2.7.3 Pan-Cancer Analysis of Whole Genomes (PCAWG) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.7.4 Catalog of Somatic Mutations in Cancer (COSMIC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.7.5 ClinVar . . ...... ..... ..... ..... ..... ..... ..... ..... ...... ..... ..... ..... ..... ..... ..... .... 32
2.8 Opportunities, Challenges, and Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
References ...... ...... ...... ...... ...... ...... ...... ...... ...... ....... ...... ...... ...... ...... ...... ... 36
What You Will Learn in This Chapter
In this chapter, we will discuss NGS applications in cancer research, starting with a
brief section on tumor driver genes and their mutational patterns, and then exploring
how DNA and RNA sequencing can aid cancer diagnosis, shed light on causal
agents, elucidate the biological mechanisms that participate in tumor evolution and
contribute to the design of effective therapies. The technological advances that have
allowed sequencing to be fast, efficient, and cost-effective have also created technical
challenges, which mainly comprise the combining, categorization, comparison, and
storage of large amounts of information, followed by the need for efficient analysis
methodologies to extract meaningful biological information. Considering this, we
will also briefly review the existing international collaborative efforts that aim to use
genome and transcriptome sequencing to deepen our understanding of cancer, and
will give our vision of the opportunities that this type of research offers for cancer
prevention and monitoring, the challenges it still has to overcome, and perspectives
for the future.
2.1
Introduction: Using Genomic Data to Understand Cancer
Cancer is a complex group of diseases that arise when mutations accumulate in cells, leading
to uncontrolled cell growth, abnormal morphology, and the ability to invade surrounding
tissues [1]. Therefore, it is now generally accepted that cancer is a disease of the genome.
Mutations that contribute to the acquisition of these characteristics are referred to as driver
mutations, whereas those that “hitchhike” with these are known as passenger mutations.
These alterations can be caused by exogenous agents, such as exposure to environmental
carcinogens like ultraviolet radiation, or endogenous factors, such as defects in DNA repair
genes (Fig. 2.1). When mutations occur during the lifetime of a cell these are known as
somatic mutations (as opposed to genetic variants, which are those present from birth).
As cancer represents the second main cause of death worldwide [2], research efforts are
focusing heavily on improving early detection, elucidating the main biological mechanisms
behind tumor types and identifying potential therapeutic targets. Research in all of these
areas has been boosted by whole-genome and -exome sequencing of matched tumor/
normal tissue, whose analysis allows researchers to identify mutations that fuel cancer
growth and that are potentially targetable. These advances have meant that clinicians and
18
C. Molina-Aguilar et al.
2.7.4 Catalog of Somatic Mutations in Cancer (COSMIC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.7.5 ClinVar . . ...... ..... ..... ..... ..... ..... ..... ..... ...... ..... ..... ..... ..... ..... ..... .... 32
2.8 Opportunities, Challenges, and Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
References ...... ...... ...... ...... ...... ...... ...... ...... ...... ....... ...... ...... ...... ...... ...... ... 36
What You Will Learn in This Chapter
In this chapter, we will discuss NGS applications in cancer research, starting with a
brief section on tumor driver genes and their mutational patterns, and then exploring
how DNA and RNA sequencing can aid cancer diagnosis, shed light on causal
agents, elucidate the biological mechanisms that participate in tumor evolution and
contribute to the design of effective therapies. The technological advances that have
allowed sequencing to be fast, efficient, and cost-effective have also created technical
challenges, which mainly comprise the combining, categorization, comparison, and
storage of large amounts of information, followed by the need for efficient analysis
methodologies to extract meaningful biological information. Considering this, we
will also briefly review the existing international collaborative efforts that aim to use
genome and transcriptome sequencing to deepen our understanding of cancer, and
will give our vision of the opportunities that this type of research offers for cancer
prevention and monitoring, the challenges it still has to overcome, and perspectives
for the future.
2.1
Introduction: Using Genomic Data to Understand Cancer
Cancer is a complex group of diseases that arise when mutations accumulate in cells, leading
to uncontrolled cell growth, abnormal morphology, and the ability to invade surrounding
tissues [1]. Therefore, it is now generally accepted that cancer is a disease of the genome.
Mutations that contribute to the acquisition of these characteristics are referred to as driver
mutations, whereas those that “hitchhike” with these are known as passenger mutations.
These alterations can be caused by exogenous agents, such as exposure to environmental
carcinogens like ultraviolet radiation, or endogenous factors, such as defects in DNA repair
genes (Fig. 2.1). When mutations occur during the lifetime of a cell these are known as
somatic mutations (as opposed to genetic variants, which are those present from birth).
As cancer represents the second main cause of death worldwide [2], research efforts are
focusing heavily on improving early detection, elucidating the main biological mechanisms
behind tumor types and identifying potential therapeutic targets. Research in all of these
areas has been boosted by whole-genome and -exome sequencing of matched tumor/
normal tissue, whose analysis allows researchers to identify mutations that fuel cancer
growth and that are potentially targetable. These advances have meant that clinicians and
18
C. Molina-Aguilar et al.