Comprehensive Analysis of LincRNAs in Classical and Basal-Like Subtypes of Pancreatic Cancer

An Integrated Multi-Omics Analysis Identifying Immune Subtypes of Pancreatic Cancer

Limited studies have explored novel pancreatic cancer (PC) subtypes or prognostic biomarkers based on the altered activity of relevant signaling pathway gene sets. Here, we employed non-negative matrix factorization (NMF) to identify three immune subtypes of PC based on C7 immunologic signature gene set activity in PC and normal samples. Cluster 1, the immune-inflamed subtype, showed a higher response rate to immune checkpoint blockade (ICB) and had the lowest tumor immune dysfunction and exclusion (TIDE) scores. Cluster 2, the immune-excluded subtype, exhibited strong associations with stromal activation, characterized by elevated expression levels of transforming growth factor (TGF)-β, cell adhesion, extracellular matrix remodeling, and epithelial-to-mesenchymal transition (EMT) related genes. Cluster 3, the immune-desert subtype, displayed limited immune activity. For prognostic prediction, we developed an immune-related prognostic risk model (IRPM) based on four immune-related prognostic genes in pancreatic cancer, RHOF, CEP250, TSC1, and KIF20B. The IRPM demonstrated excellent prognostic efficacy and successful validation in an external cohort. Notably, the key gene in the prognostic model, RHOF, exerted significant influence on the proliferation, migration, and invasion of pancreatic cancer cells through in vitro experiments. Furthermore, we conducted a comprehensive analysis of somatic mutational landscapes and immune landscapes in PC patients with different IRPM risk scores. Our findings accurately stratified patients based on their immune microenvironment and predicted immunotherapy responses, offering valuable insights for clinicians in developing more targeted clinical strategies.

Exploiting the molecular subtypes and genetic landscape in pancreatic cancer: the quest to find effective drugs

Pancreatic Ductal Adenocarcinoma (PDAC) is a very lethal disease that typically presents at an advanced stage and is non-compliant with most treatments. Recent technologies have helped delineate associated molecular subtypes and genetic variations yielding important insights into the pathophysiology of this disease and having implications for the identification of new therapeutic targets. Drug repurposing has been evaluated as a new paradigm in oncology to accelerate the application of approved or failed target-specific molecules for the treatment of cancer patients. This review focuses on the impact of molecular subtypes on key genomic alterations in PDAC, and the progress made thus far. Importantly, these alterations are discussed in light of the potential role of drug repurposing in PDAC.

Establishment and validation of a ubiquitination-related gene signature associated with prognosis in pancreatic duct adenocarcinoma

Background

Patients with pancreatic duct adenocarcinoma (PDAC) have varied prognoses that depend on numerous variables. However, additional research is required to uncover the latent impact of ubiquitination-related genes (URGs) on determining PDAC patients' prognoses.

Methods

The URGs clusters were discovered via consensus clustering, and the prognostic differentially expressed genes (DEGs) across clusters were utilized to develop a signature using a least absolute shrinkage and selection operator (LASSO) regression analysis of data from TCGA-PAAD. Verification analyses were conducted across TCGA-PAAD, GSE57495 and ICGC-PACA-AU to show the robustness of the signature. RT-qPCR was used to verify the expression of risk genes. Lastly, we formulated a nomogram to improve the clinical efficacy of our predictive tool.

Results

The URGs signature, comprised of three genes, was developed and was shown to be highly correlated with the prognoses of PAAD patients. The nomogram was established by combining the URGs signature with clinicopathological characteristics. We discovered that the URGs signature was remarkably superior than other individual predictors (age, grade, T stage, et al). Also, the immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, and StromalScores were elevated in the low-risk group. The immune cells that infiltrated the tissues were different between the two groups, as did the expression of immune-related genes.

Conclusion

The URGs signature could act as the biomarker of prognosis and selecting appropriate therapeutic drugs for PDAC patients.

Genomic Heterogeneity of Pancreatic Ductal Adenocarcinoma and Its Clinical Impact

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer death due to limited advances in recent years in early diagnosis and personalized therapy capable of overcoming tumor resistance to chemotherapy. In the last decades, significant advances have been achieved in the identification of recurrent genetic and molecular alterations of PDAC including those involving the KRAS, CDKN2A, SMAD4, and TP53 driver genes. Despite these common genetic traits, PDAC are highly heterogeneous tumors at both the inter- and intra-tumoral genomic level, which might contribute to distinct tumor behavior and response to therapy, with variable patient outcomes. Despite this, genetic and genomic data on PDAC has had a limited impact on the clinical management of patients. Integration of genomic data for classification of PDAC into clinically defined entities-i.e., classical vs. squamous subtypes of PDAC-leading to different treatment approaches has the potential for significantly improving patient outcomes. In this review, we summarize current knowledge about the most relevant genomic subtypes of PDAC including the impact of distinct patterns of intra-tumoral genomic heterogeneity on the classification and clinical and therapeutic management of PDAC.

The Role of lncRNAs in the Stem Phenotype of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma is one of the deadliest tumors. This neoplasia is characterized by an important cellular and phenotypic heterogeneity. In particular, it has been shown that at least two subtypes can be found: basal-like, which presents stem-like properties, and classical. Cancer stem cells have been isolated and characterized from these tumors, showing their dependance on general and tissue-specific stem transcription factors and signaling pathways. Nevertheless, little is known about their tissue microenvironment and cell non-autonomous regulators, such as long-non-coding RNAs. (lncRNAs). In this review, we summarize the current knowledge about the positive and negative effects of lncRNAs in the stemness phenotype of pancreatic ductal adenocarcinoma cancer (PDAC).