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Schwarcz S, Kovács P, Nyerges P, Ujlaki G, Sipos A, Uray K, Bai P, Mikó E. The bacterial metabolite, lithocholic acid, has antineoplastic effects in pancreatic adenocarcinoma. Cell Death Discov 2024; 10:248. [PMID: 38782891 PMCID: PMC11116504 DOI: 10.1038/s41420-024-02023-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 05/08/2024] [Accepted: 05/10/2024] [Indexed: 05/25/2024] Open
Abstract
Lithocholic acid (LCA) is a secondary bile acid. LCA enters the circulation after bacterial synthesis in the gastrointestinal tract, reaches distantly located cancer cells, and influences their behavior. LCA was considered carcinogenic, but recent studies demonstrated that LCA has antitumor effects. We assessed the possible role of LCA in pancreatic adenocarcinoma. At the serum reference concentration, LCA induced a multi-pronged antineoplastic program in pancreatic adenocarcinoma cells. LCA inhibited cancer cell proliferation and induced mesenchymal-to-epithelial (MET) transition that reduced cell invasion capacity. LCA induced oxidative/nitrosative stress by decreasing the expression of nuclear factor, erythroid 2-like 2 (NRF2) and inducing inducible nitric oxide synthase (iNOS). The oxidative/nitrosative stress increased protein nitration and lipid peroxidation. Suppression of oxidative stress by glutathione (GSH) or pegylated catalase (pegCAT) blunted LCA-induced MET. Antioxidant genes were overexpressed in pancreatic adenocarcinoma and decreased antioxidant levels correlated with better survival of pancreatic adenocarcinoma patients. Furthermore, LCA treatment decreased the proportions of cancer stem cells. Finally, LCA induced total and ATP-linked mitochondrial oxidation and fatty acid oxidation. LCA exerted effects through the farnesoid X receptor (FXR), vitamin D receptor (VDR), and constitutive androstane receptor (CAR). LCA did not interfere with cytostatic agents used in the chemotherapy of pancreatic adenocarcinoma. Taken together, LCA is a non-toxic compound and has antineoplastic effects in pancreatic adenocarcinoma.
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Affiliation(s)
- Szandra Schwarcz
- Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, Debrecen, 4032, Hungary
| | - Patrik Kovács
- Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, Debrecen, 4032, Hungary
| | - Petra Nyerges
- Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, Debrecen, 4032, Hungary
| | - Gyula Ujlaki
- Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, Debrecen, 4032, Hungary
- HUN-REN-UD Cell Biology and Signaling Research Group, Debrecen, 4032, Hungary
| | - Adrienn Sipos
- Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, Debrecen, 4032, Hungary
- HUN-REN-UD Cell Biology and Signaling Research Group, Debrecen, 4032, Hungary
| | - Karen Uray
- Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, Debrecen, 4032, Hungary
| | - Péter Bai
- Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, Debrecen, 4032, Hungary
- HUN-REN-UD Cell Biology and Signaling Research Group, Debrecen, 4032, Hungary
- MTA-DE Lendület Laboratory of Cellular Metabolism, Debrecen, 4032, Hungary
- Research Center for Molecular Medicine, Faculty of Medicine, University of Debrecen, Debrecen, 4032, Hungary
| | - Edit Mikó
- Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, Debrecen, 4032, Hungary.
- MTA-DE Lendület Laboratory of Cellular Metabolism, Debrecen, 4032, Hungary.
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Asleh K, Dery V, Taylor C, Davey M, Djeungoue-Petga MA, Ouellette RJ. Extracellular vesicle-based liquid biopsy biomarkers and their application in precision immuno-oncology. Biomark Res 2023; 11:99. [PMID: 37978566 PMCID: PMC10655470 DOI: 10.1186/s40364-023-00540-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 11/06/2023] [Indexed: 11/19/2023] Open
Abstract
While the field of precision oncology is rapidly expanding and more targeted options are revolutionizing cancer treatment paradigms, therapeutic resistance particularly to immunotherapy remains a pressing challenge. This can be largely attributed to the dynamic tumor-stroma interactions that continuously alter the microenvironment. While to date most advancements have been made through examining the clinical utility of tissue-based biomarkers, their invasive nature and lack of a holistic representation of the evolving disease in a real-time manner could result in suboptimal treatment decisions. Thus, using minimally-invasive approaches to identify biomarkers that predict and monitor treatment response as well as alert to the emergence of recurrences is of a critical need. Currently, research efforts are shifting towards developing liquid biopsy-based biomarkers obtained from patients over the course of disease. Liquid biopsy represents a unique opportunity to monitor intercellular communication within the tumor microenvironment which could occur through the exchange of extracellular vesicles (EVs). EVs are lipid bilayer membrane nanoscale vesicles which transfer a plethora of biomolecules that mediate intercellular crosstalk, shape the tumor microenvironment, and modify drug response. The capture of EVs using innovative approaches, such as microfluidics, magnetic beads, and aptamers, allow their analysis via high throughput multi-omics techniques and facilitate their use for biomarker discovery. Artificial intelligence, using machine and deep learning algorithms, is advancing multi-omics analyses to uncover candidate biomarkers and predictive signatures that are key for translation into clinical trials. With the increasing recognition of the role of EVs in mediating immune evasion and as a valuable biomarker source, these real-time snapshots of cellular communication are promising to become an important tool in the field of precision oncology and spur the recognition of strategies to block resistance to immunotherapy. In this review, we discuss the emerging role of EVs in biomarker research describing current advances in their isolation and analysis techniques as well as their function as mediators in the tumor microenvironment. We also highlight recent lung cancer and melanoma studies that point towards their application as predictive biomarkers for immunotherapy and their potential clinical use in precision immuno-oncology.
