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Insights from public DNA methylation data derived from cancer or normal tissues from cancer patients or healthy people can be obtained by machine learning. The goal is to determine methylation patterns that could be useful for predicting the prognosis for cancer patients and correcting lifestyles for healthy people. DNA methylation data were obtained from the DNA of 446 healthy participants from the Korean Genome Epidemiology Study (KoGES) and from the DNA of normal tissues or from cancer tissues of 11 types of carcinomas from The Cancer Genome Atlas (TCGA) database. To correct for the batch effect, R’s ComBat function was used. Using the K-mean clustering (k = 3), the survival rates of the cancer patients and the incidence of chronic diseases were compared between the three clusters for TCGA and KoGES, respectively. Based on the public DNA methylation and clinical data of healthy participants and cancer patients, I present an analysis pipeline that integrates and clusters the methylation data from the two groups. As a result of clustering, CpG sites from gene or genomic regions, such as AFAP1, NINJ2, and HOOK2 genes, that correlated with survival rate and chronic disease are presented.

Nonalcoholic steatohepatitis (NASH) is considered as a progressive form of nonalcoholic fatty liver disease (NAFLD). To distinguish NASH from nonalcoholic fatty liver (NAFL), we evaluated the diagnostic value of circulating miRNAs. Small RNA sequencing was performed on 12 NAFL patients and 12 NASH patients, and the miRNA expression was compared. After selecting miRNAs for the diagnosis of NASH, we analyzed the diagnostic accuracy of each miRNA and the combination of miRNAs. External validation was performed using quantitative reverse transcription PCR. Among the 2,588 miRNAs, 26 miRNAs significantly increased in the NASH group than in the NAFL group. Among the 26 elevated miRNAs in the NASH group, 8 miRNAs were selected, and in silico analysis was performed. Only four miRNAs (miR-21-5p, miR-151a-3p, miR-192-5p, and miR-4449) showed significant area under the receiver operating characteristic curve (AUC) values for NASH diagnosis. The combination of the four miRNAs showed satisfactory diagnostic accuracy for NASH (AUC 0.875; 95% CI 0.676–0.973). External validation revealed similar diagnostic accuracy for NASH (AUC 0.874; 95% CI 0.724–0.960). NASH represents significantly distinct miRNA expression profile compared with NAFL. The combination of serum circulating miRNAs can be used as a novel biomarker for the NASH diagnosis in NAFLD.

Tuberculosis (TB) and non-tuberculous mycobacterial (NTM) infections, both caused by acid-fast bacteria, exhibit overlapping clinical presentations and radiological findings, making accurate and swift differentiation imperative for appropriate patient management. The ability to promptly distinguish between TB and NTM is pivotal, particularly in healthcare settings where TB patients require isolation. So, there is a pressing need to identify reliable biomarkers capable of delineating these conditions. In this study, we carefully analyzed a group of 108 patients, including 38 with TB, 29 with NTM, and 41 with other respiratory diseases. We used bacterial 16 S rRNA sequencing to examine the relative amounts of different microbial species in each patient group. We also used advanced methods like co-occurrence analysis, mutually exclusive analysis, and decision tree analysis to explore the complex patterns within the microbial communities. Our investigation revealed intriguing associations between microbial taxa and disease entities. In TB patients, prominent species were Enterococcus faecalis , Streptococcus mutans , and Snodgrassella alvi , while in NTM, prominent species were Cariobacterium hominis and Prevotella nigrescens . The absence of Mobiluncus curtisii indicated a higher probability of NTM, especially if Olsenella phocaeensis was also absent. This comprehensive analysis unveiled distinct microbial signatures that serve as discerning markers for discriminating TB, NTM infections, and other respiratory ailments. By elucidating microbial patterns unique to each condition, our findings offer valuable insights into the development of diagnostic strategies and therapeutic interventions tailored to specific respiratory infections.

