Somatic or acquired mutations are non-heritable mutations that can arise spontaneously in somatic cells due to mistakes in DNA replication, or from exposure to mutagens like UV radiation or certain chemicals, and the changes resulting from these mutations can lead to cellular transformation. Copy number alterations (CNAs) are somatic changes to chromosome structure that result in gain or loss in copies of sections of DNA, and are prevalent in many types of cancer (2). Mutation of certain genes has a broad impact across a variety of cancers. For example, mutations in the cell cycle master regulator TP53, which has crucial roles in many other cellular processes including apoptosis and DNA damage repair, are observed in a host of cancers, including small-cell lung cancer (3), melanoma (4), breast cancer (5), and others. RB1, a tumor suppressor whose protein product plays roles in cell cycle, apoptosis, chromatin remodeling, and transcription (6), was initially described in retinoblastoma, but mutations in RB1 have also been linked to a variety of other cancers, including glioblastoma (7) and SCLC (3). Mutations in genes in the RAS and RAF families are also observed in a wide variety of cancers (8, 9). Genes harboring somatic mutations are frequently targets for therapy; for example, use of vemurafenib to inhibit BRAF has recently shown success in melanoma treatment (10), although less so in colon cancer (11), and tyrosine kinase inhibitors for EGFR have been in use for many years (12).
Linking less-common mutations involved in cancers to therapeutic outcome is also of critical importance. For example, a recent study that began with a bladder cancer patient with unusually successful responsiveness to everolimus identified an association in several more patients between TSC1 mutations and responsiveness to the drug. Conversely, cancers from patients with normal TSC1 continued to progress even under treatment with everolimus (13). Studies like this underline the importance of somatic mutations not only as tools for understanding the pathways involved in certain cancers, but also as biomarkers for directly determining whether a patient would respond to specific therapeutic agents. Research into somatic mutations and copy number alterations continues to yield potential insights into more effective tumor classification.
Diffuse large-cell B-cell lymphomas (DLBCL) often originate from germinal center B cells, and are known to harbor many somatic mutations and copy number alterations. This diversity has led to many attempts to classify tumors based on common characteristics, such as which cell types they originate from (germinal center B cells or activated B cells), or transcriptional profiling. Monti et al. recently uncovered a set of copy number changes in certain DLBCL tumors that affected apoptotic and cell cycle pathways, predicted patient response to conventional treatment with chemoimmunotherapy, and suggested a new treatment strategy for patients with a specific copy number alteration profile (14).
The team used SNP arrays and bioinformatics analysis to identify recurrent copy number changes in DLCBL. In addition to tumor recognition components, copy number changes largely affected three complementary pathways: cell cycle regulation, apoptosis, and p53 signaling (see figure Copy number alterations in cancer). Intriguingly, primary DLBCL tumors examined by the team had either "complex" CNA patterns, containing one of several combinations of the CNAs affecting these pathways, or "clean" tumors, which did not. Significantly, among patients on conventional R-CHOP therapy, only 62% patients with complex CNA patterns survived to 5 years, compared to 100% of patients with clean CNA patterns, suggesting that these alterations may be used as a prognostic indicator for therapeutic success. Pan-CDK inhibitors blocked growth of cell lines from patients with recurrent or refractory DLBCL, and also diminished tumor growth in xenograft models. By identifying several copy number changes, therefore, the team was able to identify a treatment target for patients with cancer that does not respond to current therapies.
Another important somatic mutation in DLBCL and follicular lymphoma (and other cancers) is the mutation of EZH2, a methyltransferase that methylates H3K27 as part of the polycomb repressive complex 2 (PRC2). Somatic mutations in its catalytic domain overactivate the enzyme, and a recent study proposed to target its methyltransferase activity to treat types of lymphoma with these mutations (15). A small-molecule EZH2 inhibitor, GSK126, was identified and tested, and showed success both with cell lines in vitro and with mouse xenograft models. Xenograft models for two DLBCL cell lines showed total inhibition of tumor growth when treated with GSK126, and even tumor regression at higher doses. Survival was significantly improved, and even if the dosage stopped or was given less frequently, tumors still did not resume growth, suggesting that this drug may be an effective treatment for cancers carrying activating mutations for EZH2.
Somatic mutations in BRAF and NRAS are frequent in melanoma, and vemurafenib, an inhibitor targeting BRAF, has been successful in the clinic. However, activating BRAF mutations are not universal, occurring in about half of cutaneous melanomas, so the search for other important mutations continues. Krauthammer and colleagues screened 147 primary or metastatic melanomas by exome sequencing to identify these alterations, dividing tumors by bodily location (sun-exposed areas, or the sun-shielded acral, mucosal, and uveal regions) (4).
