tbuckley/cabot-search huggingface dataset:
Abstract A021: <i>In silico</i> Prediction of Proteins Interacting with a Basal-like Pancreatic Cancer marker, RhoV, Using AlphaFold
Authors: Zebang Mark Li, Xiaoxu Zhou, Shaolei Lu
Journal: Cancer Research (2024)

Abstract Introduction Basal-like pancreatic cancer is a subtype with a worse clinical outcome than other subtypes. Ras homolog family member V (RhoV) is one of the basal-like markers that was recently identified. RhoV is a Rho GTPase and is closely regulated by guanine exchange factors (GEFs) and GTPase activating proteins (GAPs). An in silico prediction was performed using AlphaFold to identify RhoV regulators. Methods Amino acid sequences of 120 known GEFs and GAPs were collected. AlphaFold Colab, which uses AlphaFold2 and AlphaFold2-multier, was initially used to screen GEFs and GAPs for their binding affinities to RhoV. The top hits from AlphaFold2 were further verified by AlphaFold3, the most current version of AlphaFold partially open to nonprofit users. RAC1, a well-studied Rho GTPase with known GEFs and GAPs, was used as a control for the prediction process. Results AlphaFold predicted strong interactions of RAC1 and RhoV with GTP and GDP (ipTM of 0.92 between RAC1 and GTP; 0.95 between RAC1 and GDP; 0.92 between GTP and RhoV; 0.95 between GDP and RhoV). Known RAC1 binding partners, ARHGEF5 and ARHGAP21, showed strong binding affinities with RAC1 with ipTM of 0.91 and 0.92, respectively. Out of 120 GEFs and GAPs, AlphaFold2 predicted 6 of them with high binding affinities to RhoV (ipTM greater than 0.79). They are ARHGEF5, ARHGEF3, ARHGAP21, ITSN1, and ITSN2. Their binding affinities were confirmed by AlphaFold3, showing a strong correlation with AlphaFold2 (R of 0.79). AlphaFold3 also demonstrated high binding affinities between RhoV and compounds Palmitic acid (PLM), Citric acid (CIT), and Oleic acid (OLA). Conclusion AlphaFold is a revolutionary protein structural prediction tool with the ability to predict protein-protein binding affinities with high accuracy. AlphaFold2 is open to researchers in the field and allows unlimited queries on its server. AlphaFold3 only allows 20 predictions per research account per day. AlphaFold successfully predicted known binding partners of RAC1 and that RhoV could interact with the following GEFs and GAPs, ARHGEF5, ARHGAP21, and ARHGEF3, with high affinities. AlphaFold is a reliable in silico tool to screen binding partners of any protein of interest before meaningful biochemical interaction is confirmed in vitro and in vivo. Citation Format: Zebang Mark Li, Xiaoxu Zhou, Shaolei Lu. In silico Prediction of Proteins Interacting with a Basal-like Pancreatic Cancer marker, RhoV, Using AlphaFold [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A021.
Abstract B057: The circadian master regulator BMAL1 blocks immune cell recognition of pancreatic ductal adenocarcinomas via tumor-derived interleukin-1 receptor antagonist
Authors: Orjola Prela, Lan Wang, Chris Harris, Darren Carpizo
Journal: Cancer Research (2024)

