Halting the hallmarks: a cellular automaton model of early cancer growth inhibition

Cancer treatment is a fragmented and varied process, as ‘‘cancer’’ is really hundreds of different diseases. The ‘‘hallmarks of cancer’’ proposed by Hanahan and Weinberg (Cell 100(1):57–70, 2000) are a framework for viewing cancer within a common set of underlying principles—ten properties that are common to almost all cancers, allowing them to grow uncontrollably and ravage the body. We used a cellular automaton model of tumour growth paired with lattice Boltzmann methods modelling oxygen flow to simulate combination drugs targeted at knocking out pairs of hallmarks. We found that knocking out some pairs of cancer-enabling hallmarks did not prevent tumour formation, while other pairs significantly prevent tumour growth (p ¼ 0:0004 using Wilcoxon signed-rank adjusted with the Bonferroni correction for multiple comparisons). This is not what would be expected from models of knocking out the hallmarks individually, as many pairs did not have an additive effect but had either no statistically significant effect or a multiplicative one. We propose that targeting certain pairs of cancer hallmarks, specifically cancers ability to induce blood vessel development paired with another cancer hallmark, could prove an effective cancer treatment option

Effectiveness of a brief behavioural intervention to prevent weight gain over the Christmas holiday period: randomised controlled trial

OBJECTIVE To test the effectiveness of a brief behavioural intervention to prevent weight gain over the Christmas holiday period. DESIGN Two group, double blinded randomised controlled trial. SETTING Recruitment from workplaces, social media platforms, and schools pre-Christmas 2016 and 2017 in Birmingham, UK. PARTICIPANTS 272 adults aged 18 years or more with a body mass index of 20 or more: 136 were randomised to a brief behavioural intervention and 136 to a leaflet on healthy living (comparator). Baseline assessments were conducted in November and December with follow-up assessments in January and February (4-8 weeks after baseline). INTERVENTIONS The intervention aimed to increase restraint of eating and drinking through regular self weighing and recording of weight and reflection on weight trajectory; providing information on good weight management strategies over the Christmas period; and pictorial information on the physical activity calorie equivalent (PACE) of regularly consumed festive foods and drinks. The goal was to gain no more than 0.5 kg of baseline weight. The comparator group received a leaflet on healthy living. MAIN OUTCOME MEASURES The primary outcome was weight at follow-up. The primary analysis compared weight at follow-up between the intervention and comparator arms, adjusting for baseline weight and the stratification variable of attendance at a commercial weight loss programme. Secondary outcomes (recorded at followup) were: weight gain of 0.5 kg or less, self reported frequency of self weighing (at least twice weekly versus less than twice weekly), percentage body fat, and cognitive restraint of eating, emotional eating, and uncontrolled eating. RESULTS Mean weight change was −0.13 kg (95% confidence interval −0.4 to 0.15) in the intervention group and 0.37 kg (0.12 to 0.62) in the comparator group. The adjusted mean difference in weight (intervention− comparator) was −0.49 kg (95% confidence interval −0.85 to −0.13, P=0.008). The odds ratio for gaining no more than 0.5 kg was non-significant (1.22, 95% confidence interval 0.74 to 2.00, P=0.44). CONCLUSION A brief behavioural intervention involving regular self weighing, weight management advice, and information about the amount of physical activity required to expend the calories in festive foods and drinks prevented weight gain over the Christmas holiday period

MoKCa database - mutations of kinases in cancer

Members of the protein kinase family are amongst the most commonly mutated genes in human cancer, and both mutated and activated protein kinases have proved to be tractable targets for the development of new anticancer therapies The MoKCa database (Mutations of Kinases in Cancer, http://strubiol.icr.ac.uk/extra/mokca) has been developed to structurally and functionally annotate, and where possible predict, the phenotypic consequences of mutations in protein kinases implicated in cancer. Somatic mutation data from tumours and tumour cell lines have been mapped onto the crystal structures of the affected protein domains. Positions of the mutated amino-acids are highlighted on a sequence-based domain pictogram, as well as a 3D-image of the protein structure, and in a molecular graphics package, integrated for interactive viewing. The data associated with each mutation is presented in the Web interface, along with expert annotation of the detailed molecular functional implications of the mutation. Proteins are linked to functional annotation resources and are annotated with structural and functional features such as domains and phosphorylation sites. MoKCa aims to provide assessments available from multiple sources and algorithms for each potential cancer-associated mutation, and present these together in a consistent and coherent fashion to facilitate authoritative annotation by cancer biologists and structural biologists, directly involved in the generation and analysis of new mutational data

In situ Biological Dose Mapping Estimates the Radiation Burden Delivered to ‘Spared’ Tissue between Synchrotron X-Ray Microbeam Radiotherapy Tracks

