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Daniel W Chan

Publications and source records attributed to Daniel W Chan.

At least 19 recordsLinked to original sources

Proteomics: a new diagnostic frontier.

BACKGROUND: Analysis of proteins has been an integral part of the field of clinical chemistry for decades. Recent advances in technology and complete identification of the human genome sequence have opened up new opportunities for analysis of proteins for clinical diagnostic purposes. METHODS: Content of a recent conference of proteomics is summarized. RESULTS: New analytical methods allow the simultaneous analysis of a large number of proteins in biological fluids such as serum and plasma, offering partial views of the complete set of proteins or proteome. Plasma presents many analytical challenges, such as the complexity of components, predominance of a few major components, and the large concentration range of components, but the number of proteins that can be detected in plasma has expanded dramatically from hundreds to thousands. At the same time, there is increased capability to detect structural variations of proteins. Recent studies also identified the presence of complex sets of small protein fragments in plasma. This set of protein fragments, the fragmentome or peptidome, is potentially a rich source of information about physiologic and disease processes. CONCLUSIONS: Advances in proteomics offer great promise for the discovery of markers that might serve as the basis for new clinical laboratory tests. There are many challenges, however, in the translation of newly discovered markers into clinical laboratory tests.

Biomarkers↗

Quantification of fragments of human serum inter-alpha-trypsin inhibitor heavy chain 4 by a surface-enhanced laser desorption/ionization-based immunoassay.

BACKGROUND: Several proteolytically derived fragments from the proline-rich region (PRR) of human inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4) have been identified by surface-enhanced or matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS or MALDI-TOF-MS) as potential disease markers. METHODS: Previously, we developed a SELDI-based immunoassay that can simultaneously distinguish and quantify multiple isoforms/variants of a protein/peptide of interest. In this study, we used this high-throughput approach to quantify and characterize the extensive fragmentation within the PRR of human serum ITIH4 and determined its association with different disease conditions. The ITIH4-related fragments were first immunocaptured by use of beads coupled with peptide-specific antibodies. The eluates were then studied by SELDI-TOF-MS. In addition, freshly collected and immediately processed serum and plasma samples were used to analyze the ex vivo stability of these ITIH4 fragments. RESULTS: Human serum ITIH4 was shown to be extensively proteolytically processed within the PRR, and its fragmentation patterns were closely associated with different disease conditions. Fragmentation patterns were generally consistent with cleavages by endoprotease followed by exoprotease actions. Observed fragments changed little under different assay conditions or blood collection and processing procedures. CONCLUSIONS: The fragmentation patterns within the PRR of human serum ITIH4 are associated with different disease conditions and may hold important diagnostic information. These fragmentation patterns could be useful as potential biomarkers for detection and classification of cancer.

Adult↗

Serum markers in patients with resectable pancreatic adenocarcinoma: macrophage inhibitory cytokine 1 versus CA19-9.

PURPOSE: More accurate serum markers of pancreatic cancer could improve the early detection and prognosis of this deadly disease. We compared the diagnostic utility of a panel of candidate serum markers of pancreatic cancer. EXPERIMENTAL DESIGN: We collected preoperative serum from 50 patients with resectable pancreatic adenocarcinoma, as well as sera from 50 patients with chronic pancreatitis and 50 age/sex-matched healthy controls from our institution. Sera were analyzed for the following candidate markers of pancreatic cancer: CA19-9, macrophage inhibitory cytokine 1 (MIC-1), osteopontin, tissue inhibitor of metalloproteinase 1, and hepatocarcinoma-intestine-pancreas protein levels. RESULTS: By logistic regression analysis, MIC-1 and CA19-9 were significant independent predictors of diagnosis. Receiver operating characteristic curve analysis showed that MIC-1 was significantly better than CA19-9 in differentiating patients with pancreatic cancer from healthy controls (area under the curve is 0.99 and 0.78, respectively; P = 0.003), but not in distinguishing pancreatic cancer from chronic pancreatitis (area under the curve of 0.81 and 0.74, respectively; P = 0.63). Hepatocarcinoma-intestine-pancreas/pancreatitis-associated protein, osteopontin, and tissue inhibitor of metalloproteinase 1 serum levels did not provide additional diagnostic power. CONCLUSION: In the differentiation of patients with resectable pancreatic cancer from controls, serum MIC-1 outperforms other markers including CA19-9.