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Affiliation(s)
- Karama Asleh
- Atlantic Cancer Research Institute, Moncton, New Brunswick, Canada.
| | - Valerie Dery
- Department of Chemistry and Biochemistry, Université de Moncton, Moncton, New Brunswick, Canada
| | - Catherine Taylor
- Atlantic Cancer Research Institute, Moncton, New Brunswick, Canada
| | - Michelle Davey
- Atlantic Cancer Research Institute, Moncton, New Brunswick, Canada
| | | | - Rodney J Ouellette
- Atlantic Cancer Research Institute, Moncton, New Brunswick, Canada
- Department of Chemistry and Biochemistry, Université de Moncton, Moncton, New Brunswick, Canada
- Dr Georges L. Dumont University Hospital, Vitalite Health Network, Moncton, New Brunswick, Canada
- Beatrice Hunter Cancer Research Institute, Halifax, Nova Scotia, Canada
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Naudin S, Sampson JN, Moore SC, Albanes D, Freedman ND, Weinstein SJ, Stolzenberg-Solomon R. Lipidomics and pancreatic cancer risk in two prospective studies. Eur J Epidemiol 2023; 38:783-793. [PMID: 37169992 PMCID: PMC11152614 DOI: 10.1007/s10654-023-01014-3] [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: 01/07/2023] [Accepted: 04/27/2023] [Indexed: 05/13/2023]
Abstract
Pancreatic ductal carcinoma (PDAC) is highly fatal with limited understanding of mechanisms underlying its carcinogenesis. We comprehensively investigated whether lipidomic measures were associated with PDAC in two prospective studies. We measured 904 lipid species and 252 fatty acids across 15 lipid classes in pre-diagnostic serum (up to 24 years) in a PDAC nested-case control study within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, NCT00002540) with 332 matched case-control sets including 272 having serial blood samples and Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (ATBC, NCT00342992) with 374 matched case-control sets. Controls were matched to cases by cohort, age, sex, race, and date at blood draw. We used conditional logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI) per one-standard deviation increase in log-lipid concentrations within each cohort, and combined ORs using fixed-effects meta-analyses. Forty-three lipid species were associated with PDAC (false discovery rate, FDR ≤ 0.10), including lysophosphatidylcholines (LPC, n = 2), phosphatidylethanolamines (PE, n = 17), triacylglycerols (n = 13), phosphatidylcholines (PC, n = 3), diacylglycerols (n = 4), monoacylglycerols (MAG, n = 2), cholesteryl esters (CE, n = 1), and sphingomyelins (n = 1). LPC(18:2) and PE(O-16:0/18:2) showed significant inverse associations with PDAC at the Bonferroni threshold (P value < 5.5 × 10-5). The fatty acids LPC[18:2], LPC[16:0], PC[15:0], MAG[18:1] and CE[22:0] were significantly associated with PDAC (FDR < 0.10). Similar associations were observed in both cohorts. There was no significant association for the differences between PLCO serial lipidomic measures or heterogeneity by follow-up time overall. Results support that the pre-diagnostic serum lipidome, including 43 lipid species from 8 lipid classes and 5 fatty acids, is associated with PDAC.
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Affiliation(s)
- Sabine Naudin
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, DHHS, 9609 Medical Center Drive, NCI Shady Grove, Room 6E420, Rockville, MD, 20850, USA
| | - Joshua N Sampson
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Rockville, MD, USA
| | - Steven C Moore
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, DHHS, 9609 Medical Center Drive, NCI Shady Grove, Room 6E420, Rockville, MD, 20850, USA
| | - Demetrius Albanes
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, DHHS, 9609 Medical Center Drive, NCI Shady Grove, Room 6E420, Rockville, MD, 20850, USA
| | - Neal D Freedman
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, DHHS, 9609 Medical Center Drive, NCI Shady Grove, Room 6E420, Rockville, MD, 20850, USA
| | - Stephanie J Weinstein
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, DHHS, 9609 Medical Center Drive, NCI Shady Grove, Room 6E420, Rockville, MD, 20850, USA
| | - Rachael Stolzenberg-Solomon
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, DHHS, 9609 Medical Center Drive, NCI Shady Grove, Room 6E420, Rockville, MD, 20850, USA.
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Muranaka H, Hendifar A, Osipov A, Moshayedi N, Placencio-Hickok V, Tatonetti N, Stotland A, Parker S, Van Eyk J, Pandol SJ, Bhowmick NA, Gong J. Plasma Metabolomics Predicts Chemotherapy Response in Advanced Pancreatic Cancer. Cancers (Basel) 2023; 15:3020. [PMID: 37296982 PMCID: PMC10252041 DOI: 10.3390/cancers15113020] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Revised: 05/26/2023] [Accepted: 05/30/2023] [Indexed: 06/12/2023] Open
Abstract
Pancreatic cancer (PC) is one of the deadliest cancers. Developing biomarkers for chemotherapeutic response prediction is crucial for improving the dismal prognosis of advanced-PC patients (pts). To evaluate the potential of plasma metabolites as predictors of the response to chemotherapy for PC patients, we analyzed plasma metabolites using high-performance liquid chromatography-mass spectrometry from 31 cachectic, advanced-PC subjects enrolled into the PANCAX-1 (NCT02400398) prospective trial to receive a jejunal tube peptide-based diet for 12 weeks and who were planned for palliative chemotherapy. Overall, there were statistically significant differences in the levels of intermediates of multiple metabolic pathways in pts with a partial response (PR)/stable disease (SD) vs. progressive disease (PD) to chemotherapy. When stratified by the chemotherapy regimen, PD after 5-fluorouracil-based chemotherapy (e.g., FOLFIRINOX) was associated with decreased levels of amino acids (AAs). For gemcitabine-based chemotherapy (e.g., gemcitabine/nab-paclitaxel), PD was associated with increased levels of intermediates of glycolysis, the TCA cycle, nucleoside synthesis, and bile acid metabolism. These results demonstrate the feasibility of plasma metabolomics in a prospective cohort of advanced-PC patients for assessing the effect of enteral feeding as their primary source of nutrition. Metabolic signatures unique to FOLFIRINOX or gemcitabine/nab-paclitaxel may be predictive of a patient's response and warrant further study.
