Ultrasonographic characteristics of Hürthle cell neoplasms: prediction of malignancy

Purpose@#This study investigated the ultrasound (US) features of malignancy in patients with Hürthle cell neoplasms (HCNs) of the thyroid gland. @*Methods@#The present study included 139 HCNs that had undergone surgical excision at a single institution from 1996 to 2020 and had preoperative US images. The sonographic characteristics of HCNs were correlated with their pathological results. The US findings associated with malignancy were explored using logistic regression analysis, and the diagnostic performance and cutoff were assessed using receiver operating characteristic analysis. @*Results@#The most common US findings of HCNs were a solid content (76.3%), oval to round shape (100%), hypoechogenicity (70.5%), a smooth margin (95.0%), the halo sign (90.6%), and no calcifications (93.5%). HCNs were commonly smaller in pathologic measurements than in US measurements (smaller, same, and greater than US measurements in 60.4%, 21.6%, and 18.0% of HCNs, respectively; P3.35 cm might be used as a criterion to suggest malignancy. The size of HCNs often showed discrepancies between US and pathologic measurements.

Elucidating molecular mechanisms of acquired resistance to BRAF inhibitors in melanoma using a microfluidic device and deep sequencing

BRAF inhibitors (e.g., vemurafenib) are widely used to treat metastatic melanoma with the BRAF V600E mutation. The initial response is often dramatic, but treatment resistance leads to disease progression in the majority of cases. Although secondary mutations in the mitogen-activated protein kinase signaling pathway are known to be responsible for this phenomenon, the molecular mechanisms governing acquired resistance are not known in more than half of patients. Here we report a genome- and transcriptome-wide study investigating the molecular mechanisms of acquired resistance to BRAF inhibitors. A microfluidic chip with a concentration gradient of vemurafenib was utilized to rapidly obtain therapy-resistant clones from two melanoma cell lines with the BRAF V600E mutation (A375 and SK-MEL-28). Exome and transcriptome data were produced from 13 resistant clones and analyzed to identify secondary mutations and gene expression changes. Various mechanisms, including phenotype switching and metabolic reprogramming, have been determined to contribute to resistance development differently for each clone. The roles of microphthalmia-associated transcription factor, the master transcription factor in melanocyte differentiation/dedifferentiation, were highlighted in terms of phenotype switching. Our study provides an omics-based comprehensive overview of the molecular mechanisms governing acquired resistance to BRAF inhibitor therapy.

Elucidating molecular mechanisms of acquired resistance to BRAF inhibitors in melanoma using a microfluidic device and deep sequencing

BRAF inhibitors (e.g., vemurafenib) are widely used to treat metastatic melanoma with the BRAF V600E mutation. The initial response is often dramatic, but treatment resistance leads to disease progression in the majority of cases. Although secondary mutations in the mitogen-activated protein kinase signaling pathway are known to be responsible for this phenomenon, the molecular mechanisms governing acquired resistance are not known in more than half of patients. Here we report a genome- and transcriptome-wide study investigating the molecular mechanisms of acquired resistance to BRAF inhibitors. A microfluidic chip with a concentration gradient of vemurafenib was utilized to rapidly obtain therapy-resistant clones from two melanoma cell lines with the BRAF V600E mutation (A375 and SK-MEL-28). Exome and transcriptome data were produced from 13 resistant clones and analyzed to identify secondary mutations and gene expression changes. Various mechanisms, including phenotype switching and metabolic reprogramming, have been determined to contribute to resistance development differently for each clone. The roles of microphthalmia-associated transcription factor, the master transcription factor in melanocyte differentiation/dedifferentiation, were highlighted in terms of phenotype switching. Our study provides an omics-based comprehensive overview of the molecular mechanisms governing acquired resistance to BRAF inhibitor therapy.

