-106a and hsa-miR-503) were identified using the cut-off criteria of P<0.05 and |log 2FC|>1.0. Hsa-miR-3613-5p was identified as a prognostic DE-miRNA. The functional enrichment analyses demonstrated that the target genes of hsa-miR-3613-5p may be associated with the p53 signaling pathway. Survival analysis performed for genes in the p53 signaling pathway revealed that cyclin-dependent kinase 6 and ribonucleoside-diphosphate reductase subunit M2 may be the most likely to be associated with prognostic value. The integrated analysis performed in the current study demonstrated that hsa-miR-3613-5p may be used as a potential prognostic marker for pancreatic cancer.
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Affiliation(s)
- Jing Ma
- Department of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China
| | - Siwen Sun
- Department of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China
| | - Chen Song
- Department of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China
| | - Ning Li
- Department of Foreign Languages, Dalian Medical University, Dalian, Liaoning 116023, P.R. China
| | - Na Li
- Department of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China
| | - Lingzhi Xu
- Department of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China
| | - Ting Yang
- Department of Neurosurgery, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China
| | - Yulong Lan
- Department of Neurosurgery, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China
| | - Man Li
- Department of Oncology, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning 116023, P.R. China
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20
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Meleady P, Abdul Rahman R, Henry M, Moriarty M, Clynes M. Proteomic analysis of pancreatic ductal adenocarcinoma. Expert Rev Proteomics 2020; 17:453-467. [PMID: 32755290 DOI: 10.1080/14789450.2020.1803743] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
INTRODUCTION Pancreatic ductal adenocarcinoma (PDAC), which represents approximately 80% of all pancreatic cancers, is a highly aggressive malignant disease and one of the most lethal among all cancers. Overall, the 5-year survival rate among all pancreatic cancer patients is less than 9%; these rates have shown little change over the past 30 years. A more comprehensive understanding of the molecular mechanisms underlying this complex disease is crucial to the development of new diagnostic tools for early detection and disease monitoring, as well as to identify new and more effective therapeutics to improve patient outcomes. AREA COVERED We summarize recent advances in proteomic strategies and mass spectrometry to identify new biomarkers for early detection and monitoring of disease progression, predict response to therapy, and to identify novel proteins that have the potential to be 'druggable' therapeutic targets. An overview of proteomic studies that have been conducted to further our mechanistic understanding of metastasis and chemotherapy resistance in PDAC disease progression will also be discussed. EXPERT COMMENTARY The results from these PDAC proteomic studies on a variety of PDAC sample types (e.g., blood, tissue, cell lines, exosomes, etc.) provide great promise of having a significant clinical impact and improving patient outcomes.
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Affiliation(s)
- Paula Meleady
- National Institute for Cellular Biotechnology, Dublin City University , Dublin, Ireland
| | - Rozana Abdul Rahman
- St. Vincent's University Hospital , Dublin, Ireland.,St. Luke's Hospital , Dublin, Ireland
| | - Michael Henry
- National Institute for Cellular Biotechnology, Dublin City University , Dublin, Ireland
| | - Michael Moriarty
- National Institute for Cellular Biotechnology, Dublin City University , Dublin, Ireland.,St. Luke's Hospital , Dublin, Ireland
| | - Martin Clynes
- National Institute for Cellular Biotechnology, Dublin City University , Dublin, Ireland
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21
