Figure 1 - uploaded by Hyunsoo Kim
Content may be subject to copyright.
Venn diagram of data mining and overall flowchart. (A) A Venn diagram of the data mining. A total of 235 proteins were searched in the public database Oncomine, and four proteins with mutant forms were added to the Oncomine-based proteins: KRAS_G12D, AGER_G82S, GNAS_R201C, and GNAS_R201H. The sum of these proteins is displayed with the ONCOMINE + Mutant category of the Venn diagram. A total of 161 proteins were then searched in previous papers and PPD. These proteins are displayed with previous papers and the PPD category of the Venn diagram. A total of 260 proteins were selected as the initial target proteins and processed further. (B) Overall flowchart of the quantitative analysis of IPMN. The IPMN samples were divided into two groups: a training set and a test set. The training set consisted of 34 IPMN and 50 heterogeneous control plasma samples, including benign controls. The test set was composed of 50 IPMN and 50 healthy control plasma samples after sample randomization and blind testing. MRM quantification for the discovery of marker candidates was performed in the training set, and 22 proteins were discovered as IPMN candidate markers for further verification; 11 of the 22 proteins were verified in an independent sample set (test set) and were selected as IPMN candidate markers. For the fixed-marker candidates, multivariate analysis was performed by combining candidates by logistic regression. Consequently, a six-protein panel was constructed in the training set and verified in the test set. This panel had powerful discriminatory power against benign controls and healthy controls. In a further verification step by cross-validation, the classifiers performed consistently and reliably, regardless of sample composition.
Source publication
Intraductal papillary mucinous neoplasm (IPMN) is a common precursor of pancreatic cancer (PC). Much clinical attention has been directed toward IPMNs due to the increase in the prevalence of PC. The diagnosis of IPMN depends primarily on a radiological examination, but the diagnostic accuracy of this tool is not satisfactory, necessitating the dev...
Contexts in source publication
Context 1
... total of four mutant forms of KRAS, GNAS, and AGER were added on the basis of their significance in PC. 11−13 Next, 18 studies that were related to the pancreatic cancer proteome were examined by manual inspection 14−31 and filtered using the Plasma Proteome Database (PPD, http:// www.plasmaproteomedatabase.org) 32 to improve the detection rate by mass spectrometry; 161 proteins were selected as a result. Thus, a total of 260 proteins were selected as initial MRM target proteins through these steps ( Figure 1A), listed in Supplementary Table 1. ...
Context 2
... total of 260 PC-related proteins were selected by data-mining with previous reports and a public database ( Figure 1A). Of these proteins, 104 unique candidates were detected in the pooled plasma sample by MRM analysis (40% detection rate). ...
Context 3
... we performed 5-fold cross- validation with 100 replicates to determine whether the discriminatory power of the multimarker panel was over- estimated. The overall scheme is presented in Figure 1B. ...
Context 4
... suitable sample size of the test set was calculated using the design sample-size module in MSstats based on data on the training set. Consequently, approximately 50 biological replicates were required to show a statistical power of 0.9 on the basis of 22 preliminary candidates (Supplementary Figure 1). Thus, the test set was composed of 50 healthy control and 50 IPMN plasma samples. ...
Similar publications
The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadt...
Due to its specificity and sensitivity, targeted proteomics using mass spectrometry for multiple reaction monitoring (MRM) is a powerful tool to detect and quantify pre-selected peptides from a complex background and facilitates the absolute quantification of peptides using isotope-labeled forms as internal standards. How to generate isotope-labele...
Background: Multipotent Mesenchymal Stromal Cells (MSCs) are used in tissue engineering and regenerative medicine. The in vitro isolation and expansion of MSCs involve the use of foetal bovine serum (FBS). However, many concerns have been raised regarding the safety of this product. In this study, alternative additives derived either from periphera...
The multiple roles of extracellular vesicles (EVs) in pathogenesis have received much attention, as they are valuable as diagnostic and prognostic biomarkers. We employed polymeric EV precipitation to isolate EVs from clinical specimens to overcome the limitations of ultracentrifugation (UC), such as low protein yields, a large volume of specimens...
