Serum Biomarker Panels for the Detection of Pancreatic Cancer
Purpose: Serum–biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations. Experimental Design: Eighty-three circulating proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC, n = 333), ben...
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| Published in | Clinical cancer research Vol. 17; no. 4; pp. 805 - 816 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Philadelphia, PA
American Association for Cancer Research
15.02.2011
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1078-0432 1557-3265 1557-3265 |
| DOI | 10.1158/1078-0432.CCR-10-0248 |
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| Abstract | Purpose: Serum–biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations.
Experimental Design: Eighty-three circulating proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC, n = 333), benign pancreatic conditions (n = 144), and healthy control individuals (n = 227). Samples from each group were split randomly into training and blinded validation sets prior to analysis. A Metropolis algorithm with Monte Carlo simulation (MMC) was used to identify discriminatory biomarker panels in the training set. Identified panels were evaluated in the validation set and in patients diagnosed with colon (n = 33), lung (n = 62), and breast (n = 108) cancers.
Results: Several robust profiles of protein alterations were present in sera of PDAC patients compared to the Healthy and Benign groups. In the training set (n = 160 PDAC, 74 Benign, 107 Healthy), the panel of CA 19–9, ICAM-1, and OPG discriminated PDAC patients from Healthy controls with a sensitivity/specificity (SN/SP) of 88/90%, while the panel of CA 19–9, CEA, and TIMP-1 discriminated PDAC patients from Benign subjects with an SN/SP of 76/90%. In an independent validation set (n = 173 PDAC, 70 Benign, 120 Healthy), the panel of CA 19–9, ICAM-1 and OPG demonstrated an SN/SP of 78/94% while the panel of CA19–9, CEA, and TIMP-1 demonstrated an SN/SP of 71/89%. The CA19–9, ICAM-1, OPG panel is selective for PDAC and does not recognize breast (SP = 100%), lung (SP = 97%), or colon (SP = 97%) cancer.
Conclusions: The PDAC-specific biomarker panels identified in this investigation warrant additional clinical validation to determine their role in screening targeted high-risk populations. Clin Cancer Res; 17(4); 805–16. ©2010 AACR. |
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| AbstractList | Serum-biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations.
Eighty-three circulating proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC, n = 333), benign pancreatic conditions (n = 144), and healthy control individuals (n = 227). Samples from each group were split randomly into training and blinded validation sets prior to analysis. A Metropolis algorithm with Monte Carlo simulation (MMC) was used to identify discriminatory biomarker panels in the training set. Identified panels were evaluated in the validation set and in patients diagnosed with colon (n = 33), lung (n = 62), and breast (n = 108) cancers.
Several robust profiles of protein alterations were present in sera of PDAC patients compared to the Healthy and Benign groups. In the training set (n = 160 PDAC, 74 Benign, 107 Healthy), the panel of CA 19-9, ICAM-1, and OPG discriminated PDAC patients from Healthy controls with a sensitivity/specificity (SN/SP) of 88/90%, while the panel of CA 19-9, CEA, and TIMP-1 discriminated PDAC patients from Benign subjects with an SN/SP of 76/90%. In an independent validation set (n = 173 PDAC, 70 Benign, 120 Healthy), the panel of CA 19-9, ICAM-1 and OPG demonstrated an SN/SP of 78/94% while the panel of CA19-9, CEA, and TIMP-1 demonstrated an SN/SP of 71/89%. The CA19-9, ICAM-1, OPG panel is selective for PDAC and does not recognize breast (SP = 100%), lung (SP = 97%), or colon (SP = 97%) cancer.
The PDAC-specific biomarker panels identified in this investigation warrant additional clinical validation to determine their role in screening targeted high-risk populations. Serum-biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations.PURPOSESerum-biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations.Eighty-three circulating proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC, n = 333), benign pancreatic conditions (n = 144), and healthy control individuals (n = 227). Samples from each group were split randomly into training and blinded validation sets prior to analysis. A Metropolis algorithm with Monte Carlo simulation (MMC) was used to identify discriminatory biomarker panels in the training set. Identified panels were evaluated in the validation set and in patients diagnosed with colon (n = 33), lung (n = 62), and breast (n = 108) cancers.EXPERIMENTAL DESIGNEighty-three circulating proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC, n = 333), benign pancreatic conditions (n = 144), and healthy control individuals (n = 227). Samples from each group were split randomly into training and blinded validation sets prior to analysis. A Metropolis algorithm with Monte Carlo simulation (MMC) was used to identify discriminatory biomarker panels in