proteomic studies are powerful tools for identifying useful new biomarkers , and much research is currently being performed in this area . however , the blood proteome is extraordinary difficult to analyze because protein concentrations can vary by 12 orders of magnitude . thus , biomarker discovery using proteomics requires the development of effective pretreatment protocols to reduce the complexity of blood samples . the identification of biomarkers from clinical samples generally needs large numbers of samples to be compared . the same is true for the identification of biomarkers by mass - spectrometry - coupled proteomics [ 2 , 3 ] . our proteomics analysis system of 2-dimensional image - converted analysis of liquid chromatography and mass spectrometry ( lc / ms ; 2dical ) and the procedure for reducing blood sample complexity have overcome these problems . we report the successful discovery of several new blood biomarkers for pancreatic and colorectal cancer [ 4 , 5 ] . we developed a multi - institutional protocol to preserve blood condition during sampling , storing , freezing , and thawing ; all samples were collected and managed at the national cancer center research institute . as the concentrations of different blood proteins can vary by over 12-orders of magnitude , it is essential to remove abundant proteins or to concentrate specific proteins before proteomics analysis . for this purpose , we used lectin affinity column [ 5 , 7 ] , major protein removal column , and hollow fiber membrane ( hfm ) [ 9 , 10 ] . to identify candidate biomarkers from the proteomics data , we utilized our 2dical analysis system that performs a quantitative comparison of unlabeled shotgun proteomics data generated by lc / ms and enables biomarker discovery from a large number of clinical samples . for selecting blood biomarkers , several decades of samples from cancer patients and healthy controls biomarkers selected by 2dical must be verified . as a rule , we first confirmed 2dical results using specific antibodies in small - scale immunoblotting assays . once marker expression was detected and differences in the expression between patient and control samples were confirmed , large - scale verification was conducted . for this purpose , we used in - house reverse phase protein microarrays ( rppa ) , which can simultaneously assess hundreds of blood samples by antibody staining [ 11 , 12 ] . validation at the hundred - sample scale by multiple reaction monitoring / selective reaction monitoring ( mrm / srm )   is also ongoing . we developed our original application for biomarker identification , that is , 2dical and rppa . it analyzes the data of mass to charge ratio ( m / z ) , peak intensity , retention time ( rt ) , and each sample generated by lc / ms as the elemental data ; it deploys various 2-dimensional images with different combinations of axes using these four elements . from the m / z - rt image , peaks derived from the same peptide in the direction of acquiring time are integrated . by adding algorisms to ensure reproducibility of m / z and rt , the same peak can be compared precisely across different samples , and a statistical comparison of identical peaks in different samples leads to the discovery of specific differentially expressed peptide peaks . specific peaks are designated by their m / z and rt coordinates , and further analysis is based on these identifiers . isotopic labeling is not necessary , and large numbers of samples can be analyzed in this way [ 4 , 8 ] . rppa is an emerging high - throughput proteomics technique for validating new biomarkers [ 14 , 15 ] . furthermore , rppa requires significantly lower amounts of clinical samples for quantification than established clinical tests such as enzyme - linked immunosorbent assay ( elisa ) . we made in - house rppa using proteochip glass slides ( proteogen , seoul , republic of korea ) to test hundreds of blood samples simultaneously . for this technique , serially diluted samples are randomly plotted in quadruplicate in a 6,144-spot / slide format using a robot . the spotted slides are incubated with the primary antibody and biotinylated secondary antibody and then processed with a streptavidin - horseradish peroxidase conjugate . statistical evaluation of the fluorescence intensity of individual samples is performed for large - scale validation of biomarker candidates [ 11 , 12 ] . several blood biomarkers have already been discovered . sample recruitment , sample preparation , biomarker discovery , and validation prolyl - hydroxylated -fibrinogen   and cxc chemokine ligand 7 ( cxcl-7 )   were identified as pancreatic cancer biomarkers . samplesin total , 86 plasma samples ( collected from 43 patients with pancreatic ductal adenocarcinomas and 43 healthy controls ) were used for biomarker identification , and 273 plasma samples ( collected from 160 patients with pancreatic ductal adenocarcinomas and 113 healthy controls ) were used for validation . 
