ABSTRACT
Prognostically relevant RNA expression states exist in pancreatic ductal adenocarcinoma (PDAC), but our understanding of their drivers, stability, and relationship to therapeutic response is limited. To examine these attributes systematically, we profiled metastatic biopsies and matched organoid models at single-cell resolution. In vivo, we identify a new intermediate PDAC transcriptional cell state and uncover distinct site- and state-specific tumor microenvironments (TMEs). Benchmarking models against this reference map, we reveal strong culture-specific biases in cancer cell transcriptional state representation driven by altered TME signals. We restore expression state heterogeneity by adding back in vivo-relevant factors and show plasticity in culture models. Further, we prove that non-genetic modulation of cell state can strongly influence drug responses, uncovering state-specific vulnerabilities. This work provides a broadly applicable framework for aligning cell states across in vivo and ex vivo settings, identifying drivers of transcriptional plasticity and manipulating cell state to target associated vulnerabilities.
Subject(s)
Biomarkers, Tumor/metabolism , Carcinoma, Pancreatic Ductal/metabolism , Pancreatic Neoplasms/metabolism , Tumor Microenvironment , Adult , Aged , Cell Line, Tumor , Female , Gene Expression Regulation, Neoplastic , Humans , Male , Middle Aged , Single-Cell AnalysisABSTRACT
The fatty acid methyl ester (FAME) content of biodiesel fuels has traditionally been determined using gas chromatography with a polar stationary phase. In this study, a direct comparison of the separation of FAMEs present in various biodiesel samples on three polar stationary phases and one moderately polar stationary phase (with comparable column dimensions) was performed. Retention on each column was based on solubility in and polarity of the phase. Quantitative metrics describing the resolution of important FAME pairs indicate high resolution on all polar columns, yet the best resolution, particularly of geometric isomers, is achieved on the cyanopropyl column. In addition, the separation of four C18 monounsaturated isomers was optimized and the elution order determined on each column. FAME composition of various biodiesel fuel types was determined on each column to illustrate (1) chemical differences in biodiesels produced from different feedstocks and (2) chemical similarities in biodiesels of the same feedstock type produced in different locations and harvest seasons.