Abstract Many tumor types, including pancreatic adenocarcinomas, have dysregulated circadian rhythms. Previous work in our lab has shown that disseminated dormant tumor cells have increased expression of Dec2, a circadian rhythm gene, and knocking out Dec2 leads to increased overall survival in our murine resectable PDAC model. To see whether the effect of Dec2 is due to a circadian effect, we deleted the master regulator circadian gene, BMAL1. Using CRISPR-generated knockout (KO) cell lines, we saw that loss of Bmal1 completely abrogated metastasis in immunocompetent mice, but not in immunocompromised mice indicating an immune mediated mechanism. Similarly in our murine resectable PDAC model, loss of BMAL1 led to an increase in overall survival in immunocompetent mice only. Looking at the tumor microenvironment, we saw an increase in CD4+ and CD8+ T cell infiltration in the tumors derived from the BMAL KO cells. We then evaluated the BMAL KO cells for their cytokine secretion and saw that loss of BMAL1 led to decreased interleukin-1 receptor antagonist both in vitro and in vivo. IL-Ra has been shown in literature to suppress the immunogenic anti-tumor response by impairing the activities of APCs, CD4+ and CD8+ T cells and disruption of IL-1Ra can reverse the TME towards more immunogenic leading to an antitumor effect. Taken together these studies implicate Bmal1 in regulating anti-tumor immunity in PDAC through its regulation of IL-1Ra secretion. This is a novel function for a circadian rhythm gene in PDAC biology. Citation Format: Orjola Prela, Lan Wang, Chris Harris, Darren Carpizo. The circadian master regulator BMAL1 blocks immune cell recognition of pancreatic ductal adenocarcinomas via tumor-derived interleukin-1 receptor antagonist [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr B057.
Abstract C011: Targeting STAT3 overcomes PDAC resistance to EGFR/RAF1 inhibition leading to complete and durable tumor regression
Authors: Vasiliki Liaki, Mariano Barbacid, Carmen Guerra
Journal: Cancer Research (2024)

Abstract Pancreatic ductal adenocarcinoma (PDAC) belongs to the tumors with worst prognosis due to the lack of effective treatment. It was previously demonstrated that combined elimination of EGFR and RAF1, two main mediators of the KRAS signaling, induces complete regression of a limited subset of small tumors in a genetically engineered mouse model (Blasco et al., 2019). In the current study, we show that resistance of PDACs with big sizes to the elimination of RAF1 and EGFR is mediated by STAT3. Indeed, combined genetic ablation of EGFR, RAF1 and STAT3 both in vitro and in vivo, results in complete and irreversible regression of more than 40 independent mouse PDAC tumors driven by Kras/Trp53 mutations. Importantly, all PDACs were characterized by increased initial tumor size and highly heterogeneous molecular profile similar to that of Basal human tumors. Moreover, we have validated the efficacy of this novel therapeutic strategy using pharmacological agents, such as EGFR inhibitors approved for clinical use and the STAT3 PROTAC degrader SD-36. Finally, inhibition of RAF1, EGFR and STAT3 expression effectively blocked in vitro and in vivo tumor progression in ten independent patient-derived organoid (PDO) and patient-derived xenograft (PDX) cultures carrying KRAS and TP53 mutations. These results open the door to the development of novel targeted therapies for PDAC patients. Citation Format: Vasiliki Liaki, Mariano Barbacid, Carmen Guerra. Targeting STAT3 overcomes PDAC resistance to EGFR/RAF1 inhibition leading to complete and durable tumor regression [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C011.
Abstract PR-09: Temporally resolved proteomics identifies nidogen-2 as a co-target in pancreatic cancer that modulates fibrosis and therapy response
Authors: Paul Timpson, Brooke Pereira, Shona Ritchie, None katie Gordon, Thomas Cox
Journal: Cancer Research (2024)

