Identification and validation of a novel autoantibody biomarker panel for differential diagnosis of pancreatic ductal adenocarcinoma
IntroductionNew biomarkers are urgently needed to detect pancreatic ductal adenocarcinoma (PDAC) at an earlier stage for individualized treatment strategies and to improve outcomes. Autoantibodies (AAbs) in principle make attractive biomarkers as they arise early in disease, report on disease-associ...
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Frontiers Media S.A.
2025-01-01
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| author | Metoboroghene O. Mowoe Metoboroghene O. Mowoe Hisham Allam Joshua Nqada Marc Bernon Karan Gandhi Sean Burmeister Urda Kotze Miriam Kahn Christo Kloppers Suba Dharshanan Zafirah Azween Pamela Maimela Paul Townsend Eduard Jonas Jonathan M. Blackburn Jonathan M. Blackburn |
| author_facet | Metoboroghene O. Mowoe Metoboroghene O. Mowoe Hisham Allam Joshua Nqada Marc Bernon Karan Gandhi Sean Burmeister Urda Kotze Miriam Kahn Christo Kloppers Suba Dharshanan Zafirah Azween Pamela Maimela Paul Townsend Eduard Jonas Jonathan M. Blackburn Jonathan M. Blackburn |
| author_sort | Metoboroghene O. Mowoe |
| collection | DOAJ |
| description | IntroductionNew biomarkers are urgently needed to detect pancreatic ductal adenocarcinoma (PDAC) at an earlier stage for individualized treatment strategies and to improve outcomes. Autoantibodies (AAbs) in principle make attractive biomarkers as they arise early in disease, report on disease-associated perturbations in cellular proteomes, and are static in response to other common stimuli, yet are measurable in the periphery, potentially well in advance of the onset of clinical symptoms.MethodsHere, we used high-throughput, custom cancer antigen microarrays to identify a clinically relevant autoantibody biomarker combination able to differentially detect PDAC. Specifically, we quantified the serological AAb profiles of 94 PDAC, chronic pancreatitis (CP), other pancreatic- (PC) and prostate cancers (PRC), non-ulcer dyspepsia patients (DYS), and healthy controls (HC).ResultsCombinatorial ROC curve analysis on the training cohort data from the cancer antigen microarrays identified the most effective biomarker combination as CEACAM1-DPPA2-DPPA3-MAGEA4-SRC-TPBG-XAGE3 with an AUC = 85·0% (SE = 0·828, SP = 0·684). Additionally, differential expression analysis on the samples run on the iOme™ array identified 4 biomarkers (ALX1-GPA33-LIP1-SUB1) upregulated in PDAC against diseased and healthy controls. Identified AAbs were validated in silico using public immunohistochemistry datasets and experimentally using a custom PDAC protein microarray comprising the 11 optimal AAb biomarker panel. The clinical utility of the biomarker panel was tested in an independent cohort comprising 223 PDAC, PC, PRC, colorectal cancer (CRC), and HC samples. Combinatorial ROC curve analysis on the validation data identified the most effective biomarker combination to be CEACAM1-DPPA2-DPPA3-MAGEA4-SRC-TPBG-XAGE3 with an AUC = 85·0% (SE = 0·828, SP = 0·684). Subsequently, the specificity of the 11-biomarker panel was validated against other cancers (PDAC vs PC: AUC = 70·3%; PDAC vs CRC: AUC = 84·3%; PDAC vs PRC: AUC = 80·2%) and healthy controls (PDAC vs HC: AUC = 80·9%), confirming that this novel AAb biomarker panel is able to selectively detect PDAC amongst other confounding diseases.ConclusionThis AAb panel may therefore have the potential to form the basis of a novel diagnostic test for PDAC. |
| format | Article |
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| institution | Kabale University |
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| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-7ccbf643a1fb4a32a4af1759b26b69d22025-01-30T06:23:05ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-01-011610.3389/fimmu.2025.14944461494446Identification and validation of a novel autoantibody biomarker panel for differential diagnosis of pancreatic ductal adenocarcinomaMetoboroghene O. Mowoe0Metoboroghene O. Mowoe1Hisham Allam2Joshua Nqada3Marc Bernon4Karan Gandhi5Sean Burmeister6Urda Kotze7Miriam Kahn8Christo Kloppers9Suba Dharshanan10Zafirah Azween11Pamela Maimela12Paul Townsend13Eduard Jonas14Jonathan M. Blackburn15Jonathan M. Blackburn16Department of Integrative Biomedical Sciences, Division of Chemical and Systems Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaInstitute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaSurgical Gastroenterology Unit, Division of General Surgery, Groote Schuur Hospital, University of Cape Town, Cape Town, South AfricaSurgical Gastroenterology Unit, Division of General Surgery, Groote Schuur Hospital, University of Cape Town, Cape Town, South AfricaSurgical Gastroenterology Unit, Division of General Surgery, Groote Schuur Hospital, University of Cape Town, Cape Town, South AfricaSurgical Gastroenterology Unit, Division of General Surgery, Groote Schuur Hospital, University of Cape Town, Cape Town, South AfricaSurgical Gastroenterology Unit, Division of General Surgery, Groote Schuur Hospital, University of Cape Town, Cape Town, South AfricaSurgical Gastroenterology Unit, Division