Mutational Events in Lung Cancer: Present and Developing Technologies

The advent of targeted therapies has brought about a paradigm shift in the management of lung cancer. The majority of these drugs, however, only benefit a small subset of patients whose tumors are driven by specific aberrations in cell signaling pathways. Cancer cells demonstrate several types of genomic alterations including base substitutions, copy-number alterations (amplifications or deletions), and structural rearrangements (translocations or chromosomal rearrangements). Point mutations or single base substitutions (also known as single nucleotide variants [SNVs]) represent one of the most common types of DNA alteration. SNVs in protein-coding genes may result in a variety of effects in the resulting proteins. Synonymous mutations alter the DNA sequence of protein-coding genes in a way that the modified sequence at the mutated location still codes for the same amino acid. These mutations are therefore viewed as being “silent,” although recent data suggest that some of these mutations could have important functional consequences. By contrast, missense and nonsense mutations are associated with the substitution of one amino acid for another or premature termination of protein synthesis, respectively. Mutations that arise from the insertion or deletion of one or more nucleotides are referred to as “Indels” (short for insertions and deletions). These mutations can result in frameshift mutations that alter the reading frame of a protein-coding gene. The reading frame of a coding sequence refers to groups of three bases (or codons) in the sequence of a gene, each of which codes for a specific amino acid. When the number of nucleotides inserted or deleted from a coding sequence is not a multiple of three, the reading frame of the coding sequence downstream of the mutation is shifted, resulting in missense or nonsense alterations and the production of an abnormal or nonfunctional protein.

The processing of precursor messenger RNA (mRNA) into mature form occurs through removal of introns and joining of exons in a process termed “splicing.” This process is regulated in cells through proteins that constitute a cell’s splicing machinery. These proteins distinguish introns from exons based on characteristic base sequences within the intron, within the exon, and at intron–exon junctions. Splicing mutations alter these specific sites and deregulate splicing, leading to the abnormal inclusion or exclusion of introns or exons from the final mRNA. This can result in the production of aberrant and nonfunctional proteins. Copy-number alterations are changes in gene number from the two copies present in the normal diploid genome. Rearrangements occur when DNA from one segment is broken and rejoined to a DNA segment from elsewhere in the genome. Rearrangements occurring within the same chromosome or involving regions on different chromosomes are referred to as intrachromosomal or interchromosomal translocations, respectively.

Somatic mutations in cancer cells are identified by comparing the DNA sequence of cancer cells with that of noncancerous “normal” cells acquired from the same individual. Although these somatic mutations occur randomly throughout the genome of a cancer cell, a subset of somatic mutations occurs in a key set of genes that confer growth advantage to the cells harboring them. These “driver” mutations are positively selected during cancer evolution and implicated in oncogenesis. One of the important objectives of cancer genomic studies is to distinguish these driver mutations from bystander “passenger” mutations that do not confer a survival advantage, in an unbiased fashion. This process entails the use of complex statistical algorithms. Apart from offering an insight into the biology underlying malignant transformation, such analyses also facilitate the identification of novel therapeutic targets.