The team identified many potentially important mutations at different sites, as well as copy number alterations. Based on these results, they were able to classify the tumors into three groups. The sun-shielded group had normal BRAF and NRAS and few somatic mutations in general (the median number of somatic mutations in sun-exposed versus sun-shielded tumors overall was 171 to 9), but many copy number amplifications, particularly for RICTOR, CCND1 and CDK4. The second group, seen more in older patients, also had normal BRAF and NRAS, but showed more somatic mutations and fewer copy number changes; these tumors were sun-exposed, and mutated genes included tumor suppressors like TP53 and PTPRK, as well as NF1 in ~30% of the tumors. The final group, also sun-exposed, were the BRAF- or NRAS-mutated tumors. These had copy number changes, like PTEN and/or CDKN2A loss in many, as well as somatic mutations in genes like PPP6C.
In sun-exposed tumors, RAC1P29S was one of the most frequent recurrent somatic mutations, and was associated with UV DNA damage. The team analyzed its presence in a new set of tumors, 217 of which were sun-exposed, and found that it was present in 9.2% of these samples and seemed to occur early on in tumor development, because it was present at about the same rate in primary and metastatic tumors. They saw a conformational change in the mutant by crystal structure analysis, and enhanced binding activity to its targets compared to wild-type. Moreover, expressing the mutant RAC1 in melanocytes led to more ERK phosphorylation as well as increased cell migration and proliferation, indicating that the mutation conferred gain-of-function consequences that could exacerbate melanoma.
The Cancer Genome Atlas Network recently published a study characterizing breast tumors at the molecular level, including epigenetics, miRNA, gene expression profiling, copy number changes, sequencing, and protein analysis (16). The study identified variations in the somatic mutations present in four mRNA expression subtypes (luminal A, luminal B, HER2-enriched, and basal-like), and also suggested potential therapeutic targets based on their findings.
Whole exome sequencing of tumors and bioinformatics analysis identified 35 genes that were significantly mutated in breast cancer, some already well-known to be involved such as PIK3CA, PTEN, AKT1, TP53, and CDKN1B, as well as others, including TBX3, RUNX1, PIK3R1, NF1, and CCND3. The mRNA expression subtypes bore major differences in mutated genes present, as well as in mutation type. For example, PIK3CA was mutated in a large portion of luminal and HER2-enriched tumors, but only 9% of basal-like tumors. A specific recurrent mutation in E545K, however, was mostly in the luminal A subtype, and luminal A tumors also showed higher mutation rates in MAP3K1 and MAP2K4. Basal-like and HER2-enriched tumors showed much higher rates of TP53 mutation compared to either of the luminal subtypes and higher overall mutation rates, but less diversity in mutated genes.
The authors suggest that future therapeutic targets for luminal cancers might include highly mutated genes in this subtype, such as PIK3CA or AKT1, or amplified genes such as FGF receptors, cyclin D1, and CDK4 and 6. For the HER2E mRNA subtype, suggested drug targets included mutated genes like PIK3CA, PTEN, and PIK3R1, as well as amplified genes like FGFRs, EGFR, CDK4, and cyclin D1. Finally, for basal-like tumors, they suggested targeting genes affected by copy number changes, such as PIK3CA, KRAS, BRAF, EGFR, PTEN, or INPP4B. Intriguingly, they noted that serous ovarian carcinomas and basal-like tumors show significant overlap in copy number gains and losses as well as other factors, suggesting a potential commonality in underlying cause and potential therapies for these cancers.
The mapping of somatic mutations and copy number changes in various types of cancer is a swiftly growing field, yielding new ways to classify tumors, novel target genes, and fresh opportunities for developing better therapies. Much more remains to be characterized in regard to how these mutations affect the pathways involved in cancer progression, as well as in finding easy, cost-effective ways to profile the mutations that individual patients carry in order to tailor their treatment.
QIAGEN has developed arrays of real-time PCR assays for somatic mutations and copy number changes, based on comprehensive bioinformatics and text-mining analysis in a variety of disease states, that provide fast, easy profiling of the most important mutations in cancer, other disorders, and various signaling pathways. These arrays, the qBiomarker Somatic Mutation PCR Arrays and qBiomarker Copy Number PCR Arrays, are an excellent way to classify research samples by the most relevant genomic alterations in your area of study.
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