Serum protein profiles to identify head and neck cancer

Comparison between two cell collecting methods for liquid-based brush biopsies: a consecutive and retrospective study

Background

This study compares two different cell collectors, the Orcellex Brush (rigid brush) and the Cytobrush GT (nylon brush), using liquid-based cytology. A comparison of their obtainment procedures was also considered. The aim was to determine the diagnostic accuracy for detection of malignancy in oral brush biopsies. PICO-Statement: In this consecutive and retrospective study we had as population of interests, patients with oral lesions, the intervention was the brush biopsy with two different cell collectors and the control was healthy oral mucosa. The outcome of the study was to compare both cell collectors.

Methods

From 2009 to 2018, 2018 patients with oral lesions were studied using the nylon brush (666 cases) and rigid brush (1352 cases). In the first cohort five smears per patient were taken with the nylon brush, while each patient received one smear with the rigid brush in the second cohort. These were further processed in a liquid-based procedure. Cytological evaluations were categorised into ‘negative’, which were considered as negative, whereas ‘doubtful’, ‘suspicious’ and ‘positive’ cytological results were overall considered as positive for malignancy in comparison to the final histological diagnoses. Additionally, the clinical expenditure for each collector was estimated.

Results

2018 clinically and histologically proven diagnoses were established, including 181 cases of squamous cell carcinomas, 524 lichen, 454 leukoplakias, 34 erythroplakias and 825 other benign lesions. The sensitivity and specificity of the nylon brush was 93.8% (95% CI 91.6–95.5%) and 94.2% (95% CI 91.8–95.5%) respectively, whereas it was 95.6% (95% CI 94.4–96.6%) and 84.9% (95% CI 83.8–87.5%) for the rigid brush. The temporal advantage using the plastic brushes was 4×  higher in comparison to the nylon brush. The risk suffering from a malignant oral lesion when the result of the brushes was positive, suspicious, or doubtful was significantly high for both tests (nylon brush OR: 246.3; rigid brush OR: 121.5).

Conclusions

Both systems have a similar sensitivity, although only the rigid brush achieved a satisfactory specificity. Additional methods, such as DNA image cytometry, should also be considered to improve the specificity. Furthermore, the rigid brush proved to be more effective at taking a sufficient number of cells, whilst also being quicker and presenting less stress for the patient.

Proteomic Strategies and their Application in Cancer Research

The understanding of carcinogenesis and tumor progression on a molecular basis needs a detailed study of proteins as effector molecules and as critical components of the multiple interconnected signaling pathways that drive the neoplastic phenotype. Thus, the proteomic approach represents a powerful tool for the challenge of the post-genomic era. The term “cancer proteome” refers to the collection of proteins expressed by a given cancer cell and should be considered as a highly dynamic entity within the cell, which affects a variety of cellular activities. The emerging proteomic analysis platforms including 2D-PAGE, mass spectrometry technologies, and protein microarrays represent powerful tools to study and understand cancer. These systems aim to not only identify, catalogue, and characterize cancer proteins, but also to unveil how they interact to affect overall tumor progression. Moreover, recent studies on various cancers have reported promising results concerning the detection of novel molecular biomarkers useful in the early diagnosis of cancer and in drug discovery. Thus, a new subdiscipline named clinical proteomics, concomitant with new molecular technologies that are developed, demonstrates promise to discover new cancer biomarkers. The early diagnosis of cancer, even in a premalignant state, is crucial for the successful treatment of this disease. For these reasons, it is clear that the identification of biomarkers for the early diagnosis of cancer should represent one of the main goals of this emerging field of study.

Saliva: Its Value as a Biological Matrix and Current Methods of Sampling

Saliva is a non-invasive medium, its analysis is useful to measure a wide range of hormones, drugs, narcotics, antibodies, host, microbial, fungal and viral DNA up to salivary mRNA; hence, it has been suggested to be an easy and reliable biomarker in disease diagnostics, such as inflammatory mouth infections/diseases, and in normal health surveillance. In light of this potential, our primary endpoint is to review the current knowledge on saliva analyses and its recent methods of sampling.

Fusaric acid: A novel agent and mechanism to treat HNSCC

OBJECTIVE: A new class of carboxylic acids has tumoricidal activity for head and neck squamous cell cancer (HNSCC). Fusaric acid (FA) can chelate divalent cations, especially zinc, and inactivate zinc finger proteins involved in DNA repair and protein synthesis.

METHODS: 2 squamous carcinoma lines were utilized for in vitro and in vivo portions of this study. Cell counting and flow cytometry were used to analyze cells in culture in treatment and control groups over 96 hours. HNSCC subcutaneous implants were created in treatment and control groups of BALB-c nude mice (N = 30).

RESULTS: In vitro studies demonstrated significant changes in cell numbers and cell cycle. In vivo studies of daily intralesional therapy for 1 month also showed reduced onset of growth and overall growth compared to controls.

CONCLUSION: FA appears to have a tumoristatic/tumoricidal effect on HNSCC. Further nude mice studies are needed to optimize dosing and administration regimens for FA in anticipation of clinical trials.

Identification of Serum Peptidome Signatures of Non-Small Cell Lung Cancer

Due to high mortality rates of lung cancer, there is a need for identification of new, clinically useful markers, which improve detection of this tumor in early stage of disease. In the current study, serum peptide profiling was evaluated as a diagnostic tool for non-small cell lung cancer patients. The combination of the ZipTip technology with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for the analysis of peptide pattern of cancer patients (n = 153) and control subjects (n = 63) was presented for the first time. Based on the observed significant differences between cancer patients and control subjects, the classification model was created, which allowed for accurate group discrimination. The model turned out to be robust enough to discriminate a new validation set of samples with satisfactory sensitivity and specificity. Two peptides from the diagnostic pattern for non-small cell lung cancer (NSCLC) were identified as fragments of C3 and fibrinogen α chain. Since ELISA test did not confirm significant differences in the expression of complement component C3, further study will involve a quantitative approach to prove clinical utility of the other proteins from the proposed multi-peptide cancer signature.