Adenocarcinoma↗

Identification of biomarkers for breast cancer in nipple aspiration and ductal lavage fluid.

PURPOSE: To establish a comprehensive proteomic approach for biomarker discovery and validation in breast fluid. EXPERIMENTAL DESIGN: A total of 95 specimens from three institutions were used including 10 nipple aspiration fluid (5 stage I/II cancerous breasts and 5 age-matched healthy controls), 42 ductal lavage fluid from 14 patients with unilateral stage I/II cancer (25 from 9 cancerous breasts and 17 from 7 contralateral breasts), and 42 ductal lavage fluid from 14 high-risk women (multiple ducts repeated lavage). Differentially expressed protein/peptides were discovered by proteomic analysis of training sample, using ProteinChip arrays and surface-enhanced laser desorption ionization (SELDI) time-of-flight mass spectrometry, and validated on independently collected testing samples. After protein identification, ELISA was done to confirm the SELDI findings. RESULTS: We were able to obtain reproducible protein profiles using minimal amount of protein (1 mug) by applying an optimized chip protocol and SELDI. We were able to select cancer-associated biomarkers despite large individual variability by applying both unsupervised and supervised cluster analysis. Furthermore, we were able to train and test candidate biomarkers on independently collected samples and identified one component of a multimarker panel as human neutrophil peptides 1 to 3. CONCLUSIONS: Breast fluid is a rich source of breast cancer biomarkers. In combination with high-throughput novel proteomic profiling technology and multicenter study design, markers that are highly specific to breast cancer can be discovered and validated. Our observations also suggest that persistent elevation of human neutrophil peptide in high-risk women may imply early onset of cancer not yet detectable by current detection method. Proof of this hypothesis requires follow-up on a larger study population.

Adenocarcinoma↗

Independent validation of candidate breast cancer serum biomarkers identified by mass spectrometry.

BACKGROUND: We previously selected a panel of 3 breast cancer biomarkers (BC1, BC2, and BC3) from serum samples collected at a single hospital based on their collective contribution to the optimal separation of breast cancer patients and noncancer controls by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). The identities and general applicability of these markers, however, were unknown. In this study, we performed protein expression profiling on samples obtained from a second hospital, included a greater number of ductal carcinoma in situ (DCIS) cases, and performed purification and identification of the 2 confirmed markers. METHODS: Using a case-control study design, we performed protein expression profiling on serum samples from the National Cancer Institute (Milan, Italy). The validation sample cohort consisted of 61 women with locally invasive breast cancer, 32 with DCIS, 37 with various benign breast diseases (including 13 atypical), and 46 age-matched apparently healthy women (age range, 44-68 years). Validated biomarkers were purified and identified with serial chromatography, 1-dimensional gel electrophoresis, in-gel ASP-N digestion, peptide mass fingerprinting, and tandem mass peptide sequencing. RESULTS: The BC3 and BC2 expression patterns in this sample set were consistent with the first study sample set. BC3 and BC2 were identified to be complement component C3a(desArg) and a C-terminal-truncated form of C3a(desArg), respectively. CONCLUSIONS: Evaluation of biomarkers in independent sample sets can help determine the broader utility of candidate markers, and protein identification permits understanding of their molecular basis. C3a(desArg) appears to lack specificity among patients with benign diseases, limiting its utility as a stand-alone tumor marker, but it may still be useful in a multimarker panel for early detection of breast cancer.

Adolescent↗

The clinical application of proteomics.

