Diagnostic performance enhancement of pancreatic cancer using proteomic multimarker panel

Park, Jiyoung; Choi, Y. S.; Namkung, Junghyun; Yi, Sung Gon; Kim, Hyunsoo; Yu, Jeesuk; Kim, Yongkang; Kwon, Min Seok; Kwon, Wooil; Oh, Do Youn; Kim, Sun Whe; Jeong, Seung Yong; Han, Wonshik; Lee, Kyu Eun; Heo, Jin Seok; Park, Joon Oh; Park, Joo Kyung; Kim, Song Cheol; Kang, Chang Moo; Lee, Woojin; Lee, Seungyeoun; Han, Sang-Hyun; Park, Taesung; Jang, Jin Young; Kim, Youngsoo

doi:10.18632/oncotarget.21861

Cited by 37 publications

(61 citation statements)

References 53 publications

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“…and specificity of 92.1%. 26 Although the origins and functions of LRG1 and transthyretin are unclear, the authors suggested that these proteins are highly relevant to PC. In their study, the target markers were not confined to metabolites, and this triple-marker panel appears to be useful for patients with PC and low CA19-9.…”

Section: Discussionmentioning

confidence: 99%

Metabolic Profiling of Plasma from Pancreatic Cancer Patients in Korea

Gwon¹,

Yoon²,

Seol³

et al. 2019

Korean J Pancreas Biliary Tract

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Backgrounds/Aims: Pancreatic cancer (PC) patients have poor prognoses because this cancer is typically diagnosed at an advanced stage and the therapeutic options are limited. We examined the potential of metabolic profiling for early diagnosis and identification of potential therapeutic targets. Methods: Ten patients and 10 healthy volunteer controls older than 20 years of age were enrolled between May and December 2015. The patients were confirmed to have pancreatic ductal adenocarcinoma cytologically or histologically. Blood plasma samples were derivatized and analyzed by gas chromatography mass spectrometry (GC-MS). Untargeted GC-MS data were analyzed using statistical methods, including Wilcoxon rank-sum test and principal component analyses. Results: L-lysine was 1.36-fold higher in patients than in healthy controls (p<0.05). L-leucine was 0.63-fold lower (p<0.01) and palmitic acid was 0.93-fold lower (p<0.5) in patients than in controls. Orthogonal partial least squared-discriminant analysis revealed significant differences between the patients and controls. Conclusions:This study suggests that the metabolic profiles of patients with PC are distinct from those of the healthy population. Further studies are required to develop methods for early diagnosis and identify therapeutic targets. Korean J Pancreas Biliary Tract 2019;24(2):61-67

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Section: Discussionmentioning

confidence: 99%

Metabolic Profiling of Plasma from Pancreatic Cancer Patients in Korea

Gwon¹,

Yoon²,

Seol³

et al. 2019

Korean J Pancreas Biliary Tract

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“…Park et al have verified 176 protein candidates with MRM in 134 clinical samples, and 54 of these were further validated with MRM and ELISA in large‐clinical plasma samples ( n = 1002) from multi‐clinics. In distinguishing PC from normal, benign disease states, and other cancers (colorectal, thyroid and breast cancer), a triple‐marker panel (LRG1, transthyretin (TTR) and CA 19‐9) can have AUC values of 0.931, 0.892 and 0.899, respectively …”

Section: Pancreatic Cancer (Pc)mentioning

confidence: 99%

“…Selected studies of analytically validated protein markers discovered by MS-based proteomics approach for PC BC: benign control and other cancers (colorectal, thyroid and breast cancer), a triplemarker panel (LRG1, transthyretin (TTR) and CA can have AUC values of 0.931, 0.892 and 0.899, respectively 70. …”

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confidence: 99%

Analytically validated protein biomarkers of chronic pancreatitis and pancreatic cancer for potential clinical diagnosis with mass spectrometry

Chang

Chen

2020

Rapid Comm Mass Spectrometry

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Rationale Chronic pancreatitis (CP) is a pancreatic disease with poor prognosis and pancreatic cancer (PC) is one of the most lethal types of cancer that is symptomless in the early stage. Because the clinical and image findings of CP can overlap that of pancreatic cancer (PC) which leads to confusion in the diagnosis and treatment of PC, discovery/verification/validation of more accurate protein biomarkers to diagnose CP and PC is in urgent need. Methods The PubMed, Web of Science, and Google Scholar were searched using the keywords: ‘biomarker’, ‘marker’, ‘chronic pancreatitis’, “pancreatic cancer” or “proteomics” for highly related researches. We focused on the articles published after the year 2005 in this review. Results We introduce the background to CP and PC and summarize the diagnosis of CP and PC, analytically validated protein biomarkers, and proteomic approaches for discovery/verification/validation. The potential use of mass spectrometry (MS) in clinical diagnosis is also discussed. Conclusions Continuously improving sensitivity of MS can provide deeper proteome for new marker discovery and high reliability for protein marker verification, validation, and clinical diagnosis. The analytically validated protein markers could be considered as targeted protein biomarkers for developing a MS platform in the clinical validation process or clinical diagnosis of CP and PC.

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“…Since Pearson's work in 1899, linear regression method has been the most popular way to develop stature estimation equations [13,19,21,[26][27][28][29][30][31]. In general, under an assumption of linearity between variables, linear regression analysis 1) describes a pattern of the relationship in a numeric form and/or 2) predicts one variable from another variable.…”

Section: Application To Extrapolation/extreme Casesmentioning

confidence: 99%

Caveats in Using Trotter and Gleser's (1958) Asian Equations for Stature Estimation

Jeong¹,

Jantz

2016

Korean J Phys Anthropol

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: Trotter and Gleser's (1958) Asian equations have most frequently been used for stature estimation of Korean skeletal remains. However, limitations or caveats in using those equations have rarely been argued. This study reviews five issues frequently overlooked in applying the equations and interpreting the outcomes.First, Trotter and Gleser (1958) multiply the standard errors by 2 to obtain the 95% prediction interval (PI). However, there is discrepancy between their calculation and actual PIs, and thus correct method for PI calculation is recommended. Secondly, given the uncertainty about the tibia length measurement, there is a possibility that the tibia-related equations yield biased estimates. Thirdly, since a mathematical error was incorporated in the development process of the combined equations, caution should be taken. Fourthly, extrapolation may cause additional unexpected error in applying regression equations. Therefore, it is necessary to check if a target sample falls within the reference sample range prior to using the equations. Lastly, applying Trotter and Gleser's (1958) equations to female samples should be avoided because they produce highly biased estimates.The issues discussed in this study will contribute to reducing potential errors associated with application of these equations, and eventually enhancing accuracy of the final stature estimates. If errors are anticipated but unavoidable, discussions about the potential errors should be made to minimize misunderstanding about the outcomes.

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Diagnostic performance enhancement of pancreatic cancer using proteomic multimarker panel

Cited by 37 publications

References 53 publications

Metabolic Profiling of Plasma from Pancreatic Cancer Patients in Korea

Metabolic Profiling of Plasma from Pancreatic Cancer Patients in Korea

Analytically validated protein biomarkers of chronic pancreatitis and pancreatic cancer for potential clinical diagnosis with mass spectrometry

Caveats in Using Trotter and Gleser's (1958) Asian Equations for Stature Estimation

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