Exploring the key genetic association between chronic pancreatitis and pancreatic ductal adenocarcinoma through integrated bioinformatics

Uncovering the therapeutic potentials of marine-derived natural compounds with small amounts for neurological disorders

The discovery of novel drugs from the ocean is a relatively recent development. However, for most studies of marine drugs, the priority is the discovery of compounds with new structures. Normally, only small amounts (< 1 mg) of new compounds could be extracted from marine microbes, and it is difficult to evaluate the therapeutic potentials of these newly-identified marine-derived natural compounds by traditional cell- or animal-based phenotypic screenings. Genes play a crucial role in determining the phenotype of diseases and the action of drugs. By comparing genomic expression associated with disease conditions and compound treatments, it is possible to predict the potential of a certain compound to counteract a specific type of disease. In this study, marine-derived natural compounds-induced genomic changes in cells were collected either from public databases or by using RNA-seq analysis. The therapeutic potentials of representative marine-derived natural compounds, namely phycocyanobilin, cycloheximide and NBU-1, a newly-identified natural compound extracted from a marine sponge-associated Streptomyces, on bipolar disorder (BD), Parkinson's disease (PD) and Alzheimer's disease (AD), were predicted by gene set enrichment analysis (GSEA), respectively. The anti-neurological disorder activity of these marine-derived natural compounds were further validated in methamphetamine-induced rats mimicking manic phase of BD, 6-OHDA-treated PC12 cells mimicking PD neurotoxicity and β-amyloid oligomer-incubated SH-SY5Y cells mimicking AD neuronal loss. Our study provides not only new insights for pharmacological applications of the marine-derived natural compounds here studied, but also a method for predicting and evaluating therapeutic potentials of newly-identified marine-derived natural compounds with small quantities.

Innate Immunity and Platelets: Unveiling Their Role in Chronic Pancreatitis and Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal forms of cancer, characterized by a highly desmoplastic tumor microenvironment. One main risk factor is chronic pancreatitis (CP). Progression of CP to PDAC is greatly influenced by persistent inflammation promoting genomic instability, acinar-ductal metaplasia, and pancreatic intraepithelial neoplasia (PanIN) formation. Components of the extracellular matrix, including immune cells, can modulate this progression phase. This includes cells of the innate immune system, such as natural killer (NK) cells, macrophages, dendritic cells, mast cells, neutrophils, and myeloid-derived suppressor cells (MDSCs), either promoting or inhibiting tumor growth. On one hand, innate immune cells can trigger inflammatory responses that support tumor progression by releasing cytokines and growth factors, fostering tumor cell proliferation, invasion, and metastasis. On the other hand, they can also activate immune surveillance mechanisms, which can limit tumor development. For example, NK cells are cytotoxic innate lymphoid cells that are able to kill tumor cells, and active dendritic cells are crucial for a functioning anti-tumor immune response. In contrast, mast cells and MDSCs rather support a pro-tumorigenic tumor microenvironment that is additionally sustained by platelets. Once thought to play a role in hemostasis only, platelets are now recognized as key players in inflammation and cancer progression. By releasing cytokines, growth factors, and pro-angiogenic mediators, platelets help shape an immunosuppressive microenvironment that promotes fibrotic remodeling, tumor initiation, progression, metastasis, and immune evasion. Neutrophils and macrophages exist in different functional subtypes that can both act pro- and anti-tumorigenic. Understanding the complex interactions between innate immune cells, platelets, and early precursor lesions, as well as PDAC cells, is crucial for developing new therapeutic approaches that can harness the immune and potentially also the coagulation system to target and eliminate tumors, offering hope for improved patient outcomes.

Identification of key regulators in pancreatic ductal adenocarcinoma using network theoretical approach

Pancreatic Ductal Adenocarcinoma (PDAC) is a devastating disease with poor clinical outcomes, which is mainly because of delayed disease detection, resistance to chemotherapy, and lack of specific targeted therapies. The disease's development involves complex interactions among immunological, genetic, and environmental factors, yet its molecular mechanism remains elusive. A major challenge in understanding PDAC etiology lies in unraveling the genetic profiling that governs the PDAC network. To address this, we examined the gene expression profile of PDAC and compared it with that of healthy controls, identifying differentially expressed genes (DEGs). These DEGs formed the basis for constructing the PDAC protein interaction network, and their network topological properties were calculated. It was found that the PDAC network self-organizes into a scale-free fractal state with weakly hierarchical organization. Newman and Girvan's algorithm (leading eigenvector (LEV) method) of community detection enumerated four communities leading to at least one motif defined by G (3,3). Our analysis revealed 33 key regulators were predominantly enriched in neuroactive ligand-receptor interaction, Cell adhesion molecules, Leukocyte transendothelial migration pathways; positive regulation of cell proliferation, positive regulation of protein kinase B signaling biological functions; G-protein beta-subunit binding, receptor binding molecular functions etc. Transcription Factor and mi-RNA of the key regulators were obtained. Recognizing the therapeutic potential and biomarker significance of PDAC Key regulators, we also identified approved drugs for specific genes. However, it is imperative to subject Key regulators to experimental validation to establish their efficacy in the context of PDAC.

