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

Recent Contributions of Mass Spectrometry-Based "Omics" in the Studies of Breast Cancer

Breast cancer (BC) is one of the most heterogeneous groups of cancer. As every biotype of BC is unique and presents a particular "omic" signature, they are increasingly characterized nowadays with novel mass spectrometry (MS) strategies. BC therapeutic approaches are primarily based on the two features of human epidermal growth factor receptor 2 (HER2) and estrogen receptor (ER) positivity. Various strategic MS implementations are reported in studies of BC also involving data independent acquisitions (DIAs) of MS which report novel differential proteomic, lipidomic, proteogenomic, phosphoproteomic, and metabolomic characterizations associated with the disease and its therapeutics. Recently many "omic" studies have aimed to identify distinct subsidiary biotypes for diagnosis, prognosis, and targets of treatment. Along with these, drug-induced-resistance phenotypes are characterized by "omic" changes. These identifying aspects of the disease may influence treatment outcomes in the near future. Drug quantifications and characterizations are also done regularly and have implications in therapeutic monitoring and in drug efficacy assessments. We report these studies, mentioning their implications toward the understanding of BC. We briefly provide the MS instrumentation principles that are adopted in such studies as an overview with a brief outlook on DIA-MS strategies. In all of these, we have chosen a model cancer for its revelations through MS-based "omics".

Urinalysis of individuals with renal hyperfiltration using ATR-FTIR spectroscopy

Abnormal increased glomerular filtration rate (GFR), otherwise known as renal hyperfiltration (RHf), is associated with an increased risk of chronic kidney disease and cardiovascular mortality. Although it is not considered as a disease alone in medicine today, early detection of RHf is essential to reducing risk in a timely manner. However, detecting RHf is a challenge since it does not have a practical biochemical marker that can be followed or quantified. In this study, we tested the ability of ATR-FTIR spectroscopy to distinguish 17 individuals with RHf (hyperfiltraters; RHf (+)), from 20 who have normal GFR (normofiltraters; RHf(-)), using urine samples. Spectra collected from hyperfiltraters were significantly different from the control group at positions 1621, 1390, 1346, 933 and 783/cm. Intensity changes at these positions could be followed directly from the absorbance spectra without the need for pre-processing. They were tentatively attributed to urea, citrate, creatinine, phosphate groups, and uric acid, respectively. Using principal component analysis (PCA), major peaks of the second derivative forms for the classification of two groups were determined. Peaks at 1540, 1492, 1390, 1200, 1000 and 840/cm were significantly different between the two groups. Statistical analysis showed that the spectra of normofiltraters are similar; however, those of hyperfiltraters show diversity at multiple positions that can be observed both from the absorbance spectra and the second derivative profiles. This observation implies that RHf can simultaneously affect the excretion of many substances, and that a spectroscopic analysis of urine can be used as a rapid and non-invasive pre-screening tool.

Understanding Cervical Cancer through Proteomics

Cancer is one of the leading public health issues worldwide, and the number of cancer patients increases every day. Particularly, cervical cancer (CC) is still the second leading cause of cancer death in women from developing countries. Thus, it is essential to deepen our knowledge about the molecular pathogenesis of CC and propose new therapeutic targets and new methods to diagnose this disease in its early stages. Differential expression analysis using high-throughput techniques applied to biological samples allows determining the physiological state of normal cells and the changes produced by cancer development. The cluster of differential molecular profiles in the genome, the transcriptome, or the proteome is analyzed in the disease, and it is called the molecular signature of cancer. Proteomic analysis of biological samples of patients with different grades of cervical intraepithelial neoplasia (CIN) and CC has served to elucidate the pathways involved in the development and progression of cancer and identify cervical proteins associated with CC. However, several cervical carcinogenesis mechanisms are still unclear. Detecting pathologies in their earliest stages can significantly improve a patient's survival rate, prognosis, and recurrence. The present review is an update on the proteomic study of CC.

