Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
500
result(s) for
"Hoffmann, Jens"
Sort by:
Molecular dissection of colorectal cancer in pre-clinical models identifies biomarkers predicting sensitivity to EGFR inhibitors
Colorectal carcinoma represents a heterogeneous entity, with only a fraction of the tumours responding to available therapies, requiring a better molecular understanding of the disease in precision oncology. To address this challenge, the OncoTrack consortium recruited 106 CRC patients (stages I–IV) and developed a pre-clinical platform generating a compendium of drug sensitivity data totalling >4,000 assays testing 16 clinical drugs on patient-derived
in vivo
and
in vitro
models. This large biobank of 106 tumours, 35 organoids and 59 xenografts, with extensive omics data comparing donor tumours and derived models provides a resource for advancing our understanding of CRC. Models recapitulate many of the genetic and transcriptomic features of the donors, but defined less complex molecular sub-groups because of the loss of human stroma. Linking molecular profiles with drug sensitivity patterns identifies novel biomarkers, including a signature outperforming
RAS/RAF
mutations in predicting sensitivity to the EGFR inhibitor cetuximab.
The heterogeneity of colorectal cancer has important clinical and therapeutic implications. Here the authors analysed the responses of a large biobank of organoids and xenografts derived from colorectal patients to a panel of clinically relevant therapeutic agents to identify genes signatures associated with drug response.
Journal Article
Heterogeneous pathway activation and drug response modelled in colorectal-tumor-derived 3D cultures
Organoid cultures derived from colorectal cancer (CRC) samples are increasingly used as preclinical models for studying tumor biology and the effects of targeted therapies under conditions capturing in vitro the genetic make-up of heterogeneous and even individual neoplasms. While 3D cultures are initiated from surgical specimens comprising multiple cell populations, the impact of tumor heterogeneity on drug effects in organoid cultures has not been addressed systematically. Here we have used a cohort of well-characterized CRC organoids to study the influence of tumor heterogeneity on the activity of the KRAS/MAPK-signaling pathway and the consequences of treatment by inhibitors targeting EGFR and downstream effectors. MAPK signaling, analyzed by targeted proteomics, shows unexpected heterogeneity irrespective of RAS mutations and is associated with variable responses to EGFR inhibition. In addition, we obtained evidence for intratumoral heterogeneity in drug response among parallel \"sibling\" 3D cultures established from a single KRAS-mutant CRC. Our results imply that separate testing of drug effects in multiple subpopulations may help to elucidate molecular correlates of tumor heterogeneity and to improve therapy response prediction in patients.
Journal Article
The power of pictures : early Soviet photography, early Soviet film
\"Covering the period from the Revolution to the beginning of World War II, this book considers Soviet avant-garde photography and film in the context of political history and culture. Three essays trace this generation of artists, their experiments with new media, and their pursuit of a new political order. A wealth of stunning photographs, film stills, and film posters, as well as magazine and book designs, demonstrate that their output encompassed a spectacular range of style, content, and perspective, and an extraordinary sense of the power of the photograph to change the world\"--Provided by publisher.
Book
Model Fusion for Building Type Classification from Aerial and Street View Images
This article addresses the question of mapping building functions jointly using both aerial and street view images via deep learning techniques. One of the central challenges here is determining a data fusion strategy that can cope with heterogeneous image modalities. We demonstrate that geometric combinations of the features of such two types of images, especially in an early stage of the convolutional layers, often lead to a destructive effect due to the spatial misalignment of the features. Therefore, we address this problem through a decision-level fusion of a diverse ensemble of models trained from each image type independently. In this way, the significant differences in appearance of aerial and street view images are taken into account. Compared to the common multi-stream end-to-end fusion approaches proposed in the literature, we are able to increase the precision scores from 68% to 76%. Another challenge is that sophisticated classification schemes needed for real applications are highly overlapping and not very well defined without sharp boundaries. As a consequence, classification using machine learning becomes significantly harder. In this work, we choose a highly compact classification scheme with four classes, commercial, residential, public, and industrial because such a classification has a very high value to urban geography being correlated with socio-demographic parameters such as population density and income.
Journal Article
RPL22L1 induction in colorectal cancer is associated with poor prognosis and 5-FU resistance
We have previously demonstrated that loss of the tumor suppressive activity of ribosomal protein (RP) RPL22 predisposes to development of leukemia in mouse models and aggressive disease in human patients; however, the role of RPL22 in solid tumors, specifically colorectal cancer (CRC), had not been explored. We report here that RPL22 is either deleted or mutated in 36% of CRC and provide new insights into its mechanism of action. Indeed, Rpl22 inactivation causes the induction of its highly homologous paralog, RPL22L1, which serves as a driver of cell proliferation and anchorage-independent growth in CRC cells. Moreover, RPL22L1 protein is highly expressed in patient CRC samples and correlates with poor survival. Interestingly, the association of high RPL22L1 expression with poor prognosis appears to be linked to resistance to 5-Fluorouracil, which is a core component of most CRC therapeutic regimens. Indeed, in an avatar trial, we found that human CRC samples that were unresponsive to 5-Fluorouracil in patient-derived xenografts exhibited elevated expression levels of RPL22L1. This link between RPL22L1 induction and 5-Fluorouracil resistance appears to be causal, because ectopic expression or knockdown of RPL22L1 in cell lines increases and decreases 5-Fluorouracil resistance, respectively, and this is associated with changes in expression of the DNA-repair genes, MGMT and MLH1. In summary, our data suggest that RPL22L1 might be a prognostic marker in CRC and predict 5-FU responsiveness.
