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Tamburello, M.

Publications and source records attributed to Tamburello, M..

3 recordsLinked to original sources

A multilayered in silico analysis links UHRF1, DNA methylation and developmental chromatin memory to lineage-dependent prognosis in gastric, renal and adrenal cancers

Aberrant DNA methylation is a hallmark of cancer, but its clinical interpretation remains debated. UHRF1, a key epigenetic adaptor for DNA methylation maintenance and chromatin bivalency regulation in embryonic stem cells, is frequently overexpressed yet shows context-dependent prognostic behaviour. By integrating bulk and single-cell transcriptomics, CpG-resolution methylation, developmental chromatin states, immune profiling and clinical outcomes across gastric (STAD), clear-cell renal (KIRC) and adrenal (ACC) carcinomas, we identified a four-class UHRF1-embryonic morphogenesis (UHRF1-EM) framework resolving this paradox. This axis revealed an inverse prognostic pattern: whilst across all three tumours EM-low and EM-high states mark better or worse prognosis, respectively, UHRF1-high levels associate with favourable outcome in STAD (UH-EML), and unfavourable in KIRC and ACC (UH-EMH). The classification proved reproducible and independently prognostic after adjustment for stage and molecular subtypes, outperforming existing classifiers and exceeding pathological stage in KIRC and ACC. Multivariable models incorporating UHRF1-EM yielded uniformly positive {Delta}C-indices. Hypermethylation associated with the UHRF1-EM axis was enriched at ESC bivalent developmental loci (EM and oncofoetal genes), but not at housekeeping cell-cycle sites. In STAD, this pattern was related to oncofoetal gene downregulation and best prognosis, whereas in KIRC and ACC it matched with gene-body/enhancer methylation, higher EM expression, immunosuppressive microenvironments and worst prognosis. Together, these findings establish the UHRF1-EM axis as a clinically robust molecular classifier and support a mechanistic model in which tumour-specific epigenetic engagement of developmental loci may contribute to the prognostic inversion, providing a foundation for further mechanistic experimental validation.

cancer biology↗

Updating ACC preclinical models: characterization of two new patient-derived cell lines

AdrenoCortical Carcinoma (ACC) is an aggressive, rare and heterogenous malignancy, that requires diverse preclinical models. For this reason, the development of new cell lines is pivotal. Here we describe the development and characterization of two of them, SMAC-2 and SMAC-3, established from surgical specimens of ACC patients. The characterization included their mutational profiling, the evaluation of steroidogenic enzymes expression, secretory activity and the expression of steroid hormone receptors. The proliferative ability of these cells within a zebrafish embryos xenograft was also evaluated. SMAC-2 originated from a metastatic EDP-M-treated ACC in a female patient with Cushing syndrome and hyperandrogenism, while SMAC-3 derived from a male patient with a mitotane-treated local recurrence, with no sign of hypercortisolism. TP53 was mutated in both lines. SMAC-2 cells were characterized by a pathogenic alteration on CTTNB1 gene and a deletion of CDKN2A gene, while SMAC-3 on MSH2 gene. Basal hormonal status analysis showed a cell model-specific fingerprint either in the hormonal secretion and gene and protein expression of steroid hormone receptors. SMAC-2 secreted high levels of cortisol. SMAC-3 secreted low basal level of cortisol. Mitotane displayed in both cell lines a low potency. Under the experimental conditions used, the xenografted area did not increase for both cell models. Experiments were carried out to study the stability of the two cell lines. SMAC-2 and SMAC-3 display unique molecular and functional features, expanding the repertoire of experimental ACC models and representing valuable tools for preclinical research alongside established cell lines.

pharmacology and toxicology↗

Dlk1 is a novel adrenocortical stem/progenitor cell marker that predicts malignancy in adrenocortical carcinoma

Disruption of processes involved in tissue development and homeostatic self-renewal is increasingly implicated in cancer initiation, progression, and recurrence. The adrenal cortex is a dynamic tissue that undergoes life-long turnover. Here, using genetic fate mapping and murine adrenocortical carcinoma (ACC) models, we have identified a population of adrenocortical stem cells that express delta-like non-canonical Notch ligand 1 (DLK1). These cells are active during development, near dormant postnatally but are re-expressed in ACC. In a study of over 200 human ACC samples, we have shown DLK1 expression is ubiquitous and is an independent prognostic marker of recurrence-free survival. Paradoxically, despite its progenitor role, spatial transcriptomic analysis has identified DLK1 expressing cell populations to have increased steroidogenic potential in human ACC, a finding also observed in four human and one murine ACC cell lines. Finally, the cleavable DLK1 ectodomain is measurable in patients serum and can discriminate between ACC and other adrenal pathologies with high sensitivity and specificity to aid in diagnosis and follow-up of ACC patients. These data demonstrate a prognostic role for DLK1 in ACC, detail its hierarchical expression in homeostasis and oncogenic transformation and propose a role for its use as a biomarker in this malignancy. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/609117v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@12aba74org.highwire.dtl.DTLVardef@374daaorg.highwire.dtl.DTLVardef@cbdc37org.highwire.dtl.DTLVardef@1e6aeac_HPS_FORMAT_FIGEXP M_FIG C_FIG Statement of significanceThis study presents DLK1 as a novel biomarker in ACC with opportunities for use in the diagnosis, prognosis and longitudinal follow up of patients. DLK1, a marker of adrenocortical stem cells, is re-expressed in ACC, is measurable in patients serum and is associated with increased malignancy.

cancer biology↗