In this work, we developed and validated a robust and sensitive method of liquid chromatography with high-resolution mass spectrometry in parallel reaction monitoring (PRM) mode for ST-246 (tecovirimat) quantification in human blood plasma. The method was compared with the multiple reaction monitoring (MRM) technique and showed better selectivity a...
Citations
... High levels distinguish PDAC from chronic pancreatitis. Elevated during formation of intraductal papillary mucinous neoplasm [185,[253][254][255][256][257][258] Serum ...
The secreted glycoprotein leucine-rich α-2 glycoprotein 1 (LRG1) was first described as a key player in pathogenic ocular neovascularization almost a decade ago. Since then, an increasing number of publications have reported the involvement of LRG1 in multiple human conditions including cancer, diabetes, cardiovascular disease, neurological disease, and inflammatory disorders. The purpose of this review is to provide, for the first time, a comprehensive overview of the LRG1 literature considering its role in health and disease. Although LRG1 is constitutively expressed by hepatocytes and neutrophils, Lrg1 −/− mice show no overt phenotypic abnormality suggesting that LRG1 is essentially redundant in development and homeostasis. However, emerging data are challenging this view by suggesting a novel role for LRG1 in innate immunity and preservation of tissue integrity. While our understanding of beneficial LRG1 functions in physiology remains limited, a consistent body of evidence shows that, in response to various inflammatory stimuli, LRG1 expression is induced and directly contributes to disease pathogenesis. Its potential role as a biomarker for the diagnosis, prognosis and monitoring of multiple conditions is widely discussed while dissecting the mechanisms underlying LRG1 pathogenic functions. Emphasis is given to the role that LRG1 plays as a vasculopathic factor where it disrupts the cellular interactions normally required for the formation and maintenance of mature vessels, thereby indirectly contributing to the establishment of a highly hypoxic and immunosuppressive microenvironment. In addition, LRG1 has also been reported to affect other cell types (including epithelial, immune, mesenchymal and cancer cells) mostly by modulating the TGFβ signalling pathway in a context-dependent manner. Crucially, animal studies have shown that LRG1 inhibition, through gene deletion or a function-blocking antibody, is sufficient to attenuate disease progression. In view of this, and taking into consideration its role as an upstream modifier of TGFβ signalling, LRG1 is suggested as a potentially important therapeutic target. While further investigations are needed to fill gaps in our current understanding of LRG1 function, the studies reviewed here confirm LRG1 as a pleiotropic and pathogenic signalling molecule providing a strong rationale for its use in the clinic as a biomarker and therapeutic target.
... Tissue specific upregulation of IGFBP3 in PDAC compared to IPMN have been previously found [13]. IGFBP3 has been shown to discriminate the early stage IPMNC from that of healthy controls [14,15] and our results show that already at LG stage of IPMN this protein is discriminatory to healthy controls. ...
Background
Intraductal Papillary Mucinous Neoplasia (IPMN) are potentially malignant cystic tumors of the pancreas. IPMN can progress from low to moderate to high grade dysplasia and further to IPMN associated carcinoma. Often the difference between benign and malignant nature of the IPMN is not clear preoperatively. We aim to elucidate molecular expression patterns of various grades of IPMN and pancreatic carcinoma. Additionally we suggest potential novel biomarkers to differentiate IPMN from healthy individuals and pancreatic carcinoma to enable early detection as well as help in differential diagnosis in future.
Methods
We have performed retrospective label-free proteomic analysis of the serum samples from 44 patients with various grades of benign IPMN or IPMN associated carcinoma and 11 healthy controls. Proteomic data was further analyzed by various multivariate statistical methods. Four groups of samples (low-grade, high-grade IPMN, pancreatic carcinoma and age- and sex-matched healthy controls) were compared with ANOVA. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) modeling gave S-plot for feature selection. Stringently selected potential markers were further evaluated with ROC curve analysis and area under the curve was calculated. Differentially expressed proteins were used for pathway analysis. Linear trend analysis (Mann Kendall test) was used for identifying significant increasing or decreasing trends from healthy-low grade-high grade IPMN-pancreatic carcinoma.
