Biology subjects

Vogel, R.

Publications and source records attributed to Vogel, R..

7 recordsLinked to original sources

bioRxiv2020

APOBEC3B expression generates an immunogenic model of Kras mutant lung cancer

Mutations in oncogenes such as KRAS and EGFR cause a high proportion of lung cancers. Drugs targeting these proteins cause tumour regression but ultimately fail to cure these cancers, leading to intense interest in how best to combine them with other treatments, such as immunotherapies. However, preclinical systems for studying the interaction of lung tumours with the host immune system are inadequate, in part due to the low tumour mutational burden in genetically engineered mouse models. Here we set out to develop mouse models of mutant KRAS-driven lung cancer with an elevated tumour mutational burden by expressing the human DNA cytosine deaminase, APOBEC3B, to mimic the mutational signature seen in human lung cancer. This failed to substantially increase clonal tumour mutational burden and autochthonous tumours remained refractory to immunotherapy. However, by establishing clonal cell lines from these tumours we generated an immunogenic syngeneic transplantation model of KRAS mutant lung adenocarcinoma that was sensitive to immunotherapy. Unexpectedly, we found that anti-tumour immune responses were not directed against neoantigens but instead targeted derepressed endogenous retroviral antigens. The ability of KRASG12C inhibitors to cause regression of KRASG12C-expressing versions of these tumours was markedly potentiated by the adaptive immune system, providing a unique opportunity for the study of combinations of targeted and immunotherapies in immune-hot lung cancer.

cancer biology↗

bioRxiv2020

YAP and β-catenin co-operate to drive oncogenesis in basal breast cancer

Targeting cancer stem cells (CSCs) can serve as an effective approach toward limiting resistance to therapies and the development of metastases in many forms of cancer. While basal breast cancers encompass cells with CSC features, rational therapies remain poorly established. Here, we show that receptor tyrosine kinase Met signalling promotes the activity of the Hippo component YAP in basal breast cancer. Further analysis revealed enhanced YAP activity within the CSC population. Using both genetic and pharmaceutical approaches, we show that interfering with YAP activity delays basal cancer formation, prevents luminal to basal trans-differentiation and reduces CSC survival. Gene expression analysis of YAP knock-out mammary glands revealed a strong decrease in {beta}-catenin target genes in basal breast cancer, suggesting that YAP is required for nuclear {beta}-catenin activity. Mechanistically, we find that nuclear YAP interacts and overlaps with {beta}-catenin and TEAD4 at common gene regulatory elements. Analysis of proteomic data from primary breast cancer patients identified a significant upregulation of the YAP activity signature in basal compared to other breast cancers, suggesting that YAP activity is limited to basal types. Our findings demonstrate that in basal breast cancers, {beta}-catenin activity is dependent on YAP signalling and controls the CSC program. These findings suggest that targeting the YAP/TEAD4/{beta}-catenin complex offers a potential therapeutic strategy for eradicating CSCs in basal (triple-negative) breast cancers.

cancer biology↗

bioRxiv2019

APOBEC3A Catalyzes Mutation and Drives Carcinogenesis In Vivo

The APOBEC3 family of antiviral DNA cytosine deaminases is implicated as the second largest source of mutation in cancer. This mutational process may be a causal driver or inconsequential passenger to the overall tumor phenotype. We show that human APOBEC3A expression in murine colon and liver tissues increases tumorigenesis. All other APOBEC3 family members including APOBEC3B did not as strongly promote liver tumor formation. DNA sequences from APOBEC3A-expressing animals display hallmark APOBEC signature mutations in TCA/T motifs. Bioinformatic comparisons of the observed APOBEC3A mutation signature in murine tumors, previously reported APOBEC3A and APOBEC3B mutation signatures in yeast, and reanalyzed APOBEC mutation signatures in human tumor data sets support cause-and-effect relationships for APOBEC3A-catalyzed deamination and mutagenesis in driving multiple human cancers.

