Biology subjects

Zoni, E.

Publications and source records attributed to Zoni, E..

4 recordsLinked to original sources

bioRxiv2023

MicroCT-based imaging of microvasculature within the bone tissue

Angiogenesis is essential for skeletal development, bone healing, and regeneration. Improved non-destructive, three-dimensional (3D) imaging of the vasculature within bone tissue benefits many research areas, especially implantology and tissue engineering. X-ray microcomputed tomography (microCT) is a well-suited non-destructive 3D imaging technique for bone morphology. For microCT-based detection of vessels, it is paramount to use contrast enhancement. Limited differences in radiopacity between perfusion agents and mineralized bone make their distinct segmentation problematic and have been a major drawback of this approach. A decalcification step resolves this issue but inhibits the simultaneous assessment of bone microstructure and vascular morphology. The problem of contrasting becomes further complicated in samples with metal implants. This study describes contrast-enhanced microCT-based visualization of vasculature within bone tissue in small and large animal models, also in the vicinity of the metal implants. We present simultaneous microvascular and bone imaging in murine tibia, a murine bone metastatic model, the pulp chamber, gingiva, and periodontal ligaments. In a large animal model (minipig), we perform visualization and segmentation of different tissue types and vessels in the hemimandible containing metal implants. We further demonstrate the potential of dual-energy imaging in distinguishing bone tissue from the applied contrast agents. This work introduces a non-destructive approach for 3D imaging of vasculature within soft and hard tissues near metal implants in a large animal model.

physiology↗

bioRxiv2021

Tumour mutations in long noncoding RNAs that enhance cell fitness

Long noncoding RNAs (lncRNAs) can act as tumour suppressors or oncogenes to repress/promote tumour cell proliferation via RNA-dependent mechanisms. Recently, genome sequencing has identified elevated densities of tumour somatic single nucleotide variants (SNVs) in lncRNA genes. However, this has been attributed to phenotypically-neutral "passenger" processes, and the existence of positively-selected fitness-altering "driver" SNVs acting via lncRNAs has not been addressed. We developed and used ExInAtor2, an improved driver-discovery pipeline, to map pancancer and cancer-specific mutated lncRNAs across an extensive cohort of 2583 primary and 3527 metastatic tumours. The 54 resulting lncRNAs are mostly linked to cancer for the first time. Their significance is supported by a range of clinical and genomic evidence, and display oncogenic potential when experimentally expressed in matched tumour models. Our results revealed a striking SNV hotspot in the iconic NEAT1 oncogene, which was ascribed by previous studies to passenger processes. To directly evaluate the functional significance of NEAT1 SNVs, we used in cellulo mutagenesis to introduce tumour-like mutations in the gene and observed a consequent increase in cell proliferation in both transformed and normal backgrounds. Mechanistic analyses revealed that SNVs alter NEAT1 ribonucleoprotein assembly and boost subnuclear paraspeckles. This is the first experimental evidence that mutated lncRNAs can contribute to the pathological fitness of tumour cells.

genomics↗

bioRxiv2020

Stroma transcriptomic and proteomic profile of prostate cancer metastasis xenograft models reveals conservation of bonemicroenvironment signatures

Prostate cancer (PCa) is the second leading cause of cancer-associated death in men with therapy resistance acquisition to androgen deprivation treatment and metastasis progression. Understanding the mechanisms of tumor progression to metastatic stage is necessary for the design of therapeutic and prognostic schemes. The main objective of the current study is to determine, using transcriptomic and proteomic analyses on patient derived-xenograft models, whether differentially aggressive PCa tumors predispose their microenvironment (stroma) to a metastatic gene expression pattern, and how this information could be applied in prognostics. Transcriptomic profiling (RNA Sequencing) was performed on PCa PDX models representing different disease stages; BM18 (androgen dependent bone metastasis) and LAPC9 (androgen independent bone metastasis). Using organism-specific reference databases, the human-specific transcriptome, representing the tumor, was identified and separated from the mouse-specific transcriptome (representing the contributing stroma counterpart) from the same PDX tumor samples. To identify proteome changes in the tumor (human) versus the stroma (mouse), we performed human and mouse cell separation using the MACS mouse depletion sorting kit, and subjected protein lysates to quantitative TMT labeling and mass spectrometry. We show that tenascin C is one of the most abundant stromal genes in bone metastasis PCa PDXs, is modulated by androgen levels in vivo and is highly expressed in castration resistant LAPC9 PDX compared to castration sensitive BM18 PDX. Tissue microarray of primary PCa samples (N=210) was used to evaluate the potential of TNC to act as a metastasis prognosis marker. Low number of TNC-positive cells were associated with statistically significant clinical progression to local recurrence or metastasis, compared to high TNC-positive group. Our data showed that metastatic PCa PDXs that differ in androgen sensitivity trigger a differential stroma response suggesting that stroma was influenced by tumor cues. Selected stromal markers of osteoblastic PCa induced bone metastases, were induced in the microenvironment of the host organism in metastatic xenografts, although implanted in a non-bone site, indicating a conserved mechanism of tumor cells to induce a stromal pre-metastatic signature with high potential prognostic or diagnostic value.

cancer biology↗

bioRxiv2020

Patient-derived xenografts and organoids model therapy response in prostate cancer

Therapy resistance and metastatic processes in prostate cancer (PCa) remain undefined, due to lack of experimental models that mimic different disease stages. We describe a novel androgen-dependent PCa patient-derived xenograft (PDX) model from treatment-naive, soft tissue metastasis (PNPCa). RNA and whole-exome sequencing of the PDX tissue and organoids confirmed transcriptomic and genomic similarity to primary tumor. PNPCa harbours BRCA2 and CHD1 somatic mutations, shows an SPOP/FOXA1-like transcriptomic signature and microsatellite instability, which occurs in 3% of advanced PCa and has never been modelled in vivo. Comparison of the treatment-naive PNPCa with additional metastatic PDXs (BM18, LAPC9), in a medium-throughput organoid screen of FDA-approved compounds, revealed differential drug sensitivities. Multikinase inhibitors (ponatinib, sunitinib, sorafenib) were broadly effective on all PDX- and patient-derived organoids from advanced cases with acquired resistance to standard-of-care compounds. This proof-of-principle study may provide a preclinical tool to screen drug responses to standard-of-care and newly identified, repurposed compounds.

cancer biology↗