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Affiliation(s)
- Hayato Muranaka
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (H.M.); (A.H.); (A.O.); (N.M.); (V.P.-H.); (S.J.P.); (N.A.B.)
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Andrew Hendifar
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (H.M.); (A.H.); (A.O.); (N.M.); (V.P.-H.); (S.J.P.); (N.A.B.)
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Arsen Osipov
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (H.M.); (A.H.); (A.O.); (N.M.); (V.P.-H.); (S.J.P.); (N.A.B.)
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Natalie Moshayedi
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (H.M.); (A.H.); (A.O.); (N.M.); (V.P.-H.); (S.J.P.); (N.A.B.)
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Veronica Placencio-Hickok
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (H.M.); (A.H.); (A.O.); (N.M.); (V.P.-H.); (S.J.P.); (N.A.B.)
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Nicholas Tatonetti
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA;
| | - Aleksandr Stotland
- Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (A.S.); (S.P.); (J.V.E.)
| | - Sarah Parker
- Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (A.S.); (S.P.); (J.V.E.)
| | - Jennifer Van Eyk
- Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (A.S.); (S.P.); (J.V.E.)
| | - Stephen J. Pandol
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (H.M.); (A.H.); (A.O.); (N.M.); (V.P.-H.); (S.J.P.); (N.A.B.)
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Neil A. Bhowmick
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (H.M.); (A.H.); (A.O.); (N.M.); (V.P.-H.); (S.J.P.); (N.A.B.)
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
- Department of Research, VA Greater Los Angeles Healthcare System, Los Angeles, CA 90073, USA
| | - Jun Gong
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; (H.M.); (A.H.); (A.O.); (N.M.); (V.P.-H.); (S.J.P.); (N.A.B.)
- Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
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Zhao R, Ren S, Li C, Guo K, Lu Z, Tian L, He J, Zhang K, Cao Y, Liu S, Li D, Wang Z. Biomarkers for pancreatic cancer based on tissue and serum metabolomics analysis in a multicenter study. Cancer Med 2023; 12:5158-5171. [PMID: 36161527 PMCID: PMC9972159 DOI: 10.1002/cam4.5296] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 08/10/2022] [Accepted: 09/15/2022] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND Early detection of pancreatic ductal adenocarcinoma (PDAC) may improve the prognosis of patients. This study was to identify metabolic features of PDAC and to discover early detection biomarkers for PDAC by tissue and serum metabolomics analysis. METHODS We conducted nontargeted metabolomics analysis in tissue samples of 51 PDAC tumors, 40 noncancerous pancreatic tissues (NT), and 14 benign pancreatic neoplasms (BP) as well as serum samples from 80 patients with PDAC, 36 with BP, and 48 healthy controls (Ctr). The candidate metabolites identified from the initial analysis were further quantified using targeted analysis in serum samples of an independent cohort of 22 early stage PDAC, 27 BP, and 27 Ctr subjects. Unconditional binary logistic regression analysis was used to construct the optimal model for PDAC diagnosis. RESULTS Upregulated levels of fatty acids and lipids and downregulated amino acids were observed in tissue and serum samples of PDAC patients. Proline, creatine, and palmitic acid were identified as a panel of potential biomarkers to distinguish PDAC from BP and Ctr (odds ratio = 2.17, [95% confidence interval 1.34-3.53]). The three markers showed area under the receiver-operating characteristic curves (AUCs) of 0.854 and 0.865, respectively, for the comparison of PDAC versus Ctr and PDAC versus BP. The AUCs were 0.830 and 0.852 in the validation set and were improved to 0.949 and 0.909 when serum carbohydrate antigen 19-9 (CA19-9) was added to the model. CONCLUSION The novel metabolite biomarker panel identified in this study exhibited promising performance in distinguishing PDAC from BP or Ctr, especially in combination with CA19-9.
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Affiliation(s)
- Rui Zhao
- Department of Radiology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Shuai Ren
- Department of Radiology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Changyin Li
- Department of Clinical Pharmacology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Kai Guo
- Department of Radiology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Zipeng Lu
- Pancreas Center, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Lei Tian
- Pancreas Center, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Jian He
- Department of Nuclear Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Kai Zhang
- Pancreas Center, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China
| | - Yingying Cao
- Department of Radiology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Shijia Liu
- Department of Pharmacy, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Zhongqiu Wang
- Department of Radiology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
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Cao YY, Guo K, Zhao R, Li Y, Lv XJ, Lu ZP, Tian L, Ren S, Wang ZQ. Untargeted metabolomics characterization of the resectable pancreatic ductal adenocarcinoma. Digit Health 2023; 9:20552076231179007. [PMID: 37312938 PMCID: PMC10259126 DOI: 10.1177/20552076231179007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 05/12/2023] [Indexed: 06/15/2023] Open
Abstract
Background Diagnosis of pancreatic ductal adenocarcinoma (PDAC) is difficult due to the lack of specific symptoms and screening methods. Only less than 10% of PDAC patients are candidates for surgery at the time of diagnosis. Thus, there is a great global unmet need for valuable biomarkers that could improve the opportunity to detect PDAC at the resectable stage. This study aimed to develop a potential biomarker model for the detection of resectable PDAC by tissue and serum metabolomics. Methods Ultra-high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS/MS) was performed for metabolome quantification in 98 serum samples (49 PDAC patients and 49 healthy controls (HCs)) and 20 pairs of matched pancreatic cancer tissues (PCTs) and adjacent noncancerous tissues (ANTs) from PDAC patients. Univariate and multivariate analyses were used to profile the differential metabolites between PDAC and HC. Results A total of 12 differential metabolites were present in both serum and tissue samples of PDAC. Among them, a total of eight differential metabolites showed the same expressional levels, including four upregulated and four downregulated metabolites. Finally, a panel of three metabolites including 16-hydroxypalmitic acid, phenylalanine, and norleucine was constructed by logistic regression analysis. Notably, the panel was capable of distinguishing resectable PDAC from HC with an AUC value of 0.942. Additionally, a multimarker model based on the 3-metabolites-based panel and CA19-9 showed a better performance than the metabolites panel or CA19-9 alone (AUC: 0.968 vs. 0.942, 0.850). Conclusions Taken together, the resectable early-stage PDAC has unique metabolic features in serum and tissue samples. The defined panel of three metabolites has the potential value for early screening of PDAC at the resectable stage.