cancer biology↗

bioRxiv2018

A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection

Respiratory viruses are highly infectious; however, the variation of individuals physiologic responses to viral exposure is poorly understood. Most studies examining molecular predictors of response focus on late stage predictors, typically near the time of peak symptoms. To determine whether pre- or early post-exposure factors could predict response, we conducted a community-based analysis to identify predictors of resilience or susceptibility to several respiratory viruses (H1N1, H3N2, Rhinovirus, and RSV) using peripheral blood gene expression profiles collected from healthy subjects prior to viral exposure, as well as up to 24 hours following exposure. This analysis revealed that it is possible to construct models predictive of symptoms using profiles even prior to viral exposure. Analysis of predictive gene features revealed little overlap among models; however, in aggregate, these genes were enriched for common pathways. Heme Metabolism, the most significantly enriched pathway, was associated with higher risk of developing symptoms following viral exposure.

immunology↗

bioRxiv2017

Origins of fractional control in regulated cell death

Individual cells in clonal populations often respond differently to environmental changes; for binary phenotypes, such as cell death, this can be measured as a fractional response. These types of responses have been attributed to cell-intrinsic stochastic processes and variable abundances of biochemical constituents, such as proteins, but the influence of organelles has yet to be determined. We use the response to TNF-related apoptosis inducing ligand (TRAIL) and a new statistical framework for determining parameter influence on cell-to-cell variability through the inference of variance explained, DEPICTIVE, to demonstrate that variable mitochondria abundance correlates with cell survival and determines the fractional cell death response. By quantitative data analysis and modeling we attribute this effect to variable effective concentrations at the mitochondria surface of the pro-apoptotic protein Bax. Further, we demonstrate that inhibitors of antiapoptotic Bcl-2 family proteins, used in cancer treatment, may increase the diversity of cellular responses, enhancing resistance to treatment.

systems biology↗

bioRxiv2017

Community assessment of cancer drug combination screens identifies strategies for synergy prediction

The effectiveness of most cancer targeted therapies is short lived since tumors evolve and develop resistance. Combinations of drugs offer the potential to overcome resistance, however the number of possible combinations is vast necessitating data-driven approaches to find optimal treatments tailored to a patients tumor. AstraZeneca carried out 11,576 experiments on 910 drug combinations across 85 cancer cell lines, recapitulating in vivo response profiles. These data, the largest openly available screen, were hosted by DREAM alongside deep molecular characterization from the Sanger Institute for a Challenge to computationally predict synergistic drug pairs and associated biomarkers. 160 teams participated to provide the most comprehensive methodological development and subsequent benchmarking to date. Winning methods incorporated prior knowledge of putative drug target interactions. For >60% of drug combinations synergy was reproducibly predicted with an accuracy matching biological replicate experiments, however 20% of drug combinations were poorly predicted by all methods. Genomic rationale for synergy predictions were identified, including antagonism unique to combined PIK3CB/D inhibition with the ADAM17 inhibitor where synergy is seen with other PI3K pathway inhibitors. All data, methods and code are freely available as a resource to the community.

bioinformatics↗

bioRxiv2017

Modeling of cytometry data in logarithmic space: when is a bimodal distribution not bimodal?

Recent efforts in systems immunology lead researchers to build quantitative models of cell activation and differentiation. One goal is to account for the distributions of proteins from single-cell measurements by flow cytometry or mass cytometry as a readout of biological regulation. In that context, large cell-to-cell variability is often observed in biological quantities. We show here that these readouts, viewed in logarithmic scale may result in two easily-distinguishable modes, while the underlying distribution (in linear scale) is unimodal. We introduce a simple mathematical test to highlight this mismatch. We then dissect the flow of influence of cell-to-cell variability proposing a graphical model which motivates higher-dimensional analysis of the data. Finally we show how acquiring additional biological information can be used to reduce uncertainty introduced by cell-to-cell variability, helping to clarify whether the data is uni- or bimodal. This communication has cautionary implications for manual and automatic gating strategies, as well as clustering and modeling of single-cell measurements.

immunology↗