Jing Tang

Inhibiting the growth of ovarian cancer cells in vitro and in vivo by a small molecular inhibitor targeting La-RNA interactions

To identify small molecules blocking La-RNA interactions by using structural dynamics, molecular biology, and in vivo efficacy experiments. A docking virtual assay on the Chemdiv database was used to screen La binders, and their affinity were measured by surface plasmon resonance (SPR). A novel fluorescence polarization (FP) assay referring to the binding of La protein and 3'UUUOH was established to identify the inhibitors. Their activity on ovarian cancer cell proliferation, apoptosis and cell cycle were evaluated using Cell Counting Kit 8 (CCK8) and flow cytometry assay, respectively. Their in vivo efficacy against ovarian cancer growth were evaluated in a cell line-derived xenograft (CDX) model of A2780 cells. From a total of 20 compounds with high potential binding activity with La protein, two small molecule compounds 4424-1120 and 8017-5932 with relatively stronger inhibition ability on La-RNA interactions were identified. These two compounds shared the same active centers with hydroxyimidazole and hydroxybenzene to interact with La protein through residues ARG57, GLN20 and GLN136. The in vitro assays showed that 4424-1120 and 8017-5932 effectively cause G0/G1 cell cycle arrest, inhibit cell proliferation, reduce cell invasion and promote apoptosis in ovarian cancer cells. In a CDX model on BALB/C Nude mice, we found that the growth rate of the tumor was inhibited by 4424-1120. Our results demonstrated compound 4424-1120 shows good antitumor activity and safety in vitro and in vivo, and it provides a new idea for the discovery of antitumor lead compounds from small drug-like molecules.

Drug target proteome profiling identifies HES1-driven mitotic catastrophe in ovarian serous carcinoma.

Ovarian high-grade serous cancer (HGSC) is the most aggressive ovarian cancer subtype with limited treatment options. We identify the PDPK1 inhibitor BX-912 as a promising candidate, showing strong single-agent activity and synergy with the PARP inhibitor olaparib, independent of BRCA status. Unexpectedly, BX-912 induces multinucleation, a phenotype not seen with other PDPK1 inhibitors. Proteome Integral Solubility Alteration (PISA) assay reveals HES1 as a functional off-target, while structural modeling suggested BX-912 acts as a protein-protein interaction modulator, driving nuclear accumulation of HES1 complexes and hence inducing mitotic catastrophe. Cell-cycle analyses confirm enhanced DNA damage response and G2/M arrest when combined with olaparib. These findings uncover a novel mechanism for BX-912, establish HES1 inhibition as a therapeutic strategy in HGSC, demonstrate proteomics' power to reveal hidden drug activities, and propose sequential cell-cycle targeting to improve treatment efficacy.

Tracing back primed resistance in cancer via sister cells

Abstract Exploring non-genetic evolution of cell states during cancer treatments has become attainable by recent advances in lineage-tracing methods. However, transcriptional changes that drive cells into resistant fates may be subtle, necessitating high resolution analysis. Here, we present ReSisTrace that uses shared transcriptomic features of sister cells to predict the states priming treatment resistance. Applying ReSisTrace in ovarian cancer cells perturbed with olaparib, carboplatin or natural killer (NK) cells reveals pre-resistant phenotypes defined by proteostatic and mRNA surveillance features, reflecting traits enriched in the upcoming subclonal selection. Furthermore, we show that DNA repair deficiency renders cells susceptible to both DNA damaging agents and NK killing in a context-dependent manner. Finally, we leverage the obtained pre-resistance profiles to predict and validate small molecules driving cells to sensitive states prior to treatment. In summary, ReSisTrace resolves pre-existing transcriptional features of treatment vulnerability, facilitating both molecular patient stratification and discovery of synergistic pre-sensitizing therapies.

Ex Vivo Immuno-Oncology Platform Reveals Spatial T-cell Infiltration Patterns Linked to ATR Inhibition Responses in High-Grade Serous Ovarian Cancer

Abstract Identifying new therapeutic approaches in high-grade serous ovarian cancer (HGSC) requires the development of more accurate preclinical models that replicate the patient-specific tumor and its microenvironment. To address this, we established immunocompetent patient-derived cultures (iPDC) for HGSC, cultured on a physiologically relevant human omentum gel matrix. We developed a high-throughput platform that combines drug testing, histologic analysis, genomic profiling, single-cell studies, and spatial biomarker discovery. Our results from 47 tumors showed that iPDCs recapitulated the tumor genomic and histologic characteristics while also retaining the intratumoral immune cells. The iPDC treatment responses correlated significantly with the patients’ clinical treatment responses. Using iPDCs and single-cell RNA sequencing, we identified potentially effective therapeutic options for patients with recurrent HGSC linked to distinct tumor cell states and mechanisms of resistance. High-throughput drug response profiling with single-cell imaging identified ataxia telangiectasia and Rad3-related inhibitor (ATRi) combined with an immunotherapy targeting autotaxin as a promising new combination treatment for HGSC. Using hyperplexed imaging and spatial analysis, we discovered that ATRi responses were associated with significant increases in both intra- and peritumoral T-cell infiltration, particularly in PD-1+ CD8+ T cells. Additionally, the ATRi-induced reactivation of CD8+ T cells was linked to spatial interactions with replication stress–positive tumor cells. Thus, our iPDC platform presents a representative high-throughput ex vivo model to advance precision oncology in HGSC, uncovering the ATRi-immunotherapy combination as a potentially effective therapeutic option for clinical translation.