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Maldi tof-ms analysis in identification of prostate cancer
1. MALDI-TOF-MS analysis in
identification of prostate cancer
Prof./Moustafa Rizk
Clinical pathology department
Facutly of Medicine, Alexandria University
Clinical Pathology Department
Assiut university
20/2/2019
2. Today I’ll cover
Prostate Cancer Risk Factors
Prostate cancer detection using PSA
Proteomic pattern in Prostate Cancer
Sample preparation
Sample separation
Sample identification
Model Generation
Bioinformatics
The 5- peak model used
Conclusion
4. Epidemiology
In Egypt in the year 2008, prostate cancer diagnosis was approximately 1,661 men with a rate of 6.6 per 100,000
and 1,283 men were expected to die from PCa with a rate of 5.1 per 100,000
5. Five most frequent cancers in MENA compared with North America and rest of the World
6. Prostate Cancer Risk Factors
Established
Advancing Age
Race/ethnicity
Geography
Family history
Gene changes
Presence of androgens
Potential
High dietary fat , Obesity
Sexual transmitted diseases
Smoking
Alcohol consumption
Vitamin D or E deficiency
Selenium deficiency
7.
8. Pathophysiology
1. Prostatic intraepithelial neoplasia [PIN]
2. Adenocarcinoma (More than 95%)
3. Other rare types:
a. Ductal carcinoma ( 1% of prostatic adenocarcinoma )
b. Transitional cell carcinoma
c. Small cell (neuroendocrine) carcinoma
d. Mesenchymal tumors (0.1% to 0.2%)
e. Urothelial carcinoma (1% to 4% )
f. Metastatic (From colorectal tumours)
9. The US preventive services task force (USPSTF) no longer recommends routine PSA screening
10. Prostate cancer detection as a function of serum PSA level and
DRE findings in a contemporary series
11. PSA Screening
Pros Cons
PSA screening may help you detect prostate cancer early. Some prostate cancers are slow growing and never spread beyond
the prostate gland.
Cancer is easier to treat and is more likely to be cured if it's
diagnosed in the early stages of the disease.
Not all prostate cancers need treatment. Treatment for prostate
cancer may have risks and side effects, including urinary
incontinence, erectile dysfunction or bowel dysfunction.
PSA testing can be done with a simple, widely available blood test. PSA tests aren't foolproof. It's possible for your PSA levels to be
elevated when cancer isn't present, and to not be elevated when
cancer is present.
For some men, knowing is better than not knowing. Having the test
can provide you with a certain amount of reassurance — either that
you probably don't have prostate cancer or that you do have it and
can now have it treated.
A diagnosis of prostate cancer can provoke anxiety and confusion.
Concern that the cancer may not be life-threatening can make
decision-making complicated.
The number of deaths from prostate cancer has gone down since
PSA testing became available.
PSA testing has lowered deaths, but the number may not be
substantial enough to justify the cost and possibility of harm to the
person undergoing the testing.
12. Schematic outline presenting the key elements of routine clinical practice in the management of patients with prostate cancer.
The context of use for novel biomarkers is indicated in each case.
13. Proteomic pattern in Prostate Cancer
Sample preparation
Platelet-depleted EDTA plasma is preferable to serum
The addition of protease inhibitors is recommended, but should be incorporated
early and used wisely
Transport of samples must be on ice
Samples to be centrifuged in a cold centrifuge at 4oC for 15 minutes at 1800 g
Samples should be aliquoted in DNA low bind Eppendorf tubes
Eppendorf was numbered and stored in a box in a -80oC freezer
Further, the use of reference materials for quality control and quality assurance
is recommended
All samples during the collection should be handled in a similar manner.
14. Sample separation
Using magnetic beads as a method for peptide/protein capture
from complex biological samples :
WCX (weak cation exchange) separate proteins based on charge
RPC18 beads C8 (reversed phase) separate proteins based on strong
hydrophobic interaction
MagSi-WCX beads
Efficient and reproducible way before MALDI-TOF/MS analysis
15. 1. 1 µL of the sample elute was applied
to a target spot and left to dry at
room temperature.