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Affiliation(s)
- Ying-Ying Cao
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Kai Guo
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Rui Zhao
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Yuan Li
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Xiao-Jing Lv
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Zi-Peng Lu
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Lei Tian
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shuai Ren
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Zhong-Qiu Wang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
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Wang J, Yang WY, Li XH, Xu B, Yang YW, Zhang B, Dai CM, Feng JF. Study on potential markers for diagnosis of renal cell carcinoma by serum untargeted metabolomics based on UPLC-MS/MS. Front Physiol 2022; 13:996248. [PMID: 36523562 PMCID: PMC9745078 DOI: 10.3389/fphys.2022.996248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Accepted: 11/16/2022] [Indexed: 08/30/2023] Open
Abstract
Objective: Renal cell carcinoma (RCC) is the most common malignancy of the kidney. However, there is no reliable biomarker with high sensitivity and specificity for diagnosis and differential diagnosis. This study aims to analyze serum metabolite profile of patients with RCC and screen for potential diagnostic biomarkers. Methods: Forty-five healthy controls (HC), 40 patients with benign kidney tumor (BKT) and 46 patients with RCC were enrolled in this study. Serum metabolites were detected by ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), and then subjected to multivariate statistical analysis, metabolic pathway analysis and diagnostic performance evaluation. Results: The changes of glycerophospholipid metabolism, phosphatidylinositol signaling system, glycerolipid metabolism, d-glutamine and d-glutamate metabolism, galactose metabolism, and folate biosynthesis were observed in RCC group. Two hundred and forty differential metabolites were screened between RCC and HC groups, and 64 differential metabolites were screened between RCC and BKT groups. Among them, 4 differential metabolites, including 3-β-D-Galactosyl-sn-glycerol, 7,8-Dihydroneopterin, lysophosphatidylcholine (LPC) 19:2, and γ-Aminobutyryl-lysine (an amino acid metabolite), were of high clinical value not only in the diagnosis of RCC (RCC group vs. HC group; AUC = 0.990, 0.916, 0.909, and 0.962; Sensitivity = 97.73%, 97.73%, 93.18%, and 86.36%; Specificity = 100.00%, 73.33%, 80.00%, and 95.56%), but also in the differential diagnosis of benign and malignant kidney tumors (RCC group vs. BKT group; AUC = 0.989, 0.941, 0.845 and 0.981; Sensitivity = 93.33%, 93.33%, 77.27% and 93.33%; Specificity = 100.00%, 84.21%, 78.38% and 92.11%). Conclusion: The occurrence of RCC may involve changes in multiple metabolic pathways. The 3-β-D-Galactosyl-sn-glycerol, 7,8-Dihydroneopterin, LPC 19:2 and γ-Aminobutyryl-lysine may be potential biomarkers for the diagnosis or differential diagnosis of RCC.
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Affiliation(s)
- Jun Wang
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Wen-Yu Yang
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xiao-Han Li
- Department of Medical Laboratory, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Bei Xu
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Yu-Wei Yang
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Bin Zhang
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Chun-Mei Dai
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Jia-Fu Feng
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
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Roth HE, Powers R. Meta-Analysis Reveals Both the Promises and the Challenges of Clinical Metabolomics. Cancers (Basel) 2022; 14:3992. [PMID: 36010984 PMCID: PMC9406125 DOI: 10.3390/cancers14163992] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 08/09/2022] [Accepted: 08/16/2022] [Indexed: 11/17/2022] Open
Abstract
Clinical metabolomics is a rapidly expanding field focused on identifying molecular biomarkers to aid in the efficient diagnosis and treatment of human diseases. Variations in study design, metabolomics methodologies, and investigator protocols raise serious concerns about the accuracy and reproducibility of these potential biomarkers. The explosive growth of the field has led to the recent availability of numerous replicate clinical studies, which permits an evaluation of the consistency of biomarkers identified across multiple metabolomics projects. Pancreatic ductal adenocarcinoma (PDAC) is the third-leading cause of cancer-related death and has the lowest five-year survival rate primarily due to the lack of an early diagnosis and the limited treatment options. Accordingly, PDAC has been a popular target of clinical metabolomics studies. We compiled 24 PDAC metabolomics studies from the scientific literature for a detailed meta-analysis. A consistent identification across these multiple studies allowed for the validation of potential clinical biomarkers of PDAC while also highlighting variations in study protocols that may explain poor reproducibility. Our meta-analysis identified 10 metabolites that may serve as PDAC biomarkers and warrant further investigation. However, 87% of the 655 metabolites identified as potential biomarkers were identified in single studies. Differences in cohort size and demographics, p-value choice, fold-change significance, sample type, handling and storage, data collection, and analysis were all factors that likely contributed to this apparently large false positive rate. Our meta-analysis demonstrated the need for consistent experimental design and normalized practices to accurately leverage clinical metabolomics data for reliable and reproducible biomarker discovery.
