Identification of potential markers for the detection of pancreatic cancer through comparative serum protein expression profiling

Confounding effect of obstructive jaundice in the interpretation of proteomic plasma profiling data for pancreatic cancer

It is well established that variation in sampling, processing and storage protocols can alter the levels of potential biomarkers in serum and plasma. Here, using pancreatic cancer as an example, we demonstrate that consideration of clinical parameters related to the patient's illness is equally important when seeking cancer-specific biomarkers. Bile duct-obstruction is a feature of pancreatic disease that can cause jaundice. Comparing patients with pancreatic cancer, chronic pancreatitis or biliary duct obstruction, we observed that the plasma levels of apolipoprotein A1, transthyretin, and apolipoprotein E, when examined in isolation, were each associated with pancreatic cancer. However, when the effect of bile duct obstruction was considered, only transthyretin levels were independently associated with cancer likelihood. Our results demonstrate the importance of accounting for disease-related confounding factors when analyzing data for the detection of cancer biomarkers.

Examining the significance of fingerprint-based classifiers

Background

Experimental examinations of biofluids to measure concentrations of proteins or their fragments or metabolites are being explored as a means of early disease detection, distinguishing diseases with similar symptoms, and drug treatment efficacy. Many studies have produced classifiers with a high sensitivity and specificity, and it has been argued that accurate results necessarily imply some underlying biology-based features in the classifier. The simplest test of this conjecture is to examine datasets designed to contain no information with classifiers used in many published studies.

Results

The classification accuracy of two fingerprint-based classifiers, a decision tree (DT) algorithm and a medoid classification algorithm (MCA), are examined. These methods are used to examine 30 artificial datasets that contain random concentration levels for 300 biomolecules. Each dataset contains between 30 and 300 Cases and Controls, and since the 300 observed concentrations are randomly generated, these datasets are constructed to contain no biological information. A modest search of decision trees containing at most seven decision nodes finds a large number of unique decision trees with an average sensitivity and specificity above 85% for datasets containing 60 Cases and 60 Controls or less, and for datasets with 90 Cases and 90 Controls many DTs have an average sensitivity and specificity above 80%. For even the largest dataset (300 Cases and 300 Controls) the MCA procedure finds several unique classifiers that have an average sensitivity and specificity above 88% using only six or seven features.

Conclusion

While it has been argued that accurate classification results must imply some biological basis for the separation of Cases from Controls, our results show that this is not necessarily true. The DT and MCA classifiers are sufficiently flexible and can produce good results from datasets that are specifically constructed to contain no information. This means that a chance fitting to the data is possible. All datasets used in this investigation are available on the web.

This work is funded by NCI Contract N01-CO-12400.

Differentially expressed serum haptoglobin alpha chain isoforms with potential application for diagnosis of head and neck cancer

BACKGROUND

The discovery of molecular biomarkers is crucial to the diagnosis of head and neck squamous cell cancer (HNSCC).

METHODS

Proteins from pre-surgery serum samples of patients with HNSCC and healthy individuals were analyzed by 2-dimensional gel electrophoresis (2-DE) using a 17 cm-long immobilized pH gradient gel strip (large gel). The differentially expressed protein spots were detected by statistical analysis. Because 2 haptoglobin (Hp) alpha chains were found to be differentially expressed, the genotypic distribution of Hp alpha chains in patients and healthy individuals was assayed by polymerase chain reaction. The protein expression levels of Hp alpha chains in individuals carrying different Hp alleles were analyzed by 2-DE with a small gel.

RESULTS

Two isoforms of haptoglobin alpha2 chain (Hp alpha2) in patients' sera were found from 2-DE analysis to be up-regulated, while the isoforms of haptoglobin alpha1 chain (Hp alpha1) were significantly down-regulated. Apolipoprotein AII and 2 isoforms of apolipoprotein CII were also differentially expressed in the sera of patients with HNSCC. The Hp alpha2 chain was significantly up-regulated in the patients carrying at least one haptoglobin 2 allele, according to the spot intensities from scanned images of small-gel 2-DE.

CONCLUSIONS

The expression pattern of seven differentially expressed polypeptides and the up-regulation of Hp alpha2 in individuals with the Hp 2 allele are potential biomarkers.

