Biology subjects

De Falco, A.

Publications and source records attributed to De Falco, A..

8 recordsLinked to original sources

bioRxiv2026

Introducing the digital PCR data essentials standard to harmonize data structure for clinical and research use

Digital PCR (dPCR) is a powerful technology for absolute quantification of nucleic acids, valued for its accuracy, sensitivity, and repeatability. Yet, the commercialization of different instruments with proprietary software has introduced challenges to data analysis, interoperability, and comparability. Therefore, we present the Digital PCR Data Essentials Standard (DDES) - a lightweight, human- and machine-readable, and cross-platform data standard developed in collaboration with the dPCR community. The standard consists of three file types designed to enable both manual inspection and automated analysis: (i) a main file summarizing experiment and reaction-level (meta-)data; (ii) an assay file describing targets and detection chemistry, and (iii) intensity files capturing partition-level raw fluorescence data per reaction. DDES supports a wide range of current dPCR applications, including singleplex and multiplex assays, endpoint and real-time readouts, and will be curated to implement future dPCR developments. By harmonizing the data structure, DDES lays out the foundation for FAIR dPCR data practices and supports improved software compatibility, collaborative and reproducible research, and future dPCR data repositories.

bioinformatics↗

bioRxiv2026

Distinct mechanisms of CNV formation at the human 15q13.3 locus

Human chromosome 15q13.3 is a hotspot for recurrent pathogenic copy number variants (CNVs), which remain unresolved at the sequence level. We generated haplotype-resolved assemblies for 10 patient-parent trios and found that both the long ("BP4-BP5") and short ("CHRNA7") forms of 15q13.3 CNVs arise predominantly by non-allelic homologous recombination (NAHR) enabled by inversion polymorphisms. While most BP4-BP5 CNVs are structurally distinct, three breakpoints cluster in a 2 kbp PRDM9-enriched recombination hotspot. CHRNA7 CNVs originate from NAHR between CHRNA7-LCR repeats embedded within locus-spanning inversions and give rise to paired deletion/duplication events. Population analyses of 581 population haplotypes reveal at least 18 distinct structural haplotypes in 15q13.3 and more than 10-fold ancestry-stratification of BP4-BP5 CNV risk, where 68.4% of Europeans but only 5.1% of East Asians are predisposed. Comparison to six ape species indicates that the duplication architecture promoting instability expanded recently and is largely human-specific.

genetics↗

bioRxiv2025

Knowledge-informed multimodal cfDNA analysis improves sensitivity and generalization in cancer detection

Liquid biopsy offers a minimally invasive opportunity to detect and monitor cancers through analysis of cell-free DNA (cfDNA). However, current approaches face challenges of limited sensitivity at low tumor fractions, technical variability, and poor generalization across cohorts. Tumor-informed targeted methods offer high specificity but suffer from low sensitivity due to random sampling, tumor evolution and adaptation (including resistance mechanisms), and other sources of heterogeneity. Conversely, tumor-naive genome-wide methods can increase sensitivity but often sacrifice specificity, particularly at low tumor fractions. We developed Fragmentomics Analysis for Tumor Evaluation with AI (Fate-AI), a multimodal framework that integrates fragmentomic and methylation-derived features from low-pass whole-genome sequencing (LPWGS) and cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq). It employs a knowledge-informed strategy to select recurrently altered genomic regions and tissue-specific methylation loci to combine the advantages of tumor-naive approaches with the specificity of tumor-informed approaches. This approach derives robust per-sample normalized features that mitigate batch effects and enhance cross-cohort reproducibility. We evaluated Fate-AI on a total of 1,219 plasma samples spanning ten cancer types and healthy controls from multiple laboratories and sequencing centers, including 432 newly profiled cases (280 with both cfMeDIP-seq and LPWGS) together with 787 samples from four independent public datasets. Fate-AI achieved superior sensitivity and specificity compared to state-of-the-art methods, detecting tumor-derived signals at fractions as low as 10-5 in experimental dilutions. Fate-AI scores correlated with disease stage and tracked longitudinal progression, anticipating relapse months before clinical progression. Furthermore, Fate-AI enabled tissue-of-origin classification, with AUCs ranging from 0.84 to 0.97 across six cancer types. Collectively, our results demonstrate that Fate-AI provides a sensitive, generalizable, and clinically actionable platform for early detection, minimal residual disease monitoring, and tissue-of-origin classification, supporting its potential as a liquid biopsy framework in precision oncology.

cancer biology↗

bioRxiv2025

Transposable Elements and Homotypic Niches Drive Immune Dynamics and Resistance in Melanoma Epigenetic-based immunotherapy

