Applied Oncobiology

Instance: 2019/2020 - 2S (of 10-02-2020 to 31-07-2020)

Cycles of Study/Courses

Teaching language

Objectives

• Describe the mechanisms yielding to genetic variation, and be familiar with the various types of genetic variants.


• Distinguish hereditary genetic anomalies from acquired genetic anomalies.


• Discuss the advantages and limitations of different genetic laboratory methodologies for diagnostic testing.


• Demonstrate how to interpret non-hotspot mutations using public databases and taking into account overall genomic aberrations and clonal evolution.


• Be aware of ethical implications of incidental genetic findings.

• Understand the basics (procedures and rules) of an accredited clinical laboratory.


• Gain knowledge about different types of specimens (e.g. tissue biopsy, cytology, resections).


• Get familiar with all the steps that lead from samples collection to final molecular report generation along with all possible bottlenecks.


• Have an overview about the currently used technological platforms in molecular diagnostics (comparison with the research setting).


• Get familiar with the most common clinically relevant variants along with their interpretation and classification system.

• Communicate efficiently with bioinformaticians.


• Describe a bioinformatics analysis pipeline to call mutations from NGS data.


• Perform quality control at the run, read and variant levels.


• Use off-the-shelf bioinformatics tools to annotate and support the interpretation of variants.


• Consider hardware, security and privacy issues when managing omics data.


• Understand how artificial intelligence contributes to and will further impact personalized oncology.

• Describe main intracellular signaling pathways in solid tumors and molecular aberrations hampering this signaling.


• Get detailed knowledge of immunological mechanisms and how these may be used to optimize therapeutic approaches.


• Get a basic understanding of the principles underlying the design and analysis of clinical trials in oncology.


• Understand the importance of predictive markers in molecular oncology.


• Get familiar with the most frequent molecular aberrations in solid tumors and routinely used targeted therapies.

Learning outcomes and competences

• Describe the mechanisms yielding to genetic variation, and be familiar with the various types of genetic variants.


• Distinguish hereditary genetic anomalies from acquired genetic anomalies.


• Discuss the advantages and limitations of different genetic laboratory methodologies for diagnostic testing.


• Demonstrate how to interpret non-hotspot mutations using public databases and taking into account overall genomic aberrations and clonal evolution.


• Be aware of ethical implications of incidental genetic findings.

• Understand the basics (procedures and rules) of an accredited clinical laboratory.


• Gain knowledge about different types of specimens (e.g. tissue biopsy, cytology, resections).


• Get familiar with all the steps that lead from samples collection to final molecular report generation along with all possible bottlenecks.


• Have an overview about the currently used technological platforms in molecular diagnostics (comparison with the research setting).


• Get familiar with the most common clinically relevant variants along with their interpretation and classification system.

• Communicate efficiently with bioinformaticians.


• Describe a bioinformatics analysis pipeline to call mutations from NGS data.


• Perform quality control at the run, read and variant levels.


• Use off-the-shelf bioinformatics tools to annotate and support the interpretation of variants.


• Consider hardware, security and privacy issues when managing omics data.


• Understand how artificial intelligence contributes to and will further impact personalized oncology.

• Describe main intracellular signaling pathways in solid tumors and molecular aberrations hampering this signaling.


• Get detailed knowledge of immunological mechanisms and how these may be used to optimize therapeutic approaches.


• Get a basic understanding of the principles underlying the design and analysis of clinical trials in oncology.


• Understand the importance of predictive markers in molecular oncology.


• Get familiar with the most frequent molecular aberrations in solid tumors and routinely used targeted therapies.

Working method

Program

• Basic cytogenetics and molecular genetics


• Hereditary vs. acquired genetics


• Genetic recombination, DNA damage and repair


• Solid tumors and hematological malignancies


• Genetic predisposition to cancer


• Diagnostic genetic testing


• Clonal evolution & tumor heterogeneity

• Sample classification and preparation


• Principles of nucleic acids extraction


• Sequencing platforms and setup


• Understanding gene panels


• Internal / external Quality controls


• Laboratory accreditation


• Reporting genomic variants


• Interpreting a molecular profile

• Data pre-processing


• Read mapping


• Variant calling


• Quality control


• Variant annotation


• Hardware, security, privacy

• Tumor Physiology


• Tumor Immunology


• Cancer Statistics and Epidemiology


• Prognostic and Predictive Markers


• Targeted Therapies in Clinical Oncology


• Risks / probabilities for the interpretation of genetic results and counseling


• Clinical Trials in Molecular Oncology

Mandatory literature

Teaching methods and learning activities

keywords

Evaluation Type

Assessment Components

Amount of time allocated to each course unit

Eligibility for exams

Calculation formula of final grade