The Human Papillomavirus (HPV) E6 Oncoprotein Regulates CD40 Expression via the AT-Hook Transcription Factor AKNA

Potential of AKNA as a Predictive Biomarker for Ovarian Cancer and Its Relationship to Tumor Grading

BACKGROUND

Ovarian cancer exhibits a significant prevalence and incidence on a global scale. Low-grade or high-grade epithelial-type ovarian cancer can be classified by using the dualistic model. Inflammation has been associated with AKNA protein by cancer researchers. The potential of AKNA as a cancer biomarker is supported by its significance and association with ovarian carcinoma. Uninvestigated is this enormous potential.

AIM

This study examines the correlation between AKNA expression in low-grade and high-grade ovarian tumors and its utility as a predictive biomarker for ovarian cancer.

METHODS

This study examined a total of thirty-one samples, which were classified into three groups: cyst, low-grade, and high-grade ovarian carcinoma. The departmental archive was accessed for the following information: age, tumor size, nuclear grade, mitosis, ovary volume, implant tumor status, lymph vascular invasion status, lymph node metastasis, and tumor-infiltrating lymphocyte. The expression of AKNA was determined using IHC staining. The information was collected and analyzed via analysis of variance.

RESULTS

The AKNA H-score shows the mean difference between all three groups (P < 0.001). Cysts had the highest AKNA expression, followed by low-grade and high-grade ovarian carcinoma.

CONCLUSION

Higher-grade ovarian cancer expressed less AKNA compared to cysts or low-grade forms of the disease. This considerable difference suggests that AKNA might predict ovarian cancer tumor grade.

Binding to the Other Side: The AT-Hook DNA-Binding Domain Allows Nuclear Factors to Exploit the DNA Minor Groove

The "AT-hook" is a peculiar DNA-binding domain that interacts with DNA in the minor groove in correspondence to AT-rich sequences. This domain has been first described in the HMGA protein family of architectural factors and later in various transcription factors and chromatin proteins, often in association with major groove DNA-binding domains. In this review, using a literature search, we identified about one hundred AT-hook-containing proteins, mainly chromatin proteins and transcription factors. After considering the prototypes of AT-hook-containing proteins, the HMGA family, we review those that have been studied in more detail and that have been involved in various pathologies with a particular focus on cancer. This review shows that the AT-hook is a domain that gives proteins not only the ability to interact with DNA but also with RNA and proteins. This domain can have enzymatic activity and can influence the activity of the major groove DNA-binding domain and chromatin docking modules when present, and its activity can be modulated by post-translational modifications. Future research on the function of AT-hook-containing proteins will allow us to better decipher their function and contribution to the different pathologies and to eventually uncover their mutual influences.

Identification of biomarkers for hepatocellular carcinoma based on single cell sequencing and machine learning algorithms

Hepatocellular carcinoma (HCC) remains one of the most lethal cancers around the world. Precision oncology will be crucial for further improving the prognosis of HCC patients. Compared with traditional bulk RNA-seq, single-cell RNA sequencing (scRNA-seq) enables the transcriptomes of a great deal of individual cells assayed in an unbiased manner, showing the potential to deeply reveal tumor heterogeneity. In this study, based on the scRNA-seq results of primary neoplastic cells and paired normal liver cells from eight HCC patients, a new strategy of machine learning algorithms was applied to screen core biomarkers that distinguished HCC tumor tissues from the adjacent normal liver. Expression profiles of HCC cells and normal liver cells were first analyzed by maximum relevance minimum redundancy (mRMR) to get a top 50 signature gene feature. For further analysis, the incremental feature selection (IFS) method and leave-one-out cross validation (LOOCV) were conducted to build an optimal classification model and to extract 21 potentially essential biomarkers for HCC cells. Our results provided new insights into HCC pathogenesis that might be valuable for HCC diagnosis and therapy.

Functional Role of AKNA: A Scoping Review

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.

AKNA Is a Potential Prognostic Biomarker in Gastric Cancer and Function as a Tumor Suppressor by Modulating EMT-Related Pathways

The AT-hook transcription factor, AKNA, is a nuclear protein that affects a few physiological and pathological processes including cancer. Here, we investigated the role of AKNA in gastric cancer (GC). By using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot assays, AKNA was found deregulated in both GC cell lines and 32 paired GC tissues. Subsequently, Kaplan-Meier analysis and clinicopathological analysis were conducted using both 32 GC cases' data above and RNA-Seq data of AKNA in 354 GC patients and the corresponding clinical-pathological data obtained from The Cancer Genome Atlas (TCGA), and AKNA expression was found closely related to location, metastasis, and TNM staging of GC. Then, the potential molecular mechanisms of AKNA in GC were explored by gene set enrichment analysis (GSEA), qRT-PCR, and Western blot assays. AKNA was found to be a hub gene related to homotypic cell to cell adhesion, regulation of cell to cell adhesion, leukocyte cell to cell adhesion, and regulation of T cell proliferation in GC. GO analysis revealed that AKNA involved in the regulation of epithelial-mesenchymal transition (EMT)-related pathways including chemokine signaling pathway, cytokine to cytokine receptor interaction, cell adhesion molecules, and jak-stat signaling pathway in GC. To explore the regulation of AKNA expression, Targetscan and TargetMiner were used to predict the possible miRNA which targeted AKNA and found the expression of AKNA was negatively correlated to miR-762 which could be sponged by circTRNC18. In conclusion, AKNA could function as a tumor suppressor by modulating EMT-related pathways in GC. The expression of AKNA might be regulated by circTRNC18/miR-762 axis. AKNA could serve as a potential biomarker and an effective target for GC diagnosis and therapy.

AKNA Frameshift Variant in Three Dogs with Recurrent Inflammatory Pulmonary Disease

We investigated three related Rough Collies with recurrent inflammatory pulmonary disease. The clinical symptoms were similar to primary ciliary dyskinesia (PCD). However, the affected dogs did not carry any known pathogenic PCD variants. Pedigree analysis suggested a recessive mode of inheritance. Combined linkage and homozygosity mapping in three cases and seven non-affected family members delineated 19 critical intervals on 10 chromosomes comprising a total of 99 Mb. The genome of one affected dog was sequenced and compared to 601 control genomes. We detected only a single private homozygous protein-changing variant in the critical intervals. The detected variant was a 4 bp deletion, c.2717_2720delACAG, in the AKNA gene encoding the AT-hook transcription factor. It causes a frame-shift introducing a premature stop codon and truncates 37% of the open reading frame, p.(Asp906Alafs*173). We genotyped 88 Rough Collies consisting of family members and unrelated individuals. All three available cases were homozygous for the mutant allele and all 85 non-affected dogs were either homozygous wildtype (n = 67) or heterozygous (n = 18). AKNA modulates inflammatory immune responses. Akna-/- knockout mice die shortly after birth due to systemic autoimmune inflammatory processes including lung inflammation that is accompanied by enhanced leukocyte infiltration and alveolar destruction. The perfect genotype-phenotype association and the comparative functional data strongly suggest that the detected AKNA:c.2717_2720delACAG variant caused the observed severe airway inflammation in the investigated dogs. Our findings enable genetic testing, which can be used to avoid the unintentional breeding of affected puppies.