  in total , 86 plasma samples ( collected from 43 patients with pancreatic ductal adenocarcinomas and 43 healthy controls ) were used for biomarker identification , and 273 plasma samples ( collected from 160 patients with pancreatic ductal adenocarcinomas and 113 healthy controls ) were used for validation . sample preparationsamples were treated with concanavalin a ( con a ) to reduce plasma protein complexity . samples were treated with concanavalin a ( con a ) to reduce plasma protein complexity . a total of 115325 peaks were detected , and 6 peaks of 412  m / z ( rt 13.7  min ) , 546  m / z ( 8.3  min ) , 552  m / z ( 8.3  min ) , 827  m / z ( 8.3  min ) , 1141  m / z ( 29.0  min ) , and 1185  m / z ( 9.2  min ) were statistically significant with > 2 fold difference and p < 0.0005 ( mann - whitney u test ) between the pancreatic cancer patient group and healthy control group . three of the 6 peaks were identified as hydroxyproline - modified -fibrinogen fragments ( figure 1(a ) ) . a total of 115325 peaks were detected , and 6 peaks of 412  m / z ( rt 13.7  min ) , 546  m / z ( 8.3  min ) , 552  m / z ( 8.3  min ) , 827  m / z ( 8.3  min ) , 1141  m / z ( 29.0  min ) , and 1185  m / z ( 9.2  min ) were statistically significant with > 2 fold difference and p < 0.0005 ( mann - whitney u test ) between the pancreatic cancer patient group and healthy control group . three of the 6 peaks were identified as hydroxyproline - modified -fibrinogen fragments ( figure 1(a ) ) . biomarker validationan antibody recognizing -fibrinogen fragments with an essshh p*giaefpsr ( p * , 4-hydroxyproline ) modification was generated and used for small - scale confirmation of the expression of prolyl - hydroxylated -fibrinogen and the differences in the expression of modified protein between samples of pancreatic cancer patients and healthy controls ( figure 1(b ) ) . a competitive elisa was developed using this antibody to quantify plasma levels of prolyl - hydroxylated -fibrinogen . a significant difference in prolyl - hydroxylated -fibrinogen expression between plasma samples from pancreatic cancer patients and healthy controls was observed ( p = 3.80  10 , mann - whitney u test ; figure 1(c ) ) . 
  an antibody recognizing -fibrinogen fragments with an essshh p*giaefpsr ( p * , 4-hydroxyproline ) modification was generated and used for small - scale confirmation of the expression of prolyl - hydroxylated -fibrinogen and the differences in the expression of modified protein between samples of pancreatic cancer patients and healthy controls ( figure 1(b ) ) . a competitive elisa was developed using this antibody to quantify plasma levels of prolyl - hydroxylated -fibrinogen . a significant difference in prolyl - hydroxylated -fibrinogen expression between plasma samples from pancreatic cancer patients and healthy controls was observed ( p = 3.80  10 , mann - whitney u test ; figure 1(c ) ) . samplesa total of 45 plasma samples ( collected from 24 patients with pancreatic ductal adenocarcinomas and 21 healthy controls ) were used for biomarker discovery and 227 plasma samples ( collected from 140 patients with pancreatic ductal adenocarcinomas and 87 healthy controls ) were used for biomarker validation . a total of 45 plasma samples ( collected from 24 patients with pancreatic ductal adenocarcinomas and 21 healthy controls ) were used for biomarker discovery and 227 plasma samples ( collected from 140 patients with pancreatic ductal adenocarcinomas and 87 healthy controls ) were used for biomarker validation . a total of 53009 peaks were detected , and 140 peaks were differentially expressed between pancreatic cancer patients and healthy controls , with an area under curve ( auc ) of > 0.800 . of these , 10 proteins were annotated by