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Affiliation(s)
- Heidi E. Roth
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
- Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
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9
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Islam MM, Goertzen A, Singh PK, Saha R. Exploring the metabolic landscape of pancreatic ductal adenocarcinoma cells using genome-scale metabolic modeling. iScience 2022; 25:104483. [PMID: 35712079 PMCID: PMC9194136 DOI: 10.1016/j.isci.2022.104483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 04/08/2022] [Accepted: 05/23/2022] [Indexed: 11/18/2022] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a major research focus because of its poor therapy response and dismal prognosis. PDAC cells adapt their metabolism to the surrounding environment, often relying on diverse nutrient sources. Because traditional experimental techniques appear exhaustive to find a viable therapeutic strategy, a highly curated and omics-informed PDAC genome-scale metabolic model was reconstructed using patient-specific transcriptomics data. From the model-predictions, several new metabolic functions were explored as potential therapeutic targets in addition to the known metabolic hallmarks of PDAC. Significant downregulation in the peroxisomal beta oxidation pathway, flux modulation in the carnitine shuttle system, and upregulation in the reactive oxygen species detoxification pathway reactions were observed. These unique metabolic traits of PDAC were correlated with potential drug combinations targeting genes with poor prognosis in PDAC. Overall, this study provides a better understanding of the metabolic vulnerabilities in PDAC and will lead to novel effective therapeutic strategies.
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Affiliation(s)
- Mohammad Mazharul Islam
- Department of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Andrea Goertzen
- Department of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
| | - Pankaj K. Singh
- Fred & Pamela Buffett Cancer Center, University of Nebraska Medical Center, Omaha, NE 68198, USA
- Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Rajib Saha
- Department of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
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10
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Cao Y, Zhao R, Guo K, Ren S, Zhang Y, Lu Z, Tian L, Li T, Chen X, Wang Z. Potential Metabolite Biomarkers for Early Detection of Stage-I Pancreatic Ductal Adenocarcinoma. Front Oncol 2022; 11:744667. [PMID: 35127469 PMCID: PMC8807510 DOI: 10.3389/fonc.2021.744667] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 12/31/2021] [Indexed: 12/21/2022] Open
Abstract
Background & Objectives Pancreatic ductal adenocarcinoma remains an extremely malignant tumor having a poor prognosis. The 5-year survival rate of PDAC is related to its stage (about 80% for stage I vs 20% for other stages). However, detection of PDAC in an early stage is difficult due to the lack of effective screening methods. In this study, we aimed to construct a novel metabolic model for stage-I PDAC detection, using both serum and tissue samples. Methods We employed an untargeted technique, UHPLC-Q-TOF-MS, to identify the potential metabolite, and then used a targeted technique, GC-TOF-MS, to quantitatively validate. Multivariate and univariate statistics were performed to analyze the metabolomic profiles between stage-I PDAC and healthy controls, including 90 serum and 53 tissue samples. 28 patients with stage-I PDAC and 62 healthy controls were included in this study. Results A total of 10 potential metabolites presented the same expression levels both in serum and in tissue. Among them, a 2-metabolites-model (isoleucine and adrenic acid) for stage-I PDAC was constructed. The area under the curve (AUC) value was 0.93 in the discovery set and 0.90 in the independent validation set. Especially, the serum metabolite model had a better diagnostic performance than CA19-9 (AUC = 0.79). Pathway analysis revealed 11 altered pathways in both serum and tissue of stage-I PDAC. Conclusions This study developed a novel serum metabolites model that could early separate stage-I PDAC from healthy controls.
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Affiliation(s)
- Yingying Cao
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Rui Zhao
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Kai Guo
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Shuai Ren
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Yaping Zhang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Zipeng Lu
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Lei Tian
- Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Tao Li
- Department of Pathology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiao Chen
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
- *Correspondence: Xiao Chen, ; Zhongqiu Wang,
| | - Zhongqiu Wang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
- *Correspondence: Xiao Chen, ; Zhongqiu Wang,
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11
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Ge P, Luo Y, Chen H, Liu J, Guo H, Xu C, Qu J, Zhang G, Chen H. Application of Mass Spectrometry in Pancreatic Cancer Translational Research. Front Oncol 2021; 11:667427. [PMID: 34707986 PMCID: PMC8544753 DOI: 10.3389/fonc.2021.667427] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 05/31/2021] [Indexed: 12/15/2022] Open
Abstract
Pancreatic cancer (PC) is one of the most common malignant tumors in the digestive tract worldwide, with increased morbidity and mortality. In recent years, with the development of surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, and the change of the medical thinking model, remarkable progress has been made in researching comprehensive diagnosis and treatment of PC. However, the present situation of diagnostic and treatment of PC is still unsatisfactory. There is an urgent need for academia to fully integrate the basic research and clinical data from PC to form a research model conducive to clinical translation and promote the proper treatment of PC. This paper summarized the translation progress of mass spectrometry (MS) in the pathogenesis, diagnosis, prognosis, and PC treatment to promote the basic research results of PC into clinical diagnosis and treatment.
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Affiliation(s)
- Peng Ge
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China.,Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China.,Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yalan Luo
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China.,Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China
| | - Haiyang Chen
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China.,Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China.,Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Jiayue Liu
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China.,Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China.,Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Haoya Guo
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China.,Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China.,Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Caiming Xu
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Jialin Qu
- Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China.,Laboratory of Integrative Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Guixin Zhang
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China.,Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China
| | - Hailong Chen
- Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China.,Institute (College) of Integrative Medicine, Dalian Medical University, Dalian, China
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12
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Perales S, Torres C, Jimenez-Luna C, Prados J, Martinez-Galan J, Sanchez-Manas JM, Caba O. Liquid biopsy approach to pancreatic cancer. World J Gastrointest Oncol 2021; 13:1263-1287. [PMID: 34721766 PMCID: PMC8529923 DOI: 10.4251/wjgo.v13.i10.1263] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 05/18/2021] [Accepted: 08/27/2021] [Indexed: 02/06/2023] Open
Abstract
Pancreatic cancer (PC) continues to pose a major clinical challenge. There has been little improvement in patient survival over the past few decades, and it is projected to become the second leading cause of cancer mortality by 2030. The dismal 5-year survival rate of less than 10% after the diagnosis is attributable to the lack of early symptoms, the absence of specific biomarkers for an early diagnosis, and the inadequacy of available chemotherapies. Most patients are diagnosed when the disease has already metastasized and cannot be treated. Cancer interception is vital, actively intervening in the malignization process before the development of a full-blown advanced tumor. An early diagnosis of PC has a dramatic impact on the survival of patients, and improved techniques are urgently needed to detect and evaluate this disease at an early stage. It is difficult to obtain tissue biopsies from the pancreas due to its anatomical position; however, liquid biopsies are readily available and can provide useful information for the diagnosis, prognosis, stratification, and follow-up of patients with PC and for the design of individually tailored treatments. The aim of this review was to provide an update of the latest advances in knowledge on the application of carbohydrates, proteins, cell-free nucleic acids, circulating tumor cells, metabolome compounds, exosomes, and platelets in blood as potential biomarkers for PC, focusing on their clinical relevance and potential for improving patient outcomes.
