Publications

@article{Thomas2025-td,

title = {Evolution of preclinical models for glioblastoma modelling and drug screening},

author = {Grace Thomas and Ruman Rahman},

doi = {10.1007/s11912-025-01672-4},

year  = {2025},

date = {2025-05-01},

urldate = {2025-05-01},

journal = {Curr. Oncol. Rep.},

volume = {27},

number = {5},

pages = {601\textendash624},

publisher = {Springer Science and Business Media LLC},

abstract = {PURPOSE OF REVIEW: Isocitrate dehydrogenase wild-type 

 glioblastoma is an extremely aggressive and fatal primary brain 

 tumour, characterised by extensive heterogeneity and diffuse 

 infiltration of brain parenchyma. Despite multimodal treatment 

 and diverse research efforts to develop novel therapies, there 

 has been limited success in improving patient outcomes. 

 Constructing physiologically relevant preclinical models is 

 essential to optimising drug screening processes and identifying 

 more effective treatments. RECENT FINDINGS: Traditional in-vitro 

 models have provided critical insights into glioblastoma 

 pathophysiology; however, they are limited in their ability to 

 recapitulate the complex tumour microenvironment and its 

 interactions with surrounding cells. In-vivo models offer a more 

 physiologically relevant context, but often do not fully 

 represent human pathology, are expensive, and time-consuming. 

 These limitations have contributed to the low translational 

 success of therapies from trials to clinic. Organoid and 

 glioblastoma-on-a-chip technology represent significant advances 

 in glioblastoma modelling and enable the replication of key 

 features of the human tumour microenvironment, including its 

 structural, mechanical, and biochemical properties. Organoids 

 provide a 3D system that captures cellular heterogeneity and 

 tumour architecture, while microfluidic chips offer dynamic 

 systems capable of mimicking vascularisation and nutrient 

 exchange. Together, these technologies hold tremendous potential 

 for high throughput drug screening and personalised, precision 

 medicine. This review explores the evolution of preclinical 

 models in glioblastoma modelling and drug screening, emphasising 

 the transition from traditional systems to more advanced 

 organoid and microfluidic platforms. Furthermore, it aims to 

 evaluate the advantages and limitations of both traditional and 

 next-generation models, investigating their combined potential 

 to address current challenges by integrating complementary 

 aspects of specific models and techniques.},

keywords = {Glioblastoma, Glioblastoma-on-a-chip, Microfluids, Organoids, Preclinical model},

pubstate = {published},

tppubtype = {article}

}

@article{Gajera2023-kn,

title = {In vitro and in vivo assays for testing retinoids effect on 

 intestinal progenitors' lineage commitments},

author = {Krishna R Gajera and Kathryn L Fair and Gordon W Moran and Nicholas R F Hannan and Joerg Huelsken and Paloma Ord\'{o}\~{n}ez-Mor\'{a}n},

year  = {2023},

date = {2023-01-01},

journal = {Methods Mol. Biol.},

volume = {2650},

pages = {53\textendash61},

abstract = {The intestine consists of epithelial cells surrounded by a 

 complex environment as mesenchymal cells and the gut microbiota. 

 With its impressive stem cell regeneration capability, the 

 intestine is able to constantly replenish cells lost through 

 apoptosis or abrasion by food passing through. Over the past 

 decade, researchers have identified signaling pathways involved 

 in stem cell homeostasis such as retinoids pathway. Retinoids are 

 also involved in cell differentiation of healthy and cancer 

 cells. In this study, we describe several approaches in vitro and 

 in vivo to further investigate the effect of retinoids on stem 

 cells, progenitors, and differentiated intestinal cells.},

keywords = {Absorptive, Differentiation, Intestine, Organoids, Retinoids, Secretory, Stem cells},

pubstate = {published},

tppubtype = {article}

}

@article{Dionellis2021-py,

title = {Genomic instability profiles at the single cell level in mouse 

 colorectal cancers of defined genotypes},

author = {Vasilis S Dionellis and Maxim Norkin and Angeliki Karamichali and Giacomo G Rossetti and Joerg Huelsken and Paloma Ordonez-Moran and Thanos D Halazonetis},

year  = {2021},

date = {2021-03-01},

journal = {Cancers (Basel)},

volume = {13},

number = {6},

pages = {1267},

publisher = {MDPI AG},

abstract = {The genomes of many human CRCs have been sequenced, revealing a 

 large number of genetic alterations. However, the molecular 

 mechanisms underlying the accumulation of these alterations are 

 still being debated. In this study, we examined colorectal 

 tumours that developed in mice with Apclox/lox, LSL-KrasG12D, 

 and Tp53lox/lox targetable alleles. Organoids were derived from 

 single cells and the spectrum of mutations was determined by 

 exome sequencing. The number of single nucleotide substitutions 

 (SNSs) correlated with the age of the tumour, but was unaffected 

 by the number of targeted cancer-driver genes. Thus, tumours 

 that expressed mutant Apc, Kras, and Tp53 alleles had as many 

 SNSs as tumours that expressed only mutant Apc. In contrast, the 

 presence of large-scale (\>10 Mb) copy number alterations (CNAs) 

 correlated strongly with Tp53 inactivation. Comparison of the 

 SNSs and CNAs present in organoids derived from the same tumour 

 revealed intratumoural heterogeneity consistent with genomic 

 lesions accumulating at significantly higher rates in tumour 

 cells compared to normal cells. The rate of acquisition of SNSs 

 increased from the early stages of cancer development, whereas 

 large-scale CNAs accumulated later, after Tp53 inactivation. 

 Thus, a significant fraction of the genomic instability present 

 in cancer cells cannot be explained by aging processes occurring 

 in normal cells before oncogenic transformation.},

keywords = {cancer drivers, colorectal cancer, copy number alterations, exome sequencing, genomic instability, mouse models, mutational   signature, Organoids, single cell, single nucleotide variants},

pubstate = {published},

tppubtype = {article}

}