Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers with almost no curative chemotherapeutic treatment. Besides the development of new compounds, repurposing of approved drugs to treat cancer, alone or in combination, has become an attractive strategy, showing many therapeutic and economic advantages. However, it is necessary to improve our knowledge about the mechanism of cell death elicited by approved drugs itself, but also to rationally develop more powerful multidrug treatments. In this work, we focus our attention on determining the mechanism promoting cell death following trifluoperazine (TFP) treatment, which is an antipsychotic drug with strong anticancer activity in PDAC. We demonstrate that TFP induces cell death by apoptosis and necroptosis, which can be partially inhibited by Z-VAD-FMK as well as necrostatin-1, respectively. This cell death promotion is triggered by a poor ATP content, observed in TFP-treated cells as a consequence of a dramatic decrease in OXPHOS metabolism due to mitochondrial stress. Remarkably, mitochondrial homeostasis was seriously affected, and a loss of mitochondrial membrane potential and ROS overproduction was observed. Moreover, this mitochondrial stress was coupled with an ER stress and the activation of the endoplasmic-reticulum-associated protein degradation (ERAD) and the unf olded protein response (UPR) pathways. We took advantage of this information and inhibited this process by using the proteasome inhibitors MG-132 or bortezomib compounds in combination with TFP and found a significant improvement of the anticancer effect of the TFP on primary PDAC-derived cells. In conclusion, this study not only uncovers the molecular mechanisms that are triggered upon TFP-treatment but also its possible combination with bortezomib for the future development of therapies for pancreatic cancer.

Purpose: Compare pancreatic ductal adenocarcinoma (PDAC), preclinical models, by their transcriptome and drug response landscapes to evaluate their complementarity. Experimental Design: Three paired PDAC preclinical models—patient-derived xenografts (PDX), xenograft-derived pancreatic organoids (XDPO) and xenograft-derived primary cell cultures (XDPCC)—were derived from 20 patients and analyzed at the transcriptomic and chemosensitivity level. Transcriptomic characterization was performed using the basal-like/classical subtyping and the PDAC molecular gradient (PAMG). Chemosensitivity for gemcitabine, irinotecan, 5-fluorouracil and oxaliplatin was established and the associated biological pathways were determined using independent component analysis (ICA) on the transcriptome of each model. The selection criteria used to identify the different components was the chemosensitivity score (CSS) found for each drug in each model. Results: PDX was the most dispersed model whereas XDPO and XDPCC were mainly classical and basal-like, respectively. Chemosensitivity scoring determines that PDX and XDPO display a positive correlation for three out of four drugs tested, whereas PDX and XDPCC did not correlate. No match was observed for each tumor chemosensitivity in the different models. Finally, pathway analysis shows a significant association between PDX and XDPO for the chemosensitivity-associated pathways and PDX and XDPCC for the chemoresistance-associated pathways. Conclusions: Each PDAC preclinical model possesses a unique basal-like/classical transcriptomic phenotype that strongly influences their global chemosensitivity. Each preclinical model is imperfect but complementary, suggesting that a more representative approach of the clinical reality could be obtained by combining them. Translational Relevance: The identification of molecular signatures that underpin drug sensitivity to chemotherapy in PDAC remains clinically challenging. Importantly, the vast majority of studies using preclinical in vivo and in vitro models fail when transferred to patients in a clinical setting despite initially promising results. This study presents for the first time a comparison between three preclinical models directly derived from the same patients. We show that their applicability to preclinical studies should be considered with a complementary focus, avoiding tumor-based direct extrapolations, which might generate misleading conclusions and consequently the overlook of clinically relevant features.