Diagnostic accuracy of serum biomarkers for head and neck cancer: A systematic review and meta-analysis

Serum biomarkers could be helpful to characterize head and neck squamous cell carcinoma (HNSCC). Thus, the purpose of this systematic review and meta-analysis was to determine the diagnostic capability of serum biomarkers in the assessment of HNSCC patients. Studies were gathered by searching LILACS, PubMed, Science Direct, Scopus and Web of Science up to April 10th, 2015. Studies that focused on serum biomarkers in the diagnosis of HNSCC compared with controls were considered. Sixty-five studies were identified, and the sample size included 9098 subjects. Combined biomarkers demonstrated improved accuracy than those tested individually. Therefore, 12.8% of single and 34.3% of combined indicated that serum biomarkers discriminate patients with HNSCC from controls. The combined biomarkers with better diagnostic capability included Epidermal growth factor receptor (EGFR)+Cyclin D1 and squamous cell cancer-associated antigen (SCCA)+EGFR+Cyclin D1. Beta2-microglobin may also be a promising single biomarker for future studies. Serum biomarkers can be potentially useful in the diagnosis of HNSCC. However, further research is required to validate these biomarkers.

Identification of biomarkers for radiation-induced acute intestinal symptoms (RIAISs) in cervical cancer patients by serum protein profiling

Radiation-induced acute intestinal symptoms (RIAISs) are the most frequent complication of radiotherapy that causes great pain and limits the treatment efficacy. The aim of this study was to identify serum biomarkers of RIAISs in cervical cancer patients by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Serum samples were collected from 66 cervical cancer patients prior to pelvic radiotherapy. In our study, RIAISs occurred in 11 patients. An additional 11 patients without RIAISs were selected as controls, whose age, stage, histological type and treatment methods were matched to RIAISs patients. The 22 sera were subsequently analyzed by SELDI-TOF MS, and the resulting protein profiles were evaluated to identify biomarkers using appropriate bioinformatics tools. Comparing the protein profiles of serum samples from the RIAIS group and the control group, it was found that 22 protein peaks were significantly different (P < 0.05), and six of these peaks with mass-to-charge (m/z) ratios of 7514.9, 4603.94, 6887.41, 2769.21, 3839.72 and 4215.7 were successfully identified. A decision tree model of biomarkers was constructed based on three biomarkers (m/z 1270.88, 1503.23 and 7514.90), which separated RIAIS-affected patients from the control group with an accuracy of 81%. This study suggests that serum proteomic analysis by SELDI-TOF MS can identify cervical cancer patients that are susceptible to RIAISs prior to pelvic radiotherapy.

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 Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation

The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still needed for triage of people accidentally exposed to ionizing radiation. In this study, we investigated the impact of localized irradiation of the skin on the early alteration of the serum proteome of mice in an effort to discover markers associated with the exposure and severity of impending damage. Using two different large-scale quantitative proteomic approaches, 2D-DIGE-MS and SELDI-TOF-MS, we performed global analyses of serum proteins collected in the clinical latency phase (days 3 and 7) from non-irradiated and locally irradiated mice exposed to high doses of 20, 40 and 80 Gy which will develop respectively erythema, moist desquamation and necrosis. Unsupervised and supervised multivariate statistical analyses (principal component analysis, partial-least square discriminant analysis and Random Forest analysis) using 2D-DIGE quantitative protein data allowed us to discriminate early between non-irradiated and irradiated animals, and between uninjured/slightly injured animals and animals that will develop severe lesions. On the other hand, despite a high number of animal replicates, PLS-DA and Random Forest analyses of SELDI-TOF-MS data failed to reveal sets of MS peaks able to discriminate between the different groups of animals. Our results show that, unlike SELDI-TOF-MS, the 2D-DIGE approach remains a powerful and promising method for the discovery of sets of proteins that could be used for the development of clinical tests for triage and the prognosis of the severity of radiation-induced skin lesions. We propose a list of 15 proteins which constitutes a set of candidate proteins for triage and prognosis of skin lesion outcomes.

The Fanconi anemia pathway: repairing the link between DNA damage and squamous cell carcinoma

Fanconi anemia (FA) is a rare inherited recessive disease caused by mutations in one of fifteen genes known to encode FA pathway components. In response to DNA damage, nuclear FA proteins associate into high molecular weight complexes through a cascade of post-translational modifications and physical interactions, followed by the repair of damaged DNA. Hematopoietic cells are particularly sensitive to the loss of these interactions, and bone marrow failure occurs almost universally in FA patients. FA as a disease is further characterized by cancer susceptibility, which highlights the importance of the FA pathway in tumor suppression, and will be the focus of this review. Acute myeloid leukemia is the most common cancer type, often subsequent to bone marrow failure. However, FA patients are also at an extreme risk of squamous cell carcinoma (SCC) of the head and neck and gynecological tract, with an even greater incidence in those individuals who have received a bone marrow transplant and recovered from hematopoietic disease. FA tumor suppression in hematopoietic versus epithelial compartments could be mechanistically similar or distinct. Definition of compartment specific FA activities is now critical to assess the effects of today's bone marrow failure treatments on tomorrow's solid tumor development. It is our hope that current therapies can then be optimized to decrease the risk of malignant transformation in both hematopoietic and epithelial cells. Here we review our current understanding of the mechanisms of action of the Fanconi anemia pathway as it contributes to stress responses, DNA repair and squamous cell carcinoma susceptibility.