Psoralen Derivatives with Enhanced Potency

Psoralen is a furocoumarin natural product that intercalates within DNA and forms covalent adducts when activated by ultraviolet radiation. It is well known that this property contributes to psoralen's clinical efficacy in several disease contexts, which include vitiligo, psoriasis, graft-versus-host disease and cutaneous T-cell lymphoma. Given the therapeutic relevance of psoralen and its derivatives, we attempted to synthesize psoralens with even greater potency. In this study, we report a library of 73 novel psoralens, the largest collection of its kind. When screened for the ability to reduce cell proliferation, we identified two derivatives even more cytotoxic than 4'-aminomethyl-4,5',8-trimethylpsoralen (AMT), one of the most potent psoralens identified to date. Using MALDI-TOF MS, we studied the DNA adduct formation for a subset of novel psoralens and found that in most cases enhanced DNA binding correlated well with cytotoxicity. Generally, our most potent derivatives contain positively charged substituents, which we believe increase DNA affinity and enhance psoralen intercalation. Thus, we provide a rational approach to guide efforts toward further optimizing psoralens to fully capitalize on this drug class' therapeutic potential. Finally, the structure-activity insights we have gained shed light on several opportunities to study currently underappreciated aspects of psoralen's mechanism.

Proteomic investigations into resistance in colorectal cancer

Introduction: Despite advances in screening and treatment options, colorectal cancer (CRC) remains one of the most prevalent and lethal cancer subtypes. Resistance to cytotoxic or targeted therapy has remained a constant challenge to the treatment and long-term management of patients, attracting intense worldwide investigation since the 1950s. Through extensive investigations into the proteomic mechanisms and functions that convey resistance to therapy/s, researchers have become able to implicate alterations in several signaling pathways that provide and sustain resistance to treatment.Areas covered: In this review, we summarize how protein alterations are associated with resistance to therapy, with particular emphasis on CRC. An overview of the mechanisms of therapeutic resistance is described, highlighting recent studies which endeavor to elucidate the proteomic changes that are associated with the acquisition and promulgation of therapeutic resistance.Expert opinion: While cancers such as CRC have been intensively studied for decades, unresponsiveness and the resistance to therapy remain critical obstacles in the treatment of patients. Due to the inherent biological and clinical heterogeneity of individual CRCs, proteomic methods stand to become powerful tools to provide biological insights that may guide therapeutic strategies with the ultimate goal of refining emergent immunotherapeutic treatments.

The Relevance of Mass Spectrometry Analysis for Personalized Medicine through Its Successful Application in Cancer "Omics"

Mass spectrometry (MS) is an essential analytical technology on which the emerging omics domains; such as genomics; transcriptomics; proteomics and metabolomics; are based. This quantifiable technique allows for the identification of thousands of proteins from cell culture; bodily fluids or tissue using either global or targeted strategies; or detection of biologically active metabolites in ultra amounts. The routine performance of MS technology in the oncological field provides a better understanding of human diseases in terms of pathophysiology; prevention; diagnosis and treatment; as well as development of new biomarkers; drugs targets and therapies. In this review; we argue that the recent; successful advances in MS technologies towards cancer omics studies provides a strong rationale for its implementation in biomedicine as a whole.

An efficient biomarker panel for diagnosis of breast cancer using surface-enhanced laser desorption ionization time-of-flight mass spectrometry

