Purpose: Patient-derived cells (PDCs) and patient-derived organoids (PDOs) are complementary preclinical models widely used in translational cancer research. However, their molecular and functional differences have not been systematically characterized. This study established and analyzed paired PDC and PDO models derived from the same gastric cancer ascites to delineate platform-dependent molecular and functional profiles. Materials and Methods: Malignant ascites or pleural fluid obtained from 6 patients with advanced gastric cancer were used to establish paired PDC and PDO models. All pairs underwent comprehensive multi-omics profiling, integrating genomic, transcriptomic, and proteomic data. Phenotypic characterization included morphological, histological, proliferative, and cell cycle analyses. Drug sensitivity assays were performed using 4 chemotherapeutic agents commonly used to treat gastric cancer. Results: The 6 paired PDC and PDO models exhibited distinct morphological characteristics.Whole-genome analyses demonstrated high concordance among primary tumors, PDCs, and PDOs, confirming tumor representation across platforms. Multi-omics profiling identified platform-dependent molecular signatures; PDOs were enriched for extracellular matrix remodeling and stemness, whereas PDCs displayed proliferation- and immune-related signatures. Clinically relevant biomarkers, including HER2 and MET alterations, were concordant with primary tumors. Notably, drug responses differed between platforms and patients, indicating platform-dependent and patient-specific chemosensitivity. Conclusions Paired PDC and PDO models derived from the same patients preserved core patient-specific tumor characteristics while exhibiting distinct molecular and functional profiles. These findings underscore the culture platform as a critical determinant of experimental outcomes and therapeutic responses. Therefore, careful selection of an appropriate preclinical model is essential to accurately address biological questions and optimize precision oncology strategies.

Purpose: This study aimed to perform a genome characterization of Streptococcus mitis KHUD 011, a strain isolated from the oral microbiome of a healthy Korean individual, and to compare its genomic features with other S. mitis strains. Materials and Methods: The strain was identified through 16S rRNA gene sequencing, and its genome was sequenced using the PacBio Sequel II platform. De novo assembly and annotation were performed, followed by comparative genomic analysis with three additional strains (S. mitis NCTC 12261, S022-V3-A4, and B6). Pan-genome and phylogenetic analyses were conducted to identify strain-specific genes and assess inter-strain genomic diversity. Results: The genome of S. mitis KHUD 011 consisted of 1,782 protein-coding genes, with a G+C content of 40.24%. Pan-genome analysis identified 1,263 core gene clusters (50.0%), 496 dispensable clusters (19.7%), and 763 strain-specific clusters (30.3%). KHUD 011 displayed 88 strain-specific genes, particularly associated with cell wall/membrane biogenesis, transcriptional regulation, and carbohydrate metabolism. Phylogenetic analysis placed KHUD 011 closely with NCTC 12261, forming a distinct cluster apart from other strains. Conclusion The genome characterization of S. mitis KHUD 011 underscores substantial inter-strain genomic diversity influenced by host interactions, ecological niches, and health status. The identified strain-specific genes, particularly those associated with cell wall/ membrane biogenesis, transcriptional regulation, and carbohydrate metabolism, suggest adaptations to the oral microbiome and its interaction with the host. These findings highlight the ecological versatility of S. mitis and the importance of exploring strains from diverse environments to better understand their role within the host and the broader microbiome.

Purpose: This study aimed to perform a genome characterization of Streptococcus mitis KHUD 011, a strain isolated from the oral microbiome of a healthy Korean individual, and to compare its genomic features with other S. mitis strains. Materials and Methods: The strain was identified through 16S rRNA gene sequencing, and its genome was sequenced using the PacBio Sequel II platform. De novo assembly and annotation were performed, followed by comparative genomic analysis with three additional strains (S. mitis NCTC 12261, S022-V3-A4, and B6). Pan-genome and phylogenetic analyses were conducted to identify strain-specific genes and assess inter-strain genomic diversity. Results: The genome of S. mitis KHUD 011 consisted of 1,782 protein-coding genes, with a G+C content of 40.24%. Pan-genome analysis identified 1,263 core gene clusters (50.0%), 496 dispensable clusters (19.7%), and 763 strain-specific clusters (30.3%). KHUD 011 displayed 88 strain-specific genes, particularly associated with cell wall/membrane biogenesis, transcriptional regulation, and carbohydrate metabolism. Phylogenetic analysis placed KHUD 011 closely with NCTC 12261, forming a distinct cluster apart from other strains. Conclusion The genome characterization of S. mitis KHUD 011 underscores substantial inter-strain genomic diversity influenced by host interactions, ecological niches, and health status. The identified strain-specific genes, particularly those associated with cell wall/ membrane biogenesis, transcriptional regulation, and carbohydrate metabolism, suggest adaptations to the oral microbiome and its interaction with the host. These findings highlight the ecological versatility of S. mitis and the importance of exploring strains from diverse environments to better understand their role within the host and the broader microbiome.