of General Surgery, Groote Schuur Hospital, University of Cape Town, Cape Town, South AfricaSurgical Gastroenterology Unit, Division of General Surgery, Groote Schuur Hospital, University of Cape Town, Cape Town, South AfricaSurgical Gastroenterology Unit, Division of General Surgery, Groote Schuur Hospital, University of Cape Town, Cape Town, South AfricaRecombinant Protein Facility, Sengenics Corporation, Kuala Lumpur, MalaysiaRecombinant Protein Facility, Sengenics Corporation, Kuala Lumpur, MalaysiaDepartment of Integrative Biomedical Sciences, Division of Chemical and Systems Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaFaculty of Health Sciences and Sports, University of Stirling, Stirling, United KingdomSurgical Gastroenterology Unit, Division of General Surgery, Groote Schuur Hospital, University of Cape Town, Cape Town, South AfricaDepartment of Integrative Biomedical Sciences, Division of Chemical and Systems Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaInstitute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South AfricaIntroductionNew biomarkers are urgently needed to detect pancreatic ductal adenocarcinoma (PDAC) at an earlier stage for individualized treatment strategies and to improve outcomes. Autoantibodies (AAbs) in principle make attractive biomarkers as they arise early in disease, report on disease-associated perturbations in cellular proteomes, and are static in response to other common stimuli, yet are measurable in the periphery, potentially well in advance of the onset of clinical symptoms.MethodsHere, we used high-throughput, custom cancer antigen microarrays to identify a clinically relevant autoantibody biomarker combination able to differentially detect PDAC. Specifically, we quantified the serological AAb profiles of 94 PDAC, chronic pancreatitis (CP), other pancreatic- (PC) and prostate cancers (PRC), non-ulcer dyspepsia patients (DYS), and healthy controls (HC).ResultsCombinatorial ROC curve analysis on the training cohort data from the cancer antigen microarrays identified the most effective biomarker combination as CEACAM1-DPPA2-DPPA3-MAGEA4-SRC-TPBG-XAGE3 with an AUC = 85·0% (SE = 0·828, SP = 0·684). Additionally, differential expression analysis on the samples run on the iOme™ array identified 4 biomarkers (ALX1-GPA33-LIP1-SUB1) upregulated in PDAC against diseased and healthy controls. Identified AAbs were validated in silico using public immunohistochemistry datasets and experimentally using a custom PDAC protein microarray comprising the 11 optimal AAb biomarker panel. The clinical utility of the biomarker panel was tested in an independent cohort comprising 223 PDAC, PC, PRC, colorectal cancer (CRC), and HC samples. Combinatorial ROC curve analysis on the validation data identified the most effective biomarker combination to be CEACAM1-DPPA2-DPPA3-MAGEA4-SRC-TPBG-XAGE3 with an AUC = 85·0% (SE = 0·828, SP = 0·684). Subsequently, the specificity of the 11-biomarker panel was validated against other cancers (PDAC vs PC: AUC = 70·3%; PDAC vs CRC: AUC = 84·3%; PDAC vs PRC: AUC = 80·2%) and healthy controls (PDAC vs HC: AUC = 80·9%), confirming that this novel AAb biomarker panel is able to selectively detect PDAC amongst other confounding diseases.ConclusionThis AAb panel may therefore have the potential to form the basis of a novel diagnostic test for PDAC.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1494446/fullpancreatic ductal adenocarcinomabiomarker paneldiagnosisautoantibodiesprotein microarray |
| spellingShingle | Metoboroghene O. Mowoe Metoboroghene O. Mowoe Hisham Allam Joshua Nqada Marc Bernon Karan Gandhi Sean Burmeister Urda Kotze Miriam Kahn Christo Kloppers Suba Dharshanan Zafirah Azween Pamela Maimela Paul Townsend Eduard Jonas Jonathan M. Blackburn Jonathan M. Blackburn Identification and validation of a novel autoantibody biomarker panel for differential diagnosis of pancreatic ductal adenocarcinoma Frontiers in Immunology pancreatic ductal adenocarcinoma biomarker panel diagnosis autoantibodies protein microarray |
| title | Identification and validation of a novel autoantibody biomarker panel for differential diagnosis of pancreatic ductal adenocarcinoma |
| title_full | Identification and validation of a novel autoantibody biomarker panel for differential diagnosis of pancreatic ductal adenocarcinoma |
| title_fullStr | Identification and validation of a novel autoantibody biomarker panel for differential diagnosis of pancreatic ductal adenocarcinoma |
| title_full_unstemmed | Identification and validation of a novel autoantibody biomarker panel for differential diagnosis of pancreatic ductal adenocarcinoma |
| title_short | Identification and validation of a novel autoantibody biomarker panel for differential diagnosis of pancreatic ductal adenocarcinoma |
| title_sort | identification and validation of a novel autoantibody biomarker panel for differential diagnosis of pancreatic ductal adenocarcinoma |
| topic | pancreatic ductal adenocarcinoma biomarker panel diagnosis autoantibodies protein microarray |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1494446/full |
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