Results
Based on protein expression (436 proteins quantified), PCA separated most sample groups from each other. S-Plot selected biomarker panels with moderate to very high AUC values for differentiating controls from Low-, High-Grade IPMN and carcinoma. Linear trend analysis identified 12 proteins which were consistently increasing or decreasing trend among the groups. We found potential biomarkers to differentiate healthy controls from different degrees of dysplasia and pancreatic carcinoma. These biomarkers can classify IPMN, carcinoma and healthy controls from each other which is an unmet clinical need. Data are available via ProteomeXchange with identifier PXD009139.
Conclusion
Kininogen-1 was able to differentiate healthy persons from low and high-grade IPMN. Retinol binding protein-4 could classify the low-grade IPMN from pancreatic carcinoma. Twelve proteins including apolipoproteins and complement proteins had significantly increasing or decreasing trends from healthy to low to high-grade IPMN to pancreatic carcinoma.
... This study presents an effective workflow for the selection of putative biomarkers, including validation in a large cohort (Tier 2) [56]. Kim et al. [57] focused on the diagnosis of Intraductal papillary mucinous neoplasm (IPMN), which is a precursor of PC stages. Plasma samples from 184 patients corresponding tolow and intermediate-grade dysplasia IPMN, high-grade dysplasia IPMN, invasive IPMN, and controls were divided into a training (n = 84) and a test (n = 100) set (Table S1). ...
... This panel exhibited better performance than the known biomarkers CEA and CA19-9 (training set: AUC CEA = 0.568, AUC CA19-9= 0.628test set: AUC CEA = 0.647, AUC CA19-9= 0.551). This study (classified as Tier 2) addressed a significant clinical need (biomarkers for early PC detection), nevertheless, the risk for overfitting is existent and, as also indicated by the authors, results should be validated in a larger independent cohort [57]. ...
Introduction: Multiple (or selected) reaction monitoring-mass spectrometry (MRM/SRM) is a targeted proteomic method that can be used for relative and absolute quantification. Multiple reports exist supporting the potential of the approach in proteomic biomarker validation.
Areas covered: To get an overview of the applications of MRM in protein quantification in plasma, a search in MedLine/PubMed was performed using the key words: “MRM/SRM plasma proteomic/proteomics/proteome”. The retrieved studies were further filtered to focus on disease biomarkers and main results are summarized.
Expert opinion: MRM is increasingly employed for the quantification of both well-established but also newly discovered putative biomarkers and occasionally their post-translationally modified forms in plasma. Fractionation is regularly required for the detection of low abundance proteins. Standardized procedures to facilitate assay establishment and marker quantification have been proposed and, in few cases, implemented. Nevertheless, in most cases, absolute quantification is not performed. To advance, multiple technical issues including the regular use of standard labelled peptides and appropriate quality controls to monitor assay performance should be considered. Additionally, clinical aspects involving careful study design to address biomarker clinical use should also be considered.
... Yoneyama et al. [92] observed that the diagnostic value of CA19-9 to detect early-stage PC was improved when combined with insulin-like growth factor binding protein (IGFBP) 2 and IGFBP3. Likewise, Kim et al. [93] recently reported that a biomarker panel comprised of six proteins, including IGFBP2 and IGFBP3, had a high capacity to distinguish patients with intraductal papillary mucinous neoplasm (IPMN) from controls (healthy individuals or with other benign disease). ...
