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Sayed K, Dolin CE, Wilkey DW, Li J, Sato T, Beier JI, Argemi J, Vatsalya V, McClain CJ, Bataller R, Wahed AS, Merchant ML, Benos PV, Arteel GE. A plasma peptidomic signature reveals extracellular matrix remodeling and predicts prognosis in alcohol-associated hepatitis. Hepatol Commun 2024; 8:e0510. [PMID: 39082970 DOI: 10.1097/hc9.0000000000000510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 05/07/2024] [Indexed: 08/07/2024] Open
Abstract
BACKGROUND Alcohol-associated hepatitis (AH) is plagued with high mortality and difficulty in identifying at-risk patients. The extracellular matrix undergoes significant remodeling during inflammatory liver injury and could potentially be used for mortality prediction. METHODS EDTA plasma samples were collected from patients with AH (n = 62); Model for End-Stage Liver Disease score defined AH severity as moderate (12-20; n = 28) and severe (>20; n = 34). The peptidome data were collected by high resolution, high mass accuracy UPLC-MS. Univariate and multivariate analyses identified differentially abundant peptides, which were used for Gene Ontology, parent protein matrisomal composition, and protease involvement. Machine-learning methods were used to develop mortality predictors. RESULTS Analysis of plasma peptides from patients with AH and healthy controls identified over 1600 significant peptide features corresponding to 130 proteins. These were enriched for extracellular matrix fragments in AH samples, likely related to the turnover of hepatic-derived proteins. Analysis of moderate versus severe AH peptidomes was dominated by changes in peptides from collagen 1A1 and fibrinogen A proteins. The dominant proteases for the AH peptidome spectrum appear to be CAPN1 and MMP12. Causal graphical modeling identified 3 peptides directly linked to 90-day mortality in >90% of the learned graphs. These peptides improved the accuracy of mortality prediction over the Model for End-Stage Liver Disease score and were used to create a clinically applicable mortality prediction assay. CONCLUSIONS A signature based on plasma peptidome is a novel, noninvasive method for prognosis stratification in patients with AH. Our results could also lead to new mechanistic and/or surrogate biomarkers to identify new AH mechanisms.
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Affiliation(s)
- Khaled Sayed
- Department of Epidemiology, University of Florida, Gainesville, Florida, USA
- Department of Electrical & Computer Engineering and Computer Science, University of New Haven, West Haven, Connecticut, USA
| | - Christine E Dolin
- Department of Medicine, University of Louisville, Louisville, Kentucky, USA
| | - Daniel W Wilkey
- Department of Medicine, University of Louisville, Louisville, Kentucky, USA
| | - Jiang Li
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Toshifumi Sato
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Juliane I Beier
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Josepmaria Argemi
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Department of Internal Medicine, Clinical University of Navarra, Navarra, Spain
| | - Vatsalya Vatsalya
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Louisville, Louisville, Kentucky, USA
- University of Louisville Alcohol Research Center, University of Louisville, Louisville, Kentucky, USA
| | - Craig J McClain
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Louisville, Louisville, Kentucky, USA
- University of Louisville Alcohol Research Center, University of Louisville, Louisville, Kentucky, USA
| | - Ramon Bataller
- Liver Unit, Hospital Clinic. Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Abdus S Wahed
- Department of Biostatistics and Computational Biology, University of Rochester, Rochester, New York, USA
| | - Michael L Merchant
- Department of Medicine, University of Louisville, Louisville, Kentucky, USA
- University of Louisville Alcohol Research Center, University of Louisville, Louisville, Kentucky, USA
| | - Panayiotis V Benos
- Department of Epidemiology, University of Florida, Gainesville, Florida, USA
| | - Gavin E Arteel
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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Zhang X, Hong B, Li H, Zhao J, Li M, Wei D, Wang Y, Zhang N. Basement membrane-related MMP14 predicts poor prognosis and response to immunotherapy in bladder cancer. BMC Cancer 2024; 24:746. [PMID: 38898429 PMCID: PMC11186261 DOI: 10.1186/s12885-024-12489-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 06/10/2024] [Indexed: 06/21/2024] Open
Abstract
BACKGROUND Basement membrane (BM) is an important component of the extracellular matrix, which plays an important role in the growth and metastasis of tumor cells. However, few biomarkers based on BM have been developed for prognostic assessment and prediction of immunotherapy in bladder cancer (BLCA). METHODS In this study, we used the BLCA public database to explore the relationship between BM-related genes (BMRGs) and prognosis. A novel molecular typing of BLCA was performed using consensus clustering. LASSO regression was used to construct a signature based on BMRGs, and its relationship with prognosis was explored using survival analysis. The pivotal BMRGs were further analyzed to assess its clinical characteristics and immune landscape. Finally, immunohistochemistry was used to detect the expression of the hub gene in BLCA patients who underwent surgery or received immune checkpoint inhibitor (ICI) immunotherapy in our hospital. RESULTS We comprehensively analyzed the relationship between BMRGs and BLCA, and established a prognostic-related signature which was an independent influence on the prognostic prediction of BLCA. We further screened and validated the pivotal gene-MMP14 in public database. In addition, we found that MMP14 expression in muscle invasive bladder cancer (MIBC) was significantly higher and high MMP14 expression had a poorer response to ICI treatment in our cohort. CONCLUSIONS Our findings highlighted the satisfactory value of BMRGs and suggested that MMP14 may be a potential biomarker in predicting prognosis and response to immunotherapy in BLCA.
