Single-cell RNA-seq reveals heterogeneity in metastatic renal cell carcinoma and effect of anti-angiogenesis therapy in the pancreas metastatic lesion.

Metastatic clear cell renal cell carcinoma has heterogenous tumor microenvironment (TME). Among the metastatic lesions, pancreas metastasis is rare and controversy in treatment approaches. Here, extensive primary and metastatic lesion samples were included by single-cell RNA-seq to decipher the distinct metastasis TME.

Unbiasedly decoding the tumor microenvironment with single-cell multiomics analysis in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a poor prognosis and limited therapeutic options. Research on the tumor microenvironment (TME) of PDAC has propelled the development of immunotherapeutic and targeted therapeutic strategies with a promising future. The emergence of single-cell sequencing and mass spectrometry technologies, coupled with spatial omics, has collectively revealed the heterogeneity of the TME from a multiomics perspective, outlined the development trajectories of cell lineages, and revealed important functions of previously underrated myeloid cells and tumor stroma cells.

FBXO32 Stimulates Protein Synthesis to Drive Pancreatic Cancer Progression and Metastasis.

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death worldwide, primarily due to its rapid progression. The current treatment options for PDAC are limited, and a better understanding of the underlying mechanisms responsible for PDAC progression is required to identify improved therapeutic strategies. In this study, we identified FBXO32 as an oncogenic driver in PDAC.

Multiomics integration reveals NETosis heterogeneity and TLR2 as a prognostic biomarker in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant neoplasm characterized by a poor prognosis and limited therapeutic strategy. The PDAC tumor microenvironment presents a complex heterogeneity, where neutrophils emerge as the predominant constituents of the innate immune cell population. Leveraging the power of single-cell RNA-seq, spatial RNA-seq, and multi-omics approaches, we included both published datasets and our in-house patient cohorts, elucidating the inherent heterogeneity in the formation of neutrophil extracellular traps (NETs) and revealed the correlation between NETs and immune suppression.

E3 ubiquitin ligase RBCK1 confers ferroptosis resistance in pancreatic cancer by facilitating MFN2 degradation.

Ferroptosis, a novel form of iron-dependent non-apoptotic cell death, plays an active role in the pathogenesis of diverse diseases, including cancer. However, the mechanism through which ferroptosis is regulated in pancreatic ductal adenocarcinoma (PDAC) remains unclear. Here, our study, via combining bioinformatic analysis with experimental validation, showed that ferroptosis is inhibited in PDAC.

The NF-κB/NUAK2 signaling axis regulates pancreatic cancer progression by targeting SMAD2/3.

Nuclear factor kappa B (NF-κB) plays a pivotal role in the development of pancreatic cancer, and its phosphorylation has previously been linked to the regulation of NUAK2. However, the regulatory connection between NF-κB and NUAK2, as well as NUAK2's role in pancreatic cancer, remains unclear. In this study, we observed that inhibiting NUAK2 impeded the proliferation, migration, and invasion of pancreatic cancer cells while triggering apoptosis.

Ribosome profiling: a powerful tool in oncological research.

Neoplastic cells need to adapt their gene expression pattern to survive in an ever-changing or unfavorable tumor microenvironment. Protein synthesis (or mRNA translation), an essential part of gene expression, is dysregulated in cancer. The emergence of distinct translatomic technologies has revolutionized oncological studies to elucidate translational regulatory mechanisms.

Epidemiology of pancreatic cancer: New version, new vision.

Pancreatic cancer (PC) is a devastating malignancy with an extremely high mortality rate and poses significant challenges to healthcare systems worldwide. The prevalence of PC risk factors spiked over the years, leading to a global increase in PC incidence rates. The contribution of different risk factors, however, varied from region to region due to genetic predisposition, environmental, social, and political factors underlying disease prevalence in addition to public health strategies.

Novel strategies optimize immunotherapy by improving the cytotoxic function of T cells for pancreatic cancer treatment.

Pancreatic cancer (PC) is considered highly malignant due to its unsatisfying prognosis and limited response to therapies. Immunotherapy has therefore been developed to harness the antigen-specific properties and cytotoxicity of the immune system, aiming to induce a robust anti-tumor immune response that specifically demolishes PC cells while minimizing lethality in healthy tissue. The activation and augmentation of cytotoxic T cells play a critical role in the initiation and final success of immunotherapy.

Organoid: Bridging the gap between basic research and clinical practice.

Nowadays, the diagnosis and treatment system of malignant tumors has increasingly tended to be more precise and personalized while the existing tumor models are still unable to fully meet the needs of clinical practice. Notably, the emerging organoid platform has been proven to have huge potential in the field of basic-translational medicine, which is expected to promote a paradigm shift in personalized medicine. Here, given the unique advantages of organoid platform, we mainly explore the prominent role of organoid models in basic research and clinical practice from perspectives of tumor biology, tumorigenic microbes-host interaction, clinical decision-making, and regenerative strategy.

