A LETM2-Regulated PI3K-Akt Signaling Axis Reveals a Prognostic and Therapeutic Target in Pancreatic Cancer

Circular RNA Profile in Atherosclerotic Disease: Regulation during ST-Elevated Myocardial Infarction

Circular (circ) RNAs are non-coding RNAs with important functions in the nervous system, cardiovascular system, and cancer. Their role in atherosclerosis and myocardial infarction (MI) remains poorly described. We aim to investigate the potential circRNAs in immune cells during atherogenesis and examine the most regulated during MI and the modulation by interleukin (IL)-6 receptor inhibition by tocilizumab. Wild-type (WT) and ApoE-/- mice were fed an atherogenic diet for 10 weeks, and the circRNA profile was analyzed by circRNA microarray. Whole blood from patients with ST-elevated MI (STEMI) and randomized to tocilizumab (n = 21) or placebo (n = 19) was collected at admission, 3-7 days, and at 6 months, in addition to samples from healthy controls (n = 13). Primers for human circRNA were designed, and circRNA levels were measured using RT-qPCR. mRNA regulation of predicted circRNA targets was investigated by RNA sequencing. The expression of 867 circRNAs differed between atherogenic and WT mice. In STEMI patients, circUBAC2 was significantly lower than in healthy controls. CircANKRD42 and circUBAC2 levels were inversely correlated with troponin T, and for circUBAC2, an inverse correlation was also seen with final infarct size at 6 months. The predicted mRNA targets for circUBAC2 and circANKRD42 were investigated and altered levels of transcripts involved in the regulation of inflammatory/immune cells, apoptosis, and mitochondrial function were found. Finally, tocilizumab induced an up-regulation of circANKRD42 and circUBAC2 3-7 days after percutaneous coronary intervention. CircRNA levels were dysregulated in STEMI, potentially influencing the immune system, apoptosis, and mitochondrial function.

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.

Integrated multi-omics analysis and machine learning developed a prognostic model based on mitochondrial function in a large multicenter cohort for Gastric Cancer

BACKGROUND

Gastric cancer (GC) is a common and aggressive type of cancer worldwide. Despite recent advancements in its treatment, the prognosis for patients with GC remains poor. Understanding the mechanisms of cell death in GC, particularly those related to mitochondrial function, is crucial for its development and progression. However, more research is needed to investigate the significance of the interaction between mitochondrial function and GC cell death.

METHODS

We employed a robust computational framework to investigate the role of mitochondria-associated proteins in the progression of GC in a cohort of 1,199 GC patients. Ten machine learning algorithms were utilized and combined into 101 unique combinations. Ultimately, we developed a Mitochondrial-related-Score (MitoScore) using the machine learning model that exhibited the best performance. We observed the upregulation of LEMT2 and further explored its function in tumor progression. Mitochondrial functions were assessed by measuring mitochondrial ATP, mitochondrial membrane potential, and levels of lactate, pyruvate, and glucose.

RESULTS

MitoScore showed significant correlations with GC immune and metabolic functions. The higher MitoScore subgroup exhibited enriched metabolic pathways and higher immune activity. Overexpression of LETM2 (leucine zipper and EF-hand containing transmembrane protein 2) significantly enhanced tumor proliferation and metastasis. LETM2 plays a role in promoting GC cell proliferation by activating the mTOR pathway, maintaining mitochondrial homeostasis, and promoting glycolysis.

CONCLUSION

The powerful machine learning framework highlights the significant potential of MitoScore in providing valuable insights and accurate assessments for individuals with GC. This study also enhances our understanding of LETM2 as an oncogene signature in GC. LETM2 may promote tumor progression by maintaining mitochondrial health and activating glycolysis, offering potential targets for diagnosis, treatment, and prognosis of GC.

Pancancer analysis uncovers an immunological role and prognostic value of the m6A reader IGF2BP2 in pancreatic cancer

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant gastrointestinal tumors worldwide with a dismal prognosis and high relapse rate. PDAC is considered a "cold cancer" for which immunotherapy is not effective. Therefore, to improve the prognosis for PDAC patients, it is urgent to explore the mechanism driving its insensitivity to immunotherapy.

MATERIALS AND METHODS

We conducted pancancer analyses to test IGF2BP family expression and survival in patients with different cancers via TCGA and GETx databases. Then, we determined the immunological role and prognostic value of IGF2BP2 in vitro, in vivo and in clinical specimens.

RESULTS

In the present study, we found that the m6A reader IGF2BP2 was the most clinically relevant member of the IGF2BP family for pancreatic cancer. High expression of IGF2BP2 was most associated with poor prognosis and an immunosuppressive microenvironment in PDAC. By IGF2BP2 knockdown, we found that tumor cell proliferation and invasive ability were significantly diminished. Importantly, we found that IGF2BP2 expression was closely associated with high expression of immunosuppressive molecules such as PD-L1. IGF2BP2 modulated downstream PD-L1 expression by regulating its mRNA stability via m6A methylation control, and we obtained the same verification in animal experiments and human tissue specimens.

CONCLUSION

Our study contributes to existing knowledge regarding the IGF2BP2-regulated PD-L1 signaling pathway as a potential prognostic and immune biomarker in pancreatic cancer.

Azeliragon inhibits PAK1 and enhances the therapeutic efficacy of AKT inhibitors in pancreatic cancer

Pancreatic cancer is a lethal malignancy for which there is currently no effective treatment strategy. We previously reported that p21-activated kinase 1 (PAK1) is aberrantly expressed in pancreatic cancer patients and that targeted inhibition of PAK1 significantly suppressed pancreatic cancer progression in vitro and in vivo. In this study, we identified the drug azeliragon as a novel inhibitor of PAK1. Cell experiments revealed that azeliragon abolished PAK1 activation and promoted apoptosis in pancreatic cancer cells. Azeliragon was also found to significantly inhibit tumor growth in a pancreatic cancer xenograft model; when combined with afuresertib, an oral pan-AKT kinase inhibitor, azeliragon exhibited a strong synergistic effect against pancreatic cancer cells. Interestingly, afuresertib enhanced the antitumor efficacy of azeliragon in a xenograft mouse model. Collectively, our findings revealed previously unreported aspects of the drug azeliragon, and identified a novel combination strategy for the treatment of pancreatic cancer patients.