Ryuji Hamamoto - Academia.edu (original) (raw)
Papers by Ryuji Hamamoto
Experimental & Molecular Medicine, Oct 1, 2023
High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecological malignancy. To date,... more High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecological malignancy. To date, the profiles of gene mutations and copy number alterations in HGSOC have been well characterized. However, the patterns of epigenetic alterations and transcription factor dysregulation in HGSOC have not yet been fully elucidated. In this study, we performed integrative omics analyses of a series of stepwise HGSOC model cells originating from human fallopian tube secretory epithelial cells (HFTSECs) to investigate early epigenetic alterations in HGSOC tumorigenesis. Assay for transposase-accessible chromatin using sequencing (ATAC-seq), chromatin immunoprecipitation sequencing (ChIP-seq), and RNA sequencing (RNA-seq) methods were used to analyze HGSOC samples. Additionally, protein expression changes in target genes were confirmed using normal HFTSECs, serous tubal intraepithelial carcinomas (STICs), and HGSOC tissues. Transcription factor motif analysis revealed that the DNA-binding activity of the AP-1 complex and GATA family proteins was dysregulated during early tumorigenesis. The protein expression levels of JUN and FOSL2 were increased, and those of GATA6 and DAB2 were decreased in STIC lesions, which were associated with epithelialmesenchymal transition (EMT) and proteasome downregulation. The genomic region around the FRA16D site, containing a cadherin cluster region, was epigenetically suppressed by oncogenic signaling. Proteasome inhibition caused the upregulation of chemokine genes, which may facilitate immune evasion during HGSOC tumorigenesis. Importantly, MEK inhibitor treatment reversed these oncogenic alterations, indicating its clinical effectiveness in a subgroup of patients with HGSOC. This result suggests that MEK inhibitor therapy may be an effective treatment option for chemotherapy-resistant HGSOC.
BioMed Research International, 2016
Research Square (Research Square), Mar 24, 2022
Lymph node metastasis (LNM) is a well-established prognostic factor in endometrial cancer (EC). W... more Lymph node metastasis (LNM) is a well-established prognostic factor in endometrial cancer (EC). We aimed to construct a model that predicts LNM and prognosis using preoperative factors such as myometrial invasion (MI), enlarged lymph nodes (LNs), histological grade determined by endometrial biopsy, and serum cancer antigen 125 (CA125) level using two independent cohorts consisting of 254 EC patients. The area under the receiver operating characteristic curve (AUC) of the constructed model was 0.80 regardless of the machine learning techniques. Enlarged LNs and higher serum CA125 levels were more signi cant in patients with low-grade EC (LGEC) and LNM than patients without LNM, whereas deep MI and higher CA125 levels were more signi cant in patients with high-grade EC (HGEC) and LNM than patients without LNM. The predictive performance of LNM in the HGEC group was higher than that in the LGEC group (AUC = 0.84 and 0.75, respectively). Patients in the group without postoperative pathological LNM and positive LNM prediction had signi cantly worse relapse-free and overall survival than patients with negative LNM prediction (log-rank test, P < 0.01). This study showed that preoperative clinicopathological factors can predict LNM with high precision and detect patients with poor prognosis. Furthermore, clinicopathological factors associated with LNM were different between HGEC and LGEC patients.
Gastroenterology, Apr 1, 1998
Cancer Medicine, Aug 3, 2023
BackgroundAlthough cervical cancer is often characterized as preventable, its incidence continues... more BackgroundAlthough cervical cancer is often characterized as preventable, its incidence continues to increase in low‐ and middle‐income countries, underscoring the need to develop novel therapeutics for this disease.This study assessed the distribution of fusion genes across cancer types and used an RNA‐based classification to divide cervical cancer patients with a poor prognosis into subgroups.Material and MethodsRNA sequencing of 116 patients with cervical cancer was conducted. Fusion genes were extracted using StarFusion program. To identify a high‐risk group for recurrence, 65 patients who received postoperative adjuvant therapy were subjected to non‐negative matrix factorization to identify differentially expressed genes between recurrent and nonrecurrent groups.ResultsWe identified three cases with FGFR3‐TACC3 and one with GOPC‐ROS1 fusion genes as potential targets. A search of publicly available data from cBioPortal (21,789 cases) and the Center for Cancer Genomics and Advanced Therapeutics (32,608 cases) showed that the FGFR3 fusion is present in 1.5% and 0.6% of patients with cervical cancer, respectively. The frequency of the FGFR3 fusion gene was higher in cervical cancer than in other cancers, regardless of ethnicity. Non‐negative matrix factorization identified that the patients were classified into four Basis groups. Pathway enrichment analysis identified more extracellular matrix kinetics dysregulation in Basis 3 and more immune system dysregulation in Basis 4 than in the good prognosis group. CIBERSORT analysis showed that the fraction of M1 macrophages was lower in the poor prognosis group than in the good prognosis group.ConclusionsThe distribution of FGFR fusion genes in patients with cervical cancer was determined by RNA‐based analysis and used to classify patients into clinically relevant subgroups.