Abstract Pancreatic cancer (PC) is highly lethal, with a five-year survival rate of ∼13%. PC is characterised by progressive cancer-associated fibrosis. We and others have shown that targeting cancer fibrosis can improve chemotherapy efficacy and impair metastasis in pre-clinical models. As such, we aimed to use integrated temporal proteomics to dissect the matrix signatures of pancreatic tumours from the highly-metastatic KPC (Pdx1-Cre; LSL-K-rasG12D/+; LSL-p53R172H/+) and poorly-metastatic KPflC (Pdx1-Cre; LSL-K-rasG12D/+; LSL-p53fl/+) mouse models, with an aim to identify new metastatic drivers in this deadly disease. We collected pancreatic tissue from KPflC, KPC and wildtype (WT) controls at early (∼50 days), mid (∼90 days) and late-stage disease (∼200 days), enriched them for matrix proteins using ISDoT de-cellularisation and analysed them using data independent acquisition liquid chromatography-tandem mass spectrometry (DIA LC-MS/MS). DIA LC-MS/MS revealed an increased abundance of Nidogen-2 (NID2) in KPC tumours compared to KPflC. Organotypic matrices generated with NID2 CRISPR-interference (CRISPRi) CAFs had reduced fibrosis, shown via second harmonic generation (SHG) multiphoton imaging and Picrosirius Red/birefringence analysis. Organotypic invasion assays revealed that depletion of CAF NID2 significantly impeded the 3D invasion of cancer cells. Subcutaneous and orthotopic co-seeding experiments using NID2 CRISPRi CAFs with cancer cells showed that NID2 inhibition significantly impeded tumour growth and fibrosis. Intravital (in vivo) imaging with quantum dots revealed improved vascular patency in live NID2 targeted tumours, with improved response to chemotherapy. Strikingly, in orthotopic models, mice bearing NID2 targeting had significantly reduced liver metastasis and increased survival, revealing NID2 as a new stromal co-target in this aggressive disease. Citation Format: Paul Timpson, Brooke Pereira, Shona Ritchie, katie Gordon, Thomas Cox. Temporally resolved proteomics identifies nidogen-2 as a co-target in pancreatic cancer that modulates fibrosis and therapy response [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr PR-09.
Abstract A041: Deciphering the bidirectional influences of sympathetic neurons and cancer associated fibroblasts and the resulting contributions to PDAC progression
Authors: Ariana Sattler, Parham Diba, Tetiana Korzun, Marigold Kuykendall, Kevin MacPherson-Hawthorne, Mara Sherman, Teresa Zimmers, Sebnem E Eksi
Journal: Cancer Research (2024)

Abstract The pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment (TME) is innervated by a variety of peripheral nerves that are emerging as facilitators of tumor initiation, progression and metastasis. However, the influences of sympathetic nerves on the TME and how these bi-directional interactions can exacerbate PDAC progression remains unclear. Sympathetic nerves innervate both human and murine PDAC tumors and are frequently surrounded by abundant and heterogeneous cancer-associated fibroblasts (CAFs), which are known to play various crucial roles in PDAC progression. In our studies, we aim to elucidate the bidirectional CAF and sympathetic-neuron crosstalk that may promote tumor growth using a variety of in vitro coculture systems to model sympathetic-CAF interactions, as well as in vivo modeling of nerves in murine PDAC tumors. Our nerve-CAF cocultures reveal that CAFs closely and frequently interact with sympathetic nerves, and also enhance sympathetic nerve outgrowth. We further sequenced these cocultured conditions to evaluate intrinsic transcriptional changes that may be contributing to the enhanced nerve outgrowth. We identified several genes that may contribute to upregulated CAF adhesion, ECM deposition and neuroactive ligand-receptor interactions, which may also be supportive of the axon outgrowth and tumor cell growth. We are also currently characterizing human and murine PDAC samples that contain and lack sympathetic innervation to evaluate spatial phenotypic shifts within the TME. Collectively, our results suggest that this crosstalk between sympathetic neurons and CAFs may both enhance tumor innervation and tumor-promoting phenotypes in the TME, such as axonogenesis and fibrosis in PDAC. Citation Format: Ariana Sattler, Parham Diba, Tetiana Korzun, Marigold Kuykendall, Kevin MacPherson-Hawthorne, Mara Sherman, Teresa Zimmers, Sebnem E Eksi. Deciphering the bidirectional influences of sympathetic neurons and cancer associated fibroblasts and the resulting contributions to PDAC progression [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A041.
Abstract C049: Computational Methods for Central and Lipid Metabolism Networks Analysis to Reveals Flux Change in PDAC
Authors: Sha Cao, Haiqi Zhu, Yijie Wang, Melissa Fishel, Chi Zhang
Journal: Cancer Research (2024)

