Zinc-finger nucleases (ZFNs), transcription activator-like endonucleases (TALENs), and CRISPR-associated Cas9 endonucleases are three major generations of genome editing tools. However, no parallel comparison about the efficiencies and off-target activity of the three nucleases has been reported, which is critical for the final clinical decision. We for the first time developed the genome-wide unbiased identification of double-stranded breaks enabled by sequencing (GUIDE-seq) method in ZFNs and TALENs with novel bioinformatics algorithms to evaluate the off-targets. By targeting human papillomavirus 16 (HPV16), we compared the performance of ZFNs, TALENs, and SpCas9 in vivo. Our data showed that ZFNs with similar targets could generate distinct massive off-targets (287–1,856), and the specificity could be reversely correlated with the counts of middle “G” in zinc finger proteins (ZFPs). We also compared the TALENs with different N-terminal domains (wild-type [WT]/αN/βN) and G recognition modules (NN/NH) and found the design (αN or NN) to improve the efficiency of TALEN inevitably increased off-targets. Finally, our results showed that SpCas9 was more efficient and specific than ZFNs and TALENs. Specifically, SpCas9 had fewer off-target counts in URR (SpCas9, n = 0; TALEN, n = 1; ZFN, n = 287), E6 (SpCas9, n = 0; TALEN, n = 7), and E7 (SpCas9, n = 4; TALEN, n = 36). Taken together, we suggest that for HPV gene therapies, SpCas9 is a more efficient and safer genome editing tool. Our off-target data could be used to improve the design of ZFNs and TALENs, and the universal in vivo off-target detection pipeline for three generations of artificial nucleases provided useful tools for genome engineering-based gene therapy.

Gamma delta (γδ) T cells demonstrate strong cytotoxicity against diverse cancer cell types in an MHC-independent manner, rendering them promising contenders for cancer therapy. Although amplification and adoptive transfer of γδ T cells are being evaluated in the clinic, their therapeutic efficacy remains unsatisfactory, primarily due to the influence of the immunosuppressive tumor microenvironment (TME). Currently, the utilization of targeted therapeutic antibodies against inhibitory immune checkpoint (ICP) molecules is a viable approach to counteract the immunosuppressive consequences of the TME. Notably, PD-1/PD-L1 checkpoint inhibitors are considered primary treatment options for diverse malignancies, with the objective of preserving the response of αβ T cells. However, γδ T cells also infiltrate various human cancers and are important participants in cancer immunity, thereby influencing patient prognosis. Hence, it is imperative to comprehend the reciprocal impact of the PD-1/PD-L1 axis on γδ T cells. This understanding can serve as a therapeutic foundation for improving γδ T cells adoptive transfer therapy and may offer a novel avenue for future combined immunotherapeutic approaches.

A genome editing tool targeting the high-risk human papillomavirus (HPV) oncogene is a promising therapeutic strategy to treat HPV-related cervical cancer. To improve gene knockout efficiency, we developed a gene knockout chain reaction (GKCR) method for continually generating mutagenic disruptions and used this method to disrupt the HPV18 E6 and E7 genes. We verified that the GKCR Cas9/guide RNA (gRNA) cassettes could integrated into the targeted loci via homology-independent targeted insertion (HITI). The qPCR results revealed that the GKCR method enabled a relatively higher Cas9/gRNA cassette insertion rate than a control method (the common CRISPR-Cas9 strategy). Tracking of Indels by DEcomposition (TIDE) assay results showed that the GKCR method produced a significantly higher percentage of insertions or deletions (indels) in the HPV18 E6 and E7 genes. Furthermore, by targeting the HPV18 E6/E7 oncogenes, we found that the GKCR method significantly upregulated the P53/RB proteins and inhibited the proliferation and motility of HeLa cells. The GKCR method significantly improved the gene knockout efficiency of the HPV18 E6/E7 oncogenes, which might provide new insights into treatment of HPV infection and related cervical cancer.

Neoadjuvant chemotherapy (NACT) remains an attractive alternative for controlling locally advanced cervical cancer. However, approximately 15–34% of women do not respond to induction therapy. To develop a risk stratification tool, 56 patients with stage IB‐IIB cervical cancer are included in 2 research centers from the discovery cohort. Patient‐specific somatic mutations led to NACT non‐responsiveness are identified by whole‐exome sequencing. Next, CRISPR/Cas9‐based library screenings are performed based on these genes to confirm their biological contribution to drug resistance. A 15‐gene classifier is developed by generalized linear regression analysis combined with the logistic regression model. In an independent validation cohort of 102 patients, the classifier showed good predictive ability with an area under the curve of 0.80 (95% confidence interval (CI), 0.69–0.91). Furthermore, the 15‐gene classifier is significantly associated with patient responsiveness to NACT in both univariate (odds ratio, 10.8; 95% CI, 3.55–32.86; p = 2.8 × 10⁻⁵) and multivariate analysis (odds ratio, 17.34; 95% CI, 4.04–74.40; p = 1.23 × 10⁻⁴) in the validation set. In conclusion, the 15‐gene classifier can accurately predict the clinical response to NACT before treatment, representing a promising approach for guiding the selection of appropriate treatment strategies for locally advanced cervical cancer.

Clinical trials have shown that immunotherapy based on Vγ9Vδ2 T cells (Vδ2 T cells) is safe and well-tolerated for various cancers including cervical cancer (CC), but its overall treatment efficacy remains limited. Therefore, exploring the mechanisms underlying the suboptimal efficacy of Vδ2 T cell-based cancer immunotherapy is crucial for enabling its successful clinical translation. Tumor samples from CC patients and CC cell line-derived xenograft (CDX) mice were analyzed using flow cytometry to examine the exhausted phenotype of tumor-infiltrating Vδ2 T cells. The interrelationship between BTN3A1 expression and Vδ2 T cells in CC, along with their correlation with patient prognosis, was analyzed using data from The Cancer Genome Atlas (TCGA) database. CC cell lines with BTN3A1 knockout (KO) and overexpression (OE) were constructed through lentivirus transduction, which were then co-cultured with expanded Vδ2 T cells, followed by detecting the function of Vδ2 T cells using flow cytometry. The pathways and transcription factors (TFs) related to BTN3A1-induced Vδ2 T cells exhaustion and the factors affecting BTN3A1 expression were identified by RNA-seq analysis, which was confirmed by flow cytometry, Western Blot, and gene manipulation. Tumor-infiltrating Vδ2 T cells exhibited an exhausted phenotype in both CC patients and CDX mice. BTN3A1 expressed in CC is highly enhancing exhaustion markers, while reducing the secretion of effector molecules in Vδ2 T cells. Blocking TCR or knocking down nuclear receptor subfamily 4 group A (NR4A) 2/3 can reverse BTN3A1-induced exhaustion in Vδ2 T cells. On the other hand, IFN-γ secreted by Vδ2 T cells promoted the expression of BTN3A1 and PD-L1. Through binding γδ TCRs, BTN3A1 expressed on tumor cells, which is induced by IFN-γ, can promote Vδ2 T cells to upregulate the expression of TFs NR4A2/3, thereby affecting their activation and expression of exhaustion-related molecules in the tumor microenvironment (TME). Therefore, targeting BTN3A1 might overcome the immunosuppressive effect of the TME on Vδ2 T cells in CC.