Gene expression analysis of “complex” tissues
21
Gene expression analysis of “complex” tissues t is gene expression? t is a “complex” tissue? can gene expression analysis be done? should the findings be validated? this be used for diagnosis or prediction? e conditions suited for diagnosis or predict
description
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 Presentation
Transcript of Gene expression analysis of “complex” tissues
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.
What is gene expression?
Genome
Transcription
mRNA
Translation
Protein
Secretion
What is a “complex” tissue? Anatomical complexity (1)
Normal gastric corpus Adenocarcinoma
What is a “complex” tissue? Patho-anatomical complexity (2)
mageECL-cellEC-cellD-cellD1-cellA-like cellX-cell
What is a “complex” tissue? Physiological complexity (1)
What is a “complex” tissue? Physiological complexity (2)
Digital camera/computer
Lid
Cell smear on an object glass with a polyethylene naphthalate membrane
Motorised stage
Objective
Laser
Laser-assisted microdissection
Small (ECL?)cell
Large (parietal?)cell
Laser-assisted microdissectionVideo view
ECL cell Parietal cell Corpus Template-
CCK2-r
HDC H+K+
CCK2-r
Laser-assisted microdissectionSingle-cell nested PCR
Gene expression analysis -a systematic approach?
High throughputsingle gene testing
Genome- or system-wide screening
Biomedicalproblem
Statistical andcomputational analysis
Applicationand ethics
• A physiological experiment• A pharmacological intervention• A subspecies characteristic • A dysfunction or a disease
Biomedicalproblem
Genome- or system-wide screening
• Microarray with genome or dedicated sets• Differential display• Various proteomics techniques
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.
High throughputsingle gene testing
• High throughput si-RNA testing• Tissue microarray methods
Final verification by carefullydesigned experiments, transgenicsor other more laborious methods
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
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)
Diagnosis and treatment ofgastrointestinal premalignancies
Polypectomy FAP
Diagnosis and predictionExamples from gastroenterology (1)
Diagnosis and therapy response inUlcerative colitis Crohn’s disease
Diagnosis and predictionExamples from gastroenterology (2) Development of malignancy in ulcerative colitis
DALM Adenocarcinoma
Diagnosis and predictionExamples from gastroenterology (3)
Gastric stump cancer
Diagnosis and predictionExamples from gastroenterology (4)
Predicting: • Penetration• Haematogenic metastasis• Lymphatic metastasis• Intracavitary metastasis