Purpose: This study aimed to perform a genome characterization of Streptococcus mitis KHUD 011, a strain isolated from the oral microbiome of a healthy Korean individual, and to compare its genomic features with other S. mitis strains. Materials and Methods: The strain was identified through 16S rRNA gene sequencing, and its genome was sequenced using the PacBio Sequel II platform. De novo assembly and annotation were performed, followed by comparative genomic analysis with three additional strains (S. mitis NCTC 12261, S022-V3-A4, and B6). Pan-genome and phylogenetic analyses were conducted to identify strain-specific genes and assess inter-strain genomic diversity. Results: The genome of S. mitis KHUD 011 consisted of 1,782 protein-coding genes, with a G+C content of 40.24%. Pan-genome analysis identified 1,263 core gene clusters (50.0%), 496 dispensable clusters (19.7%), and 763 strain-specific clusters (30.3%). KHUD 011 displayed 88 strain-specific genes, particularly associated with cell wall/membrane biogenesis, transcriptional regulation, and carbohydrate metabolism. Phylogenetic analysis placed KHUD 011 closely with NCTC 12261, forming a distinct cluster apart from other strains. Conclusion The genome characterization of S. mitis KHUD 011 underscores substantial inter-strain genomic diversity influenced by host interactions, ecological niches, and health status. The identified strain-specific genes, particularly those associated with cell wall/ membrane biogenesis, transcriptional regulation, and carbohydrate metabolism, suggest adaptations to the oral microbiome and its interaction with the host. These findings highlight the ecological versatility of S. mitis and the importance of exploring strains from diverse environments to better understand their role within the host and the broader microbiome.

Purpose: This study aimed to perform a genome characterization of Streptococcus mitis KHUD 011, a strain isolated from the oral microbiome of a healthy Korean individual, and to compare its genomic features with other S. mitis strains. Materials and Methods: The strain was identified through 16S rRNA gene sequencing, and its genome was sequenced using the PacBio Sequel II platform. De novo assembly and annotation were performed, followed by comparative genomic analysis with three additional strains (S. mitis NCTC 12261, S022-V3-A4, and B6). Pan-genome and phylogenetic analyses were conducted to identify strain-specific genes and assess inter-strain genomic diversity. Results: The genome of S. mitis KHUD 011 consisted of 1,782 protein-coding genes, with a G+C content of 40.24%. Pan-genome analysis identified 1,263 core gene clusters (50.0%), 496 dispensable clusters (19.7%), and 763 strain-specific clusters (30.3%). KHUD 011 displayed 88 strain-specific genes, particularly associated with cell wall/membrane biogenesis, transcriptional regulation, and carbohydrate metabolism. Phylogenetic analysis placed KHUD 011 closely with NCTC 12261, forming a distinct cluster apart from other strains. Conclusion The genome characterization of S. mitis KHUD 011 underscores substantial inter-strain genomic diversity influenced by host interactions, ecological niches, and health status. The identified strain-specific genes, particularly those associated with cell wall/ membrane biogenesis, transcriptional regulation, and carbohydrate metabolism, suggest adaptations to the oral microbiome and its interaction with the host. These findings highlight the ecological versatility of S. mitis and the importance of exploring strains from diverse environments to better understand their role within the host and the broader microbiome.