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Peng H, Pan S, Yan Y, Brand RE, Petersen GM, Chari ST, Lai LA, Eng JK, Brentnall TA, Chen R. Systemic Proteome Alterations Linked to Early Stage Pancreatic Cancer in Diabetic Patients. Cancers (Basel) 2020; 12:cancers12061534. [PMID: 32545216 PMCID: PMC7352938 DOI: 10.3390/cancers12061534] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 06/05/2020] [Accepted: 06/07/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Diabetes is a risk factor associated with pancreatic ductal adenocarcinoma (PDAC), and new adult-onset diabetes can be an early sign of pancreatic malignancy. Development of blood-based biomarkers to identify diabetic patients who warrant imaging tests for cancer detection may represent a realistic approach to facilitate earlier diagnosis of PDAC in a risk population. METHODS A spectral library-based proteomic platform was applied to interrogate biomarker candidates in plasma samples from clinically well-defined diabetic cohorts with and without PDAC. Random forest algorithm was used for prediction model building and receiver operating characteristic (ROC) curve analysis was applied to evaluate the prediction probability of potential biomarker panels. RESULTS Several biomarker panels were cross-validated in the context of detection of PDAC within a diabetic background. In combination with carbohydrate antigen 19-9 (CA19-9), the panel, which consisted of apolipoprotein A-IV (APOA4), monocyte differentiation antigen CD14 (CD14), tetranectin (CLEC3B), gelsolin (GSN), histidine-rich glycoprotein (HRG), inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), plasma kallikrein (KLKB1), leucine-rich alpha-2-glycoprotein (LRG1), pigment epithelium-derived factor (SERPINF1), plasma protease C1 inhibitor (SERPING1), and metalloproteinase inhibitor 1 (TIMP1), demonstrated an area under curve (AUC) of 0.85 and a two-fold increase in detection accuracy compared to CA19-9 alone. The study further evaluated the correlations of protein candidates and their influences on the performance of biomarker panels. CONCLUSIONS Proteomics-based multiplex biomarker panels improved the detection accuracy for diagnosis of early stage PDAC in diabetic patients.
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Affiliation(s)
- Hong Peng
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA; (H.P.); (S.P.)
| | - Sheng Pan
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA; (H.P.); (S.P.)
- Department of Integrative Biology and Pharmacology, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Yuanqing Yan
- Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030, USA;
| | - Randall E. Brand
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA 15261, USA;
| | - Gloria M. Petersen
- Department of Medicine, Mayo Clinic, Rochester, MN 55902, USA; (G.M.P.); (S.T.C.)
| | - Suresh T. Chari
- Department of Medicine, Mayo Clinic, Rochester, MN 55902, USA; (G.M.P.); (S.T.C.)
| | - Lisa A. Lai
- Division of Gastroenterology, Department of Medicine, the University of Washington, Seattle, WA 98195, USA; (L.A.L.); (T.A.B.)
| | - Jimmy K. Eng
- Proteomics Resource, The University of Washington, Seattle, WA 98109, USA;
| | - Teresa A. Brentnall
- Division of Gastroenterology, Department of Medicine, the University of Washington, Seattle, WA 98195, USA; (L.A.L.); (T.A.B.)
| | - Ru Chen
- Section of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
- Correspondence:
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22
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Kim H, Kang KN, Shin YS, Byun Y, Han Y, Kwon W, Kim CW, Jang JY. Biomarker Panel for the Diagnosis of Pancreatic Ductal Adenocarcinoma. Cancers (Basel) 2020; 12:cancers12061443. [PMID: 32492943 PMCID: PMC7352313 DOI: 10.3390/cancers12061443] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 05/29/2020] [Accepted: 05/30/2020] [Indexed: 12/27/2022] Open
Abstract
A single tumor marker has a low diagnostic value in pancreatic cancer. Combinations of multiple biomarkers and unique analysis algorithms can be applied to overcome these limitations. This study sought to develop diagnostic algorithms using multiple biomarker panels and to validate their performance in the diagnosis of pancreatic ductal adenocarcinoma (PDAC). We used blood samples from 180 PDAC patients and 573 healthy controls. Candidate markers consisted of 11 markers that are commonly expressed in various cancers and which have previously demonstrated increased expression in pancreatic cancer. Samples were divided into training and validation sets. Five linear or non-linear classification methods were used to determine the optimal model. Differences were identified in 10 out of the 11 markers tested. We identified 2047 combinations, all of which were applied to 5 separate algorithms. The new biomarker combination consisted of 6 markers (ApoA1, CA125, CA19-9, CEA, ApoA2, and TTR). The area under the curve, specificity, and sensitivity were 0.992, 95%, and 96%, respectively, in the training set. Meanwhile, the measures were 0.993, 96%, and 93% in the validation set. This study demonstrated the utility of multiple biomarker combinations in the early detection of PDAC. A diagnostic panel of 6 biomarkers was developed and validated. These algorithms will assist in the early diagnosis of PDAC.