Pancreatic cancer (PC) is a highly malignant disease that represents the fourth leading cancer-related death worldwide. There has been very little improvement in survival rates over recent years, and surgical resection remains the only reliable curative approach. Factors that contribute to this dismal prognosis for PC include its rapid progression and invasion, the absence of specific symptoms, and the little impact of available chemotherapy. Importantly, the management of this malignancy is also limited by the lack of highly specific and sensitive biomarkers for its diagnosis and follow-up, and their identification is therefore considered a promising strategy to improve outcomes in these patients. Numerous translational studies have explored the usefulness of body fluids as a non-invasive source of PC-specific biomarkers, and innovations in proteomic methods and technologies have provided a myriad of protein biomarkers for different cancers. The adoption of a proteomic approach has improved understanding of the biology of PC and contributed to the potential identification of protein biomarkers for this disease. This review considers the most recent research efforts to develop novel proteomic biomarkers in body fluids for PC.
... Besides being controversial and raising debates, current IPMN management lacks biofluid based markers. In this regard, based on a multi reaction monitoring (MRM) proteomics study Kim et al. [19] proposed a six plasma protein multimarker panel to assist the overall diagnosis of IPMN in comparison to healthy controls. Furthermore, first efforts to classify IPMN as benign or malignant were directed towards already established cancer biomarkers. ...
... Samples like tissue [24,25] and cyst fluids [24] can identify released proteins which can be further analyzed in targeted approaches in biofluids. However, more recently, Kim et al. [19] analyzed plasma in an MRM approach and proposed a six-protein panel for the diagnosis of IPMN in comparison to controls. Four of those proteins, namely insulin growth factor binding protein 2 (IBP2), plasma kallikrein (KLKB1), cofactor 5 (CO5), and leucine-rich alpha-2-glycoprotein (A2GL) were among our 370 proteins considered for quantification. ...
... Four of those proteins, namely insulin growth factor binding protein 2 (IBP2), plasma kallikrein (KLKB1), cofactor 5 (CO5), and leucine-rich alpha-2-glycoprotein (A2GL) were among our 370 proteins considered for quantification. For IBP2 and KLKB1 our findings are in line with Kim et al. [19] with IBP2 and KLKB1 being more and less abundant, respectively, in the plasma of IPMN patients compared to HC patients (Supplementary Tables S1 and S2). However, when comparing IPMN and CP, a sample group which was not included by Kim et al., no significant difference was found for the two proteins. ...
Efforts for the early diagnosis of the pancreatic ductal adenocarcinoma (PDAC) have recently been driven to one of the precursor lesions, namely intraductal papillary mucinous neoplasm of the pancreas (IPMN). Only a few studies have focused on IPMN molecular biology and its overall progression to cancer. Therefore, IPMN lacks comprehensive characterization which makes its clinical management controversial. In this study, we characterized plasma proteins in the presence of IPMNs in comparison to healthy controls, chronic pancreatitis, and PDAC by a proteomics approach using data-independent acquisition based mass spectrometry. We describe several protein sets that could aid IPMN diagnosis, but also differentiation of IPMN from healthy controls, as well as from benign and malignant diseases. Among all, high levels of carbonic anhydrases and hemoglobins were characteristic for the IPMN group. By employing ELISA based quantification we validated our results for human tissue inhibitor of metalloproteinase inhibitor 1 (TIMP-1). We consider IPMN management directed towards an early potential cancer development a crucial opportunity before PDAC initiation and thus its early detection and cure.
... For the discovery and verification study, 134 plasma samples [pancreatic ductal adenocarcinoma (PDAC) =50, pancreatic benign (PB) =34, normal control (NL) =50] were drawn between January 2011 and December 2013. All samples, except for PDAC, were acquired from our study on intraductal papillary mucinous neoplasms (IPMNs) [13], the purpose of which differed and in which the data were processed independently. The details on the collection of clinical samples are provided on Supplementary materials and methods. ...
... High abundant plasma proteins were immunedepleted on a multiple affinity removal system (MARS) column, concentrated, digested by trypsin, and desalted as described previously [13]. The prepared samples were frozen, lyophilized on speed vacuum centrifuges, and stored at -80°C until analysis. ...
