Fang Li

LIG1 Is a Synthetic Lethal Target in BRCA1 Mutant Cancers

Abstract Synthetic lethality approaches in BRCA1/2-mutated cancers have focused on PARP inhibitors, which are subject to high rates of innate or acquired resistance in patients. In this study, we used CRISPR/Cas9-based screening to identify DNA ligase I (LIG1) as a novel target for synthetic lethality in BRCA1-mutated cancers. Publicly available data supported LIG1 hyperdependence of BRCA1 mutant cells across a variety of breast and ovarian cancer cell lines. We used CRISPRn, CRISPRi, RNAi, and protein degradation to confirm the lethal effect of LIG1 inactivation at the DNA, RNA, and protein level in BRCA1 mutant cells in vitro. LIG1 inactivation resulted in viability loss across multiple BRCA1-mutated cell lines, whereas no effect was observed in BRCA1/2 wild-type cell lines, demonstrating target selectivity for the BRCA1 mutant context. On-target nature of the phenotype was demonstrated through rescue of viability with exogenous wild-type LIG1 cDNA. Next, we demonstrated a concentration-dependent relationship of LIG1 protein expression and BRCA1 mutant cell viability using a titratable, degradable LIG1 fusion protein. BRCA1 mutant viability required LIG1 catalytic activity, as catalytically dead mutant LIG1K568A failed to rescue viability loss caused by endogenous LIG1 depletion. LIG1 perturbation produced proportional increases in PAR staining in BRCA1 mutant cells, indicating a mechanism consistent with the function of LIG1 in sealing ssDNA nicks. Finally, we confirmed LIG1 hyperdependence in vivo using a xenograft model in which LIG1 loss resulted in tumor stasis in all mice. Our cumulative findings demonstrate that LIG1 is a promising synthetic lethal target for development in patients with BRCA1-mutant cancers.

Oligoclonal tumor-specific CD8 T-cell revival and IRE1α/XBP1-GDF15-mediated immunosuppressive niches determine neoadjuvant chemoimmunotherapy efficacy in cervical cancer

Background Neoadjuvant chemoimmunotherapy (NACI) shows promise for locally advanced cervical cancer (LACC), but drug-tolerant persister (DTP) cells and immunosuppressive microenvironmental adaptations limit clinical efficacy. The underlying determinants governing heterogeneous responses to NACI regimens remain poorly understood, particularly regarding how dynamic tumor-immune interactions shape therapeutic outcomes. Methods We characterized microenvironmental dynamics in patients with LACC by integrating single-cell RNA sequencing (RNA-seq), single-cell VDJ sequencing (n=10, five paired pre-NACI/post-NACI samples) and spatial transcriptomics (ChiCTR2300072535). Pathological response was assessed using major pathological response criteria. The findings were validated in an independent NACI cohort (n=23 with RNA-seq), multiplex immunohistochemistry (mIHC) analysis of six surgically resected specimens, as well as functional in vitro and murine models. Results MPR patients exhibited cytotoxic revival via oligoclonal expansion of tumor-reactive CD8+T cell clones and CCR5-mediated myeloid-T cell crosstalk. Conversely, non-MPR tumors exhibited endoplasmic reticulum (ER) stress-adapted DTP cells with elevated ER stress signaling, accompanied by a deficiency in tumor-specific T-cell clone expansion and an accumulation of transforming growth factor beta receptor 2 (TGFBR2) + myeloid DTP niches. Mechanistically, ER stress signaling via the inositol‑requiring enzyme 1 alpha (IRE1α) / X‑box binding protein 1 (XBP1) axis induces growth differentiation factor 15 (GDF15) production in DTP cells, contributing to treatment‑resistant microdomains. Pharmacological IRE1α inhibition synergized with chemoimmunotherapy to eradicate DTP populations in murine models. Conclusions This study provides critical insights that NACI resistance stems from adaptive ER stress signaling in DTP cells and spatially organized immunosuppressive networks. Targeting the IRE1α/XBP1-GDF15 axis represents an actionable strategy to reprogram microenvironmental ecology and improve immunotherapy outcomes.

Evaluation of the accuracy of colposcopy in detecting high-grade squamous intraepithelial lesion and cervical cancer

The primary aim of this study was to evaluate the diagnostic accuracy of colposcopy in identifying high-grade squamous intraepithelial lesion or worse (HSIL+) and the characteristic performance of colposcopic images with various severity levels of cervical lesions. The medical records from 1828 women who underwent colposcopy at Affiliated Hospital of Tongji University from February 2016 to March 2019 were reviewed. Human papilloma virus (HPV) GenoArray test kit (HybriBio Ltd) and Thinprep cytologic test (TCT, Hologic, USA) were used to perform HPV genotyping and cytology. All colposcopic images were collected from the standard-of-care colposcope (Leisegang 3ML LED) and evaluated based on the 2011 International Federation of Cervical Pathology and Colposcopy (IFCPC) Colposcopy Standards. The linear by linear association, Pearson χ The consistency between colposcopy and biopsy pathology was 59.35% with the moderate strength of kappa coefficient of 0.464. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of colposcopy and cytology for HSIL+ were 56.29%, 93.82%, 77.47%, 85.04% and 37.13%, 98.49%, 90.29%, 80.58%, respectively. The colposcopic features of HSIL+ were as follows: (1) thick or bulgy acetowhite epithelium with sharp border; (2) completely nonstained of Lugol's iodine; (3) type III/IV/V of gland openings; (4) punctation or atypical vessels. The data and findings herein provide the resource for evaluating the diagnostic value of colposcopy, and suggested that the accuracy of colposcopy is required to be further improved.