Validity of patient-derived xenograft mouse models for lung cancer based on exome sequencing data

Patient-derived xenograft (PDX) mouse models are frequently used to test the drug efficacy in diverse types of cancer. They are known to recapitulate the patient characteristics faithfully, but a systematic survey with a large number of cases is yet missing in lung cancer. Here we report the comparison of genomic characters between mouse and patient tumor tissues in lung cancer based on exome sequencing data. We established PDX mouse models for 132 lung cancer patients and performed whole exome sequencing for trio samples of tumor-normal-xenograft tissues. Then we computed the somatic mutations and copy number variations, which were used to compare the PDX and patient tumor tissues. Genomic and histological conclusions for validity of PDX models agreed in most cases, but we observed eight (~7%) discordant cases. We further examined the changes in mutations and copy number alterations in PDX model production and passage processes, which highlighted the clonal evolution in PDX mouse models. Our study shows that the genomic characterization plays complementary roles to the histological examination in cancer studies utilizing PDX mouse models.

Bioinformatics services for analyzing massive genomic datasets

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.

Validity of patient-derived xenograft mouse models for lung cancer based on exome sequencing data

Patient-derived xenograft (PDX) mouse models are frequently used to test the drug efficacy in diverse types of cancer. They are known to recapitulate the patient characteristics faithfully, but a systematic survey with a large number of cases is yet missing in lung cancer. Here we report the comparison of genomic characters between mouse and patient tumor tissues in lung cancer based on exome sequencing data. We established PDX mouse models for 132 lung cancer patients and performed whole exome sequencing for trio samples of tumor-normal-xenograft tissues. Then we computed the somatic mutations and copy number variations, which were used to compare the PDX and patient tumor tissues. Genomic and histological conclusions for validity of PDX models agreed in most cases, but we observed eight (~7%) discordant cases. We further examined the changes in mutations and copy number alterations in PDX model production and passage processes, which highlighted the clonal evolution in PDX mouse models. Our study shows that the genomic characterization plays complementary roles to the histological examination in cancer studies utilizing PDX mouse models.

Bioinformatics services for analyzing massive genomic datasets

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.

FusionScan: accurate prediction of fusion genes from RNA-Seq data

Identification of fusion gene is of prominent importance in cancer research field because of their potential as carcinogenic drivers. RNA sequencing (RNA-Seq) data have been the most useful source for identification of fusion transcripts. Although a number of algorithms have been developed thus far, most programs produce too many false-positives, thus making experimental confirmation almost impossible. We still lack a reliable program that achieves high precision with reasonable recall rate. Here, we present FusionScan, a highly optimized tool for predicting fusion transcripts from RNA-Seq data. We specifically search for split reads composed of intact exons at the fusion boundaries. Using 269 known fusion cases as the reference, we have implemented various mapping and filtering strategies to remove false-positives without discarding genuine fusions. In the performance test using three cell line datasets with validated fusion cases (NCI-H660, K562, and MCF-7), FusionScan outperformed other existing programs by a considerable margin, achieving the precision and recall rates of 60% and 79%, respectively. Simulation test also demonstrated that FusionScan recovered most of true positives without producing an overwhelming number of false-positives regardless of sequencing depth and read length. The computation time was comparable to other leading tools. We also provide several curative means to help users investigate the details of fusion candidates easily. We believe that FusionScan would be a reliable, efficient and convenient program for detecting fusion transcripts that meet the requirements in the clinical and experimental community. FusionScan is freely available at http://fusionscan.ewha.ac.kr/.

Silencing of peroxiredoxin II by promoter methylation is necessary for the survival and migration of gastric cancer cells

Peroxiredoxin (Prx), a family of ubiquitous thiol peroxidases, functions as a redox signaling regulator that controls cellular Hâ‚‚Oâ‚‚ in mammalian cells and has recently received attention for being overexpressed in various cancer types. In this study, we show that Prx type II (PrxII) is rather silenced in gastric cancer cells. PrxII expression is severely downregulated in 9 out of the 28 gastric cancer cell lines. Strikingly, PrxII expression is completely lost in three cell lines, MKN28, MKN74 and SNU484. Loss of PrxII expression is due to DNA methyltransferase 1-dependent methylation at the promoter region of the PrxII gene. Restoration of PrxII expression using a retroviral system markedly reduces the colony-forming ability and migratory activity of both MKN28 and SNU484 cells by inhibiting Src kinase. Mechanistically, PrxII peroxidase activity is essential for regulating gastric cancer cell migration. Bioinformatics analysis from The Cancer Genome Atlas stomach cancer data (STAD) revealed significantly low PrxII expression in gastric cancer patients and a negative correlation between PrxII expression and methylation levels. More importantly, low PrxII expression also strongly correlates with poor survival in cancer patients. Thus our study suggests that PrxII may be the first thiol peroxidase that simultaneously regulates both survival and metastasis in gastric cancer cells with high clinical relevance.

