• Journal of Biomedical Engineering Research
• /
• v.44 no.1
• /
• pp.11-18
• /
• 2023

Currently, studies to predict the risk of rectal cancer surgery select MRI image slices based on the clinical experience of surgeons. The purpose of this study is to semi-automatically select and classify 2D MRI image slides to predict the risk of rectal cancer surgery using biomarkers. The data used were retrospectively collected MRI imaging data of 50 patients who underwent laparoscopic surgery for rectal cancer at Gachon University Gil Medical Center. Expert-selected MRI image slices and non-selected slices were screened and radiomics was used to extract a total of 102 features. A total of 16 approaches were used, combining 4 classifiers and 4 feature selection methods. The combination of Random Forest and Ridge performed with a sensitivity of 0.83, a specificity of 0.88, an accuracy of 0.85, and an AUC of 0.89±0.09. Differences between expert-selected MRI image slices and non-selected slices were analyzed by extracting the top five significant features. Selected quantitative features help expedite decision making and improve efficiency in studies to predict risk of rectal cancer surgery.

• Journal of Korean geriatric psychiatry
• /
• v.16 no.1
• /
• pp.17-23
• /
• 2012

The diagnosis of Alzheimer's disease (AD) is still obscure even to specialists. To improve the diagnostic accuracy, to find at-risk people as early as possible, to predict the efficacy or adverse reactions of pharmacotherapy on an individual basis, to attain more reliable results of clinical trials by recruiting better defined participants, to prove the disease-modifying ability of new candidate drugs, to establish prognosis-based therapeutic plans, and to do more, is now increasing the need for biomarkers for AD. Among AD-related biochemical markers, cerebrospinal beta-amyloid and tau have been paid the most attention since they are materials directly interfacing the brain interstitium and can be obtained through the lumbar puncture. Level of beta-amyloid is reduced whereas tau is increased in cerebrospinal fluid of AD patients relative to cognitively normal elderly people. Remarkably, such information has been found to help predict AD conversion of mild cognitive impairment. Despite inconsistent findings from previous studies, plasma beta-amyloid is thought to be increased before the disease onset, but show decreasing change as the disease progress. Regarding other peripheral biochemical markers, omics tools are being widely used not only to find useful biomarkers but also to generate novel hypotheses for AD pathogenesis and to lead new personalized future medicine.

• The Journal of Churna Manual Medicine for Spine and Nerves
• /
• v.18 no.2
• /
• pp.1-8
• /
• 2023

Objectives This study aimed to propose biomarkers for diagnosing Chuna manual therapy (CMT) based on X-ray images in the thoracic and lumbar spines. Methods Through a literature review and expert consensus process, diagnostic biomarkers for CMT were selected based on the listing system in thoracic and lumbar radiograph anterior-posterior (AP) and lateral views. Results 1. Diagnostic biomarkers were derived from four points on the outer contour of the vertebral body in the thoracic and lumbar spine radiograph lateral view, enabling the diagnosis of flexion and extension malposition. 2. Additional diagnostic biomarkers were identified in the thoracic and lumbar radiographAP view, utilizing points on the outer contour of the vertebral body. These biomarkers facilitate the diagnosis of lateral bending. Moreover, biomarkers derived from the innermost point of the pedicle contour allow for the diagnosis of rotation malposition. 3. Furthermore, through the biomarkers proposed in this study, all malpositions of the thoracolumbar spines and complex Type I and II malpositions can be diagnosed in CMT. Conclusions The biomarkers reported in this study consist of minimal points to determine the position of the vertebral body, providing the advantage of simplicity while minimizing potential errors during the CMT diagnostic process. Further clinical research and the development of related programs should be pursued to expand the evidence for CMT.

• Genomics & Informatics
• /
• v.21 no.3
• /
• pp.38.1-38.8
• /
• 2023

Non-small cell lung cancer (NSCLC) is an important cause of cancer-associated deaths worldwide. Therefore, the exact molecular mechanisms of NSCLC are unidentified. The present investigation aims to identify the miRNAs with predictive value in NSCLC. The two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEmiRNA) and mRNAs (DEmRNA) were selected from the normalized data. Next, miRNA-mRNA interactions were determined. Then, co-expression network analysis was completed using the WGCNA package in R software. The co-expression network between DEmiRNAs and DEmRNAs was calculated to prioritize the miRNAs. Next, the enrichment analysis was performed for DEmiRNA and DEmRNA. Finally, the drug-gene interaction network was constructed by importing the gene list to dgidb database. A total of 3,033 differentially expressed genes and 58 DEmiRNA were recognized from two datasets. The co-expression network analysis was utilized to build a gene co- expression network. Next, four modules were selected based on the Z_summary score. In the next step, a bipartite miRNA-gene network was constructed and hub miRNAs (let-7a-2-3p, let-7d-5p, let-7b-5p, let-7a-5p, and let-7b-3p) were selected. Finally, a drug-gene network was constructed while SUNITINIB, MEDROXYPROGESTERONE ACETATE, DOFETILIDE, HALOPERIDOL, and CALCITRIOL drugs were recognized as a beneficial drug in NSCLC. The hub miRNAs and repurposed drugs may act a vital role in NSCLC progression and treatment, respectively; however, these results must validate in further clinical and experimental assessments.