ProApolipoprotein A1: a serum marker of brain metastases in lung cancer patients

BACKGROUND

Central nervous system (CNS) diagnostics is a promising tool for detection of neurological disorders, including brain metastases. One of the earliest applications of CNS diagnostics was based on serum markers of blood-brain barrier (BBB) dysfunction, which often correlates with acute, chronic, or incipient brain disease. In the case of brain metastases, serum levels of S100beta demonstrated a good negative predictive value comparable to radiologic investigations. However, a confounding factor was the presence of BBB changes due to cerebrovascular disease.

METHODS

Of 103 patients enrolled in a lung cancer study, greater than 50% presented with magnetic resonance imaging (MRI) changes consistent with chronic cerebrovascular disease and reflected by elevated serum S100beta. To unveil serum protein, the authors used proteomic techniques that allow discrimination between patients with brain metastases and lung cancer patients affected by cerebrovascular ischemic changes without infiltrating tumor.

RESULTS

ProApolipoprotein A1, transferrin, haptoglobin, and transthyretin were upregulated in patients affected by chronic cerebrovascular disease and brain metastases compared with those affected only by vascular diseases. ProApolipoprotein A1 was significantly increased (p<.05) in patients with CNS disease.

CONCLUSIONS

In conclusion, these data support the use of serum markers for the early detection of brain metastases. ProApolipoprotein A1 may be used in conjunction with S100beta for serum-based, MRI-independent diagnosis of metastatic brain tumors.

Proteomics of pancreatic cancer

Pancreatic cancer is a devastating disease, with a mortality rate almost identical with its incidence. Late diagnosis and limited therapeutic options make early detection of pancreatic cancer a pressing clinical problem. In this context, the investigation of the pancreatic cancer proteome has recently gained considerable attention because profiles of proteins may be able to more accurately identify disease states, such as cancer. Recent pancreatic cancer proteome studies may be categorized into basic studies cataloguing the pancreatic proteome, studies investigating differential protein expression patterns, and studies searching for proteome-based biomarkers for early cancer detection and differentiation. Although these studies clearly demonstrate that a range of biological samples are suitable for proteomic analyses, comparison of different studies is problematic due to the diversity of methodologies, sample sources, and characterization of patient populations. Reproducibility between studies has rarely been investigated, and no investigation has compared the different methods of proteomic research. The results of this review have shown that more stringent requirements concerning the design and the analysis of future studies should be implemented. These include an adequate patient number, obligatory histological examination of tissues, appropriate control groups, identification of proteins and peaks, validation of differential expression using independent cohorts and/or a second methodology, and, finally, demonstration of result reproducibility. This will hopefully lead to the discovery of prognostic and predictive biomarkers that help to improve prognosis of pancreatic cancer patients.

Survival in pancreatic carcinoma based on tumor size

OBJECTIVES

The size of pancreatic tumors that can be diagnosed by preoperative imaging continues to decrease because advances in diagnostic imaging. Several surgical series have suggested that survival is better in tumors 20 mm or smaller (vs tumors >20 mm), but the incremental benefit of diagnosing progressively smaller tumors from 30 mm (currently, the average size of pancreatic tumor at diagnosis) to 20 mm or smaller is not known. We investigated survival and resectability as tumor size increased from 20 mm or smaller to 30 mm or larger.

METHODS

This is a retrospective analysis of consecutive patients with pancreatic cancer, who underwent endoscopic ultrasound-guided fine-needle aspiration at MD Anderson Cancer Center between December 2000 and December 2001. Tumor size was based on the combination of endoscopic ultrasound and computed tomography imaging.

RESULTS

The median (+/-SE) for tumors 20 mm or smaller, 21 to 25 mm, 26 to 30 mm and larger than 30 mm was 17.2 +/- 8.2, 12.3 +/- 4.9, 8.5 +/- 3.6, and 7.6 +/- 1.2 months (P = 0.021), respectively. Tumors were resectable in 10 (83%) of 12 tumors 20 mm or smaller, 8 (67%) of 12 tumors 21 to 25 mm, 5 (36%) of 14 of tumors 26 to 30 mm, and 2 (7%) of 27 tumors larger than 30 mm (P < 0.001).

CONCLUSIONS

A dramatic change in survival occurs as the size of pancreatic tumor increases from 20 mm or smaller to 30 mm or larger. To be effective, future strategies for early diagnosis of pancreatic cancer should aim at diagnosing most pancreatic cancers before they are 20 mm in size.