Breast cancer (BC) is the most frequently diagnosed cancer that affects women worldwide. Early detection of BC is important to improve survival rates and decrease mortality. The aim of the present study was to investigate serum biomarkers using surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to distinguish patients with BC from the healthy population and patients with benign breast diseases (BBDs). A total of 62 patients with invasive ductal carcinoma, as confirmed by histopathology, and 47 non-cancerous individuals (NCIs) [16 healthy controls (HCs) and 31 patients with BBD] were enrolled in the present study. Serum protein profiles were determined by SELDI-TOF-MS using an immobilized metal affinity capture array. Serum from patients with BC were compared with that from the HC group using univariate and multivariate statistical analyses. A total of 118 clusters were generated from the individual serum. Univariate analysis revealed that 5 peaks were significantly downregulated (m/z 1,452, 2,670, 3,972, 5,354 and 5,523; P<0.001) and 4 were upregulated (m/z 6,850, 7,926, 8,115 and 8,143; P<0.001) in patients with BC compared with the HC group. A comparison of patients with BC and patients with BBD revealed an additional 9 protein peaks. Among these, 3 peaks (m/z 3,972, 5,336 and 11,185) were significantly downregulated and 6 peaks (m/z 4,062, 4,071, 4,609, 6,850, 8,115 and 8,133) were significantly upregulated. A total of 3 peaks [mass-to-change ratio (m/z) 3,972, 6,850 and 8,115 (BC2)] were common in both sets. The results of the present study suggest that a 4 protein peak set [m/z 3,972, 6,850 and 8,115 (BC2) and 8,949 (BC3)] could be used to distinguish patients with BC from NCI.

Identification of Apolipoprotein C-I Peptides as a Potential Biomarker and its Biological Roles in Breast Cancer

Background

Breast cancer (BC) is one of the most common cancers and is among the main causes of death in females around the world. Although several serum biomarkers have been identified for breast cancer, due to lack of adequate sensitivity and specificity they do not adequately distinguish BC from confounding conditions. New approaches are urgently needed to improve BC detection and treatment.

Material/Methods

Eighty serum samples from 20 healthy individuals and 60 patients with BC (22 triple-negative breast cancer, TNBC; 38 non-triple-negative breast cancer, NTNBC) were included. Protein profiling of serum samples was analyzed using surface-enhanced laser desorption/ionization time-of-flight mass spectroscopy (SELDI-TOF-MS). Candidate biomarkers were purified by SDS-PAGE electrophoresis and identified by MALDI-TOF/TOF.

Results

The candidate biomarker positioned at 6447.9 m/z was significantly decreased in BC patients. Moreover, the expression intensity of the candidate biomarker was weaker in the TNBC and pre-surgery group compared with the NTNBC and post-surgery group. We ultimately identified the biomarker as apolipoprotein C-I (ApoC-I). Furthermore, we found that ApoC-I peptides inhibited proliferation of human breast cancer cells in vitro and suppressed tumor growth in vivo.

Conclusions

These results suggest that ApoC-I peptides may be a potential diagnostic biomarker and therapeutic approach for BC.

Development of a test to identify bladder cancer in the urine of patients using mass spectroscopy and subcellular localization of the detected proteins

The survival rate for bladder cancer is much better when the disease is detected early, so improvements in methodology for early detection would be beneficial. When urine contains neoplastic urothelial cells, it carries biomarkers of the disease. This study aims to develop a test for the detection of urothelial carcinoma in the urine. The sediments from urines of ten patients with carcinoma and ten randomly selected normal controls were tested for cancer biomarkers using high-resolution mass spectroscopy. 212 unique individual proteins were identified. Most of them occurred only once or twice in the entire cohort of cases. When sorting the detected proteins by their subcellular compartments, we were able to develop a test that differentiates between the two sets. When the combination of nuclear and red blood cell proteins was used as the discriminating function, the level of statistical significance was p=0.003, the sensitivity was 90%, the specificity 67% and the area under the Receiver-Operating Characteristic curve (ROC) was 94%. When the lack of any detectible proteins, which includes nuclear proteins, was included as a criterion indicating benign urine, the specificity increased to 80%. This use of cellular compartment localization of the detected proteins in the discriminating function is less restrictive than requiring the presence of specific proteins, and we were able to develop a screening test with this less stringent criterion. This approach can be applied to other tumors, such as breast, lung and colon cancers, where the need for a simple screening test is even greater.