Genetic variability and functional implication of HPV16 from cervical intraepithelial neoplasia in Shanghai women

AbstractHuman papillomavirus (HPV)16 gene mutation is usually associated with persistent HPV infection and cervical intraepithelial neoplasia (CIN). However, the functional implications of HPV16 mutations remain poorly understood.145 LCR/E6/E7 of the HPV16 isolates were amplified and sequenced, and HPV16 integration status was detected. In total, 89 SNPs (68 in the LCR, 13 in E6, 8 in E7) were discovered, 11 of which were nonsynonymous mutations (8 in E6, 3 in E7). The H85Y and E120D variants in E6 were significantly reduced in the high‐grade squamous intraepithelial lesion (HSIL) group compared to the <HSIL group (P = .046 and .005), conversely the N29S in E7(P = .01). Amino acid substitutions (D32N/E, E36Q, H85Y, and E120D in E6 and N29H/S and R77C in E7) were predicted to have an effect on conserved structural and functional residues, and five amino acid substitutions (H85Y, E36Q, I34L, and D32E in E6; R77C in E7) would potentially change the secondary structure. “6329G>T,” a potential binding site for TATA‐binding protein, is the most common in LCR variants. A4 (Asian) was associated with an increased risk of HSIL compared to A1–3(P = .009). The H85/E120 in E6 and N29 in HPV16 E7 might play a critical role in carcinogenesis by disrupting p53 and Rb degradation due to affecting their interaction, respectively. In a word, the findings in this study provide preventative and therapeutic interventions of HPV16 ‐related cervical lesions/cancer.

Deep learning based cervical screening by the cross-modal integration of colposcopy, cytology, and HPV test

To develop and evaluate the colposcopy based deep learning model using all kinds of cervical images for cervical screening, and investigate the synergetic benefits of the colposcopy, the cytology test, and the HPV test for improving cervical screening performance. This study consisted of 2160 women who underwent cervical screening, there were 442 cases with the histopathological confirmed high-grade squamous intraepithelial lesion (HSIL) or cancer, and the remained 1718 women were controls. Three kinds of cervical images were acquired from colposcopy including the saline image of cervix after saline irrigation, the acetic acid image of cervix after applying acetic acid solution, and the iodine image of cervix after applying Lugol's iodine solution. Each kind of image was used to build a single-image based deep learning model by the VGG-16 convolutional neural network, respectively. A multiple-images based deep learning model was built using multivariable logistic regression (MLR) by combining the single-image based models. The performance of the visual inspection was also obtained. The results of the cytology test and HPV test were used to build a Cytology-HPV joint diagnostic model by MLR. Finally, a cross-modal integrated model was built using MLR by combining the multiple-images based deep learning model, the cytology test results, and the HPV test results. The performances of models were tested in an independent test set using the area under the receiver operating characteristic curve (AUC). The saline image, acetic acid image, and iodine image based deep learning models had AUC of 0.760, 0.791, and 0.840. The multiple-images based deep learning model achieved an improved AUC of 0.845. The AUC of the visual inspection was 0.751. The Cytology-HPV joint diagnostic model had an AUC of 0.837, which was higher than the cytology test (AUC = 0.749) and the HPV test (AUC = 0.742). The cross-modal integrated model achieved the best performance with AUC of 0.921. Combining all kinds of cervical images were benefit for improving the performance of the colposcopy based deep learning model, and more accurate cervical screening could be achieved by incorporating the colposcopy based deep learning model, the cytology test results, and the HPV test results.

Long-read sequencing reveals oncogenic mechanism of HPV-human fusion transcripts in cervical cancer

Integration of high-risk human papillomavirus (HPV) into the host genome is a crucial event for the development of cervical cancer, however, the underlying mechanism of HPV integration-driven carcinogenesis remains unknown. Here, we performed long-read RNA sequencing on 12 high-grade squamous intraepithelial lesions (HSIL) and cervical cancer patients, including 3 pairs of cervical cancer and corresponding para-cancerous tissue samples to investigate the full-length landscape of cross-species genome integrations. In addition to massive unannotated isoforms, transcriptional regulatory events, and gene chimerism, more importantly, we found that HPV-human fusion events were prevalent in HPV-associated cervical cancers. Combined with the genome data, we revealed the existence of a universal transcription pattern in these fusion events, whereby structurally similar fusion transcripts were generated by specific splicing in E6 and a canonical splicing donor site in E1 linking to various human splicing acceptors. Highly expressed HPV-human fusion transcripts, eg, HPV16 E6*I-E7-E1