Abstract Pancreatic ductal adenocarcinoma (PDAC) is among the most challenging cancers to treat due to its aggressive nature and the difficulties in early detection. The disease progresses rapidly from stage T1 to T4, leaving a narrow window for effective intervention. This swift progression is closely tied to significant metabolic alterations, and current studies have highlighted specific metabolic changes. This includes elevated glutamine metabolism and altered aspartate and alpha-ketoglutarate production to support uncontrolled tumor growth; and elevated lysophosphatidylcholines secretion by cancer-associated fibroblasts to support tumor progression. These insights underscore the need for a holistic understanding of PDAC metabolism. Hence, there is an urgent need for a comprehensive and high-resolution analysis of PDAC's metabolic landscape remains unexplored. To computationally characterize the PDAC metabolism and fully leverage the large-scale transcriptomics with matched or unmatched metabolomics data, we developed an algorithm based on the Michaelis-Menten equation to estimate distribution-wise variations in mass-carrying metabolic networks using gene expression and metabolomics data. We start by manually curating a PDAC-specific metabolic network that focuses on central metabolism, glutamine-glutamate metabolism, and lipid metabolism. We then gathered comprehensive kinetic parameters, predicted enzyme activity from transcriptomics data, and conducted metabolomic profiling to determine metabolic compound concentrations. By applying Monte Carlo sampling methods, we achieved an overall balance of metabolic flux, enabling us to model reaction rates accurately and predict metabolic shifts. This approach holds potential to provide a comprehensive perspective on the rewired metabolism in PDAC, inspiring the development of metabolic targets or diet interventions for therapeutic treatment. Citation Format: Sha Cao, Haiqi Zhu, Yijie Wang, Melissa Fishel, Chi Zhang. Computational Methods for Central and Lipid Metabolism Networks Analysis to Reveals Flux Change in PDAC [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C049.
Abstract A006: Generation of a flexible pancreatic cancer mouse model via somatic tissue engineering
Authors: Ziyue (Zoey) Yang, Mara Cardenas, Akihiko Miyauchi, Caroline Snider, Ronald Parchem
Journal: Cancer Research (2024)

Abstract Pancreatic cancer, recognized as one of the most lethal cancer types, exhibits a dismal five-year survival rate below 12%. The genetic and epigenetic heterogeneity in human cancer poses a tremendous challenge in understanding disease mechanisms and developing targeted therapeutics. Current mouse models in the field can recapitulate some features of human pathophysiology but have limitations. While tumor formation in patients is focal, most genetically engineered mouse models (GEMMs) express oncogenes throughout the pancreas. GEMMs also have limited flexibility to manipulate gene expression and model the heterogeneity of human cancer. Additionally, GEMMs require significant time for crossing and tumor formation. Tumor transplantation models offer greater flexibility, however, they often require immunodeficient mice, which limits their applications in modeling the tumor microenvironment. To overcome the limits of current mouse models, we combined the piggyBac transposon system, CRISPR/Cas9, and in vivo electroporation to engineer somatic pancreatic tissue to induce focal tumor formation in immune-competent mice. With this approach, we engineered wildtype pancreata to express oncogenic KrasG12D while knocking out multiple tumor suppressors. We optimized this protocol by generating multiplexed gRNA constructs and cell type-specific promoters to improve reproducibility. Low-grade tumors formed within 10 days after electroporation, progressed to higher grade within a month, and metastasized to peritoneal organs during disease progression. Mouse tumors also recapitulated histopathological features in human patients. Lastly, we used our novel mouse model to study how mutant Kras disrupts post-transcriptional regulation by microRNA to drive pancreatic tumorigenesis. This model offers a powerful platform for manipulating gene expression and functionality to model cancer heterogeneity, ultimately advancing precision oncology's prospects for treating human patients. Citation Format: Ziyue (Zoey) Yang, Mara Cardenas, Akihiko Miyauchi, Caroline Snider, Ronald Parchem. Generation of a flexible pancreatic cancer mouse model via somatic tissue engineering [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A006.
Abstract PR-05: Endocrine beta-cell stress promotes pancreatic ductal adenocarcinoma through endocrine-exocrine cell crosstalk
Authors: Cathy Garcia, Aarthi Venkat, Daniel McQuaid, Sherry Agabiti, Alex Tong, Rebecca Cardone, Richard Kibbey, Smita Krishnaswamy, Mandar Muzumdar
Journal: Cancer Research (2024)