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Affiliation(s)
- Sonia Perales
- Department of Biochemistry and Molecular Biology I, Faculty of Sciences, University of Granada, Granada 18071, Spain
| | - Carolina Torres
- Department of Biochemistry and Molecular Biology III and Immunology, Faculty of Sciences, University of Granada, Granada 18071, Spain
| | - Cristina Jimenez-Luna
- Institute of Biopathology and Regenerative Medicine (IBIMER), Center of Biomedical Research (CIBM), University of Granada, Granada 18100, Spain
| | - Jose Prados
- Institute of Biopathology and Regenerative Medicine (IBIMER), Center of Biomedical Research (CIBM), University of Granada, Granada 18100, Spain
| | - Joaquina Martinez-Galan
- Department of Medical Oncology, Hospital Universitario Virgen de las Nieves, Granada 18011, Spain
| | | | - Octavio Caba
- Institute of Biopathology and Regenerative Medicine (IBIMER), Center of Biomedical Research (CIBM), University of Granada, Granada 18100, Spain
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13
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Rajesh S, Cox MJ, Runau F. Molecular advances in pancreatic cancer: A genomic, proteomic and metabolomic approach. World J Gastroenterol 2021; 27:5171-5180. [PMID: 34497442 PMCID: PMC8384751 DOI: 10.3748/wjg.v27.i31.5171] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 04/11/2021] [Accepted: 08/03/2021] [Indexed: 02/06/2023] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) represents a challenging pathology with very poor outcomes and is increasing in incidence within the general population. The majority of patients are diagnosed incidentally with insidious symptoms and hence present late in the disease process. This significantly affects patient outcomes: the only cure is surgical resection but only up to 20% of patients present with resectable disease at the time of clinical presentation. The use of “omic” technology is expanding rapidly in the field of personalised medicine - using genomic, proteomic and metabolomic approaches allows researchers and clinicians to delve deep into the core molecular processes of this difficult disease. This review gives an overview of the current findings in PDAC using these “omic” approaches and summarises useful markers in aiding clinicians treating PDAC. Future strategies incorporating these findings and potential application of these methods are presented in this review article.
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Affiliation(s)
- Srujan Rajesh
- Department of General Surgery, Leicester General Hospital, Leicester LE5 4PW, United Kingdom
| | - Michael J Cox
- Department of General Surgery, Leicester General Hospital, Leicester LE5 4PW, United Kingdom
| | - Franscois Runau
- Department of General Surgery, Leicester General Hospital, Leicester LE5 4PW, United Kingdom
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14
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Padthaisong S, Phetcharaburanin J, Klanrit P, Li JV, Namwat N, Khuntikeo N, Titapun A, Jarearnrat A, Wangwiwatsin A, Mahalapbutr P, Loilome W. Integration of global metabolomics and lipidomics approaches reveals the molecular mechanisms and the potential biomarkers for postoperative recurrence in early-stage cholangiocarcinoma. Cancer Metab 2021; 9:30. [PMID: 34348794 PMCID: PMC8335966 DOI: 10.1186/s40170-021-00266-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 07/21/2021] [Indexed: 02/08/2023] Open
Abstract
Background Cholangiocarcioma (CCA) treatment is challenging because most of the patients are diagnosed when the disease is advanced, and cancer recurrence is the main problem after treatment, leading to low survival rates. Therefore, our understanding of the mechanism underlying CCA recurrence is essential in order to prevent CCA recurrence and improve patient outcomes. Methods We performed 1H-NMR and UPLC-MS-based metabolomics on the CCA serum. The differential metabolites were further analyzed using pathway analysis and potential biomarker identification. Results At an early stage, the metabolites involved in energy metabolisms, such as pyruvate metabolism, and the TCA cycle, are downregulated, while most lipids, including TGs, PCs, PEs, and PAs, are upregulated in recurrence patients. This metabolic feature has been described in cancer stem-like cell (CSC) metabolism. In addition, the CSC markers CD44v6 and CD44v8-10 are associated with CD36 (a protein involved in lipid uptake) as well as with recurrence-free survival. We also found that citrate, sarcosine, succinate, creatine, creatinine and pyruvate, and TGs have good predictive values for CCA recurrence. Conclusion Our study demonstrates the possible molecular mechanisms underlying CCA recurrence, and these may associate with the existence of CSCs. The metabolic change involved in the recurrence pathway might be used to determine biomarkers for predicting CCA recurrence. Supplementary Information The online version contains supplementary material available at 10.1186/s40170-021-00266-5.
