Biology subjects

Mazzarella, L.

Publications and source records attributed to Mazzarella, L..

10 recordsLinked to original sources

bioRxiv2026

Seed variation impacts clustering stability in Single-Cell RNA-Seq and can be mitigated by StAbility-BasEd-Reassignment (SABER)

Single-cell RNA-seq clustering is commonly treated as reproducible once a random seed is fixed, yet the choice of seed itself may alter cell assignments and downstream interpretation. We systematically quantified seed-induced clustering variability by running Louvain and Leiden clustering across 100 seeds in Seurat and Scanpy on 28 single-cell RNA-seq datasets from the Human Cell Atlas and IMMUcan. Using Element-Centric Consistency, we found that seed choice affected a substantial fraction of cells, with Scanpy showing more unstable assignments than Seurat on average, 40.46% versus 26.78% unstable cells, respectively. This increased stability came at a marked computational cost: Seurat required approximately 19-fold higher median memory than Scanpy. Seed-dependent clustering variability also propagated to cell-type annotation, particularly among transcriptionally related populations including macrophage/monocyte, endothelial/epithelial and T/NK cell states. To mitigate this instability, we developed StAbility-BasEd Reassignment (SABER), a Scanpy-based framework that identifies seed-sensitive cells across repeated clusterings and reassigns them to stable cluster cores using cosine similarity. SABER improved clustering quality while preserving annotation concordance and reduced median memory usage 3.5-fold compared with Seurat-Louvain. Our results identify seed choice as an underappreciated source of variability in single-cell analysis and provide a scalable strategy to improve clustering robustness.

bioinformatics↗

bioRxiv2024

PoreMeth2: decoding the evolution of methylome alterations with Nanopore sequencing

In epigenetic analysis, identifying differentially methylated regions (DMRs) typically involves detecting groups of consecutive CpGs that show significant changes in their average methylation levels. However, the methylation state of a genomic region can also be characterized by a mixture of patterns (epialleles) with variable frequencies, and the relative proportions of such patterns can provide insights into its mechanisms of formation. Traditional methods based on bisulfite conversion and NGS, due to the read size (150 bp), allow epiallele frequency analysis only in high-CpG-density regions, limiting differential methylation studies to just 50% of the human methylome. Nanopore sequencing, with its long reads, enables the analysis of epiallele frequency across both high- and low-CpG-density regions. We introduce a novel computational approach, PoreMeth2, an R library that integrates epiallelic diversity and methylation frequency changes from Nanopore data to identify DMRs, assess their formation mechanisms, and annotate them to genic and regulatory elements. We applied PoreMeth2 to cancer and glial cell datasets, demonstrating its ability to distinguish epigenomic changes with a strong effect on gene expression from those with a weaker impact on transcriptional activity. PoreMeth2 is publicly available at https://github.com/Lab-CoMBINE/PoreMeth2.

bioinformatics↗

bioRxiv2023

A novel, RAS-independent role for NF1 in microtubular dynamics and damage repair dictates sensitivity to T-DM1 in HER2-positive breast cancer

Antibody-Drug Conjugates (ADC) have revolutionized the treatment of several tumors, and extensive research is being devoted to the identification of predictive biomarkers. These are particularly sought after in fields, like breast cancer, in which multiple ADCs with identical target but different payloads have been approved. NF1 is a tumor suppressor widely mutated across several cancers, best characterized as an inhibitor of RAS signaling. Additional functions have been proposed but not deeply investigated, due to its large size and complex domain structure. Whether somatic NF1 mutations can be used to guide clinical decisions is not known. Here, combining patient data, in vitro/in vivo models and protein biochemistry, we show that NF1 loss sensitizes cancer cells to T-DM1, the first approved ADC in breast cancer, through a novel, RAS-independent function on microtubular dynamics and repair. NF1 exhibits all biochemical properties of a bona fide Microtubule-Associated Protein (MAP) and specifically enhances intratubular repair, a recently discovered phenomenon whose regulation remains poorly characterized. NF1 loss results in mitotic defects and low-grade aneuploidy in cell lines and patients. Increased sensitivity to T-DM1 upon NF1 loss is confirmed in breast cancer patients analysed across institutions in Europe and USA. Our results define NF1 as a key regulatory factor for microtubular repair and the first ADC payload-associated predictive biomarker identified to date.

cancer biology↗

bioRxiv2023

GASOLINE: detecting germline and somatic structural variants from long-reads data.