A Review: Proteomics in Nasopharyngeal Carcinoma

Although radiotherapy is generally effective in the treatment of major nasopharyngeal carcinoma (NPC), this treatment still makes approximately 20% of patients radioresistant. Therefore, the identification of blood or biopsy biomarkers that can predict the treatment response to radioresistance and that can diagnosis early stages of NPC would be highly useful to improve this situation. Proteomics is widely used in NPC for searching biomarkers and comparing differentially expressed proteins. In this review, an overview of proteomics with different samples related to NPC and common proteomics methods was made. In conclusion, identical proteins are sorted as follows: Keratin is ranked the highest followed by such proteins as annexin, heat shock protein, 14-3-3σ, nm-23 protein, cathepsin, heterogeneous nuclear ribonucleoproteins, enolase, triosephosphate isomerase, stathmin, prohibitin, and vimentin. This ranking indicates that these proteins may be NPC-related proteins and have potential value for further studies.

Biomarker Characterization by MALDI-TOF/MS

Mass spectrometric techniques frequently used in clinical diagnosis, such as gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, ambient ionization mass spectrometry, and matrix-assisted laser desorption ionization/time-of-flight mass spectrometry (MALDI-TOF/MS), are discussed. Due to its ability to rapidly detect large biomolecules in trace amounts, MALDI-TOF/MS is an ideal tool for characterizing disease biomarkers in biologic samples. Clinical applications of MS for the identification and characterization of microorganisms, DNA fragments, tissues, and biofluids are introduced. Approaches for using MALDI-TOF/MS to detect various disease biomarkers including peptides, proteins, and lipids in biological fluids are further discussed. Finally, various sample pretreatment methods which improve the detection efficiency of disease biomarkers are introduced.

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.

MALDI-TOF MS as evolving cancer diagnostic tool: a review

Recent developments in mass spectrometry have introduced clinical proteomics to the forefront of diseases diagnosis, offering reliable, robust and efficient analytical method for biomarker discovery and monitoring. MALDI-TOF is a powerful tool for surveying proteins and peptides comprising the realm for clinical analysis. MALDI-TOF has the potential to revolutionize cancer diagnostics by facilitating biomarker discovery, enabling tissue imaging and quantifying biomarker levels. Healthy (control) and cancerous tissues can be analyzed on the basis of mass spectrometry (MALDI-TOF) imaging to identify cancer-specific changes that may prove to be clinically useful. We review MALDI-TOF profiling techniques as tools for detection of cancer biomarkers in various cancers. We mainly discuss recent advances including period from 2011 to 2013.

Omic-profiling in breast cancer metastasis to bone: implications for mechanisms, biomarkers and treatment

Despite well-recognised advances in breast cancer treatment, there remain substantial numbers of patients who develop metastatic disease, of which up to 70% involves spread to bone, resulting in skeletal complications which have a major negative impact on mortality and quality of life. Bisphosphonates and newer bone-targeted agents have reduced the prevalence of skeletal complications, yet there remains significant unmet clinical need, particularly for the development of more specific therapies for the prevention and treatment of metastatic bone disease, for the prediction of risk of its development in individual patients and for the prediction of response to treatments. Modern 'omic' strategies can potentially make a major contribution to meeting this need. Technological advances in the field of nucleic acid sequencing, mass spectrometry and metabolic profiling have driven progress in genomics, transcriptomics (functional genomics), proteomics and metabolomics. This review appraises the recent application of these approaches to studies of breast cancer metastasis (particularly to bone), with a focus on understanding how omic approaches may lead to new therapeutic options and to novel biomarker molecules or molecular signatures with potential value in clinical practise. The increasingly recognised need for rigorous sample quality control and both pre-clinical and clinical validation to meet the ultimate goals of clinical utility and patient benefit is discussed. Future directions of omic driven research in breast cancer metastasis are considered, in particular micro-RNAs and their role in the post-transcriptional regulation of gene function and the possible role of cancer-stem cells and epigenetic modifications in the development of distant metastases.

