SELDI-TOF MS profiling of plasma proteins in ovarian cancer

Influence of honeybee sting on peptidome profile in human serum

The aim of this study was to explore the serum peptide profiles from honeybee stung and non-stung individuals. Two groups of serum samples obtained from 27 beekeepers were included in our study. The first group of samples was collected within 3 h after a bee sting (stung beekeepers), and the samples were collected from the same person a second time after at least six weeks after the last bee sting (non-stung beekeepers). Peptide profile spectra were determined using MALDI-TOF mass spectrometry combined with Omix, ZipTips and magnetic beads based on weak-cation exchange (MB-WCX) enrichment strategies in the mass range of 1–10 kDa. The samples were classified, and discriminative models were established by using the quick classifier, genetic algorithm and supervised neural network algorithms. All of the statistical algorithms used in this study allow distinguishing analyzed groups with high statistical significance, which confirms the influence of honeybee sting on the serum peptidome profile. The results of this study may broaden the understanding of the human organism’s response to honeybee venom. Due to the fact that our pilot study was carried out on relatively small datasets, it is necessary to conduct further proteomic research of the response to honeybee sting on a larger group of samples.

Advances in Proteomic Technologies and Its Contribution to the Field of Cancer

Systematic studies of the cancer genome have generated a wealth of knowledge in recent years. These studies have uncovered a number of new cancer genes not previously known to be causal targets in cancer. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies are not widely available for most cancers. Precision care plans still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics is continuing to make major strides in the discovery of fundamental biological processes as well as more recent transition into an assay platform capable of measuring hundreds of proteins in any biological system. As such, proteomics can translate basic science discoveries into the clinical practice of precision medicine. The proteomic field has progressed at a fast rate over the past five years in technology, breadth and depth of applications in all areas of the bioscience. Some of the previously experimental technical approaches are considered the gold standard today, and the community is now trying to come to terms with the volume and complexity of the data generated. Here I describe contribution of proteomics in general and biological mass spectrometry in particular to cancer research, as well as related major technical and conceptual developments in the field.

The value of surface enhanced laser desorption/ionization-time of flight mass spectrometry at the diagnosis of non-small cell lung cancer: a systematic review

Numbers of studies used surface enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS) to find novel serum biomarkers for non-small cell lung cancer (NSCLC). It is arguable whether the SELDI technique has its value of diagnostic accuracy for NSCLC. The purpose of our study is to determine the diagnostic accuracy of SELDI-TOF-MS for diagnosing NSCLC. The Cochrane Central Register of Controlled Trials, MEDLINE, Pub Med, EMBASE, the Chinese Biomedical Literature Database, the China Academic Journals Full-text Database, and the Chinese Scientific Journals Database were searched systematically for potential studies. Reference lists of included studies and review articles were also reviewed. All studies that reported data on patients with a confirmed diagnosis of NSCLC and that compared the measurement of SELDI-TOF-MS with pathology standard were considered for inclusion. 11 studies were included in the systematic review. The ranges of the diagnostic value of SELDI-TOF-MS for NSCLC were as follows: sensitivity (SEN) was 0.70~1.00; specificity (SPE) was 0.68~1.00; positive likelihood ratio (PLR) was 2.23~23.14; negative likelihood ratio (NLR) was 0.04~0.43; and diagnostic odds ratio (DOR) was 5.17~621.0, respectively. SELDI-TOF-MS showed high accuracy in identifying NSCLC, and could be a potential screening tool for diagnosing NSCLC patients.

Detection of serum protein biomarkers by surface enhanced laser desorption/ionization in patients with adenocarcinoma of the lung

AIM

Early diagnosis of lung cancer is important for successful treatment and improving the outcome of patients. We explored novel tools for screening serum biomarkers to distinguish adenocarcinoma of the lung from healthy controls by serum protein profiles.

METHODS

Serum samples were taken from 31 patients with adenocarcinoma of the lung and 31 healthy controls, matched for age, sex and smoking status. Serum samples were applied to strong anion 2(SAX-2) protein chips to generate mass spectra by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Protein peak identification and clustering were performed using Biomarker Wizard, compared by MATLAB 7.5 and a classification tree was constructed using R weka software. The validity of the classification tree was then challenged with a blind test.

RESULTS

The software identified 102 peaks and m/z 14022.9 and m/z 3735.99 was used to construct a classification tree. The classification tree effectively separated adenocarcinoma of lung patients from healthy controls, achieving a validity of 100%. The blind test challenged the model with a sensitivity of 100% and a specificity of 100%.

CONCLUSION

The results suggested that the SELDI-TOF-MS technique can correctly distinguish adenocarcinoma of lung patients from healthy controls and showed great potential for development as a screening test for the detection of lung cancer.

