Discovery of serum biomarkers for pancreatic adenocarcinoma using proteomic analysis

Clinical development of a blood biomarker using apolipoprotein-A2 isoforms for early detection of pancreatic cancer

BACKGROUND

We have previously reported apolipoprotein A2-isoforms (apoA2-is) as candidate plasma biomarkers for early-stage pancreatic cancer. The aim of this study was the clinical development of apoA2-is.

METHODS

We established a new enzyme-linked immunosorbent sandwich assay for apoA2-is under the Japanese medical device Quality Management System requirements and performed in vitro diagnostic tests with prespecified end points using 2732 plasma samples. The clinical equivalence and significance of apoA2-is were compared with CA19-9.

RESULTS

The point estimate of the area under the curve to distinguish between pancreatic cancer (n = 106) and healthy controls (n = 106) was higher for apoA2-ATQ/AT [0.879, 95% confidence interval (CI): 0.832-0.925] than for CA19-9 (0.849, 95% CI 0.793-0.905) and achieved the primary end point. The cutoff apoA2-ATQ/AT of 59.5 μg/mL was defined based on a specificity of 95% in 2000 healthy samples, and the reliability of specificities was confirmed in two independent healthy cohorts as 95.3% (n = 106, 95% CI 89.4-98.0%) and 95.8% (n = 400, 95% CI 93.3-97.3%). The sensitivities of apoA2-ATQ/AT for detecting both stage I (47.4%) and I/II (50%) pancreatic cancers were higher than those of CA19-9 (36.8% and 46.7%, respectively). The combination of apoA2-ATQ/AT (cutoff, 59.5 μg/mL) and CA19-9 (37 U/mL) increased the sensitivity for pancreatic cancer to 87.7% compared with 69.8% for CA19-9 alone. The clinical performance of apoA2-is was blindly confirmed by the National Cancer Institute Early Detection Research Network.

CONCLUSIONS

The clinical performance of ApoA2-ATQ/AT as a blood biomarker is equivalent to or better than that of CA19-9.

A Comprehensive Review of the Potential Role of Liquid Biopsy as a Diagnostic, Prognostic, and Predictive Biomarker in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma is one of the most lethal malignant diseases, with a mortality rate being close to incidence. Due to its heterogeneity and plasticity, as well as the lack of distinct symptoms in the early phases, it is very often diagnosed at an advanced stage, resulting in poor prognosis. Traditional tissue biopsies remain the gold standard for making a diagnosis, but have an obvious disadvantage in their inapplicability for frequent sampling. Blood-based biopsies represent a non-invasive method which potentially offers easy and repeated sampling, leading to the early detection and real-time monitoring of the disease and hopefully an accurate prognosis. Given the urgent need for a reliable biomarker that can estimate a patient's condition and response to an assigned treatment, blood-based biopsies are emerging as a potential new tool for improving patients' survival and surveillance. In this article, we discuss the current advances and challenges in using liquid biopsies for pancreatic cancer, focusing on circulating tumour DNA (ctDNA), extracellular vesicles (EVs), and circulating tumour cells (CTCs), and compare the performance and reliability of different biomarkers and combinations of biomarkers.

Proteomics-Driven Biomarkers in Pancreatic Cancer

Pancreatic cancer is a devastating disease that has a grim prognosis, highlighting the need for improved screening, diagnosis, and treatment strategies. Currently, the sole biomarker for pancreatic ductal adenocarcinoma (PDAC) authorized by the U.S. Food and Drug Administration is CA 19-9, which proves to be the most beneficial in tracking treatment response rather than in early detection. In recent years, proteomics has emerged as a powerful tool for advancing our understanding of pancreatic cancer biology and identifying potential biomarkers and therapeutic targets. This review aims to offer a comprehensive survey of proteomics' current status in pancreatic cancer research, specifically accentuating its applications and its potential to drastically enhance screening, diagnosis, and treatment response. With respect to screening and diagnostic precision, proteomics carries the capacity to augment the sensitivity and specificity of extant screening and diagnostic methodologies. Nonetheless, more research is imperative for validating potential biomarkers and establishing standard procedures for sample preparation and data analysis. Furthermore, proteomics presents opportunities for unveiling new biomarkers and therapeutic targets, as well as fostering the development of personalized treatment strategies based on protein expression patterns associated with treatment response. In conclusion, proteomics holds great promise for advancing our understanding of pancreatic cancer biology and improving patient outcomes. It is essential to maintain momentum in investment and innovation in this arena to unearth more groundbreaking discoveries and transmute them into practical diagnostic and therapeutic strategies in the clinical context.

Feasibility of ApoC1 serum levels as tumor biomarker in glioblastoma patients: a pilot study

Apolipoprotein C1 (ApoC1) has been detected immunohistochemically in glioblastoma tissue, probably expressed by activated monocytes and microglia. The present study was conceived to determine whether the amount of intratumoral ApoC1 expression leads to measurable changes of serum levels after glioblastoma resection or during recurrence. 176 blood samples from 70 glioblastoma patients were collected perioperatively and during subsequent therapy. ApoC1 serum levels were determined using an enzyme linked immunosorbent assay (ELISA). High absorption values due to lipemic or hemolytic serum were removed from the final dataset using a stem and leaf plot. Samples were grouped according to the treatment stage to compare mean ApoC1 serum levels. The number of patients with falling or increasing perioperative values was assessed. 167 ApoC1 serum values from 68 glioblastoma patients were amenable to statistical evaluation. Mean ApoC1 serum level was 91.9 µg/ml (n = 167, sd = 36.0). In samples from patients undergoing first glioblastoma resection, the mean preoperative value was significantly higher (94.8 µg/ml, n = 37, sd = 29.5) than after surgery (77.4 µg/ml, n = 41, sd = 23.2, p = 0.009). Individually, falling ApoC1 levels were detected in 25 and rising levels in 9 patients (p = 0.0061). Single absolute serum levels of ApoC1 do not allow an estimation of glioblastoma activity or tumor response. Although pathophysiologically of interest, ApoC1 serum levels did not qualify as a potential biomarker in glioblastoma management. Our results do not seem to encourage larger, multicenter studies.

