Hrq1/RECQL4 regulation is critical for preventing aberrant recombination during DNA intrastrand crosslink repair and is upregulated in breast cancer.

Human RECQL4 is a member of the RecQ family of DNA helicases and functions during DNA replication and repair. RECQL4 mutations are associated with developmental defects and cancer. Although RECQL4 mutations lead to disease, RECQL4 overexpression is also observed in cancer, including breast and prostate. Thus, tight regulation of RECQL4 protein levels is crucial for genome stability. Because mammalian RECQL4 is essential, how cells regulate RECQL4 protein levels is largely unknown. Utilizing budding yeast, we investigated the RECQL4 homolog, HRQ1, during DNA crosslink repair. We find that Hrq1 functions in the error-free template switching pathway to mediate DNA intrastrand crosslink repair. Although Hrq1 mediates repair of cisplatin-induced lesions, it is paradoxically degraded by the proteasome following cisplatin treatment. By identifying the targeted lysine residues, we show that preventing Hrq1 degradation results in increased recombination and mutagenesis. Like yeast, human RECQL4 is similarly degraded upon exposure to crosslinking agents. Furthermore, over-expression of RECQL4 results in increased RAD51 foci, which is dependent on its helicase activity. Using bioinformatic analysis, we observe that RECQL4 overexpression correlates with increased recombination and mutations. Overall, our study uncovers a role for Hrq1/RECQL4 in DNA intrastrand crosslink repair and provides further insight how misregulation of RECQL4 can promote genomic instability, a cancer hallmark.

Acquired mutations and transcriptional remodeling in long-term estrogen-deprived locoregional breast cancer recurrences.

BACKGROUND: Endocrine therapy resistance is a hallmark of advanced estrogen receptor (ER)-positive breast cancer. In this study, we aimed to determine acquired genomic changes in endocrine-resistant disease. METHODS: We performed DNA/RNA hybrid-capture sequencing on 12 locoregional recurrences after long-term estrogen deprivation and identified acquired genomic changes versus each tumor's matched primary. RESULTS: Despite being up to 7 years removed from the primary lesion, most recurrences harbored similar intrinsic transcriptional and copy number profiles. Only two genes, AKAP9 and KMT2C, were found to have single nucleotide variant (SNV) enrichments in more than one recurrence. Enriched mutations in single cases included SNVs within transcriptional regulators such as ARID1A, TP53, FOXO1, BRD1, NCOA1, and NCOR2 with one local recurrence gaining three PIK3CA mutations. In contrast to DNA-level changes, we discovered recurrent outlier mRNA expression alterations were common-including outlier gains in TP63 (n = 5 cases [42%]), NTRK3 (n = 5 [42%]), NTRK2 (n = 4 [33%]), PAX3 (n = 4 [33%]), FGFR4 (n = 3 [25%]), and TERT (n = 3 [25%]). Recurrent losses involved ESR1 (n = 5 [42%]), RELN (n = 5 [42%]), SFRP4 (n = 4 [33%]), and FOSB (n = 4 [33%]). ESR1-depleted recurrences harbored shared transcriptional remodeling events including upregulation of PROM1 and other basal cancer markers. CONCLUSIONS: Taken together, this study defines acquired genomic changes in long-term, estrogen-deprived disease; highlights the importance of longitudinal RNA profiling; and identifies a common ESR1-depleted endocrine-resistant breast cancer subtype with basal-like transcriptional reprogramming.

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.

Comprehensive evaluation of fusion transcript detection algorithms and a meta-caller to combine top performing methods in paired-end RNA-seq data.

BACKGROUND: Fusion transcripts are formed by either fusion genes (DNA level) or trans-splicing events (RNA level). They have been recognized as a promising tool for diagnosing, subtyping and treating cancers. RNA-seq has become a precise and efficient standard for genome-wide screening of such aberration events. Many fusion transcript detection algorithms have been developed for paired-end RNA-seq data but their performance has not been comprehensively evaluated to guide practitioners. In this paper, we evaluated 15 popular algorithms by their precision and recall trade-off, accuracy of supporting reads and computational cost. We further combine top-performing methods for improved ensemble detection. RESULTS: Fifteen fusion transcript detection tools were compared using three synthetic data sets under different coverage, read length, insert size and background noise, and three real data sets with selected experimental validations. No single method dominantly performed the best but SOAPfuse generally performed well, followed by FusionCatcher and JAFFA. We further demonstrated the potential of a meta-caller algorithm by combining top performing methods to re-prioritize candidate fusion transcripts with high confidence that can be followed by experimental validation. CONCLUSION: Our result provides insightful recommendations when applying individual tool or combining top performers to identify fusion transcript candidates.

