Abstract A026: Combination of carboplatin and the PP2A inhibitor LB100 as novel therapeutic strategy in pre-clinical SCLC model using quantitative super resolution imaging analysis for PP2A and STAT3

Abstract Small cell lung cancer (SCLC) is a devastating malignancy with limited treatment options, mainly consisting of chemotherapy and/or immunotherapy. We identified the combination of carboplatin (carbo) standard therapy with the protein phosphatase 2A (PP2A) inhibitor LB100 as a potential new therapeutic approach in SCLC. Primary SCLC cells are difficult to obtain, and we therefore sought to define its on-target in vivo efficacy using a pre-clinical H146 murine xenograft model (athymic nu/nu mice). Tumor-bearing mice were treated with carbo (50 mg/kg) and LB100 (0.25 mg/kg) for 40 days, after which tumors were excised and weighed. Tumors were significantly smaller following combination treatment compared to control or monotherapy (control:1.68±0.18g vs. treated: carbo–0.54± 0.1g, LB100–0.77±0.1g, carbo/LB100–0.18±0.04g, (monotherapy vs. combination: p< 0.01-0.001)). Next, we used tumor FFPE tissue slides to evaluate the levels of PP2A (PP2A A subunit) and pSTAT3 (phospho-Ser727 STAT3), a PP2A substrate and a key regulator of tumor immune dysfunction and growth. Slides were analyzed using Zeiss Elyra super-resolution (SR) microscopy and rapid, unbiased quantification and object colocalization. The tumor proliferation marker Ki67 was significantly higher in the control samples as compared to drug treated samples. SR imaging revealed the presence of pSTAT3 and PP2A spots in nuclei. Quantification was performed using Zeiss Zen Blue and Imaris (version10.2.0) software: (a) Machine learning segmentation of 3D nucleus surfaces was used to determine the nuclear volume. Object-object statistics were used for the filtering of spots. DAPI imaging of nuclear DNA was selected and set to a surface detail of 0.23 µm and was iterated across image sets to create four different parameters. (b) Segmentation was manually adjusted to separate objects. Spots were then created for PP2A A and pSTAT3 using the spot function and object-object statistics turned on. Spot detection included background subtraction, selecting spots that are only localized within the nuclei. (c) Colocalization was determined by filtering the PP2A spots. Spots were selected by the filter tab to find shortest distance to pSTAT3 spots. The filter threshold remained constant for each image to allow for consistent counting of colocalized spots. Combination treatment with carbo/LB100 significantly increased colocalization of PP2A A with pSTAT3 (control: 0.316±0.063 vs. carbo/LB100: 0.757±0.115 spots/nucleus, p < 0.05) and reduced nuclear presence of both pSTAT3 and PP2A A. These findings support the use of SR microscopy for rapid, unbiased quantification and object colocalization of therapeutic targets and effectors in combination with preclinical in vivo models. SR imaging and Imaris analysis of FFPE slides from murine xenograft model may advance and simplify the detection of novel therapeutic targets and drug combinations in clinical studies. Funding: DoD grant HT9425-23-1-0581. Citation Format: Tamara Mirzapoiazova, Nathan Evans, Bolot Mambetsariev, Siddhika Pareek, Isa Mambetsariev, Brian Armstrong, Sharad Singhal, Ravi Salgia. Combination of carboplatin and the PP2A inhibitor LB100 as novel therapeutic strategy in pre-clinical SCLC model using quantitative super resolution imaging analysis for PP2A and STAT3 [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Functional and Genomic Precision Medicine in Cancer: Different Perspectives, Common Goals; 2025 Mar 11-13; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(5 Suppl):Abstract nr A026.