Biology subjects

Frige, G.

Publications and source records attributed to Frige, G..

4 recordsLinked to original sources

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

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↗

bioRxiv2021

Nanopore ReCappable Sequencing maps SARS-CoV-2 5' capping sites and provides new insights into the structure of sgRNAs

The SARS-CoV-2 virus has a complex transcriptome characterised by multiple, nested sub genomic RNAs used to express structural and accessory proteins. Long-read sequencing technologies such as nanopore direct RNA sequencing can recover full-length transcripts, greatly simplifying the assembly of structurally complex RNAs. However, these techniques do not detect the 5' cap, thus preventing reliable identification and quantification of full-length, coding transcript models. Here we used Nanopore ReCappable Sequencing (NRCeq), a new technique that can identify capped full-length RNAs, to assemble a complete annotation of SARS-CoV-2 sgRNAs and annotate the location of capping sites across the viral genome. We obtained robust estimates of sgRNA expression across cell lines and viral isolates and identified novel canonical and non-canonical sgRNAs, including one that uses a previously un-annotated leader-to-body junction site. The data generated in this work constitute a useful resource for the scientific community and provide important insights into the mechanisms that regulate the transcription of SARS-CoV-2 sgRNAs.

genomics↗