Long-read sequencing allows analyses of single nucleic-acid molecules and produces sequences in the order of tens to hundreds kilobases. Its application to whole-genome analyses allows identification of complex genomic structural-variants (SVs) with unprecedented resolution. SV identification, however, requires complex computational methods, based on either read-depth or intra- and inter-alignment signatures approaches, which are limited by size or type of SVs. Moreover, most currently available tools only detect germline variants, thus requiring separate computation of sample pairs for comparative analyses. To overcome these limits, we developed a novel tool (Germline And SOmatic structuraL varIants detectioN and gEnotyping; GASOLINE) that groups SV signatures using a sophisticated clustering procedure based on a modified reciprocal overlap criterion, and is designed to identify germline SVs, from single samples, and somatic SVs from paired test and control samples. GASOLINE is a collection of Perl, R and Fortran codes, it analyzes aligned data in BAM format and produces VCF files with statistically significant somatic SVs. Germline or somatic analysis of 30x sequencing coverage experiments requires 4-5 hours with 20 threads. GASOLINE outperformed currently available methods in the detection of both germline and somatic SVs in synthetic and real long-reads datasets. Notably, when applied on a pair of metastatic melanoma and matched-normal sample, GASOLINE identified 6 genuine somatic SVs that were missed using five different sequencing technologies and state-of-the art SV calling approaches. Thus, GASOLINE identifies germline and somatic SVs with unprecedented accuracy and resolution, outperforming currently available state-of-the-art WGS long-reads computational methods.

bioinformatics↗

bioRxiv2022

Coexisting morpho-biotypes unveil the regulatory bases of phenotypic plasticity in pancreatic ductal adenocarcinoma

Intratumor morphological heterogeneity predicts clinical outcomes of pancreatic ductal adenocarcinoma (PDAC). However, it is only partially understood at the molecular level and devoid of clinical actionability. In this study we set out to determine the gene regulatory networks and expression programs underpinning intra-tumor morphological variation in PDAC. To this aim, we identified and deconvoluted at single cell level the molecular profiles characteristic of morphologically distinguishable clusters of PDAC cells that coexisted in individual tumors. We identified three major morpho-biotypes that co-occurred in various proportions in most PDACs: a glandular biotype with classical epithelial ductal features; a biotype with abortive ductal structures and expressing a partial epithelial-to-mesenchymal transition program; and a poorly differentiated biotype showing partial neuronal lineage priming and absence of both ductal features and basement membrane. The identification of PDAC morpho-biotypes may help improve patient stratification and therapeutic schemes taking into account the spectrum of actionable targets expressed by coexisting tumor components.

cancer biology↗

bioRxiv2022

Tumor infiltrating iNKT cells sustain neutrophil pro-tumorigenic functions influencing disease progression in human colorectal cancer

iNKT cells account for a relevant fraction of effector T-cells in the intestine. Although iNKT cells are cytotoxic lymphocytes, their role in colorectal cancer (CRC) remains controversial. From the analysis of colonic LPMCs of human and murine CRC specimens we report that tumor-infiltrating iNKT cells are characterized by an IL17/GM-CSF pro-tumorigenic phenotype, while maintaining cytotoxic properties in the adjacent non-tumoral tissue. Exposure of iNKT cells to the tumor-associated pathobiont Fusobacterium nucleatum blunted their cytotoxic capability and enhanced iNKT cell-mediated neutrophils chemotaxis, which upregulated PMN-MDSC gene signatures and functions. Importantly, in vivo stimulation of iNKT cells with GalCer restored their anti-tumorigenic functions. Survival analyses demonstrated that human CRC co-infiltration by iNKT cells and tumor-associated neutrophils correlates with negative outcomes. Our results reveal a functional plasticity of human intestinal iNKT cells with pro- and anti-tumorigenic activities in CRC, suggesting an iNKT pivotal role in shaping the cancer developmental trajectory.

immunology↗

bioRxiv2022

High-resolution Nanopore methylome-maps reveal random hyper-methylation at CpG-poor regions as driver of chemoresistance in leukemias.

Aberrant DNA methylation at CpG dinucleotides is a hallmark of cancer and is associated with the emergence of resistance to anti cancer treatment, though molecular mechanisms and biological significance remain elusive. Genome scale methylation maps by currently used methods are based on chemical modification of DNA and are best suited for analyses of methylation at CpG rich regions (CpG islands). We report the first high coverage whole genome map in cancer using the long read nanopore technology, which allows simultaneous DNA-sequence and -methylation analyses on native DNA. We analyzed clonal epigenomic/genomic evolution in Acute Myeloid Leukemias (AMLs) at diagnosis and relapse, after chemotherapy. Long read sequencing coupled to a novel computational method allowed definition of differential methylation at unprecedented resolution, and showed that the relapse methylome is characterized by hypermethylation at both CpG islands and sparse CpGs regions. Most differentially methylated genes, however, were not differentially expressed nor enriched for chemoresistance genes. A small fraction of under-expressed and hyper-methylated genes at sparse CpGs, in the gene body, was significantly enriched in transcription factors (TFs). Remarkably, these few TFs supported large gene-regulatory networks including 50% of all differentially expressed genes in the relapsed AMLs and highly-enriched in chemoresistance genes. Notably, hypermethylated regions at sparse CpGs were poorly conserved in the relapsed AMLs, under-represented at their genomic positions and showed higher methylation entropy, as compared to CpG islands. Relapsed AMLs carried few patient specific structural variants and DNA mutations, apparently not involved in drug resistance. Thus, drug resistance in AMLs can be mainly ascribed to the selection of random epigenetic alterations at sparse CpGs of a few transcription factors, which then induce reprogramming of the relapsing phenotype, independently of clonal genomic evolution.