Advances in understanding the role of metallopanstimulin-1 in tumors

Metallopanstimulin-1 (MPS-1), belonging to the ribosomal protein S27E family, is ubiquitously expressed in all normal tissues except the brain and placenta. In addition, MPS-1 is highly expressed in malignant tumors and cells. MPS-1 as a tumor marker or tumor-associated antigen has been extensively studied in head and neck cancer and breast cancer. MPS-1 is highly expressed in gastric cancer. Knockdown of MPS-1 expression inhibits the growth of cancer cells both in vitro and in vivo and induces spontaneous apoptosis of gastric cancer cells by repressing the NF-κB signaling pathway. In addition, MPS-1 is also highly expressed in colonic cancer and has a close relationship with the degree of malignancy and prognosis. Therefore, MPS-1 may be a novel potential therapeutic target for cancers.

The development of a population-level clinical screening tool for self-harm repetition and suicide: the ReACT Self-Harm Rule

BACKGROUND

Self-harm is a common reason for Emergency Department (ED) attendance. We aimed to develop a clinical tool to help identify patients at higher risk of repeat self-harm, or suicide, within 6 months of an ED self-harm presentation.

METHOD

The tool, the ReACT Self-Harm Rule, was derived using multicentre data from a prospective cohort study. Binary recursive partitioning was applied to data from two centres, and data from a separate centre were used to test the tool. There were 29 571 self-harm presentations to five hospital EDs between January 2003 and June 2007, involving 18 680 adults aged ⩾16 years. We estimated sensitivity, specificity and positive and negative predictive values to measure the performance of the tool.

RESULTS

A self-harm presentation was classified as higher risk if at least one of the following factors was present: recent self-harm (in the past year), living alone or homelessness, cutting as a method of harm and treatment for a current psychiatric disorder. The rule performed with 95% sensitivity [95% confidence interval (CI) 94-95] and 21% specificity (95% CI 21-22), and had a positive predictive value of 30% (95% CI 30-31) and a negative predictive value of 91% (95% CI 90-92) in the derivation centres; it identified 83/92 of all subsequent suicides.

CONCLUSIONS

The ReACT Self-Harm Rule might be used as a screening tool to inform the process of assessing self-harm presentations to ED. The four risk factors could also be used as an adjunct to in-depth psychosocial assessment to help guide risk formulation. The use of multicentre data helped to maximize the generalizability of the tool, but we need to further verify its external validity in other localities.

Plasma and tissue proteomic prognostic factors of response in primary breast cancer patients receiving neoadjuvant chemotherapy

A pathological complete response (pCR) after neoadjuvant chemotherapy is observed in approximately 20% of breast cancer patients. A proteomic analysis was performed on plasma and tumor tissue before treatment to evaluate its potential impact on the prediction of response. One hundred and forty-nine breast cancer patients eligible for neoadjuvant chemotherapy were included in the study between February 2004 and January 2009 at three centers. The proteomic analysis was performed using SELDI Technology (ProteinChip CM10 pH4, IMAC-Cu and H50). Three acquisition protocols were used according to the mass range. Plasma and tumor proteomic signatures were generated using generalized ROC criteria and cross-validation. Twenty-eight (18.8%) patients out of 149 experienced a pCR according to Sataloff criteria. In the cytosol analysis, respectively 4, 2 and 8 proteins had significantly different levels of expression in the responders and non-responders using IMAC-Cu, H50 and CM10 pH4. Among the 8 proteins of interest on CM10 pH4, 2 (C1 and C7) were selected and were validated in 95.0 and 85.6% of the models. In the plasma analysis, respectively 12, 6 and 2 proteins had different levels of expression using the same proteinchips. Among the 12 plasma proteins of interest on IMAC-Cu, 2 (P1 and P7) were selected and were validated in 94.8 and 97.6% of the models. A combined proteomic signature was generated, which remained statistically significant when adjusted for hormone receptor status and Ki-67. Our results show that proteomic analysis can differentiate complete pathological responders in breast cancer patients after neoadjuvant chemotherapy.

MALDI-MS-Based Profiling of Serum Proteome: Detection of Changes Related to Progression of Cancer and Response to Anticancer Treatment

Mass spectrometry-based analyses of the low-molecular-weight fraction of serum proteome allow identifying proteome profiles (signatures) that are potentially useful in detection and classification of cancer. Several published studies have shown that multipeptide signatures selected in numerical tests have potential values for diagnostics of different types of cancer. However due to apparent problems with standardization of methodological details, both experimental and computational, none of the proposed peptide signatures analyzed directly by MALDI/SELDI-ToF spectrometry has been approved for routine diagnostics. Noteworthy, several components of proposed cancer signatures, especially those characteristic for advanced cancer, were identified as fragments of blood proteins involved in the acute phase and inflammatory response. This indicated that among cancer biomarker candidates to be possibly identified by serum proteome profiling were rather those reflecting overall influence of a disease (and the therapy) upon the human organism, than products of cancer-specific genes. Current paper focuses on changes in serum proteome that are related to response of patient's organism to progressing malignancy and toxicity of anticancer treatment. In addition, several methodological issues that affect robustness and interlaboratory reproducibility of MS-based serum proteome profiling are discussed.

Identification of Regional Lymph Node Involvement of Colorectal Cancer by Serum SELDI Proteomic Patterns

Background. To explore the application of serum proteomic patterns for the preoperative detection of regional lymph node involvement of colorectal cancer (CRC). Methods. Serum samples were applied to immobilized metal affinity capture ProteinChip to generate mass spectra by Surface-Enhanced Laser Desorption/ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS). Proteomic spectra of serum samples from 70 node-positive CRC patients and 75 age- and gender-matched node-negative CRC patients were employed as a training set, and a classification tree was generated by using Biomarker Pattern Software package. The validity of the classification tree was then challenged with a blind test set including another 65 CRC patients. Results. The software identified an average of 46 mass peaks/spectrum and 5 of the identified peaks at m/z 3,104, 3,781, 5,867, 7,970, and 9,290 were used to construct the classification tree. The classification tree separated effectively node-positive CRC patients from node-negative CRC patients, achieving a sensitivity of 94.29% and a specificity of 100.00%. The blind test challenged the model independently with a sensitivity of 91.43% a specificity of 96.67%. Conclusions. The results indicate that SELDI-TOF-MS can correctly distinguish node-positive CRC patients from node-negative ones and show great potential for preoperative screening for regional lymph node involvement of CRC.

