Linking CRISPR-Cas9 double-strand break profiles to gene editing precision with BreakTag.

Cas9 can cleave DNA in both blunt and staggered configurations, resulting in distinct editing outcomes, but what dictates the type of Cas9 incisions is largely unknown. In this study, we developed BreakTag, a versatile method for profiling Cas9-induced DNA double-strand breaks (DSBs) and identifying the determinants of Cas9 incisions. Overall, we assessed cleavage by SpCas9 at more than 150,000 endogenous on-target and off-target sites targeted by approximately 3,500 single guide RNAs. We found that approximately 35% of SpCas9 DSBs are staggered, and the type of incision is influenced by DNA:gRNA complementarity and the use of engineered Cas9 variants. A machine learning model shows that Cas9 incision is dependent on the protospacer sequence and that human genetic variation impacts the configuration of Cas9 cuts and the DSB repair outcome. Matched datasets of Cas9 and engineered variant incisions with repair outcomes show that Cas9-mediated staggered breaks are linked with precise, templated and predictable single-nucleotide insertions, demonstrating that a scission-based gRNA design can be used to correct clinically relevant pathogenic single-nucleotide deletions.

High clonal diversity and spatial genetic admixture in early prostate cancer and surrounding normal tissue.

Somatic copy number alterations (SCNAs) are pervasive in advanced human cancers, but their prevalence and spatial distribution in early-stage, localized tumors and their surrounding normal tissues are poorly characterized. Here, we perform multi-region, single-cell DNA sequencing to characterize the SCNA landscape across tumor-rich and normal tissue in two male patients with localized prostate cancer. We identify two distinct karyotypes: 'pseudo-diploid' cells harboring few SCNAs and highly aneuploid cells. Pseudo-diploid cells form numerous small-sized subclones ranging from highly spatially localized to broadly spread subclones. In contrast, aneuploid cells do not form subclones and are detected throughout the prostate, including normal tissue regions. Highly localized pseudo-diploid subclones are confined within tumor-rich regions and carry deletions in multiple tumor-suppressor genes. Our study reveals that SCNAs are widespread in normal and tumor regions across the prostate in localized prostate cancer patients and suggests that a subset of pseudo-diploid cells drive tumorigenesis in the aging prostate.

Inhibition of O-GlcNAcylation Reduces Cell Viability and Autophagy and Increases Sensitivity to Chemotherapeutic Temozolomide in Glioblastoma.

Glioblastoma (GB) is the most aggressive primary malignant brain tumor and is associated with short survival. O-GlcNAcylation is an intracellular glycosylation that regulates protein function, enzymatic activity, protein stability, and subcellular localization. Aberrant O-GlcNAcylation is related to the tumorigenesis of different tumors, and mounting evidence supports O-GlcNAc transferase (OGT) as a potential therapeutic target. Here, we used two human GB cell lines alongside primary human astrocytes as a non-tumoral control to investigate the role of O-GlcNAcylation in cell proliferation, cell cycle, autophagy, and cell death. We observed that hyper O-GlcNAcylation promoted increased cellular proliferation, independent of alterations in the cell cycle, through the activation of autophagy. On the other hand, hypo O-GlcNAcylation inhibited autophagy, promoted cell death by apoptosis, and reduced cell proliferation. In addition, the decrease in O-GlcNAcylation sensitized GB cells to the chemotherapeutic temozolomide (TMZ) without affecting human astrocytes. Combined, these results indicated a role for O-GlcNAcylation in governing cell proliferation, autophagy, cell death, and TMZ response, thereby indicating possible therapeutic implications for treating GB. These findings pave the way for further research and the development of novel treatment approaches which may contribute to improved outcomes and increased survival rates for patients facing this challenging disease.

R-loop proximity proteomics identifies a role of DDX41 in transcription-associated genomic instability.

Transcription poses a threat to genomic stability through the formation of R-loops that can obstruct progression of replication forks. R-loops are three-stranded nucleic acid structures formed by an RNA-DNA hybrid with a displaced non-template DNA strand. We developed RNA-DNA Proximity Proteomics to map the R-loop proximal proteome of human cells using quantitative mass spectrometry. We implicate different cellular proteins in R-loop regulation and identify a role of the tumor suppressor DDX41 in opposing R-loop and double strand DNA break accumulation in promoters. DDX41 is enriched in promoter regions in vivo, and can unwind RNA-DNA hybrids in vitro. R-loop accumulation upon loss of DDX41 is accompanied with replication stress, an increase in the formation of double strand DNA breaks and transcriptome changes associated with the inflammatory response. Germline loss-of-function mutations in DDX41 lead to predisposition to acute myeloid leukemia in adulthood. We propose that R-loop accumulation and genomic instability-associated inflammatory response may contribute to the development of familial AML with mutated DDX41.

Single-cell analysis of structural variations and complex rearrangements with tri-channel processing.

Structural variation (SV), involving deletions, duplications, inversions and translocations of DNA segments, is a major source of genetic variability in somatic cells and can dysregulate cancer-related pathways. However, discovering somatic SVs in single cells has been challenging, with copy-number-neutral and complex variants typically escaping detection. Here we describe single-cell tri-channel processing (scTRIP), a computational framework that integrates read depth, template strand and haplotype phase to comprehensively discover SVs in individual cells. We surveyed SV landscapes of 565 single cells, including transformed epithelial cells and patient-derived leukemic samples, to discover abundant SV classes, including inversions, translocations and complex DNA rearrangements. Analysis of the leukemic samples revealed four times more somatic SVs than cytogenetic karyotyping, submicroscopic copy-number alterations, oncogenic copy-neutral rearrangements and a subclonal chromothripsis event. Advancing current methods, single-cell tri-channel processing can directly measure SV mutational processes in individual cells, such as breakage-fusion-bridge cycles, facilitating studies of clonal evolution, genetic mosaicism and SV formation mechanisms, which could improve disease classification for precision medicine.