the training set. Identified panels were evaluated in the validation set and in patients diagnosed with colon (n = 33), lung (n = 62), and breast (n = 108) cancers.Several robust profiles of protein alterations were present in sera of PDAC patients compared to the Healthy and Benign groups. In the training set (n = 160 PDAC, 74 Benign, 107 Healthy), the panel of CA 19-9, ICAM-1, and OPG discriminated PDAC patients from Healthy controls with a sensitivity/specificity (SN/SP) of 88/90%, while the panel of CA 19-9, CEA, and TIMP-1 discriminated PDAC patients from Benign subjects with an SN/SP of 76/90%. In an independent validation set (n = 173 PDAC, 70 Benign, 120 Healthy), the panel of CA 19-9, ICAM-1 and OPG demonstrated an SN/SP of 78/94% while the panel of CA19-9, CEA, and TIMP-1 demonstrated an SN/SP of 71/89%. The CA19-9, ICAM-1, OPG panel is selective for PDAC and does not recognize breast (SP = 100%), lung (SP = 97%), or colon (SP = 97%) cancer.RESULTSSeveral robust profiles of protein alterations were present in sera of PDAC patients compared to the Healthy and Benign groups. In the training set (n = 160 PDAC, 74 Benign, 107 Healthy), the panel of CA 19-9, ICAM-1, and OPG discriminated PDAC patients from Healthy controls with a sensitivity/specificity (SN/SP) of 88/90%, while the panel of CA 19-9, CEA, and TIMP-1 discriminated PDAC patients from Benign subjects with an SN/SP of 76/90%. In an independent validation set (n = 173 PDAC, 70 Benign, 120 Healthy), the panel of CA 19-9, ICAM-1 and OPG demonstrated an SN/SP of 78/94% while the panel of CA19-9, CEA, and TIMP-1 demonstrated an SN/SP of 71/89%. The CA19-9, ICAM-1, OPG panel is selective for PDAC and does not recognize breast (SP = 100%), lung (SP = 97%), or colon (SP = 97%) cancer.The PDAC-specific biomarker panels identified in this investigation warrant additional clinical validation to determine their role in screening targeted high-risk populations.CONCLUSIONSThe PDAC-specific biomarker panels identified in this investigation warrant additional clinical validation to determine their role in screening targeted high-risk populations. Purpose: Serum–biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations. Experimental Design: Eighty-three circulating proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC, n = 333), benign pancreatic conditions (n = 144), and healthy control individuals (n = 227). Samples from each group were split randomly into training and blinded validation sets prior to analysis. A Metropolis algorithm with Monte Carlo simulation (MMC) was used to identify discriminatory biomarker panels in the training set. Identified panels were evaluated in the validation set and in patients diagnosed with colon (n = 33), lung (n = 62), and breast (n = 108) cancers. Results: Several robust profiles of protein alterations were present in sera of PDAC patients compared to the Healthy and Benign groups. In the training set (n = 160 PDAC, 74 Benign, 107 Healthy), the panel of CA 19–9, ICAM-1, and OPG discriminated PDAC patients from Healthy controls with a sensitivity/specificity (SN/SP) of 88/90%, while the panel of CA 19–9, CEA, and TIMP-1 discriminated PDAC patients from Benign subjects with an SN/SP of 76/90%. In an independent validation set (n = 173 PDAC, 70 Benign, 120 Healthy), the panel of CA 19–9, ICAM-1 and OPG demonstrated an SN/SP of 78/94% while the panel of CA19–9, CEA, and TIMP-1 demonstrated an SN/SP of 71/89%. The CA19–9, ICAM-1, OPG panel is selective for PDAC and does not recognize breast (SP = 100%), lung (SP = 97%), or colon (SP = 97%) cancer. Conclusions: The PDAC-specific biomarker panels identified in this investigation warrant additional clinical validation to determine their role in screening targeted high-risk populations. Clin Cancer Res; 17(4); 805–16. ©2010 AACR. |
| Author | Langmead, Christopher J. Brand, Randall E. Grizzle, William E. Lokshin, Anna E. Allen, Peter J. Landsittel, Douglas P. Elton, Eric Whitcomb, David C. Goldberg, Michael Arnoletti, Juan P. Vickers, Selwyn M. Eloubeidi, Mohamad A. Zeh, Herbert J. Christein, John D. Nolen, Brian M. |
| AuthorAffiliation | 16 Department of Pathology, School of Medicine, University of Pittsburgh, S-417 BST, 200 Lothrop Street, Pittsburgh, PA 15261 9 Department of Surgery, General Surgical Gastrointestinal Section, University of Alabama at Birmingham, 1922 7th Avenue South, KB 417, Birmingham, AL 35294 14 Department of Cell Biology and Physiology, School of Medicine, University of Pittsburgh, S362 Biomedical Science Towers, 3500 Terrace Street, Pittsburgh, PA 15261 12 Center for Research on Health Care Data Center, Institute for Clinical Research Education, University of Pittsburgh, 200 Meyran Ave, Suite 300, Pittsburgh, PA 15213 7 Department of Medicine, Section of Gastroenterology, NorthShore University HealthSystems, 2650 Ridge Ave, Evanston, IL 60021 4 Department of Surgery, Hillman Cancer Center, University of Pittsburgh Cancer Institute, Pittsburgh, PA 15213 11 Department of Computer Science and Lane Center for Computational Biology, Carnegie Mellon University, 7401 Gates-Hillman Center, 5000 Forbes Avenue |