Five serum proteins identified using SELDI-TOF-MS as potential biomarkers of gastric cancer

OBJECTIVE

The aims of this study were to detect serum proteomic patterns in gastric cancer serum samples using Surface-enhanced Laser Desorption/ionization-Time-of-flight-Mass Spectrometry ProteinChip array technology, to screen biomarker candidates, to build diagnostic models and to evaluate their clinical significance.

METHODS

Serum samples from patients with gastric cancer and normal healthy control subjects (n = 125) were analysed using surface-enhanced laser desorption/ionization technology. The spectra were generated on weak cation exchange (WCX2) chips, and protein peak clustering and classification analyses were established using Ciphergen Biomarker Wizard and Biomarker Pattern software, respectively. The diagnostic models were developed and validated by discriminant analysis. In addition, the results of the surface-enhanced laser desorption/ionization model were compared with the biomarkers carcinoembryonic antigen and carbohydrate antigen 199 in a subset of samples using a microparticle enzyme immunoassay.

RESULTS

Five protein peaks at 2046, 3179, 1817, 1725 and 1929 m/z were automatically chosen as components of the best biomarker pattern for diagnosis of gastric cancer. In addition, we identified a single protein peak at 4665 m/z, which could distinguish between stage I/II and stage III/IV gastric cancer with a specificity and sensitivity of 91.6% (11/12) and 95.4% (21/22), respectively. When this biomarker was validated in the second set of samples, the specificity and sensitivity were 91.7% (11/12) and 86.3% (19/22), respectively.

CONCLUSIONS

The present results suggest that serum surface-enhanced laser desorption/ionization protein profiling can distinguish patients with gastric cancer, and in particular stage I/II patients, from normal subjects with a relatively high sensitivity and specificity. Surface-enhanced Laser Desorption/ionization-Time-of-flight-Mass Spectrometry is a potential new diagnostic tool for the screening of gastric cancer.

Advances and Perspectives in the Molecular Diagnosis of Head and Neck Cancer

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is a debilitating and lethal disease. Despite significant advances in radiotherapy and surgical management, the 5-year survival rate for head and neck cancer has remained a dismal 50%. Advances in early detection have been made, but to improve patient outcomes better biomarkers and targeted therapeutic agents are needed. Novel biomarkers can improve early detection and provide data to optimize therapeutic strategy and patient survival, and could lead to potentially effective targeted therapies. OBJECTIVE: Report the advances in the discovery of novel biomarkers for HNSCC, and review the potential utility of biomarkers in the molecular diagnosis of HNSCC. METHODS: A review of the English literature (PubMed) from 1980 to 2009. RESULTS/CONCLUSION: Currently the most widely accepted biomarker for HNSCC is high risk HPV status. EGFR is another promising biomarker, however, further research is necessary to determine its prognostic benefit. A large number of promising biomarker candidates are currently being evaluated including epigenetic, expression, and genomic based markers. Studies to validate the sensitivity and specificity of these biomarkers in clinical samples from adequately powered prospective cohorts are needed for successful translation of these findings into potential molecular diagnostic, prognostic, and therapeutic biomarkers for HNSCC.

Functional alterations in the glutathione S-transferase family associated with enhanced occurrence of esophageal carcinoma in China

Glutathione S-transferases (GST) belong to a superfamily of phase II enzymes believed to be associated with enhanced frequency of esophageal carcinoma. This study was performed to evaluate whether the GST family was associated with susceptibility to esophageal carcinoma in China. Ninety-seven patients with newly diagnosed, untreated esophageal squamous-cell carcinoma (ESCC) and 97 healthy controls matched in age, gender, and residence were recruited in this community-based case-control study. Null genotypes of GSTM1 and GSTT1 were determined by multiplex polymerase chain reaction (PCR) technique. Ile105Val polymorphism in the fifth exon, mRNA level, CpG island hypermethylation of promoter, and protein levels of GSTP1 gene were measured with peripheral blood mononuclear cell (PBMC) by PCR-restriction fragment length polymorphism (PCR-RFLP) techniques, quantitative real-time reverse transcription PCR, methylation-specific PCR (MSP), and Western blotting, respectively. The results showed that GSTM1 null genotype and GSTT1 null genotype were significantly associated with increased risk for esophageal cancer in Chinese population. Compared with the control, the relative expression levels of mRNA were significantly reduced in ESCC patients. The conditional logistic regression analysis demonstrated that increased risk for esophageal cancer was associated with CpG island hypermethylation of promoter of GSTP1 gene. GSTP1 protein levels also showed significant decrease in ESCC when adjusted for age, gender, smoking status, and alcohol use. An individual with GSTM1 or GSTT1 null genotype may thus be more susceptible to esophageal cancer development. Reduced expression in mRNA and protein levels were the main manifestations noted in aberrant function of GSTP1 gene. Data thus suggest that the CpG island hypermethylation of promoter gene may serve as a useful biomarker for early diagnosis of esophageal carcinoma development.

Comparative proteomic profiling of 2 muscles from 5 different pure pig breeds using surface-enhanced laser desorption/ionization time-of-flight proteomics technology

The objectives of this study were to evaluate the influence of different pure pig breeds and muscle types on the expression of muscle proteins, as well as their interactions, and second, to find biomarkers for breed and muscle types. A total of 126 male pigs, including 43 Landrace, 21 Duroc, 43 Large White, 13 Pietrain, and 6 Belgian Landrace, were slaughtered at the age of 174 +/- 6 d. Samples from the semimembranosus muscle (SM) and LM were collected 24 h postmortem. Proteomic spectra were generated on an anion exchanger (Q10), a cation exchanger (CM10), and on immobilized metal affinity capture (IMAC30) ProteinChip arrays and analyzed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip techniques. Breed and muscle type did not affect the number of peaks per spectrum but, interestingly, affected the average intensity of the peaks. Of these peaks, a total of 4 proved to be potential protein biomarkers to differentiate LM or SM muscles, and 2 to classify specific breed types. Additionally, several peaks influenced by the interaction between muscle and breed types could correctly classify pig muscles according to their breed. Further studies need to be carried out to validate and identify these potential protein biomarkers for breed and muscle types in finishing pigs.