BACKGROUND: Proteomics is defined as a scientific approach used to elucidate all protein species within a cell or tissue, and many researchers are taking advantage of proteomic technology to elucidate protein changes between healthy and diseased states. METHODS: The application of proteomic techniques and strategies to the field of medicine is slowly transforming the way biomarker discovery is conducted. However, the complexity of serum is the source of both its promise to clinical applications and its challenge to proteomic analysis. Like any new technology when it is first introduced, proteomics has been touted with much hope and promise. RESULTS AND CONCLUSIONS: We provide a review of the clinical application of proteomics with the emphasis on current practical issues and challenges facing proteomic research.

Humans↗

Classification of cancer types by measuring variants of host response proteins using SELDI serum assays.

Protein expression profiling has been increasingly used to discover and characterize biomarkers that can be used for diagnostic, prognostic or therapeutic purposes. Most proteomic studies published to date have identified relatively abundant host response proteins as candidate biomarkers, which are often dismissed because of an apparent lack of specificity. We demonstrate that 2 host response proteins previously identified as candidate markers for early stage ovarian cancer, transthyretin and inter-alpha trypsin inhibitor heavy chain 4 (ITIH4), are posttranslationally modified. These modifications include proteolytic truncation, cysteinylation and glutathionylation. Assays using Surface Enhanced Laser Desorption/Ionization Time of Flight Mass Spectrometry (SELDI-TOF-MS) may provide a means to confer specificity to these proteins because of their ability to detect and quantitate multiple posttranslationally modified forms of these proteins in a single assay. Quantitative measurements of these modifications using chromatographic and antibody-based ProteinChip array assays reveal that these posttranslational modifications occur to different extents in different cancers and that multivariate analysis permits the derivation of algorithms to improve the classification of these cancers. We have termed this process host response protein amplification cascade (HRPAC), since the process of synthesis, posttranslational modification and metabolism of host response proteins amplifies the signal of potentially low-abundant biologically active disease markers such as enzymes.

Algorithms↗

HUPO Plasma Proteome Project specimen collection and handling: towards the standardization of parameters for plasma proteome samples.

There is a substantial list of pre-analytical variables that can alter the analysis of blood-derived samples. We have undertaken studies on some of these issues including choice of sample type, stability during storage, use of protease inhibitors, and clinical standardization. As there is a wide range of sample variables and a broad spectrum of analytical techniques in the HUPO PPP effort, it is not possible to define a single list of pre-analytical standards for samples or their processing. We present here a compendium of observations, drawing on actual results and sound clinical theories and practices. Based on our data, we find that (1) platelet-depleted plasma is preferable to serum for certain peptidomic studies; (2) samples should be aliquoted and stored preferably in liquid nitrogen; (3) the addition of protease inhibitors is recommended, but should be incorporated early and used judiciously, as some form non specific protein adducts and others interfere with peptide studies. Further, (4) the diligent tracking of pre-analytical variables and (5) the use of reference materials for quality control and quality assurance, are recommended. These findings help provide guidance on sample handling issues, with the overall suggestion being to be conscious of all possible pre-analytical variables as a prerequisite of any proteomic study.

Blood Platelets↗

Analysis of Human Proteome Organization Plasma Proteome Project (HUPO PPP) reference specimens using surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry: multi-institution correlation of spectra and identification of biomarkers.

We report on a multicenter analysis of HUPO reference specimens using SELDI-TOF MS. Eight sites submitted data obtained from serum and plasma reference specimen analysis. Spectra from five sites passed preliminary quality assurance tests and were subjected to further analysis. Intralaboratory CVs varied from 15 to 43%. A correlation coefficient matrix generated using data from these five sites demonstrated high level of correlation, with values >0.7 on 37 of 42 spectra. More than 50 peaks were differentially present among the various sample types, as observed on three chip surfaces. Additionally, peaks at approximately 9200 and approximately 15,950 m/z were present only in select reference specimens. Chromatographic fractionation using anion-exchange, membrane cutoff, and reverse phase chromatography, was employed for protein purification of the approximately 9200 m/z peak. It was identified as the haptoglobin alpha subunit after peptide mass fingerprinting and high-resolution MS/MS analysis. The differential expression of this protein was confirmed by Western blot analysis. These pilot studies demonstrate the potential of the SELDI platform for reproducible and consistent analysis of serum/plasma across multiple sites and also for targeted biomarker discovery and protein identification. This approach could be exploited for population-based studies in all phases of the HUPO PPP.