Microbeam radiation therapy (MRT) using high doses of synchrotron X-rays can destroy tumours in animal models whilst causing little damage to normal tissues. Determining the spatial distribution of radiation doses delivered during MRT at a microscopic scale is a major challenge. Film and semiconductor dosimetry as well as Monte Carlo methods struggle to provide accurate estimates of dose profiles and peak-to-valley dose ratios at the position of the targeted and traversed tissues whose biological responses determine treatment outcome. The purpose of this study was to utilise γ-H2AX immunostaining as a biodosimetric tool that enables in situ biological dose mapping within an irradiated tissue to provide direct biological evidence for the scale of the radiation burden to ‘spared’ tissue regions between MRT tracks. Γ-H2AX analysis allowed microbeams to be traced and DNA damage foci to be quantified in valleys between beams following MRT treatment of fibroblast cultures and murine skin where foci yields per unit dose were approximately five-fold lower than in fibroblast cultures. Foci levels in cells located in valleys were compared with calibration curves using known broadbeam synchrotron X-ray doses to generate spatial dose profiles and calculate peak-to-valley dose ratios of 30–40 for cell cultures and approximately 60 for murine skin, consistent with the range obtained with conventional dosimetry methods. This biological dose mapping approach could find several applications both in optimising MRT or other radiotherapeutic treatments and in estimating localised doses following accidental radiation exposure using skin punch biopsies

High-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium.

Automated methods are needed to facilitate high-throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large-scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37-0.87) and study (kappa range = 0.39-0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p-value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000-4,500 cells: kappa = 0.78) than those with lower counts (50-500 cells: kappa = 0.41; p-value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre- and post-analytical quality control procedures are necessary in order to ensure satisfactory performance.ABCS was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009-4363]; BBMRI-NL, which is a Research Infrastructure financed by the Dutch government (NWO 184.021.007); and the Dutch National Genomics Initiative. CNIO-BCS was supported by the Genome Spain Foundation, the Red Tematica de Investigacion Cooperativa en Cancer and grants from the Asociacion Espaola Contra el Cancer and the Fondo de Investigacion Sanitario (PI11/00923 and PI081120). The Human Genotyping-CEGEN Unit (CNIO) is supported by the Instituto de Salud Carlos III. The ESTHER study was supported by a grant from the Baden Wurttemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). The KBCP was financially supported by the special Government Funding (EVO) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, the Academy of Finland and by the strategic funding of the University of Eastern Finland. We wish to thank Heather Thorne, Eveline Niedermayr, all the kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the Clinical Follow Up Study (which has received funding from the NHMRC, the National Breast Cancer Foundation, Cancer Australia, and the National Institute of Health (USA)) for their contributions to this resource, and the many families who contribute to kConFab. kConFab is supported by a grant from the National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. The MARIE study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. The MCBCS was supported by an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], the Breast Cancer Research Foundation, the Mayo Clinic Breast Cancer Registry and a generous gift from the David F. and Margaret T. Grohne Family Foundation and the Ting Tsung and Wei Fong Chao Foundation. ORIGO authors thank E. Krol-Warmerdam, and J. Blom; The contributing studies were funded by grants from the Dutch Cancer Society (UL1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). SEARCH is funded by programme grant from Cancer Research UK [C490/A10124. C490/A16561] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. Part of this work was supported by the European Community’s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009223175) (COGS). The UKBGS is funded by Breakthrough Breast Cancer and the Institute of Cancer Research (ICR), London. ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. We acknowledge funds from Breakthrough Breast Cancer, UK, in support of MGC at the time this work was carried out and funds from the Cancer Research, UK, in support of MA.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/cjp2.4

Homologous recombination DNA repair deficiency and PARP inhibition activity in primary triple negative breast cancer

Funder: Breast Cancer Now (BCN); doi: https://doi.org/10.13039/100009794Abstract: Triple negative breast cancer (TNBC) encompasses molecularly different subgroups, with a subgroup harboring evidence of defective homologous recombination (HR) DNA repair. Here, within a phase 2 window clinical trial, RIO trial (EudraCT 2014-003319-12), we investigate the activity of PARP inhibitors in 43 patients with untreated TNBC. The primary end point, decreased Ki67, occured in 12% of TNBC. In secondary end point analyses, HR deficiency was identified in 69% of TNBC with the mutational-signature-based HRDetect assay. Cancers with HRDetect mutational signatures of HR deficiency had a functional defect in HR, assessed by impaired RAD51 foci formation on end of treatment biopsy. Following rucaparib treatment there was no association of Ki67 change with HR deficiency. In contrast, early circulating tumor DNA dynamics identified activity of rucaparib, with end of treatment ctDNA levels suppressed by rucaparib in mutation-signature HR-deficient cancers. In ad hoc analysis, rucaparib induced expression of interferon response genes in HR-deficient cancers. The majority of TNBCs have a defect in DNA repair, identifiable by mutational signature analysis, that may be targetable with PARP inhibitors

High-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium (BCAC)

Automated methods are needed to facilitate high-throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large-scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performanc

Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large-scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose-response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large-scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker-specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results.Peer reviewe