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From initial human papillomavirus (HPV) infection and precursor stages, the development of cervical cancer takes decades. High-sensitivity HPV DNA testing is currently recommended as primary screening method for cervical cancer, whereas better triage methodologies are encouraged to provide accurate risk management for HPV-positive women. Given that virus-driven genomic variation accumulates during cervical carcinogenesis, we designed a 39 Mb custom capture panel targeting 17 HPV types and 522 mutant genes related to cervical cancer. Using capture-based next-generation sequencing, HPV integration status, somatic mutation and copy number variation were analyzed on 34 paired samples, including 10 cases of HPV infection (HPV+), 10 cases of cervical intraepithelial neoplasia (CIN) grade and 14 cases of CIN2+ (CIN2: n = 1; CIN2-3: n = 3; CIN3: n = 9; squamous cell carcinoma: n = 1). Finally, the machine learning algorithm (Random Forest) was applied to build the risk stratification model for cervical precursor lesions based on CIN2+ enriched biomarkers. Generally, HPV integration events (11 in HPV+, 25 in CIN1 and 56 in CIN2+), non-synonymous mutations (2 in CIN1, 12 in CIN2+) and copy number variations (19.1 in HPV+, 29.4 in CIN1 and 127 in CIN2+) increased from HPV+ to CIN2+. Interestingly, ‘common’ deletion of mitochondrial chromosome was significantly observed in CIN2+ (P = 0.009). Together, CIN2+ enriched biomarkers, classified as HPV information, mutation, amplification, deletion and mitochondrial change, successfully predicted CIN2+ with average accuracy probability score of 0.814, and amplification and deletion ranked as the most important features. Our custom capture sequencing combined with machine learning method effectively stratified the risk of cervical lesions and provided valuable integrated triage strategies.

Genome editing technologies hold tremendous potential in biomedical research and drug development. Therefore, it is imperative to discover gene editing tools with superior cutting efficiency, good fidelity, and fewer genomic restrictions. Here, we report a CRISPR/Cas9 from Faecalibaculum rodentium, which is characterized by a simple PAM (5′-NNTA-3′) and a guide RNA length of 21–22 bp. We find that FrCas9 could achieve comparable efficiency and specificity to SpCas9. Interestingly, the PAM of FrCas9 presents a palindromic sequence, which greatly expands its targeting scope. Due to the PAM sequence, FrCas9 possesses double editing-windows for base editor and could directly target the TATA-box in eukaryotic promoters for TATA-box related diseases. Together, our results broaden the understanding of CRISPR/Cas-mediated genome engineering and establish FrCas9 as a safe and efficient platform for wide applications in research, biotechnology and therapeutics.

Human papillomavirus (HPV) integration is a critical step in cervical cancer development; however, the oncogenic mechanism at the genome-wide transcriptional level is still poorly understood. In this study, we employed integrative analysis on multi-omics data of six HPV-positive and three HPV-negative cell lines. Through HPV integration detection, super-enhancer (SE) identification, SE-associated gene expression and extrachromosomal DNA (ecDNA) investigation, we aimed to explore the genome-wide transcriptional influence of HPV integration. We identified seven high-ranking cellular SEs generated by HPV integration in total (the HPV breakpoint-induced cellular SEs, BP-cSEs), leading to intra-chromosomal and inter-chromosomal regulation of chromosomal genes. The pathway analysis revealed that the dysregulated chromosomal genes were correlated to cancer-related pathways. Importantly, we demonstrated that BP-cSEs existed in the HPV–human hybrid ecDNAs, explaining the above transcriptional alterations. Our results suggest that HPV integration generates cellular SEs that function as ecDNA to regulate unconstrained transcription, expanding the tumorigenic mechanism of HPV integration and providing insights for developing new diagnostic and therapeutic strategies.