Potential role of proteomics in the diagnosis of lymphoma: a meta-analysis

Surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF-MS) has been approved for identifying biomarkers and diagnosing many diseases such as lymphomas. It is arguable whether the SELDI technique has its value of diagnostic accuracy for lymphomas. The purpose of our study is to determine the diagnostic accuracy of SELDI-TOF-MS for diagnosing lymphomas. The Cochrane Central Register of Controlled Trials, MEDLINE, Pub Med, EMBASE, the Chinese Biomedical Literature Database, the China Academic Journals Full-text Database, and the Chinese Scientific Journals Database were searched systematically for potential studies. Reference lists of included studies and review articles were also reviewed. All studies that reported data on patients with a confirmed diagnosis of lymphomas and that compared the measurement of SELDI-TOF-MS with pathology standard were considered for inclusion. Eleven studies were included in the systematic review. The ranges of the diagnostic value of SELDI-TOF-MS for lymphoma were as follows: sensitivity (SEN) was 0.69-0.96; specificity (SPE) was 0.70-1.00; positive likelihood ratio (PLR) was 2.99-96.09; negative likelihood ratio (NLR) was 0.04-0.35; and diagnostic odds ratio (DOR) was 18.13-1250.71, respectively. Further, we analysed serum samples as a subgroup, and the pooled endpoints were as follows: pooled SEN was 0.89 (0.85-0.91); pooled SPE was 0.91 (0.88-0.93); pooled PLR was 12.35 (5.36-28.44); pooled NLR was 0.13 (0.09-0.20); and pooled DOR was 101.04 (39.57-258.04), respectively. SELDI-TOF-MS showed high accuracy in identifying lymphoma and could be a useful screening tool for diagnosing lymphoma patients.

Molecular biology techniques for the surgeon

New technologies are constantly being introduced into the medical and surgical fields. These technologies come in the form of newer medicines, imaging methods and prognostic tools, among others, and allow clinicians to make more rational and informed decisions on the care of their patients. Many of these technologies utilize advanced techniques which are at the forefront of many research fields and represent a transition of bench advances into the clinical realm. This review will highlight four technologies that are at the forefront in the treatment of oncology patients treated by surgeons on a daily basis. Circulating tumor cells, microarray analysis, proteomic studies and rapid sequencing technologies will be highlighted. These technologies will be reviewed and their potential use in the care of surgical patients will be discussed.

Reproducibility of mass spectrometry based protein profiles for diagnosis of ovarian cancer across clinical studies: A systematic review

The focus of this systematic review is to give an overview of the current status of clinical protein profiling studies using MALDI and SELDI MS platforms in the search for ovarian cancer biomarkers. A total of 34 profiling studies were qualified for inclusion in the review. Comparative analysis of published discriminatory peaks to peaks found in an original MALDI MS protein profiling study was made to address the key question of reproducibility across studies. An overlap was found despite substantial heterogeneity between studies relating to study design, biological material, pre-analytical treatment, and data analysis. About 47% of the peaks reported to be associated to ovarian cancer were also represented in our experimental study, and 34% of these redetected peaks also showed a significant difference between cases and controls in our study. Thus, despite known problems related to reproducibility an overlap in peaks between clinical studies was demonstrated, which indicate convergence toward a set of common discriminating, reproducible peaks for ovarian cancer. The potential of the discriminating protein peaks for clinical use as ovarian cancer biomarkers will be discussed and evaluated. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Application of SELDI-TOF-MS and LCM to screen protein markers for early diagnosis of liver metastasis of colorectal carcinoma

AIM: To screen protein markers for liver metastases of colorectal cancer using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry protein chip (SELDI-TOF-MS) in combination with laser capture microdissection (LCM) technology.

METHODS: Normal colorectal cells, primary tumor cells and liver metastatic cells were obtained from 24 colorectal cancer patients with liver metastases using the LCM technology. Protein profiling was performed using SELDI-TOF-MS technology. Differentially expressed proteins were analyzed using Biomarker Wizard software and identified by querying the database.

RESULTS: Fifteen differentially expressed proteins were found between primary tumor cells and normal colorectal cells, of which 12 were up-regulated and 3 down-regulated. Nine differentially expressed proteins were found between liver metastatic cells and primary tumor cells, of which 5 were up-regulated and 4 down-regulated. Twenty differentially expressed proteins were identified by querying ExPasy protein database, including integral membrane protein 2C, DNA repair protein RAD51 homolog 4, cell cycle checkpoint protein RAD1, human epididymis protein 4, centromere protein R, and pleckstrin homology domain family member 3. Apoptosis regulator Bax-γ, S100A11, Raf kinase inhibitor protein (RKIP) and heat shock protein 27 (HSP-27) displayed most obvious differential expression among normal colorectal cells, primary tumor cells and liver metastatic cells (all P < 0. 01).

CONCLUSION: SELDI-TOF-MS technology combined with LCM may allow to screen highly sensitive and specific protein markers for colorectal cancer and liver metastases of colorectal cancer.