Research Square (Research Square), Feb 5, 2021
Deep learning is promising for medical image analysis because it can automatically acquire meanin... more Deep learning is promising for medical image analysis because it can automatically acquire meaningful representations from raw data. However, a technical challenge lies in the difficulty of determining which types of internal representation are associated with a specific task, because feature vectors, which collectively constitute the feature maps, can vary dynamically according to individual inputs. Therefore, based on the magnetic resonance imaging (MRI) of gliomas, we propose a novel technique to extract a shareable set of feature vectors that encode various parts in tumor imaging phenotypes. Because the set of feature vectors is shared across a population, it can be used in other downstream tasks as if these feature vectors are imaging markers. Then, based on the feature vectors, a classifier is established using logistic regression to predict the glioma grade, and an accuracy of 90% is achieved. Besides, we develop an algorithm to visualize the image region encoded by each feature vector, and demonstrate that the classification model preferentially relies on feature vectors associated with the presence or absence of contrast enhancement in tumor regions. The proposed method provides a data-driven approach to enhance the understanding of physicians on the imaging appearance of gliomas.
Journal of Biochemistry, Nov 1, 1998
We studied spheroid (multicellular aggregate) formation by hepatocytes and the expression of live... more We studied spheroid (multicellular aggregate) formation by hepatocytes and the expression of liver-specific functions such as albumin secretion when hepatocytes were cultured with various extracellular matrices. Hepatocytes cultured on Primaria® and poly-D-lysine coated dishes, and in the presence of a polymer, Eudragit, formed spheroids, and they also exhibited higher liver-specific functions and poor growth compared to monolayer cultures. The results indicated that the cell morphological change and cell-cell interaction caused by the spheroid formation were key factors promoting the expression of the liver-specific functions. To elucidate the mechanism underlying the poor growth in spheroids, we examined the HGF signaling pathway. Phosphorylation and down-regulation of the HGF receptor (c-Met proto-oncogene product) were observed for the cells from both monolayer and spheroid cultures, but Ras activation was partly blocked in spheroids. Furthermore, we found that CDK inhibitors, p21 and p27, were highly expressed in spheroids. These results suggested that the reduced Ras signaling and high expression of the CDK inhibitors might cause the lower growth in spheroids. We then examined the relationship between liver-enriched transcription factors (C/EBPa and ft) and liver-specific functions. The results revealed that the high expression of C/EBPa was maintained during cultures when hepatocytes formed spheroids. Antisense oligonucleotides of C/EBPa repressed albumin secretion and the expression of p21, suggesting that the transcription factor, C/EBPa, may play a crucial role in the growth and differentiation of hepatocytes in spheroids.