An integrated LC-ESI-MS platform for quantitation of serum peptide ladders. Application for colon carcinoma study

Mounting evidence indicates that MS analysis of the human blood peptidome allows to distinguish between cancer and non-cancer samples, giving promise for a new MS-based diagnostic tool. However, several aspects of already published work have been criticized and demand for more methodical approach has been formulated. Motivated by this we undertook a systematic study of the plasma and serum peptidome using an integrated ESI-LC-MS-based platform, equipped with new data analysis tools for relative and absolute peptide quantitation. We used a high resolution LC-ESI-MS to analyze well-separated MS signals corresponding to peptides, and measured the variability of >1000 peptide signal amplitudes across a set of plasma and serum samples from healthy individuals. By spiking serum samples with known amounts of isotopically labeled versions of a selected set of peptides we measured the variability of their absolute concentration in this sample set and demonstrated a strong influence of clotting time on the concentration of these peptides in serum. Finally, we used this new LC-ESI-MS analytical platform for the differential analysis of healthy versus colon cancer serum samples and found that it was possible to distinguish the two groups with 89.8% sensitivity and 94.6% specificity.

Searching for Potential Ovarian Cancer Biomarkers with Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Ovarian cancer is a common gynecological malignant disease, causing more deaths among women .The key objective in the treatment of ovarian cancer is early diagnosis. The objective of our study was to seek new ovarian cancer biomarkers based on a serum protein profile with the aim of discriminating ovarian cancer patients from healthy controls. An MB-WCX kit was used to analyze serum samples obtained from 20 ovarian cancer patients and 20 healthy controls and then we generated MALDI-TOF protein profiles from the analysis. After pre-processing of the spectra, linear analysis with ClinProTools bioinformatics software was used to classify protein profiles and search for prominent peaks that could be used as potential ovarian cancer biomarkers. Using ClinproTools bioinformatics and statistical software, we found 5 prominent expressed proteins in the ovarian cancer and healthy control groups. The mass to charge ratio were 4648.21(m/z), 9294.03(m/z), 3886.1(m/z), 9066.38(m/z) and 4254.71(m/z), respectively, and the former four proteins were expressed higher in the ovarian cancer patients, but the later one was expressed at lower levels in the cancer patients. The sensitivity and specificity were both more than 90%. From our study, we found that MALDI-TOF MS is a high-throughput sample preparation method and is a new potential tool for the diagnosis of human disease, not only to search for new early detection biomarkers in the ovarian cancer patients' serum samples, but also with a potential use for routine clinical work.

Circulating and imaging markers for angiogenesis

Abundant preclinical and indirect clinical data have for several decades convincingly supported the notion that anti-angiogenesis is an effective strategy for the inhibition of tumor growth. The recent success achieved in patients with metastatic colon carcinoma using a neutralizing antibody directed against vascular endothelial growth factor (VEGF) has translated preclinical optimism into a clinical reality.With this transformation in the field of angiogenesis has come a need for reliable surrogate markers. A surrogate marker by definition serves as a substitute for the underlying process in question, and in the case of angiogenesis, microvessel density (usually in so-called "hot-spots") has until now been the most widely used parameter. However, this parameter is more akin to a static "snap-shot" and does not lend itself either to the dynamic in situ assessment of the status of the tumor microvasculature or to the molecular factors that regulate its growth and involution. This has led to an acute need for developing circulating and imaging markers of angiogenesis that can be monitored in vivo at repeated intervals in large number of patients with a variety of tumors in a non-invasive manner. Such markers of angiogenesis are the subject of this review.

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.

Update on molecular diagnostic tests in head and neck cancer

Head and neck cancers (HNCs) include several cancers originating in the upper airways that represent a variety of histologies. The most common type of HNC is squamous cell carcinoma (SCC), which is linked to tobacco and alcohol use and to human papilloma virus (HPV). At present, there are no standard molecular tests that are routinely used in clinics. This overview will discuss the current knowledge on molecular markers with the potential to be developed as diagnostic tests for cancer risk assessment, early detection, clinical response prediction to specific therapies, and prognosis. These markers are usually based on recent findings in tumor biology and genetic defects in HNC, and provide information both independently and in combination with currently available clinical parameters. In practice, many potential markers are difficult to measure due to assay variability, lack of standards for the interpretation of assay results, and incomplete knowledge of the effects on disease biology and response to treatment. However, there is great enthusiasm for the general concept of using molecular knowledge for the clinical management of HNC. Although it will be a great challenge to develop robust and reliable molecular diagnostic tests, the development of promising assays fueled by advances in science and technology will continue and will ultimately reach the goal of improving the care of HNC patients.

Identification of lung cancer patients by serum protein profiling using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry

OBJECTIVE

Diagnosis of lung cancer at an early disease stage is important for successful treatment and improving the outcome of patients. To improve its prognosis, we attempted to explore novel tools for screening serum biomarkers to distinguish lung cancer from healthy individuals by serum protein profiles and a classification tree algorithm.

METHODS

Serum samples were applied to metal affinity protein chips to generate mass spectra by surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry. Protein peak identification and clustering were performed using the Biomarker Wizard software. Proteomic spectra of serum samples from 89 lung cancer patients and age- and sex-matched 68 healthy individuals were used as a training set and a classification tree with 3 distinct protein masses was generated by using Biomarker Pattern software. The validity of the classification tree was then challenged with a blind test set including another 62 lung cancer patients and 34 healthy individuals. We additionally determined Cyfra21-1 and carcinoembryonic antigen in all the serum samples included in this study using an electrochemiluminescent immunoassay.

