R-17934

Pancreatic ductal adenocarcinoma (PDAC) is highly aggressive, with limited success in traditional therapies due to the fibrotic, immunosuppressive, pro-metastatic tumor microenvironment (TME), which collectively impede the drug accumulation and accelerate the tumor progression. In this work, we developed a PDAC-customized nutrient-mimicking reconstituted high-density lipoprotein (rHDL) capable of efficiently co-encapsulate versatile TME regulating cannabidiol and cytotoxic gemcitabine to simultaneously reprogram TME while suppressing PDAC progression. Specifically, a small-sized, nutrient-like rHDL was constructed to realize deep PDAC parenchyma penetration and efficient intra-tumoral uptake. Next, natural herbal compound cannabidiol was screened and incorporated into rHDL to regulate TME via attenuating fibrosis, reliving immunosuppression and mitigating metastatic tendency. At last, gemcitabine, the PDAC gold standard first-line therapy was co-delivered by the PDAC-customized rHDL to overcome drug resistance and amplify its PDAC suppression. Our findings demonstrate the feasibility of an integrated multi-stage TME regulation strategy for improved PDAC therapy, and might represent a modality in promoting chemotherapy against PDAC.

Fluorescence lifetime imaging microscopy (FLIM) is an advanced microscopy technique capable of providing a deeper understanding of the molecular environment of a fluorophore. While FLIM data were traditionally analyzed through the exponential fitting of the fluorophores' emission decays, the use of phasor plots is increasingly becoming the preferred standard. This is due to their ability to visualize the distribution of fluorescent lifetimes within a sample, offering insights into molecular interactions in the sample without the need for modeling assumptions regarding the exponential decay behavior of the fluorophores. However, so far, most researchers have had to rely on commercial phasor plot software packages which are closed-source and only work with proprietary data formats. In this paper, we introduce FLIMPA, an accessible, open-source, stand-alone software for phasor plot analysis that provides many of the features found in commercial software, and more. FLIMPA is fully developed in Python and offers advanced tools for data analysis and visualization. It enhances FLIM data comparison by integrating phasor points from multiple trials and experimental conditions into a single plot, while also providing the possibility to explore detailed, localized insights within individual samples interactively. We apply FLIMPA to introduce a novel cell-based assay for the quantification of microtubule depolymerization, measured through fluorescence lifetime changes of SiR-tubulin, in response to various concentrations of Nocodazole, a microtubule depolymerizing drug relevant to anticancer treatment.