Mass Spec Assgn

Module – 3 Assignment: Analytical Chemistry and Molecular Modelling – November 2009 Importance of Mass Spectrometry in Biomedicine Illustrated by Cancer Screening Applications

Jyotika Govil, MSc Molecular Medicine (044322)

Abstract: Mass Spectrometry is one of most widely applicable analytical technique used for identification and characterization of molecules of a large range of molecular weights. There are different components of a mass spectrometer, which can be altered according to experimental needs, and are briefly described in this paper. To visualize impact of MS in biomedicine, applications are mentioned in drug discovery. However, for the purpose of recognizing a clinical impact on general population, use of protein profiling by MALDI-TOF MS in detection of cancer is the main focus of this review.

1. Introduction The technique used and advanced for the characterization and identification of unknown and known compounds in a charged molecular state, since 1912, when J.J. Thomson first devised it, is Mass Spectrometry. The technology started as spectroscopy using fluorescent graphs was later modified into magnetic field detection and hence termed as spectrometry . The basic principle of mass spectrometry is to convert the introduced sample into gaseous state charged ions which are accelerated and separated under a magnetic field on the basis of their mass/charge (m/z) ratio, analyzed and detected to form a mass spectrum. The schematic diagram in Figure-1 shows the basic components of a mass spectrometer.

Figure-1: General schematic of parts of a Mass Spectrometer Moving across the various components, as shown above, the processes that occur are: 1. Introduction of sample through an inlet, which can be direct or through a chromatograph. 2. Vaporization and ionization of sample to impart a charge (often positive) to the molecule..

3. The ions are propelled to a mass analyzer, which consists of a magnetic field and due to difference in m/z ratios, the molecules follow different trajectories and speeds which are then scanned by the analyzers. 4. To produce an interpretable signal, detectors are employed which convert the molecular analysis into electronic current signals, producing a visual spectrum, recorded and displayed by computers.

1.1 Ionization Techniques Electron Ionisation (EI): this is the oldest method, where a beam of electrons from a cathode is bombarded upon the gaseous sample, leading to knocking out of electrons. The positively charged sample ions are then accelerated and analyzed. Being a strong ionization technique, often leads to fragmentation of sample. Fast Atom Bombardment (FAB): The sample solubilised in a non-volatile matrix (eg. Glycerol) is bombarded with a high current beam of atoms/ions (Argon or Xenon) which does not fragment the sample and only eject surface ions dissolved in the matrix. Has advantage of producing ions from biological compounds of high molecular weight, polar samples and also generating ions for longer duration . Electrospray Ionisation (ESI): Commonly used for large biomolecules, it ionizes at atmospheric pressure, from solution. The sample is converted into fine spray and is ionized in presence of strong electric field. The nozzle at high electric potential forms the droplets, which are evaporated by action of heat/gas at atmospheric pressure. Concentrating charge upon smaller droplets increases the charge density. The ion formation and conversion into smaller droplets is illustrated in Figure-2.

Figure–2: Mass Spec by ESI Matrix Assisted Laser Desorption Ionisation (MALDI): This is an advanced soft ionisation method for analysis if biomolecules of up to 500,000 Daltons with high accuracy and without causing fragmentation. The principle is to co-crystallize the sample onto a matrix of UV-absorbing material which is irradiated with a laser. The photons excite and vaporize matrix molecules, along with the analyte and ionisation occurs. The ions are accelerated by the presence of electric field in between the MALDI plate and analyser. It enables simultaneous analysis of many samples of complex molecules. A similar technique is Surface Enhanced Laser Desorption/Ionisation (SELDI) also used for biomolecules .

1.2 Analyzers Magnetic Field Analyzers: A magnetic field is applied by an electromagnet which is perpendicular to the path followed by the accelerated ions. The path is curved and ions have the same kinetic energy when coming from the ionizers. They separate depending upon their m/z ratio and only the ions with corresponding trajectory are able to pass through. The strength of the magnetic field is changed and hence due to varied m/z ratios, the components of the sample are analyzed. Time of Flight (TOF) Analyzers: The ions after being expelled from the sample/matrix are accelerated by an electric potential and move a certain distance before hitting the detector. By measuring this time-of-flight of the ions,

their m/z ratios are determined. The ions with lower mass have high speed and are detected first. This detection method has no mass limit hence can be used for high mass biomolecules and is most often combined with MALDI for detection. Quadrupolar Analyzers: The apparatus has four parallel metal electrodes which produce a Direct Current (DC) and Alternating Current (AC) field in between them. At a particular time only a specific m/z ratio resonant ion can pass through the field path and read by the detector as shown in Figure-3. By modifying the fields produced by the electrodes, the whole spectra of different m/z ratios can be established.