| AuthorAffiliation_xml | – name: 14 Department of Cell Biology and Physiology, School of Medicine, University of Pittsburgh, S362 Biomedical Science Towers, 3500 Terrace Street, Pittsburgh, PA 15261 – name: 17 Department of Ob/Gyn, School of Medicine, University of Pittsburgh, 300 Halket Street Pittsburgh, PA 15213 – name: 6 Department of Medicine, Gastroenterology/Hepatology, University of Alabama at Birmingham, 701 19th Street South, LHRB 408, Birmingham, AL 35294 – name: 15 Department of Pathology, University of Alabama at Birmingham, Birmingham, Alabama 35294 – name: 4 Department of Surgery, Hillman Cancer Center, University of Pittsburgh Cancer Institute, Pittsburgh, PA 15213 – name: 13 Department of Medicine, School of Medicine, University of Pittsburgh, 1218 Scaife Hall, 3550 Terrace Street, Pittsburgh, PA 15213 – name: 5 Department of Surgery, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065 – name: 9 Department of Surgery, General Surgical Gastrointestinal Section, University of Alabama at Birmingham, 1922 7th Avenue South, KB 417, Birmingham, AL 35294 – name: 7 Department of Medicine, Section of Gastroenterology, NorthShore University HealthSystems, 2650 Ridge Ave, Evanston, IL 60021 – name: 3 Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, A300 Crabtree Hall, 130 Desoto Street, Pittsburgh, PA 15261 – name: 16 Department of Pathology, School of Medicine, University of Pittsburgh, S-417 BST, 200 Lothrop Street, Pittsburgh, PA 15261 – name: 11 Department of Computer Science and Lane Center for Computational Biology, Carnegie Mellon University, 7401 Gates-Hillman Center, 5000 Forbes Avenue, Pittsburgh, PA 15213 – name: 12 Center for Research on Health Care Data Center, Institute for Clinical Research Education, University of Pittsburgh, 200 Meyran Ave, Suite 300, Pittsburgh, PA 15213 – name: 1 Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh and University of Pittsburgh Medical Center, Hillman Cancer Center, Suite 2.32, 5117 Centre Ave, Pittsburgh, PA 15213 – name: 2 University of Pittsburgh Cancer Institute, Hillman Cancer Center, 5117 Centre Avenue 1.18, Pittsburgh, PA, 15213 – name: 8 Department of Surgery, General Surgical Oncology Section, University of Alabama at Birmingham, 1922 7th Avenue South, KB 321, Birmingham, AL 35294 – name: 10 Department of Surgery, University of Minnesota, MMC195, 420 Delaware, Minneapolis, MN, 55455 |
| Author_xml | – sequence: 1 givenname: Randall E. surname: Brand fullname: Brand, Randall E. – sequence: 2 givenname: Brian M. surname: Nolen fullname: Nolen, Brian M. – sequence: 3 givenname: Herbert J. surname: Zeh fullname: Zeh, Herbert J. – sequence: 4 givenname: Peter J. surname: Allen fullname: Allen, Peter J. – sequence: 5 givenname: Mohamad A. surname: Eloubeidi fullname: Eloubeidi, Mohamad A. – sequence: 6 givenname: Michael surname: Goldberg fullname: Goldberg, Michael – sequence: 7 givenname: Eric surname: Elton fullname: Elton, Eric – sequence: 8 givenname: Juan P. surname: Arnoletti fullname: Arnoletti, Juan P. – sequence: 9 givenname: John D. surname: Christein fullname: Christein, John D. – sequence: 10 givenname: Selwyn M. surname: Vickers fullname: Vickers, Selwyn M. – sequence: 11 givenname: Christopher J. surname: Langmead fullname: Langmead, Christopher J. – sequence: 12 givenname: Douglas P. surname: Landsittel fullname: Landsittel, Douglas P. – sequence: 13 givenname: David C. surname: Whitcomb fullname: Whitcomb, David C. – sequence: 14 givenname: William E. surname: Grizzle fullname: Grizzle, William E. – sequence: 15 givenname: Anna E. surname: Lokshin fullname: Lokshin, Anna E. |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23865332$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/21325298$$D View this record in MEDLINE/PubMed |
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| Keywords | Biological fluid Pancreas cancer Biological marker Digestive diseases Serum Malignant tumor Diagnosis Detection Cancer Pancreatic disease |
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| Snippet | Purpose: Serum–biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations.
Experimental... Serum-biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations. Eighty-three circulating... Serum-biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations.PURPOSESerum-biomarker... |
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| SubjectTerms | Adolescent Adult Aged Aged, 80 and over Antineoplastic agents Biological and medical sciences Biomarkers, Tumor - blood Blood Proteins - metabolism Carcinoma, Pancreatic Ductal - diagnosis Carcinoma, Pancreatic Ductal - metabolism Case-Control Studies Female Gastroenterology. Liver. Pancreas. Abdomen Humans Liver. Biliary tract. Portal circulation. Exocrine pancreas Male Medical sciences Middle Aged Molecular Diagnostic Techniques - methods Molecular Diagnostic Techniques - statistics & numerical data Multivariate Analysis Pancreatic Neoplasms - diagnosis Pancreatic Neoplasms - metabolism Pharmacology. Drug treatments ROC Curve Sensitivity and Specificity Tumors Young Adult |
| Title | Serum Biomarker Panels for the Detection of Pancreatic Cancer |
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