Nature Communications, May 26, 2023
Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a sm... more Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P interaction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications. Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer and accounts for approximately 40% of lung cancer incidence worldwide 1-3. In studies drawn from East Asian (EA) ancestry, LUAD has been the predominant histologic subtype among females 2 and has replaced squamous cell carcinoma as the most common subtype in males 4,5. Well established risk factors, namely, tobacco smoking, certain environmental/occupational exposures and lifestyle factors, and family history, contribute to the risk of LUAD 6-8. In addition, multiple genome-wide association studies (GWAS) have identified at least 24 susceptibility loci for LUAD that achieved genome-wide significance, many drawn from studies in EA 9-15 and European (EUR) 16-23 populations, as well as multi-ancestry meta-analyses 24,25. Of these, 12 loci have been reported at genome-wide significance in GWAS of either never-smokers 9,11-13 or smokers and nonsmokers combined 10,14,15,24 in EA populations while another two loci were suggested in a multi-ancestry meta-analysis 24. We estimated that the known susceptibility variants account for only 13% of the estimated familial risk in EA populations. Accordingly, larger studies are needed to investigate the underlying architecture of susceptibility to LUAD in never-smokers and individuals with a history of smoking and in different ancestral populations. The importance of multi-ancestry analyses is further highlighted by reports of susceptibility loci showing association for LUAD in EA but not in EUR populations 13. In the current study, we conducted a two-stage GWAS metaanalysis in EA populations using unpublished and previously published data from four studies: the Female Lung Cancer Consortium in Asia (FLCCA), Nanjing Lung Cancer Study (NJLCS) 10,24 , National Cancer Center Research Institute (NCC) and Aichi Cancer Center (ACC), with 11,753 cases and 30,562 controls in the discovery set and 9905 cases and 120,114 controls in the replication set. A multi-ancestry metaanalysis of EA and EUR studies 16,22 (from the International Lung Cancer Consortium, ILCCO) was performed to identify variants shared by both populations. We also investigated the heterogeneity of effect sizes for susceptibility variants identified in EA and EUR populations 16,22 and
Briefings in Bioinformatics, Mar 23, 2023
The analysis of super-enhancers (SEs) has recently attracted attention in elucidating the molecul... more The analysis of super-enhancers (SEs) has recently attracted attention in elucidating the molecular mechanisms of cancer and other diseases. SEs are genomic structures that strongly induce gene expression and have been reported to contribute to the overexpression of oncogenes. Because the analysis of SEs and integrated analysis with other data are performed using large amounts of genome-wide data, artificial intelligence technology, with machine learning at its core, has recently begun to be utilized. In promoting precision medicine, it is important to consider information from SEs in addition to genomic data; therefore, machine learning technology is expected to be introduced appropriately in terms of building a robust analysis platform with a high generalization performance. In this review, we explain the history and principles of SE, and the results of SE analysis using state-of-the-art machine learning and integrated analysis with other data are presented to provide a comprehensive understanding of the current status of SE analysis in the field of medical biology. Additionally, we compared the accuracy between existing machine learning methods on the benchmark dataset and attempted to explore the kind of data preprocessing and integration work needed to make the existing algorithms work on the benchmark dataset. Furthermore, we discuss the issues and future directions of current SE analysis.
in Vivo, 2021
Background/Aim: We established a data-driven method for extracting spatial patterns of dose distr... more Background/Aim: We established a data-driven method for extracting spatial patterns of dose distribution associated with radiation injuries, based on patients with prostate cancer who underwent iodine-125 (I-125) seed implantation. Patients and Methods: Seventy-five patients underwent I-125 seed implantation for prostate cancer. We modeled the severity of lower urinary tract symptoms (LUTS) to be estimated using a linear model, which is formulated as an inner product between the dose distribution D and voxelwise radiosensitivity B inside the prostate. For the estimation, tensor regression based on a low-rank decomposition with generalized fused lasso penalty was applied. Results: The spatial distribution of B was visually assessed. Positive parameters appeared dominantly in the region close to the urethra and the prostate base. Conclusion: Our tensor regression-based model can predict intra-organ radiosensitivity in a data-driven manner, providing a compelling parameter distribution associated with the development of LUTS after I-125 seed implantation for prostate cancer.
Ultrasound in Obstetrics & Gynecology, Oct 1, 2020
Purpose: In 2008, the European Academy of Chiropractic decided to develop a competency-based mode... more Purpose: In 2008, the European Academy of Chiropractic decided to develop a competency-based model for graduate education in Europe. The CanMEDS (Canadian Medical Education Directives for Specialists) framework describes seven competency roles (fields) and key competencies identified as fundamental to all specialist doctors. It was not known how these fields are perceived by chiropractors in Europe. The purpose of this study was to compare perception scores of senior chiropractic as well as medical students with perception scores of licensed chiropractors and to analyze practitioners' remembered confidence in these competency fields. Methods: An anonymous 5-point Likert scale electronic questionnaire was sent to senior students of two chiropractic schools and licensed chiropractors of five European nations. Age and gender differences as well as differences in appraisal of the competencies in respect to importance and remembered confidence were analyzed. Results: Response rates were low to moderate. Agreement of importance of the seven competencies was not different between chiropractic and medical students as well as licensed chiropractors. Chiropractic students and chiropractors regarded all key competencies as important (averages ½4.0). The importance versus remembered confidence was consistently judged higher by about 1/2 point on the 5-point scale, significant for all competency fields (p < .001). Conclusion: The seven competency fields seem to be of the same importance for chiropractic senior students and licensed chiropractors and might be considered as a base for future graduate training in chiropractic. The survey should be replicated with additional samples and further information should be gathered to reflect reality.
