Biology subjects

Attard, G.

Publications and source records attributed to Attard, G..

6 recordsLinked to original sources

bioRxiv2026

The RNA cargo of plasma-derived extracellular vesicles in mCRPC patients captures cancer cells and tumor microenvironment signals

Circulating analytes in cancer patients capture tumor-related signals. We profiled matched extracellular vesicle (EV) total RNA and cell-free DNA (cfDNA) from the same plasma aliquots of chemo-naive metastatic castration-resistant prostate cancer (mCRPC) patients treated with Enzalutamide (n=54 patients, n=119 longitudinal samples; NCT06981377) at four Italian clinical centers and interrogated data from >10,000 cancer patients' and healthy individuals' samples. Transcript integrity analysis identified coding and non-coding species with fragmentation patterns varying across RNA biotypes. EV-RNA data deconvolution revealed signal from immune populations, including fractions classified as CD4+ T cells, whose abundance increased with disease progression in plasma EVs and mCRPC tissues. By leveraging tissue data-informed mining, we established a novel prostate cancer-related EV-RNA signature that resulted in an independent predictor of poor prognosis and captured tumor microenvironment-derived signals. Integrating EV-RNA and ctDNA information improved patient stratification for progression-free survival. These findings suggest a multifaceted role for plasma EVs as a source of cancer biomarkers.

cancer biology↗

bioRxiv2024

Androgen deprivation therapy-resistant club cells are linked to myeloid cell-driven immunosuppression in the prostate tumor microenvironment

Prostate cancer treatment resistance is a significant challenge facing the field. Genomic and transcriptomic profiling have partially elucidated the mechanisms through which cancer cells escape treatment, but their relation toward the tumor microenvironment (TME) remains elusive. Here we present a comprehensive transcriptomic landscape of the prostate TME at multiple points in the standard treatment timeline employing single-cell RNA-sequencing and spatial transcriptomics data from 110 patients. We identify club-like cells as a key epithelial cell subtype that acts as an interface between the prostate and the immune system. Tissue areas enriched with club-like cells have depleted androgen signaling and upregulated expression of luminal progenitor cell markers. Club-like cells display a senescence-associated secretory phenotype and their presence is linked to increased polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC) activity. Our results indicate that club-like cells partake in inducing myeloid inflammation previously associated with androgen deprivation therapy resistance, providing a rationale for their therapeutic targeting.

cancer biology↗

bioRxiv2023

Integrating extracellular vesicle and circulating cell-free DNA analysis on a single plasma aliquot from breast cancer patients improves the detection of HER2 positivity

BackgroundMulti-analyte liquid biopsies represents an emerging opportunity for non-invasive cancer assessment. We developed ONCE (ONe Aliquot for Circulating Elements), a novel multi-analytes liquid biopsy approach for the isolation of extracellular vesicles (EVs) and cell-free DNA (cfDNA) from a single aliquot of blood. MethodsWe assessed ONCE performance to classify HER2-positive early-stage breast cancer (BrCa) patients by combining RNA and DNA signals on n=64 healthy donors (HD) and non-metastatic BrCa patients. Specifically, we investigated EVs-derived RNA (EV-RNA) and cfDNA by next-generation sequencing (NGS) and by digital droplet PCR (ddPCR). Additionally, we utilized imaging flow cytometry to evaluate EVs as potential carriers of the HER2 protein. ResultsWestern blot analysis and immunocapture assay revealed that EVs-enriched proteins were detected at similar levels among the HER2+ and HER2- subtypes. Sequencing of cfDNA and EV-RNA from HER2- and HER2+ patients demonstrated concordance with in situ molecular analyses of matched tissues. Combined analysis of the two circulating analytes by ddPCR showed increased sensitivity in ERBB2/HER2 detection compared to single nucleic acid components. Multi-analyte liquid biopsy prediction performance was comparable to tissue-based sequencing results from TCGA. Also, we observed HER2 protein on the surface of EVs isolated from the HER2+ BrCa plasma, thus corroborating the potential relevance of studying EVs as companion analyte to cfDNA. ConclusionsThis data confirms the relevance of combining cfDNA and EV-RNA analytes for cancer assessment and supports the ONCE approach as a valuable tool for multi-analytes liquid biopsies clinical implementation.

cancer biology↗

bioRxiv2022

Treatment-mediated selection of lethal prostate cancer clones defined by copy number architectures

Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient relationships of metastases that evade treatment, we performed genomewide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 142 metastatic regions from 10 organs harvested post-mortem from nine men who died from prostate cancer. We identified diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number change, we confirmed a common clone of origin across metastases and diagnostic biopsies; and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. Autosome-defined clusters were characterized by cluster-specific AR gene architectures that in two index cases were topologically more congruent than by chance (p-values 0.03, 3.07x10-8). Integration with anatomical site suggested patterns of spread and points of genomic divergence. Copy number boundaries identified treatment-selected clones with putatively distinct lethal trajectories. Statement of significanceLethal prostate cancer evolves from a single clone of origin and upon a treatment-mediated selection, progresses to lethal disease via a limited number of related clones harboring patient-unique androgen receptor gene architectures.

cancer biology↗

bioRxiv2021

Single-cell ATAC and RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer

Prostate cancer is profoundly heterogeneous and patients would benefit from methods that stratify clinically indolent from more aggressive forms of the disease. We employed single-cell assay for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identified pre-existing and treatment-persistent cell subpopulations that possess transcriptional stem-like features and regenerative potential when subjected to treatment. We found distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent stem-like cells were able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal hitherto unrecognized molecular predictors of treatment response. This suggests that high analytical resolution of pre-clinical models may powerfully inform clinical decision-making.

cancer biology↗

bioRxiv2018

Identification of single nucleotide variants using position-specific error estimation in deep sequencing data

BackgroundTargeted deep sequencing is a highly effective technology to identify known and novel single nucleotide variants (SNVs) with many applications in translational medicine, disease monitoring and cancer profiling. However, identification of SNVs using deep sequencing data is a challenging computational problem as different sequencing artifacts limit the analytical sensitivity of SNV detection, especially at low variant allele frequencies (VAFs).\n\nMethodsTo address the problem of relatively high noise levels in amplicon-based deep sequencing data (e.g. with the Ion AmpliSeq technology) in the context of SNV calling, we have developed a new bioinformatics tool called AmpliSolve. AmpliSolve uses a set of normal samples to model position-specific, strand-specific and nucleotide-specific background artifacts (noise), and deploys a Poisson model-based statistical framework for SNV detection.\n\nResultsOur tests on both synthetic and real data indicate that AmpliSolve achieves a good trade-off between precision and sensitivity, even at VAF below 5% and as low as 1%. We further validate AmpliSolve by applying it to the detection of SNVs in 96 circulating tumor DNA samples at three clinically relevant genomic positions and compare the results to digital droplet PCR experiments.\n\nConclusionsAmpliSolve is a new tool for in-silico estimation of background noise and for detection of low frequency SNVs in targeted deep sequencing data. Although AmpliSolve has been specifically designed for and tested on amplicon-based libraries sequenced with the Ion Torrent platform it can, in principle, be applied to other sequencing platforms as well. AmpliSolve is freely available at https://github.com/dkleftogi/AmpliSolve.

genomics↗