Ranitidine as an adjuvant regulates macrophage polarization and activates CTLs through the PI3K-Akt2 signaling pathway

Interplay of CD36, autophagy, and lipid metabolism: insights into cancer progression

CD36, a scavenger receptor B2 that is dynamically distributed between cell membranes and organelle membranes, plays a crucial role in regulating lipid metabolism. Abnormal CD36 activity has been linked to a range of metabolic disorders, such as obesity, nonalcoholic fatty liver disease, insulin resistance and cardiovascular disease. CD36 undergoes various modifications, including palmitoylation, glycosylation, and ubiquitination, which greatly affect its binding affinity to various ligands, thereby triggering and influencing various biological effects. In the context of tumors, CD36 interacts with autophagy to jointly regulate tumorigenesis, mainly by influencing the tumor microenvironment. The central role of CD36 in cellular lipid homeostasis and recent molecular insights into CD36 in tumor development indicate the applicability of CD36 as a therapeutic target for cancer treatment. Here, we discuss the diverse posttranslational modifications of CD36 and their respective roles in lipid metabolism. Additionally, we delve into recent research findings on CD36 in tumors, outlining ongoing drug development efforts targeting CD36 and potential strategies for future development and highlighting the interplay between CD36 and autophagy in the context of cancer. Our aim is to provide a comprehensive understanding of the function of CD36 in both physiological and pathological processes, facilitating a more in-depth analysis of cancer progression and a better development and application of CD36-targeting drugs for tumor therapy in the near future.

H2 antihistamines: May be useful for combination therapies in cancer?

Cancer morbimortality is still a great concern despite advances in research and therapies. Histamine and its receptors' ligands can modulate different biological responses according to the cell type and the receptor subtype involved. Besides the wide variety of histamine functions in normal tissues, diverse roles in the acquisition of hallmarks of cancer such as sustained proliferative signaling, resistance to cell death, angiogenesis, metastasis, altered immunity and modified microenvironment have been described. This review summarizes the present knowledge of the various roles of histamine H2 receptor (H2R) ligands in neoplasias. A bioinformatic analysis of human tumors showed dissimilar results in the expression of the H2R gene according to tumor type when comparing malignant versus normal tissues. As well, the relationship between patients' survival parameters and H2R gene expression levels also varied, signaling important divergences in the role of H2R in neoplastic progression in different cancer types. Revised experimental evidence showed multiple effects of H2R antihistamines on several of the cited hallmarks of cancer. Interventional and retrospective clinical studies evaluated different H2R antihistamines in cancer patients with two main adjuvant uses: improving antitumor efficacy (which includes regulation of immune response) and preventing toxic adverse effects produced by chemo or radiotherapy. While there is a long path to go, research on H2R antihistamines may provide new opportunities for developing more refined combination therapeutic strategies for certain cancer types to improve patients' survival and health-related quality of life.

An immune-related exosome signature predicts the prognosis and immunotherapy response in ovarian cancer

BACKGROUND

Cancer-derived exosomes contribute significantly in intracellular communication, particularly during tumorigenesis. Here, we aimed to identify two immune-related ovarian cancer-derived exosomes (IOCEs) subgroups in ovarian cancer (OC) and establish a prognostic model for OC patients based on immune-related IOCEs.

METHODS

The Cancer Genome Atlas (TCGA) database was used to obtain RNA-seq data, as well as clinical and prognostic information. Consensus clustering analysis was performed to identify two IOCEs-associated subgroups. Kaplan-Meier analysis was used to compare the overall survival (OS) between IOCEs-high and IOCEs-low subtype. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to investigate the mechanisms and biological effects of differentially expressed genes (DEGs) between the two subtypes. Besides, an IOCE-related prognostic model of OC was constructed by Lasso regression analysis, and the signature was validated using GSE140082 as the validation set.

RESULTS

In total, we obtained 21 differentially expressed IOCEs in OC, and identified two IOCE-associated subgroups by consensus clustering. IOCE-low subgroup showed a favorable prognosis while IOCE-high subgroup had a higher level of immune cell infiltration and immune response. GSEA showed that pathways in cancer and immune response were mainly enriched in IOCE-high subgroup. Thus, IOCE-high subgroup may benefit more in immunotherapy treatment. In addition, we constructed a risk model based on nine IOCE-associated genes (CLDN4, AKT2, CSPG5, ALDOC, LTA4H, PSMA2, PSMA5, TCIRG1, ANO6).

CONCLUSION

We developed a novel stratification system for OV based on IOCE signature, which could be used to estimate the prognosis as well as immunotherapy for OC patient.