2. Then 1 µL of MALDI-Matrix
HCCA was applied on the top of the
sample spot and left to dry.
3. 2-4 spots were spotted on the target
for each sample.
Polished steel target
Sample spotting on the polished steel target
17. FlexControl software allows the introduction of the target into the
MS.
Before starting the MS analysis, the FlexControl™ software was
calibrated and optimized using the ClinProt standard.
17
Spectra Acquisition
Using MALDI-TOF-MS (Bruker Daltonics, Germany)
18. Constitution of the ClinProt standard
Calibration was done using
Clinprot standard (CPA)
which was spotted on the
target and tested as the
samples.
Detection limit of mass spectrometer was set to 800-20000 Da
19. Flex control analysis program
For each spot, 3000 shots were done by shooting 500 laser shots at 6 different spot positions
After finishing the shooting of spots of each sample, they were gathered into one spectrum
21. Analyte ions are produced after
ionization in the ion source.
The ions that are produced are
separated according to their
mass-to-charge ratio (m/z)
The output, which is recorded
at the detector, is the intensity
at different m/z values.
The result is visualized as a
m/z vs intensity (mass
spectrum)
Mass Spectrum
22. Typical MALDI-TOF MS spectrum
Each ion has a single charge
(z = 1); thus, the m/z ratio is
equal to the mass, meaning
the mass is the variable that
determines the time of flight
and which affects the
separation
23. Bioinformatics is the field of science in which biology, computer science, and information
technology merge to form a single discipline. As large volumes of proteomics data are generated,
subsequent database searching must keep pace.
Bioinformatics and database utilization
3
23
Definition
http://www.openms.de/
WHAT IS OPENMS?
OpenMS offers an open-source software library for LC/MS data management
and analyses.
It provides an infrastructure for the rapid development of mass spectrometry
related software
OpenMS is free software available
24.
25. Each group has been randomly distributed into two sets: training set for model generation, and
validation set for external validation.
The spectra of the training sets of studied groups were loaded onto the software.
Models were generated using Genetic Algorithm (GA), Supervised Neural Network (SNN) and
QuickClassifier (QC).
25
ClinProTools Version: 3.0 build 22
Name Algo
Validation
XVal X1 X2
Recogn
ition
Capabil
ity
Patients vs controls GA 91.5 % 88.1 % 94.8 % 100 %
Patients vs controls SNN 84 % 90.5 % 77.6 % 100 %
Patients vs controls QC 86.4 % 95.2 % 77.6 % 98.2 %
Model Generation
26. The 5- peak model used for discriminating between prostate cancer and
healthy control
26
Index Mass Start Mass End Mass
11 2485.97 2478.63 2496
3 1061.24 1057.89 1068.51
24 3295.1 3288.51 3306.45
33 4612.54 4603.15 4622.91
14 2817.28 2808.44 2825.01
This model achieved a sensitivity of 87.5 % and a specificity of 92.9 % during
external validation.
27. spectra of class I (patients) in red color against class II
(controls) in green
29. The peak is over expressed
.
Peak 24 with m/z ratio 3295.1
Patients (red)
Controls (grey)
Peak distribution command
Peak 24 with m/z ratio 3295.1
Patients (red)
Controls (grey)
31. It could be concluded that:
01
02
Inthe era of “big data” and “personalized medicine”
proteomics-based biomarkers hold great promise to
provide clinically applicable tools
31
MALDI-TOF proteomic profiling represents a new
frontier for screening and early diagnosis of Prostate
cancer in Egypt.