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Affiliation(s)
- Hongbeom Kim
- Departments of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Korea; (H.K.); (Y.B.); (Y.H.); (W.K.)
| | - Kyung Nam Kang
- BIOINFRA Life Science Inc., Seoul 03127, Korea; (K.N.K.); (Y.S.S.); (C.W.K.)
| | - Yong Sung Shin
- BIOINFRA Life Science Inc., Seoul 03127, Korea; (K.N.K.); (Y.S.S.); (C.W.K.)
| | - Yoonhyeong Byun
- Departments of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Korea; (H.K.); (Y.B.); (Y.H.); (W.K.)
| | - Youngmin Han
- Departments of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Korea; (H.K.); (Y.B.); (Y.H.); (W.K.)
| | - Wooil Kwon
- Departments of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Korea; (H.K.); (Y.B.); (Y.H.); (W.K.)
| | - Chul Woo Kim
- BIOINFRA Life Science Inc., Seoul 03127, Korea; (K.N.K.); (Y.S.S.); (C.W.K.)
| | - Jin-Young Jang
- Departments of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul 03080, Korea; (H.K.); (Y.B.); (Y.H.); (W.K.)
- Correspondence: ; Tel.: +82-2-2072-2194; Fax: +82-2-766-3975
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23
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Wu L, Zhou WB, Zhou J, Wei Y, Wang HM, Liu XD, Chen XC, Wang W, Ye L, Yao LC, Chen QH, Tang ZG. Circulating exosomal microRNAs as novel potential detection biomarkers in pancreatic cancer. Oncol Lett 2020; 20:1432-1440. [PMID: 32724386 PMCID: PMC7377032 DOI: 10.3892/ol.2020.11691] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 04/28/2020] [Indexed: 02/06/2023] Open
Abstract
Circulating exosomal microRNAs (ex-miRNAs) are reflective of the characteristics of the tumor and are valuable biomarkers in different types of tumor. In addition, miRNAs serve important roles in tumor progression and metastasis. The present study aimed to investigate the circulating ex-miRNA-21 and miRNA-210 as novel biomarkers for patients with pancreatic cancer (PC). For this purpose, serum ex-miRNAs were extracted from the serum of patients with PC (n=30) and chronic pancreatitis (CP) (n=10) using an RNA isolation kit. For exosome identification in serum, transmission electron micrographs were used to determine crystalline structure, western blotting was used to identify exosomal markers, and NanoSight was used for nanoparticle characterization. The relative expression levels of ex-miRNAs were quantified using quantitative PCR and compared between patients with PC and CP. The expression levels of both ex-miRNA-21 and miRNA-210 were significantly higher in patients with PC compared with patients with CP (both P<0.001). However, no significant difference in the relative serum levels of free miR-21 and miR-210 was observed between the 2 groups of patients (both P>0.05). ex-miRNA-21 and miRNA-210 were associated with tumor stage, as well as other factors. The diagnostic potential of ex-miRNA-21 and miRNA-210 levels was 83 and 85%, respectively. In addition, when ex-miRNA and serum carbohydrate antigen 19-9 expression levels were combined, the accuracy increased to 90%. The present study identified that serum ex-miRNAs, miRNA-21 and miRNA-210 may be of value as potential biomarkers and therapeutic targets for the diagnosis and treatment of PC.