RESULTS

The software identified an average of 48 mass peaks/spectrum and 3 of the identified peaks at 5808, 5971, and 7779 d were used to construct the classification tree. The classification tree separated effectively lung cancer from healthy individuals, achieving a sensitivity of 91% (81 of 89) and a specificity of 97% (66 of 68). The blind test challenged the model with a sensitivity of 89% (55 of 62) and a specificity of 91% (31 of 34), and a positive predictive value of 90% (86 of 96), respectively. The specificity of Cyfra21-1 and the sensitivity provided by Cyfra21-1 and carcinoembryonic antigen used individually or in combination were significantly lower than that of the SELDI marker pattern (P < 0.05 or P < 0.005, respectively).

CONCLUSION

The results suggest that SELDI time-of-flight mass spectrometry technique can correctly distinguish lung cancer patients from healthy individuals and shows great potential for the development of a screening test for the detection of lung cancer.

Role of metalloproteins in the clinical management of head and neck squamous cell carcinoma

Metalloproteins are a group of catalytic proteins, which play significant roles in cell cycle and death. Matrix metalloproteinases (MMPs) are a family of endopeptidases that are capable of digesting extracellular matrix components. They have been implicated in carcinogenesis and recent developments have been made to use MMPs clinically to predict outcomes. In the future, selective inhibition of these proteins and their regulatory pathways may prove useful in anticancer therapeutics. We present a review article on the clinical applications of metalloproteins in head and neck squamous cell carcinoma (HNSCC). Metalopanstimulin is highlighted as a putative metalloprotein of interest for those treating HNSCC. Expression of particular metalloproteins has correlation with lymph node metastasis, tumor invasiveness, and overall prognosis in HNSCC.

Autocrine and paracrine chemokine receptor 7 activation in head and neck cancer: implications for therapy

BACKGROUND

The chemokine receptor 7 (CCR7) mediates survival and invasiveness of metastatic squamous cell carcinoma of the head and neck (SCCHN) to regional lymph nodes. Constitutive prosurvival signaling by the phosphoinositide-3 kinase/Akt pathway has been observed in SCCHN cells independent of epidermal growth factor receptor (EGFR) signaling.

METHODS

Human SCCHN cell lines were treated with agents that block or activate CCR7-mediated signaling, and Akt activation, cell viability in the presence or absence of EGFR inhibition, and cisplatin-induced apoptosis (in the presence or absence of Akt inhibition) were assessed by immunoblotting, the MTT assay, and the detection of annexin V, respectively. Expression and secretion of chemokines by primary tumors, metastatic nodes, and benign nodes of patients with SCCHN were determined by quantitative real-time polymerase chain reaction and enzyme-linked immunosorbent assay, respectively. The role of paracrine activation of CCR7 on tumor growth was analyzed by comparing the growth of orthotopic tumors derived from B7E3 murine oral carcinoma cells in wild-type BALB/c mice, in paucity of lymphoid T cell (plt, deficient in CCL19 and CCL21 expression) mice, and in plt mice in which the implanted B7E3 cells overexpressed CCR7 (n = 14 mice per group).

RESULTS

In the absence of exogenous ligand treatment, blockade of CCR7 signaling reduced levels of phosphorylated (activated) Akt and decreased SCCHN cell viability by up to 59% (95% confidence interval [CI] = 58.2% to 59.8%), enhancing the effect of EGFR inhibition. CCR7 stimulation protected metastatic SCCHN cells from cisplatin-induced apoptosis in an Akt-dependent manner. Metastatic nodes expressed and secreted higher levels of CCL19 than benign nodes or primary tumors. CCR7-positive murine SCCHN tumors grew more slowly in plt mice than in control BALB/c mice (mean average tumor volume on day 20 = 12.2 and 26.5 mm(3), respectively; difference = 14.3 mm(3), 95% CI = 12.3 to 17.1 mm(3)).

CONCLUSIONS

Secretion of CCL19 and CCL21 by SCCHN cells and by paracrine sources combine to promote activation of CCR7 prosurvival signaling associated with tumor progression and disease relapse. CCR7 and its cognate chemokines may be useful biomarkers of SCCHN progression, and blockade of CCR7-mediated signaling may enhance the efficacy of platinum- and EGFR-based therapies.

Use of SELDI-TOF mass spectrometry for identification of new biomarkers: potential and limitations

Surface-enhanced laser desorption time of flight mass spectrometry (SELDI-TOF-MS) is an important proteomic technology that is immediately available for the high throughput analysis of complex protein samples. Over the last few years, several studies have demonstrated that comparative protein profiling using SELDI-TOF-MS breaks new ground in diagnostic protein analysis particularly with regard to the identification of novel biomarkers. Importantly, researchers have acquired a better understanding also of the limitations of this technology and various pitfalls in biomarker discovery. Bearing these in mind, great emphasis must be placed on the development of rigorous standards and quality control procedures for the pre-analytical as well as the analytical phase and subsequent bioinformatics applied to analysis of the data. To avoid the risk of false-significant results studies must be designed carefully and control groups accurately selected. In addition, appropriate tools, already established for analysis of highly complex microarray data, need to be applied to protein profiling data. To validate the significance of any candidate biomarker derived from pilot studies in appropriately designed prospective multi-center studies is mandatory; reproducibility of the clinical results must be shown over time and in different diagnostic settings. SELDI-TOF-MS-based studies that are in compliance with these requirements are now required; only a few have been published so far. In the meantime, further evaluation and optimization of both technique and marker validation strategies are called for before MS-based proteomic algorithms can be translated into routine laboratory testing.