Apolipoprotein A-II, a Player in Multiple Processes and Diseases

Apolipoprotein A-II (apoA-II) is the second most abundant apolipoprotein in high-density lipoprotein (HDL) particles, playing an important role in lipid metabolism. Human and murine apoA-II proteins have dissimilar properties, partially because human apoA-II is dimeric whereas the murine homolog is a monomer, suggesting that the role of apoA-II may be quite different in humans and mice. As a component of HDL, apoA-II influences lipid metabolism, being directly or indirectly involved in vascular diseases. Clinical and epidemiological studies resulted in conflicting findings regarding the proatherogenic or atheroprotective role of apoA-II. Human apoA-II deficiency has little influence on lipoprotein levels with no obvious clinical consequences, while murine apoA-II deficiency causes HDL deficit in mice. In humans, an increased plasma apoA-II concentration causes hypertriglyceridemia and lowers HDL levels. This dyslipidemia leads to glucose intolerance, and the ensuing high blood glucose enhances apoA-II transcription, generating a vicious circle that may cause type 2 diabetes (T2D). ApoA-II is also used as a biomarker in various diseases, such as pancreatic cancer. Herein, we provide a review of the most recent findings regarding the roles of apoA-II and its functions in various physiological processes and disease states, such as cardiovascular disease, cancer, amyloidosis, hepatitis, insulin resistance, obesity, and T2D.

Blood biomarkers for differential diagnosis and early detection of pancreatic cancer

Pancreatic cancer is currently the most lethal tumor entity and case numbers are rising. It will soon be the second most frequent cause of cancer-related death in the Western world. Mortality is close to incidence and patient survival after diagnosis stands at about five months. Blood-based diagnostics could be one crucial factor for improving this dismal situation and is at a stage that could make this possible. Here, we are reviewing the current state of affairs with its problems and promises, looking at various molecule types. Reported results are evaluated in the overall context. Also, we are proposing steps toward clinical utility that should advance the development toward clinical application by improving biomarker quality but also by defining distinct clinical objectives and the respective diagnostic accuracies required to achieve them. Many of the discussed points and conclusions are highly relevant to other solid tumors, too.

Apolipoprotein C1 stimulates the malignant process of renal cell carcinoma via the Wnt3a signaling

Background

Renal cell carcinoma (RCC) is a clinically common tumor in the urinary system, showing an upward trend of both incidence and mortality. Apolipoprotein C1 (APOC1) has been identified as a vital regulator in tumor progression. This study aims to uncover the biological function of APOC1 in RCC process and the underlying mechanism.

Methods

Differential levels of APOC1 in RCC samples and normal tissues in a downloaded TCGA profile and clinical samples collected in our center were detected by quantitative reverse transcription PCR (qRT-PCR). The prognostic value of APOC1 in RCC was assessed by depicting Kaplan–Meier survival curves. After intervening APOC1 level by transfection of sh-APOC1 or oe-APOC1, changes in phenotypes of RCC cells were examined through CCK-8, colony formation, Transwell assay and flow cytometry. Subsequently, protein levels of EMT-related genes influenced by APOC1 were determined by Western blot. The involvement of the Wnt3a signaling in APOC1-regulated malignant process of RCC was then examined through a series of rescue experiments. Finally, a RCC xenograft model was generated in nude mice, aiming to further clarify the in vivo function of APOC1 in RCC process.

Results

APOC1 was upregulated in RCC samples. Notably, its level was correlated to overall survival of RCC patients, displaying a certain prognostic value. APOC1 was able to stimulate proliferative, migratory and invasive abilities in RCC cells. The Wnt3a signaling was identified to be involved in APOC1-mediated RCC process. Notably, Wnt3a was able to reverse the regulatory effects of APOC1 on RCC cell phenotypes. In vivo knockdown of APOC1 in xenografted nude mice slowed down the growth of RCC.

Conclusions

APOC1 stimulates the malignant process of RCC via targeting the Wnt3a signaling.

Pancreatic adenocarcinoma preferentially takes up and is suppressed by synthetic nanoparticles carrying apolipoprotein A-II and a lipid gemcitabine prodrug in mice

We hypothesised that synthetic HDL nanoparticles carrying a gemcitabine prodrug and apolipoprotein A-II (sHDLGemA2) would target scavenger receptor-B1 (SR-B1) to preferentially and safely deliver gemcitabine into pancreatic ductal adenocarcinoma (PDAC). We designed, manufactured and characterised sHDLGemA2 nanoparticles sized ~130 nm, incorporating 20 mol% of a gemcitabine prodrug within the lipid bilayer, which strengthens on adding ApoA-II. We measured their ability to inhibit growth in cell lines and cell-derived and patient-derived murine PDAC xenografts. Fluorescent-labelled sHDLGemA2 delivered gemcitabine inside xenografts. Xenograft levels of active gemcitabine after sHDLGemA2 were similar to levels after high-dose free gemcitabine. Growth inhibition in mice receiving 4.5 mg gemcitabine/kg/d, carried in sHDLGemA2, was equivalent to inhibition after high-dose (75 mg/kg/d) free gemcitabine, and greater than inhibition after low-dose (4.5 mg/kg/d) free gemcitabine. sHDLGemA2 slowed growth in semi-resistant cells and a resistant human xenograft. sHDLGemA2 targeted xenografts more effectively than sHDLGemA1. SR-B1 was over-expressed in PDAC cells and xenografts. Targeting by ApoA-II was suppressed by anti-SR-B1. Because sHDLGemA2 provided only ~6% of the free gemcitabine dose for an equivalent response, patient side effects can be greatly reduced, and the sHDLGemA2 concept should be developed through clinical trials.

LDL, HDL and endocrine-related cancer: From pathogenic mechanisms to therapies

Cholesterol is essential for a variety of functions in endocrine-related cells, including hormone and steroid production. We have reviewed the progress to date in research on the role of the main cholesterol-containing lipoproteins; low-density lipoprotein (LDL) and high-density lipoprotein (HDL), and their impact on intracellular cholesterol homeostasis and carcinogenic pathways in endocrine-related cancers. Neither LDL-cholesterol (LDL-C) nor HDL-cholesterol (HDL-C) was consistently associated with endocrine-related cancer risk. However, preclinical studies showed that LDL receptor plays a critical role in endocrine-related tumor cells, mainly by enhancing circulating LDL-C uptake and modulating tumorigenic signaling pathways. Although scavenger receptor type BI-mediated uptake of HDL could enhance cell proliferation in breast, prostate, and ovarian cancer, these effects may be counteracted by the antioxidant and anti-inflammatory properties of HDL. Moreover, 27-hydroxycholesterol a metabolite of cholesterol promotes tumorigenic processes in breast and epithelial thyroid cancer. Furthermore, statins have been reported to reduce the incidence of breast, prostate, pancreatic, and ovarian cancer in large clinical trials, in part because of their ability to lower cholesterol synthesis. Overall, cholesterol homeostasis deregulation in endocrine-related cancers offers new therapeutic opportunities, but more mechanistic studies are needed to translate the preclinical findings into clinical therapies.

