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- Menden, MP, et al.
(author)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Journal article (peer-reviewed)abstract
- The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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- Fauria, K., et al.
(author)
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Exploring cognitive and biological correlates of sleep quality and their potential links with Alzheimer's disease (ALFASleep project): protocol for an observational study
- 2022
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In: Bmj Open. - : BMJ. - 2044-6055. ; 12:12
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Journal article (peer-reviewed)abstract
- INTRODUCTION: The growing worldwide prevalence of Alzheimer's disease (AD) and the lack of effective treatments pose a dire medical challenge. Sleep disruption is also prevalent in the ageing population and is increasingly recognised as a risk factor and an early sign of AD. The ALFASleep project aims to characterise sleep with subjective and objective measurements in cognitively unimpaired middle/late middle-aged adults at increased risk of AD who are phenotyped with fluid and neuroimaging AD biomarkers. This will contribute to a better understanding of the pathophysiological mechanisms linking sleep with AD, thereby paving the way for the development of non-invasive biomarkers and preventive strategies targeting sleep. METHODS AND ANALYSIS: We will invite 200 participants enrolled in the ALFA+ (for ALzheimer and FAmilies) prospective observational study to join the ALFASleep study. ALFA+ participants are cognitively unimpaired middle-aged/late middle-aged adults who are followed up every 3years with a comprehensive set of evaluations including neuropsychological tests, blood and cerebrospinal fluid (CSF) sampling, and MRI and positron emission tomography acquisition. ALFASleep participants will be additionally characterised with actigraphy and CSF-orexin-A measurements, and a subset (n=90) will undergo overnight polysomnography. We will test associations of sleep measurements and CSF-orexin-A with fluid biomarkers of AD and glial activation, neuroimaging outcomes and cognitive performance. In case we found any associations, we will test whether changes in AD and/or glial activation markers mediate the association between sleep and neuroimaging or cognitive outcomes and whether sleep mediates associations between CSF-orexin-A and AD biomarkers. ETHICS AND DISSEMINATION: The ALFASleep study protocol has been approved by the independent Ethics Committee Parc de Salut Mar, Barcelona (2018/8207/I). All participants have signed a written informed consent before their inclusion (approved by the same ethics committee). Study findings will be presented at national and international conferences and submitted for publication in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04932473.
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- Salvado, G., et al.
(author)
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Centiloid cut-off values for optimal agreement between PET and CSF core AD biomarkers
- 2019
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In: Alzheimers Research & Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 11
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Journal article (peer-reviewed)abstract
- BackgroundThe Centiloid scale has been developed to standardize measurements of amyloid PET imaging. Reference cut-off values of this continuous measurement enable the consistent operationalization of decision-making for multicentre research studies and clinical trials. In this study, we aimed at deriving reference Centiloid thresholds that maximize the agreement against core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers in two large independent cohorts.MethodsA total of 516 participants of the ALFA+ Study (N=205) and ADNI (N=311) underwent amyloid PET imaging ([F-18]flutemetamol and [F-18]florbetapir, respectively) and core AD CSF biomarker determination using Elecsys (R) tests. Tracer uptake was quantified in Centiloid units (CL). Optimal Centiloid cut-offs were sought that maximize the agreement between PET and dichotomous determinations based on CSF levels of A(42), tTau, pTau, and their ratios, using pre-established reference cut-off values. To this end, a receiver operating characteristic analysis (ROC) was conducted, and Centiloid cut-offs were calculated as those that maximized the Youden's J Index or the overall percentage agreement recorded.ResultsAll Centiloid cut-offs fell within the range of 25-35, except for CSF A(42) that rendered an optimal cut-off value of 12 CL. As expected, the agreement of tau/A(42) ratios was higher than that of CSF A(42). Centiloid cut-off robustness was confirmed even when established in an independent cohort and against variations of CSF cut-offs.ConclusionsA cut-off of 12 CL matches previously reported values derived against postmortem measures of AD neuropathology. Together with these previous findings, our results flag two relevant inflection points that would serve as boundary of different stages of amyloid pathology: one around 12 CL that marks the transition from the absence of pathology to subtle pathology and another one around 30 CL indicating the presence of established pathology. The derivation of robust and generalizable cut-offs for core AD biomarkers requires cohorts with adequate representation of intermediate levels.Trial registrationALFA+ Study, NCT02485730ALFA PET Sub-study, NCT02685969
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