RESUMO
Despite the effectiveness of antiretroviral therapy (ART) in prolonging the lifespan of individuals infected with HIV-1, it does not offer a cure for acquired immunodeficiency syndrome (AIDS). The "block and lock" approach aims to maintain the provirus in a state of extended transcriptional arrest. By employing the "block and lock" strategy, researchers endeavor to impede disease progression by preventing viral rebound for an extended duration following patient stops receiving ART. The crux of this strategy lies in the utilization of latency-promoting agents (LPAs) that are suitable for impeding HIV-1 provirus transcription. However, previously documented LPAs exhibited limited efficacy in primary cells or samples obtained from patients, underscoring the significance of identifying novel LPAs that yield substantial outcomes. In this study, we performed high-throughput screening of FDA-approved compound library in the J-Lat A2 cell line to discover more efficacious LPAs. We discovered ripretinib being an LPA candidate, which was validated and observed to hinder proviral activation in cell models harboring latent infections, as well as CD4+ T cells derived from infected patients. We demonstrated that ripretinib effectively impeded proviral activation through inhibition of the PI3K-AKT-mTOR signaling pathway in the HIV-1 latent cells, thereby suppressing the opening states of cellular chromatin. The results of this research offer a promising drug candidate for the implementation of the "block and lock" strategy in the pursuit of an HIV-1 cure.
RESUMO
BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) remains one of the most intractable malignancies. The development of effective drug treatments for ICC is seriously hampered by the lack of reliable tumor models. At present, patient derived xenograft (PDX) models prove to accurately reflect the genetic and biological diversity required to decipher tumor biology and therapeutic vulnerabilities. This study was designed to investigate the establishment and potential application of PDX models for guiding personalized medicine and identifying potential biomarker for lenvatinib resistance. METHODS: We generated PDX models from 89 patients with ICC and compared the morphological and molecular similarities of parental tumors and passaged PDXs. The clinicopathologic features affecting PDX engraftment and the prognostic significance of PDX engraftment were analyzed. Drug treatment responses were analyzed in IMF-138, IMF-114 PDX models and corresponding patients. Finally, lenvatinib treatment response was examined in PDX models and potential drug resistance mechanism was revealed. RESULTS: Forty-nine PDX models were established (take rate: 55.1%). Successful PDX engraftment was associated with negative HbsAg (P = 0.031), presence of mVI (P = 0.001), poorer tumor differentiation (P = 0.023), multiple tumor number (P = 0.003), presence of lymph node metastasis (P = 0.001), and later TNM stage (P = 0.039). Moreover, patients with tumor engraftment had significantly shorter time to recurrence (TTR) (P < 0.001) and worse overall survival (OS) (P < 0.001). Multivariate analysis indicated that PDX engraftment was an independent risk factor for shortened TTR (HR = 1.84; 95% CI, 1.05-3.23; P = 0.034) and OS (HR = 2.13; 95% CI, 1.11-4.11; P = 0.024). PDXs were histologically and genetically similar to their parental tumors. We also applied IMF-138 and IMF-114 PDX drug testing results to guide clinical treatment for patients with ICC and found similar treatment responses. PDX models also facilitated personalized medicine for patients with ICC based on drug screening results using whole exome sequencing data. Additionally, PDX models reflected the heterogeneous sensitivity to lenvatinib treatment and CDH1 might be vital to lenvatinib-resistance. CONCLUSION: PDX models provide a powerful platform for preclinical drug discovery, and potentially facilitate the implementation of personalized medicine and improvement of survival of ICC cancer patient.
RESUMO
Circulating tumor cell (CTC) analysis holds great potential to be a noninvasive solution for clinical cancer management. A complete workflow that combined CTC detection and single-cell molecular analysis is required. We developed the ChimeraX® -i120 platform to facilitate negative enrichment, immunofluorescent labeling, and machine learning-based identification of CTCs. Analytical performances were evaluated, and a total of 477 participants were enrolled to validate the clinical feasibility of ChimeraX® -i120 CTC detection. We analyzed copy number alteration profiles of isolated single cells. The ChimeraX® -i120 platform had high sensitivity, accuracy, and reproducibility for CTC detection. In clinical samples, an average value of > 60% CTC-positive rate was found for five cancer types (i.e., liver, biliary duct, breast, colorectal, and lung), while CTCs were rarely identified in blood from healthy donors. In hepatocellular carcinoma patients treated with curative resection, CTC status was significantly associated with tumor characteristics, prognosis, and treatment response (all P < 0.05). Single-cell sequencing analysis revealed that heterogeneous genomic alteration patterns resided in different cells, patients, and cancers. Our results suggest that the use of this ChimeraX® -i120 platform and the integrated workflow has validity as a tool for CTC detection and downstream genomic profiling in the clinical setting.
