Biology subjects

Suarez, C. J.

Publications and source records attributed to Suarez, C. J..

5 recordsLinked to original sources

bioRxiv2024

DNA-PKcs Inhibition Improves Sequential Gene Insertion of the Full-Length CFTR cDNA in Airway Stem Cells

Cystic fibrosis (CF) is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Although many people with CF (pwCF) are treated using CFTR modulators, some are non-responsive due to their genotype or other uncharacterized reasons. Autologous airway stem cell therapies, in which the CFTR cDNA has been replaced, may enable a durable therapy for all pwCF. Previously, CRISPR-Cas9 with two AAVs was used to sequentially insert two halves of the CFTR cDNA and an enrichment cassette into the CFTR locus. However, the editing efficiency was <10% and required enrichment to restore CFTR function. Further improvement in gene insertion may enhance cell therapy production. To improve CFTR cDNA insertion in human airway basal stem cells (ABCs), we evaluated the use of the small molecules AZD7648 and ART558 which inhibit non-homologous end joining (NHEJ) and micro-homology mediated end joining (MMEJ). Adding AZD7648 alone improved gene insertion by 2-3-fold. Adding both ART558 and AZD7648 improved gene insertion but induced toxicity. ABCs edited in the presence of AZD7648 produced differentiated airway epithelial sheets with restored CFTR function after enrichment. Adding AZD7648 did not increase off-target editing. Further studies are necessary to validate if AZD7648 treatment enriches cells with oncogenic mutations.

genetics↗

bioRxiv2022

Experimental evolution in TP53 deficient gastric organoids recapitulates tumorigenesis

The earliest events during human tumor initiation, while poorly characterized, may hold clues to malignancy detection and prevention1. Here we model occult pre-neoplasia by bi-allelically inactivating TP53, a common early event in gastric cancer, in human gastric organoids. Causal relationships between this initiating genetic lesion and resulting phenotypes were established using experimental evolution in multiple clonally derived cultures over two years. TP53 loss elicited progressive aneuploidy, including copy number alterations and structural variants prevalent in gastric cancers, with evident preferred orders. Longitudinal single cell sequencing of TP53 deficient gastric organoids similarly indicates progression towards malignant transcriptional programs. Moreover, high-throughput lineage tracing with expressed cellular barcodes demonstrates reproducible dynamics whereby initially rare subclones with shared transcriptional programs repeatedly attain clonal dominance. This powerful platform for experimental evolution exposes stringent selection, clonal interference, and a striking degree of phenotypic convergence in pre-malignant epithelial organoids. These data imply predictability in the earliest stages of tumorigenesis and reveal evolutionary constraints and barriers to malignant transformation with implications for earlier detection and interception of aggressive, genome instable tumors.

cancer biology↗

bioRxiv2021

A Deep Learning Model for Molecular Label Transfer that Enables Cancer Cell Identification from Histopathology Images

Deep learning cancer classification systems have the potential to improve cancer diagnosis. However, development of these computational approaches depends on prior annotation through a pathologist. This initial step relying on a manual, low-resolution, time-consuming process is highly variable and subject to observer variance. To address this issue, we developed a novel method, H&E Molecular neural network (HEMnet). This two-step process utilises immunohistochemistry as an initial molecular label for cancer cells on a H&E image and then we train a cancer classifier on the overlapping clinical histopathological images. Using this molecular transfer method, we show that HEMnet accurately distinguishes colorectal cancer from normal tissue at high resolution without the need for an initial manual histopathologic evaluation. Our validation study using histopathology images from TCGA samples accurately estimates tumour purity. Overall, our method provides a path towards a fully automated delineation of any type of tumor so long as there is a cancer-oriented molecular stain available for subsequent learning. Software, tutorials and interactive tools are available at: https://github.com/BiomedicalMachineLearning/HEMnet

bioinformatics↗

bioRxiv2021

Targeted replacement of full-length CFTR in human airway stem cells by CRISPR/Cas9 for pan-mutation correction in the endogenous locus

Cystic fibrosis (CF) is a monogenic disease caused by impaired production and/or function of the cystic fibrosis transmembrane conductance regulator (CFTR) protein. Although we have previously shown correction of the most common pathogenic mutation, there are many other pathogenic mutations throughout the CF gene. An autologous airway stem cell therapy in which the CFTR cDNA is precisely inserted into the CFTR locus may enable the development of a durable cure for almost all CF patients, irrespective of the causal mutation. Here, we use CRISPR/Cas9 and two adeno-associated viruses (AAV) carrying the two halves of the CFTR cDNA to sequentially insert the full CFTR cDNA along with a truncated CD19 (tCD19) enrichment tag in upper airway basal stem cells (UABCs) and human bronchial basal stem cells (HBECs). The modified cells were enriched to obtain 60-80% tCD19+ UABCs and HBECs from 11 different CF donors with a variety of mutations. Differentiated epithelial monolayers cultured at air-liquid interface showed restored CFTR function that was >70% of the CFTR function in non-CF controls. Thus, our study enables the development of a therapy for almost all CF patients, including patients who cannot be treated using recently approved modulator therapies.

bioengineering↗

bioRxiv2018

Joint single cell DNA-Seq and RNA-Seq of gastric cancer reveals subclonal signatures of genomic instability and gene expression

Sequencing the genomes of individual cancer cells provides the highest resolution of intratumoral heterogeneity. To enable high throughput single cell DNA-Seq across thousands of individual cells per sample, we developed a droplet-based, automated partitioning technology for whole genome sequencing. We applied this approach on a set of gastric cancer cell lines and a primary gastric tumor. In parallel, we conducted a separate single cell RNA-Seq analysis on these same cancers and used copy number to compare results. This joint study, covering thousands of single cell genomes and transcriptomes, revealed extensive cellular diversity based on distinct copy number changes, numerous subclonal populations and in the case of the primary tumor, subclonal gene expression signatures. We found genomic evidence of positive selection - where the percentage of replicating cells per clone is higher than expected - indicating ongoing tumor evolution. Our study demonstrates that joining single cell genomic DNA and transcriptomic features provides novel insights into cancer heterogeneity and biology. SIGNIFICANCEWe conducted a massively parallel DNA sequencing analysis on a set of gastric cancer cell lines and a primary gastric tumor in combination with a joint single cell RNA-Seq analysis. This joint study, covering thousands of single cell genomes and transcriptomes, revealed extensive cellular diversity based on distinct copy number changes, numerous subclonal populations and in the case of the primary tumor, subclonal gene expression signatures. We found genomic evidence of positive selection where the percentage of replicating cells per clone is higher than expected indicating ongoing tumor evolution. Our study demonstrates that combining single cell genomic DNA and transcriptomic features provides novel insights into cancer heterogeneity and biology.

genomics↗