KRT13 is upregulated in pancreatic cancer stem-like cells and associated with radioresistance

Prognostic model identification of ribosome biogenesis-related genes in pancreatic cancer based on multiple machine learning analyses

BACKGROUND

Pancreatic cancer is a highly aggressive cancer characterized by low survival rate. Enhanced ribosome biogenesis may be associated with tumor drug resistance and malignant phenotypes, representing a potential therapeutic target in pancreatic cancer. Therefore, exploring the molecular mechanisms of ribosome biogenesis in pancreatic cancer may uncover new biomarkers and potential therapeutic targets, facilitating the development of personalized treatment strategies.

METHODS

Ribosome biogenesis-related gene signatures were acquired from TCGA and Gene Cards databases. Prognostic gene sets were screened using machine learning algorithms to construct a risk model, which was externally validated via GEO database. Single-cell RNA sequencing analysis (GSE155698 dataset) was performed to assess gene expression patterns and module scores.

RESULTS

Sixty ribosome biogenesis-related prognostic genes were identified in pancreatic cancer. Cox regression and machine learning algorithms selected nine pivotal biomarkers (ECT2; CKB; HMGA2; TPX2; ERBB3; SLC2A1; KRT13; PRSS3; CRABP2) with high diagnostic and prognostic specificity for PAAD. The machine learning-derived risk score correlated strongly with tumor proliferation pathways and immunosuppression, suggesting dual roles in tumor promotion and immunosuppressive microenvironment remodeling. Single-cell analysis highlighted predominant expression of CKB, SLC2A1, ERBB3, CRABP2, and PRSS3 in pancreatic ductal epithelial cells.

CONCLUSIONS

Our results shed light on the potential connections between ribosome biogenesis-related molecular characteristics and clinical features, the tumor microenvironment, and clinical drug responses. The research underscores the critical role of ribosome biogenesis in the progression and treatment resistance of pancreatic cancer, offering valuable new perspectives for prognostic evaluation and therapeutic response prediction in pancreatic cancer.

Senomorphic activity of a combination of niacinamide and hyaluronic acid: correlation with clinical improvement of skin aging

Intrinsic and extrinsic factors, including lifestyle and sun exposure, can contribute to cell senescence, which impairs skin homeostasis, that may in turn lead to skin aging. Senescent cells have a specific secretome, called the senescence-associated secretory phenotype (SASP) that includes MMPs, CXCLs and S100A8/9. Reducing the SASP with senotherapeutics is a promising strategy to reduce skin aging. Here we evaluated the effect of a formula containing niacinamide and hyaluronic acid, which are known to limit senescence and skin aging. We conducted three different studies. (1) Ex vivo explants treated with the formula had more collagen and glycosaminoglycan. (2) In a clinical trial with forty-four women, two months of treatment improved fine lines, wrinkles, luminosity, smoothness, homogeneity, and plumpness. (3) In a third study on thirty women, we treated one arm for two months and took skin biopsies to study gene expression. 101 mRNAs and 13 miRNAs were differentially expressed. We observed a likely senomorphic effect, as there was a decrease in many SASP genes including MMP12 and CXCL9 and a significant downregulation of autocrine signaling genes: S100A8 and S100A9. These pharmaco-clinical results are the first to demonstrate the senomorphic properties of an effective anti-aging formula in skin.

Fundamental insights and molecular interactions in pancreatic cancer: Pathways to therapeutic approaches

The gastrointestinal tract can be affected by a number of diseases that pancreatic cancer (PC) is a malignant manifestation of them. The prognosis of PC patients is unfavorable and because of their diagnosis at advanced stage, the treatment of this tumor is problematic. Owing to low survival rate, there is much interest towards understanding the molecular profile of PC in an attempt in developing more effective therapeutics. The conventional therapeutics for PC include surgery, chemotherapy and radiotherapy as well as emerging immunotherapy. However, PC is still incurable and more effort should be performed. The molecular landscape of PC is an underlying factor involved in increase in progression of tumor cells. In the presence review, the newest advances in understanding the molecular and biological events in PC are discussed. The dysregulation of molecular pathways including AMPK, MAPK, STAT3, Wnt/β-catenin and non-coding RNA transcripts has been suggested as a factor in development of tumorigenesis in PC. Moreover, cell death mechanisms such as apoptosis, autophagy, ferroptosis and necroptosis demonstrate abnormal levels. The EMT and glycolysis in PC cells enhance to ensure their metastasis and proliferation. Furthermore, such abnormal changes have been used to develop corresponding pharmacological and nanotechnological therapeutics for PC.

A bioinformatics analysis, pre-clinical and clinical conception of autophagy in pancreatic cancer: Complexity and simplicity in crosstalk

Pancreatic cancer (PC) is a serious gastrointestinal tract disease for which the 5-year survival rate is less than 10%, even in developed countries such as the USA. The genomic profile alterations and dysregulated biological mechanisms commonly occur in PC. Macroautophagy/autophagy is a cell death process that is maintained at a basal level in physiological conditions, whereas its level often changes during tumorigenesis. The function of autophagy in human cancers is dual and can be oncogenic and onco-suppressor. Autophagy is a potent controller of tumorigenesis in PC. The supportive autophagy in PC escalates the growth rate of PC cells and its suppression can mediate cell death. Autophagy also determines the metastasis of PC cells, and it can control the EMT in affecting migration. Moreover, starvation and hypoxia can stimulate glycolysis, and glycolysis induction can be mediated by autophagy in enhancing tumorigenesis in PC. Furthermore, protective autophagy stimulates drug resistance and gemcitabine resistance in PC cells, and its inhibition can enhance radiosensitivity. Autophagy can degrade MHC-I to mediate immune evasion and also regulates polarization of macrophages in the tumor microenvironment. Modulation of autophagy activity is provided by silibinin, ursolic acid, chrysin and huaier in the treatment of PC. Non-coding RNAs are also controllers of autophagy in PC and its inhibition can improve therapy response in patients. Moreover, mitophagy shows dysregulation in PC, which can enhance the proliferation of PC cells. Therefore, a bioinformatics analysis demonstrates the dysregulation of autophagy-related proteins and genes in PC as biomarkers.