arXiv (Cornell University), Aug 4, 2019
We compared the spheroid formation (multi-cellular aggregation) of hepatocytes and the expression... more We compared the spheroid formation (multi-cellular aggregation) of hepatocytes and the expression of liver specific functions such as albumin secretion when hepatocytes were cultured with various extracellular materials. We found that poly-D-lysine and Eudragit enhanced spheroid formation and hepatocytes in spheroids exhibited higher liver specific functions comparing to monolayer culture. The results indicated that cell-cell interaction caused by spheroid formation was a key factor to promote the expression of liver specific function. On the other hand, HGF response ability was declined when hepatocytes formed spheroids. We then examined that the relations between the expression of transcription factors and liver specific function during the spheroid formation. The expression of a CCAAT enhancer binding protein (C/EBP-α) increased and the high expression level was maintained when hepatocytes formed spheroids. The effects of cAMP and calcium ionophore on albumin secretion were also examined, and it was found that the increase of calcium ion concentration in the cells was important for the expression of the liver function.
Journal of Gastroenterology, Aug 16, 2022
Background Improved optical diagnostic technology is needed that can be used by also outside expe... more Background Improved optical diagnostic technology is needed that can be used by also outside expert centers. Hence, we developed an artificial intelligence (AI) system that automatically and robustly predicts the pathological diagnosis based on the revised Vienna Classification using standard colonoscopy images. Methods We prepared deep learning algorithms and colonoscopy images containing pathologically proven lesions (56,872 images, 6775 lesions). Four classifications were adopted: revised Vienna Classification category 1, 3, and 4/5 and normal images. The best algorithm-ResNet152in the independent internal validation (14,048 images, 1718 lesions) was used for external validation (255 images, 128 lesions) based on neoplastic and non-neoplastic classification. Diagnostic performance of endoscopists was compared using a computer-assisted interpreting test. Results In the internal validation, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for adenoma (category 3) of 84.6% (95% CI 83.
Briefings in Bioinformatics, Jul 5, 2022
The increase in the expectations of artificial intelligence (AI) technology has led to machine le... more The increase in the expectations of artificial intelligence (AI) technology has led to machine learning technology being actively used in the medical field. Non-negative matrix factorization (NMF) is a machine learning technique used for image analysis, speech recognition, and language processing; recently, it is being applied to medical research. Precision medicine, wherein important information is extracted from large-scale medical data to provide optimal medical care for every individual, is considered important in medical policies globally, and the application of machine learning techniques to this end is being handled in several ways. NMF is also introduced differently because of the characteristics of its algorithms. In this review, the importance of NMF in the field of
Molecular and Clinical Oncology, Dec 8, 2017
The aim of the present study was to investigate the prognostic value of the C-reactive protein-to... more The aim of the present study was to investigate the prognostic value of the C-reactive protein-to-albumin ratio (CAR) and compare it with other inflammation-based prognostic scores (Glasgow prognostic score, modified Glasgow prognostic score, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, prognostic nutritional index and prognostic index) in patients with esophageal squamous cell cancer (ESCC). A database of 116 patients with primary ESCC who underwent treatment at the Division of Surgical Oncology at Nagasaki University Hospital between January 2007 and August 2014 was retrospectively reviewed and the correlations between CAR and overall survival (OS) were investigated. Kaplan-Meier and Cox regression analyses were used to assess independent prognostic factors. The area under the curve (AUC) was used to compare the prognostic value of different scores. According to the receiver operator characteristics analysis, the recommended cutoff value for CAR was 0.042, with an AUC of 0.678 (sensitivity 31.1%, specificity 66.7%). Thus, patients were dichotomized into low (<0.042) and high (≥0.042) CAR groups. On multivariate analysis, CAR was found to be significantly associated with OS in patients with ESCC [hazard ratio (HR)=2.350; 95% confidence interval (CI): 1.189-4.650; P=0.014], as was tumor-node-metastasis stage (HR=3.059; 95% CI: 1.422-6.582; P=0.004). In addition, CAR had a higher AUC value (0.678) compared with several other systemic inflammation-based prognostic scores (P<0.001). This study suggested that CAR is a novel and promising inflammation-based prognostic score in patients with ESCC. Due to its simplicity, affordability and availability, CAR may be important for improving clinical decision-making and may contribute to more rational study design and analyses.
