Beyond histology: translating tumor genotypes into clinically effective targeted therapies

Abstract

Increased understanding of intertumoral heterogeneity at the genomic level has led to significant advancements in the treatment of solid tumors. Functional genomic alterations conferring sensitivity to targeted therapies can take many forms, and appropriate methods and tools are needed to detect these alterations. This review provides an update on genetic variability among solid tumors of similar histologic classification, using non-small cell lung cancer and melanoma as examples. We also discuss relevant technological platforms for discovery and diagnosis of clinically actionable variants and highlight the implications of specific genomic alterations for response to targeted therapy.

Figure 1. Examples of types of ‘driver’ genomic alterations found in cancer

Schematic representations of mutations known to occur in NSCLC, including point mutations, insertions/deletions, copy number variants, and structural variants. A, single nucleotide variant in exon 21 of EGFR (c.2573 T>G) encoding a substitution of arginine for leucine at codon 858 (L858R), and B, combined insertion/deletion (indel) in exon 19 of EGFR confer sensitivity to EGFR TKIs. Red indicates a nucleotide or amino acid that has been altered in the mutant form. C, amplification of MET and D, structural variants resulting in EML4-ALK fusions confer sensitivity to ALK TKIs.

Figure 2. Routine molecular subtyping of non-small cell lung cancers and melanomas

Frequency of mutations identified by SNaPshot genotyping through Vanderbilt’s PCMI from July 2010 to August 2013. A, frequency of lung-cancer associated mutations. 34 lung tumor specimens contained multiple mutations in the genes listed. *Note: ALK FISH performed separately. B, spectrum of mutations identified in EGFR. 27 lung tumor specimens contained multiple mutations in EGFR. C, frequency of melanoma-associated mutations. 23 melanoma specimens contained multiple mutations in the genes listed. D, spectrum of mutations identified in BRAF. 1 melanoma specimen contained multiple mutations in BRAF. N = number of tested specimens containing at least one mutation in the genes listed. Frequencies are listed as percentages of total mutations identified.

Figure 3. “BRAF-omas”: location and relative frequency of BRAF mutations across multiple different solid tumors

Indications for targeted therapies differ based on anatomical site (see text for details). A, percentage of lung adenocarcinoma, colon adenocarcinoma, melanoma, and thyroid carcinoma samples with documented BRAF mutations in the Catalog of Somatic Mutations in Cancer (COSMIC) database. B, codon location of non-synonymous BRAF mutations with frequencies of greater than 0.1% in COSMIC database for each tumor type listed in A.