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Affiliation(s)
- Sureerat Padthaisong
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, 123 Mittraparp Road, Muang District, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Screening and Care Program (CASCAP), Khon Kaen University, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Research Institute, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Jutarop Phetcharaburanin
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, 123 Mittraparp Road, Muang District, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Screening and Care Program (CASCAP), Khon Kaen University, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Research Institute, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Poramate Klanrit
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, 123 Mittraparp Road, Muang District, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Screening and Care Program (CASCAP), Khon Kaen University, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Research Institute, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Jia V Li
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - Nisana Namwat
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, 123 Mittraparp Road, Muang District, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Screening and Care Program (CASCAP), Khon Kaen University, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Research Institute, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Narong Khuntikeo
- Cholangiocarcinoma Screening and Care Program (CASCAP), Khon Kaen University, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Research Institute, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand.,Department of Surgery, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Attapol Titapun
- Cholangiocarcinoma Screening and Care Program (CASCAP), Khon Kaen University, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Research Institute, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand.,Department of Surgery, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Apiwat Jarearnrat
- Cholangiocarcinoma Screening and Care Program (CASCAP), Khon Kaen University, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Research Institute, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand.,Department of Surgery, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Arporn Wangwiwatsin
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, 123 Mittraparp Road, Muang District, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Screening and Care Program (CASCAP), Khon Kaen University, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Research Institute, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Panupong Mahalapbutr
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, 123 Mittraparp Road, Muang District, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Screening and Care Program (CASCAP), Khon Kaen University, Khon Kaen, 40002, Thailand.,Cholangiocarcinoma Research Institute, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand
| | - Watcharin Loilome
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, 123 Mittraparp Road, Muang District, Khon Kaen, 40002, Thailand. .,Cholangiocarcinoma Screening and Care Program (CASCAP), Khon Kaen University, Khon Kaen, 40002, Thailand. .,Cholangiocarcinoma Research Institute, Faculty of Medicine, Khon Kaen University, Khon Kaen, 40002, Thailand.
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15
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Li Y, Su Z, Wei B, Qin M, Liang Z. Bioinformatics analysis identified MMP14 and COL12A1 as immune-related biomarkers associated with pancreatic adenocarcinoma prognosis. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2021; 18:5921-5942. [PMID: 34517516 DOI: 10.3934/mbe.2021296] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND Pancreatic adenocarcinoma (PAAD) is one of the most common malignant tumors with high mortality rates and a poor prognosis. There is an urgent need to determine the molecular mechanism of PAAD tumorigenesis and identify promising biomarkers for the diagnosis and targeted therapy of the disease. METHODS Three GEO datasets (GSE62165, GSE15471 and GSE62452) were analyzed to obtain differentially expressed genes (DEGs). The PPI networks and hub genes were identified through the STRING database and MCODE plugin in Cytoscape software. GO and KEGG enrichment pathways were analyzed by the DAVID database. The GEPIA database was utilized to estimate the prognostic value of hub genes. Furthermore, the roles of MMP14 and COL12A1 in immune infiltration and tumor-immune interaction and their biological functions in PAAD were explored by TIMER, TISIDB, GeneMANIA, Metascape and GSEA. RESULTS A total of 209 common DEGs in the three datasets were obtained. GO function analysis showed that the 209 DEGs were significantly enriched in calcium ion binding, serine-type endopeptidase activity, integrin binding, extracellular matrix structural constituent and collagen binding. KEGG pathway analysis showed that DEGs were mainly enriched in focal adhesion, protein digestion and absorption and ECM-receptor interaction. The 14 genes with the highest degree of connectivity were defined as the hub genes of PAAD development. GEPIA revealed that PAAD patients with upregulated MMP14 and COL12A1 expression had poor prognoses. In addition, TIMER analysis revealed that MMP14 and COL12A1 were closely associated with the infiltration levels of macrophages, neutrophils and dendritic cells in PAAD. TISIDB revealed that MMP14 was strongly positively correlated with CD276, TNFSF4, CD70 and TNFSF9, while COL12A1 was strongly positively correlated with TNFSF4, CD276, ENTPD1 and CD70. GSEA revealed that MMP14 and COL12A1 were significantly enriched in epithelial mesenchymal transition, extracellular matrix receptor interaction, apical junction, and focal adhesion in PAAD development. CONCLUSIONS Our study revealed that overexpression of MMP14 and COL12A1 is significantly correlated with PAAD patient poor prognosis. MMP14 and COL12A1 participate in regulating tumor immune interactions and might become promising biomarkers for PAAD.
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Affiliation(s)
- Yuexian Li
- Department of Gastroenterology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
| | - Zhou Su
- Department of Gastroenterology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
| | - Biwei Wei
- Department of Gastroenterology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
| | - Mengbin Qin
- Department of Gastroenterology, The Second Affiliated Hospital of Guangxi Medical University, Nanning 530007, China
| | - Zhihai Liang
- Department of Gastroenterology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
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16
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Al-Shaheri FN, Alhamdani MSS, Bauer AS, Giese N, Büchler MW, Hackert T, Hoheisel JD. Blood biomarkers for differential diagnosis and early detection of pancreatic cancer. Cancer Treat Rev 2021; 96:102193. [PMID: 33865174 DOI: 10.1016/j.ctrv.2021.102193] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 03/17/2021] [Accepted: 03/19/2021] [Indexed: 12/12/2022]
Abstract
Pancreatic cancer is currently the most lethal tumor entity and case numbers are rising. It will soon be the second most frequent cause of cancer-related death in the Western world. Mortality is close to incidence and patient survival after diagnosis stands at about five months. Blood-based diagnostics could be one crucial factor for improving this dismal situation and is at a stage that could make this possible. Here, we are reviewing the current state of affairs with its problems and promises, looking at various molecule types. Reported results are evaluated in the overall context. Also, we are proposing steps toward clinical utility that should advance the development toward clinical application by improving biomarker quality but also by defining distinct clinical objectives and the respective diagnostic accuracies required to achieve them. Many of the discussed points and conclusions are highly relevant to other solid tumors, too.