Evolutionary signatures amongst disease genes permit novel methods for gene prioritization and construction of informative gene-based networks.

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 MCL1 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.

Forkhead Box Q1 Is a Novel Target of Breast Cancer Stem Cell Inhibition by Diallyl Trisulfide.

Diallyl trisulfide (DATS), a metabolic byproduct of garlic, is known to inhibit the growth of breast cancer cells in vitro and in vivo This study demonstrates that DATS targets breast cancer stem cells (bCSC). Exposure of MCF-7 and SUM159 human breast cancer cells to pharmacological concentrations of DATS (2.5 and 5 µm) resulted in dose-dependent inhibition of bCSC, as evidenced by a mammosphere assay and flow cytometric analysis of aldehyde dehydrogenase 1 (ALDH1) activity and the CD44(high)/CD24(low)/epithelial specific antigen-positive fraction. DATS-mediated inhibition of bCSC was associated with a decrease in the protein level of FoxQ1. Overexpression of FoxQ1 in MCF-7 and SUM159 cells increased ALDH1 activity and the CD49f(+)/CD24(-) fraction. Inhibition of ALDH1 activity and/or mammosphere formation upon DATS treatment was significantly attenuated by overexpression of FoxQ1. In agreement with these results, stable knockdown of FoxQ1 using small hairpin RNA augmented bCSC inhibition by DATS. Expression profiling for cancer stem cell-related genes suggested that FoxQ1 may negatively regulate the expression of Dachshund homolog 1 (DACH1), whose expression is lost in invasive breast cancer. Chromatin immunoprecipitation confirmed recruitment of FoxQ1 at the DACH1 promoter. Moreover, inducible expression of DACH1 augmented DATS-mediated inhibition of bCSC. Expression of FoxQ1 protein was significantly higher in triple-negative breast cancer cases compared with normal mammary tissues. Moreover, an inverse association was observed between FoxQ1 and DACH1 gene expression in breast cancer cell lines and tumors. DATS administration inhibited ALDH1 activity in vivo in SUM159 xenografts. These results indicate that FoxQ1 is a novel target of bCSC inhibition by DATS.

Morbid obesity resulting from inactivation of the ciliary protein CEP19 in humans and mice.

Obesity is a major public health concern, and complementary research strategies have been directed toward the identification of the underlying causative gene mutations that affect the normal pathways and networks that regulate energy balance. Here, we describe an autosomal-recessive morbid-obesity syndrome and identify the disease-causing gene defect. The average body mass index of affected family members was 48.7 (range = 36.7-61.0), and all had features of the metabolic syndrome. Homozygosity mapping localized the disease locus to a region in 3q29; we designated this region the morbid obesity 1 (MO1) locus. Sequence analysis identified a homozygous nonsense mutation in CEP19, the gene encoding the ciliary protein CEP19, in all affected family members. CEP19 is highly conserved in vertebrates and invertebrates, is expressed in multiple tissues, and localizes to the centrosome and primary cilia. Homozygous Cep19-knockout mice were morbidly obese, hyperphagic, glucose intolerant, and insulin resistant. Thus, loss of the ciliary protein CEP19 in humans and mice causes morbid obesity and defines a target for investigating the molecular pathogenesis of this disease and potential treatments for obesity and malnutrition.

Clinicogenomic characterization of inflammatory breast cancer.