Soluble stroma-related biomarkers of pancreatic cancer

The clinical management of pancreatic ductal adenocarcinoma (PDAC) is hampered by the lack of reliable biomarkers. This study investigated the value of soluble stroma‐related molecules as PDAC biomarkers. In the first exploratory phase, 12 out of 38 molecules were associated with PDAC in a cohort of 25 PDAC patients and 16 healthy subjects. A second confirmatory phase on an independent cohort of 131 PDAC patients, 30 chronic pancreatitis patients, and 131 healthy subjects confirmed the PDAC association for MMP7, CCN2, IGFBP2, TSP2, sICAM1, TIMP1, and PLG. Multivariable logistic regression model identified biomarker panels discriminating respectively PDAC versus healthy subjects (MMP7 + CA19.9, AUC = 0.99, 99% CI = 0.98–1.00) (CCN2 + CA19.9, AUC = 0.96, 99% CI = 0.92–0.99) and PDAC versus chronic pancreatitis (CCN2 + PLG+FN+Col4 + CA19.9, AUC = 0.94, 99% CI = 0.88–0.99). Five molecules were associated with PanIN development in two GEM models of PDAC (PdxCre/LSL‐Kras^G12D and PdxCre/LSL‐Kras^G12D/+/LSL‐Trp53^R172H/+), suggesting their potential for detecting early disease. These markers were also elevated in patient‐derived orthotopic PDAC xenografts and associated with response to chemotherapy. The identified stroma‐related soluble biomarkers represent potential tools for PDAC diagnosis and for monitoring treatment response of PDAC patients.

Apolipoprotein C1 promotes prostate cancer cell proliferation in vitro

Here, we aimed to investigate the carcinogenic effects of apolipoprotein C1 (APOC1) in prostate cancer (PCa). APOC1 expression was evaluated in PCa and normal prostate specimens, and lentivirus-mediated RNA interference was used to knockdown APOC1 in DU145 cells. The effects of APOC1 silencing on cell proliferation, cell cycle arrest, and apoptosis were assessed. APOC1 expression was much higher in PCa tissues than in normal tissues. Moreover, APOC1 silencing inhibited cell proliferation and colony formation, arrested cell cycle progression, and enhanced apoptosis in DU145 cells. Additionally, APOC1 silencing decreased survivin, phospho-Rb, and p21 levels and increased cleaved caspase-3 expression. These data supported the procarcinogenic effects of APOC1 in the pathogenesis of PCa and suggested that targeting APOC1 may have applications in the treatment of PCa.

Identification of Small Proteins and Peptides in the Differentiation of Patients with Intraductal Mucinous Neoplasms of the Pancreas, Chronic Pancreatitis and Pancreatic Adenocarcinoma

BACKGROUND

There are a limited number of studies investigating the type of serum proteins capable of differentiating intraductal papillary mucinous neoplasms from benign or malignant diseases of the pancreas.

AIMS

To select proteins able to differentiate intraductal papillary mucinous neoplasms from benign and malignant pancreatic disease using semiquantitative proteomics.

METHODS

Serum samples were obtained from 74 patients (19 with type II intraductal papillary mucinous neoplasms, 8 with type I/III intraductal papillary mucinous neoplasms, 24 with chronic pancreatitis, 23 with pancreatic ductal adenocarcinomas) and 21 healthy subjects. Small proteins and peptides were assayed by matrix-assisted laser desorption/ionization for the detection of differentially abundant species possibly related to tumor onset. Serum pancreatic amylase, lipase, carcinoembryonic antigen and carbohydrate antigen 19-9 (CA 19-9) were also assayed.

RESULTS

Twenty-six of 84 peaks detected were dysregulated (7 more abundant and 19 less abundant in the type II intraductal papillary mucinous neoplasms, p < 0.05). Of the differentially abundant peaks, 17 were commonly dysregulated (3 peaks more abundant and 13 less abundant in type II intraductal papillary mucinous neoplasms, and one at  m/z = 9961 at variance), indicating a protein fingerprint shared by types I/III and type II intraductal papillary mucinous neoplasms and pancreatic ductal adenocarcinomas.

CONCLUSIONS

These results suggest that our approach can be used to differentiate type II intraductal papillary mucinous neoplasms from type I/III neoplasms, and type II intraductal papillary mucinous neoplasms from pancreatic ductal adenocarcinomas.

Serum apolipoprotein A2 isoforms in autoimmune pancreatitis

Recently, apolipoprotein A2 (apoA2) isoforms have been reported as candidate serum/plasma biomarkers of pancreatic cancer. However, the distribution of apoA2 isoforms in patients with autoimmune pancreatitis (AIP) has not been investigated yet. In this study, we evaluated the distribution of serum apoA2 isoforms; i.e., homodimer apoA2-ATQ/ATQ, heterodimer apoA2-ATQ/AT, and homodimer apoA2-AT/AT, in AIP patients and healthy volunteers (HV) using enzyme-linked immunosorbent assays, and the clinical characteristics and serum levels of each apoA2 isoform in 32 AIP patients and 38 HV were investigated. The calculated apoA2-ATQ/AT levels of the AIP patients were significantly lower than those of the HV, which agreed with results obtained for patients with pancreatic cancer. Interestingly, most of the AIP patients exhibited high levels of apoA2-ATQ along with low levels of apoA2-AT, indicating that the processing of the C-terminal regions of apoA2 dimer was inhibited in the AIP patients. This specific distribution of serum apoA2 isoforms might provide important information about the disease states of AIP patients and aid the differential diagnosis of AIP versus pancreatic cancer.

Salivary glycopatterns as potential biomarkers for diagnosis of gastric cancer

Gastric cancer (GC) is still an extremely severe health issue with high mortality due to the lacking of effective biomarkers. In this study, we aimed to investigate the alterations of salivary protein glycosylation related to GC and assess the possibility of salivary glycopatterns as potential biomarkers for the diagnosis of GC. Firstly, 94 patients with GC (n = 64) and atrophic gastritis (AG) (n = 30), as well as 30 age- and sex-matched healthy volunteers (HV) were enrolled in the test group to probe the difference of salivary glycopatterns using lectin microarrays, the results were validated by saliva microarrays and lectin blotting analysis. Then, the diagnostic model of GC (Model GC) and AG (Model AG) were constructed based on 15 candidate lectins which exhibited significant alterations of salivary glycopattern by logistic stepwise regression. Finally, two diagnostic models were assessed in the validation group including HV (n = 30) and patients with GC (n = 23) and AG (n = 24) and achieved high diagnostic power (Model GC (AUC: 0.89, sensitivity: 0.96 and specificity: 0.80), Model AG (AUC: 0.83, sensitivity: 0.92 and specificity: 0.72)). This study provides pivotal information to distinguish HV, AG and GC based on precise alterations in salivary glycopatterns, which have great potential to be biomarkers for diagnosis of GC.

