Background: Women with Human Papilloma Virus (HPV) persistence are characterized by high levels of IL-10 at cervix. We have determined whether polymorphisms of IL-10 gene promoter might be associated with increased risk of squamous intraepithelial cervical lesions (SICL) and whether exist significative differences of IL-10 mRNA expression at cervix and systemic and serum IL-10 protein between SICL cases and non-Cervical Lesions (NCL).Methods: Peripheral blood samples from SICL (n = 204) and NCL (n = 166) were used to detect IL-10 promoter polymorphisms at loci -592A/C (rs1800872), -819C/T (rs1800871), -1082A/G (rs1800896), -1352A/G (rs1800893), by allelic discrimination and to evaluate serum IL-10 protein. Cervical epithelial scrapings from NCL and biopsies from SICLs were used for HPV-typing and to evaluate IL-10 mRNA expression level. The systemic and local IL-10 mRNA expression levels were measured by real time-PCR. Genotypic and allelic frequencies of the selected polymorphisms were analyzed by logistic regression, adjusting by age and HPV-genotype, to determine the association with SICL.Results: No significant differences were found between genotype frequencies at loci −819, -1082, and −1352. Individuals carrying at least one copy of risk allele A of polymorphism −592 had a two-fold increased risk of developing SICL [adjusted odds ratio (OR), 2.02 (95% CI, 1.26-3.25), p = 0.003], compared to NCL. The IL-10 mRNA expression and serum IL-10 protein, were significantly higher in SICL cases (p < 0.01), being higher in patients carrying the risk allele A.Conclusions: The −592 polymorphism is associated with increased risk of SICL and can serve as a marker of genetic susceptibility to SICL among Mexican women. According to IL-10 levels found in SICL, IL-10 can be relevant factor for viral persistence and progression disease.

Background/Objectives: Cervical cancer (CC) is the fourth most common cancer among women worldwide. This study explored the use of machine learning (ML) and deep learning (DL) in the prediction, diagnosis, and prognosis of CC. Methods: An electronic search was conducted in the PubMed, IEEE, Web of Science, and Scopus databases from January 2015 to April 2025 using the search terms ML, DL, and uterine cervical neoplasms. A total of 153 studies were selected in this review. A comprehensive summary of the available evidence was compiled. Results: We found that 54.9% of the studies addressed the application of ML and DL in CC for diagnostic purposes, followed by prognosis (22.9%) and an incipient focus on CC treatment (22.2%). The five countries where most ML and DL applications have been generated are China, the United States, India, Republic of Korea, and Japan. Of these studies, 48.4% proposed a DL-based approach, and the most frequent input data used to train the models on CC were images. Conclusions: Although there are results indicating a promising application of these artificial intelligence approaches in oncology clinical practice, further evidence of their validity and reproducibility is required for their use in early detection, prognosis, and therapeutic management of CC.

The AKNA gene is part of the 9q32 susceptibility locus for cervical cancer. A single-nucleotide polymorphism at codon 1119 of AKNA, yields a biologically relevant amino acid change (R1119Q) at the DNA binding AT-hook motif. Genotype frequencies in 97 allele pairs were: R/R = 0.597, R/Q = 0.278, Q/Q = 0.123. Q/Q homozygosity was present in 8.33% of healthy controls, 16.67% of patients with cervical intraepithelial neoplasia and 75% of cervical cancer patients. These differences are highly significant for the presence of Q/Q in cervical cancer (p = 0.01, odds ratio 3.66, 95% confidence interval 1.35–9.94). Therefore, AKNA appears to be an important genetic factor associated with the risk cervical cancer.

Human akna encodes an AT-hook transcription factor whose expression participates in various cellular processes. We conducted a scoping review on the literature regarding the functional role of AKNA according to the evidence found in human and in vivo and in vitro models, stringently following the “PRISMA-ScR” statement recommendations. Methods: We undertook an independent PubMed literature search using the following search terms, AKNA OR AKNA ADJ gene OR AKNA protein, human OR AKNA ADJ functions. Observational and experimental articles were considered. The selected studies were categorized using a pre-determined data extraction form. A narrative summary of the evidence was produced. Results: AKNA modulates the expression of CD40 and CD40L genes in immune system cells. It is a negative regulator of inflammatory processes as evidenced by knockout mouse models and observational studies for several autoimmune and inflammatory diseases. Furthermore, AKNA contributes to the de-regulation of the immune system in cancer, and it has been proposed as a susceptibility genetic factor and biomarker in CC, GC, and HNSCC. Finally, AKNA regulates neurogenesis by destabilizing the microtubules dynamics. Conclusion: Our results provide evidence for the role of AKNA in various cellular processes, including immune response, inflammation, development, cancer, autoimmunity, and neurogenesis.