Biomarkers↗

Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

Algorithms↗

Intermittent cardiac troponin-I screening is an effective means of surveillance for a perioperative myocardial infarction.

OBJECTIVE: Several studies suggest that cardiac troponin-I (cTn-I) is a more sensitive indicator of cardiac injury compared with other biochemical markers of injury, but the strategy with the highest diagnostic yield (true positive and true negative) for perioperative surveillance is unknown. The authors undertook a prospective evaluation of the perioperative incidence of myocardial infarction (MI) and evaluated surveillance strategies for the diagnosis of MI. DESIGN: Prospective, cohort study. SETTING: Two university hospitals. PARTICIPANTS: Four hundred sixty-seven high-risk patients requiring noncardiac surgery. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The diagnosis of myocardial injury was determined by cardiac protein markers combined with either postoperative changes on 12-lead electrocardiography or 1 of 3 clinical symptoms consistent with MI (chest pain, dyspnea, requirement for hemodynamic support). A receiver operating characteristic curve evaluating troponin in the diagnosis of MI revealed a value of 2.6 ng/mL as having the highest sensitivity and specificity. The sensitivity and specificity of cTn-I value > or =2.6 ng/mL, troponin > or =1.5 ng/mL, total creatine kinase (CK) > or =170 IU/L with MB > or =5%, and CK-MB > or =8 ng/mL were compared. Surveillance strategies were determined on a subset of patients (n = 257). The incidence of MI was 9.0% by cTn-I > or =2.6 ng/mL criteria, 19% by cTn-I > or =1.5 ng/mL, 13% by CK-MB mass, and 2.8% by CK-MB%. The specificity of cTn-I > or =2.6 ng/mL as an indicator of MI was 98%, and its positive predictive value (PPV) was 85%. Cardiac troponin-I > or =2.6 ng/mL had equal specificity but greater PPV than the cTn-I > or =1.5 ng/mL (specificity 98% and PPV 79%). If surveillance of cTn-I > or =2.6 ng/mL was used to detect MI, then the strategy with the highest diagnostic yield was surveillance on postoperative days 1, 2, and 3. CONCLUSIONS: Perioperative cardiac injury continues to occur frequently after noncardiac surgery, as detected by cTn-I. Serial monitoring of cardiac troponin-I on postoperative days 1, 2, and 3 provides the strategy with the highest diagnostic yield for surveillance of MI.

Aged↗

Comparison of predictive accuracy for pathologically organ confined clinical stage T1c prostate cancer using human glandular kallikrein 2 and prostate specific antigen combined with clinical stage and Gleason grade.