genomics↗

bioRxiv2022

The breast cancer pro-metastatic phenotype requires concomitant hyper-activation of ECM remodeling and dsRNA-IFN1 signaling in rare clone cells

The molecular determinants of breast cancer (BC) pro-metastatic phenotype are largely unknown. Here, we leveraged lentiviral barcoding coupled to single-cell RNA sequencing to trace clonal and transcriptional evolution during BC metastatization. We showed that metastases derive from rare pro-metastatic clones that are under-represented in primary tumors. Both low clonal-fitness and high metastatic-potential are independent of clonal origin. Differential expression and classification analyses revealed that the pro-metastatic phenotype is acquired in rare cells by concomitant hyper-activation of extracellular-matrix remodeling, dsRNA-interferon signaling, and stress-response pathways. Notably, genetic silencing of single pro-metastatic genes from different pathways significantly impairs migration in vitro and metastatization in vivo, with negligible effects on cell proliferation and tumor growth. In addition, gene-expression signatures from identified pro-metastatic genes predicts metastatic progression in BC patients, independently of known prognostic factors. This study elucidates previously unknown mechanisms of BC metastatization, and provides novel prognosis predictors and therapeutic targets for metastasis prevention.

cancer biology↗

bioRxiv2022

High-fat diet promotes Acute Promyelocytic Leukemia through PPARδ-enhanced self-renewal of preleukemic progenitors

Obesity is associated with a higher risk of developing many cancer types including acute promyelocytic leukaemia (APL), a subset of acute myeloid leukemias (AML) characterized by expression of the PML-RAR oncogene. The molecular mechanisms linking obesity and APL development are not known. To model clinical observations, we established a mouse model of diet-induced obesity using transgenic mice constitutively expressing PML-RARA in the hematopoietic system (PML-RAR KI mice) fed either standard (SD) or high-fat (HFD) diets. HFD-fed PML-RAR KI mice developed leukaemia with reduced latency and increased penetrance, as compared to SD-fed mice. HFD leads to accumulation of DNA damage in hematopoietic stem cells (HSCs), but, surprisingly, this was not associated with mutational load gain, as shown by whole genome/exome sequencing of pre-leukemic and leukemic cells. Importantly, very few of the observed mutations were predicted to act as cancer drivers, suggesting the relevance of nongenetic mechanisms. HFD led to an expansion of hematopoietic progenitor cells with a concomitant reduction in long-term hematopoietic stem cells, and in the presence of PML-RAR this was also accompanied by an enhancement of in vitro and in vivo self-renewal. Interestingly, Linoleic Acid (LA), abundant in HFD, recapitulates the effect of HFD on the self-renewal of PML-RAR HPCs by activating the peroxisome proliferator-activated receptor delta (PPAR{delta}), a central regulator of fatty acid metabolism involved in the promotion of cancer progression. Our findings have implications for dietary or pharmacological interventions aimed at counteracting the cancer-promoting effect of obesity. Key pointsO_LIhigh fat diet (HFD) promotes APL leukemogenesis in mouse models, reproducing the exquisite sensitivity to obesity observed in humans C_LIO_LIalthough HFD leads to DNA damage and mutations, the molecular mechanism is nongenetic and linked to the transcription factor PPAR{delta} C_LI

cancer biology↗

bioRxiv2021

Inhibiting LSD1 suppresses coronavirus-induced inflammation but spares innate antiviral activity

Tissue-resident macrophages exert critical but conflicting effects on the progression of coronavirus infections by secreting both anti-viral type I Interferons and tissue-damaging inflammatory cytokines. Steroids, the only class of host-targeting drugs approved for Covid19, indiscriminately suppress both responses, possibly impairing viral clearance, and provide limited clinical benefit. Here we set up a mouse in vitro co-culture system that reproduces the macrophage response to SARS-CoV2 seen in patients and allows quantitation of inflammatory and antiviral activities. We show that the NFKB-dependent inflammatory response can be selectively inhibited by ablating the lysine-demethylase LSD1, which additionally unleashed interferon-independent ISG activation and blocked viral egress through the lysosomal pathway. These results provide a rationale for repurposing LSD1 inhibitors, a class of drugs extensively studied in oncology, for Covid-19 treatment. One-Sentence SummaryTargeting a chromatin-modifying enzyme in coronavirus infections curbs tissue-damage without affecting antiviral response

immunology↗