Figure-3: Quadrupole analysis after electron beam ionisation (Wittmann, 2007)

1.3 Detectors Faraday-Cup Detector: This is one of the older methods of charge detection, the ions passing through the analyzers, release their charge at the electrodes and the current is amplified and measured. These are not highly sensitive detectors. Electron Multipliers: The basic principle is use of dynodes, which release secondary particles after receiving the analyte ions. There is cascade of ions/electron release, amplifying the signal many folds, which can be through a continuous dynode electron multiplier giving a measurable current.

Photon Multipliers: These detectors involve electron dynodes as well as phosphorescent plates which convert electronic signal into photons. A visible signal is recorded by the photomultiplier.

1.4 Tandem Mass Spectrometry This process involves better analysis of components of a large molecule, composition and structure elucidation with higher sensitivity. Usually abbreviated as MS/MS it applies two stages of mass spectrometry. Firstly, the molecular ions are selected by the m/z ratio using a particular MS technique, then the molecule is fragmented by use of inert gas to be analysed again by a MS technique.

1.5 MS Coupling MS is coupled with various separation techniques to analyse complex mixtures and separate natural products and to identify unknown compounds. Coupling with various chromatographic techniques like Gas Chromatography (GC-MS), Liquid (LC-MS), High Performance Liquid Chromatography (HPLC-MS) or Capillary Electrophoresis (EC-MS) is done to co-ordinate separation, purification of analytes before characterisation with MS .

2. Literature Review Mass spectrometry in its various forms is widely used in pharmaceutical and biomedical field. Apart from drug analysis, MS is applicable for characterization and elucidation of biomolecules like nucleic acid, lipids, biopolymers and proteins. MS is used to initiate serum and urine diagnosis tools for detecting marker proteins, drugs, metabolites etc . MS is coupled with proteomics and bioinformatic tools to build systems that can screen protein libraries and generate new ones. With the availability of highthroughput screening by MS, it is applied for detecting protein biomarkers of diseases in plasma/serum/urine which is a highly sought after field .

Hence, the focus of this review is particularly on the use of MALDI/SELDI – TOF for screening of cancer by biomarker characterization in serum/saliva/cells.

2.1 Article: Use of proteomic patterns in serum to identify ovarian cancer – Petricoin III et al, 2002; The Lancet. Background: With the availability of treatment for ovarian cancer with only surgery, and high survival rate, detection in stage-I can have a major impact on women at high risk due to familial history or genetic predisposition with BRCA1 and BRCA2 genes. Biomarkers like CA125 have been used for detection, but with low positive predictive value. Hence, developing a bioinformatic technique for high-risk population is important and feasible with the aid of high-throughput SELDI/MALDI-TOF screening to measure low molecular weight serum proteins that can profile a diseased condition. Aim: To establish a population based screening technique with MS and proteomic patterns by bioinformatic algorithms, for early and consistent detection of ovarian cancer. Methods: A training set of data was accumulated by acquiring serum samples from 50 healthy females and 50 with confirmed ovarian cancer, and generating the proteomic mass spectra to segregate cancer from non-cancer spectra by use of genetic algorithms and cluster analysis. To test the method, 116 masked samples (50 with cancer including stage-I cancer, 66 healthy) were analysed by Protein Biology System 2 SELDI-TOF mass spectrometer on a protein chip, with specificity for molecular mass range 0-20,000Da. Positives and controls were analysed simultaneously on same as well as multiple chips. The pattern established with training set was compared with the test set data to distinguish patterns of proteins different in cancer patients by repetitive algorithm matching and classified into clusters of – unaffected, diseased and new cluster (completely new pattern).

Results: The reproducibility of the experiment was successfully tested. The results show that the algorithm correctly segregates the cancer and non-cancer spectra. In the masked set, there was 100% sensitivity, 95% specificity and also indentifying all 50 cancer samples with the 18 stage-I cancer. It shows high positive predictive value (94%) in contrast to low results with CA125 biomarker. Conclusion: Screening for ovarian cancer in high-risk groups is important to tackle the disease, hence such individuals were source of samples. The combination of proteomic mass spectra and bioinformatic genetic algorithms enables identification and segregation of low molecular weight protein patterns that discriminate cancer from non-cancer. The technique shows higher promise than other screening methods and with requiring small samples for MS and being cost-effective, this high-throughput screening, if combined with ultrasonography can be applied for clinical diagnostics .