Potential usefulness of apolipoprotein A2 isoforms for screening and risk stratification of pancreatic cancer

Given the low incidence of pancreatic cancer in the general population, screening of pancreatic cancer in the general population using invasive modalities is not feasible. Combination of invasive screening with noninvasive biomarkers for pancreatic cancer and its precancerous lesions has the potential to reduce mortality due to pancreatic cancer. In this review, we focus on biomarkers found in the blood that can indicate early-stage pancreatic cancer, and we discuss current strategies for screening for pancreatic cancer. We recently identified a unique alteration in apolipoprotein A2 isoforms in pancreatic cancer and its precancerous lesions, and we describe its clinical usefulness as a potential biomarker for the early detection and risk stratification of pancreatic cancer.

Urinary Peptide Analysis Differentiates Pancreatic Cancer From Chronic Pancreatitis

OBJECTIVES

Differentiation of pancreatic cancer (PCA) from chronic pancreatitis (CP) is challenging. We searched for peptide markers in urine to develop a diagnostic peptide marker model.

METHODS

Capillary electrophoresis-mass spectrometry was used to search for peptides in urine of patients with PCA (n = 39) or CP (n = 41). Statistical different peptides were included in a peptide multimarker model. Peptide markers were sequence identified and validated by immunoassay and immunohistochemistry (IHC).

RESULTS

Applied to a validation cohort of 54 patients with PCA and 52 patients with CP, the peptide model correctly classified 47 patients with PCA and 44 patients with CP (area under the curve, 0.93; 87% sensitivity; 85% specificity). All 5 patients with PCA with concomitant CP were classified positive. Urine proteome analysis outperformed carbohydrate antigen 19-9 (area under the curve, 0.84) by a 15% increase in sensitivity at the same specificity. From 99 healthy subjects, only four were misclassified. Fetuin-A was the most prominent peptide marker source for PCA as verified by immunoassay and IHC. In silico protease mapping of the peptide markers' terminal sequences pointed to increased meprin-A activity in PCA, which in IHC was associated with neoangiogenesis.

CONCLUSIONS

Urinary proteome analysis differentiates PCA from CP and may serve as PCA screening tool.

Apolipoprotein A-II Plus Lipid Emulsion Enhance Cell Growth via SR-B1 and Target Pancreatic Cancer In Vitro and In Vivo

BACKGROUND

Apolipoprotein A-II (ApoA-II) is down regulated in the sera of pancreatic ductal adenocarcinoma (PDAC) patients, which may be due to increase utilization of high density lipoprotein (HDL) lipid by pancreatic cancer tissue. This study examined the influence of exogenous ApoA-II on lipid uptake and cell growth in pancreatic cancer (PC) both in vitro and in vivo.

METHODS

Cryo transmission electron microscopy (TEM) examined ApoA-II's influence on morphology of SMOFLipid emulsion. The influence of ApoA-II on proliferation of cancer cell lines was determined by incubating them with lipid+/-ApoA-II and anti-SR-B1 antibody. Lipid was labeled with the fluorophore, DiD, to trace lipid uptake by cancer cells in vitro by confocal microscopy and in vivo in PDAC patient derived xenograft tumours (PDXT) by fluorescence imaging. Scavenger receptor class B type-1(SR-B1) expression in PDAC cell lines and in PDAC PDXT was measured by western blotting and immunohistochemistry, respectively.

RESULTS

ApoA-II spontaneously converted lipid emulsion into very small unilamellar rHDL like vesicles (rHDL/A-II) and enhanced lipid uptake in PANC-1, CFPAC-1 and primary tumour cells as shown by confocal microscopy. SR-B1 expression was 13.2, 10.6, 3.1 and 2.3 fold higher in PANC-1, MIAPaCa-2, CFPAC-1 and BxPC3 cell lines than the normal pancreatic cell line (HPDE6) and 3.7 fold greater in PDAC tissue than in normal pancreas. ApoA-II plus lipid significantly increased the uptake of labeled lipid and promoted cell growth in PANC-1, MIAPaCa-2, CFPAC-1 and BxPC3 cells which was inhibited by anti SR-B1 antibody. Further, ApoA-II increased the uptake of lipid in xenografts by 3.4 fold.

CONCLUSION

Our data suggest that ApoA-II enhance targeting potential of lipid in pancreatic cancer which may have imaging and drug delivery potentialities.

Proteomic identification of potential cancer markers in human urine using subtractive analysis

Urine is an ideal medium in which to focus diagnostic cancer research due to the non-invasive nature and ease of sampling. Many large-scale proteomic studies have shown that urine is unexpectedly complex. We hypothesised that novel diagnostic cancer biomarkers could be discovered using a comparative proteomic analysis of pre-existing data. We assembled a database of 100 published datasets of 5,620 urinary proteins, as well as 46 datasets of 8,620 non-redundant proteins derived from kidney and blood proteome analyses. The data were then used to either subtract or compare molecules from a novel urinary proteome profiling dataset that we generated. We identified 1,161 unique proteins in samples from either cancer-bearing or healthy subjects. Subtractive analysis yielded a subset of 44 proteins that were found uniquely in urine from cancer patients, 30 of which were linked previously to cancer. In conclusion, this approach is useful in discovering novel biomarkers in tissues where unrelated profiling data is available. Only a limited disease-specific novel dataset is required to define new targets or substantiate previous findings. We have shared this discovery platform in the form of our Large Scale Screening Resource database, accessible through the Proteomic Analysis DataBase portal (www.PADB.org).

Pancreatic Cancer: a Challenge to Cure

Pancreatic ductal adenocarcinoma (PDA) is a challenging disease, as overall survival has not improved over the last several decades. The disease is characterized by late diagnosis, difficult major surgery in resectable patients, and a biologically chemoresistant tumor. Intense research in the field is ongoing to develop biomarkers for early detection and prognostication. Surgery is presently the crux of the management of PDA and has been standardized over the years with high-volume centers reporting <5 % operative mortality. The biggest problem is to overcome the inherent chemoresistance of the tumor that is densely fibrotic and hypoxic and has a tendency to invade surrounding neuronal plexuses. This review attempts to summarize in brief the reasons why PDA is difficult to treat, and provides a glimpse of the ongoing research in the field.

Pancreatic preneoplastic lesions plasma signatures and biomarkers based on proteome profiling of mouse models

Background:

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies with a mortality that is almost identical to incidence. Because early detected PDAC is potentially curable, blood-based biomarkers that could detect currently developing neoplasia would improve patient survival and management. PDAC develops from pancreatic intraepithelial neoplasia (PanIN) lesions, graded from low grade (PanIN1) to high grade (PanIN3). We made the hypothesis that specific proteomic signatures from each precancerous stage exist and are detectable in plasma.

