Acquired resistance to oxaliplatin is not directly associated with increased resistance to DNA damage in SK-N-ASrOXALI4000, a newly established oxaliplatin-resistant sub-line of the neuroblastoma cell line SK-N-AS

The formation of acquired drug resistance is a major reason for the failure of anti-cancer therapies after initial response. Here, we introduce a novel model of acquired oxaliplatin resistance, a sub-line of the non-MYCN-amplified neuroblastoma cell line SK-N-AS that was adapted to growth in the presence of 4000 ng/mL oxaliplatin (SK-N-ASrOXALI4000). SK-N-ASrOXALI4000 cells displayed enhanced chromosomal aberrations compared to SK-N-AS, as indicated by 24-chromosome fluorescence in situ hybridisation. Moreover, SK-N-ASrOXALI4000 cells were resistant not only to oxaliplatin but also to the two other commonly used anti-cancer platinum agents cisplatin and carboplatin. SK-N-ASrOXALI4000 cells exhibited a stable resistance phenotype that was not affected by culturing the cells for 10 weeks in the absence of oxaliplatin. Interestingly, SK-N-ASrOXALI4000 cells showed no cross resistance to gemcitabine and increased sensitivity to doxorubicin and UVC radiation, alternative treatments that like platinum drugs target DNA integrity. Notably, UVC-induced DNA damage is thought to be predominantly repaired by nucleotide excision repair and nucleotide excision repair has been described as the main oxaliplatin-induced DNA damage repair system. SK-N-ASrOXALI4000 cells were also more sensitive to lysis by influenza A virus, a candidate for oncolytic therapy, than SK-N-AS cells. In conclusion, we introduce a novel oxaliplatin resistance model. The oxaliplatin resistance mechanisms in SK-N-ASrOXALI4000 cells appear to be complex and not to directly depend on enhanced DNA repair capacity. Models of oxaliplatin resistance are of particular relevance since research on platinum drugs has so far predominantly focused on cisplatin and carboplatin

Origin of reduced magnetization and domain formation in small magnetite nanoparticles

The structural, chemical, and magnetic properties of magnetite nanoparticles are compared. Aberration corrected scanning transmission electron microscopy reveals the prevalence of antiphase boundaries in nanoparticles that have significantly reduced magnetization, relative to the bulk. Atomistic magnetic modelling of nanoparticles with and without these defects reveals the origin of the reduced moment. Strong antiferromagnetic interactions across antiphase boundaries support multiple magnetic domains even in particles as small as 12–14 nm

Synergistic effects of various Her inhibitors in combination with IGF-1R, C-MET and Src targeting agents in breast cancer cell lines

Introduction: Overexpression of the receptor tyrosine kinase HER2 has been reported in around 25% of human breast cancers, usually indicating a poor prognosis. As a result, HER2 has become a popular target for therapy. However, despite recent advances in HER2 targeted therapy, many patients still experience primary and secondary resistance to such treatments. It is therefore important to understand the underlying mechanism of resistance and to develop more effective therapeutic interventions for breast cancer. Methods: The sensitivity of a panel of seven breast cancer cell lines to treatment with various types HER-family inhibitors alone, or in combination with a selection of other tyrosine kinase inhibitors (TKIs) or chemotherapeutic agents was determined using the Sulforhodamine B colorimetric assay. Receptor expression, cell-cycle distribution, cell signalling and cell migration were determined using flow cytometry, Western blot and Incucyte Zoom Live-Cell Analysis System respectively. Results: Overall, breast cancer cells were more sensitive to treatment with the irreversible pan-HER family inhibitors, particularly afatinib and neratinib, than treatment with the first-generation reversible inhibitors. Of three HER-2 overexpressing cell lines in this panel, SKBr3 and BT474 were highly sensitive to treatment with HER-family inhibitors (IC50s as low as 3 nM), while MDA-MB-453 was relatively resistant (lowest IC50 = 0.11 μM). When the HER-family inhibitors were combined with other agents such as NVP-AEW541 (an IGF-1R inhibitor), dasatinib (a Src inhibitor) or crizotinib (a c-Met/ALK inhibitor), such combination produced synergistic effects in some of the cell lines examined. Interestingly, co-targeting of Src and HER-family members in MDA-MB-453 cells led to synergistic growth inhibition, suggesting the importance of Src in mediating resistance to HER2-targeting agents. Finally, treatment with the irreversible HER family blockers and dasatinib were also most effective at inhibiting the migration of breast cancer cells. Conclusion: We concluded that the irreversible inhibitors of HER-family members are generally more effective at inhibiting growth, downstream signalling and migration compared with reversible inhibitors, and that combining HER-family inhibitors with other TKIs such as dasatinib may have therapeutic advantages in certain breast cancer subtypes and warrants further investigation

Identification of single nucleotide variants using position-specific error estimation in deep sequencing data.

