Genome engineering for estrogen receptor mutations reveals differential responses to anti-estrogens and new prognostic gene signatures for breast cancer.

Mutations in the estrogen receptor (ESR1) gene are common in ER-positive breast cancer patients who progress on endocrine therapies. Most mutations localise to just three residues at, or near, the C-terminal helix 12 of the hormone binding domain, at leucine-536, tyrosine-537 and aspartate-538. To investigate these mutations, we have used CRISPR-Cas9 mediated genome engineering to generate a comprehensive set of isogenic mutant breast cancer cell lines. Our results confirm that L536R, Y537C, Y537N, Y537S and D538G mutations confer estrogen-independent growth in breast cancer cells. Growth assays show mutation-specific reductions in sensitivities to drugs representing three classes of clinical anti-estrogens. These differential mutation- and drug-selectivity profiles have implications for treatment choices following clinical emergence of ER mutations. Our results further suggest that mutant expression levels may be determinants of the degree of resistance to some anti-estrogens. Differential gene expression analysis demonstrates up-regulation of estrogen-responsive genes, as expected, but also reveals that enrichment for interferon-regulated gene expression is a common feature of all mutations. Finally, a new gene signature developed from the gene expression profiles in ER mutant cells predicts clinical response in breast cancer patients with ER mutations.

Aging, Bone Marrow and Next-Generation Sequencing (NGS): Recent Advances and Future Perspectives.

The aging of bone marrow (BM) remains a very imperative and alluring subject, with an ever-increasing interest among fellow scientists. A considerable amount of progress has been made in this field with the established 'hallmarks of aging' and continued efforts to investigate the age-related changes observed within the BM. Inflammaging is considered as a low-grade state of inflammation associated with aging, and whilst the possible mechanisms by which aging occurs are now largely understood, the processes leading to the underlying changes within aged BM remain elusive. The ability to identify these changes and detect such alterations at the genetic level are key to broadening the knowledgebase of aging BM. Next-generation sequencing (NGS) is an important molecular-level application presenting the ability to not only determine genomic base changes but provide transcriptional profiling (RNA-seq), as well as a high-throughput analysis of DNA-protein interactions (ChIP-seq). Utilising NGS to explore the genetic alterations occurring over the aging process within alterative cell types facilitates the comprehension of the molecular and cellular changes influencing the dynamics of aging BM. Thus, this review prospects the current landscape of BM aging and explores how NGS technology is currently being applied within this ever-expanding field of research.

Plasma cell-free DNA (cfDNA) as a predictive and prognostic marker in patients with metastatic breast cancer.

BACKGROUND: Breast cancer (BC) is the most common cancer in women, and despite the introduction of new screening programmes, therapies and monitoring technologies, there is still a need to develop more useful tests for monitoring treatment response and to inform clinical decision making. The purpose of this study was to compare circulating cell-free DNA (cfDNA) and circulating tumour cells (CTCs) with conventional breast cancer blood biomarkers (CA15-3 and alkaline phosphatase (AP)) as predictors of response to treatment and prognosis in patients with metastatic breast cancer (MBC). METHODS: One hundred ninety-four female patients with radiologically confirmed MBC were recruited to the study. Total cfDNA levels were determined by qPCR and compared with CELLSEARCH® CTC counts and CA15-3 and alkaline phosphatase (AP) values. Blood biomarker data were compared with conventional tumour markers, treatment(s) and response as assessed by RECIST and survival. Non-parametric statistical hypothesis tests were used to examine differences, correlation analysis and linear regression to determine correlation and to describe its effects, logistic regression and receiver operating characteristic curve (ROC curve) to estimate the strength of the relationship between biomarkers and clinical outcomes and value normalization against standard deviation to make biomarker values comparable. Kaplan-Meier estimator and Cox regression models were used to assess survival. Univariate and multivariate models were performed where appropriate. RESULTS: Multivariate analysis showed that both the amount of total cfDNA (p value = 0.024, HR = 1.199, CI = 1.024-1.405) and the number of CTCs (p value = 0.001, HR = 1.243, CI = 1.088-1.421) are predictors of overall survival (OS), whereas total cfDNA levels is the sole predictor for progression-free survival (PFS) (p value = 0.042, HR = 1.193, CI = 1.007-1.415) and disease response when comparing response to non-response to treatment (HR = 15.917, HR = 12.481 for univariate and multivariate analysis, respectively). Lastly, combined analysis of CTCs and cfDNA is more informative than the combination of two conventional biomarkers (CA15-3 and AP) for prediction of OS. CONCLUSION: Measurement of total cfDNA levels, which is a simpler and less expensive biomarker than CTC counts, is associated with PFS, OS and response in MBC, suggesting potential clinical application of a cheap and simple blood-based test.