Methods:

We explored the peptide profiles of microdissected PanIN cells and of plasma samples corresponding to the different PanIN grade from genetically engineered mouse models of PDAC using capillary electrophoresis coupled to mass spectrometry (CE-MS) and Chip-MS/MS.

Results:

We successfully characterised differential peptides profiles from PanIN microdissected cells. We found that plasma from tumor-bearing mice and age-matched controls exhibit discriminative peptide signatures. We also determined plasma peptide signatures corresponding to low- and high-grade precancerous step present in the mice pancreas using the two mass spectrometry technologies. Importantly, we identified biomarkers specific of PanIN3.

Conclusions:

We demonstrate that benign and advanced PanIN lesions display distinct plasma peptide patterns. This strongly supports the perspectives of developing a non-invasive screening test for prediction and early detection of PDAC.

Potential prognostic significance of a new proteomic profile in patients with advanced pancreatic adenocarcinoma

OBJECTIVES

Seven-signal proteomic approach has recently been developed as a new proteomic profile measured by matrix-assisted laser desorption/ionization mass spectrometry. The aim of this study was to evaluate prognostic significance of this proteomic value in patients with pancreatic adenocarcinoma.

METHODS

Blood samples from the patients with pancreatic adenocarcinoma were prospectively collected before treatments including surgical resection and systemic chemotherapies. The seven-signal proteomic profiles of the samples were measured, and the prognostic significance of the proteomic value was evaluated through comparison with other existing prognostic markers.

RESULTS

Cut-off value of the proteomic profiles at 52 stratified overall prognosis of the patients (6.5 months vs. 10.9 months with the values ≥52 vs. <52, p = 0.020). In subgroup analyses of inoperable cases with carcinoembryonic antigen level of <5 ng/ml or performance status of 0-1, the proteomic value at 52 stratified their prognosis (p = 0.002 and p = 0.006, respectively).

CONCLUSIONS

The new seven-signal proteomics showed useful prognostic significance for patients with pancreatic adenocarcinoma. Further studies with a large sample size would be required to evaluate whether this proteomic approach possibly complements the existing parameters, such as carcinoembryonic antigen and performance status.

Identification of apolipoprotein C-I as a potential Wilms' tumor marker after excluding inflammatory factors

Wilms' tumor is one of the most common malignant tumors observed in children, and its early diagnosis is important for late-stage treatment and prognosis. We previously screened and identified protein markers for Wilms' tumor; however, these markers lacked specificity, and some were associated with inflammation. In the current study, serum samples from children with Wilms' tumors were compared with those of healthy controls and patients with systemic inflammatory response syndrome (SIRS). After exclusion of factors associated with inflammation, specific protein markers for Wilms' tumors were identified. After comparing the protein peak values obtained from all three groups, a protein with a m/z of 6438 Da was specified. Purification and identification of the target protein using high-pressure liquid chromatography (HPLC) and two-dimensional liquid chromatography-linearion trap mass spectrometry(2D-LC-LTQ-MS) mass spectrometry, respectively, revealed that it was apolipoprotein C-I (APO C-I). Thus, APO C-I is a specific protein marker for Wilms' tumor.

SELDI-TOF-MS proteomic profiling of serum, urine, and amniotic fluid in neural tube defects

Neural tube defects (NTDs) are common birth defects, whose specific biomarkers are needed. The purpose of this pilot study is to determine whether protein profiling in NTD-mothers differ from normal controls using SELDI-TOF-MS. ProteinChip Biomarker System was used to evaluate 82 maternal serum samples, 78 urine samples and 76 amniotic fluid samples. The validity of classification tree was then challenged with a blind test set including another 20 NTD-mothers and 18 controls in serum samples, and another 19 NTD-mothers and 17 controls in urine samples, and another 20 NTD-mothers and 17 controls in amniotic fluid samples. Eight proteins detected in serum samples were up-regulated and four proteins were down-regulated in the NTD group. Four proteins detected in urine samples were up-regulated and one protein was down-regulated in the NTD group. Six proteins detected in amniotic fluid samples were up-regulated and one protein was down-regulated in the NTD group. The classification tree for serum samples separated NTDs from healthy individuals, achieving a sensitivity of 91% and a specificity of 97% in the training set, and achieving a sensitivity of 90% and a specificity of 97% and a positive predictive value of 95% in the test set. The classification tree for urine samples separated NTDs from controls, achieving a sensitivity of 95% and a specificity of 94% in the training set, and achieving a sensitivity of 89% and a specificity of 82% and a positive predictive value of 85% in the test set. The classification tree for amniotic fluid samples separated NTDs from controls, achieving a sensitivity of 93% and a specificity of 89% in the training set, and achieving a sensitivity of 90% and a specificity of 88% and a positive predictive value of 90% in the test set. These suggest that SELDI-TOF-MS is an additional method for NTDs pregnancies detection.

Serum cytokine biomarker panels for discriminating pancreatic cancer from benign pancreatic disease

BACKGROUND

We investigated whether combinations of serum cytokines, used with logistic disease predictor models, could facilitate the detection of pancreatic ductal adenocarcinoma (PDAC).

METHODS

The serum levels of 27 cytokines were measured in 241 subjects, 127 with PDAC, 49 with chronic pancreatitis, 20 with benign biliary obstruction and 45 healthy controls. Samples were split randomly into independent training and test sets. Cytokine biomarker panels were selected by identifying the top performing cytokines in best fit logistic regression models during multiple rounds of resampling from the training dataset. Disease prediction by logistic models, built using the resulting cytokine panels, was evaluated with training and test sets and further examined using resampled performance evaluation.

RESULTS

For the discrimination of PDAC patients from patients with benign disease, a panel of IP-10, IL-6, PDGF plus CA19-9 offered improved diagnostic performance over CA19-9 alone in the training (AUC 0.838 vs. 0.678) and independent test set (AUC 0.884 vs. 0.798). For the discrimination of PDAC from CP, a panel of IL-8, CA19-9, IL-6 and IP-10 offered improved diagnostic performance over CA19-9 alone with the training (AUC 0.880 vs. 0.758) and test set (AUC 0.912 vs. 0.848). Finally, for the discrimination of PDAC in the presence of jaundice from benign controls with jaundice, a panel of IP-10, IL-8, IL-1b and PDGF demonstrated improvement over CA19-9 in the training (AUC 0.810 vs. 0.614) and test set (AUC 0.857 vs. 0.659).