Background Targeted deep sequencing is a highly effective technology to identify known and novel single nucleotide variants (SNVs) with many applications in translational medicine, disease monitoring and cancer profiling. However, identification of SNVs using deep sequencing data is a challenging computational problem as different sequencing artifacts limit the analytical sensitivity of SNV detection, especially at low variant allele frequencies (VAFs).Methods To address the problem of relatively high noise levels in amplicon-based deep sequencing data (e.g. with the Ion AmpliSeq technology) in the context of SNV calling, we have developed a new bioinformatics tool called AmpliSolve. AmpliSolve uses a set of normal samples to model position-specific, strand-specific and nucleotide-specific background artifacts (noise), and deploys a Poisson model-based statistical framework for SNV detection.Results Our tests on both synthetic and real data indicate that AmpliSolve achieves a good trade-off between precision and sensitivity, even at VAF below 5% and as low as 1%. We further validate AmpliSolve by applying it to the detection of SNVs in 96 circulating tumor DNA samples at three clinically relevant genomic positions and compare the results to digital droplet PCR experiments.Conclusions AmpliSolve is a new tool for in-silico estimation of background noise and for detection of low frequency SNVs in targeted deep sequencing data. Although AmpliSolve has been specifically designed for and tested on amplicon-based libraries sequenced with the Ion Torrent platform it can, in principle, be applied to other sequencing platforms as well. AmpliSolve is freely available at https://github.com/dkleftogi/AmpliSolve

Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

BACKGROUND: Targeted deep sequencing is a highly effective technology to identify known and novel single nucleotide variants (SNVs) with many applications in translational medicine, disease monitoring and cancer profiling. However, identification of SNVs using deep sequencing data is a challenging computational problem as different sequencing artifacts limit the analytical sensitivity of SNV detection, especially at low variant allele frequencies (VAFs). METHODS: To address the problem of relatively high noise levels in amplicon-based deep sequencing data (e.g. with the Ion AmpliSeq technology) in the context of SNV calling, we have developed a new bioinformatics tool called AmpliSolve. AmpliSolve uses a set of normal samples to model position-specific, strand-specific and nucleotide-specific background artifacts (noise), and deploys a Poisson model-based statistical framework for SNV detection. RESULTS: Our tests on both synthetic and real data indicate that AmpliSolve achieves a good trade-off between precision and sensitivity, even at VAF below 5% and as low as 1%. We further validate AmpliSolve by applying it to the detection of SNVs in 96 circulating tumor DNA samples at three clinically relevant genomic positions and compare the results to digital droplet PCR experiments. CONCLUSIONS: AmpliSolve is a new tool for in-silico estimation of background noise and for detection of low frequency SNVs in targeted deep sequencing data. Although AmpliSolve has been specifically designed for and tested on amplicon-based libraries sequenced with the Ion Torrent platform it can, in principle, be applied to other sequencing platforms as well. AmpliSolve is freely available at https://github.com/dkleftogi/AmpliSolve

Integrative molecular and functional profiling of ERBB2-amplified breast cancers identifies new genetic dependencies.

Overexpression of the receptor tyrosine kinase ERBB2 (also known as HER2) occurs in around 15% of breast cancers and is driven by amplification of the ERBB2 gene. ERBB2 amplification is a marker of poor prognosis, and although anti-ERBB2-targeted therapies have shown significant clinical benefit, de novo and acquired resistance remains an important problem. Genomic profiling has demonstrated that ERBB2+ve breast cancers are distinguished from ER+ve and 'triple-negative' breast cancers by harbouring not only the ERBB2 amplification on 17q12, but also a number of co-amplified genes on 17q12 and amplification events on other chromosomes. Some of these genes may have important roles in influencing clinical outcome, and could represent genetic dependencies in ERBB2+ve cancers and therefore potential therapeutic targets. Here, we describe an integrated genomic, gene expression and functional analysis to determine whether the genes present within amplicons are critical for the survival of ERBB2+ve breast tumour cells. We show that only a fraction of the ERBB2-amplified breast tumour lines are truly addicted to the ERBB2 oncogene at the mRNA level and display a heterogeneous set of additional genetic dependencies. These include an addiction to the transcription factor gene TFAP2C when it is amplified and overexpressed, suggesting that TFAP2C represents a genetic dependency in some ERBB2+ve breast cancer cell

Plasma AR Alterations and Timing of Intensified Hormone Treatment for Prostate Cancer: the STAMPEDE Phase 3 Randomized Clinical Trial

We previously reported that abiraterone acetate and prednisolone (hereafter abiraterone) added at initiation of androgen deprivation therapy (ADT) improved survival of metastatic and very high-risk locally advanced prostate cancer and that combining with enzalutamide did not change efficacy.1 Using next-generation sequencing on plasma DNA, we previously showed that genomic alterations of the androgen receptor (AR) gene contribute to resistance to abiraterone or enzalutamide when initiated for metastatic castration-resistant prostate cancer after progression with ADT alone.2 It is unknown whether hormone intensification at start of ADT alters selection of AR alterations within the gene body and/or enhancer region.