Background: Inflammatory breast cancer (IBC) is a rare and poorly characterized type of breast cancer with an aggressive clinical presentation. The biological mechanisms driving the IBC phenotype are relatively undefined-partially due to a lack of comprehensive, large-scale genomic studies and limited clinical cohorts. Patients and Methods: A retrospective analysis of 2457 patients with metastatic breast cancer who underwent targeted tumor-only DNA-sequencing was performed at Dana-Farber Cancer Institute. Clinicopathologic, single nucleotide variant (SNV), copy number variant (CNV) and tumor mutational burden (TMB) comparisons were made between clinically confirmed IBC cases within a dedicated IBC center versus non-IBC cases. Results: Clinicopathologic differences between IBC and non-IBC cases were consistent with prior reports-including IBC being associated with younger age at diagnosis, higher grade, and enrichment with hormone receptor (HR)-negative and HER2-positive tumors. The most frequent somatic alterations in IBC involved TP53 (72%), ERBB2 (32%), PIK3CA (24%), CCND1 (12%), MYC (9%), FGFR1 (8%) and GATA3 (8%). A multivariate logistic regression analysis revealed a significant enrichment in TP53 SNVs in IBC; particularly in HER2-positive and HR-positive disease which was associated with worse outcomes. Tumor mutational burden (TMB) did not differ substantially between IBC and non-IBC cases and a pathway analysis revealed an enrichment in NOTCH pathway alterations in HER2-positive disease. Conclusion: Taken together, this study provides a comprehensive, clinically informed landscape of somatic alterations in a large cohort of patients with IBC. Our data support higher frequency of TP53 mutations and a potential enrichment in NOTCH pathway activation-but overall; a lack of major genomic differences. These results both reinforce the importance of TP53 alterations in IBC pathogenesis as well as their influence on clinical outcomes; but also suggest additional analyses beyond somatic DNA-level changes are warranted.

Who's driving anyway? Herculean efforts to identify the drivers of breast cancer.

The continuing advancement of sequencing technologies has made the systematic identification of all driving somatic events in cancer a possibility. In the June 2012 issue of Nature, five papers show some significant headway in this endeavor, each a herculean effort of genome sequencing, and transcriptome and copy number analysis resulting in data on thousands of breast cancers. Integrating these massive datasets, the authors were able to further subdivide breast cancer and identify a number of novel driver genes. While the studies represent a leap forward in describing the genomics of breast cancer, and clearly highlight the tremendous diversity between tumors, the studies only scrape the surface of molecular changes in breast tumors, with more granularity to come from the study of epigenomics, single cell sequencing, and so on. The immediate importance of the data to clinical care is currently unknown, and will depend upon detailed identification and functional analysis of driver mutations.

HER2-low inflammatory breast cancer: Clinicopathologic features and prognostic implications.

BACKGROUND: HER2)-low expression is a predictive biomarker for novel anti-HER2 antibody-drug conjugates. However, little is known about its clinical significance in inflammatory breast cancer (IBC). METHODS: Patients diagnosed with HER2-negative IBC between December 1999 and December 2020 were identified from the Dana-Farber Cancer Institute IBC registry. Patients were divided into HER2-low (IHC 1+ or 2+/ISH-) and HER2-zero (IHC 0), comparing clinicopathologic features and disease outcomes between the two subgroups. RESULTS: The study included 276 patients. Among patients with stage III (n = 209) and stage IV (n = 67) IBC, 54% and 39% had HER2-low tumours, respectively. Oestrogen receptor (ER)-expressing tumours were more common in patients with HER2-low versus HER2-zero stage III IBC (65% versus 38%, p < 0.01). Among stage III patients undergoing surgery (n = 182), pathologic complete response (pCR) rates were higher for HER2-zero versus HER2-low IBC (11% versus 6%, OR: 1.8, 95%CI:0.6-5.3), but minimal differences persisted when separately analysing pCR by ER status. Similar invasive disease-free survival (iDFS) outcomes were observed among ER-positive HER2-zero versus HER2-low IBC (48-month iDFS: 63% versus 63%, HR: 1.10, 95%CI:0.57-2.13) and ER-negative HER2-zero versus HER2-low IBC (48-month iDFS: 28% versus 25%, HR: 1.19, 95%CI:0.69-2.04). Differences in overall survival (OS) were small, both among ER-positive HER2-zero versus HER2-low IBC (48-month OS: 80% versus 81%, HR: 0.82, 95%CI:0.39-1.73) and ER-negative HER2-zero versus HER2-low IBC (48-month OS: 34% versus 47%, HR: 1.34, 95%CI: 0.74-2.41). CONCLUSIONS: Marginal differences in clinicopathologic features and outcomes were observed in HER2-low versus HER2-zero IBC when controlling for ER status, not supporting the definition of HER2-low as a distinct subtype of IBC.