Recurrent hyperactive ESR1 fusion proteins in endocrine therapy-resistant breast cancer

Background

Estrogen receptor-positive (ER-positive) metastatic breast cancer is often intractable due to endocrine therapy resistance. Although ESR1 promoter switching events have been associated with endocrine-therapy resistance, recurrent ESR1 fusion proteins have yet to be identified in advanced breast cancer.

Patients and methods

To identify genomic structural rearrangements (REs) including gene fusions in acquired resistance, we undertook a multimodal sequencing effort in three breast cancer patient cohorts: (i) mate-pair and/or RNAseq in 6 patient-matched primary-metastatic tumors and 51 metastases, (ii) high coverage (>500×) comprehensive genomic profiling of 287-395 cancer-related genes across 9542 solid tumors (5216 from metastatic disease), and (iii) ultra-high coverage (>5000×) genomic profiling of 62 cancer-related genes in 254 ctDNA samples. In addition to traditional gene fusion detection methods (i.e. discordant reads, split reads), ESR1 REs were detected from targeted sequencing data by applying a novel algorithm (copyshift) that identifies major copy number shifts at rearrangement hotspots.

Results

We identify 88 ESR1 REs across 83 unique patients with direct confirmation of 9 ESR1 fusion proteins (including 2 via immunoblot). ESR1 REs are highly enriched in ER-positive, metastatic disease and co-occur with known ESR1 missense alterations, suggestive of polyclonal resistance. Importantly, all fusions result from a breakpoint in or near ESR1 intron 6 and therefore lack an intact ligand binding domain (LBD). In vitro characterization of three fusions reveals ligand-independence and hyperactivity dependent upon the 3' partner gene. Our lower-bound estimate of ESR1 fusions is at least 1% of metastatic solid breast cancers, the prevalence in ctDNA is at least 10× enriched. We postulate this enrichment may represent secondary resistance to more aggressive endocrine therapies applied to patients with ESR1 LBD missense alterations.

Conclusions

Collectively, these data indicate that N-terminal ESR1 fusions involving exons 6-7 are a recurrent driver of endocrine therapy resistance and are impervious to ER-targeted therapies.

Blocks to thyroid cancer cell apoptosis can be overcome by inhibition of the MAPK and PI3K/AKT pathways

Current treatment for recurrent and aggressive/anaplastic thyroid cancers is ineffective. Novel targeted therapies aimed at the inhibition of the mutated oncoprotein BRAF^V600E have shown promise in vivo and in vitro but do not result in cellular apoptosis. TNF-related apoptosis-inducing ligand (TRAIL) induces apoptosis in a tumor-selective manner by activating the extrinsic apoptotic pathway. Here, we show that a TRAIL-R2 agonist antibody, lexatumumab, induces apoptosis effectively in some thyroid cancer cell lines (HTh-7, TPC-1 and BCPAP), while more aggressive anaplastic cell lines (8505c and SW1736) show resistance. Treatment of the most resistant cell line, 8505c, using lexatumumab in combination with the BRAF^V600E inhibitor, PLX4720, and the PI3K inhibitor, LY294002, (triple-drug combination) sensitizes the cells by triggering both the extrinsic and intrinsic apoptotic pathways in vitro as well as 8505c orthotopic thyroid tumors in vivo. A decrease in anti-apoptotic proteins, pAkt, Bcl-xL, Mcl-1 and c-FLIP, coupled with an increase in the activator proteins, Bax and Bim, results in an increase in the Bax to Bcl-xL ratio that appears to be critical for sensitization and subsequent apoptosis of these resistant cells. Our results suggest that targeting the death receptor pathway in thyroid cancer can be a promising strategy for inducing apoptosis in thyroid cancer cells, although combination with other kinase inhibitors may be needed in some of the more aggressive tumors initially resistant to apoptosis.

The Mouse Genome Database (MGD): integrating biology with the genome

The Mouse Genome Database (MGD) is one component of the Mouse Genome Informatics (MGI) system (http://www.informatics.jax.org), a community database resource for the laboratory mouse. MGD strives to provide a comprehensive knowledgebase about the mouse with experiments and data annotated from both literature and online sources. MGD curates and presents consensus and experimental data representations of genetic, genotype (sequence) and phenotype information including highly detailed reports about genes and gene products. Primary foci of integration are through representations of relationships between genes, sequences and phenotypes. MGD collaborates with other bioinformatics groups to curate a definitive set of information about the laboratory mouse and to build and implement the data and semantic standards that are essential for comparative genome analysis. Recent developments in MGD discussed here include an extensive integration of the mouse sequence data and substantial revisions in the presentation, query and visualization of sequence data.