Experimental & Molecular Medicine, Oct 1, 2023
High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecological malignancy. To date,... more High-grade serous ovarian carcinoma (HGSOC) is the most lethal gynecological malignancy. To date, the profiles of gene mutations and copy number alterations in HGSOC have been well characterized. However, the patterns of epigenetic alterations and transcription factor dysregulation in HGSOC have not yet been fully elucidated. In this study, we performed integrative omics analyses of a series of stepwise HGSOC model cells originating from human fallopian tube secretory epithelial cells (HFTSECs) to investigate early epigenetic alterations in HGSOC tumorigenesis. Assay for transposase-accessible chromatin using sequencing (ATAC-seq), chromatin immunoprecipitation sequencing (ChIP-seq), and RNA sequencing (RNA-seq) methods were used to analyze HGSOC samples. Additionally, protein expression changes in target genes were confirmed using normal HFTSECs, serous tubal intraepithelial carcinomas (STICs), and HGSOC tissues. Transcription factor motif analysis revealed that the DNA-binding activity of the AP-1 complex and GATA family proteins was dysregulated during early tumorigenesis. The protein expression levels of JUN and FOSL2 were increased, and those of GATA6 and DAB2 were decreased in STIC lesions, which were associated with epithelialmesenchymal transition (EMT) and proteasome downregulation. The genomic region around the FRA16D site, containing a cadherin cluster region, was epigenetically suppressed by oncogenic signaling. Proteasome inhibition caused the upregulation of chemokine genes, which may facilitate immune evasion during HGSOC tumorigenesis. Importantly, MEK inhibitor treatment reversed these oncogenic alterations, indicating its clinical effectiveness in a subgroup of patients with HGSOC. This result suggests that MEK inhibitor therapy may be an effective treatment option for chemotherapy-resistant HGSOC.
BioMed Research International, 2016
Research Square (Research Square), Mar 24, 2022
Lymph node metastasis (LNM) is a well-established prognostic factor in endometrial cancer (EC). W... more Lymph node metastasis (LNM) is a well-established prognostic factor in endometrial cancer (EC). We aimed to construct a model that predicts LNM and prognosis using preoperative factors such as myometrial invasion (MI), enlarged lymph nodes (LNs), histological grade determined by endometrial biopsy, and serum cancer antigen 125 (CA125) level using two independent cohorts consisting of 254 EC patients. The area under the receiver operating characteristic curve (AUC) of the constructed model was 0.80 regardless of the machine learning techniques. Enlarged LNs and higher serum CA125 levels were more signi cant in patients with low-grade EC (LGEC) and LNM than patients without LNM, whereas deep MI and higher CA125 levels were more signi cant in patients with high-grade EC (HGEC) and LNM than patients without LNM. The predictive performance of LNM in the HGEC group was higher than that in the LGEC group (AUC = 0.84 and 0.75, respectively). Patients in the group without postoperative pathological LNM and positive LNM prediction had signi cantly worse relapse-free and overall survival than patients with negative LNM prediction (log-rank test, P < 0.01). This study showed that preoperative clinicopathological factors can predict LNM with high precision and detect patients with poor prognosis. Furthermore, clinicopathological factors associated with LNM were different between HGEC and LGEC patients.
Gastroenterology, Apr 1, 1998
Cancer Medicine, Aug 3, 2023
BackgroundAlthough cervical cancer is often characterized as preventable, its incidence continues... more BackgroundAlthough cervical cancer is often characterized as preventable, its incidence continues to increase in low‐ and middle‐income countries, underscoring the need to develop novel therapeutics for this disease.This study assessed the distribution of fusion genes across cancer types and used an RNA‐based classification to divide cervical cancer patients with a poor prognosis into subgroups.Material and MethodsRNA sequencing of 116 patients with cervical cancer was conducted. Fusion genes were extracted using StarFusion program. To identify a high‐risk group for recurrence, 65 patients who received postoperative adjuvant therapy were subjected to non‐negative matrix factorization to identify differentially expressed genes between recurrent and nonrecurrent groups.ResultsWe identified three cases with FGFR3‐TACC3 and one with GOPC‐ROS1 fusion genes as potential targets. A search of publicly available data from cBioPortal (21,789 cases) and the Center for Cancer Genomics and Advanced Therapeutics (32,608 cases) showed that the FGFR3 fusion is present in 1.5% and 0.6% of patients with cervical cancer, respectively. The frequency of the FGFR3 fusion gene was higher in cervical cancer than in other cancers, regardless of ethnicity. Non‐negative matrix factorization identified that the patients were classified into four Basis groups. Pathway enrichment analysis identified more extracellular matrix kinetics dysregulation in Basis 3 and more immune system dysregulation in Basis 4 than in the good prognosis group. CIBERSORT analysis showed that the fraction of M1 macrophages was lower in the poor prognosis group than in the good prognosis group.ConclusionsThe distribution of FGFR fusion genes in patients with cervical cancer was determined by RNA‐based analysis and used to classify patients into clinically relevant subgroups.