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Affiliation(s)
- Xuezhou Zhang
- Department of Urology, Beijing Anzhen Hospital, Capital Medical University, 2 Anzhen Road, Chaoyang District, Beijing, 100029, P. R. China
| | - Baoan Hong
- Department of Urology, Beijing Anzhen Hospital, Capital Medical University, 2 Anzhen Road, Chaoyang District, Beijing, 100029, P. R. China
| | - Hongwei Li
- Department of Pathology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, P. R. China
| | - Jiahui Zhao
- Department of Urology, Beijing Anzhen Hospital, Capital Medical University, 2 Anzhen Road, Chaoyang District, Beijing, 100029, P. R. China
| | - Mingchuan Li
- Department of Urology, Beijing Anzhen Hospital, Capital Medical University, 2 Anzhen Road, Chaoyang District, Beijing, 100029, P. R. China
| | - Dechao Wei
- Department of Urology, Beijing Anzhen Hospital, Capital Medical University, 2 Anzhen Road, Chaoyang District, Beijing, 100029, P. R. China
| | - Yongxing Wang
- Department of Urology, Beijing Anzhen Hospital, Capital Medical University, 2 Anzhen Road, Chaoyang District, Beijing, 100029, P. R. China
| | - Ning Zhang
- Department of Urology, Beijing Anzhen Hospital, Capital Medical University, 2 Anzhen Road, Chaoyang District, Beijing, 100029, P. R. China.
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Köhler B, Bes M, Chan HLY, Esteban JI, Piratvisuth T, Sukeepaisarnjaroen W, Tanwandee T, Thongsawat S, Mang A, Morgenstern D, Swiatek-de Lange M, Dayyani F. A new biomarker panel for differential diagnosis of cholangiocarcinoma: Results from an exploratory analysis. Int J Biol Markers 2024; 39:107-117. [PMID: 38549363 DOI: 10.1177/03936155241235185] [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] [Indexed: 05/14/2024]
Abstract
INTRODUCTION Diagnosis of cholangiocarcinoma (CCA) can be challenging due to unclear imaging criteria and difficulty obtaining adequate tissue biopsy. Although serum cancer antigen 19-9 and carcinoembryonic antigen have been proposed as potential diagnostic aids, their use remains limited by insufficient sensitivity and specificity. This exploratory analysis aimed to identify individual- and combinations of serum biomarkers to distinguish CCA from hepatocellular carcinoma (HCC) and chronic liver disease (CLD) controls using samples from a published study. METHODS This prospective, multicenter, case-control study included patients aged ≥18 years at high-risk of HCC. Serum and ethylene diamine tetraacetic acid-plasma samples were collected prior to any treatment and confirmed diagnosis of HCC or CCA. Fourteen biomarkers (measured by electrochemiluminescence immunoassays or enzyme-linked immunosorbent assays) were subjected to univariate analysis and 13 included in a multivariate analysis (per selected combinations and exhaustive search). RESULTS Overall, 55 CCA, 306 HCC, and 733 CLD control samples were analyzed. For distinguishing CCA from HCC, alpha-fetoprotein and matrix metalloproteinase-2 (MMP-2) showed the best individual performance (area under the curve (AUC) 86.6% and 84.4%, respectively); tissue inhibitor of metalloproteinase-1 (TIMP-1) was most able to distinguish CCA from CLD (AUC 94.5%) and from HCC + CLD (AUC 88.6%). The combination of MMP-2 and TIMP-1 was the best-performing two-marker panel, with AUC >90% for all comparisons. CONCLUSION MMP-2 and TIMP-1 are promising biomarkers that could support differential diagnosis of CCA. Incorporating these assays into the diagnostic algorithm could provide additional diagnostic information in a non-invasive, rapid manner, and could supplement existing diagnostic methods.
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Affiliation(s)
- Bruno Köhler
- Department of Medical Oncology, National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
- Liver Cancer Center Heidelberg, Heidelberg, Germany
| | - Marta Bes
- Centro de Investigación Biomédica en red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, Spain
- Transfusion Safety Laboratory, Banc de Sang i Teixits (BST), Barcelona, Spain
| | - Henry Lik-Yuen Chan
- Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region of China
| | - Juan Ignacio Esteban
- Centro de Investigación Biomédica en red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, Spain
- Liver Unit, Hospital Universitari Vall d'Hebron (HUVH), Barcelona, Spain
| | - Teerha Piratvisuth
- NKC Institute of Gastroenterology and Hepatology, Songklanagarind Hospital, Prince of Songkla University, Hat Yai, Thailand
| | | | - Tawesak Tanwandee
- Division of Gastroenterology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Satawat Thongsawat
- Department of Internal Medicine, Maharaj Nakorn Chiang Mai Hospital, Chiang Mai University, Chiang Mai, Thailand
| | - Anika Mang
- Roche Diagnostics GmbH, Penzberg, Germany
| | | | | | - Farshid Dayyani
- Department of Medicine, Division of Hematology/Oncology, University of California in Irvine, Irvine, CA, USA
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Huang J, Bai X, Qiu Y, He X. Application of AI on cholangiocarcinoma. Front Oncol 2024; 14:1324222. [PMID: 38347839 PMCID: PMC10859478 DOI: 10.3389/fonc.2024.1324222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 01/08/2024] [Indexed: 02/15/2024] Open
Abstract
Cholangiocarcinoma, classified as intrahepatic, perihilar, and extrahepatic, is considered a deadly malignancy of the hepatobiliary system. Most cases of cholangiocarcinoma are asymptomatic. Therefore, early detection of cholangiocarcinoma is significant but still challenging. The routine screening of a tumor lacks specificity and accuracy. With the application of AI, high-risk patients can be easily found by analyzing their clinical characteristics, serum biomarkers, and medical images. Moreover, AI can be used to predict the prognosis including recurrence risk and metastasis. Although they have some limitations, AI algorithms will still significantly improve many aspects of cholangiocarcinoma in the medical field with the development of computing power and technology.
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Affiliation(s)
| | | | | | - Xiaodong He
- Department of General Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
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