CONCLUSIONS

These findings support the potential role for cytokine panels in the discrimination of PDAC from patients with benign pancreatic diseases and warrant additional study.

Discrimination between adenocarcinoma and normal pancreatic ductal fluid by proteomic and glycomic analysis

Sensitive and specific biomarkers for pancreatic cancer are currently unavailable. The high mortality associated with adenocarcinoma of the pancreatic epithelium justifies the broadest possible search for new biomarkers that can facilitate early detection or monitor treatment efficacy. Protein glycosylation is altered in many cancers, leading many to propose that glycoproteomic changes may provide suitable biomarkers. In order to assess this possibility for pancreatic cancer, we have performed an in-depth LC-MS/MS analysis of the proteome and MS(n)-based characterization of the N-linked glycome of a small set of pancreatic ductal fluid obtained from normal, pancreatitis, intraductal papillary mucinous neoplasm (IPMN), and pancreatic adenocarcinoma patients. Our results identify a set of seven proteins that were consistently increased in cancer ductal fluid compared to normal (AMYP, PRSS1, GP2-1, CCDC132, REG1A, REG1B, and REG3A) and one protein that was consistently decreased (LIPR2). These proteins are all directly or indirectly associated with the secretory pathway in normal pancreatic cells. Validation of these changes in abundance by Western blotting revealed increased REG protein glycoform diversity in cancer. Characterization of the total N-linked glycome of normal, IPMN, and adenocarcinoma ductal fluid clustered samples into three discrete groups based on the prevalence of six dominant glycans. Within each group, the profiles of less prevalent glycans were able to distinguish normal from cancer on this small set of samples. Our results emphasize that individual variation in protein glycosylation must be considered when assessing the value of a glycoproteomic marker, but also indicate that glycosylation diversity across human subjects can be reduced to simpler clusters of individuals whose N-linked glycans share structural features.

Biomarkers in pancreatic cancer: diagnostic, prognostic, and predictive

Pancreatic cancer is the fourth leading cause of cancer-related death in the United States. There has been minimal progress with regard to cancer-specific outcomes in recent decades. Although effective therapies will undoubtedly change the natural history of the disease, effective biomarkers are a promising tool that will likely have a positive impact and will undoubtedly have an important role in the management of patients with pancreatic ductal adenocarcinoma (PDA) in the future. At present, serum CA-19-9 (carbohydrate antigen 19-9) is the only Food and Drug Administration-approved biomarker for PDA, and it has utility as a prognostic marker and as a marker of disease recurrence. There has been a recent explosion in the pancreatic cancer biomarker field with more than 2000 biomarker studies implicating thousands of informative genes as candidate biomarkers. In this review, we summarize the literature on CA-19-9 in PDA and highlight the most promising investigational biomarkers. Distinctions are made between diagnostic biomarkers (detection of disease), prognostic biomarkers (provide information on prognosis and recurrence pattern), and predictive biomarkers (predict treatment response).

Identification and verification of transthyretin as a potential biomarker for pancreatic ductal adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers worldwide and is difficult to detect at its early stages when treatment is most effective. Therefore, we performed a comparative proteomic study to identify new biomarkers for the detection of PDAC.

METHODS

Serum samples from patients with PDAC, chronic pancreatitis and normal controls were compared using two-dimensional difference gel electrophoresis (2D-DIGE). Differentially expressed separated proteins were subsequently identified by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF/TOF-MS). Then, transthyretin (TTR), one of the differentially expressed proteins, was validated through real-time PCR, western blot and immunohistochemistry. Finally, enzyme-linked immunosorbent assays (ELISA) were employed to confirm the levels of transthyretin in the sera.

RESULTS

A total of 21 protein spots showed greater than 1.5-fold changes in expression level in the sera from PDAC patients compared with the normal controls. Among the identified proteins, validation experiments verified the differential expression of transthyretin in PDAC tissue, confirming the proteomic data showing that transthyretin was significantly elevated in patients with PDAC. The ELISA results revealed that the sensitivity and specificity for TTR and CA19-9 in distinguishing PDAC patients from normal individuals were 90.5, 47.6, 66.7 and 85.7 %, respectively, and 81.0 and 85.7 % for their combination.

CONCLUSIONS

These results suggest that the level of transthyretin is elevated in patients with PDAC. In combination with CA19-9, transthyretin may provide additional information for the detection of PDAC and should be further investigated.

Breast cancer biomarkers: proteomic discovery and translation to clinically relevant assays

Although the molecular classification and prognostic assessment of breast tumors based on gene expression profiling is well established, a number of proteomic studies that propose potential breast cancer biomarkers has not yet led to any new diagnostic, prognostic or predictive test in wide clinical use. This review examines the current status of breast cancer biomarkers, discusses sample types (including plasma, tumor tissue, nipple aspirate and ductal lavage, as well as cell culture models) and different electrophoretic and mass spectrometry methods that have been widely used for the discovery of proteomic biomarkers in breast cancer, and also considers several approaches to biomarker validation. The pathway leading from the initial proteomic discovery and validation process to translation into a clinically useful test is also discussed.

Usefulness of MALDI-TOF/MS identification of low-MW fragments in sera for the differential diagnosis of pancreatic cancer

OBJECTIVES

To identify new biomarkers of pancreatic cancer (PaCa), we performed MALDI-TOF/MS analysis of sera from 22 controls, 51 PaCa, 37 chronic pancreatitis, 24 type II diabetes mellitus (DM), 29 gastric cancer (GC), and 24 chronic gastritis (CG).

METHODS

Sera were purified by Sep-Pak C18 before MALDI-TOF/MS Anchorchip analysis.

RESULTS

Features present in at least 5% of all spectra were selected (n = 160, m/z range, 1200-5000). At univariate analysis, 2 features (m/z 2049 and 2305) correlated with PaCa, 3 (m/z 1449, 1605, and 2006) with DM. No feature characterized gastric cancer or chronic gastritis. Ten-fold cross-validation binary recursive partitioning trees were obtained for patients' classification. The tree (CA 19-9, age, m/z 2006, 2599, 2753, and 4997), built considering only patients with diabetes, allowed a distinction between DM [area under the receiver operating characteristic curve (AUC), 0.997], chronic pancreatitis (AUC, 0.968), and PaCa (AUC, 0.980), with an overall correct classification rate of 89%. The tree including CA 19-9, 1550, and 2937 m/z features, achieved an AUC of 0.970 in distinguishing localized from advanced PaCa. MALDI-TOF-TOF analysis revealed the 1550 feature as a fragment of Apo-A1, which was determined as whole protein and demonstrated to be closely correlated with PaCa.