Colorectal cancer (CRC) demonstrates favorable clinical outcomes when diagnosed at an early stage; however, the prognosis declines substantially following recurrence or distant metastasis. Increasing evidence indicates that cancer stem cells (CSCs) are pivotal contributors to tumor recurrence, metastatic dissemination, and therapeutic resistance. The present study aimed to identify CSC-associated biomarkers through spatial transcriptomic profiling of normal colonic mucosa, primary CRC, and liver metastatic tissues, and to evaluate their functional relevance in CRC progression. Spatial transcriptomic analysis revealed that CCN2 was preferentially enriched within CSC clusters of primary CRC tissues, whereas APOC2 was predominantly upregulated in liver-metastatic CSCs. Functional validation of CCN2 was performed by establishing CCN2-knockout HCT116 cell lines using the CRISPR-Cas9 system. Loss of CCN2 expression markedly attenuated cell proliferation, migration, invasion, and oxaliplatin resistance compared with control cells. Furthermore, immunohistochemical analysis of tissue microarrays demonstrated a significant positive correlation between CCN2 expression and CSC markers SOX2 and Nestin. Collectively, these findings suggest that CCN2 functions as a central regulator of stemness and malignant potential in CRC and may represent a promising therapeutic target to prevent recurrence and metastasis. Additional mechanistic studies are warranted to further elucidate the molecular pathways of CCN2 and to validate the role of APOC2 in liver-metastatic CRC stem cells.

This study aimed to establish clinically significant microRNA (miRNA) sets using extracellular vesicles (EVs) from bone marrow (BM) aspirates of patients with acute myelogenous leukemia (AML), and to identify the genes that interact with these EV-derived miRNAs in AML. BM aspirates were collected from 32 patients with AML at the time of AML diagnosis. EVs were isolated using size-exclusion chromatography. A total of 965 EV-derived miRNAs were identified in all the samples. We analyzed the expression levels of these EV-derived miRNAs of the favorable (n = 10) and non-favorable (n = 22) risk groups; we identified 32 differentially expressed EV-derived miRNAs in the non-favorable risk group. The correlation of these miRNAs with risk stratification and patient survival was analyzed using the information of patients with AML from The Cancer Genome Atlas (TCGA) database. Of the miRNAs with downregulated expression in the non-favorable risk group, hsa-miR-181b and hsa-miR-143 were correlated with non-favorable risk and short overall survival. Regarding the miRNAs with upregulated expression in the non-favorable risk group, hsa-miR-188 and hsa-miR-501 were correlated with non-favorable risk and could predict poor survival. Through EV-derived miRNAs-mRNA network analysis using TCGA database, we identified 21 mRNAs that could be potential poor prognosis biomarkers. Overall, our findings revealed that EV-derived miRNAs can serve as biomarkers for risk stratification and prognosis in AML. In addition, these EV-derived miRNA-based bioinformatic analyses could help efficiently identify mRNAs with biomarker potential, similar to the previous cell-based approach.

Tic disorders, characterized by involuntary movements or vocalizations, are influenced by neurological and psychological factors. Although an imbalance in neurotransmitter systems, genetic factors, and environmental influences play a significant role in the expression of tic disorders, the precise mechanisms through which autonomic changes influence tic production are not fully understood yet. This study investigates the relationship between tic disorders and heart rate variability (HRV), a physiological marker of autonomic nervous system function. The study sought to identify correlations among tic symptoms, HRV indices, and perceived quality of life. In a cohort of 69 participants (39 with tic disorders and 30 controls), we assessed tic severity using the Yale Global Tic Severity Scale (YGTSS) and quality of life through the KIDSCREEN-27 instrument. HRV parameters were measured to evaluate autonomic nervous system activity. Patients with tic disorders exhibited significant differences in HRV measures compared to the control group, indicating altered autonomic nervous system functioning. Our findings revealed notable differences in HRV, especially lower Low Frequency (LF) power in the patient group, suggesting altered autonomic responses potentially linked to chronic stress. Correlations between HRV metrics (notably SDNN and RMSSD) and various life quality dimensions were observed in the patient group. These results underscore a potential interplay between tic symptoms, autonomic balance, and adolescents' perceived quality of life. The study highlights the importance of considering autonomic nervous system functioning in tic disorders, particularly in the context of stress and perceived quality of life. Our findings, which provide insights into tic disorders' physiological and psychological aspects, have important implications for developing more holistic treatment approaches that consider tic patients' mental and physical well-being.

