Identification of Acquired Molecular Dependencies in Advanced Breast and Ovarian Cancers

Although individual cancers are driven by heterogeneous processes, cancer mortality has a near universal cause—therapy resistance, recurrence and eventual metastasis to vital organs. Despite great advancements in cancer therapies this past decade, outcomes in patients with advanced disease remain static. In these translational studies, using multiple cohorts of longitudinally collected tumor specimens, we test the hypothesis that relapsed cancers are molecularly distinct from primary disease and acquire druggable vulnerabilities throughout their life histories. As a preliminary study, a targeted gene expression analysis was performed to (1) determine differences in breast cancer (BrCa) intrinsic subtypes between primary tumors and matched brain metastases (BrM) and (2) explore if druggable targets are acquired in metastases. While BrM generally retain their intrinsic molecular subtypes, even after years of dormancy, nearly all gain expression of clinically actionable genes—most notably HER2 (35% of cases). To further assess molecular features acquired in metastases, exome-capture RNA-sequencing on decade-old and degraded tumor specimens was evaluated. Applying this technology, transcriptome-wide acquisitions in BrM were discovered, including highly recurrent expression gains in RET (38% of cases). Targeting RET or HER2 using in vitro, ex vivo, and in vivo models produced marked responses, suggesting RET and HER2-driven signaling as prime targets for patients with BrM. The same approach was applied to estrogen receptor [ER]-positive BrCa bone metastases, which discerned further site-specific acquisitions—such as shifts to Her2 and LumB phenotypes, temporally influenced expression evolution and druggable gains in CDK-Rb-E2F and FGFR-signaling pathways. To determine if these changes are consistent in non-metastatic samples, both RNA expression and DNA changes were assessed in a cohort of ER-positive local recurrences. Limited DNA-level changes, yet highly recurrent transcriptional remodeling events were observed—in particular, losses of ESR1, gains of NTRKs and upregulation of the cancer stem cell marker PROM1. Lastly, these findings were corroborated in ovarian cancer recurrences, where we show fusion RNA transcripts and recurrent outlier expression gains (NTRK2, INHBA and IGF1) are acquired in relapsed disease. Taken together, these studies establish that cancer recurrences commonly acquire multimodal and readily druggable molecular dependencies, unique from primary tumors, which may have profound clinical implications

Targeted Mutation Detection in Advanced Breast Cancer Using MammaSeq Identifies RET as a Potential Contributor to Breast Cancer Metastasis

The lack of any reported breast cancer specific diagnostic NGS tests inspired the development of MammaSeq, an amplicon based NGS panel built specifically for use in advanced breast cancer. In a pilot study to define the clinical utility of the panel, 46 solid tumor samples, plus an additional 14 samples of circulating-free DNA (cfDNA) from patients with advanced breast cancer were sequenced and analyzed using the OncoKB precision oncology database. We identified 26 clinically actionable variants (levels 1-3) annotated by the OncoKB precision oncology database, distributed across 20 out of 46 solid tumor cases (40%), and 4 clinically actionable mutations distributed across 4 samples in the 14 cfDNA sample cohort (29%). The mutation allele (MAF) frequencies of ESR1-D538G and FOXA1-Y175C mutations correlated with CA.27.29 levels in patient-matched blood, indicating that MAF may be a reliable marker for disease burden. Interestingly, 4 of the mutations found in metastatic samples occurred in the gene RET, an oncogenic receptor tyrosine kinase. In an orthogonal study, the lab has recently identified RET as one of the most recurrently upregulated genes in breast cancer brain metastases. Interestingly, the ligand for RET is the family of glial-cell derived neurotrophic factors (GDNF), a growth factor secreted by glial cells of the central nervous system. This lead to the hypothesis that RET overexpression facilitates breast cancer brain metastasis in response to the high levels of GDNF, while RET activating point mutations increase metastatic capacity without specific organ tropism. While the effect of GDNF treatment on proliferation in 2D was limited, in ultra-low attachment (ULA) plates we saw a significant increase in anchorage independent growth of MCF-7 cells. To determine if GDNF acts as a chemoattractant for RET positive BrCa cells, we utilized a transwell migration assay, with GDNF as the sole chemoattractant. When RET was overexpressed, there was a visual increase in cell migration. Together, these studies demonstrate the clinical feasibility of using MammaSeq to detect clinically actionable mutations in breast cancer patients, and provides provisional data supporting the investigation of RET signaling as a potentially targetable mediator of breast cancer brain metastasis