CONCLUSIONS

The findings made demonstrate a role for serum peptides identified using MALDI-TOF/MS for addressing PaCa diagnosis.

Proteomics: methodologies and applications to the study of human diseases

Proteomic approach has allowed large-scale studies of protein expression in different tissues and body fluids in discrete conditions and/or time points. Recent advances of methodologies in this field have opened new opportunities to obtain relevant information on normal and abnormal processes occurring in the human body. In the current report, the main proteomics techniques and their application to human disease study are reviewed.

Serum biomarkers identification by mass spectrometry in high-mortality tumors

Cancer affects millions of people worldwide. Tumor mortality is substantially due to diagnosis at stages that are too late for therapies to be effective. Advances in screening methods have improved the early diagnosis, prognosis, and survival for some cancers. Several validated biomarkers are currently used to diagnose and monitor the progression of cancer, but none of them shows adequate specificity, sensitivity, and predictive value for population screening. So, there is an urgent need to isolate novel sensitive, specific biomarkers to detect the disease early and improve prognosis, especially in high-mortality tumors. Proteomic techniques are powerful tools to help in diagnosis and monitoring of treatment and progression of the disease. During the last decade, mass spectrometry has assumed a key role in most of the proteomic analyses that are focused on identifying cancer biomarkers in human serum, making it possible to identify and characterize at the molecular level many proteins or peptides differentially expressed. In this paper we summarize the results of mass spectrometry serum profiling and biomarker identification in high mortality tumors, such as ovarian, liver, lung, and pancreatic cancer.

Serum apolipoprotein C-II is prognostic for survival after pancreatic resection for adenocarcinoma

BACKGROUND

Pancreaticoduodenectomy remains a major undertaking. A preoperative blood test, which could confidently predict the benefits of surgery would improve the selection of pancreatic cancer patients for surgery. This study aimed to identify protein biomarkers prognostic for long-term survival and to validate them with clinico-pathological information.

METHODS

Serum from 40 preoperative patients was used to train for predictive biomarkers using surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI), and the results were verified on 21 independent samples. Two predictive proteins were identified by tryptic peptide mass fingerprinting and sequencing, and validated on serum from another 57 patients by enzyme-linked immunosorbent assay (ELISA). The influence of these proteins on growth and invasion of two cancer cell lines was tested in-vitro.

RESULTS

The SELDI panel of m/z 3700, 8222 and 11 522 peaks predicted <12 months' survival (ROC AUC: 0.79, 0.64-0.90; P<0.039). When CA19-9 was added, the ROC AUC increased to 0.95 (0.84-0.99; P<0.0001). The six subjects in the verification group who died within 12 months were correctly classified. The m/z 8222 and 11 522 proteins were identified as Serum ApoC-II and SAA-1, respectively. In the validation samples, ELISA results confirmed that ApoC-II was predictive of survival (Kaplan-Meier P<0.009), but not SAA-I. ApoC-II, CA19-9 and major-vessel involvement independently predicted survival. ApoC-II and SAA-1 increased cell growth and invasion of both cancer cell lines.

CONCLUSION

Serum ApoC-II, CA19-9 and major-vessel invasion independently predict survival and improves selection of patients for pancreaticoduodenectomy.

Molecular pathology of pancreatic cancer: from bench-to-bedside translation

Pancreatic ductal adenocarcinoma (referred here as pancreatic cancer) is a lethal disease with the worst prognosis among all solid tumors. Surgical resection represents the only hope for cure but it is possible only in patients that present with local disease (about 20% of cases). Whether dismal prognosis of pancreatic cancer is a result of late diagnosis or early dissemination to distant organ is still a debate. Moreover, this disease shows an intrinsic chemotherapeutic resistance that has been mainly ascribed to the presence of a dense stromal reaction that significantly impairs drugs delivery. Clinical management of pancreatic cancer patients relies on few molecular markers (e.g., the diagnostic marker CA19-9) that, however, present several limitations to their use. The clinical usefulness of somatic alterations in well-characterized genes (such as KRAS and TP53), whose detection is technically feasible in different biological samples, has been extensively investigated leading to inconsistent results. Furthermore, none of the candidate molecular markers identified in recent years has shown an appropriate clinical performance and therefore none is routinely used. This depicts a scenario where the identification of novel and effective clinical biomarkers is mandatory. Very recent genome-wide comprehensive studies have shed light on the high degree of genetic complexity and heterogeneity of the pancreatic cancers. Although far from being introduced into the clinical settings, results from those studies are expected to change definitively the perspective through which we look at the clinical management of pancreatic cancer patients towards a personalized cancer medicine.

Diagnostic, prognostic, and predictive biomarkers in pancreatic cancer

Serum CA 19-9 is the only FDA approved biomarker recommended for use in the routine management of pancreatic ductal adenocarcinoma (PDA). Over 2,000 biomarker studies related to pancreatic cancer appear in the literature, highlighting the need to discover and develop improved tests. Diagnostic biomarkers have implications for early detection of PDA, prognostic markers predict patient survival and recurrence patterns, and predictive markers can help personalize treatment regimens.

Discovery of diagnostic biomarkers for pancreatic cancer in immunodepleted serum by SELDI-TOF MS

MOTIVATION

Reports of serum pancreatic cancer (PC) biomarkers using SELDI-TOF MS have been inconsistent because different chip surfaces and interference with high-abundant proteins. This study examines the influence of these factors on the detection of discriminating diagnostic biomarkers.

METHODS

Serum from fourteen from patients with PC, disease controls (DC, n = 14) and healthy volunteers (HV, n = 14) were evaluated by SELDI using H50, IMAC, Q10 and CM10 chips. A further evaluation was undertaken after depletion of seven high-abundant proteins using spin cartridges.

RESULTS

More protein peaks were detected in whole serum than in depleted serum for IMAC, H50 and Q10 chips: 60 vs 39, 56 vs 48 and 69 vs 65, respectively, while the CM10 found less peaks in serum (27 vs 47 peaks). However, there were more differentially expressed peaks in the depleted serum samples for PC vs DC and PC vs HV samples using the H50, Q10 and CM10 ProteinChip arrays, whereas for IMAC arrays, more discriminating peaks were seen in non-depleted serum. The highly significant peaks observed on Q10, CM10 and H50 are consistent with the previous finding of ApoA-I (m/z 27,910-28000) and ApoA-II (m/z 8758 and 17,240). In addition, a number of new discriminating protein peaks were found on different ProteinChip arrays, notably peaks at m/z 4280 and 7763 on IMAC arrays.

CONCLUSION

This study confirms the diagnostic value of ApoA-I&II and identifies further potential diagnostic biomarkers for pancreatic cancer when multiple chip surfaces are used with depletion of the most highly-abundant proteins.

