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Summary Cancer Genomics

Course
- Cancer Genomics
- 2021 - 2022
- Universiteit Utrecht
- Bioinformatics and BioComplexity
91 Flashcards & Notes
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A snapshot of the summary - Cancer Genomics

  • 1 Day 1: Introduction Cancer Genomics

  • 1.1 Introduction

  • Strict defenition of cancer genomics
    The study of genome-wide DNA changes in cancer cells
  • Wider definition of cancer genomics 
    Using genome-wide technologies to understand and treat cancer cells
  • Cancer cells accumulate somatic mutations over time in differnt ways
    1. Intrinsic mutations
    2. Environmental and lifestyle exposures
    3. Mutator phenotype
    4. Chemotherapy
  • Tumor mutation burden (TMB) varies by?
    Cancer type, age and environmental exposure
  • Tumor mutation burden (TMB)
    The total number of mutations found in the DNA of cancer cells
  • Cancer genomics plays a huge role in?
    Identifying novel targets and identifying eligible patients
  • Molecular drugs are often given in combination for?
    Increased effectiveness (synergistic drug effect). But even then resistance frequently arises.
  • 1.2 Working with sequencing data

  • Typical NGS pipeline
    1. Sequence reads (fastq)
    2. Aligment to genome (sam, bam, cram)
    3. Variant calling 
      • SNVs/indels (vcf)
      • SVs (vcf)
      • CNV (bed, seq)
      • Gene fusions (txt)
  • Average depth of sequencing coverage
    (L * N) / G
    L = read length
    N = number of reads
    G = haploid genome length
  • 2 Day 2: Somatic and Germline SNV calling

  • 2.1 Calling Somatic SNVs

  • Several factors that complicate somatic SNV calling
    • Intra-tumour heterogeneity
    • Aneuploidy
    • Unbalanced structural variations
    • Normal contaminated with tumor DNA
    • Sequencing errors
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