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Affiliation(s)
- Lun Wu
- Department of Pancreatic Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Wen-Bo Zhou
- Department of Hepatobiliary Surgery, Dongfeng Hospital, Hubei University of Medicine, Shiyan, Hubei 442001, P.R. China
| | - Jiao Zhou
- Department of Urology, Dongfeng Hospital, Hubei University of Medicine, Shiyan, Hubei 442001, P.R. China
| | - Ying Wei
- Clinical Laboratory, Dongfeng Hospital, Hubei University of Medicine, Shiyan, Hubei 442001, P.R. China
| | - Hong-Mei Wang
- Liver Surgery Institute of The Experiment Center of Medicine, Dongfeng Hospital, Hubei University of Medicine, Shiyan, Hubei 442001, P.R. China
| | - Xian-De Liu
- Department of General Surgery, People's Hospital of Zhu Shan, Shiyan, Hubei 442001, P.R. China
| | - Xiao-Chun Chen
- Department of General Surgery, People's Hospital of Zhu Shan, Shiyan, Hubei 442001, P.R. China
| | - Wei Wang
- Department of Pancreatic Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Lin Ye
- Department of Pancreatic Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Li Chao Yao
- Department of Pancreatic Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
| | - Qin-Hua Chen
- Hubei Key Laboratory of Wudang Local Chinese Medicine Research, Experiment Center of Medicine, Hubei University of Medicine, Shiyan, Hubei 442001, P.R. China
| | - Zhi-Gang Tang
- Department of Pancreatic Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, P.R. China
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24
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Kim H, Kim Y, Han B, Jang JY, Kim Y. Clinically Applicable Deep Learning Algorithm Using Quantitative Proteomic Data. J Proteome Res 2019; 18:3195-3202. [DOI: 10.1021/acs.jproteome.9b00268] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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25
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Kontostathi G, Makridakis M, Zoidakis J, Vlahou A. Applications of multiple reaction monitoring targeted proteomics assays in human plasma. Expert Rev Mol Diagn 2019; 19:499-515. [PMID: 31057016 DOI: 10.1080/14737159.2019.1615448] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Introduction: Multiple (or selected) reaction monitoring-mass spectrometry (MRM/SRM) is a targeted proteomic method that can be used for relative and absolute quantification. Multiple reports exist supporting the potential of the approach in proteomic biomarker validation. Areas covered: To get an overview of the applications of MRM in protein quantification in plasma, a search in MedLine/PubMed was performed using the keywords: 'MRM/SRM plasma proteomic/proteomics/proteome'. The retrieved studies were further filtered to focus on disease biomarkers and the main results are summarized. Expert opinion: MRM is increasingly employed for the quantification of both well-established but also newly discovered putative biomarkers and occasionally their post-translationally modified forms in plasma. Fractionation is regularly required for the detection of low abundance proteins. Standardized procedures to facilitate assay establishment and marker quantification have been proposed and, in few cases, implemented. Nevertheless, in most cases, absolute quantification is not performed. To advance, multiple technical issues including the regular use of standard labeled peptides and appropriate quality controls to monitor assay performance should be considered. Additionally, clinical aspects involving careful study design to address biomarker clinical use should also be considered.