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Affiliation(s)
- Fawaz N Al-Shaheri
- Division of Functional Genome Analysis, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany; Medical Faculty Heidelberg, Heidelberg University, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany.
| | - Mohamed S S Alhamdani
- Division of Functional Genome Analysis, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Andrea S Bauer
- Division of Functional Genome Analysis, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Nathalia Giese
- Department of General Surgery, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
| | - Markus W Büchler
- Department of General Surgery, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
| | - Thilo Hackert
- Department of General Surgery, University Hospital Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany
| | - Jörg D Hoheisel
- Division of Functional Genome Analysis, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
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17
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Sahni S, Pandya AR, Hadden WJ, Nahm CB, Maloney S, Cook V, Toft JA, Wilkinson-White L, Gill AJ, Samra JS, Dona A, Mittal A. A unique urinary metabolomic signature for the detection of pancreatic ductal adenocarcinoma. Int J Cancer 2020; 148:1508-1518. [PMID: 33128797 DOI: 10.1002/ijc.33368] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 09/24/2020] [Accepted: 10/20/2020] [Indexed: 12/13/2022]
Abstract
Our study aimed to identify a urinary metabolite panel for the detection/diagnosis of pancreatic ductal adenocarcinoma (PDAC). PDAC continues to have poor survival outcomes. One of the major reasons for poor prognosis is the advanced stage of the disease at diagnosis. Hence, identification of a novel and cost-effective biomarker signature for early detection/diagnosis of PDAC could lead to better survival outcomes. Untargeted metabolomics was employed to identify a novel metabolite-based biomarker signature for PDAC diagnosis. Urinary metabolites from 92 PDAC patients (56 discovery cohort and 36 validation cohort) were compared with 56 healthy volunteers using 1 H nuclear magnetic resonance spectroscopy. Multivariate (partial-least squares discriminate analysis) and univariate (Mann-Whitney's U-test) analyses were performed to identify a metabolite panel which can be used to detect PDAC. The selected metabolites were further validated for their diagnostic potential using the area under the receiver operating characteristic (AUROC) curve. Statistical analysis identified a six-metabolite panel (trigonelline, glycolate, hippurate, creatine, myoinositol and hydroxyacetone), which demonstrated high potential to diagnose PDAC, with AUROC of 0.933 and 0.864 in the discovery and validation cohort, respectively. Notably, the identified panel also demonstrated very high potential to diagnose early-stage (I and II) PDAC patients with AUROC of 0.897. These results demonstrate that the selected metabolite signature could be used to detect PDAC and will pave the way for the development of a urinary test for detection/diagnosis of PDAC.
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Affiliation(s)
- Sumit Sahni
- Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Kolling Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia.,Australian Pancreatic Centre, Sydney, New South Wales, Australia
| | - Advait R Pandya
- Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Kolling Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - William J Hadden
- Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Kolling Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - Christopher B Nahm
- Kolling Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia.,Upper GI Surgical Unit, Royal North Shore Hospital and North Shore Private Hospital, New South Wales, Australia
| | - Sarah Maloney
- Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Kolling Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - Victoria Cook
- Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Kolling Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - James A Toft
- Nepean Clinical School, University of Sydney, New South Wales, Australia
| | | | - Anthony J Gill
- Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Kolling Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia.,Cancer Diagnosis and Pathology Group, Kolling Institute of Medical Research, Royal North Shore Hospital, St Leonards, New South Wales, Australia
| | - Jaswinder S Samra
- Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Australian Pancreatic Centre, Sydney, New South Wales, Australia.,Upper GI Surgical Unit, Royal North Shore Hospital and North Shore Private Hospital, New South Wales, Australia
| | - Anthony Dona
- Kolling Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - Anubhav Mittal
- Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Australian Pancreatic Centre, Sydney, New South Wales, Australia.,Upper GI Surgical Unit, Royal North Shore Hospital and North Shore Private Hospital, New South Wales, Australia
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Tang Z, Xu Z, Zhu X, Zhang J. New insights into molecules and pathways of cancer metabolism and therapeutic implications. Cancer Commun (Lond) 2020; 41:16-36. [PMID: 33174400 PMCID: PMC7819563 DOI: 10.1002/cac2.12112] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2020] [Revised: 08/17/2020] [Accepted: 11/04/2020] [Indexed: 12/13/2022] Open
Abstract
Cancer cells are abnormal cells that can reproduce and regenerate rapidly. They are characterized by unlimited proliferation, transformation and migration, and can destroy normal cells. To meet the needs for cell proliferation and migration, tumor cells acquire molecular materials and energy through unusual metabolic pathways as their metabolism is more vigorous than that of normal cells. Multiple carcinogenic signaling pathways eventually converge to regulate three major metabolic pathways in tumor cells, including glucose, lipid, and amino acid metabolism. The distinct metabolic signatures of cancer cells reflect that metabolic changes are indispensable for the genesis and development of tumor cells. In this review, we report the unique metabolic alterations in tumor cells which occur through various signaling axes, and present various modalities available for cancer diagnosis and clinical therapy. We further provide suggestions for the development of anti‐tumor therapeutic drugs.
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Affiliation(s)
- Zhenye Tang
- Southern Marine Science and Engineering Guangdong Laboratory Zhanjiang, the Marine Medical Research Institute of Guangdong Zhanjiang, Guangdong Medical University, Zhanjiang, Guangdong, 524023, P. R. China.,Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang), Zhanjiang, Guangdong, 524023, P. R. China
| | - Zhenhua Xu
- Center for Cancer and Immunology, Brain Tumor Institute, Children's National Health System, Washington, DC, 20010, USA
| | - Xiao Zhu
- Southern Marine Science and Engineering Guangdong Laboratory Zhanjiang, the Marine Medical Research Institute of Guangdong Zhanjiang, Guangdong Medical University, Zhanjiang, Guangdong, 524023, P. R. China.,Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang), Zhanjiang, Guangdong, 524023, P. R. China.,The Key Lab of Zhanjiang for R&D Marine Microbial Resources in the Beibu Gulf Rim, Guangdong Medical University, Zhanjiang, Guangdong, 524023, P. R. China.,The Marine Biomedical Research Institute of Guangdong Zhanjiang, Guangdong Medical University, Zhanjiang, Guangdong, 524023, P. R. China
| | - Jinfang Zhang
- Lingnan Medical Research Center, the First Affiliated Hospital of Guangzhou University of Chinese Medicine, the First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510405, P. R. China
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