database search of tandem mass spectra . the 862  m / z ( rt 50.2  min ) peak annotated as a fragment of cxcl-7 was specifically expressed in pancreatic cancer patients , with an auc of 0.839 ( p = 4.54  10 by mann - whitney u test ) ( figure 2(a ) ) . a total of 53009 peaks were detected , and 140 peaks were differentially expressed between pancreatic cancer patients and healthy controls , with an area under curve ( auc ) of > 0.800 . of these , 10 proteins were annotated by database search of tandem mass spectra . the 862  m / z ( rt 50.2  min ) peak annotated as a fragment of cxcl-7 was specifically expressed in pancreatic cancer patients , with an auc of 0.839 ( p = 4.54  10 by mann - whitney u test ) ( figure 2(a ) ) . biomarker validationsmall - scale confirmation of cxcl7 identification and differential expression was done by immunoblotting using an anti - cxcl-7 antibody ( figure 2(b ) ) . for large - scale validation , 227 plasma samples were randomly plotted onto proteochip glass slides for rppa and blotted with an anti - cxcl-7 antibody . cxcl7 expression in pancreatic cancer patients and healthy controls was confirmed to be significantly different ( p = 1.40  10 , welch t - test ; figure 2(c ) ) . small - scale confirmation of cxcl7 identification and differential expression was done by immunoblotting using an anti - cxcl-7 antibody ( figure 2(b ) ) . for large - scale validation , 227 plasma samples were randomly plotted onto proteochip glass slides for rppa and blotted with an anti - cxcl-7 antibody . cxcl7 expression in pancreatic cancer patients and healthy controls was confirmed to be significantly different ( p = 1.40  10 , welch t - test ; figure 2(c ) ) . complement component 9 ( c9 )   and adipophilin   were identified as colorectal cancer biomarkers . samplesin total , 90 plasma samples ( collected from 31 colorectal cancer patients and 59 healthy controls ) were used for biomarker discovery , and 345 plasma samples ( collected from 115 colorectal cancer patients and 230 healthy controls ) were used for validation . 
  in total , 90 plasma samples ( collected from 31 colorectal cancer patients and 59 healthy controls ) were used for biomarker discovery , and 345 plasma samples ( collected from 115 colorectal cancer patients and 230 healthy controls ) were used for validation . sample preparationsamples were treated with a 12-abundant - plasma - protein removal columns to reduce plasma protein complexity . samples were treated with a 12-abundant - plasma - protein removal columns to reduce plasma protein complexity . a total of 94803 peaks were detected , and 90 peaks showed statistically significant differences in expression between plasma from colorectal cancer patients and healthy controls . a peptide peak with 622  m / z ( rt 56.8  min ) was annotated as a fragment of c9 specific to colorectal cancer patients ( p = 3.0  10 , paired t - test ; figure 3(a ) ) . a total of 94803 peaks were detected , and 90 peaks showed statistically significant differences in expression between plasma from colorectal cancer patients and healthy controls . a peptide peak with 622  m / z ( rt 56.8  min ) was annotated as a fragment of c9 specific to colorectal cancer patients ( p = 3.0  10 , paired t - test ; figure 3(a ) ) . biomarker validationsmall - scale confirmation of c9 identification and differential expression was done by immunoblotting using an anti - c9 antibody ( figure 3(b ) ) . for large - scale validation , 345 plasma samples were randomly plotted into proteochip glass slides for rppa and blotted with an anti - c9 antibody . there was a significant difference in c9 expression in plasma from colorectal cancer patients and from healthy controls ( p = 1.43  10 , student 's t - test ; figure 3(c ) ) . 