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Affiliation(s)
- Georgia Kontostathi
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
| | - Manousos Makridakis
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
| | - Jerome Zoidakis
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
| | - Antonia Vlahou
- a Biotechnology Division , Biomedical Research Foundation, Academy of Athens (BRFAA) , Athens , Greece
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26
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Zhou Q, Andersson R, Hu D, Bauden M, Kristl T, Sasor A, Pawłowski K, Pla I, Hilmersson KS, Zhou M, Lu F, Marko-Varga G, Ansari D. Quantitative proteomics identifies brain acid soluble protein 1 (BASP1) as a prognostic biomarker candidate in pancreatic cancer tissue. EBioMedicine 2019; 43:282-294. [PMID: 30982764 PMCID: PMC6557784 DOI: 10.1016/j.ebiom.2019.04.008] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 03/27/2019] [Accepted: 04/03/2019] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Pancreatic cancer is a heterogenous disease with a poor prognosis. This study aimed to discover and validate prognostic tissue biomarkers in pancreatic cancer using a mass spectrometry (MS) based proteomics approach. METHODS Global protein sequencing of fresh frozen pancreatic cancer and healthy pancreas tissue samples was conducted by MS to discover potential protein biomarkers. Selected candidate proteins were further verified by targeted proteomics using parallel reaction monitoring (PRM). The expression of biomarker candidates was validated by immunohistochemistry in a large tissue microarray (TMA) cohort of 141 patients with resectable pancreatic cancer. Kaplan-Meier and Cox proportional hazard modelling was used to investigate the prognostic utility of candidate protein markers. FINDINGS In the initial MS-discovery phase, 165 proteins were identified as potential biomarkers. In the subsequent MS-verification phase, a panel of 45 candidate proteins was verified by the development of a PRM assay. Brain acid soluble protein 1 (BASP1) was identified as a new biomarker candidate for pancreatic cancer possessing largely unknown biological and clinical functions and was selected for further analysis. Importantly, bioinformatic analysis indicated that BASP1 interacts with Wilms tumour protein (WT1) in pancreatic cancer. TMA-based immunohistochemistry analysis showed that BASP1 was an independent predictor of prolonged survival (HR 0.468, 95% CI 0.257-0.852, p = .013) and predicted favourable response to adjuvant chemotherapy, whereas WT1 indicated a worsened survival (HR 1.636, 95% CI 1.083-2.473, p = .019) and resistance to chemotherapy. Interaction analysis showed that patients with negative BASP1 and high WT1 expression had the poorest outcome (HR 3.536, 95% CI 1.336-9.362, p = .011). INTERPRETATION We here describe an MS-based proteomics platform for developing biomarkers for pancreatic cancer. Bioinformatic analysis and clinical data from our study suggest that BASP1 and its putative interaction partner WT1 can be used as biomarkers for predicting outcomes in pancreatic cancer patients.
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Affiliation(s)
- Qimin Zhou
- Department of Surgery, Clinical Sciences Lund, Lund University and Skåne University Hospital, Lund, Sweden; The Eye Hospital, School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China; Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Roland Andersson
- Department of Surgery, Clinical Sciences Lund, Lund University and Skåne University Hospital, Lund, Sweden
| | - Dingyuan Hu
- Department of Surgery, Clinical Sciences Lund, Lund University and Skåne University Hospital, Lund, Sweden
| | - Monika Bauden
- Department of Surgery, Clinical Sciences Lund, Lund University and Skåne University Hospital, Lund, Sweden
| | - Theresa Kristl
- Department of Surgery, Clinical Sciences Lund, Lund University and Skåne University Hospital, Lund, Sweden
| | - Agata Sasor
- Department of Pathology, Skåne University Hospital, Lund, Sweden
| | - Krzysztof Pawłowski
- Department of Experimental Design and Bioinformatics, Warsaw University of Life Sciences, Warsaw, Poland; Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Indira Pla
- Department of Biomedical Engineering, Clinical Protein Science and Imaging, Lund University, Lund, Sweden
| | - Katarzyna Said Hilmersson
- Department of Surgery, Clinical Sciences Lund, Lund University and Skåne University Hospital, Lund, Sweden
| | - Mengtao Zhou
- Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Fan Lu
- The Eye Hospital, School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - György Marko-Varga
- Department of Biomedical Engineering, Clinical Protein Science and Imaging, Lund University, Lund, Sweden
| | - Daniel Ansari
- Department of Surgery, Clinical Sciences Lund, Lund University and Skåne University Hospital, Lund, Sweden.
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