Apolipoprotein C-1 maintains cell survival by preventing from apoptosis in pancreatic cancer cells

Pancreatic cancer still remains one of the most lethal diseases and establishment of new therapy is needed. The purpose of this study is to find novel factors involved in pancreatic cancer progression by proteomic approach. We compared pre- and postoperative serum protein profiling obtained from pancreatic cancer patients who had curative pancreatectomy using surface-enhanced laser desorption ionization time-of-flight mass spectrometry. The peak intensity levels of both 6630 and 6420 Da were significantly higher in the preoperative serum than in the postoperative serum (P<0.002). Sequential amino acid analysis identified these proteins to be apolipoprotein C-1 (ApoC-1). The high level of ApoC-1 in preoperative serum significantly correlated with poor prognosis. Furthermore, ApoC-1 was abundantly expressed in pancreas neoplastic epithelium, and was detected in the culture medium of the pancreatic cancer cell line in vitro, which suggests that cancer cells secrete ApoC-1. Inhibition of ApoC-1 expression by short interfering RNA suppressed cell proliferation and induced apoptosis of pancreatic cancer cells. The specific expression of ApoC-1 and its role in preventing from spontaneous apoptosis in pancreatic cancer cells suggest that ApoC-1 contributes to the aggressiveness of pancreatic cancer and will be useful as a new therapeutic target.

Protein expression profiling reveals distinctive changes in serum proteins associated with chronic pancreatitis

OBJECTIVE

Testing of serum for protein patterns to monitor progression of suspected to definite chronic pancreatitis (CP).

METHODS

Serum samples of CP patients and healthy volunteers were fractionated on anion exchange columns and analyzed by surface-enhanced laser desorption/ionization-time-of-flight mass spectrometry to elucidate CP-related protein alterations and to identify biomarkers for this disease. Potential biomarkers were purified and identified by mass spectrometry.

RESULTS

In total, 258 protein peaks were found that discriminated between the 2 groups. Analysis revealed 28 most prominent peaks on immobilized metal affinity capture coupled with Cu and CM10 protein chips, covering the m/z range between 3.3 and 33.3 kd. Performing multivariate pattern analysis, the best pattern model was obtained using fraction 6 on immobilized metal affinity capture coupled with Cu arrays with a sensitivity of 96% and a specificity of 84%. Using a combination of matrix-assisted laser desorption-ionization-time-of-flight mass spectrometry and immunodepletion, we identified 14-m/z peaks. The proteins were found to be significantly decreased in CP serum and were identified as retinol-binding protein, serum amyloid-alpha, apolipoprotein A-II (Apo A-II), Apo C-I, Apo C-II, Apo C-III, and transthyretin and truncated forms thereof.

CONCLUSIONS

Distinct protein profile differences exist between normal and CP serum and reflect the metabolic and inflammatory condition in CP patients. The identified protein panel may eventually serve as a diagnostic marker set for CP.

Proteomic analysis of human thyroid fine needle aspiration fluid

The aim of this study was to determine the protein pattern of human thyroid fine needle aspiration fluid (FNA) using a proteomic approach. FNA proteins were separated using 2-dimensional gel electrophoresis (2DE), digested and then analyzed by peptide mass fingerprinting. For the first time, we provided an image of the protein components of the FNA, in which approximately 220 protein spots can be identified. The proteome analysis revealed a specific fingerprint of FNA with proteins appertaining to various functional systems. Our preliminary results of FNA protein pattern could be a starting point in studying the presence of potential markers implicated in thyroid diseases.

Progress on molecular markers of pancreatic cancer

PURPOSE OF REVIEW

To describe advances in the development of biomarkers for pancreatic cancer over the past year.

RECENT FINDINGS

Several new approaches were taken in the search for biomarkers for pancreatic cancer. Studies of CA19-9 revealed new prognostic abilities of the already well known biomarker. New blood biomarkers were investigated and CEACAM1 and MIC-1 were found to be superior to CA19-9 at distinguishing cancer from normal but, unfortunately, not from chronic pancreatitis. MUC1 was reported to be superior to CA19-9 based on the use of a novel immunoassay. The superiority of the concept of a panel of biomarkers as opposed to single biomarkers was supported by several studies, but no such panel was identified. RNA levels in blood and DNA methylation in pancreatic juice yielded some promising findings. Advancements were also made in the area of tissue biomarkers, which can improve the diagnostic accuracy of fine-needle aspirations and provide prognostic information. A new source of potential biomarkers, microRNAs, also made its debut in the past year.

SUMMARY

The tools to identify pancreatic-cancer biomarkers and sources of samples needed in this search are expanding. The field has not yet achieved its aims, but several encouraging breakthroughs have been made.