2.2 Article: Mass spectrometry-based serum proteome pattern analysis in molecular diagnostics of early stage breast cancer – Pietrowska et al, 2009; Journal of Translational Medicine Background: With the establishment of proteomic pattern analysis for developing diagnostics for cancer, this experiment was carried out for early breast cancer detection as it is the most common malignancy in females. The analysis of complete protein profiles and not individual peptides is enabled by MALDI-TOF spectrometry which characterizes proteins of low molecular mass with high accuracy and low time from complex samples (like serum). These spectral pattern analyses can be compared as more efficient than individual biomarker analysis by immunoassays.

Aim: To develop a serum based proteome blueprint analysis, by statistical classifiers, of spectral patterns generated by MALDI-TOF and comparing it with protein biomarker immunoassays. Methods: Analysis was done on samples obtained (by informed consent) from 92 breast cancer (stage I and II) patients and from 104 healthy females (same age group) as controls. The serum was removed of albumin and other high – molecular weight proteins and analysed with Autoflex MALDI-TOF spectrometer to obtain spectra between 2,000-10,000Da mass ranges, recording four spectra for every sample. For comparison, immunoassays (ELISA, CMIA, TRACE & MEIA) were conducted for selected markers. The data analysis was carried out by identifying the [M+H]+ ions recorded on spectra, into Gaussian-Bell curves, computing algorithms and forming classifiers of patterns to distinguish between cancer and non-cancer samples. Results: Using the MALDI spectrum of proteins, a classifier was established to identify protein patterns and pick similar patterns. With this classifier, spectral patterns that discriminate between healthy and cancer samples were configured. Three positions on the spectra: m/z= 2865.54, 3578.73 & 2303.48Da were most important for segregating the diseased samples, two of which were exclusively found in this study due to sample pre-treatment and albumin removal. These patterns were independent of age differences in the source subjects. The classifier was specific even with other pathologic conditions. In comparison to other biomarker immunoassays, the biomarker from these three spectral positions, gave a higher sensitivity (88%) and specificity (78%). Due to observation of osteopontin in only cancer samples, it was also tested as a classifier biomarker in combination, but gave only 28% specificity. Conclusion: Due to high-throughput and accurate proteome analysis with MALDITOF, its combination with proteomics and bioinformatics for the analysis of serum protein fingerprints and patterns promises as a better diagnostic for early breast cancer

detection.

This

procedure

overcomes

the

limitations

immunological testing for protein breast cancer biomarkers .

of

existing

2.3 Article: Detection of colorectal cancer using MALDI-TOF serum protein profiling – de Noo et al, 2006; European Journal of Cancer Background: Serum protein profiling for distinguishing cancer from non-cancer has been used and established, as shown in many previous experiments. The same concept is being applied for early diagnosis of colorectal cancer, which has the highest cancer morbidity and mortality rates. There is a requirement for biomarkers for this cancer as well for detection, monitoring and therapeutic studies. Although the protein profiling by MS has been appreciatively used, there have been criticisms about the statistical analyses of data and chances of bias or over-interpretation. Hence, this study uses “double cross-validation” for authentic results. Aim: To use a stringent statistical analysis for non-biased development of a diagnostic technique for early detection of colorectal cancer. This is based on Mass Spectrometric analysis of serum protein profiles. Methods: For conducting the study, samples from 66 stage-IV colorectal cancer patients were taken, and as controls from 50 healthy individuals. To minimize batch effects, all samples were equally randomized and the procedure repeated a week after the first test. The peptides were isolated with use of Magnetic BeadHydrophobic Interaction Chromatography. The samples were then subjected to MALDI-TOF (Ultraflex instrument) operating with a linear mode SCOUT ion source. Peaks were specifically measured in the range of 960 – 11,169Da. The resultant data was normalized for statistical analysis and also distributed into inter-quartile ranges of intensity. For the interpretation, the “double cross-validation” method was employed, to exclude every possible bias. Results: The method displayed a 92.6% total recognition rate, 95.2% sensitivity and 90.0% specificity with the first spectra, accurately classifying 60/63 cancer