Research Square (Research Square), Feb 5, 2021
Deep learning is promising for medical image analysis because it can automatically acquire meanin... more Deep learning is promising for medical image analysis because it can automatically acquire meaningful representations from raw data. However, a technical challenge lies in the difficulty of determining which types of internal representation are associated with a specific task, because feature vectors, which collectively constitute the feature maps, can vary dynamically according to individual inputs. Therefore, based on the magnetic resonance imaging (MRI) of gliomas, we propose a novel technique to extract a shareable set of feature vectors that encode various parts in tumor imaging phenotypes. Because the set of feature vectors is shared across a population, it can be used in other downstream tasks as if these feature vectors are imaging markers. Then, based on the feature vectors, a classifier is established using logistic regression to predict the glioma grade, and an accuracy of 90% is achieved. Besides, we develop an algorithm to visualize the image region encoded by each feature vector, and demonstrate that the classification model preferentially relies on feature vectors associated with the presence or absence of contrast enhancement in tumor regions. The proposed method provides a data-driven approach to enhance the understanding of physicians on the imaging appearance of gliomas.
Journal of Biochemistry, Nov 1, 1998
We studied spheroid (multicellular aggregate) formation by hepatocytes and the expression of live... more We studied spheroid (multicellular aggregate) formation by hepatocytes and the expression of liver-specific functions such as albumin secretion when hepatocytes were cultured with various extracellular matrices. Hepatocytes cultured on Primaria® and poly-D-lysine coated dishes, and in the presence of a polymer, Eudragit, formed spheroids, and they also exhibited higher liver-specific functions and poor growth compared to monolayer cultures. The results indicated that the cell morphological change and cell-cell interaction caused by the spheroid formation were key factors promoting the expression of the liver-specific functions. To elucidate the mechanism underlying the poor growth in spheroids, we examined the HGF signaling pathway. Phosphorylation and down-regulation of the HGF receptor (c-Met proto-oncogene product) were observed for the cells from both monolayer and spheroid cultures, but Ras activation was partly blocked in spheroids. Furthermore, we found that CDK inhibitors, p21 and p27, were highly expressed in spheroids. These results suggested that the reduced Ras signaling and high expression of the CDK inhibitors might cause the lower growth in spheroids. We then examined the relationship between liver-enriched transcription factors (C/EBPa and ft) and liver-specific functions. The results revealed that the high expression of C/EBPa was maintained during cultures when hepatocytes formed spheroids. Antisense oligonucleotides of C/EBPa repressed albumin secretion and the expression of p21, suggesting that the transcription factor, C/EBPa, may play a crucial role in the growth and differentiation of hepatocytes in spheroids.