• IMMUNE NETWORK
• /
• v.20 no.3
• /
• pp.27.1-27.11
• /
• 2020

Although various studies on predictive markers in the use of PD-1/PD-L1 inhibitors are in progress, only PD-L1 expression levels in tumor tissues are currently used. In the present study, we investigated whether baseline serum levels of IL-6 can predict the treatment response of patients with advanced non-small cell lung cancer (NSCLC) treated with PD-1/PD-L1 inhibitors. In our cohort of 125 NSCLC patients, the objective response rate (ORR) and disease control rate (DCR) were significantly higher in those with low IL-6 (<13.1 pg/ml) than those with high IL-6 (ORR 33.9% vs. 11.1%, p=0.003; DCR 80.6% vs. 34.9%, p<0.001). The median progression-free survival was 6.3 months (95% confidence interval [CI], 3.9-8.7) in the low IL-6 group, significantly longer than in the high IL-6 group (1.9 months, 95% CI, 1.6-2.2, p<0.001). The median overall survival in the low IL-6 group was significantly longer than in the high IL-6 group (not reached vs. 7.4 months, 95% CI, 4.8-10.0). Thus, baseline serum IL-6 levels could be a potential biomarker for predicting the efficacy and survival benefit of PD-1/PD-L1 inhibitors in NSCLC.

• Korean Journal of Radiology
• /
• v.20 no.8
• /
• pp.1266-1274
• /
• 2019

Objective: To determine whether radiologic extranodal extension (ENE) appearing on pretreatment CT and MRI could predict the prognosis in patients with human papillomavirus (HPV)-related oropharyngeal squamous cell carcinoma (OPSCC). Materials and Methods: The study population was obtained from a historical cohort diagnosed with HPV-related OPSCC. A total of 134 OPSCC patients who had a metastatic lymph node on pretreatment CT or MRI were included, and radiologic ENE was evaluated by two experienced head and neck radiologists. Kaplan-Meier and multivariate Cox regression analyses were performed to evaluate the impact of radiologic ENE on progression-free survival (PFS). The diagnostic performance of CT and MRI for the diagnosis of ENE was also evaluated in patients who underwent neck dissection. Results: Seventy patients (52.2%) showed radiologic ENE-positive findings. Although patients showing radiologic ENE had a worse 3-year PFS (83.7% vs. 95.3%, p = 0.023), the association between radiologic ENE and PFS was not statistically significant on multivariate analysis (p = 0.141; hazard ratio, 2.68; 95% confidence interval, 0.72-9.97). CT or MRI had a sensitivity of 62%, specificity of 77.8%, and accuracy of 71.9% for predicting pathologic ENE. Conclusion: Radiologic ENE on CT or MRI did not predict poor PFS in patients with HPV-related OPSCC, although there was a trend towards worse PFS. Further studies are warranted to determine whether radiologic ENE is a useful imaging biomarker to risk-stratify patients with HPV-related OPSCC.

• Journal of Korean Neurosurgical Society
• /
• v.67 no.3
• /
• pp.364-375
• /
• 2024

Objective : Kinesin family member C1 (KIFC1), a non-essential kinesin-like motor protein, has been found to serve a crucial role in supernumerary centrosome clustering and the progression of several human cancer types. However, the role of KIFC1 in glioma has been rarely reported. Thus, the present study aimed to investigate the role of KIFC1 in glioma progression. Methods : Online bioinformatics analysis was performed to determine the association between KIFC1 expression and clinical outcomes in glioma. Immunohistochemical staining was conducted to analyze the expression levels of KIFC1 in glioma and normal brain tissues. Furthermore, KIFC1 expression was knocked in the glioma cell lines, U251 and U87MG, and the functional roles of KIFC1 in cell proliferation, invasion and migration were analyzed using cell multiplication, wound healing and Transwell invasion assays, respectively. The autophagic flux and expression levels matrix metalloproteinase-2 (MMP2) were also determined using imaging flow cytometry, western blotting and a gelation zymography assay. Results : The results revealed that KIFC1 expression levels were significantly upregulated in glioma tissues compared with normal brain tissues, and the expression levels were positively associated with tumor grade. Patients with glioma with low KIFC1 expression levels had a more favorable prognosis compared with patients with high KIFC1 expression levels. In vitro, KIFC1 knockdown not only inhibited the proliferation, migration and invasion of glioma cells, but also increased the autophagic flux and downregulated the expression levels of MMP2. Conclusion : Upregulation of KIFC1 expression may promote glioma progression and KIFC1 may serve as a potential prognostic biomarker and possible therapeutic target for glioma.

