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Prostate cancer (PCa) is the most common malignant tumor of the male urological system and poses a severe threat to the survival of middle‑aged and elderly males worldwide. The development and progression of PCa are affected by a variety of biological processes, including proliferation, apoptosis, migration, invasion and the maintenance of membrane homeostasis of PCa cells. The present review summarizes recent research advances in lipid (fatty acid, cholesterol and phospholipid) metabolic pathways in PCa. In the first section, the metabolism of fatty acids is highlighted, from formation to catabolism and associated proteins. Subsequently, the role of cholesterol in the pathogenesis and evolution of PCa is described in detail. Finally, the different types of phospholipids and their association with PCa progression is also discussed. In addition to the impact of key proteins of lipid metabolism on PCa growth, metastasis and drug resistance, the present review also summarizes the clinical value of fatty acids, cholesterol and phospholipids, as diagnostic and prognostic indicators and therapeutic targets in PCa.

MicroRNAs (miRNAs/miRs) are a class of small non‑coding RNAs that maintain the precise balance of various physiological processes through regulating the function of target mRNAs. Dysregulation of miRNAs is closely associated with various types of human cancer. miR‑222‑3p is considered a canonical factor affecting the expression and signal transduction of multiple genes involved in tumor occurrence and progression. miR‑222‑3p in human biofluids, such as urine and plasma, may be a potential biomarker for the early diagnosis of tumors. In addition, miR‑222‑3p acts as a prognostic factor for the survival of patients with cancer. The present review first summarizes and discusses the role of miR‑222‑3p as a biomarker for diverse types of cancers, and then focuses on its essential roles in tumorigenesis, progression, metastasis and chemoresistance. Finally, the current understanding of the regulatory mechanisms of miR‑222‑3p at the molecular level are summarized. Overall, the current evidence highlights the crucial role of miR‑222‑3p in cancer diagnosis, prognosis and treatment.

Gastric cancer (GC) is one of the leading causes of malignancy‑associated mortality worldwide. However, the underlying molecular mechanisms of GC are unclear and the prognosis of GC is poor. Therefore, it is important and urgent to explore the underlying mechanisms and screen for novel diagnostic and prognostic biomarkers, as well as therapeutic targets. In the current study, scale‑free gene co‑expression networks were constructed using weighted gene co‑expression network analysis, the potential associations between gene sets and clinical features were investigated, and the hub genes were identified. The gene expression profiles of GSE38749 were downloaded from the Gene Expression Omnibus database. RNA‑seq and clinical data for GC from The Cancer Genome Atlas were utilized for verification. Furthermore, the expression of candidate biomarkers in gastric tissues was investigated. Survival analysis was performed using Kaplan‑Meier and log‑rank test. The predictive role of candidate biomarkers in GC was evaluated using a receiver operator characteristic (ROC) curve. Gene Ontology, gene set enrichment analysis and gene set variation analysis methods were used to interpret the function of candidate biomarkers in GC. A total of 29 modules were identified via the average linkage hierarchical clustering. A significant module consisting of 48 genes associated with clinical traits was found; three genes with high connectivity in the clinical significant module were identified as hub genes. Among them, SLC5A6 and microfibril‑associated protein 2 (MFAP2) were negatively associated with the overall survival, and their expression was elevated in GC compared with non‑tumor tissues. Additionally, ROC curves indicated that SLC5A6 and MFAP2 showed a good diagnostic power in discriminating cancerous from normal tissues. SLC5A6 and MFAP2 were identified as novel diagnostic and prognostic biomarkers in GC patients; both of these genes were first reported here in connection with GC and deserved further research.