Proteomic analysis reflects different histologic subtypes of epithelial ovarian cancer

Ovarian carcinoma is a significant cause of cancer mortality in women worldwide. As a heterogeneous disease, distinct clinical and molecular characteristics exist among different histologic subtypes. With the developments in proteomics, surfaced-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is sensitive enough to detect minute quantity of proteins from serum or microdissected cryostat sections. Herein we hypothesized that differentially expressed protein profiles exist in ovarian carcinomas with distinct histologic subtypes. Compared with endometrioid carcinoma, two peaks were significantly higher in serous carcinoma with the m/z of 3622 Da and 4778 Da, reinforcing the need to treat different histologic subtypes of ovarian cancer as different disease entities. Better understanding of these potential diagnostic and therapeutic biomarkers followed with proof-of-target effect will finally contribute to rational combinations of novel therapy and improve individual ovarian cancer patient outcome.

The application of SELDI-TOF-MS in clinical diagnosis of cancers

Cancer diagnosis is important, and the early diagnosis of cancers could predict a more successful treatment. The proteomic studies emerged to be useful in combined analyses of samples from patients and provide more accurate diagnosis when compared to the single-factor-based diagnosis. In recent years, cancer detection with surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF MS) is flourishing and brought significant progress in this area. This paper summarizes some recent results with this technique for cancer diagnosis.

Proteomics and biomarkers for ovarian cancer diagnosis

Ovarian cancer remains a leading cause of death from gynecological malignancy. Early diagnosis is the most important determinant of survival. Current diagnostic tools have had very limited success in early detection. In recent years, the advancing techniques for proteomics have accelerated the discovery of ovarian cancer biomarkers. Numerous proteomics-based molecular biomarkers/panels have been identified and hold great potential for diagnostic applications, but they need further development and validation. This article reviews recently published data on the diagnosis of ovarian cancer with proteomics, including the major proteomics technologies and promising strategies for biomarker discovery and development.

Mass spectrometry based proteomics profiling as diagnostic tool in oncology: current status and future perspective

Proteomics analysis has been heralded as a novel tool for identifying new and specific biomarkers that may improve diagnosis and monitoring of various disease states. Recent years have brought a number of proteomics profiling technologies. Although proteomics profiling has resulted in the detection of disease-associated differences and modification of proteins, current proteomics technologies display certain limitations that are hampering the introduction of these new technologies into clinical laboratory diagnostics and routine applications. In this review, we summarize current advances in mass spectrometry based biomarker discovery. The promises and challenges of this new technology are discussed with particular emphasis on diagnostic perspectives of mass-spectrometry based proteomics profiling for malignant diseases.

New potential biomarkers in the diagnosis of esophageal squamous cell carcinoma

OBJECTIVE

To analyse the alterations of serum proteins in cases of esophageal squamous cell carcinoma (ESCC) in order to screen and validate serum marker patterns for the diagnosis of ESCC in the high-risk populations of Xinjiang, China.

METHODS

The serum proteomic patterns of 188 cases, including 139 patients with ESCC (54 Uygur, 45 Kazakh and 40 Han subjects) and 49 sex- and age-matched healthy controls, were detected using the SELDI-TOF-MS (surface-enhanced laser desorption/ionization-time of flight-mass spectrometry) technology with the CM10 ProteinChip. Differences in protein peaks between patients with ESCC and controls were analysed using the Biomarker Pattern Software, and a primary diagnosis model of ESCC was developed and validated with SVM (support vector machines). This model was further evaluated by a large-scale blind test.

RESULTS

Two hundred and eighty-three protein peaks were detected within the molecular range of 0-20 kDa, among which, 140 peaks were significantly different between ESCC cases and controls (p < 0.05). A diagnostic pattern consisting of six protein peaks (m/z 5667, 5709, 5876, 5979, 6043 and 6102) was established with a sensitivity of 97.12% and a specificity of 83.87%. The large-scale blind test generated a sensitivity of 91.43% and a specificity of 88.89%.

CONCLUSIONS

The differential protein peaks analysed by SELDI-TOF-MS may contain promising serum biomarkers for screening ESCC. The diagnostic model which combined only six protein peaks had a satisfactory discriminatory power. The model should be further evaluated in other populations of ESCC patients and tested against controls. The nature and function of the discriminating proteins have yet to be elucidated.

Proteomics and cancer epidemiology

Profiling of differentially expressed proteins is perhaps the most important and useful approach in developing tools for risk assessment in a population, diagnostic screening, and therapeutics. Proteomic markers have potential for identifying individuals at high risk of developing cancer; however, these markers have not been extensively used in cancer epidemiologic studies. Several markers have to be clinically validated. In this chapter, methods used in proteomic analysis of clinical samples, challenges in the proteomics and cancer epidemiology, and their potential solutions are discussed.