PRKRA promotes pancreatic cancer progression by upregulating MMP1 transcription via the NF-κB pathway.

Objective: Pancreatic cancer (PC) is highly malignant, but the underlying mechanisms of cancer progression remain unclear. PRKRA is involved in cellular stress response, but its role in PC was unknown.

Methods: The expression of PRKRA between normal and tumor tissues were compared, and the prognostic value of PRKRA was evaluated.

mTOR inhibitor, gemcitabine and PD-L1 antibody blockade combination therapy suppresses pancreatic cancer progression via metabolic reprogramming and immune microenvironment remodeling in Trp53LSL-KrasPdx-1-Cre murine models.

Objective: Resistance to immunotherapy and chemotherapy hinders the prognosis of pancreatic cancer(PC). We hypothesized that the combination of mTOR inhibitor sirolimus and gemcitabine would change the metabolic landscape of PC and enhance the anti-PD-L1 therapy.

Methods: In KPC mice, the following regimens were administered and tumor growth inhibition rates(TGI%) were calculated: sirolimus(S), PD-L1 antibody(P), gemcitabine(G), sirolimus + PD-L1 antibody(SP), sirolimus + gemcitabine(SG), PD-L1 + gemcitabine(PG) and sirolimus + PD-L1 antibody + gemcitabine(SPG).

Cancer-specific survival and metastasis in pancreatic mucinous cystadenocarcinoma: A SEER-based cohort study.

Aims: This study aimed to investigate the prognostic value of clinical features for cancer-specific survival (CSS) and metastasis in patients with pancreatic mucinous cystadenocarcinoma (MCAC). We further constructed and validated an effective nomogram to predict CSS.

Methods: We screened patients diagnosed with pancreatic MCAC from Surveillance Epidemiology and End Results (SEER) database.

DGCyTOF: Deep learning with graphic cluster visualization to predict cell types of single cell mass cytometry data.

Single-cell mass cytometry, also known as cytometry by time of flight (CyTOF) is a powerful high-throughput technology that allows analysis of up to 50 protein markers per cell for the quantification and classification of single cells. Traditional manual gating utilized to identify new cell populations has been inadequate, inefficient, unreliable, and difficult to use, and no algorithms to identify both calibration and new cell populations has been well established. A deep learning with graphic cluster (DGCyTOF) visualization is developed as a new integrated embedding visualization approach in identifying canonical and new cell types.

XDeathDB: a visualization platform for cell death molecular interactions.

Lots of cell death initiator and effector molecules, signalling pathways and subcellular sites have been identified as key mediators in both cell death processes in cancer. The XDeathDB visualization platform provides a comprehensive cell death and their crosstalk resource for deciphering the signaling network organization of interactions among different cell death modes associated with 1461 cancer types and COVID-19, with an aim to understand the molecular mechanisms of physiological cell death in disease and facilitate systems-oriented novel drug discovery in inducing cell deaths properly. Apoptosis, autosis, efferocytosis, ferroptosis, immunogenic cell death, intrinsic apoptosis, lysosomal cell death, mitotic cell death, mitochondrial permeability transition, necroptosis, parthanatos, and pyroptosis related to 12 cell deaths and their crosstalk can be observed systematically by the platform.

An optimized pulse coupled neural network image de-noising method for a field-programmable gate array based polarization camera.

The quality of polarization images is easy to be affected by the noise in the image acquired by a polarization camera. Consequently, a de-noising method optimized with a Pulse Coupled Neural Network (PCNN) for polarization images is proposed for a Field-Programmable Gate Array (FPGA)-based polarization camera in this paper, in which the polarization image de-noising is implemented using an adaptive PCNN improved by Gray Wolf Optimization (GWO) and Bi-Dimensional Empirical Mode Decomposition (BEMD). Unlike other artificial neural networks, PCNN does not need to be trained, but the parameters of PCNN such as the exponential decay time constant, the synaptic junction strength factor, and the inherent voltage constant play a critical influence on its de-noising performance.

kESVR: An Ensemble Model for Drug Response Prediction in Precision Medicine Using Cancer Cell Lines Gene Expression.

Background: Cancer cell lines are frequently used in research as in-vitro tumor models. Genomic data and large-scale drug screening have accelerated the right drug selection for cancer patients. Accuracy in drug response prediction is crucial for success.

Integrative Genomic Analysis of Gemcitabine Resistance in Pancreatic Cancer by Patient-derived Xenograft Models.

Purpose: Gemcitabine is most commonly used for pancreatic cancer. However, the molecular features and mechanisms of the frequently occurring resistance remain unclear. This work aims at exploring the molecular features of gemcitabine resistance and identifying candidate biomarkers and combinatorial targets for the treatment.