gene expression analysis of “complex” tissues
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Gene expression analysis of “complex” tissues. What is gene expression? What is a “complex” tissue? How can gene expression analysis be done? How should the findings be validated? Can this be used for diagnosis or prediction? Some conditions suited for diagnosis or prediction. - PowerPoint PPT PresentationTRANSCRIPT
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Gene expression analysis of“complex” tissues
• What is gene expression? • What is a “complex” tissue?• How can gene expression analysis be done?• How should the findings be validated?• Can this be used for diagnosis or prediction?• Some conditions suited for diagnosis or prediction.
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What is gene expression?
Genome
Transcription
mRNA
Translation
Protein
Secretion
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What is a “complex” tissue? Anatomical complexity (1)
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Normal gastric corpus Adenocarcinoma
What is a “complex” tissue? Patho-anatomical complexity (2)
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mageECL-cellEC-cellD-cellD1-cellA-like cellX-cell
What is a “complex” tissue? Physiological complexity (1)
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What is a “complex” tissue? Physiological complexity (2)
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Digital camera/computer
Lid
Cell smear on an object glass with a polyethylene naphthalate membrane
Motorised stage
Objective
Laser
Laser-assisted microdissection
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Small (ECL?)cell
Large (parietal?)cell
Laser-assisted microdissectionVideo view
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ECL cell Parietal cell Corpus Template-
CCK2-r
HDC H+K+
CCK2-r
Laser-assisted microdissectionSingle-cell nested PCR
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Gene expression analysis -a systematic approach?
High throughputsingle gene testing
Genome- or system-wide screening
Biomedicalproblem
Statistical andcomputational analysis
Applicationand ethics
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• A physiological experiment• A pharmacological intervention• A subspecies characteristic • A dysfunction or a disease
Biomedicalproblem
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Genome- or system-wide screening
• Microarray with genome or dedicated sets• Differential display• Various proteomics techniques
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Statistical andcomputational analysis
• Many genes-few replicates represent unique problems• Case-to-case assessment necessary at all levels of analysis• No method(s) seem routinely usable
• I.e. - close collaboration with highly skilled and scientifically competent statisticians and computing scientists is mandatory. • All experiments are opportunities to work with statistics and computational methods on a scientific level.
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High throughputsingle gene testing
• High throughput si-RNA testing• Tissue microarray methods
Final verification by carefullydesigned experiments, transgenicsor other more laborious methods
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Applicationand ethics
Medical• Classification of disease• Early diagnosis• Treatment stratification
Some applications:Biological• Generation of hypotheses• Integrated regulatory mechanisms
Some ethical concerns:• Surplus information• Is presymptomatic diagnosis desirable• Familial susceptibility
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Diagnosis and predictionGeneral
• Differentiation between malignant and non-malignant growth• Differentiation between localised and disseminated malignant tumour (surgical decision-making)• Differentiation between similar but non-malignant conditions• Differentiation between medically responsive and non-responsive conditions (medical decision-making)
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Diagnosis and treatment ofgastrointestinal premalignancies
Polypectomy FAP
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Diagnosis and predictionExamples from gastroenterology (1)
Diagnosis and therapy response inUlcerative colitis Crohn’s disease
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Diagnosis and predictionExamples from gastroenterology (2) Development of malignancy in ulcerative colitis
DALM Adenocarcinoma
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Diagnosis and predictionExamples from gastroenterology (3)
Gastric stump cancer
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Diagnosis and predictionExamples from gastroenterology (4)
Predicting: • Penetration• Haematogenic metastasis• Lymphatic metastasis• Intracavitary metastasis