ADAM22/LGI1 complex as a new actionable target for breast cancer brain metastasis

Background: Metastatic breast cancer is a major cause of cancer-related deaths in woman. Brain metastasis is a common and devastating site of relapse for several breast cancer molecular subtypes, including oestrogen receptor-positive disease, with life expectancy of less than a year. While efforts have been devoted to developing therapeutics for extra-cranial metastasis, drug penetration of blood–brain barrier (BBB) remains a major clinical challenge. Defining molecular alterations in breast cancer brain metastasis enables the identification of novel actionable targets.Methods: Global transcriptomic analysis of matched primary and metastatic patient tumours (n = 35 patients, 70 tumour samples) identified a putative new actionable target for advanced breast cancer which was further validated in vivo and in breast cancer patient tumour tissue (n = 843 patients). A peptide mimetic of the target's natural ligand was designed in silico and its efficacy assessed in in vitro, ex vivo and in vivo models of breast cancer metastasis.Results: Bioinformatic analysis of over-represented pathways in metastatic breast cancer identified ADAM22 as a top ranked member of the ECM-related druggable genome specific to brain metastases. ADAM22 was validated as an actionable target in in vitro, ex vivo and in patient tumour tissue (n = 843 patients). A peptide mimetic of the ADAM22 ligand LGI1, LGI1MIM, was designed in silico. The efficacy of LGI1MIM and its ability to penetrate the BBB were assessed in vitro, ex vivo and in brain metastasis BBB 3D biometric biohybrid models, respectively. Treatment with LGI1MIM in vivo inhibited disease progression, in particular the development of brain metastasis.Conclusion: ADAM22 expression in advanced breast cancer supports development of breast cancer brain metastasis. Targeting ADAM22 with a peptide mimetic LGI1MIM represents a new therapeutic option to treat metastatic brain disease

Comparative analysis of the AIB1 interactome in breast cancer reveals MTA2 as a repressive partner which silences E-Cadherin to promote EMT and associates with a pro-metastatic phenotype

Funder: Breast Cancer Ireland GR 14-0883Abstract: Steroid regulated cancer cells use nuclear receptors and associated regulatory proteins to orchestrate transcriptional networks to drive disease progression. In primary breast cancer, the coactivator AIB1 promotes estrogen receptor (ER) transcriptional activity to enhance cell proliferation. The function of the coactivator in ER+ metastasis however is not established. Here we describe AIB1 as a survival factor, regulator of pro-metastatic transcriptional pathways and a promising actionable target. Genomic alterations and functional expression of AIB1 associated with reduced disease-free survival in patients and enhanced metastatic capacity in novel CDX and PDX ex-vivo models of ER+ metastatic disease. Comparative analysis of the AIB1 interactome with complementary RNAseq characterized AIB1 as a transcriptional repressor. Specifically, we report that AIB1 interacts with MTA2 to form a repressive complex, inhibiting CDH1 (encoding E-cadherin) to promote EMT and drive progression. We further report that pharmacological and genetic inhibition of AIB1 demonstrates significant anti-proliferative activity in patient-derived models establishing AIB1 as a viable strategy to target endocrine resistant metastasis. This work defines a novel role for AIB1 in the regulation of EMT through transcriptional repression in advanced cancer cells with a considerable implication for prognosis and therapeutic interventions

Comparative analysis of the AIB1 interactome in breast cancer reveals MTA2 as a repressive partner which silences E-Cadherin to promote EMT and associates with a pro-metastatic phenotype

Funder: Breast Cancer Ireland GR 14-0883Abstract: Steroid regulated cancer cells use nuclear receptors and associated regulatory proteins to orchestrate transcriptional networks to drive disease progression. In primary breast cancer, the coactivator AIB1 promotes estrogen receptor (ER) transcriptional activity to enhance cell proliferation. The function of the coactivator in ER+ metastasis however is not established. Here we describe AIB1 as a survival factor, regulator of pro-metastatic transcriptional pathways and a promising actionable target. Genomic alterations and functional expression of AIB1 associated with reduced disease-free survival in patients and enhanced metastatic capacity in novel CDX and PDX ex-vivo models of ER+ metastatic disease. Comparative analysis of the AIB1 interactome with complementary RNAseq characterized AIB1 as a transcriptional repressor. Specifically, we report that AIB1 interacts with MTA2 to form a repressive complex, inhibiting CDH1 (encoding E-cadherin) to promote EMT and drive progression. We further report that pharmacological and genetic inhibition of AIB1 demonstrates significant anti-proliferative activity in patient-derived models establishing AIB1 as a viable strategy to target endocrine resistant metastasis. This work defines a novel role for AIB1 in the regulation of EMT through transcriptional repression in advanced cancer cells with a considerable implication for prognosis and therapeutic interventions