Due to its high mortality rate and asymptomatic nature, early detection rates of pancreatic ductal adenocarcinoma (PDAC) remain poor.
We measured 1000 biomarker candidates in 134 clinical plasma samples by multiple reaction monitoring-mass spectrometry (MRM-MS). Differentially abundant proteins were assembled into a multimarker panel from a training set (n=684) and validated in independent set (n=318) from five centers. The level of panel proteins was also confirmed by immunoassays. The panel including leucine-rich alpha-2 glycoprotein (LRG1), transthyretin (TTR), and CA19-9 had a sensitivity of 82.5% and a specificity of 92.1%. The triple-marker panel exceeded the diagnostic performance of CA19-9 by more than 10% (AUCCA19-9 = 0.826, AUCpanel= 0.931, P < 0.01) in all PDAC samples and by more than 30% (AUCCA19-9 = 0.520, AUCpanel = 0.830, P < 0.001) in patients with normal range of CA19-9 (<37U/mL). Further, it differentiated PDAC from benign pancreatic disease (AUCCA19-9 = 0.812, AUCpanel = 0.892, P < 0.01) and other cancers (AUCCA19-9 = 0.796, AUCpanel = 0.899, P < 0.001).
Overall, the multimarker panel that we have developed and validated in large-scale samples by MRM-MS and immunoassay has clinical applicability in the early detection of PDAC.
... 22 Mass spectrometry (MS)-based proteomics has been essential in biomarker discovery studies identifying proteins in various body fluids where accessibility is a desirable attribute. 23 Due to the proximity of cyst fluid to pancreatic neoplastic lesions, cystic fluid provides unique insight into the process by which pancreatic lesions develop. To date, few proteomic studies of pancreatic cyst fluid have been conducted. ...
Rationale:
In recent years, the molecular components of pancreatic cyst fluid has been used for diagnosis and prognosis. Because the protein markers that are currently used in clinical tests are unreliable, proteomic studies to find new protein markers are being conducted. However, such researches have been limited due to the complexity of pancreatic cyst fluid and the immaturity of proteomic techniques.
Methods:
To overcome these limitations and provide a pancreatic cyst proteome dataset, we examined cyst fluid proteome with tandem mass spectrometry. The proteomic analysis was performed using Orbitrap-based mass spectrometer Q-Exactive coupled with 50-cm long nano liquid chromatography. Protein mutations were identified using mutation sequence database search.
Results:
A total of 5,850 protein groups were identified from microliters of cyst fluid. Among those, 3,934 protein groups were reported for the first time in pancreatic cyst fluid. Although high-abundance proteins were not depleted in the experiment, our dataset detected almost all pancreatic tumor markers such as mucin family members, S100 proteins, and CEA-related proteins. In addition, 590 protein mutation marker candidates were discovered.
Conclusions:
We provide a comprehensive cyst proteome dataset that includes cystic cellular proteins and mutated proteins. Our findings would serve as a rich resource for further IPMN studies and clinical applications. The MS data have been deposited in the ProteomeXchange with identifier PXD005671 (http://proteomecentral.proteomexchange.org/dataset/PXD005671).
... IGFBP2 was also suggested to increase in risk diseases of pancreatic malignancy, such as IPMNs (Table 6). Kim et al. recently reported that a six-protein panel had high discriminating power in distinguishing between IPMMs and controls, and their protein panel included IGFBP2 and IGFBP3 [54]. This result supports the idea that these molecules are promising biomarker candidates for IPMNs. ...