CCL8 is a potential molecular candidate for the diagnosis of graft-versus-host disease

Although graft-versus-host disease (GVHD) is a life-threatening complication of hematopoietic stem-cell transplantation (HSCT), its current diagnosis depends mainly on clinical manifestations and invasive biopsies. Specific biomarkers for GVHD would facilitate early and accurate recognition of this grave condition. Using proteomics, we screened for plasma proteins specific for GVHD in a mouse model. One peak with 8972-Da molecular mass (m/z) retained a discriminatory value in 2 diagnostic groups (GVHD and normal controls) with increased expression in the disease and decreased expression during cyclosporin A treatment, and was barely detectable in syngeneic transplantation. Purification and mass analysis identified this molecule as CCL8, a member of a large chemokine family. In human samples, the serum concentration of CCL8 correlated closely with GVHD severity. All non-GVHD samples contained less than 48 pg/mL (mean +/- SE: 22.5 +/- 5.5 pg/mL, range: 12.6-48.0 pg/mL, n = 7). In sharp contrast, CCL8 was highly up-regulated in GVHD sera ranging from 52.0 to 333.6 pg/mL (mean +/- SE: 165.0 +/- 39.8 pg/mL, n = 7). Strikingly, 2 patients with severe fatal GVHD had extremely high levels of CCL8 (333.6 and 290.4 pg/mL. CCL8 is a promising specific serum marker for the early and accurate diagnosis of GVHD.

Applications of SELDI-MS technology in oncology

Considerable interest, speculation and controversy have been generated utilising surface-enhanced laser desorption/ionization in conjunction with mass spectrometry (SELDI-MS) for the diagnosis, prognosis and therapeutic monitoring of cancer and offers an attractive approach to cancer biomarker discovery from tissues and biological fluids. This technology utilises a combination of mass spectrometry and chromatography to facilitate protein profiling of complex biological mixtures. Compared to some other more traditional proteomic platforms, such as 2D polyacrylamide gel electrophoresis, it has a high-throughput capability and can resolve low-mass proteins. However, a considerable number of challenging issues related to the design of studies, including reproducibility, sensitivity, specificity, variation in sample collection, processing and storage, have been reported as problematic with this technology; albeit some of these concerns could perhaps also be lauded against other proteomic approaches that have attempted to address complex protein mixtures, such as plasma. Applications, successes and limitations of SELDI-MS in both clinical and basic science arenas will be reviewed in this article.

MALDI/SELDI protein profiling of serum for the identification of cancer biomarkers

The ability to visualize the full depth of the serum proteome in a high-throughput manner is a major goal of clinical proteomics. Methodologies, which combine higher throughput with the ability to observe differential protein expression levels, have been applied to this goal. An example of such a system is the coupling of robotic sample processing to matrix-assisted laser desorption time of flight mass spectrometry (MALDI-TOF-MS). Within this paradigm is a modification of MALDI-TOF termed surface-enhanced laser desorption/ionization-TOF (SELDI-TOF). Both conventional MALDI and SELDI have been used to generate protein expression profiles reflective of potential peptide changes in serum. This information can be used to identify proteins, which may enable new diagnostic and therapeutic strategies.

Improving mass spectrometry peak detection using multiple peak alignment results

Mass spectrometry data are often corrupted by noise. It is very difficult to simultaneously detect low-abundance peaks and reduce false-positive peak detection caused by noise. In this paper, we propose to improve peak detection using an additional constraint: the consistent appearance of similar true peaks across multiple spectra. We observe that false -positive peaks in general do not repeat themselves well across multiple spectra. When we align all the identified peaks (including false-positive ones) from multiple spectra together, those false-positive peaks are not as consistent as true peaks. Thus, we propose to use information from other spectra in order to reduce false-positive peaks. The new method improves the detection of peaks over the traditional single spectrum based peak detection methods. Consequently, the discovery of cancer biomarkers also benefits from this improvement. Source code and additional data are available at: http://www.ece.ust.hk/ approximately eeyu/mspeak.htm.

Diagnostic accuracy of MALDI mass spectrometric analysis of unfractionated serum in lung cancer

PURPOSE

There is a critical need for improvements in the noninvasive diagnosis of lung cancer. We hypothesized that matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) analysis of the most abundant peptides in the serum may distinguish lung cancer cases from matched controls.

PATIENTS AND METHODS

We used MALDI MS to analyze unfractionated serum from a total of 288 cases and matched controls split into training (n = 182) and test sets (n = 106). We used a training-testing paradigm with application of the model profile defined in a training set to a blinded test cohort.

RESULTS

Reproducibility and lack of analytical bias was confirmed in quality-control studies. A serum proteomic signature of seven features in the training set reached an overall accuracy of 78%, a sensitivity of 67.4%, and a specificity of 88.9%. In the blinded test set, this signature reached an overall accuracy of 72.6 %, a sensitivity of 58%, and a specificity of 85.7%. The serum signature was associated with the diagnosis of lung cancer independently of gender, smoking status, smoking pack-years, and C-reactive protein levels. From this signature, we identified three discriminatory features as members of a cluster of truncated forms of serum amyloid A.

CONCLUSIONS

We found a serum proteomic profile that discriminates lung cancer from matched controls. Proteomic analysis of unfractionated serum may have a role in the noninvasive diagnosis of lung cancer and will require methodological refinements and prospective validation to achieve clinical utility.

Optimization of MALDI-TOF MS detection for enhanced sensitivity of affinity-captured proteins spanning a 100 kDa mass range

Analysis of complex biological samples by MALDI-TOF mass spectrometry has been generally limited to the detection of low-mass protein (or protein fragment) peaks. We have extended the mass range of MALDI-TOF high-sensitivity detection by an order of magnitude through the combined optimization of instrument parameters, data processing, and sample preparation procedures for affinity capture. WCX, C3, and IMAC magnetic beads were determined to be complementary and most favorable for broad mass range protein profiling. Key instrument parameters for extending mass range included adjustment of the ADC offset and preamplifier filter values of the TOF detector. Data processing was improved by a combination of constant and quadratic down-sampling, preceded by exponential baseline subtraction, to increase sensitivity of signal peaks. This enhancement in broad mass range detection of protein signals will be of direct benefit in MS expression profiling studies requiring full linear range mass detection.

