Course description
Precision Oncology (PO) is already revolutionizing healthcare and will play a dominant role in the future of cancer therapy. PO integrates tumor multi-omic profiles and data that reflect the course of the disease, lifestyle and environment to guide clinical decisions during cancer patient journey such as prevention, diagnosis and treatment. Bioinformatics analyses are essential to identify patients who will benefit from treatment based on their molecular profile, and to tailor chemotherapeutic regimens accordingly. The aim of the course is to present a complete computational pipeline for the analysis and interpretation of Next-Generation Sequencing (NGS) data such as exome sequencing or targeted panels that are commonly used in the clinic. We will address the implementation of large-scale genomic sequencing in clinical practice and the recently developed computational strategies for the analysis of NGS data with a particular emphasis on the interpretation of the results, selection of biomarkers of drug response and afford opportunities to match therapies with the characteristics of the individual patient’s tumor. Exercises and case studies focused on cancer will be used to illustrate the principles of how genetics influence led to refining diagnoses and personalized treatment of cancer disease. Although focused on cancer, some of the principles and steps could be extrapolated to other complex diseases.
Target audience
This course is intended for working healthcare professionals and Bioinformaticians working in the area.
Pre-requisites
The course assumes that attendees are not intimidated by the prospect of gaining experience working on UNIX-like operating systems (including the shell, and shell scripting). Attendees should understand some of the science behind high-throughput DNA sequencing and sequence analysis, as we will not go deeply into underlying theory (or the mechanics of given algorithms, for example) as such. What will be taught are technical solutions for automating and sharing such analyses in shareable, reusable compute environments, which will include (but is not limited to) beginner-level programming, and basic Linux provisioning. General computer literacy, (e.g. editing plain text data files, navigating the command line) will be assumed.
Detailed program
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Day #1 Introduction and methods
09:30 - 10:00 Introduction to the course and self presentation of the participants
10:00 - 11:00 Introduction to Personalized Medicine & Brief description of the course workflow
11:00 - 11:30 Coffee Break
11:30 - 12:00 Alignments: basic theory
12:00 - 12:30 Introduction to NGS data formats
12:30 - 14:00 Lunch Break
14:00 - 15:00 Exercise - Quality control
15:00 - 16:00 Variant detection
16:00 - 16:30 Coffee Break
16:30 - 17:30 Exercise - Setup varca pipeline
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Day #2 Variant calling and annotation
09:30 - 10:00 Review Day 1
10:00 - 11:00 Exercise - Whole exome analysis: Ovarian cancer patient
11:00 - 11:30 Coffee Break
11:30 - 12:30 Exercise continuation
12:30 - 14:00 Lunch Break
14:00 - 15:00 Exercise - Targeted gene sequencing panel analysis: Gastrointestinal cancer patient
15:00 - 16:00 Variant annotation
16:00 - 16:30 Coffee Break
16:30 - 17:30 Exercise - Variant annotation using VEP
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Day #3 Variant annotation and filtering
09:30 - 10:00 Review day 2
10:00 - 11:00 Variant prioritization
11:00 - 11:30 Coffee Break
11:30 - 12:30 Exercise: Variant annotation, filtering and prioritization
12:30 - 14:00 Lunch Break
14:00 - 16:00 PanDrugs: Matching mutations with therapies
16:00 - 16:30 Coffee Break
16:30 - 17:30 Exercise - Running PanDrugs -
Day #4 Interpretation of the results
09:30 - 10:00 Review day 3
10:00 - 11:00 Cancer genomics resources
11:00 - 11:30 Coffee Break
11:30 - 12:30 Exercise - cBioPortal
12:30 - 14:00 Lunch Break
14:00 - 15:00 Exercise continuation
15:00 - 16:00 Exercise - Variant annotation, filtering and prioritization
16:00 - 16:30 Coffee Break -
Day #5 Case studies in Personalized cancer medicine
09:30 - 10:00 Review day 4
10:00 - 11:00 Analysis LUSC exome
File with annotations
Report template
11:00 - 11:30 Coffee Break
11:30 - 12:30 Analysis LUSC exome: continuation
12:30 - 14:00 Lunch Break
14:00 - 15:00 Analysis LUSC exome continuation
15:00 - 16:00 Interpretation & discussion
16:00 - 16:30 Coffee Break
16:30 - 17:30 Final Wrap-up session
16:30 - 17:30 Exercise continuation
Resources
Clinical Interpretation of variants
- Li MM et al. Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A Joint Consensus Recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists.J Mol Diagn. 2017 Jan;19(1):4-23
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Tsang H, Addepalli K, Davis SR. Resources for Interpreting Variants in Precision Genomic Oncology Applications. Front Oncol. 2017 Sep 19;7:214
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Meric-Bernstam F et al. A decision support framework for genomically informed investigational cancer therapy. J Natl Cancer Inst. 2015 Apr 11;107(7)
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Amendola LM et al. Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium. Am J Hum Genet. 2016 Jul 7;99(1):247
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Dienstmann R et al. Standardized decision support in next generation sequencing reports of somatic cancer variants. Mol Oncol. 2014 Jul;8(5):859-73
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Sukhai MA et al. A classification system for clinical relevance of somatic variants identified in molecular profiling of cancer. Genet Med. 2016 Feb;18(2):128-36
Authors and Contributors
María José Jiménez-Santos, Elena Piñeiro-Yáñez, Fátima Al-Shahrour & Pedro L. Fernandes