Immune status including the immune cells and cytokine profiles has been implicated in the development of endometriosis. In this study, we analyzed Th17 cells and IL-17A in peritoneal fluid (PF) and endometrial tissues of patients with (n=10) and without (n=26) endometriosis. Our study has shown increased Th17 cell population and IL-17A level in PF with endometriosis patients. To determine the roles of IL-17A and Th17 cells in the development of endometriosis, the effect of IL-17A, major cytokine of Th17, on endometrial cells isolated from endometriotic tissues was examined. Recombinant IL-17A promoted survival of endometrial cells accompanied by increased expression of anti-apoptotic genes, including Bcl-2 and MCL1, and the activation of ERK1/2 signaling. In addition, treatment of IL-17A to endometrial cells inhibited NK cell mediated cytotoxicity and induced HLA-G expression on endometrial cells. IL-17A also promoted migration of endometrial cells. Our data suggest that Th17 cells and IL-17A play critical roles in the development of endometriosis by promoting endometrial cell survival and conferring a resistance to NK cell cytotoxicity through the activation of ERK1/2 signaling. Targeting IL-17A has potential as a new strategy for the treatment of endometriosis.

Nilotinib is used for treating patients with imatinib-sensitive or -resistant chronic myeloid leukemia (CML); however, nilotinib-resistant cases have been observed in recent years. In addition, a considerable number of patients receiving nilotinib developed diabetes. Metformin is a front-line drug for the treatment of type 2 diabetes, and several studies have shown that diabetes patients treated with metformin have reduced incidence of cancer. This study aimed to define the effect of metformin on CML cells to determine whether metformin overcomes nilotinib resistance, and to identify novel targets for the treatment of nilotinib resistance. Methods: We observed the effects of metformin and nilotinib on K562 and KU812 human CML cell lines. Nilotinib-resistant CML cell lines were generated by exposing cells to gradually increasing doses of nilotinib. Then, we investigated the driving force that makes resistance to nilotinib and the effect of metformin on the driving force. Results: Sub-toxic doses of metformin enhanced nilotinib efficacy by reducing Bcl-xL expression, which induces apoptosis in CML cells. Next, we generated nilotinib-resistant K562 and KU812 cell lines that overexpressed the c-Jun N-terminal kinase (JNK) gene. JNK silencing by a JNK inhibitor restored sensitivity to nilotinib. Furthermore, metformin was effective in decreasing phosphorylated JNK levels, restoring nilotinib sensitivity. Combined treatment with nilotinib and metformin was more effective than combined treatment with nilotinib and a JNK inhibitor in terms of cell proliferation inhibition. Conclusions: This study suggested that combination therapy with metformin and nilotinib may have clinical benefits of enhancing antileukemia efficacy and overcoming resistance to nilotinib.

PURPOSE: Malnutrition and a loss of muscle mass are frequent in cancer patients and have a negative effect on clinical outcome. Nutrition risk screening aims to increase awareness and allow early recognition and treatment of cancer cachexia. Therefore, screenings should be brief, inexpensive, highly sensitive, and have good specificity. Simplified Nutritional Appetite Questionnaire (SNAQ) is a simple screening tool including four questions, and validated to predict weight loss within 6 months in community-dwelling adults and nursing home residents. Our study aimed to translate the SNAQ into Korean, and to assess the validity and reliability of the translated screening tool in advanced cancer patients. MATERIALS AND METHODS: The SNAQ was translated into Korean according to linguistic validation. The internal consistency of the SNAQ was evaluated by Cronbach's alpha coefficient. Test-retest reliability was evaluated using the intraclass correlation coefficient. Concurrent validity was evaluated by measuring the Pearson's correlation coefficient between the SNAQ and Mini-Nutritional Assessment (MNA) and Patient-Generated Subjective Global Assessment (PG-SGA). RESULTS: In the 194 patients included in full analysis set, cancer stage was predominantly metastatic (98.5%), the mean age was 60 years (range, 23 to 81 years), and the mean body mass index was 24 kg/m² (range, 15.6 to 39.6 kg/m²). According to MNA score ≤ 11, 57 patients (29.4%) were malnourished. The mean score (±standard deviation) of the Korean version of the SNAQ was 13.8±2.5 with a range of 6-19. Cronbach's alpha coefficient was 0.737, and intraclass correlation coefficient was 0.869. The SNAQ was moderately correlated with MNA (r=0.404, p < 0.001) and PG-SGA (r=–0.530, p < 0.001). A significant weight loss of > 5% of the original bodyweightwithin 6 months occurred in 46 of the 186 patients (24.7%). SNAQ score ≤ 14 predicted > 5% weight loss with a sensitivity of 56.5% and a specificity of 44.3%. CONCLUSION: The Korean version of the SNAQ had high validity and reliability. SNAQ is useful for the screening tool for advanced cancer patients. The SNAQ had a limitation to predict impending weight loss in advanced cancer patients.
Adult ; Appetite ; Body Mass Index ; Cachexia ; Humans ; Linguistics ; Longitudinal Studies ; Malnutrition ; Mass Screening ; Nursing Homes ; Nutrition Assessment ; Reproducibility of Results ; Sensitivity and Specificity ; Weight Loss

