DNA damage is well recognized as a critical factor in cancer development and progression. DNA lesions create an abnormal nucleotide or nucleotide fragment, causing a break in one or both chains of the DNA strand. When DNA damage occurs, the possibility of generated mutations increases. Genomic instability is one of the most important factors that lead to cancer development. DNA repair pathways perform the essential role of correcting the DNA lesions that occur from DNA damaging agents or carcinogens, thus maintaining genomic stability. Inefficient DNA repair is a critical driving force behind cancer establishment, progression and evolution. A thorough understanding of DNA repair mechanisms in cancer will allow for better therapeutic intervention. In this review we will discuss the relationship between DNA damage/repair mechanisms and cancer, and how we can target these pathways.

Background: Metabolic associated fatty liver disease (MAFLD) is a novel terminology introduced in 2020 to provide a more accurate description of fatty liver disease associated with metabolic dysfunction. It replaces the outdated term nonalcoholic fatty liver disease (NAFLD) and aims to improve diagnostic criteria and tailored treatment strategies for the disease. NAFLD, the most prevalent liver disease in western industrialized nations, has been steadily increasing in prevalence and is associated with serious complications such as cirrhosis and hepatocellular carcinoma. It is also linked to insulin resistance syndrome and cardiovascular diseases. However, current studies on NAFLD have limitations in meeting necessary histological endpoints.Objective: This literature review aims to consolidate recent knowledge and discoveries concerning MAFLD, integrating the diverse aspects of the disease. Specifically, it focuses on analyzing the diagnostic criteria for MAFLD, differentiating it from NAFLD and alcoholic fatty liver disease (AFLD), and exploring the epidemiology, clinical manifestations, pathogenesis, and management approaches associated with MAFLD. The review also explores the associations between MAFLD and other conditions. It discusses the heightened mortality risk associated with MAFLD and its link to chronic kidney disease (CKD), showing that MAFLD exhibits enhanced diagnostic accuracy for identifying patients with CKD compared to NAFLD. The association between MAFLD and incident/prevalent CKD is supported by cohort studies and meta-analyses.Conclusion: This literature review highlights the importance of MAFLD as a distinct terminology for fatty liver disease associated with metabolic dysfunction. The review provides insights into the diagnostic criteria, associations with CKD, and management approaches for MAFLD. Further research is needed to develop more accurate diagnostic tools for advanced fibrosis in MAFLD and to explore the underlying mechanisms linking MAFLD with other conditions. This review serves as a valuable resource for researchers and healthcare professionals seeking a comprehensive understanding of MAFLD.

Breast cancer is a leading cause of cancer-related deaths worldwide, predominantly caused by metastasis. It is generally accepted that the pattern of breast cancer metastasis is largely determined by the interaction between the chemokine receptors on cancer cells and the chemokines expressed at the sites of metastatic disease. Chemokine receptors belong to the G-protein-coupled receptors (GPCRs) family that appear to be implicated in inflammatory diseases, tumor growth and metastasis. One of its members, C-C Chemokine receptor 7 (CCR7), binds chemokines CCL19 and CCL21, which are important for tissue homeostasis, immune surveillance and tumorigenesis. These receptors have been shown to induce the pathobiology of breast cancer due to their ability to induce cellular proliferation and migration upon the binding of the cognate chemokine receptors. The underlying signaling pathways and exact cellular interactions within this biological system are not fully understood and need further insights. Thus, in this review, we summarize the essential roles of CCR7 and its receptors in breast cancer progression. Furthermore, we discuss the mechanisms of regulation that may lead to novel opportunities for therapeutic intervention. Despite the enormous advances in our knowledge of the nature of the chemokines in breast cancer metastasis, research about the involvement of CCR7 in cancer progression is still limited. Therefore, further studies are essential to illustrate the distinct roles of CCR7 in cancer progression and validate its potential as a preventive bio-factor for human breast cancer metastasis by targeting chemokine receptor genes.

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Cutaneous fatty acid–binding protein (C-FABP), a cancer promoter and metastasis inducer, is overexpressed in the majority of prostatic carcinomas. Investigation of molecular mechanisms involved in tumor-promoting activity of C-FABP has established that there is a fatty acid–initiated signaling pathway leading to malignant progression of prostatic cancer cells. Increased C-FABP expression plays an important role in this novel signaling pathway. Thus, when C-FABP expression is increased, excessive amounts of fatty acids are transported into the nucleus where they act as signaling molecules to stimulate their nuclear receptor peroxisome proliferator-activated receptor gamma (PPARγ). The activated PPARγ then modulates the expression of its downstream target regulatory genes, which eventually lead to enhanced tumor expansion and aggressiveness caused by an overgrowth of cells with reduced apoptosis and an increased angiogenesis.

Oral Squamous Cell Carcinoma (OSCC) is an aggressive tumor with a poor prognosis. Accurate and timely diagnosis is therefore essential for reducing the burden of advanced disease and improving outcomes. In this meta-analysis, we evaluated the accuracy of artificial intelligence (AI)-assisted technologies in detecting OSCC. We included studies that validated any diagnostic modality that used AI to detect OSCC. A search was performed in six databases: PubMed, Embase, Scopus, Cochrane Library, ProQuest, and Web of Science up to 15 Mar 2022. The Quality Assessment Tool for Diagnostic Accuracy Studies was used to evaluate the included studies' quality, while the Split Component Synthesis method was utilized to quantitatively synthesize the pooled diagnostic efficacy estimates. We considered 16 out of the 566 yielded studies, which included twelve different AI models with a total of 6606 samples. The summary sensitivity, summary specificity, positive and negative likelihood ratios as well as the pooled diagnostic odds ratio were 92.0 % (95 % confidence interval [CI] 86.7-95.4 %), 91.9 % (95 % CI 86.5-95.3 %), 11.4 (95 % CI 6.74-19.2), 0.087 (95 % CI 0.051-0.146) and 132 (95 % CI 62.6-277), respectively. Our findings support the capability of AI-assisted systems to detect OSCC with high accuracy, potentially aiding the histopathological examination in early diagnosis, yet more prospective studies are needed to justify their use in the real population.