32. 32
Proteomic biomarkers alone and or in
combination with clinical and pathological
risk calculators may be in future expected
to improve on decreasing the unnecessary
biopsies, stratify low risk patients, and
predict response to treatment
One million men are diagnosed with Prostate Cancer (PC) worldwide and over 300,000 are dying annually of the disease . This corresponds to more than 3000 newly diagnosed cases and around 841 deaths every day
One million men are diagnosed with Prostate Cancer (PC) worldwide and over 300,000 are dying annually of the disease . This corresponds to more than 3000 newly diagnosed cases and around 841 deaths every day
Prostate cancer antigen-3 (PCA3): It is only expressed in human prostate tissue, and the gene is highly overexpressed in prostate cancer.(13, 14) Because of its restricted expression profile, the PCA3 RNA is useful as a tumour marker. It is worth noting that although PCA3 is prostate specific it is not cancer-specific.(15)
Alpha-methyl-coA racemase (AMACR): Increased levels of AMACR protein concentration and activity are associated with prostate cancer, and the enzyme is used widely as a biomarker.(16, 17)
Transmembrane protease serine 2: erythroblast transformation specific related gene (TMPRSS2: ERG) gene fusion:
*(−) DRE nonsuspicious for cancer; (+) DRE suspicious for cancer. Cancer detection rate is the number of cancers found in those screened (total number of detected cancers divided by the total number of men screened). Cancer yield is the total number of cancers detected divided by the total number of men undergoing a biopsy. However, PSA doesn’t always aid in diagnosis specially due to the rising incidence of clinically relevant prostate cancers in patients with low PSA serum levels (less than 4.0ng/ml)
Significant efforts have been undertaken to identify novel biomarkers that can accurately discriminate between indolent and aggressive cancer forms and indicate those men at high risk for developing prostate cancer that require immediate treatment
Standardization of sample collection and handling is probably the main challenge of high-throughput proteomic methods for disease biomarker discovery in human plasma.There is a large list of pre-analytical variables that can affect the analysis of blood-derived samples including; time, conditions of storage, usage of protease inhibitors and the number of freeze/thaw cycles
Proteins bound to the magnetic beads are then eluted, diluted and directly analyzed by MALDI-TOF/MS. Magnetic beads-based enrichment approaches have the potential to capture and enrich low abundance and low molecular weight species. The large surface area of the magnetic beads provides a high binding capacity, as the specific basic groups on the surface can sufficiently combine with the low-abundance proteins in the serum increasing the varieties of proteins captured.(257, 258) As a result of that, it ensures a favorable specific system; with simple and rapid operation, preliminary treatment can be finished through; the simple blending, washing and elution process, which is suitable for clinical examination.
Analyte ions are produced after ionization in the ion source, there are several ionization methods, but the most commonly used methods in proteomics are electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI). The ions that are produced are then transferred through a vacuum tube to the mass analyzer where they are separated according to their mass-to-charge ratio (m/z), usually each ion has a single charge (z = 1); thus, the m/z ratio is equal to the mass, meaning the mass is the variable that determines the time of flight and which affects the separation. The physical entity measured by all mass analyzers is the m/z value of the ions. The output, which is recorded at the detector, is the intensity at different m/z values. The result is visualized as a m/z vs intensity plot called the mass spectrum
. MALDI is an improvement of the laser desorption ionization (LDI) technique. In LDI, a soluble analyte is air-dried on a metal surface and the ionization is achieved by irradiation with an ultraviolet laser. The disadvantage of LDI is that it has low sensitivity, the ionization method causes ion fragmentation and the signal is very dependent on the ultraviolet-absorbing characteristics of the analyte.(271) This is solved with MALDI by decoupling the energy needed for desorption and ionization of the analyte. In MALDI, the analyte is mixed with a compound called the matrix, which absorbs the energy from the laser. The sample is co-crystallized with an excess amount of the matrix (figure 11). A variety of matrices (small aromatic acids) can be used. The aromatic group absorbs at the wavelength of the laser light, while the acid supports the ionization of the analyte. Irradiation with a short-pulsed laser, often a 337-nm N2 laser, causes mainly ionization of the matrix followed by energy and proton transfer to the analyte.(272) The charged ions are then accelerated at a fixed potential, where these separate from each other on the basis of their mass-to-charge ratio (m/z). The charged analytes are then detected and measured using different types of mass analyzers like quadrupole mass analyzers, ion trap analyzers and time of flight (TOF) analyzers as shown in figure (12).