Applying Proteomic-Based Biomarker Tools for the Accurate Diagnosis of Pancreatic Cancer

Kojima, Kensuke; Asmellash, Senait; Klug, Christopher A.; Grizzle, William E.; Mobley, James A.; Christein, John D.

doi:10.1007/s11605-008-0632-6

Cited by 32 publications

(27 citation statements)

References 16 publications

(18 reference statements)

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“…Previous studies focusing on this issue were conducted considering only patients with pancreatic cancer and controls (16,24), or had controls that included few patients with chronic or acute pancreatitis (18,21,25). As yet, no studies are available that have compared the serum proteomic profile of patients with pancreatic cancer with those having type 2 diabetes mellitus.…”

Section: Discussionmentioning

confidence: 99%

“…However, proteins present in high abundance such as albumin and immunoglobulins might obscure the identification of potentially new biomarkers that are present in low abundance (13,14). Sera from patients with cancer, including that from patients with pancreatic cancer, usually have a rich protein profile in the low molecular weight range (-15,000 Da) (15)(16)(17)(18)(19)(20)(21). The enrichment of low molecular weight peptides in sera from cancer patients may occur as a consequence of direct production by the tumor, or it may be due to expression of a biological cascade of enzymatically-generated and proteolytically-cleaved biomarker fragments.…”

Section: Introductionmentioning

confidence: 99%

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Pancreatic cancer biomarkers discovery by surface-enhanced laser desorption and ionization time-of-flight mass spectrometry

Navaglia

Fogar

Basso

et al. 2009

Clinical Chemistry and Laboratory Medicine

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Background: Surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF/MS), a laboratory-friendly technique, is used to identify biomarkers for cancer. The aim of the present study was to explore the application of SELDI proteomic patterns in serum for distinguishing between cases of pancreatic cancer, chronic pancreatitis, type 2 diabetes mellitus and healthy controls. Methods: Sera from 12 healthy controls, 24 patients with type 2 diabetes mellitus, 126 with pancreatic cancer, including 84 with diabetes, and 61 with chronic pancreatitis, 32 of which were diabetics, were analyzed using SELDI-TOF/MS. Spectra (IMAC-30) were clustered and classified using Biomarker Wizard and Biomarker Pattern software. Results: Two decision tree classification algorithms, one with and one without CA 19-9, were constructed. In the absence of CA 19-9, the splitting protein peaks were: m/z 1526, 1211, and 3519; when CA 19-9 was used in the analysis, it replaced the m/z 3519 splitter. The two algorithms performed equally for classifying patients. A classification tree that considered diabetic patients only was constructed; the main splitters were: 1211, CA 19-9, 7903, 3359, 1802. With this algorithm, 100% of patients with type 2 diabetes mellitus, 97% with chronic pancreatitis and 77% of patients with pancreatic cancer were correctly classified. SEL-DI-TOF/MS features improved the diagnostic accuracy of CA 19-9 (AUCs0.883 for CA 19-9; AUCs0.935 for CA 19-9 and SELDI-TOF/MS features combined).

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Pancreatic cancer biomarkers discovery by surface-enhanced laser desorption and ionization time-of-flight mass spectrometry

Navaglia

Fogar

Basso

et al. 2009

Clinical Chemistry and Laboratory Medicine

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“…At present hundreds to thousands of endogenous peptides, including peptides from low abundance blood proteins, can be routinely extracted and identified from blood fluids (Tucholska et al, 2007;Williams et al, 2007;Hu et al, 2009a). There has been an intense effort to identify (Marshall et al, 2003 and examine the low molecular mass polypeptides of blood, sometimes referred to as the peptidome (Verhaert et al, 2001;Jurgens & Schrader, 2002;Tirumalai et al, 2003;Merrell et al, 2004;Villanueva et al, 2004Villanueva et al, , 2006aVillanueva et al, ,b, 2007Villanueva et al, , 2008Ping et al, 2005;Rai et al, 2005;Tammen et al, 2005aTammen et al, ,b, 2007Falth et al, 2006Falth et al, , 2008Geho et al, 2006;Govorukhina et al, 2006;Hortin, 2006;Ogata et al, 2006;Huang et al, 2006b;Zheng, Baker, & Hancock, 2006b;Aristoteli, Molloy, & Baker, 2007;Tian et al, 2007;Tomonaga & Nomura, 2007;Tucholska et al, 2007;Hernandez et al, 2008;Kay et al, 2008;Kojima et al, 2008;Ly & Wasinger, 2008;Mayer, Poirier, & Seidah, 2008;Navare et al, 2008;Pernemalm et al, 2008;Plavina et al, 2008;Ward et al, 2008;Xia, Wu, & Jemal, 200...…”

Section: Mass Spectromtery Of Blood Endogenous Polypeptidesmentioning

confidence: 99%

Mass spectrometry of peptides and proteins from human blood

Zhu

Bowden

Zhang

et al. 2010

Mass Spectrometry Reviews

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It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

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“…Furthermore, MALDI-MS has been employed in the detection of biomarkers in kidney disease (16), genitourinary tumours, including bladder (17) and prostate cancer (18), and tumours outwith the genitourinary tract, including pancreatic (19) and colon cancer (20). In this preliminary study, MS was used to demonstrate that urine from cachectic GO cancer patients contained significantly more protein species than urine from weight-stable GO cancer patients and healthy controls, in the absence of an elevated CK level.…”

Section: Discussionmentioning

confidence: 99%

Mass spectrometric detection of candidate protein biomarkers of cancer cachexia in human urine

Skipworth

Stewart²,

Bhana³

et al. 2010

Int J Oncol

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Abstract. Increased membrane permeability and myofibrillar protein breakdown are established features of cancer cachexia. Proteins released from cachectic muscle may be excreted in urine to act as biomarkers of the cachectic process. Onedimensional SDS polyacrylamide gel electrophoresis followed by matrix-assisted laser desorption/ionisation or liquid chromatography tandem mass spectrometry was used to compare the protein content of urine from cachectic (>10% weight loss) (n=8) and weight-stable (n=8) gastro-oesophageal cancer patients and healthy controls (n=8). Plasma creatine kinase concentration was used as a marker of gross muscle breakdown. The number of protein species identified in cachectic samples (median 42; range 28-61; total 199) was greater than that identified in weight-stable cancer (median 15; range 9-28; total 79) and control samples (median 12.5; range 5-18; total 49) (P<0.001). Many of the proteins identified have not been reported previously in the urine of cancer patients. Proteins identified specifically in cachectic samples included muscle (myosin species), cytoskeletal (·-spectrin; nischarin) and microtubule-associated proteins (microtubule-actin crosslinking factor; microtubule-associated protein-1B; bullous pemphigoid antigen 1), whereas immunoglobulin κ-light chain and zinc ·-2 glycoprotein appeared to represent markers of cancer. The presence of myosin in urine (without an increase in plasma creatine kinase) is consistent with a specific loss of myosin as part of the cachectic process. Urinary proteomics using mass spectrometry can identify muscle-specific and non-muscle-specific candidate biomarkers of cancer cachexia.

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Applying Proteomic-Based Biomarker Tools for the Accurate Diagnosis of Pancreatic Cancer

Cited by 32 publications

References 16 publications

Pancreatic cancer biomarkers discovery by surface-enhanced laser desorption and ionization time-of-flight mass spectrometry

Pancreatic cancer biomarkers discovery by surface-enhanced laser desorption and ionization time-of-flight mass spectrometry

Mass spectrometry of peptides and proteins from human blood

Mass spectrometric detection of candidate protein biomarkers of cancer cachexia in human urine

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