NEW YORK (GenomeWeb) – New thyroid cancer mutations reported recently by members of The Cancer Genome Atlas consortium are already finding their way into at least one sequencing-based genotyping test used to distinguish between benign thyroid nodules and thyroid malignancies.
"Our study, since it rounds out the whole genomic and somatic landscape of thyroid cancer, is going to make that testing so much more informative and more powerful, because now we know more of the mutations to look for, basically," Thomas Giordano, director of the University of Michigan's molecular pathology research laboratory, told Clinical Sequencing News.
As they explained online in Cell on Thursday, Giordano and other members of the TCGA team performed an integrated genomic analysis of matched tumor and normal samples from 496 individuals with a common form of thyroid cancer called papillary thyroid carcinoma.
From exome, messenger RNA, and microRNA sequences, and with additional variant, methylation, and proteomic data, the team verified known thyroid cancer mutations in the PTC tumors, identified new driver mutations or fusions, and tracked down alterations associated with particularly poor PTC patient outcomes.
With this data, members of the team came up with new classification schemes for PTC tumors based on their expression signatures, mutational profiles, and network patterns. In particular, they noted that there are multiple molecular sub-types within groups of so-called "BRAF-like" tumors.
"We found nine different versions of BRAF fusions, which was a big eye-opener," Giordano said. "We knew that BRAF could rearrange, but we didn't realize quite how promiscuous BRAF was with other genes that form oncogenes."
"Together with a few insertions or deletions of BRAF, this really shows that there are multiple ways to mutate BRAF to form an oncogene," he explained.
Moreover, authors of the study argued that as the mutations and alterations in PTC and other thyroid tumors are more fully elaborated, molecular profiling should become increasingly informative as a tool for predicting thyroid cancer outcomes, targeting treatments, and determining which thyroid growths require treatment.
"Thyroid nodules are very common in the general population, particularly with increasing age," explained co-author Yuri Nikiforov, vice chair of molecular pathology at the University of Pittsburgh and director of the center's molecular and genomic pathology division. "There are probably 10 or 15 million people in the United States that have thyroid nodules, particularly over age 50 or 60, but a very small proportion of those are malignant."
Around 70 percent of the time, cytological testing of fine-needle aspirate samples can easily differentiate between benign and cancerous cells. In the remaining 25 percent to 30 percent of cases, though, cytological results are deemed indeterminate — making it difficult to decide whether treatment is required or warranted.
"Sometimes, the cytology interpretation or the pathology interpretation is not clear-cut," Giordano said. "So there's an opportunity to do molecular testing on those nodules to see if they have certain oncogenic mutations."
At the moment, most of the molecular tests available for thyroid cancer focus on that diagnostic problem, using gene expression patterns or mutation genotyping to diagnose cases with indeterminate cytology.
Because molecular profiling can offer a peek at the presence or absence of recurrent alterations in tumors, the unfolding collection of thyroid cancer driver mutations and gene fusions also appears poised to provide prognostic information and/or clues for treatment targeting in at least some thyroid cancer cases, Nikiforov noted.
He and colleagues at the University of Pittsburgh have come up with a next-generation sequencing assay called "ThyroSeq" that's designed to detect mutation hotspots and gene fusions in fine-needle aspirate samples from cytologically indeterminate thyroid nodules so that they can be classified as cancerous or benign.
The original version of ThyroSeq focused on mutation hotspots in thyroid cancer-related genes found through prior genetic studies, Nikiforov said. ThyroSeq version 2 contains additional gene fusions and point mutations identified through the TCGA team's analysis of PTC thyroid tumors, including newly described mutations in the EIF1AX gene.
The latter version of the test — highlighted in a study online in Cancer in September — reportedly has a sensitivity of 90 percent for diagnosing cancer in thyroid nodules that have types of indeterminate cytology known as follicular neoplasm or suspected follicular neoplasm.