Personalized Detection of Circulating Tumor DNA Antedates Breast Cancer Metastatic Recurrence.

PURPOSE: Up to 30% of patients with breast cancer relapse after primary treatment. There are no sensitive and reliable tests to monitor these patients and detect distant metastases before overt recurrence. Here, we demonstrate the use of personalized circulating tumor DNA (ctDNA) profiling for detection of recurrence in breast cancer. EXPERIMENTAL DESIGN: Forty-nine primary patients with breast cancer were recruited following surgery and adjuvant therapy. Plasma samples (n = 208) were collected every 6 months for up to 4 years. Personalized assays targeting 16 variants selected from primary tumor whole-exome data were tested in serial plasma for the presence of ctDNA by ultradeep sequencing (average >100,000X). RESULTS: Plasma ctDNA was detected ahead of clinical or radiologic relapse in 16 of the 18 relapsed patients (sensitivity of 89%); metastatic relapse was predicted with a lead time of up to 2 years (median, 8.9 months; range, 0.5-24.0 months). None of the 31 nonrelapsing patients were ctDNA-positive at any time point across 156 plasma samples (specificity of 100%). Of the two relapsed patients who were not detected in the study, the first had only a local recurrence, whereas the second patient had bone recurrence and had completed chemotherapy just 13 days prior to blood sampling. CONCLUSIONS: This study demonstrates that patient-specific ctDNA analysis can be a sensitive and specific approach for disease surveillance for patients with breast cancer. More importantly, earlier detection of up to 2 years provides a possible window for therapeutic intervention.

Abdominal aortic aneurysm-an independent disease to atherosclerosis?

Atherosclerosis and abdominal aortic aneurysms (AAAs) are multifactorial and polygenic diseases with known environmental and genetic risk factors that contribute toward disease development. Atherosclerosis represents an important independent risk factor for AAA, as people with AAA often have atherosclerosis. Studies have shown that comorbidity is usually between ~25% and 55%, but it is still not fully known whether this association is causal or a result of common shared risk profiles. Most recent epidemiological, clinical, and biological evidence suggests that the two pathologies are more distinct than traditionally thought. For instance diabetes mellitus, hypercholesterolemia, and obesity are high risk for atherosclerosis development but are not as pronounced in AAA, whereas smoking, gender, and ethnicity are particularly high risk for AAA but less so for atherosclerosis. In addition, genetic and epigenetic studies have identified independent risk loci involved in AAA susceptibility that are not associated with other cardiovascular diseases, and research on important common cardiovascular biomarkers has illustrated discrepancies in those with AAA.

The potential role of DNA methylation in the pathogenesis of abdominal aortic aneurysm.

Abdominal aortic aneurysm (AAA) is characterised by the chronic degradation and gradual, irreversible dilation of the abdominal aorta. Smoking, genetics, male sex and increased age are major factors associated with developing AAA. Rupture contributes to around 2% of deaths in all Caucasians over 65, and there is no pharmaco-therapeutic treatment. Methylation is an epigenetic modification to DNA, where a methyl group is added to a cytosine base 5' to a guanine (CpG dinucleotide). Methylation patterns are long term, inherited signatures that can induce changes in gene transcription, and can be affected by both genetic and environmental factors. Methylation changes are involved in hypertension and atherosclerosis, both of which are risk factors of, and often coexist with AAA. Extra-cellular matrix degradation and inflammation, both important pathological hallmarks of AAA, are also promoted by changes in CpG methylation in other diseases. Additionally, the adverse effects of smoking and ageing take place largely through epigenetic manipulation of the genome. Every factor associated with AAA appears to be associated with DNA methylation, yet no direct evidence confirms this. Future work to identify a link between global methylation and AAA, and differentially methylated regions may reveal valuable insight. The identification of a common epigenetic switching process may also signify a promising future for AAA pharmaco-therapeutic strategies. Epigenetic therapies are being designed to target pathogenic CpG methylation changes in other diseases, and it is feasible that these therapies may also be applicable to AAA in the future.