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Biology subjects

Di Benedetto, C.

Publications and source records attributed to Di Benedetto, C..

2 recordsLinked to original sources

High-resolution Inference of Multiplexed Anti-HIV Gene Editing using Single-Cell Targeted DNA Sequencing

Gene therapy-based HIV cure strategies typically aim to excise the HIV provirus directly, or target host dependency factors (HDFs) that support viral persistence. Cure approaches will likely require simultaneous co-targeting of multiple sites within the HIV genome to prevent evolution of resistance, and/or co-targeting of multiple HDFs to fully render host cells refractory to HIV infection. Bulk cell-based methods do not enable inference of co-editing within individual viral or target cell genomes, and do not discriminate between monoallelic and biallelic gene disruption. Here, we describe a targeted single-cell DNA sequencing (scDNA-seq) platform characterizing the near full-length HIV genome and 50 established HDF genes, designed to evaluate anti-HIV gene therapy strategies. We implemented the platform to investigate the capacity of multiplexed CRISPR-Cas9 ribonucleoprotein complexes (Cas9-RNPs) to simultaneously 1) inactivate the HIV provirus, and 2) knockout the CCR5 and CXCR4 HDF (entry co-receptor) genes in microglia and primary monocyte-derived macrophages (MDMs). Our scDNA-seq pipeline revealed that antiviral gene editing is rarely observed at multiple loci (or both alleles of a locus) within an individual cell, and editing probabilities across sites are linked. Our results demonstrate that single-cell sequencing is critical to evaluate the true efficacy and therapeutic potential of HIV gene therapy.

genomics↗

NSMCE2, a Novel Super-Enhancer Regulated Gene, is Linked to Poor Prognosis and Therapy Resistance in Breast Cancer

In this study, we identified two novel super-enhancer associated genes: NSMCE2 and MAL2, highly upregulated in breast tumors, for which high RNA levels significantly and specifically correlate with breast cancer patients poor prognosis. To approach this, we took advantage of existing datasets containing super-enhancers associated genes identified in primary breast tumors and public databases comprising gene expression, genomic and clinical outcomes for patients diagnosed with breast cancer. Through in-vitro pharmacological super-enhancer disruption assays in breast cancer cells we confirmed that super-enhancers are involved in NSMCE2 and MAL2 transcript upregulation and through bioinformatics we found that high levels of NSMCE2 strongly associate with poor response to chemotherapy. This was observed especially for patients diagnosed with aggressive triple negative and HER2 positive tumor types. Finally, we showed that treating breast cancer cells with chemotherapeutic agents while simultaneously decreasing NSMCE2 gene expression by super-enhancer blockade or by directly silencing it, reduces cell viability thus increasing the effectiveness of chemotherapy. Our results indicate that moderating the transcript levels of the novel identified super-enhancer associated gene NSMCE2 could improve patients response to standard chemotherapy and, consequently, may improve disease outcome. In summary by mining existing public breast cancer datasets, our work demonstrates that searching for super-enhancer regulated genes and their association to patients survival and response to treatment, could be an effective method for identifying a signature of tumor specific -not frequently mutated, but super-enhancer dysregulated genes. Our approach offers a new avenue to identify novel biomarkers of poor prognosis and potential pharmacological targets for improving cancer treatment.

cancer biology↗