Abstract For a long time, the pancreas was thought to have separate cellular compartments that functioned distinctly from one another. The endocrine pancreas (islets of Langerhans) regulates glucose homeostasis, while the exocrine pancreas (acini and ducts) produces and secretes digestive enzymes. However, it has recently become clear that the endocrine and exocrine compartments communicate with one another, and dysfunction in one leads to dysfunction in the other, resulting in diabetes or pancreatitis. However, whether and how the endocrine pancreas drives the development of pancreatic ductal adenocarcinoma (PDAC), an exocrine tumor, remains unresolved. Strikingly, we found that genetic ablation of insulin-producing islet beta (β) cells (Akita) in a faithful Kras/Trp53-driven PDAC model (KPC: Kras LSL-G12D /+; Trp 53172 /+; Pdx1-Cre) suppressed PDAC progression. Conversely, obesity-induced β cell hormone dysregulation promoted Kras-driven PDAC development. Single-cell RNA sequencing (scRNA-seq) analysis of wild-type and obese mice (high-fat diet-fed and leptin-deficient (Lep ob/ob )) revealed increased expression of the peptide hormone cholecystokinin (CCK) in a subset of β cells concordant with increasing obesity, and transgenic β cell overexpression of CCK was sufficient to promote exocrine tumorigenesis in KC mice. Combined in silico (pseudotime (TrajectoryNET) and archetypal (AANet) analysis) and experimental (CreER) lineage tracing demonstrated that CCK-expressing β cells originated from a pre-existing immature β cell population (virgin β cells). Grainger causality analysis of transcriptional networks uncovered a stress-induced JNK-cJun pathway that promotes CCK expression β cells, which we confirmed using JNK inhibitors in β cell models. Together, our findings identify cellular and molecular mechanisms of β cell adaptation to obesity that contribute to obesity-driven pancreatic cancer. Furthermore, we define a critical role for endocrine-exocrine signaling in PDAC progression and stress-induced β cell pathways which could be leveraged to target the endocrine pancreas to subvert exocrine tumorigenesis. Citation Format: Cathy Garcia, Aarthi Venkat, Daniel McQuaid, Sherry Agabiti, Alex Tong, Rebecca Cardone, Richard Kibbey, Smita Krishnaswamy, Mandar Muzumdar. Endocrine beta-cell stress promotes pancreatic ductal adenocarcinoma through endocrine-exocrine cell crosstalk [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr PR-05.
Abstract IA-09: Spatiotemporal metabolic networks in pancreatic cancer and associated cachexia
Authors: Blanca Majem, Min-Sik Lee, Kyung Cheul Shin, Insia Naqvi, Courtney Dennis, Lucas Dailey, Sarah Jeanfavre, Mari Mino-Kenudson, Joao B Xavier, Clary B Clish, Deepti Mathur, Nada Y Kalaany
Journal: Cancer Research (2024)

Abstract Cachexia or body wasting is a significant contributing factor to the morbidity and mortality of pancreatic cancer. Despite an unmet need, its metabolic underpinnings remain poorly understood. Here, we characterize an inducible mouse model of pancreatic cancer cachexia that recaptures human disease progression. We present longitudinal systemic metabolic profiling analyses through pre-, early and late cachexia stages in male and female pancreas, its interstitial fluid (IF), plasma, liver, adipose and skeletal muscle. We find that each tissue has a unique metabolome and trajectory across stages, and reveal metabolic signatures with marked lipid enrichment in the pancreatic IF. Using mathematical modeling, we identify metabolites participating in cross-tissue networks and in vivo validate a lactate-hexose connection. We find systemic metabolic changes prior to weight loss, and use feature selection algorithms to identify potential predictive markers of cachexia progression. Our study provides a resource for system-wide metabolic network evolution of pancreatic cancer cachexia, highlighting the potential for prevention and therapy. Citation Format: Blanca Majem, Min-Sik Lee, Kyung Cheul Shin, Insia Naqvi, Courtney Dennis, Lucas Dailey, Sarah Jeanfavre, Mari Mino-Kenudson, Joao B Xavier, Clary B Clish, Deepti Mathur, Nada Y Kalaany. Spatiotemporal metabolic networks in pancreatic cancer and associated cachexia [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr IA-09.