Pancreatic cancer is one of the most lethal tumors, and reliable detection of early-stage pancreatic cancer and risk diseases for pancreatic cancer is essential to improve the prognosis. As 260 genes were previously reported to be upregulated in invasive ductal adenocarcinoma of pancreas (IDACP) cells, quantification of the corresponding proteins in plasma might be useful for IDACP diagnosis. Therefore, the purpose of the present study was to identify plasma biomarkers for early detection of IDACP by using two proteomics strategies: antibody-based proteomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics. Among the 260 genes, we focused on 130 encoded proteins with known function for which antibodies were available. Twenty-three proteins showed values of the area under the curve (AUC) of more than 0.8 in receiver operating characteristic (ROC) analysis of reverse-phase protein array (RPPA) data of IDACP patients compared with healthy controls, and these proteins were selected as biomarker candidates. We then used our high-throughput selected reaction monitoring or multiple reaction monitoring (SRM/MRM) methodology, together with an automated sample preparation system, micro LC and auto analysis system, to quantify these candidate proteins in plasma from healthy controls and IDACP patients on a large scale. The results revealed that insulin-like growth factor-binding protein (IGFBP)2 and IGFBP3 have the ability to discriminate IDACP patients at an early stage from healthy controls, and IGFBP2 appeared to be increased in risk diseases of pancreatic malignancy, such as intraductal papillary mucinous neoplasms (IPMNs). Furthermore, diagnosis of IDACP using the combination of carbohydrate antigen 19–9 (CA19-9), IGFBP2 and IGFBP3 is significantly more effective than CA19-9 alone. This suggests that IGFBP2 and IGFBP3 may serve as compensatory biomarkers for CA19-9. Early diagnosis with this marker combination may improve the prognosis of IDACP patients.
In the oncological area, pancreatic cancer is one of the most lethal diseases, with 5-year survival rising just 10% in high-development countries. This disease is genetically characterized by KRAS as a driven mutation followed by SMAD4, CDKN2, and TP53-associated mutations. In clinical aspects, pancreatic cancer presents unspecific clinical symptoms with the absence of screening and early plasmatic biomarker, being that CA19-9 is the unique plasmatic biomarker having specificity and sensitivity limitations. We analyzed the plasmatic exosome proteomic profile of 23 patients with pancreatic cancer and 10 healthy controls by using Nanoscale liquid chromatography coupled to tandem mass spectrometry (NanoLC-MS/MS). The pancreatic cancer patients were subdivided into IPMN and PDAC. Our findings show 33, 34, and 7 differentially expressed proteins when comparing the IPMN vs. control, PDAC-No treatment vs. control, and PDAC-No treatment vs. IPMN groups, highlighting proteins of the complement system and coagulation, such as C3, APOB, and SERPINA. Additionally, PDAC with no treatment showed 11 differentially expressed proteins when compared to Folfirinox neoadjuvant therapy or Gemcitabine adjuvant therapy. So here, we found plasmatic exosome-derived differentially expressed proteins among cancer patients (IPMN, PDAC) when comparing with healthy controls, which could represent alternative biomarkers for diagnostic and prognostic evaluation, supporting further scientific and clinical studies on pancreatic cancer.
Pancreatic cancer (PC) is a leading cause of cancer related mortality on a global scale. The disease itself is associated with a dismal prognosis, partly due to its silent nature resulting in patients presenting with advanced disease at the time of diagnosis. To combat this, there has been an explosion in the last decade of potential candidate biomarkers in the research setting in the hope that a diagnostic biomarker may provide a glimmer of hope in what is otherwise quite a substantial clinical dilemma. Currently, serum carbohydrate antigen 19-9 is utilized in the diagnostic work-up of patients diagnosed with PC however this biomarker lacks the sensitivity and specificity associated with a gold-standard marker. In the search for a biomarker that is both sensitive and specific for the diagnosis of PC, there has been a paradigm shift towards a focus on liquid biopsy and the use of diagnostic panels which has subsequently proved to have efficacy in the diagnosis of PC. Currently, promising developments in the field of early detection on PC using diagnostic biomarkers include the detection of microRNA (miRNA) in serum and circulating tumour cells. Both these modalities, although in their infancy and yet to be widely accepted into routine clinical practice, possess merit in the early detection of PC. We reviewed over 300 biomarkers with the aim to provide an in-depth summary of the current state-of-play regarding diagnostic biomarkers in PC (serum, urinary, salivary, faecal, pancreatic juice and biliary fluid).