An upcoming version of ThyroSeq will include copy number changes that the TCGA researchers identified in thyroid cancer. Once those fusions have been added to the next-generation sequencing test, Nikiforov explained, ThyroSeq should theoretically cover alterations that are present in around 97 percent to 98 percent of PTC tumors.
He and his team are in the process of performing genomic studies of additional thyroid cancer types, including follicular thyroid carcinoma.
Meanwhile, the molecular diagnostics firm Veracyte has developed an expression-based test called Afirma Gene Expression Classifier that uses a 142-gene expression signature to distinguish between benign and cancerous thyroid nodules tested by fine-needle aspirate when cytological testing turns up inconclusive results.
Earlier this year, Veracyte introduced another test known as the Malignancy Classifier for guiding treatment decisions in medullary thyroid cancer by determining BRAF V600E mutation status.
In a statement provided to CSN through a spokesperson, Veracyte President and CEO Bonnie Anderson commended the TCGA team for "adding to the scientific understanding of papillary thyroid cancer."
Anderson noted that the existing Afirma Gene Expression Classifier "is designed to answer the question of which thyroid nodules, deemed indeterminate by cytopathology, are actually benign … Genes that enable us to answer that question — which may be among those identified in the new study — are already included in our 142-gene signature."
Indeed, the University of Michigan's Giordano speculated that the new Cell study will have a more pronounced impact on diagnostic or prognostic tests that rely on genotyping rather than those that consider the gene expression signatures that stem from these thyroid cancer-related genetic glitches.
For their new analysis, Giordano and his colleagues focused on PTC, a form of thyroid cancer that arises from follicular cells in epithelial tissue of the thyroid.
The matched tumor and normal samples the TCGA team considered came from 324 individuals with classical-type PTC, 99 with follicular-variant PTC, 35 with tall cell variant PTC, nine with uncommon PTC variants, and 29 individuals whose tumors had not been annotated histologically.
The researchers did whole-exome sequencing on 402 of the 496 available tumor-normal pairs, generating an average exome coverage depth of 97-fold for the tumor samples and nearly 95-fold average coverage of matched normal samples.
To that, they added SNP array, RNA sequencing, microRNA sequencing, and array-based methylation profiling on 390 of the tumors to glean additional information on small insertion and deletions, gene fusions, copy number alterations, epigenetic patterns, and gene expression profiles in the PTC samples.
Overall, for example, the researchers saw relatively modest mutational burdens in the PTC tumors tested, with just 0.41 non-synonymous mutations turning up for every million bases of tumor DNA, on average — a lower somatic mutation frequency than those described in carcinomas from other tissue types.
Still, mutational burdens tended to increase in individuals with tumors prone to recurrence, in those whose tumors had the tall cell variant histology, and in older PTC patients, prompting the study's authors to argue that "age should be used as a continuous variable in risk stratification."
Their search for driver genes verified roles for known PTC contributors, including changes affecting members of the MAP kinase signaling pathway — particularly mutually exclusive mutations in the BRAF, NRAS, HRAS, or KRAS genes — and fusions involving RET and NTRK1 genes.
The analysis also implicated new driver genes in PTC, including EIF1AX, PPM1D, and CHEK2. In the 10 most rampantly mutated tumors, meanwhile, the team saw a tendency for mutations to turn up in genes coding for APOBEC proteins.
The team tracked down copy number changes in more than one-quarter of the PTC tumors tested — alterations that appeared somewhat more likely to occur in cases where other driver mutations or fusions were not identified. It also identified clusters of tumors with recurrent focal alterations and/or gains or losses affecting particular chromosomal arms.
Along with alterations that may be targetable for treatment, such as mutations to MAP kinase signaling pathway members or ALK gene fusions, the PTC analysis also highlighted mutations, fusions, and microRNA expression profiles that seem to point to particularly aggressive PTC cases.
The existing version of the ThyroSeq test already includes some of the gene mutations and fusions that are being considered as prognostic markers for PTC tumors, Nikiforov said.
While prognostic applications of the test are relatively new, he noted that molecular testing is expected to be especially useful for patients with aggressive tumors who may be eligible for specific clinical trials.