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.

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.

Protein analytical assays for diagnosing, monitoring, and choosing treatment for cancer patients

Cancer treatment is often hindered by inadequate methods for diagnosing the disease or insufficient predictive capacity regarding therapeutic efficacy. Targeted cancer treatments, including Bcr-Abl and EGFR kinase inhibitors, have increased survival for some cancer patients but are ineffective in other patients. In addition, many patients who initially respond to targeted inhibitor therapy develop resistance during the course of treatment. Molecular analysis of cancer cells has emerged as a means to tailor treatment to particular patients. While DNA analysis can provide important diagnostic information, protein analysis is particularly valuable because proteins are more direct mediators of normal and diseased cellular processes. In this review article, we discuss current and emerging protein assays for improving cancer treatment, including trends toward assay miniaturization and measurement of protein activity.

Screening and identification of serum proteomic biomarkers for gastric adenocarcinoma

The aim of the present study was to screen for possible serum biomarkers for gastric adenocarcinoma. Surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) was used to screen serum samples from 109 cases of gastric adenocarcinoma and 106 control subjects (60 healthy subjects, 30 patients with chronic superficial gastritis and 16 cases of chronic atrophic gastritis). The differentially expressed protein peaks were selected and isolated using high performance liquid chromatography (HPLC) and processed with enzyme prior to liquid chromatography-mass spectrometry tandem mass spectrometry (LC-MS/MS) analysis and data mining with software XCalibur program components BioWorks 3.2. Among the gastric cancer cases, three differentially expressed protein peaks were selected as potential serum biomarkers: the m/z peaks at 5,906.5 showed increased expression (8.53±4.33 in the cancer group, and 0.88±0.31 in the control group); the m/z peaks at 6,635.7 and 8,716.3 showed decreased expression (6.54±2.44 and 0.93±0.29, respectively, in the cancer group and 17.56±4.43 and 2.16±0.98, respectively, in the control group) (P<0.01). The m/z peaks at 5,906.5, 6,635.7 and 8,716.3, were identified as fibrinogen α-chain, apolipo-protein A-II and apolipoprotein C-I. The combined use of the three biomarkers distinguished the cancer group patients from the control group samples at a sensitivity of 93.85% (61/65) and a specificity of 94.34% (50/53). In conclusion, fibrinogen α-chain, apolipoprotein A-II and apolipoprotein C-I were identified as potential markers for gastric cancer and appear to have diagnostic value for clinical applications.

Serum peptidome patterns of breast cancer based on magnetic bead separation and mass spectrometry analysis

Background

Breast cancer is one of the most common cancers in the world, and the identification of biomarkers for the early detection of breast cancer is a relevant target. The present study aims to determine serum peptidome patterns for screening of breast cancer.

Methods

The present work focused on the serum proteomic analysis of 36 healthy volunteers and 37 breast cancer patients using a ClinProt Kit combined with mass spectrometry (MS). This approach allows the determination of peptidome patterns that are able to differentiate the studied populations. An independent group of sera (36 healthy volunteers and 37 breast cancer patients) was used to verify the diagnostic capabilities of the peptidome patterns blindly. An immunoassay method was used to determine the serum mucin 1 (CA15-3) of validation group samples.

Results

Support Vector Machine (SVM) Algorithm was used to construct the peptidome patterns for the identification of breast cancer from the healthy volunteers. Three of the identified peaks at m/z 698, 720 and 1866 were used to construct the peptidome patterns with 91.78% accuracy. Furthermore, the peptidome patterns could differentiate the validation group achieving a sensitivity of 91.89% (34/37) and a specitivity of 91.67% (33/36) (> CA 15–3, P < 0.05).

Conclusions

These results suggest that the ClinProt Kit combined with MS shows great potentiality for the diagnosis of breast cancer.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1501556838687844