samples (including all stage III,IV and 9/10 stage I) and 45/50 controls. To remove bias entire process was repeated after a week and a permutation calculation of the cross-validation was done with no significant bias found. Conclusion: The experiment followed a previously explored technique of discriminating cancer from non-cancer patients on basis of MS spectra protein profiling, in this case for colorectal cancer. The method was highly reproducible and statistical and experimental bias was endeavoured to be highly reduced. A classifier was successfully constructed and achieved high sensitivity and specificity (95.2% & 90% respectively). Due to possibility of discrepancies in previously conducted similar experiments, here special focus was on proper sample

collection,

randomized

testing

and

“double

cross-validation”

of

experimental data. The classifier was chosen as “Fisher linear discrimination” which a widely used discrimination method has given a high separation with 97.3% of data under the curve. The method yet to be completely validated is highly promising for colorectal diagnosis .

2.4 Article: Analysis of the saliva from patients with oral cancer by matrix-assisted

laser

desorption/ionization

time-of-flight

mass

spectrometry – Chen et al, 2002; Rapid Communications in Mass Spectrometry Background: There are changes in the biomolecular constitution of saliva with physiological changes in the body. The starch digesting enzyme alpha-amylase also changes in concentration in patients of oral cancer with altered hydrolytic activity of the enzyme. To proceed with this as a basis of distinguishing normal people from oral cancer patients, a combination of MALDI-TOF with SDS-PAGE is done. As electrophoresis was the only characterization method for proteins before, due to high sensitivity and rapid result generation, MALDI is used. Aim: To develop a swift method of oral cancer diagnosis by use of MALDI-TOF mass spectrometry.

Methods: Untreated saliva samples were collected from 20 healthy individuals (for control) and from 20 oral cancer patients. Also, the control samples were divided into groups pertaining to blood groups. Samples were prepared for spectrometry by mixing them with sinapinic acid matrix in acetonitrile in varying ratios. For enhanced characterization, the samples were electrophoresed with SDS-PAGE. The bands were cut and digested with trypsin and then used on sinapinic acid matrix for MALDI-TOF linear spectrometry. Results: The peak of alpha-amylase was particularly observed and studied at 57kDa in the spectra. It was seen in 13/20 control samples (in blood group-O, no peaks seen which could be due to some unknown blood group component, but could not be explained here). Another peak at 66kDa was observed, but only in 3 controls and more pronounced and present in the samples from cancer patients (15/20) with the 57kDa peak disappearing. The 66kDa peak corresponds to albumin which was confirmed with in-gel trypsin digestion fingerprinting. Electrophoresis also shows higher concentration of 66kDa band (albumin) in cancer patients. Conclusion: These results show a possibility of changed protein composition of saliva (especially in terms of albumin concentration increase and alpha-amylase suppression) in cancer patients. However, no confirmation of this direct relation could be made with this experiment. The amylase concentration is not suppressed in SDS-PAGE, and in MALDI the reduction could be attributed to a general suppression

of

alpha-amylase

concentration

due

to

increase

in

albumin

concentration (as seen by comparing spectra of different volume ratios). The combination method of SDS-PAGE with MALDI-TOF gives a rapid diagnostic approach which is minimally invasive and has easier sample acquisition, being a saliva test.

The saliva profile changes give discrimination between cancer and

non-cancer, but the relation still needs to be validated .

2.5

Article:

High-Throughput

Genotyping

of

Oncogenic

Human

Papilloma Viruses with MALDI-TOF Mass Spectrometry - Soderlund-Strand et al, 2008; Background: Cervical cancer is principally caused by the Human Papilloma Virus (HPV), which exists in various forms. Apart from the need to develop immunization, the genotyping and screening of HPV is important for detection of cervical cancer as well as monitoring of HPV load in vaccinated individuals. The different genotypes confer different risks for populations for development of cervical cancer and cervical intraepithelial neoplasia (CIN). Aim: To develop a high-throughput, screening methodology for genotyping 14 HPV types, known of causing cervical cancer by MALDI-TOF analysis. This is done in comparison with the standard HPV genotyping procedure of PCR amplimers undergoing Reverse Dot Blot Hybridisation (RDBH). Methods: The analysis was done with 532 cervical cell samples, 271 f which obtained from cancer patients undergoing treatment and follow-up. The samples were prepared by freeze-thawing followed by centrifugation and with 10-fold dilution for comparison of methods. The HPV DNA was amplified with PCR followed by target identification with immunoassay. The mass spectrometry was carried out using multiples primary PCR products on a Sequenom MassARRAY. Various primers were designed for PCR to get optimum annealing, followed up with homogenous mass extend (hME) reaction to specify each genotype. There were discrepancies in the results obtained from the two methods and reanalysis with MS and RDBH was conducted with excluding exceptions to have a total of 502 samples. Statistical analysis was done by ĸ statistics for concordance between the methods. Results: The MS method when compared with histopathology gave 91.4% sensitivity, only 46% specificity and 58.9% positive predictive value. It identified all samples shown positive by RDBH and also 5 more samples which could not be identified with RDBH. Overall concordance between MS analysis and RDBH was

