Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data

BACKGROUND: Urothelial pathogenesis is a complex process driven by an underlying network of interconnected genes. The identification of novel genomic target regions and gene targets that drive urothelial carcinogenesis is crucial in order to improve our current limited understanding of urothelial cancer (UC) on the molecular level. The inference of genome-wide gene regulatory networks (GRN) from large-scale gene expression data provides a promising approach for a detailed investigation of the underlying network structure associated to urothelial carcinogenesis.

METHODS: In our study we inferred and compared three GRNs by the application of the BC3Net inference algorithm to large-scale transitional cell carcinoma gene expression data sets from Illumina RNAseq (179 samples), Illumina Bead arrays (165 samples) and Affymetrix Oligo microarrays (188 samples). We investigated the structural and functional properties of GRNs for the identification of molecular targets associated to urothelial cancer.

RESULTS: We found that the urothelial cancer (UC) GRNs show a significant enrichment of subnetworks that are associated with known cancer hallmarks including cell cycle, immune response, signaling, differentiation and translation. Interestingly, the most prominent subnetworks of co-located genes were found on chromosome regions 5q31.3 (RNAseq), 8q24.3 (Oligo) and 1q23.3 (Bead), which all represent known genomic regions frequently deregulated or aberated in urothelial cancer and other cancer types. Furthermore, the identified hub genes of the individual GRNs, e.g., HID1/DMC1 (tumor development), RNF17/TDRD4 (cancer antigen) and CYP4A11 (angiogenesis/ metastasis) are known cancer associated markers. The GRNs were highly dataset specific on the interaction level between individual genes, but showed large similarities on the biological function level represented by subnetworks. Remarkably, the RNAseq UC GRN showed twice the proportion of significant functional subnetworks. Based on our analysis of inferential and experimental networks the Bead UC GRN showed the lowest performance compared to the RNAseq and Oligo UC GRNs.

CONCLUSION: To our knowledge, this is the first study investigating genome-scale UC GRNs. RNAseq based gene expression data is the data platform of choice for a GRN inference. Our study offers new avenues for the identification of novel putative diagnostic targets for subsequent studies in bladder tumors.

Achieving hypoxia-inducible gene expression in tumors

Hypoxia is an inevitable feature of solid tumors and a common cause of treatment failure. Hypoxia acts as a trigger to genetic instability, apoptosis and possibly metastases. The adaptive response to cellular hypoxia involves the modulation of the synthesis of multiple proteins controlling processes such as glucose homeostasis, angiogenesis, vascular permeability and inflammation. The hypoxia responsive element (HRE) sequences isolated from oxygen-responsive genes have been shown to selectively induce gene expression in response to hypoxia when placed upstream of a promoter. The levels of induced gene expression were dependent on the number of HRE copies and the oxygen tension. Hypoxia-mediated cancer gene therapy strategies may represent a promising mean to significantly improve the efficacy of standard radiation therapy and chemotherapy approaches.

Meta-analysis of prostate cancer gene expression data identifies a novel discriminatory signature enriched for glycosylating enzymes

BACKGROUND: Tumorigenesis is characterised by changes in transcriptional control. Extensive transcript expression data have been acquired over the last decade and used to classify prostate cancers. Prostate cancer is, however, a heterogeneous multifocal cancer and this poses challenges in identifying robust transcript biomarkers.

METHODS: In this study, we have undertaken a meta-analysis of publicly available transcriptomic data spanning datasets and technologies from the last decade and encompassing laser capture microdissected and macrodissected sample sets.