• Journal of Microbiology and Biotechnology
• /
• v.34 no.5
• /
• pp.1164-1177
• /
• 2024

Esophageal squamous cell carcinoma (ESCC) is among the most common malignant tumors of the digestive tract, with the sixth highest fatality rate worldwide. The ESCC-related dataset, GSE20347, was downloaded from the Gene Expression Omnibus (GEO) database, and weighted gene co-expression network analysis was performed to identify genes that are highly correlated with ESCC. A total of 91 transcriptome expression profiles and their corresponding clinical information were obtained from The Cancer Genome Atlas database. A mitochondria-associated risk (MAR) model was constructed using the least absolute shrinkage and selection operator Cox regression analysis and validated using GSE161533. The tumor microenvironment and drug sensitivity were explored using the MAR model. Finally, in vitro experiments were performed to analyze the effects of hub genes on the proliferation and invasion abilities of ESCC cells. To confirm the predictive ability of the MAR model, we constructed a prognostic model and assessed its predictive accuracy. The MAR model revealed substantial differences in immune infiltration and tumor microenvironment characteristics between high- and low-risk populations and a substantial correlation between the risk scores and some common immunological checkpoints. AZD1332 and AZD7762 were more effective for patients in the low-risk group, whereas Entinostat, Nilotinib, Ruxolutinib, and Wnt.c59 were more effective for patients in the high-risk group. Knockdown of TYMS significantly inhibited the proliferation and invasive ability of ESCC cells in vitro. Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.

• Dementia and Neurocognitive Disorders
• /
• v.21 no.4
• /
• pp.138-146
• /
• 2022

Background and Purpose: Magnetic resonance imaging (MRI) helps with brain development analysis and disease diagnosis. Brain volumes measured from different ages using MRI provides useful information in clinical evaluation and research. Therefore, we trained machine learning models that predict the brain age gap of healthy subjects in the East Asian population using T1 brain MRI volume images. Methods: In total, 154 T1-weighted MRIs of healthy subjects (55-83 years of age) were collected from an East Asian community. The information of age, gender, and education level was collected for each participant. The MRIs of the participants were preprocessed using FreeSurfer(https://surfer.nmr.mgh.harvard.edu/) to collect the brain volume data. We trained the models using different supervised machine learning regression algorithms from the scikit-learn (https://scikit-learn.org/) library. Results: The trained models comprised 19 features that had been reduced from 55 brain volume labels. The algorithm BayesianRidge (BR) achieved a mean absolute error (MAE) and r squared (R²) of 3 and 0.3 years, respectively, in predicting the age of the new subjects compared to other regression methods. The results of feature importance analysis showed that the right pallidum, white matter hypointensities on T1-MRI scans, and left hippocampus comprise some of the essential features in predicting brain age. Conclusions: The MAE and R² accuracies of the BR model predicting brain age gap in the East Asian population showed that the model could reduce the dimensionality of neuroimaging data to provide a meaningful biomarker for individual brain aging.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.23
• /
• pp.10217-10223
• /
• 2015

Hyperactivated ${\alpha}2$-6-sialylation on N-glycans due to overexpression of the Golgi enzyme ${\beta}$-galactoside: ${\alpha}2$-6-sialyltransferase (ST6Gal-I) often correlates with cancer progression, metastasis, and poor prognosis. This study was aimed to determine the association between ST6Gal-I expression and the risk of recurrence and survival of patients with localized clear-cell renal cell carcinoma (ccRCC) following surgery. We retrospectively enrolled 391 patients (265 in training cohort and 126 in validation cohort) with localized ccRCC underwent nephrectomy at a single center. Tissue microarrays were constructed for immunostaining of ST6Gal-I. Prognostic value and clinical outcomes were evaluated. High ST6Gal-I expression was associated with Fuhrman grade (p<0.001 and p=0.016, respectively) and the University of California Los-Angeles Integrated Staging System (UISS) score (p=0.004 and p=0.017, respectively) in both cohorts. Patients with high ST6Gal-I expression had significantly worse overall survival (OS) (p<0.001 and p<0.001, respectively) and recurrence free survival (RFS) (p<0.001 and p=0.002, respectively) than those with low expression in both cohorts. On multivariate analysis, ST6Gal-I expression remained associated with OS and RFS even after adjusting for the UISS score. Stratified analysis suggested that the association is more pronounced among patients with low and intermediate-risk disease defined by the UISS score. High ST6Gal-I expression is a potential independent adverse predictor of survival and recurrence in ccRCC patients, and the prognostic value is most prominent in those with low and intermediate-risk disease defined by the UISS score.