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Biomarker discovery

19 important questions on Biomarker discovery

What is the definition of a biomarker?

Biomarkers are characteristics that are objectively measured and evaluated as indicators of normal biologic processes, pathogenic processes or pharmacologic responses to a therapeutic intervention.

What are false positives and what are false negatives?

false positives: healthy individuals that are diagnosed with a disease.
false negatives: diseased individuals that are not diagnosed with the disease.

What is sensitivity? And what is specificity?

true positives/ (true positives + false negatives). This means that 1- sensitivity is the chance of a negative test in sick people
true negatives/ (true negatives + false positives). 1- specificity is the chance of a positive test in healthy people.

What is the cut-off value?

This is the line between true positives and true negatives. Of course you always will find a small part of false positives and a small number of false negatives. when you move this cut-off line, these portions will increase or decrease.

What is the difference between the rule out limit and the rule in limit?

The rule out limit is the maximum place where you transfer the cut-off value to when you want to have as much as possible true positives (no false negatives but a lot of false positives)

The rule in limit is the maximum place where you transfer the cut-off value to when you want to have as much as possible true negatives (no false positives but a lot of false negatives)

What is the receiver operating characteristics (ROC) curve?

This is the curve in which the sensitivity (% true positives) is plotted against the false positives

What is the predictive value?

This is the percentage of the true positives from the total amount of positives in a population.

What is the biomarker discovery process?

It is a cycle of failure or success. Medical sciences, analytical sciences and data sciences are involved.

What is the label-free biomarker research strategy?

During the discovery phase you will have a low number of samples from patients (blood and urine). Then a complex analytical procedure is carried out to measure the high number of compounds in MS. Then data processing, statistical analysis and validation is carried out; selection of a low number of compounds as biomarker candidates. This leads to indentification of the new biomarker and then a high-throughput analytical procedure for final statistical validation on high number of samples is needed.

What can be sources of variance in the label-free biomarker research strategy?

- influence on biological variance (patient selection and experimental design)
- influence on analytical variance (sample collection and storage)
- influence on analytical variance (sample preparation)
- influence on analytical variance (comprehensive profiling (MS settings)
- Accuracy of signal processing (data processing; classification)
- accuracy of statistical analysis (statistical analysis and validation)
- accuracy of protein identification and protein interaction network (biological validation)
- influence on analytical and biological variances (validation on large number of samples; patient cohort selection)

Summary biomarker basics:

- sensitivity and specificity
- false positives and false negatives
- receiver operating characteristics (ROC) curve
- prevalence and predictive value
- biomarker discovery strategy & sources of variance

What is time alignment?

This means that you transfer the peaks until they all com at the same time.

Summary data analysis:

- data pre-processing to discriminate signals from background noise.
- feature selection and multi-variate statistical analysis to find proteins/metabolites that contribute to group separation.
- univariate statistical analysis to assess significance of discrimination.

Summary application EAE model:

- protein analysis of cerebrospinal fluid (CSF) discriminates systemic inflammatin from neuroinflammation
- longitudinal studies provide evidence of different protein time patterns;
- paraoxonase could be an early indicator of a relapse.

How are biomarkers validated?

- you have proteins of interest.
- You select proteotypic peptides (peptides that only occur in the protein of interest and you compare it to a synthetic wit lc/msms)
- you get heavy labelled peptides. You choose and optimize the transitions and then you quantitatively analyse it by SRM.

What is the signature of those peptides?

- The cosen peptide must be unique for the protein in question (better, the SRM transitions must be specific)
- the chosen fragment peptide must ionize well and give intense fragments
- generally one transition is not enough for selective monitoring.
- for absolute quantification, stable isotope labeled internal standards must be added.

What is laser microdissection?

This is a technique by which you can cut a very small piece of tissue out of a larger piece of tissue. Within this technique the tissue is placed on a glass slide with a PEN membrane. In this way it can cut tissue. With these samples you can test if the protein of interest is really more available in the diseased state compared to healthy tissue.

How do you convert the technique with tissue to blood?

You need to take into account:
- the biomarker release from tumor cells
- the biomarker release from healthy cells
- the entry of the biomarker in vasculature from tumor
- the entry of the biomarker in vasculature from healthy tissue?
- release rate from tumor cells
- release rate from healthy cells
- number of tumor cells at time
- number of healthy cells at time
so a lot of parameters.

What is the summary of the biomarker validation?

- targeted mass spectrometry in the selected reaction monitoring (SRM) mod
- tissue analysis after laser microdissection
- tissue analysis by immunohistochemistry (IHC)
- validation in biopsies by targeted LC-MS/MS
- translation from tissue to serum is challenging.

The question on the page originate from the summary of the following study material:

introduction

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Biomarker discovery

19 important questions on Biomarker discovery

What is the definition of a biomarker?

What are false positives and what are false negatives?

What is sensitivity? And what is specificity?

What is the cut-off value?

What is the difference between the rule out limit and the rule in limit?

What is the receiver operating characteristics (ROC) curve?

What is the predictive value?

What is the biomarker discovery process?

What is the label-free biomarker research strategy?

What can be sources of variance in the label-free biomarker research strategy?

Summary biomarker basics:

What is time alignment?

Summary data analysis:

Summary application EAE model:

How are biomarkers validated?

What is the signature of those peptides?

What is laser microdissection?

How do you convert the technique with tissue to blood?

What is the summary of the biomarker validation?

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