PURPOSE: Previously human glandular kallikrein 2 (hK2) has been implicated to predict pathologically organ confined prostate cancer (PCa) in patients with stage T2 disease. Now we evaluated the usefulness of hK2, as measured by 2 entirely different immunoassay designs, to enhance the discrimination of pathologically organ from nonorgan confined clinical stage T1c PCa. MATERIALS AND METHODS: A consecutive series of pretreatment serum from 148 men with clinical stage T1c PCa was used in 2 equally sensitive and specific methods to measure total hK2 with independent reagents and entirely different assay designs. Total prostate specific antigen (tPSA) and free PSA (fPSA) were measured and percent fPSA was calculated. We determined the algorithm, hK2*tPSA/fPSA, from data generated by each hK2 assay, calculated means, medians and ranges for each analyte and algorithm, and calculated the significance of differences on univariate analysis. Using pretreatment PSA, clinical stage and biopsy Gleason grade we then developed a multivariate logistic regression base model to predict organ confined cancer and we compared predictions of the base model supplemented by the different hK2 measurements. RESULTS: hK2 and hK2 based algorithms obtained by each hK2 assay were significantly different for pT2a/b vs pT3a or greater PCa (p = 0.034 to 0.0001) compared to tPSA (p = 0.06), fPSA (p = 0.90) or percent fPSA (p = 0.059). However, AUC (0.67 to 0.70) calculated by ROC analysis of the 4 models containing hK2 derived information was not significantly larger than that of the base model (AUC = 0.64, p = 0.52). CONCLUSIONS: The current data confirm that hK2 alone or hK2*tPSA/fPSA measured by 2 immunoassays is significantly lower in men with pT2a/b vs pT3a or greater PCa compared to tPSA, fPSA or percent fPSA on univariate analysis of a validation set of clinical stage T1c prostate cancer treated at an American center of excellence for prostate cancer surgery. However, the incorporation of preoperative hK2 into multiparameter predictive models for pT2 cancers did not increase predictive accuracy in this cohort of men.

Adult↗

Evaluation of serum protein profiling by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry for the detection of prostate cancer: I. Assessment of platform reproducibility.

BACKGROUND: Protein expression profiling for differences indicative of early cancer has promise for improving diagnostics. This report describes the first stage of a National Cancer Institute/Early Detection Research Network-sponsored multiinstitutional evaluation and validation of this approach for detection of prostate cancer. METHODS: Two sequential experimental phases were conducted to establish interlaboratory calibration and standardization of the surface-enhanced laser desorption (SELDI) instrumental and assay platform output. We first established whether the output from multiple calibrated Protein Biosystem II SELDI-ionization time-of-flight mass spectrometry (TOF-MS) instruments demonstrated acceptable interlaboratory reproducibility. This was determined by measuring mass accuracy, resolution, signal-to-noise ratio, and normalized intensity of three m/z "peaks" present in a standard pooled serum sample. We next evaluated the ability of the calibrated and standardized instrumentation to accurately differentiate between selected cases of prostate cancer and control by use of an algorithm developed from data derived from a single site 2 years earlier. RESULTS: When the described standard operating procedures were established at all laboratory sites, the across-laboratory measurements revealed a CV for mass accuracy of 0.1%, signal-to-noise ratio of approximately 40%, and normalized intensity of 15-36% for the three pooled serum peaks. This was comparable to the intralaboratory measurements of the same peaks. The instrument systems were then challenged with sera from a selected group of 14 cases and 14 controls. The classification agreement between each site and the established decision algorithm were examined by use of both raw peak intensity boosting and ranked peak intensity boosting. All six sites achieved perfect blinded classification for all samples when boosted alignment of raw intensities was used. Four of six sites achieved perfect blinded classification with ranked intensities, with one site passing the criteria of 26 of 28 correct and one site failing with 19 of 28 correct. CONCLUSIONS: These results demonstrate that "between-laboratory" reproducibility of SELDI-TOF-MS serum profiling approaches that of "within-laboratory" reproducibility as determined by measuring discrete m/z peaks over time and across laboratories.

Calibration↗

Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer.

