Response determinants to immunotherapy in metastatic pancreatic ductal adenocarcinoma (mPDAC) remain unclear, limiting treatment advancements. We repo…

Author summary Pancreatic cancer is the most malignant tumor, and there is no ideal targeted drug at present, so the prognosis of patients is very poor. There is an urgent need to find targets for eva...

Pancreatic Ductal Adenocarcinoma In article number 2501774, Ruiyu Xie and co-workers demonstrate that TET3 plays a non-canonical role in regulating lipid metabolism in pancreatic ductal adenocarcinom...

This study investigates the expression and functional role of the deubiquitinase PSMD14 in PC, with a focus on the mechanism by which it promotes lactate accumulation–induced histone lactylation, the....

Pancreatic cancer is one of the deadliest cancers and has very limited therapeutic options and a dismal prognosis. Among various signaling pathways which are activated during tumor development, hypera...

Background Accurate estimation of cell type proportions from bulk gene expression data is essential for understanding the cellular heterogeneity underlying complex tissues and diseases. Here, we introduce xCell 2.0, an advanced version of the xCell algorithm, featuring a training function that permits the utilization of any reference dataset. xCell 2.0 generates cell type gene signatures using an improved methodology, including automated handling of cell type dependencies and more robust signature generation. Results We benchmark xCell 2.0 against eleven popular deconvolution methods using nine human and mouse reference sets and 26 validation datasets, encompassing 1711 samples and 67 cell types. Additionally, we validate xCell 2.0 using the independent Deconvolution DREAM Challenge dataset. xCell 2.0 outperforms all other tested methods across distinct reference datasets, demonstrating superior accuracy and consistency across diverse biological contexts. xCell 2.0 also shows the best performance in minimizing spillover effects between related cell types. In a test example of pan-cancer immune cell checkpoint blockage response prediction, xCell 2.0-derived TME features significantly improve prediction accuracy compared to models using only cancer type and treatment information, and outperformed other deconvolution methods and established prediction scores. Conclusions xCell 2.0 is a versatile and robust tool for cell type deconvolution that maintains high performance across various reference types and biological contexts. It is available both via a locally hosted web application and as a Bioconductor-compatible package, equipped with a large collection of pre-trained cell type signatures for human and mouse research.

Cell Death & Differentiation - K11- and K29-ubiquitination-mediated nuclear translocation of glycolytic enzyme aldolase A promotes pancreatic cancer progression by NF-κB activation

Pancreatic ductal adenocarcinoma (PDAC) is an exceedingly lethal cancer that lacks actionable molecular drivers, limiting precision treatment options. We previously identified the transcription factor...

Pancreatic ductal adenocarcinoma (PDAC) is characterized by dense, fibroblast-rich stroma that actively shapes the tumor microenvironment. Most PDAC cases arise from conserved genetic transformations ...

Gene expression programs directed by MYC mediate oncogenic KRAS signaling in pancreatic cancer.

Abstract. Multi-omics data, which include genomic, transcriptomic, epigenetic, and proteomic data, are gaining increasing importance for determining the cl

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, driven largely by oncogenic KRAS, yet effective targeted therapies remain unavailable. Long noncoding RNAs (lncRNAs) are emergi...

Background Pancreatic ductal adenocarcinoma (PDAC) is highly lethal, with liver metastases leading to poorer outcomes. Occult liver metastases (OLM), undetected by initial imaging, complicate treatm.....

Peritumoural pancreatitis and lobular injury are commonly seen in pancreatic cancer. Here, the authors reveal interactions between invading tumour cells and inflammation-related lobular cells, linked to switching from a basal to classical tumor cell phenotype.

Using mouse pancreatic cancer models, Tsanov et al. show that reactivation of SMAD4 at metastatic sites promotes tumor growth in the lung through RUNX1 but restrains metastatic growth through KLF4 in the liver, influenced by organ-specific epigenetic states.

Abstract. Synthetic lethality (SL) is an extreme form of negative genetic interaction, where simultaneous disruption of two non-essential genes causes cell

G3BP1 promotes pancreatic ductal adenocarcinoma (PDAC) tumorigenesis driven by oncogenic KRAS mutations through liquid liquid phase separation (LLPS) mediated assembly of stress granules (SGs). Howeve...

Pancreatic cancer has a high mortality rate and lacks early detection markers. Advanced methods, such as machine learning (ML) and network analysis, i…

Advanced pancreatic cancer presents dismal survival with limited effective, well-tolerated options beyond chemotherapy. This phase 1 trial evaluates t…