Background/Objectives: Colorectal cancer (CRC) remains a significant global health concern, with limited treatment options for metastatic stage 4 CRC. Fibroblast Growth Factor Receptor (FGFR) is a promising therapeutic target in CRC, while cannabidiol (CBD) has shown potential for inducing cell death and overcoming drug resistance. This study evaluates the efficacy of FGFR inhibitors and explores the synergistic effects of combining FGFR inhibitors with CBD in inducing apoptosis in CRC cells. Methods: Cannabidiol and FGFR inhibitors were applied, and protein expression was analyzed via Western blot. Cell viability was assessed using the WST-1 assay, while apoptosis was measured through flow cytometry using Annexin V-FITC/PI staining. CHOP-specific siRNA transfection was performed to study gene silencing effects, followed by RNA sequencing for differential expression and pathway analysis. Statistical significance was determined using ANOVA and t-tests, with p < 0.05. Results: FGFR expression patterns were confirmed in various cancer cell lines, with NCI-H716 showing high FGFR2 expression. Treatment with CBD (4 µM) and AZD4547 (10 nM) resulted in significant cell death, especially when used in combination, indicating the effectiveness of this combined therapy. Increased apoptosis in NCI-H716 cells was confirmed with the combined treatment. RNA sequencing and heatmap analysis suggested that ER stress might be related to the observed synergistic effect. The role of ER stress in the combination-induced apoptosis of NCI-H716 cells was further validated. Conclusions: The combination of FGFR inhibitors and cannabidiol exhibited a synergistic effect in inducing cell death in colorectal cancer cells, likely through the ER stress pathway. This study supports the potential of combined FGFR inhibitor and CBD therapy as a promising strategy for enhancing anticancer effects in CRC.

Background Advancements in the diagnosis, treatment, and surveillance of castration-resistant prostate cancer (CRPC) have progressed considerably, but a new biomarker that combines existing clinical and pathological data could be useful for a more precise diagnosis and prognosis. Some investigations have found that extracellular vesicle (EV)-derived miRNAs play crucial roles in various types of malignant tumors. The objective of this study was to explore EV miRNA and identify its biologic function as a biomarker for the diagnosis and prognosis of CRPC. Methods Plasma samples were collected from five healthy donors (Control, CT) and 17 CRPC patients, categorizing into two groups based on their endocrine treatment response: partial response (PR; n  = 10) and progressive disease (PD; n  = 7). Candidate extracellular vesicle (EV) miRNAs were identified using miRNA microarray and RT-qPCR. The biological functions of the selected miRNAs were evaluated using the MTT assay, wound healing assay, trans-well assay, and RNA sequencing in CRPC cells after transient miRNA expression. Results Microarray analysis revealed a significant downregulation of EV-miR-6880-5p in the PD samples compared to both CT and PR samples ( p  < 0.01). The expression of EV-miR-6880-5p in CRPC patients was decreased compared with that CT group ( p  = 0.0336) using RT-qPCR. In the PR group, EV-miR-6880-5p was increased at follow-up compared with the baseline ( p  = 0.2803), while in the PD group, it decreased at follow-up compared with the baseline samples ( p  = 0.4356). Furthermore, overexpression of miR-6880-5p hampered cell proliferation, migration, and invasion, downregulated pathways associated with tumor progression, and simultaneously upregulated pathways associated with cell growth and apoptosis in CRPC cells. Conclusions EV-miR-6880-5p shows promise as a prognostic biomarker in patients with CRPC. Further, prospective validations are necessary to evaluate the potential of these candidate miRNAs.

Various omics-based biomarkers related to the occurrence, progression, and prognosis of colorectal cancer (CRC) have been identified. In this study, we attempted to identify gut microbiome-based biomarkers and detect their association with host gene expression in the initiation and progression of CRC by integrating analysis of the gut mucosal metagenome, RNA sequencing, and sociomedical factors. We performed metagenome and RNA sequencing on colonic mucosa samples from 13 patients with advanced CRC (ACRC), 10 patients with high-risk adenoma (HRA), and 7 normal control (NC) individuals. All participants completed a questionnaire on sociomedical factors. The interaction and correlation between changes in the microbiome and gene expression were assessed using bioinformatic analysis. When comparing HRA and NC samples, which can be considered to represent the process of tumor initiation, 28 genes and five microbiome species were analyzed with correlation plots. When comparing ACRC and HRA samples, which can be considered to represent the progression of CRC, seven bacterial species and 21 genes were analyzed. When comparing ACRC and NC samples, 16 genes and five bacterial species were analyzed, and four correlation plots were generated. A network visualizing the relationship between bacterial and host gene expression in the initiation and progression of CRC indicated that Clostridium spiroforme and Tyzzerella nexilis were hub bacteria in the development and progression of CRC. Our study revealed the interactions of and correlation between the colonic mucosal microbiome and host gene expression to identify potential roles of the microbiome in the initiation and progression of CRC. Our results provide gut microbiome-based biomarkers that may be potential diagnostic markers and therapeutic targets in patients with CRC.