Nature Communications, May 26, 2023
Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a sm... more Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P interaction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications. Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer and accounts for approximately 40% of lung cancer incidence worldwide 1-3. In studies drawn from East Asian (EA) ancestry, LUAD has been the predominant histologic subtype among females 2 and has replaced squamous cell carcinoma as the most common subtype in males 4,5. Well established risk factors, namely, tobacco smoking, certain environmental/occupational exposures and lifestyle factors, and family history, contribute to the risk of LUAD 6-8. In addition, multiple genome-wide association studies (GWAS) have identified at least 24 susceptibility loci for LUAD that achieved genome-wide significance, many drawn from studies in EA 9-15 and European (EUR) 16-23 populations, as well as multi-ancestry meta-analyses 24,25. Of these, 12 loci have been reported at genome-wide significance in GWAS of either never-smokers 9,11-13 or smokers and nonsmokers combined 10,14,15,24 in EA populations while another two loci were suggested in a multi-ancestry meta-analysis 24. We estimated that the known susceptibility variants account for only 13% of the estimated familial risk in EA populations. Accordingly, larger studies are needed to investigate the underlying architecture of susceptibility to LUAD in never-smokers and individuals with a history of smoking and in different ancestral populations. The importance of multi-ancestry analyses is further highlighted by reports of susceptibility loci showing association for LUAD in EA but not in EUR populations 13. In the current study, we conducted a two-stage GWAS metaanalysis in EA populations using unpublished and previously published data from four studies: the Female Lung Cancer Consortium in Asia (FLCCA), Nanjing Lung Cancer Study (NJLCS) 10,24 , National Cancer Center Research Institute (NCC) and Aichi Cancer Center (ACC), with 11,753 cases and 30,562 controls in the discovery set and 9905 cases and 120,114 controls in the replication set. A multi-ancestry metaanalysis of EA and EUR studies 16,22 (from the International Lung Cancer Consortium, ILCCO) was performed to identify variants shared by both populations. We also investigated the heterogeneity of effect sizes for susceptibility variants identified in EA and EUR populations 16,22 and
Briefings in Bioinformatics, Mar 23, 2023
The analysis of super-enhancers (SEs) has recently attracted attention in elucidating the molecul... more The analysis of super-enhancers (SEs) has recently attracted attention in elucidating the molecular mechanisms of cancer and other diseases. SEs are genomic structures that strongly induce gene expression and have been reported to contribute to the overexpression of oncogenes. Because the analysis of SEs and integrated analysis with other data are performed using large amounts of genome-wide data, artificial intelligence technology, with machine learning at its core, has recently begun to be utilized. In promoting precision medicine, it is important to consider information from SEs in addition to genomic data; therefore, machine learning technology is expected to be introduced appropriately in terms of building a robust analysis platform with a high generalization performance. In this review, we explain the history and principles of SE, and the results of SE analysis using state-of-the-art machine learning and integrated analysis with other data are presented to provide a comprehensive understanding of the current status of SE analysis in the field of medical biology. Additionally, we compared the accuracy between existing machine learning methods on the benchmark dataset and attempted to explore the kind of data preprocessing and integration work needed to make the existing algorithms work on the benchmark dataset. Furthermore, we discuss the issues and future directions of current SE analysis.
in Vivo, 2021
Background/Aim: We established a data-driven method for extracting spatial patterns of dose distr... more Background/Aim: We established a data-driven method for extracting spatial patterns of dose distribution associated with radiation injuries, based on patients with prostate cancer who underwent iodine-125 (I-125) seed implantation. Patients and Methods: Seventy-five patients underwent I-125 seed implantation for prostate cancer. We modeled the severity of lower urinary tract symptoms (LUTS) to be estimated using a linear model, which is formulated as an inner product between the dose distribution D and voxelwise radiosensitivity B inside the prostate. For the estimation, tensor regression based on a low-rank decomposition with generalized fused lasso penalty was applied. Results: The spatial distribution of B was visually assessed. Positive parameters appeared dominantly in the region close to the urethra and the prostate base. Conclusion: Our tensor regression-based model can predict intra-organ radiosensitivity in a data-driven manner, providing a compelling parameter distribution associated with the development of LUTS after I-125 seed implantation for prostate cancer.
Ultrasound in Obstetrics & Gynecology, Oct 1, 2020
Purpose: In 2008, the European Academy of Chiropractic decided to develop a competency-based mode... more Purpose: In 2008, the European Academy of Chiropractic decided to develop a competency-based model for graduate education in Europe. The CanMEDS (Canadian Medical Education Directives for Specialists) framework describes seven competency roles (fields) and key competencies identified as fundamental to all specialist doctors. It was not known how these fields are perceived by chiropractors in Europe. The purpose of this study was to compare perception scores of senior chiropractic as well as medical students with perception scores of licensed chiropractors and to analyze practitioners' remembered confidence in these competency fields. Methods: An anonymous 5-point Likert scale electronic questionnaire was sent to senior students of two chiropractic schools and licensed chiropractors of five European nations. Age and gender differences as well as differences in appraisal of the competencies in respect to importance and remembered confidence were analyzed. Results: Response rates were low to moderate. Agreement of importance of the seven competencies was not different between chiropractic and medical students as well as licensed chiropractors. Chiropractic students and chiropractors regarded all key competencies as important (averages ½4.0). The importance versus remembered confidence was consistently judged higher by about 1/2 point on the 5-point scale, significant for all competency fields (p < .001). Conclusion: The seven competency fields seem to be of the same importance for chiropractic senior students and licensed chiropractors and might be considered as a base for future graduate training in chiropractic. The survey should be replicated with additional samples and further information should be gathered to reflect reality.