Advances in biomarker research for pancreatic cancer

Pancreatic cancer (PC) is a leading cause of cancer related deaths in United States. The lack of early symptoms results in latestage detection and a high mortality rate. Currently, the only potentially curative approach for PC is surgical resection, which is often unsuccessful because the invasive and metastatic nature of the tumor masses makes their complete removal difficult. Consequently, patients suffer relapses from remaining cancer stem cells or drug resistance that eventually lead to death. To improve the survival rate, the early detection of PC is critical. Current biomarker research in PC indicates that a serum carbohydrate antigen, CA 19-9, is the only available biomarker with approximately 90% specificity to PC. However, the efficacy of CA 19-9 for assessing prognosis and monitoring patients with PC remains contentious. Thus, advances in technology and the detection of new biomarkers with high specificity to PC are needed to reduce the mortality rate of pancreatic cancer.

Proteome-based biomarkers in pancreatic cancer

Pancreatic cancer, as a highly malignant cancer and the fourth cause of cancer-related death in world, is characterized by dismal prognosis, due to rapid disease progression, highly invasive tumour phenotype, and resistance to chemotherapy. Despite significant advances in treatment of the disease during the past decade, the survival rate is little improved. A contributory factor to the poor outcome is the lack of appropriate sensitive and specific biomarkers for early diagnosis. Furthermore, biomarkers for targeting, directing and assessing therapeutic intervention, as well as for detection of residual or recurrent cancer are also needed. Thus, the identification of adequate biomarkers in pancreatic cancer is of extreme importance. Recently, accompanying the development of proteomic technology and devices, more and more potential biomarkers have appeared and are being reported. In this review, we provide an overview of the role of proteome-based biomarkers in pancreatic cancer, including tissue, serum, juice, urine and cell lines. We also discuss the possible mechanism and prospects in the future. That information hopefully might be helpful for further research in the field.

Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis

The aim of this study is to find the potential biomarkers from the rat hepatocellular carcinoma (HCC) disease model by using a non-target metabolomics method, and test their usefulness in early human HCC diagnosis. The serum metabolic profiling of the diethylnitrosamine-induced rat HCC model, which presents a stepwise histopathological progression that is similar to human HCC, was performed using liquid chromatography-mass spectrometry. Multivariate data analysis methods were utilized to identify the potential biomarkers. Three metabolites, taurocholic acid, lysophosphoethanolamine 16:0, and lysophosphatidylcholine 22:5, were defined as "marker metabolites," which can be used to distinguish the different stages of chemical hepatocarcinogenesis. These metabolites represented the abnormal metabolism during the progress of hepatocarcinogenesis, which could also be found in patients. To test their diagnosis potential 412 sera from 262 patients with HCC, 76 patients with cirrhosis and 74 patients with chronic hepatitis B were collected and studied, it was found that 3 marker metabolites were effective for the discrimination of small liver tumor (solitary nodules of less than 2 cm in diameter) patients, achieved a sensitivity of 80.5% and a specificity of 80.1%,which is better than those of α-fetoprotein (53 and 64%, respectively). Moreover, they were also effective for the discrimination of all HCCs and chronic liver disease patients, which could achieve a sensitivity of 87.5% and a specificity of 72.3%, better than those of α-fetoprotein (61.2 and 64%). These results indicate metabolomics method has the potential of finding biomarkers for the early diagnosis of HCC.

New serum biomarkers for detection of tuberculosis using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry

BACKGROUND

New technologies for the early detection of tuberculosis (TB) are urgently needed. Pathological changes within an organ might be reflected in proteomic patterns in serum. The aim of the present study was to screen for the potential protein biomarkers in serum for the diagnosis of TB using proteomic fingerprint technology.

METHODS

Proteomic fingerprint technology combining protein chips with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) was used to profile the serum proteins from 50 patients with TB, 25 patients with lung disease other than TB, and 25 healthy volunteers. The protein fingerprint expression of all the serum samples and the resulting profiles between TB and control groups were analyzed with the Biomarker Wizard system.

RESULTS

A total of 30 discriminating m/z peaks were detected that were related to TB (p<0.01). The model of biomarkers constructed by the Biomarker Patterns Software based on the three biomarkers (2024, 8007, and 8598 Da) generated excellent separation between the TB and control groups. The sensitivity was 84.0% and the specificity was 86.0%. Blind test data indicated a sensitivity of 80.0% and a specificity of 84.2%.

CONCLUSIONS

The data suggested a potential application of SELDI-TOF MS as an effective technology to profile serum proteome, and with pattern analysis, a diagnostic model comprising three potential biomarkers was indicated to differentiate people with TB and healthy controls rapidly and precisely.

Prediction of metastasis and recurrence in colorectal cancer based on gene expression analysis: ready for the clinic?

Cancers of the colon and rectum, which rank among the most frequent human tumors, are currently treated by surgical resection in locally restricted tumor stages. However, disease recurrence and formation of local and distant metastasis frequently occur even in cases with successful curative resection of the primary tumor (R0). Recent technological advances in molecular diagnostic analysis have led to a wealth of knowledge about the changes in gene transcription in all stages of colorectal tumors. Differential gene expression, or transcriptome analysis, has been proposed by many groups to predict disease recurrence, clinical outcome, and also response to therapy, in addition to the well-established clinico-pathological factors. However, the clinical usability of gene expression profiling as a reliable and robust prognostic tool that allows evidence-based clinical decisions is currently under debate. In this review, we will discuss the most recent data on the prognostic significance and potential clinical application of genome wide expression analysis in colorectal cancer.

Screening technologies for target identification in pancreatic cancer

Pancreatic cancer exhibits an extraordinarily high level of resistance to almost any kind of systemic therapy evaluated in clinical trials so far. Therefore, the identification of novel therapeutic targets is urgently required. High-throughput screens have emerged as an important tool to identify putative targets for diagnosis and therapy in an unbiased manner. More than a decade ago, microarray technology was introduced to identify differentially expressed genes in pancreatic cancer as compared to normal pancreas, chronic pancreatitis and other cancer types located in close proximity to the pancreas. In addition, proteomic screens have facilitated the identification of differentially secreted proteins in body fluids of pancreatic cancer patients, serving as possible biomarkers. Recently, RNA interference-based loss-of-function screens have been used to identify functionally relevant genes, whose knock-down has impact on pancreatic cancer cell viability, thereby representing potential new targets for therapeutic intervention. This review summarizes recent results of transcriptional, proteomic and functional screens in pancreatic cancer and discusses potentials and limitations of the respective technologies as well as their impact on future therapeutic developments.