Evolutionary Signatures amongst Disease Genes Permit Novel Methods for Gene Prioritization and Construction of Informative Gene-Based Networks

<div><p>Genes involved in the same function tend to have similar evolutionary histories, in that their rates of evolution covary over time. This coevolutionary signature, termed Evolutionary Rate Covariation (ERC), is calculated using only gene sequences from a set of closely related species and has demonstrated potential as a computational tool for inferring functional relationships between genes. To further define applications of ERC, we first established that roughly 55% of genetic diseases posses an ERC signature between their contributing genes. At a false discovery rate of 5% we report 40 such diseases including cancers, developmental disorders and mitochondrial diseases. Given these coevolutionary signatures between disease genes, we then assessed ERC's ability to prioritize known disease genes out of a list of unrelated candidates. We found that in the presence of an ERC signature, the true disease gene is effectively prioritized to the top 6% of candidates on average. We then apply this strategy to a melanoma-associated region on chromosome 1 and identify <i>MCL1</i> as a potential causative gene. Furthermore, to gain global insight into disease mechanisms, we used ERC to predict molecular connections between 310 nominally distinct diseases. The resulting “disease map” network associates several diseases with related pathogenic mechanisms and unveils many novel relationships between clinically distinct diseases, such as between Hirschsprung's disease and melanoma. Taken together, these results demonstrate the utility of molecular evolution as a gene discovery platform and show that evolutionary signatures can be used to build informative gene-based networks.</p></div

ERC gene prioritization compared to other methods.

<p>ERC gene prioritization compared to other methods.</p

Diseases with significant ERC at a 5% false discovery rate.

<p>Diseases with significant ERC at a 5% false discovery rate.</p

Nucleo-cytoplasmic localization domains regulate Krüppel-like factor 6 (KLF6) protein stability and tumor suppressor function.

The tumor suppressor KLF6 and its oncogenic cytoplasmic splice variant KLF6-SV1 represent a paradigm in cancer biology in that their antagonistic cancer functions are encoded within the same gene. As a consequence of splicing, KLF6-SV1 loses both the C-terminus C2H2 three zinc finger (ZF) domain, which characterizes all KLF proteins, as well as the adjacent 5' basic region (5BR), a putative nuclear localization signal (NLS). It has been hypothesized that this NLS is a functional domain critical to direct the distinct subcellular localization of the tumor suppressor and its splice variant.In this study, we demonstrate using EGFP fusion constructs that KLF6/KLF6-SV1 nucleo-cytoplasmic transport is not regulated by the 5' basic region but activated by a novel NLS encoded within the ZF domain, and a nuclear export signal (NES) located in the first 16 amino acids of the shared N-terminus sequence. We demonstrate KLF6 nuclear export to be Crm1-dependent. The dysregulation of nucleo-cytoplasmic transport when disrupting the KLF6 NLS using site-directed mutagenesis showed that its integrity is necessary for appropriate protein stability. Moreover, these mutations impaired transcriptional induction of two KLF6 well-characterized target genes, E-cadherin and p21, as shown by RT-PCR and luciferase promoter assays. The addition of the ZF domain to KLF6-SV1 results in its nuclear localization and a markedly decreased half-life similar to wild type KLF6.We describe the domains that control KLF6 nucleo-cytoplasmic shuttling and how these domains play a role in KLF6 protein half-life and tumor suppressor function. The results begin to mechanistically explain, at least in part, the opposing functions of KLF6 and KLF6-SV1 in cancer

ERC disease gene prioritization.

<p>The prioritization of the true disease gene relative to its chromosomal neighbors improves with a stronger ERC signal within the training set. A low p-value (x-axis) indicates strong ERC within a training set. Prioritization (y-axis) is presented as the proportion of candidate genes scoring lower than the true disease gene, i.e. higher represents better prioritization. The blue series is for diseases with training sets with 20 or fewer genes, representing the majority (70%) of OMIM diseases interrogated. The dotted green line is for those diseases with larger training sets.</p