Construction and evaluation of an aging-associated genes-based model for pancreatic adenocarcinoma prognosis and therapies

Identification of basement membrane-related prognostic model associated with the immune microenvironment and synthetic therapy response in pancreatic cancer: integrated bioinformatics analysis and clinical validation

Pancreatic cancer (PC) is a common and highly malignant tumor. Basement membrane (BM) is formed by the crosslinking of extracellular matrix macromolecules and acts as a barrier against tumor cell metastasis. However, the role of BM in PC prognosis, immune infiltration, and treatment remains unclear. This study collected transcriptome and clinical survival data of PC via TCGA, GEO, and ICGC databases. PC patients (PCs) from the First Affiliated Hospital of Dalian Medical University were obtained as the clinical validation cohort. BM-related genes (BMRGs) were acquired from GeneCards and basement membraneBASE databases. A total of 46 differential-expressed BMRGs were identified. Then the BM-related prognostic model (including DSG3, MET, and PLAU) was built and validated. PCs with a low BM-related score had a better outcome and were more likely to benefit from oxaliplatin, irinotecan, and KRAS(G12C) inhibitor-12, and immunotherapy. Immune analysis revealed that BM-related score was positively correlated with neutrophils, cancer-associated fibroblasts, and macrophages infiltration, but negatively correlated with CD8+ T cells, NK cells, and B cells infiltration. PCs from the clinical cohort further verified that BM-related model could accurately predict PCs' outcomes. DSG3, MET, and PLAU were notably up-regulated within PC tissues and linked to a poor prognosis. In vitro experiments showed that DSG3 knockdown markedly suppressed the proliferation, migration, and invasion of PC cells. Molecular docking indicated that epigallocatechin gallate had a strong binding activity with DSG3, MET, and PLAU and may be used as a potential therapeutic agent for PC. In conclusion, this study developed a BM-related model associated with PC prognosis, immune infiltration, and treatment, which provided new insights into PC stratification and drug intervention.

Identification and Validation of a Hypoxia and Glycolysis Prognostic Signatures in Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) represents a prevalent subtype of non-small cell lung cancer with a complex molecular landscape. Dysregulated cellular energetics, notably the interplay between hypoxia and glycolysis, has emerged as a hallmark feature of LUAD tumorigenesis and progression. In this study, we aimed to identify hypoxia and glycolysis related gene signatures and construct a prognostic model to enhance the clinical management of LUAD. Methods: A gene signature associated with hypoxia and glycolysis was established within the The Cancer Genome Atlas (TCGA) cohort and subsequently validated in the GSE31210 cohort. Additionally, a nomogram was formulated to aid in predictive modeling. Subsequently, an evaluation of the tumor microenvironment and immune checkpoints expression levels was conducted to discern disparities between low risk and high risk groups. Lastly, an exploration for drugs with potential effectiveness was carried out. Results: Our analyses revealed a distinct hypoxia and glycolysis related gene signature consisting of 6 genes significantly associated with LUAD patient survival. Integration of these genes into the prognostic model demonstrated superior predictive accuracy for patient outcomes. Furthermore, we developed a user-friendly nomogram that effectively translates the model's prognostic information into a practical tool for clinical decision-making. Conclusion: This study elucidates the critical role of hypoxia and glycolysis related genes in LUAD and offers a novel prognostic model with promising clinical utility. This model has the potential to refine risk stratification and guide personalized therapeutic interventions, ultimately improving the prognosis of LUAD patients.

The Biological Behavior and Clinical Application Prospects of Deoxythymidine Kinase Gene in Tumors

Malignant tumors have become a significant risk factor for human mortality. Although there have been notable advancements in the treatment of tumors, patient prognosis remains poor. In recent years, gene diagnosis and gene therapy have brought great benefits to patients. Deoxythymidine kinase (DTYMK) is a highly promising biomarker, has been studied by many scholars, and plays a crucial role in the occurrence and development of various types of cancer. The abnormal expression of DTYMK is involved in tumor occurrence and development, and may also serve as a biomarker for tumor diagnosis, treatment, and prognosis. Several experimental studies have shown that DTYMK can impact tumor progression by regulating mechanisms such as cell cycle, tumor microenvironment, immune infiltration, and signaling pathways. Therefore, this article focuses on clarifying the mechanism of DTYMK in tumors and exploring its clinical application value to help patients prolong their survival cycle and improve their quality of life.