Plasma Androgen Receptor and Serum Chromogranin a in Advanced Prostate Cancer

Recently, mixed forms between adenocarcinoma and neuroendocrine prostate cancer (NEPC) have emerged that are characterized by persistent androgen receptor (AR)-signalling and elevated chromogranin A (CgA) levels. The main aim of this study was to analyze castration-resistant prostate cancer (CRPC) patients treated with abiraterone or enzalutamide, assessing progression-free/overall survival (PFS/OS) in association with circulating AR and CgA. AR aberrations were analyzed by droplet digital PCR in pre-treatment plasma samples collected from two biomarker protocols [197 patients from a retrospective study (REC 2192/2013) and 59 from a prospective trial (REC 6798/2015)]. We subdivided patients into three groups according to CgA by receiver-operating characteristic (ROC) curves. In the primary cohort, plasma AR gain and mutations (p.L702H/p.T878A) were detected in 78 (39.6%) and 16 (8.1%) patients, respectively. We observed a significantly worse PFS/OS in patients with higher-CgA than in patients with normal-CgA, especially those with no AR-aberrations. Multivariable analysis showed AR gain, higher-CgA and LDH levels as independent predictors of PFS [hazard ratio (HR) = 2.16, 95% confidence interval (95% CI) 1.50-3.12, p < 0.0001, HR = 1.73, 95% CI 1.06-2.84, p = 0.026, and HR = 2.13, 95% CI 1.45-3.13, p = 0.0001, respectively) and OS (HR = 1.72, 95% CI 1.15-2.57, p = 0.008, HR = 3.63, 95% CI 2.13-6.20, p < 0.0001, and HR = 2.31, 95% CI 1.54-3.48, p < 0.0001, respectively). These data were confirmed in the secondary cohort. Pre-treatment CgA detection could be useful to identify these mixed tumors and would seem to have a prognostic role, especially in AR-normal patients. This association needs further evaluation in larger prospective cohorts

Accumulation of copy number alterations and clinical progression across advanced prostate cancer.

BACKGROUND: Genomic copy number alterations commonly occur in prostate cancer and are one measure of genomic instability. The clinical implication of copy number change in advanced prostate cancer, which defines a wide spectrum of disease from high-risk localised to metastatic, is unknown. METHODS: We performed copy number profiling on 688 tumour regions from 300 patients, who presented with advanced prostate cancer prior to the start of long-term androgen deprivation therapy (ADT), in the control arm of the prospective randomised STAMPEDE trial. Patients were categorised into metastatic states as follows; high-risk non-metastatic with or without local lymph node involvement, or metastatic low/high volume. We followed up patients for a median of 7 years. Univariable and multivariable Cox survival models were fitted to estimate the association between the burden of copy number alteration as a continuous variable and the hazard of death or disease progression. RESULTS: The burden of copy number alterations positively associated with radiologically evident distant metastases at diagnosis (P=0.00006) and showed a non-linear relationship with clinical outcome on univariable and multivariable analysis, characterised by a sharp increase in the relative risk of progression (P=0.003) and death (P=0.045) for each unit increase, stabilising into more modest increases with higher copy number burdens. This association between copy number burden and outcome was similar in each metastatic state. Copy number loss occurred significantly more frequently than gain at the lowest copy number burden quartile (q=4.1 × 10-6). Loss of segments in chromosome 5q21-22 and gains at 8q21-24, respectively including CHD1 and cMYC occurred more frequently in cases with higher copy number alteration (for either region: Kolmogorov-Smirnov distance, 0.5; adjusted P<0.0001). Copy number alterations showed variability across tumour regions in the same prostate. This variance associated with increased risk of distant metastases (Kruskal-Wallis test P=0.037). CONCLUSIONS: Copy number alteration in advanced prostate cancer associates with increased risk of metastases at diagnosis. Accumulation of a limited number of copy number alterations associates with most of the increased risk of disease progression and death. The increased likelihood of involvement of specific segments in high copy number alteration burden cancers may suggest an order underlying the accumulation of copy number changes. TRIAL REGISTRATION: ClinicalTrials.gov NCT00268476 , registered on December 22, 2005. EudraCT  2004-000193-31 , registered on October 4, 2004