The known genetic variants of BRCA1, BRCA2 and NOD2 in pancreatitis and pancreatic cancer risk assessment

The single nucleotide polymorphism in NOD2 (rs2066847) is associated with conditions that may predispose to the development of gastrointestinal disorders, as well as the known BRCA1 and BRCA2 variants classified as risk factors in many cancers. In our study, we analyzed these variants in a group of patients with pancreatitis and pancreatic cancer to clarify their role in pancreatic disease development. The DNA was isolated from whole blood samples of 553 patients with pancreatitis, 83 patients with pancreatic cancer, 44 cases of other pancreatic diseases, and 116 healthy volunteers. The NOD2 (rs2066847), BRCA1 (rs80357914) and BRCA2 (rs276174813) were genotyped. The statistically significant 3-fold increased risk of pancreatic cancer was detected among the patients with rs2066847 polymorphism (OR = 2.77, p-value = 0.019). We did not find the studied polymorphisms in BRCA1 (rs80357914) and BRCA2 (rs276174813). However, the adjacent polymorphisms have been detected only in patients with pancreatic diseases. The studied variant in NOD2 occurs more frequently in pancreatic patients and significantly increases the risk of pancreatic cancer. It can be considered as a genetic risk factor that predisposes to cancer development. The analyzed regions in BRCA1 and BRCA2 may be a potential target in further search for a genetic marker of pancreatic diseases.

Integrated bioinformatics analysis reveals upregulated extracellular matrix hub genes in pancreatic cancer: Implications for diagnosis, prognosis, immune infiltration, and therapeutic strategies

BACKGROUND

Pancreatic cancer (PC) stands out as one of the most formidable malignancies and exhibits an exceptionally unfavorable clinical prognosis due to the absence of well-defined diagnostic indicators and its tendency to develop resistance to therapeutic interventions. The primary objective of this present study was to identify extracellular matrix (ECM)-related hub genes (HGs) and their corresponding molecular signatures, with the intent of potentially utilizing them as biomarkers for diagnostic, prognostic, and therapeutic applications.

METHODS

Three microarray datasets were sourced from the NCBI database to acquire upregulated differentially expressed genes (DEGs), while MatrisomeDB was employed for filtering ECM-related genes. Subsequently, a protein-protein interaction (PPI) network was established using the STRING database. The created network was visually inspected through Cytoscape, and HGs were identified using the CytoHubba plugin tool. Furthermore, enrichment analysis, expression pattern analysis, clinicopathological correlation, survival analysis, immune cell infiltration analysis, and examination of chemical compounds were carried out using Enrichr, GEPIA2, ULCAN, Kaplan Meier plotter, TIMER2.0, and CTD web platforms, respectively. The diagnostic and prognostic significance of HGs was evaluated through the ROC curve analysis.

RESULTS

Ten genes associated with ECM functions were identified as HGs among 131 DEGs obtained from microarray datasets. Notably, the expression of these HGs exhibited significantly (p < 0.05) higher in PC, demonstrating a clear association with tumor advancement. Remarkably, higher expression levels of these HGs were inversely correlated with the likelihood of patient survival. Moreover, ROC curve analysis revealed that identified HGs are promising biomarkers for both diagnostic (AUC > 0.75) and prognostic (AUC > 0.64) purposes. Furthermore, we observed a positive correlation between immune cell infiltration and the expression of most HGs. Lastly, our study identified nine compounds with significant interaction profiles that could potentially act as effective chemical agents targeting the identified HGs.

CONCLUSION

Taken together, our findings suggest that COL1A1, KRT19, MMP1, COL11A1, SDC1, ITGA2, COL1A2, POSTN, FN1, and COL5A1 hold promise as innovative biomarkers for both the diagnosis and prognosis of PC, and they present as prospective targets for therapeutic interventions aimed at impeding the progression PC.