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Simple Summary: Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, but effective biomarkers has yet been developed. Here, we identified ATP1A1 as prognostic marker and therapeutic target via integrated analysis of DNA methylome and transcriptome of TNBC. These data will provide new insight into not only developing specific biomarker for TNBC but also understanding TNBC pathogenesis. Dysregulated DNA methylation in cancer is critical in the transcription machinery associated with cancer progression. Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, but no treatment targeting TNBC biomarkers has yet been developed. To identify specific DNA methylation patterns in TNBC, methyl-binding domain protein 2 (MBD) sequencing data were compared in TNBC and the three other major breast cancer subtypes. Integrated analysis of DNA methylation and gene expression identified a gene set showing a correlation between DNA methylation and gene expression. ATPase Na+/K+-transporting subunit alpha 1 (ATP1A1) was found to be specifically hypomethylated in the coding sequence (CDS) region and to show increased expression in TNBC. The Cancer Genome Atlas (TCGA) database also showed that hypomethylation and high expression of ATP1A1 were strongly associated with poor survival in patients with TNBC. Furthermore, ATP1A1 knockdown significantly reduced the viability and tumor-sphere formation of TNBC cells. These results suggest that the hypomethylation and overexpression of ATP1A1 could be a prognostic marker in TNBC and that the manipulation of ATP1A1 expression could be a therapeutic target in this disease. [ABSTRACT FROM AUTHOR]

Ticks are vectors of disease‐causing pathogens and are found on domestic and wild animals; thus, they are also vectors of significant human diseases. For this reason, pre‐emptive measures to prevent tick‐borne diseases are necessary in the form of exploring their major habitats, population increase period, and factors affecting their population growth, all of which indicate the purpose of this study. In the study, a variation of Haemaphysalis longicornis, a major vector of fever‐causing conditions, was statistically analyzed to identify the spatial and climatic factors affecting the time‐dependent variations of its population. The survey occurred in different habitats (grassland, mixed forest, deciduous forest, and coniferous forest) in South Korea. In addition, we fitted a phenology model by using a probability function to find the peak occurrence time annually. As a result, the numbers of adults and nymphs were found to be related to temperature and relative humidity and their population peaked at the end of May in all habitats except deciduous forests. This study is expected to provide information on habitat types, times, and climate patterns that require attention to help control H. longicornis populations. [ABSTRACT FROM AUTHOR]

To investigate the impact on the ovarian reserve after minimally invasive ovarian cystectomy using two platforms, the Da Vinci robotic system (Xi and SP) and the laparoscopic system. Patients underwent laparoscopic or Da Vinci robotic (Xi or SP) ovarian cystectomy for benign ovarian cysts between January 1, 2018, and December 31, 2022 at Guro Hospital, Korea University Medical center. We measured the change of AMH values (%) = [(postAMH - preAMH)] × 100/preAMH. No significant differences in preoperative age, cyst size, estimated blood loss during surgery, hemoglobin drop, length of hospital stay, adhesion detachment rate and cyst rupture rate were observed. However, the operative time was significantly shorter in the laparoscopic group than that in the robotic group (67.78 ± 30.58 min vs. 105.17 ± 38.87 min, p < 0.001) The mean preAMH and postAMH were significantly higher with the Da Vinci robotic group than with the laparoscopic group (preAMH: 5.89 ± 4.81 ng/mL vs. 4.01 ± 3.59 ng/mL, p = 0.02, postAMH: 4.36 ± 3.31 ng/mL vs. 3.08 ± 2.60 ng/mL, p = 0.02). However, the mean ΔAMH was not significantly different between two groups. ΔAMH also did not demonstrate significant differences among the three groups; laparoscopic, Xi and SP robotic. Even in the patient groups with preAMH < 2 and diagnosed with endometriosis, the ΔAMH did not show significant differences between the laparoscopic and robotic groups. The Da Vinci robotic system is no inferior to conventional laparoscopic systems in preserving ovarian function., (© 2024. The Author(s).)

Background/aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression., Methods: Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD., Results: After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort., Conclusion: We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.