Journal Article
Peritoneal metastasis of colorectal cancer (pmCRC): identification of predictive molecular signatures by a novel preclinical platform of matching pmCRC PDX/PD3D models
According to tumor heterogeneity, enrichment or loss of individual tumor cell types during model generation, some occurring cancer-related mutations were not detected in every sample of the respective model. In turn, analyzing the transcriptomes of patient metastases and derived models according to cancer hallmark gene signatures (including DNA repair in general), showed similar patterns of gene set enrichments at transcriptome and proteome level (Fig. Furthermore, gene set enrichment analysis (GSEA) of combined PDX models showing treatment response to 5-FU versus resistant models resulted in significantly enriched gene sets indicating DNA repair (ES = 0.44, p = 0.009), specifically NER (ES = 0.42, p = 0.002), and response to veliparib (ES = 0.62, p < 0.001; Fig. 2F, Fig. For response analysis of combination treatment of the PARP inhibitor olaparib with either 5-FU or trametinib in vitro, we selected pmCRC models according to the list of identified predictive biomarkers (Table S12) and employed different approaches: first we used single cell suspensions of PDX tumor tissues, applied a drug concentration matrix (Fig. 2G) and measured cell cytotoxicity over time.
Journal Article
On the Highly Ordered Graphene Structure of Non-Graphitic Carbons (NGCs)—A Wide-Angle Neutron Scattering (WANS) Study
Non-graphitic carbons (NGCs), such as glass-like carbons, pitch cokes, and activated carbon consist of small graphene layer building stacks arranged in a turbostratic order. Both structure features, including the single graphene sheets as well as the stacks, possess structural disorder, which can be determined using wide-angle X-ray or neutron scattering (WAXS/WANS). Even if WANS data of NGCs have already been extensively reported and evaluated in different studies, there are still open questions with regard to their validation with WAXS, which is usually used for routine characterization. In particular, using WAXS for the damping of the atomic form factor and the limited measured range prevent the analysis of higher-ordered reflections, which are crucial for determining the stack/layer size (La, Lc) and disorder (σ1, σ3) based on the reflection widths. Therefore, in this study, powder WANS was performed on three types of carbon materials (glass-like carbon made out of a phenol-formaldehyde resin (PF-R), a mesophase pitch (MP), and a low softening-point pitch (LSPP)) using a beamline at ILL in Grenoble, providing a small wavelength and thus generating WANS data covering a large range of scattering vectors (0.052 Å−1 < s < 3.76 Å−1). Merging these WANS data with WANS data from previous studies, possessing high resolution in the small s range, on the same materials allowed us to determine both the interlayer and the interlayer structure as accurately as possible. As a main conclusion, we found that the structural disorder of the graphene layers themselves was significantly smaller than previously assumed.
Journal Article
Breaking the crosstalk of the Cellular Tumorigenic Network by low-dose combination therapy in lung cancer patient-derived xenografts
Non-small cell lung cancer (NSCLC) is commonly diagnosed at advanced stages limiting treatment options. Although, targeted therapy has become integral part of NSCLC treatment therapies often fail to improve patient’s prognosis. Based on previously published criteria for selecting drug combinations for overcoming resistances, NSCLC patient-derived xenograft (PDX) tumors were treated with a low dose combination of cabozantinib, afatinib, plerixafor and etoricoxib. All PDX tumors treated, including highly therapy-resistant adeno- and squamous cell carcinomas without targetable oncogenic mutations, were completely suppressed by this drug regimen, leading to an ORR of 81% and a CBR of 100%. The application and safety profile of this low dose therapy regimen was well manageable in the pre-clinical settings. Overall, this study provides evidence of a relationship between active paracrine signaling pathways of the Cellular Tumorigenic Network, which can be effectively targeted by a low-dose multimodal therapy to overcome therapy resistance and improve prognosis of NSCLC.
The identification of novel therapeutic strategies for advanced non-small cell lung cancer (NSCLC) is essential as the outcome of most of these patients is poor. Here the authors provide a proof-of concept that specific low-dose drug combinations can disrupt intercellular crosstalk to overcome drug resistance in NSCLC patient-derived xenografts.
Journal Article