Cancers have heterogeneous genetic profiles across and within tissue types resulting in a highly complex set of diseases. Genetic changes that are acquired in one’s lifetime are called somatic mutations, as opposed to inherited variations. These somatic mutations occur throughout the human genome and can have a variety of molecular, cellular and clinical effects. To understand the effect of these mutations, the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) have performed whole-genome sequencing of tumor-normal pairs to catalog somatic mutations across many different types of cancer. These and other studies have identified several hundred genes where somatic mutations frequently occur and are thus implicated in driving cancer development. However, previous studies have primarily focused on somatic mutations in coding regions of the human genome, the regions that encode proteins, which amount to less than 2% of the entire genome. Somatic mutations occurring in the remaining 98% of the noncoding genome have largely gone uncharacterized.

So, what functional effect, if any, do the millions of noncoding somatic mutations have? Do these mutations also have implications in cancer development?

One challenge to studying noncoding mutations and their role in cancer development is that there is not an easy way to associate these mutations to cellular functions that can be observed or measured. Another challenge is to harness enough statistical power to overcome the “noise” created by mutations with no effect. Previous studies have identified a few examples of somatic noncoding mutations that alter gene expression levels (Melton et al., 2015; Weinhold et al., 2014; Fredriksson et al., 2014). The most well-known examples are mutations in the promoter of telomerase reverse transcriptase (TERT) leading to increased levels of expression (Huang et al., 2013). These mutations occur frequently enough that they have been repeatedly identified. However, most other somatic noncoding mutations reported to impact gene expression levels in cancer have not been verified in other studies.

Now, researchers from the University of California San Diego School of Medicine have found 193 loci in which noncoding mutations are associated with changes in gene expression levels. Dr. Wei Zhang, a postdoctoral fellow in Dr. Trey Ideker’s laboratory, integrated recent reference maps linking noncoding loci to known “target” genes (ENCODE Project Consortium et al., 2012; Roadmap Epigenomics Consortium et al., 2015) along with whole genome sequences of over 900 patients from TCGA. These samples spanned 22 different types of cancer and were used to identify 35 million single nucleotide variants (SNVs) in noncoding DNA present in the patient’s tumor but not their normal sample. Dr. Zhang then sought to identify which of these many somatic mutations were associated with changes in target gene expression levels. The resulting 193 loci are called somatic expression quantitative trait loci (eQTLs) and include the most documented somatic eQTL, TERT.

But are these somatic eQTLs drivers of gene expression changes or a result of those changes? For example, a somatic eQTL upstream of the DAAM1 gene, which was only observed in metastatic melanomas, was associated with an increase in DAAM1 mRNA expression levels. Interestingly, other studies have shown that increases in DAAM1 expression promote metastasis. So, is the somatic eQTL upstream of DAAM1 a cause or an effect of the increased gene expression? To answer this question, researchers in Dr. Ideker’s lab created plasmids in which the noncoding regions where the somatic mutations reside were placed upstream of the gene encoding the green fluorescent protein (GFP). If there were a causal relationship between these somatic mutations and gene expression, then a change in GFP levels would be observed between the wild type sequence and the mutant sequence. By inserting the plasmids into melanoma, sarcoma and breast cancer cell lines, and allowing the cells to transcribe and express the GFP gene, researchers were able to measure the abundance of GFP. In each of these cell lines, the mutated regulatory element caused significantly higher levels of GFP expression than wild type, thus establishing the causal relationship between the somatic eQTL and the increase in expression. In a separate set of experiments, researchers found that cells overexpressing DAAM1 migrated with greater persistence and invaded for longer distances than wild type cells. This finding suggests that increased DAAM1 expression allows cells to invade their local microenvironment more efficiently, and links this somatic eQTL to DAAM1 overexpression and cell invasion.

These newly discovered somatic eQTLs provide an exciting and potentially useful resource towards the development of personalized medicine. Current efforts to stratify patients into distinct groups with different therapeutic needs have to date only used somatic mutation profiles in coding regions of the DNA or gene expression data. Further work by the Ideker Lab revealed that noncoding mutations can also impact patient stratification. By integrating the somatic eQTL profiles of these patients along with their mutations in the coding regions of known oncogenes and tumor suppressors, Dr. Ideker’s team was able to group patients into 10 subtypes with distinct and significant clinical outcomes. Four of the subtypes contained a large number of patients with many noncoding mutations. One subtype that included many patients with noncoding mutations affecting expression levels of TERT was the most aggressive, with a disease-free survival period averaging only 13 months. It is therefore evident that incorporating noncoding somatic mutations with functional effects into our studies is a step towards understanding a widespread feature of cancer biology and achieving effective personalized medicine.

Reference: Zhang W, et al. A global transcriptional network connecting noncoding mutations to changes in tumor gene expression. Nat Genet. 2018 Apr;50(4):613-620. doi: http://dx.doi.org/10.1038/s41588-018-0091-2

Bibliography:

Melton C, Reuter JA, Spacek DV, Snyder M. Recurrent somatic mutations in regulatory regions of human cancer genomes. Nat Genet. 2015 Jul;47(7):710-6. doi: http://dx.doi.org/10.1038/ng.3332

Weinhold N, et al. Genome-wide analysis of noncoding regulatory mutations in cancer. Nat Genet. 2014 Nov;46(11):1160-5. doi: http://dx.doi.org/10.1038/ng.3101

Fredriksson NJ, et al. Systematic analysis of noncoding somatic mutations and gene expression alterations across 14 tumor types. Nat Genet. 2014 Dec;46(12):1258-63. doi: 10.1038/ng.3141.

Huang FW, et al. Highly recurrent TERT promoter mutations in human melanoma. Science. 2013 Feb 22;339(6122):957-9. doi: http://dx.doi.org/10.1126/science.1229259

NCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012 Sep 6;489(7414):57-74. doi: http://dx.doi.org/10.1038/nature11247

Roadmap Epigenomics Consortium, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015 Feb 19;518(7539):317-30. doi: http://dx.doi.org/10.1038/nature14248

Ana Bojórquez-Gómez y Jason Kreisberg

Department of Medicine, University of California, San Diego, La Jolla, CA, USA

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