BACKGROUND/AIMS: Colorectal cancer is associated with different anatomical, biological, and clinical characteristics. We determined the impact of the primary tumor location in patients with metastatic colorectal cancer (mCRC). METHODS: Demographic data and clinical information were collected from 1,115 patients from the Republic of Korea, who presented with mCRC between January 2009 and December 2011, using web-based electronic case report forms. Associations between the primary tumor location and the patient's clinical characteristics were assessed, and factors inf luencing overall survival were analyzed using Cox proportional hazards regression models. RESULTS: Of the 1,115 patients recruited to the study, 244 (21.9%) had right colon cancer, 483 (43.3%) had left colon cancer, and 388 (34.8%) had rectal cancer. Liver and lung metastases occurred more frequently in patients with left colon and rectal cancer (p = 0.005 and p = 0.006, respectively), while peritoneal and ovarian metastases occurred more frequently in patients with right and left colon cancer (p < 0.001 and p = 0.031, respectively). The median overall survival of patients with tumors originating in the right colon was significantly shorter than that of patients whose tumors had originated in the left colon or rectum (13.7 months [95% confidence interval (CI), 12.0 to 15.5] vs. 18.0 months [95% CI, 16.3 to 19.7] or 19.9 months [95% CI, 18.5 to 21.3], respectively; p = 0.003). Tumor resection, the number of metastatic sites, and primary tumor location correlated with overall survival in the univariate and multivariate analyses. CONCLUSIONS: Primary tumor location influences the metastatic sites and prognosis of patients with mCRC.
Colon ; Colonic Neoplasms ; Colorectal Neoplasms* ; Humans ; Liver ; Lung ; Multivariate Analysis ; Neoplasm Metastasis ; Prognosis ; Rectal Neoplasms ; Rectum ; Republic of Korea

PURPOSE: Because data as a basis for the determination of proper age and modality for screening of colorectal neoplasms is lacking, we evaluated detection rates and anatomical distribution of colorectal neoplasms according to age in healthy individuals who underwent total colonoscopy for health checkup. METHODS: A total of 16,100 cases that had received the colonoscopic examination from January to December in 2014 were analyzed. The total number of individuals who received total colonoscopy were divided by the number of individuals harboring colorectal adenoma to calculate the detection rate of colorectal adenoma. Individuals ≤50 years old were classified as young-age group and aged >50 were old-age group. Differences in anatomical locations of colorectal neoplasms were analyzed in the 2 age groups by chi-square test. Risk factors for colorectal adenoma in each age group were analyzed using univariate and multivariate logistic regression analyses. RESULTS: Detection rates of colorectal adenoma were 13.7% in all cases and 12.8% for those in their 40′s. The main anatomical location of colorectal adenoma was proximal colon in both age groups (P < 0.001). Hyperplastic polyp was mainly distributed to the distal colon in both age groups (P < 0.001). Distal colon was the major site for colorectal cancer in the old-age group (P = 0.001). Proximal location of neoplasms was a risk factor for colorectal adenoma in both age groups with multivariate analysis. CONCLUSION: These data could be the bases for earlier initiation of screening for colorectal neoplasms with total colonoscopy to detect clinically significant colorectal polyps.
Adenoma ; Colon ; Colonoscopy ; Colorectal Neoplasms ; Humans ; Logistic Models ; Mass Screening ; Multivariate Analysis ; Polyps ; Risk Factors