Melanoma plasticity drives immune evasion and therapy resistance through dynamic cell-state transitions beyond genetic alterations. Epigenetic remodeling critically influences such processes, yet its role in reshaping the tumor ecosystem under therapeutic pressure remains unresolved. Here, we profiled longitudinal biopsies from melanoma patients treated in the phase Ib NIBIT-M4 epi-immunotherapy clinical trial (NCT02608437), testing the combination of a DNMT1 inhibitor with anti-CTLA4 using single-cell multiome and high-resolution spatial transcriptomics. Integrated analyses resolved seven malignant meta-programs, including a rare Wnt/{beta}-catenin-driven melanocytic state and a de-differentiated neural crest-like state enriched in non-responders. Spatial modeling revealed that homotypic clustering stabilizes resistant programs, with neural crest-like cells forming compact, centrally localized niches, whereas Wnt/{beta}-catenin subpopulations displayed a bimodal architecture, either cohesive clusters sustained by adhesion or dispersed, transcriptionally plastic cells. Responders exhibited progressive enrichment of an antigen presentation/interferon program and coordinated remodeling of the tumor microenvironment with T and B cell expansion, whereas tumors from non-responder patients maintained stable composition of neural crest-like clusters. Epigenetic therapy reactivated transposable elements, providing both regulatory signals that prime innate immunity within microenvironment and generating antigens that drive immunoediting and immunogenicity of Antigen presentation/interferon cell states in responders. Finally, NFATC2 emerged as a master regulator of neural crests-like transcriptional phenotypes and promoter of resistance to therapeutic interventions in melanoma patients. NFATC2 perturbation was able to shift tumor cells towards more differentiated and immunogenic states. These findings reveal how epigenetic-based immunotherapy reshapes melanoma ecosystems, provide mechanistic insights into how multiple transcriptional programs promote tumor plasticity and resistance to both combinatorial therapies and immune checkpoint blockade, identify spatial clustering as a principle stabilizing resistant niches, and highlight {beta}-catenin and NFATC2 as actionable vulnerabilities to overcome resistance.

genomics↗

bioRxiv2025

From Plasmid to Pure Protein: Production and Characterization of SARS-CoV-2 PLpro

Papain-like protease (PLpro) from SARS-CoV-2 is a high-priority target for COVID-19 antiviral drug development. We present protocols for PLpro production in Escherichia coli. PLpro expressed as a fusion with the Saccharomyces cerevisiae Smt3 protein (SUMO), is purified and obtained in its native form upon hydrolysis, with yields as high as 38 mg L-1. The protocol also provides isotope-enriched samples suitable for NMR studies. Protocols are also presented for PLpro characterization by mass spectrometry, 1D 19F-NMR and 2D heteronuclear NMR, and a fluorescence-based enzyme assay. HighlightsO_LIProduction, purification, and biochemical analysis of native N- and C-termini PLpro C_LIO_LIHigh yields in E. coli, up to 38 mg L-1 using lysogeny broth. C_LIO_LISupports labeled samples for inhibitor interaction studies. C_LIO_LI19F NMR and fluorescence assays for inhibitor screening and IC50 determination. C_LI eTOC BlurbSARS-CoV-2 PLpro is a key cysteine protease involved in viral replication and immune evasion, making it an important target for antiviral drug development. This study presents a detailed protocol for PLpro production, purification, and biochemical analysis, achieving high yields in E. coli. The workflow includes fusion expression with a His-SUMO tag, isotope labeling for inhibitor studies, and assays for screening and quantifying inhibitors. This comprehensive guide facilitates large-scale production of active PLpro for drug discovery and structural studies.

biochemistry↗

bioRxiv2024

Sifting Through the Noise: A Computational Pipeline for Accurate Prioritization of Protein- Protein Binding Candidates in High-Throughput Protein Libraries

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners, but often include false positives. Furthermore, they provide no information about what the binding region is (e.g. the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competition Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment, along with the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies to AF and AF-CBA, to help users identify scenarios where the approach will be most useful. Given the speed and accuracy of the methodology, we expect it to be generally applicable to facilitate target selection for experimental verification starting from high-throughput protein libraries. Table of Contents O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=173 SRC="FIGDIR/small/576374v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@b90071org.highwire.dtl.DTLVardef@1cc2f66org.highwire.dtl.DTLVardef@3c1109org.highwire.dtl.DTLVardef@1827353_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2021

A fast variational algorithm to detect the clonal copy number substructure of tumors from single-cell data

Here we report Single CEll Variational ANeuploidy analysis (SCEVAN), a fast variational algorithm for the deconvolution of the clonal substructure of tumors from single cell data. It uses a multichannel segmentation algorithm exploiting the assumption that all the cells in a given copy number clone share the same breakpoints. Thus, the smoothed expression profile of every individual cell constitutes part of the evidence of the copy number profile in each subclone. SCEVAN can automatically and accurately discriminate between malignant and non-malignant cells, resulting in a practical framework to analyze tumors and their microenvironment. We apply SCEVAN to several datasets encompassing 106 samples and 93,322 cells from different tumors types and technologies. We demonstrate its application to characterize the intratumor heterogeneity and geographic evolution of malignant brain tumors.

bioinformatics↗

bioRxiv2020

Primary and recurrent glioma patient-derived orthotopic xenografts (PDOX) represent relevant patient avatars for precision medicine

Patient-derived cancer models are essential tools for studying tumor biology and preclinical interventions. Here, we show that glioma patient-derived orthotopic xenografts (PDOXs) enable long-term propagation of patient tumors and represent clinically relevant patient avatars. We created a large collection of PDOXs from primary and recurrent gliomas with and without mutations in IDH1, which retained histopathological, genetic, epigenetic and transcriptomic features of patient tumors with no mouse-specific clonal evolution. Longitudinal PDOX models recapitulate the limited genetic evolution of gliomas observed in patient tumors following treatment. PDOX-derived standardized tumor organoid cultures enabled assessment of drug responses, which were validated in mice. PDOXs showed clinically relevant responses to Temozolomide and to targeted treatments such as EGFR and CDK4/6 inhibitors in (epi)genetically defined groups, according to MGMT promoter and EGFR/CDK status respectively. Dianhydrogalactitol, a bifunctional alkylating agent, showed promising potential against glioblastoma. Our study underlines the clinical relevance of glioma PDOX models for translational research and personalized treatment studies.

cancer biology↗