Pancreatic cancer is one of the most lethal malignancies with a poor and gloomy prognosis and the highest mortality-to-incidence ratio. Pancreatic cancer remains an incurable malignancy, and current therapies are ineffective. We isolated cancer stem cells (CSCs) from the human PANC-1 pancreatic cancer cell line as CD44⁺CD24⁺EpCAM⁺ cells. These CSCs form pancreatic cancer spheres or spheroids and develop tumors in SCID mice after subcutaneous injection of as few as 100 cells per mouse. Here, we found that the alkylphospholipid analog edelfosine inhibited CSC pancreatic cancer spheroid formation and induced cell death, as assessed by an increase in the percentage of cells in the sub-G₀/G₁ region by means of flow cytometry, indicative of DNA breakdown and apoptosis. This correlated with an increase in caspase-3 activity and PARP breakdown, as a major substrate of caspase-3, following PANC-1 CSC treatment with edelfosine. The antitumor ether lipid edelfosine colocalized with the endoplasmic reticulum in both PANC-1 cells as well as PANC-1 CSCs by using a fluorescent edelfosine analog, and induced an endoplasmic reticulum stress response in both PANC-1 cells and PANC-1 CSCs, with a potent CHOP/GADD153 upregulation. Edelfosine elicited a strong autophagy response in both PANC-1 cells and PANC-1 CSCs, and preincubation of CSCs with autophagy inhibitors, chloroquine or bafilomycin A1, enhanced edelfosine-induced apoptosis. Primary cultures from pancreatic cancer patients were sensitive to edelfosine, as well as their respective isolated CSCs. Nontumorigenic pancreatic human cell line HPNE and normal human fibroblasts were largely spared. These data suggest that pancreatic CSCs isolated from established cell lines and pancreatic cancer patients are sensitive to edelfosine through its accumulation in the endoplasmic reticulum and induction of endoplasmic reticulum stress.

Emerging evidence suggests that chemotherapy can accumulate senescent-like cells within tumor tissues, a phenomenon linked to therapy resistance. The aim of this study is to analyze the senescence-like state of after-treatment persistent cells associated with KRAS mutational status to offer a therapeutic strategy to target these cells in pancreatic ductal adenocarcinoma (PDAC). Three commercial cell lines and five patient-derived primary cell cultures with different KRAS statuses were studied following gemcitabine treatment. Senescence-like status was assessed using SA-β-gal, together with cell cycle regulators such as p21. Additionally, KRAS mutations were modulated using MRTX1133 and AMG-510, and the signaling pathways ERK and AKT were analyzed and modulated in vitro. Finally, p21 expression, associated with the senescence-like state, on patient outcomes and treatment response was analyzed in publicly available bulk RNA-seq and single-nucleus datasets. We observed an overexpression of p21 alongside an increase in SA-β-gal signal in response to gemcitabine treatment, indicating the induction of a senescence-like state. Specific inhibition of KRAS G12D or G12C mutations reduced SA-β-gal signal and sensitized PDAC cells to gemcitabine. Moreover, ERK inhibition but not AKT inhibition decreased SA-β-gal signal. Additionally, we characterized p21 expression levels in relation to patient outcomes and found that they are modulated by treatment. This dual-targeted therapeutic strategy holds promises for overcoming the challenges posed by KRAS-driven cancers, particularly in addressing the formidable obstacle of pancreatic cancer.

Single-cell RNA sequencing is a powerful approach for characterising cellular heterogeneity and elucidating transcriptional programs that drive tumour plasticity, therapeutic resistance, and disease progression. In this study, we present a single-cell transcriptomic dataset comprising 41 patient-derived cell cultures (PDCs) established from pancreatic ductal adenocarcinoma (PDAC). The dataset was generated using Evercode™ technology, which is based on Split Pool Ligation-based Transcriptome sequencing (SPLiT-seq). This scalable method enables high-throughput profiling across multiple samples without droplet-based microfluidics, allowing efficient capture of inter-sample heterogeneity. This functionally annotated collection of experimentally derived models reveals transcriptional heterogeneity both within and across PDCs, enabling in-depth exploration of PDAC cell diversity, to support the development of computational tools for single-cell analysis, and to guide functional studies on tumour cell subpopulations. This resource constitutes a valuable reference for computational and experimental studies aiming to decipher PDAC heterogeneity and identify therapeutic vulnerabilities.