0.945. There were discrepancies in some data when compared for the two methods, however, these were mostly in the samples taken from stage I of CIN. Conclusion: MS-based screening and HPV genotyping proved to be consistent, more sensitive and also economical. 10 x 384 samples could be analysed in 2 days with an individual cost of US$2 per sample. Due to the study being conducted on a large sample, the results can be considered as generally valid. MS enabled detection of HPV types which are missed by other tests (type 16 and 18) and carrying out detection of 1-100 HPV DNA copies of 14 types with high efficacy and speed. These plus points could enable a clinical application of MS high-throughput screening for cervical cancer.

3. Conclusion Before the development of Mass Spectrometry, the characterization of absolute molecular weight was dependent on conformations and calculations based on data obtained from chromatography, electrophoresis and centrifugation. The error rates with these are high and other molecular properties also interfere. Large molecules like biomolecules have been successfully characterized with MS purely on basis of experimental proof and not theoretical optimizations. With the ability to convert samples into molecular ions and highly specific

separation on basis of

mass/charge, MS has been developed as a prime analytical tool. With advances like MALDI, ESI, SELDI and TOF identification of blood and plasma components has been possible as they are soft and more specific techniques and do not cause fragmentation of biomolecules. In the process of drug development MS is applied for characterization of compounds at each step of discovery – screening of purity, physical and chemical characteristics,

lead

optimization,

in

vitro

screening

of

pharamacokinetic

properties (ADME- Absorption, Distribution, Metabolism & Excretion) of drugs,

metabolite identification both in vitro and in vivo, therapeutic assessments, toxicology studies, drug-protein interactions etc . Mass Spectrometry is used in combination with separation techniques like Liquid Chromatography, HPLC, Electrophoresis and the analytes are directly sent from the purification columns into the ionization chambers. The purification of compounds is very important as MS being highly sensitive obtains an m/z peak for all components. Occurrence of impurities and interfering particles causes suppression of peaks or distorted spectra. As it has been observed from the articles, in the complex constitution of serum various proteins alter observations of the desired proteins. Albumin has been shown to suppress peaks of small molecular weight proteins needed for screening as biomarkers. Hence, it is important to pre-treat the samples before analysing with MS . The right choice of ionization technique is very important as a strong technique like EI or CI can lead to fragmentation, which could be important for certain molecules, for example, in metabolite analysis in ADME studies of drugs where Desorption ESI and MALDI are used to build high-throughput screening libraries for fast development process . The benefit of high-throughput screening has increased usage in drug screening, however, the complexity of MS restricts usage for analysing millions of lead . In the reviewed articles, MS has been extensively applied to combine proteomic libraries with spectral data to identify biomarkers. MS was used since small proteins could only be detected with this technique. However, individual biomarkers are not identified, hence, profiling of complete spectra of components is done. There have been successful discriminations built with bioinformatic and statistical tools, yet there have been high chances of optimistic bias and reproducibility issues which have prevented such techniques to be clinically applied. On one hand, where the high sensitivity and specificity of MS enables such characterizations, on the other hand, the same qualities limit its ability to be consistently used in a clinical environment. Some of the studies have been conducted on small sample sizes and in a specific population which limits the potential of being applied for different races, as they may differ in their protein profiles. For every study a training set is to be made for comparisons and if

clinically applied it would be difficult to have a standard profile with which comparisons could be made. To summarize, Mass Spectrometry due to adaptability and applicability with fast and accurate analysis, is utilized and has a high impact in drug discovery, screening, lead optimization, drug monitoring, biomedicine, disease diagnosis, molecular modelling, imaging, isotopic identification, biomarker identification, molecular weight determination, fingerprinting and structural analysis of peptides in proteomics, lipids, nucleotides and other biopolymers , .

BIBLIOGRAPHY Wittmann, (2007), “Schematic view of the ion source based on electron impact ionization and the quadrupole mass filter typically found in a GC-MS instrument”, Microbial Cell Factories, vol.6.