RESULTS: We identified a 33 gene signature that can discriminate between benign tissue controls and localised prostate cancers irrespective of detection platform or dissection status. These genes were significantly overexpressed in localised prostate cancer versus benign tissue in at least three datasets within the Oncomine Compendium of Expression Array Data. In addition, they were also overexpressed in a recent exon-array dataset as well a prostate cancer RNA-seq dataset generated as part of the The Cancer Genomics Atlas (TCGA) initiative. Biologically, glycosylation was the single enriched process associated with this 33 gene signature, encompassing four glycosylating enzymes. We went on to evaluate the performance of this signature against three individual markers of prostate cancer, v-ets avian erythroblastosis virus E26 oncogene homolog (ERG) expression, prostate specific antigen (PSA) expression and androgen receptor (AR) expression in an additional independent dataset. Our signature had greater discriminatory power than these markers both for localised cancer and metastatic disease relative to benign tissue, or in the case of metastasis, also localised prostate cancer.

CONCLUSION: In conclusion, robust transcript biomarkers are present within datasets assembled over many years and cohorts and our study provides both examples and a strategy for refining and comparing datasets to obtain additional markers as more data are generated.

In vitro blood-brain barrier models to predict the permeation of gene therapy vectors into the brain

A terapia génica tem-se revelado uma alternativa relevante no tratamento de doenças neurodegenerativas (DN). Contudo, a entrega de vetores para transferência génica no cérebro representa ainda um enorme desafio devido à presença da barreira hemato-encefálica (BHE). A BHE é uma interface dinâmica e seletiva entre o sangue e o cérebro, constituída pelas células endoteliais cerebrais, astrócitos e pericitos, desempenhando um importante papel na regulação da homeostasia cerebral. A BHE representa um dos maiores obstáculos no tratamento de DN, uma vez que esta barreira impede o transporte para o cérebro da maioria das moléculas terapêuticas, incluindo os vetores para terapia génica. Embora tenham sido desenvolvidos diferentes modelos in vitro da BHE de forma a avaliar o transporte de fármacos através da BHE, muito poucos foram criados com o intuito de testar a permeabilidade desta barreira a vetores de terapia génica. O presente trabalho teve como objetivo principal o desenvolvimento e a avaliação de modelos in vitro de BHE que permitam a investigação da capacidade dos vetores de terapia génica de penetrarem no cérebro. No nosso estudo, foram testados diferentes modelos in vitro de BHE em monocultura, constituídos por células endoteliais de rato ou murganho (RBE4 e bEnd3, respetivamente), e modelos de co-cultura, que combinam células endoteliais com células neuronais (Neuro2a) ou astrócitos primários, cultivados num sistema transwell. Para caraterizar estes modelos foram realizados testes de permeabilidade e de resistência elétrica transendotelial, bem como estudos baseados na técnica de PCR quantitativo e na imunocitoquímica das proteínas das junções intercelulares. Verificámos que os modelos baseados na cultura de células bEnd3 e células neuronais ou astrócitos apresentavam as melhores propriedades de barreira. Posteriormente foi avaliada nos modelos selecionados a penetração de um vetor não-viral que reconhecidamente tem a capacidade de atravessar in vivo a BHE: o peptídeo da glicoproteína do vírus da raiva (RGV-9r). Os siRNAs marcados com um fluoróforo e acoplados ao peptídeo RVG-9r foram capazes de penetrar eficientemente as células bEnd3, localizadas no lado luminal do insert, via endocitose mediada por recetores, e ainda de penetrar os astrócitos ou células neuronais, previamente cultivadas no lado abluminal. Estes resultados correlacionam-se, de forma clara, com os resultados previamente descritos em estudos in vivo. Em conclusão, os modelos in vitro de BHE baseados na co-cultura de células bEnd3 com células Neuro2a ou astrócitos, têm grande potencial na seleção de candidatos a vetores de terapia génica para o cérebro, uma vez que apresentam importantes características da BHE e se baseiam num método fácil e reprodutível. Tal facto representa uma promessa significativa para a identificação de novas estratégias de terapia génica não invasiva para o tratamento de doenças neurológicas.

Development of non-viral vectors for gene therapy for pathologies of the retina

Tese de doutoramento, Ciências Biomédicas, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2015

mRNA metabolism: nonsense mediated mRNA decay as a tool for gene therapy and the role of human DIS3L2 in transcript degradation

Tese de mestrado em Biologia Humana e Ambiente, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2015