CRISPR-Cas9 globin editing can induce megabase-scale copy-neutral losses of heterozygosity in hematopoietic cells

CRISPR-Cas9 is a promising technology for gene therapy. However, the ON-target genotoxicity of CRISPR-Cas9 nuclease due to DNA double-strand breaks has received little attention and is probably underestimated. Here we report that genome editing targeting globin genes induces megabase-scale losses of heterozygosity (LOH) from the globin CRISPR-Cas9 cut-site to the telomere (5.2 Mb). In established lines, CRISPR-Cas9 nuclease induces frequent terminal chromosome 11p truncations and rare copy-neutral LOH. In primary hematopoietic progenitor/stem cells, we detect 1.1% of clones (7/648) with acquired megabase LOH induced by CRISPR-Cas9. In-depth analysis by SNP-array reveals the presence of copy-neutral LOH. This leads to 11p15.5 partial uniparental disomy, comprising two Chr11p15.5 imprinting centers (H19/IGF2:IG-DMR/IC1 and KCNQ1OT1:TSS-DMR/IC2) and impacting H19 and IGF2 expression. While this genotoxicity is a safety concern for CRISPR clinical trials, it is also an opportunity to model copy-neutral-LOH for genetic diseases and cancers.

O-089 A Genome Wide Association Study in men with unexplained infertility identifies nine SNPs at the FSHB locus to be associated with Follicle Stimulating Hormone level

Study question Which single nucleotide polymorphisms (SNPs) are associated with Follicle stimulating hormone (FSH) levels in men with unexplained infertility and can affect FSH action and spermatogenesis? Summary answer We identified a genomic region at chromosome 11p.14.1, including nine SNPs, that are significantly associated with FSH levels in men with unexplained infertility. What is known already FSH action is essential for the initiation and maintenance of human spermatogenesis. One well-studied SNP, FSHB c.-211G>T (rs10835638), is associated with FSHB mRNA transcription and directly affects FSH serum levels, testicular volume and spermatogenesis. Carriers of a T-allele in this promoter are diagnosed with functional secondary hypogonadism with isolated FSH deficiency. Other genetic variants, for example at the FSHR have been shown to slightly modulate FSH action, however the clinical impact in these variants seems to be low. The so far identified FSH-associated SNPs revealed an impact of up to 2.3 % on FSH serum level variance. Study design, size, duration A Genome wide association study (GWAS) was performed on a clinically well characterized cohort of 742 men with unexplained infertility (discovery study). Of the nine identified SNPs, validation was performed for rs11031005 and the already described rs10835638 in an independent cohort of 1123 men with unexplained infertility (validation study). Participants/materials, setting, methods Patients were retrospectively selected from our CeRA database Androbase® applying strict selection criteria; DNA was isolated from stored EDTA-blood samples. Informative genetic variants were identified using Illumina PsychArray v1.3. Illumina®GenomeStudio v2.0, PLINK v1.90 and R 3.6.3 were used to perform quantitative association analysis based on normalized FSH values. The validation study was performed using TaqMan PCR for SNP detection and R 3.6.3 for quantitative association to analyze the impact of each SNP on FSH level. Main results and the role of chance Imputation of the GWAS data revealed 94 SNPs with suggestive significance (p < 8.56e-06) and nine SNPs (including rs10835638) with genome-wide significance (p < 4.28e-07). The nine SNPs are all located at the FSHB locus on Chromosome 11p.14.1 and are in high linkage disequilibrium (LD). The validation study of 1123 patients with unexplained infertility for the SNPs rs11003005 and rs10835638 revealed a significant association with FSH (p = 4.71e-06 and p = 5.55e-07) and FSH/LH ratio (p = 2.08e-12 and p = 6.4e-12).The nine significant SNPs accounted for 3.60 –4.65 % variance in FSH serum level each in the entire discovery cohort. In an oligozoospermic subgroup (n = 249) this effect was increased to 4.89 – 6.95 %. This the first GWAS in men with unexplained infertility. This study shows that not one single SNP, but rather a genomic region has an impact on FSH serum level in men with unexplained male infertility. This effect is even more pronounced in the more severe phenotype of oligozoospermic men. Limitations, reasons for caution The study is restricted to men with unexplained infertility, which might cause a selection bias. Validation and functional evaluation of the eight newly identified SNPs in independent cohorts would emphasize the results more. The sample size of 742 limits detection of loci with smaller effect on FSH levels. Wider implications of the findings The determination of one of the nine SNPs can improve diagnostic precision in identifying men with secondary functional hypogonadism with isolated FSH deficiency. An oligozoospermic subgroup of these men would putatively benefit from FSH treatment and has to be proven in randomized controlled trials. Trial registration number German Research Foundation CRU326

Cellworks Omics Biology Model (CBM) to identify amplifications of chromosome 11p and 1p predict paclitaxel and carboplatin resistance.

e21208 Background: Paclitaxel and carboplatin (PC) is used to treat a wide variety of malignancies including gynecologic, breast, lung, and occult primary cancers. In NSCLC, PC led to a substantial improvement in 1-yr survival from 10% (P alone) to approximately 50% seen with the combination. Nevertheless, a large proportion of patients do not respond. An optimal cytotoxic strategy for managing NSCLC and the discovery of chemotherapy biomarkers to guide treatment selection remain unmet needs in the clinic. Cellworks CBM platform identified a unique chromosomal signature which permits a stratification of which patients are most likely to respond to PC treatment. Methods: 22 patients treated with PC were published in TCGA dataset and selected for analysis. The mutation and copy number aberrations from individual cases served as input into the CBM (generated from PubMed and other online resources) to create a patient-specific protein network map. Disease-biomarkers unique to each patient were identified within protein network maps. Digital drug simulations were conducted by measuring effect of PC on a cell growth score comprised of a composite of cell proliferation, apoptosis, and other cancer hallmarks. Drug simulations were systematically conducted to identify and evaluate therapeutic efficacy. The drug combination was mapped to the patient genome along with a rational mechanism of action and validated based on the genomic profile and its biological consequences. Results: Of the 22 patients treated with PC, 13 had clinical responses and 9 were non-responders. The computer simulation correctly predicted response in 16/22 with 72.73% accuracy, 55.56% specificity and 84.62% sensitivity. CBM identified novel amplified segments of Chromosome 11p and 1p were responsible for non-responsiveness to PC. Key genes on these chromosomes were identified belonging to the autophagy, reactive oxygen species (ROS) scavenging, DNA repair, and microtubule polymerization pathways. Amplification of AMBRA1, ATG13 and TRAF6 (11p) led to autophagy upregulation resulting in low ROS level, a well-documented resistance loop for chemotherapy. SIRT3 and CAT (11p), ROS scavenging genes, were also upregulated due to increase in copy number. CTH (1p) is another key enzyme involved in GSH-mediated ROS scavenging and was also upregulated. Biosimulation indicated a low ROS level was the key reason of resistance to PC. Heightened DNA damage repair due FANCF and ZNF143 (11p amp) and USP1 (1p amp), was another cause of PC resistance. These discoveries suggest that a combination of an autophagy inhibitor / BCL2 mimetic might prove useful to reverse PC resistance associated with 11p and 1p amp. Conclusions: This study highlights how CBM simulation platform can help to identify novel patient segments for therapy response prediction and use drug re-purposing to overcome chemotherapy resistance.