SELDI protein profiling of dunning R-3327 derived cell lines: identification of molecular markers of prostate cancer progression

BACKGROUND

We recently demonstrated the protein expression profiling of Dunning rat tumor cell lines of varying metastatic potential (G (0%), AT-1 ( approximately 20%), and MLL (100%)) using SELDI-TOF-MS. As a parallel effort, we have been pursuing the identification of the protein(s) comprising the individual discriminatory "peaks" and evaluating their utility as potential biomarkers for prostate cancer progression.

METHODS

To identify the observed SELDI-TOF-MS m/z (mass/charge) values with discriminatory expression between different sublines, we employed a combination of chemical pre-fractionation, liquid chromatography, gel electrophoresis and tandem mass spectroscopy. Identified proteins were then verified by immuno-assay and Western analysis.

RESULTS

A 17.5 K m/z SELDI-TOF-MS peak was found to retain discriminatory value in each of two separate study-sets with an increased expression in the metastatic MLL line. Sequence identification and subsequent immunoassays verified that Histone H2B is the observed 17.5 K m/z SELDI peak. SELDI-based immuno-assay and Western Blotting revealed that Histone H2B is specifically over-expressed in metastatic MLL lines.

CONCLUSIONS

SELDI-TOF MS analysis of the Dunning prostate cancer cell lines confirmed the consistent overexpression of a 17.5 K m/z peak in metastatic MLL subline. The 17.5 kDa protein from MLL has been isolated and identified as Histone H2B.

Classification of pancreatic cystic lesions using SELDI-TOF mass spectrometry

BACKGROUND

The diagnosis of pancreatic cystic lesions is problematical with difficulties arising in the differentiation between malignant, premalignant or benign lesions. This preliminary study aimed to analyse pancreatic cyst fluid, using a proteomic approach, to generate reproducible protein profiles to assist in the classification of malignant and non-carcinoma samples.

METHODS

Pancreatic cyst fluid samples from patients with pancreatic adenocarcinoma and non-carcinoma cystic lesions were analysed on hydrophobic protein chip arrays by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS).

RESULTS

Differential protein expression profiles were observed between pancreatic adenocarcinoma and non-carcinoma cyst fluid samples using SELDI-TOF MS, with 12 protein peaks differentially expressed between pancreatic adenocarcinoma and non-carcinoma. Additionally, unique patterns were observed between the different subtypes of non-carcinoma samples as well as malignant adenocarcinoma.

CONCLUSIONS

In this preliminary study we used SELDI-TOF MS to identify protein expression profiles of pancreatic cyst fluid, showing a potential to aid in the differential diagnosis of pancreatic cystic lesions.

Sample preparation for serum/plasma profiling and biomarker identification by mass spectrometry

In this article, we present an overview of the different strategies for sample preparation for identification by mass spectrometry (MS) of biomarkers from serum and/or plasma. We consider the effects of the variables involved in sample collection, handling and storage, and describe different approaches for removal of high abundance proteins and serum/plasma fractionation. We review the advantages and disadvantages of such techniques as centrifugal ultrafiltration, different formats for solid phase extraction, organic solvent extraction, gel and capillary electrophoresis, and liquid chromatography. We also discuss a variety of current proteomic methods and their main applications for biomarker-related studies.

Bioinformatics approaches in clinical proteomics

Protein expression profiling is increasingly being used to discover, validate and characterize biomarkers that can potentially be used for diagnostic purposes and to aid in pharmaceutical development. Correct analysis of data obtained from these experiments requires an understanding of the underlying analytic procedures used to obtain the data, statistical principles underlying high-dimensional data and clinical statistical tools used to determine the utility of the interpreted data. This review summarizes each of these steps, with the goal of providing the nonstatistician proteomics researcher with a working understanding of the various approaches that may be used by statisticians. Emphasis is placed on the process of mining high-dimensional data to identify a specific set of biomarkers that may be used in a diagnostic or other assay setting.

Opportunities and limitations of SELDI-TOF-MS in biomedical research: practical advices

Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry, or surface-enhanced laser desorption/ionization ProteinChip technology, has been widely used in obtaining the quantitative profiles of tissue proteomes, particularly plasma proteomes. Its high-throughput nature and simplicity in its experimental procedures have allowed this technology to become a popular research tool for biomarker discovery in the past 5 years. After accumulating more research experiences, researchers now have a better understanding of the characteristics and limitations of this technology, as well as the pitfalls in biomarker research, by undertaking a comparative proteomic approach. This review provides an overview of the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry, discusses its limitations and provides some possible solutions to help apply this technology to biomarker research.

Annotated regions of significance of SELDI-TOF-MS spectra for detecting protein biomarkers

Peak detection is a key step in the analysis of SELDI-TOF-MS spectra, but the current default method has low specificity and poor peak annotation. To improve data quality, scientists still have to validate the identified peaks visually, a tedious and time-consuming process, especially for large data sets. Hence, there is a genuine need for methods that minimize manual validation. We have previously reported a multi-spectral signal detection method, called RS for 'region of significance', with improved specificity. Here we extend it to include a peak quantification algorithm based on annotated regions of significance (ARS). For each spectral region flagged as significant by RS, we first identify a dominant spectrum for determining the number of peaks and the m/z region of these peaks. From each m/z region of peaks, a peak template is extracted from all spectra via the principal component analysis. Finally, with the template, we estimate the amplitude and location of the peak in each spectrum with the least-squares method and refine the estimation of the amplitude via the mixture model. We have evaluated the ARS algorithm on patient samples from a clinical study. Comparison with the standard method shows that ARS (i) inherits the superior specificity of RS, and (ii) gives more accurate peak annotations than the standard method. In conclusion, we find that ARS alleviates the main problems in the preprocessing of SELDI-TOF spectra. The R-package ProSpect that implements ARS is freely available for academic use at http://www.meb.ki.se/ yudpaw.