  small - scale confirmation of c9 identification and differential expression was done by immunoblotting using an anti - c9 antibody ( figure 3(b ) ) . for large - scale validation , 345 plasma samples were randomly plotted into proteochip glass slides for rppa and blotted with an anti - c9 antibody . there was a significant difference in c9 expression in plasma from colorectal cancer patients and from healthy controls ( p = 1.43  10 , student 's t - test ; figure 3(c ) ) . samplesa total of 43 plasma samples ( collected from 22 colorectal cancer patients and 21 healthy controls ) were used for biomarker discovery , and 323 plasma samples ( collected from 127 colorectal cancer patients and 196 healthy controls ) were used for validation . a total of 43 plasma samples ( collected from 22 colorectal cancer patients and 21 healthy controls ) were used for biomarker discovery , and 323 plasma samples ( collected from 127 colorectal cancer patients and 196 healthy controls ) were used for validation . a total of 53009 peptide peaks were detected , and 103 peaks with an auc of > 0.800 were differentially expressed in healthy controls and colorectal cancer patients . of these , 6 proteins were annotated by database search of tandem mass spectra . the 749  m / z ( rt 47.4  min ) peak represents a fragment of adipophilin specifically present in colorectal cancer patients ( 0.814 in auc ; figure 4(a ) ) . a total of 53009 peptide peaks were detected , and 103 peaks with an auc of > 0.800 were differentially expressed in healthy controls and colorectal cancer patients . of these , 6 proteins were annotated by database search of tandem mass spectra . the 749  m / z ( rt 47.4  min ) peak represents a fragment of adipophilin specifically present in colorectal cancer patients ( 0.814 in auc ; figure 4(a ) ) . biomarker validationsmall - scale confirmation of adipophilin identification and differential expression was done by immunoblotting using an anti - adipophilin antibody ( figure 4(b ) ) . for large - scale validation , 323 plasma samples were randomly plotted into proteochip glass slides for rppa and blotted with an anti - adipophilin antibody . differential expression of adipophilin between plasma samples from colorectal cancer patients and from healthy controls was significant ( p = 5.49  10 , welch t - test ; figure 4(c ) ) . 
  small - scale confirmation of adipophilin identification and differential expression was done by immunoblotting using an anti - adipophilin antibody ( figure 4(b ) ) . for large - scale validation , 323 plasma samples were randomly plotted into proteochip glass slides for rppa and blotted with an anti - adipophilin antibody . differential expression of adipophilin between plasma samples from colorectal cancer patients and from healthy controls was significant ( p = 5.49  10 , welch t - test ; figure 4(c ) ) . samplesa total of 47 plasma samples collected from patients with pancreatic ductal adenocarcinomas and treated with gemcitabine ( 2,2-difluorodeoxycytidine ) monotherapy ( 25 with severe adverse effects ( aes ) and 22 without ) were used for biomarker discovery , and 253 plasma samples and 52 serum samples were collected from patients with pancreatic ductal adenocarcinomas treated by gemcitabine monotherapy for validation . a total of 47 plasma samples collected from patients with pancreatic ductal adenocarcinomas and treated with gemcitabine ( 2,2-difluorodeoxycytidine ) monotherapy ( 25 with severe adverse effects ( aes ) and 22 without ) were used for biomarker discovery , and 253 plasma samples and 52 serum samples were collected from patients with pancreatic ductal adenocarcinomas treated by gemcitabine monotherapy for validation . sample preparationsamples were treated with a 12 abundant plasma protein removal column to reduce plasma protein complexity . samples were treated with a 12 abundant plasma protein removal column to reduce plasma protein complexity . a total of 60,888 peaks were detected and 757 peaks differed significantly between patients with severe aes and patients without aes ( p < 0.001 , welch t - test ) . among these , the peak with highest value to discriminate patients with severe aes from those without aes was annotated as haptoglobin . the haptoglobin fragment peak of 491  m / z ( rt 44.5  min ) is shown in figure 5(a ) . a total of 60,888 peaks were detected and 757 peaks differed significantly between patients with severe aes and patients without aes ( p < 0.001 , welch t - test ) . among these , the peak with highest value to discriminate patients with severe aes from those without aes was annotated as haptoglobin . the haptoglobin fragment peak of 491  m / z ( rt 44.5  min ) is shown in figure 5(a ) . biomarker validationsmall - scale confirmation of haptoglobin identification and differential expression was confirmed by immunoblotting using an anti - haptoglobin antibody ( figure 5(b ) ) . haptoglobin concentration in 305 plasma and serum samples was measured by immunonephelometry . the severity of ae severity inversely correlated with the concentration of haptoglobin ( figure 5(c ) ) . small - scale confirmation of haptoglobin identification and differential expression was confirmed by immunoblotting using an anti - haptoglobin antibody ( figure 5(b ) ) . haptoglobin concentration in 305 plasma and serum samples was measured by immunonephelometry . the severity of ae severity inversely correlated with the concentration of haptoglobin ( figure 5(c ) ) . samplesa total of 60 plasma samples collected from patients with pancreatic ductal adenocarcinomas and treated by gemcitabine monotherapy ( 29 with short - term survival and 31 with long - term survival ) were used for biomarker discovery , and 304 samples collected from patients with pancreatic ductal adenocarcinomas and treated by gemcitabine monotherapy were used for validation . a total of 60 plasma samples collected from patients with pancreatic ductal adenocarcinomas and treated by gemcitabine monotherapy ( 29 with short - term survival and 31 with long - term survival ) were used for biomarker discovery , and 304 samples collected from patients with pancreatic ductal adenocarcinomas and treated by gemcitabine monotherapy were used for validation . sample preparationsamples were treated with 12-abundant - plasma - protein removal column to reduce plasma protein complexity . samples were treated with 12-abundant - plasma - protein removal column to reduce plasma protein complexity . a total of 45227 peaks were detected , and 637 peaks differed significantly between patients with long - term survival and those with short - term survival ( p < 0.001 , welch t - test ) . the peptide peak that best discriminated patients with short - term survival from those with long - term survival ( p = 2.57  10 ) at 491  m / z ( rt 44.5  min ) was annotated as a fragment of a1-antitrypsin ( figure 6(a ) ) . a total of 45227 peaks were detected , and 637 peaks differed significantly between patients with long - term survival and those with short - term survival ( p < 0.001 , welch t - test ) . the peptide peak that best discriminated patients with short - term survival from those with long - term survival ( p = 2.57  10 ) at 491  m / z ( rt 44.5  min ) was annotated as a fragment of a1-antitrypsin ( figure 6(a ) ) . biomarker validationsmall - scale confirmation of 1-antitrypsin identification and differential expression was done by immunoblotting using an anti-1-antitrypsinantibody ( figure 6(b ) ) . for large - scale validation , 304 samples were randomly plotted into proteochip glass slides for rppa and blotted with antibody to 1-antitrypsin . improved survival of patients with pancreatic ductal adenocarcinoma treated by gemcitabine monotherapy correlated with low blood concentrations of 1-antitrypsin ( figure 6(c ) ) . small - scale confirmation of 1-antitrypsin identification and differential expression was done by immunoblotting using an anti-1-antitrypsinantibody ( figure 6(b ) ) . for large - scale validation , 304 samples were randomly plotted into proteochip glass slides for rppa and blotted with antibody to 1-antitrypsin . improved survival of patients with pancreatic ductal adenocarcinoma treated by gemcitabine monotherapy correlated with low blood concentrations of 1-antitrypsin ( figure 6(c ) ) . we have established a comprehensive method for identifying blood biomarkers , which covers all aspects of analysis from sample recruitment to biomarker discovery and validation . the next stage in the development of these novel biomarkers is to test them in a clinical context . the proteomics approach for blood biomarker discovery identifies a new function for common proteins such as these biomarkers . with technological advances in sample preparations , resolution and sensitivity of mass spectrometer , and methods for the identification of proteins from mass spectra , we can expect to discover biomarkers existing in much smaller amount or those with new structures in the future . we also expect that large - scale validation of biomarkers discovered using mass spectrometer will be conducted by mrm / srm . 2dical is applicable not only for proteomics but also for metabolomics or glycomics and has a great potential for identifying disease - associated post - translational protein modifications . 2dical will evolve along with technological advances and contribute the discovery of new biomarkers in future .
biomarkers tested by blood sample are of great use to clinicians as they provide useful information to aid an early and accurate diagnosis . comprehensive 
 omics 
 studies are expected to facilitate the identification of such new biomarkers , and much research is being performed in this area . 
 our proteomics analysis system of 2-dimensional image - converted analysis of liquid chromatography and mass spectrometry ( 2dical ) has successfully identified several new blood biomarkers from the clinical blood samples of pancreatic and colorectal cancer patients .