Early detection remains the most promising approach to improve long-term survival of patients with ovarian cancer. In a five-center case-control study, serum proteomic expressions were analyzed on 153 patients with invasive epithelial ovarian cancer, 42 with other ovarian cancers, 166 with benign pelvic masses, and 142 healthy women. Data from patients with early stage ovarian cancer and healthy women at two centers were analyzed independently and the results cross-validated to discover potential biomarkers. The results were validated using the samples from two of the remaining centers. After protein identification, biomarkers for which an immunoassay was available were tested on samples from the fifth center, which included 41 healthy women, 41 patients with ovarian cancer, and 20 each with breast, colon, and prostate cancers. Three biomarkers were identified as follows: (a) apolipoprotein A1 (down-regulated in cancer); (b) a truncated form of transthyretin (down-regulated); and (c) a cleavage fragment of inter-alpha-trypsin inhibitor heavy chain H4 (up-regulated). In independent validation to detect early stage invasive epithelial ovarian cancer from healthy controls, the sensitivity of a multivariate model combining the three biomarkers and CA125 [74% (95% CI, 52-90%)] was higher than that of CA125 alone [65% (95% CI, 43-84%)] at a matched specificity of 97% (95% CI, 89-100%). When compared at a fixed sensitivity of 83% (95% CI, 61-95%), the specificity of the model [94% (95% CI, 85-98%)] was significantly better than that of CA125 alone [52% (95% CI, 39-65%)]. These biomarkers demonstrated the potential to improve the detection of early stage ovarian cancer.

Amino Acid Sequence↗

Serum macrophage inhibitory cytokine 1 as a marker of pancreatic and other periampullary cancers.

PURPOSE: Patients with pancreatic ductal adenocarcinoma usually present with advanced-stage disease and a dismal prognosis. One effective strategy likely to improve the morbidity and mortality from pancreatic cancer would be the identification of accurate, noninvasive diagnostic markers that would enable earlier diagnosis of symptomatic patients and earlier detection of cancer in asymptomatic individuals at high risk for developing pancreatic cancer. In this study, we evaluated serum macrophage inhibitory cytokine-1 (MIC-1) as a marker of pancreatic cancer. EXPERIMENTAL DESIGN: MIC-1 expression in primary pancreatic cancers, intraductal papillary mucinous neoplasms, and pancreatic cancer cell lines was determined using the National Center for Biotechnology Information serial analysis of gene expression database, oligonucleotide microarrays analysis, in situ hybridization, and immunohistochemistry. Serum MIC-1 levels were determined by ELISA in 80 patients with pancreatic adenocarcinomas, in 30 patients with ampullary and cholangiocellular carcinomas, in 42 patients with benign pancreatic tumors, in 76 patients with chronic pancreatitis, and in 97 healthy control subjects. The diagnostic performance of serum MIC-1 as a marker of pancreatic cancer was compared with that of serum CA19-9. RESULTS: Oligonucleotide microarray and serial analysis of gene expression data demonstrated that MIC-1 RNA levels were higher in primary pancreatic cancers, intraductal papillary mucinous neoplasms, and pancreatic cancer cell lines than in nonneoplastic pancreatic ductal epithelium. MIC-1 expression was localized to the malignant epithelium in pancreatic adenocarcinomas by in situ hybridization. MIC-1 protein was expressed in 14 of 16 primary pancreatic adenocarcinomas (88%) by immunohistochemistry and was also expressed in some pancreata affected by pancreatitis but not in normal pancreas. Serum MIC-1 levels were significantly higher in patients with pancreatic ductal adenocarcinoma (mean +/- SD, 2428 +/- 2324 pg/ml) and in patients with ampullary and cholangiocellular carcinomas (2123 +/- 2387 pg/ml) than in those with benign pancreatic neoplasms (940 +/- 469 pg/ml), chronic pancreatitis (1364 +/- 1236 pg/ml), or in healthy controls (546 +/- 262 pg/ml). An elevated serum MIC-1 (defined as 2 SD above the mean for healthy controls) performed as well as CA19-9 (area under the receiver operating characteristic curve, 0.81 and 0.77, respectively), and the combination of MIC-1 and CA19-9 significantly improved diagnostic accuracy (P < 0.05; area under the receiver operating characteristic curve, 0.87; sensitivity, 70%; specificity, 85%). CONCLUSION: Serum MIC-1 measurement can aid in the diagnosis of pancreatic adenocarcinoma.

Adenocarcinoma↗