Bioinformatics Resources of the Korean Bioinformation Center (KOBIC)

The Korean Bioinformation Center (KOBIC) is a national bioinformatics research center in Korea. We developed many bioinformatics algorithms and applications to facilitate the biological interpretation of OMICS data. Here we present an introduction to major bioinformatics resources of databases and tools developed at KOBIC. These resources are classified into three main fields: genome, proteome, and literature. In the genomic resources, we constructed several pipelines for next generation sequencing (NGS) data processing and developed analysis algorithms and web-based database servers including miRGator, ESTpass, and CleanEST. We also built integrated databases and servers for microarray expression data such as MDCDP. As for the proteome data, VnD database, WDAC, Localizome, and CHARMM_HM web servers are available for various purposes. We constructed IntoPub server and Patome database in the literature field. We continue constructing and maintaining the bioinformatics infrastructure and developing algorithms.

Prediction of Mammalian MicroRNA Targets : Comparative Genomics Approach with Longer 3' UTR Databases

MicroRNAs play an important role in regulating gene expression, but their target identification is a difficult task due to their short length and imperfect complementarity. Burge and coworkers developed a program called TargetScan that allowed imperfect complementarity and established a procedure favoring targets with multiple binding sites conserved in multiple organisms. We improved their algorithm in two major aspects - (i) using well-defined UTR (untranslated region) database, (ii) examining the extent of conservation inside the 3' UTR specifically. Average length in our UTR database, based on the ECgene annotation, is more than twice longer than the Ensembl. Then, TargetScan was used to identify putative binding sites. The extent of conservation varies significantly inside the 3' UTR. We used the "tight" tracks in the UCSC genome browser to select the conserved binding sites in multiple species. By combining the longer 3' UTR data, TargetScan, and tightly conserved blocks of genomic DNA, we identified 107 putative target genes with multiple binding sites conserved in multiple species, of which 85 putative targets are novel.

ChimerDB - Database of Chimeric Sequences in the GenBank

Fusion proteins resulting from chimeric sequences are excellent targets for therapeutic drug development. We developed a database of chimeric sequences by examining the genomic alignment of mRNA and EST sequences in the GenBank. We identified 688 chimeric mRNA and 20,998 chimeric EST sequences. Including EST sequences greatly expands the scope of chimeric sequences even though it inevitably accompanies many artifacts. Chimeric sequences are clustered according to the ECgene ID so that the user can easily find chimeric sequences related to a specific gene. Alignments of chimeric sequences are displayed as custom tracks in the UCSC genome browser. ChimerDB, available at http://genome.ewha.ac.kr/ECgene/ChimerDB/, should be a valuable resource for finding drug targets to treat cancers.

The Relationship between Mystic Experience and Dissociation / 신경정신의학

Mystic experience is highly evaluated so as to be called as core of experience in the religious world and also becomes the subject of concern among various social groups. Psychologists and psychiatrists are concerned about it, but because of its individuality and subjectivity, the scientific approach was difficult so that only the description of mystic experience has been researched so far. There is a current report saying that mystic experience is the one of the dissociative phenomenon. And there are a lot of reports saying that dissociation is related to childhood trauma experience and rises as much as psychopathological tendencies exist. Consequently, based on the reference that mystic experience is connected with dissociation, the study has been progressed to find out the level of dissociation, psychopathology and trauma experience for religious people who experienced mystic experience but excluding patients. Among them, it has been compared between group of non-mystic experience (n=35) and group of mystic experience (n=42). We used Dissociative Experience scale-Korean version (DES-K), Symptom Checklist-90-Revised (SCL-90-R), questionnaire about trauma. The result is that the group of mystic experience had a significantly higher tendency to have dissociation and trauma experience than group of non-mystic experience. However, the difference of psychopathology has not been found.