arXiv (Cornell University), Aug 4, 2019
We compared the spheroid formation (multi-cellular aggregation) of hepatocytes and the expression... more We compared the spheroid formation (multi-cellular aggregation) of hepatocytes and the expression of liver specific functions such as albumin secretion when hepatocytes were cultured with various extracellular materials. We found that poly-D-lysine and Eudragit enhanced spheroid formation and hepatocytes in spheroids exhibited higher liver specific functions comparing to monolayer culture. The results indicated that cell-cell interaction caused by spheroid formation was a key factor to promote the expression of liver specific function. On the other hand, HGF response ability was declined when hepatocytes formed spheroids. We then examined that the relations between the expression of transcription factors and liver specific function during the spheroid formation. The expression of a CCAAT enhancer binding protein (C/EBP-α) increased and the high expression level was maintained when hepatocytes formed spheroids. The effects of cAMP and calcium ionophore on albumin secretion were also examined, and it was found that the increase of calcium ion concentration in the cells was important for the expression of the liver function.
Journal of Gastroenterology, Aug 16, 2022
Background Improved optical diagnostic technology is needed that can be used by also outside expe... more Background Improved optical diagnostic technology is needed that can be used by also outside expert centers. Hence, we developed an artificial intelligence (AI) system that automatically and robustly predicts the pathological diagnosis based on the revised Vienna Classification using standard colonoscopy images. Methods We prepared deep learning algorithms and colonoscopy images containing pathologically proven lesions (56,872 images, 6775 lesions). Four classifications were adopted: revised Vienna Classification category 1, 3, and 4/5 and normal images. The best algorithm-ResNet152in the independent internal validation (14,048 images, 1718 lesions) was used for external validation (255 images, 128 lesions) based on neoplastic and non-neoplastic classification. Diagnostic performance of endoscopists was compared using a computer-assisted interpreting test. Results In the internal validation, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for adenoma (category 3) of 84.6% (95% CI 83.
Briefings in Bioinformatics, Jul 5, 2022
The increase in the expectations of artificial intelligence (AI) technology has led to machine le... more The increase in the expectations of artificial intelligence (AI) technology has led to machine learning technology being actively used in the medical field. Non-negative matrix factorization (NMF) is a machine learning technique used for image analysis, speech recognition, and language processing; recently, it is being applied to medical research. Precision medicine, wherein important information is extracted from large-scale medical data to provide optimal medical care for every individual, is considered important in medical policies globally, and the application of machine learning techniques to this end is being handled in several ways. NMF is also introduced differently because of the characteristics of its algorithms. In this review, the importance of NMF in the field of
Molecular and Clinical Oncology, Dec 8, 2017
The aim of the present study was to investigate the prognostic value of the C-reactive protein-to... more The aim of the present study was to investigate the prognostic value of the C-reactive protein-to-albumin ratio (CAR) and compare it with other inflammation-based prognostic scores (Glasgow prognostic score, modified Glasgow prognostic score, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, prognostic nutritional index and prognostic index) in patients with esophageal squamous cell cancer (ESCC). A database of 116 patients with primary ESCC who underwent treatment at the Division of Surgical Oncology at Nagasaki University Hospital between January 2007 and August 2014 was retrospectively reviewed and the correlations between CAR and overall survival (OS) were investigated. Kaplan-Meier and Cox regression analyses were used to assess independent prognostic factors. The area under the curve (AUC) was used to compare the prognostic value of different scores. According to the receiver operator characteristics analysis, the recommended cutoff value for CAR was 0.042, with an AUC of 0.678 (sensitivity 31.1%, specificity 66.7%). Thus, patients were dichotomized into low (<0.042) and high (≥0.042) CAR groups. On multivariate analysis, CAR was found to be significantly associated with OS in patients with ESCC [hazard ratio (HR)=2.350; 95% confidence interval (CI): 1.189-4.650; P=0.014], as was tumor-node-metastasis stage (HR=3.059; 95% CI: 1.422-6.582; P=0.004). In addition, CAR had a higher AUC value (0.678) compared with several other systemic inflammation-based prognostic scores (P<0.001). This study suggested that CAR is a novel and promising inflammation-based prognostic score in patients with ESCC. Due to its simplicity, affordability and availability, CAR may be important for improving clinical decision-making and may contribute to more rational study design and analyses.