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Feature-region combination AUCs and benchmarking Sheet 1: Log2 fold-change, p-value, and q-value between ARPC and NEPC lines for central mean coverage in all queried (338) TFs (two tailed Mann-Whitney U test, Benjamini-Hochberg adjusted). Sheet 2: 100-fold cross-validation AUCs for all region and feature combinations subset by the ‘AR10’ overlapping features (see Methods). Sheet 3: 100-fold cross-validation AUCs for all region and feature combinations subset by the ‘Phenotype 47-defining’ overlapping features. Sheet 4: 100-fold cross-validation AUCs for all region and feature combinations (global). Sheet 5: Predictions scores, tumor fraction, depth of coverage, and subtype for benchmarking admixtures. Sheet 6: AUCs for unsupervised prediction of admixture subtypes grouped by tumor fraction and depth. Sheet 7: NEPC:ARPC ratio, tumor fraction, and ARPC and NEPC fraction predictions for mixed phenotype admixtures using Keraon (see Methods).

Supplementary Figures S1-S18 and Supplementary Table legends.

Advanced prostate cancers comprise distinct phenotypes, but tumor classification remains clinically challenging. Here, we harnessed circulating tumor DNA (ctDNA) to study tumor phenotypes by ascertaining nucleosome positioning patterns associated with transcription regulation. We sequenced plasma ctDNA whole genomes from patient-derived xenografts representing a spectrum of androgen receptor active (ARPC) and neuroendocrine (NEPC) prostate cancers. Nucleosome patterns associated with transcriptional activity were reflected in ctDNA at regions of genes, promoters, histone modifications, transcription factor binding, and accessible chromatin. We identified the activity of key phenotype-defining transcriptional regulators from ctDNA, including AR, ASCL1, HOXB13, HNF4G, and GATA2. To distinguish NEPC and ARPC in patient plasma samples, we developed prediction models that achieved accuracies of 97% for dominant phenotypes and 87% for mixed clinical phenotypes. Although phenotype classification is typically assessed by IHC or transcriptome profiling from tumor biopsies, we demonstrate that ctDNA provides comparable results with diagnostic advantages for precision oncology. Significance: This study provides insights into the dynamics of nucleosome positioning and gene regulation associated with cancer phenotypes that can be ascertained from ctDNA. New methods for classification in phenotype mixtures extend the utility of ctDNA beyond assessments of somatic DNA alterations with important implications for molecular classification and precision oncology. This article is highlighted in the In This Issue feature, p. 517

Basal cell carcinoma (BCC) of the prostate is a rare tumor. Compared with the more common acinar adenocarcinoma (AAC) of the prostate, BCCs show features of basal cell differentiation and are thought to be biologically distinct from AAC. The spectrum of molecular alterations of BCC has not been comprehensively described, and genomic studies are lacking. Herein, whole genome sequencing was performed on archival formalin-fixed, paraffin-embedded specimens of two cases with BCC. Prostatic BCCs were characterized by an overall low copy number and mutational burden. Recurrent copy number loss of chromosome 16 was observed. In addition, putative driver gene alterations in KIT, DENND3, PTPRU, MGA, and CYLD were identified. Mechanistically, depletion of the CYLD protein resulted in increased proliferation of prostatic basal cells in vitro. Collectively, these studies show that prostatic BCC displays distinct genomic alterations from AAC and highlight a potential role for loss of chromosome 16 in the pathogenesis of this rare tumor type.

Danshen (Salvia miltiorrhiza) is a traditional medicinal plant widely used in Asian countries for its pharmacological activities (e.g., amelioration of cardiovascular diseases). In this study, we investigated the anti-atherosclerotic activity of raw danshen root extract prepared using high hydrostatic pressure (HHP) at 550 MPa for 5 min and hot water extraction. This method was useful for elimination of bacteria from cultured danshen plants and for better extraction yield of active principles. The HHPtreated danshen extract (HDE) inhibited proliferation of human umbilical vein endothelial cells (HUVECs) and induced autophagy that was assessed by LC3 conversion and p62 degradation. HDE suppressed foam cell formation in oxLDL-induced RAW264.7 macrophages; lysosomal activity simultaneously increased, measured by acridine orange staining. HDE also reduced atherosclerotic plaque development in vivo in apolipoprotein E knock-out (ApoE-/-) mice fed a high cholesterol diet. Taken together, these results indicated that HDE exhibited anti-atherosclerotic activity via autophagy induction. [BMB Reports 2020; 53(12): 652-657].

Lymphoma is one of the most prevalent hematological cancers, accounting for 15-20 % of new cancer diagnoses in dogs. Therefore, this study aims to explore the important genes and pathways involved in canine lymphoma progression and understand the underlying molecular mechanisms using RNA sequencing. In this study, RNAs acquired from seven pairs of lymphoma and non-lymphoma blood samples were sequenced from different breeds of dogs. Sequencing reads were preprocessed, aligned with the reference genome, assembled and expressions were estimated through bioinformatics approaches. At a false discovery rate (FDR) 0.05 and fold change (FC) ≥ 1.5, a total of 625 differentially expressed genes (DEGs) were identified between lymphoma and non-lymphoma samples, including 347 up-regulated DEGs such as SLC38A11, SCN3A, ZIC5 etc. and 278 down-regulated DEGs such as LOC475937, CSMD1, KRT14 etc. GO enrichment analysis showed that these DEGs were highly enriched for molecular function of ATP binding and calcium ion binding, cellular process of focal adhesion, and biological process of immune response, and defense response to virus. Similarly, KEGG pathways analysis revealed 11 significantly enriched pathways such as ECM-receptor interaction, cell cycle, PI3K-Akt signaling pathway, ABC transporters etc. In the protein-protein interaction (PPI) network, CDK1 was found to be a top hub gene with highest degree of connectivity. Three modules selected from the PPI network showed that canine lymphoma was highly associated with cell cycle, ECM-receptor interaction, hypertrophic cardiomyopathy, dilated cardiomyopathy and RIG-I-like receptor signaling pathway. Overall, our findings highlighted new candidate therapeutic targets for further testing in canine lymphoma and facilitate the understanding of molecular mechanism of lymphoma's progression in dogs.

Color matching experiments were conducted for 11 pairs of displays, using 7 displays with different spectral characteristics. The color matching results between the LCD display and displays that have a narrowband spectrum, such as a laser projector, QLED, or OLED, demonstrated a significant color difference between two matched colors. The maximum difference was 18.52 ΔE00, which indicates the white color difference between the LCD and laser projector. There was also a clear observer variability of 2.27 ΔE00. The new cone fundamental function derived from 757 metameric pairs showed good performance compared to CIE standard observers reducing the display color mismatching significantly. This function also demonstrated a better performance when evaluating color matching in color chart image.

Direct identification of the proteins targeted by small molecules can provide clues for disease diagnosis, prevention, and drug development. Despite concentrated attempts, there are still technical limitations associated with the elucidation of direct interactors. Herein, we report a target-ID system called proximity-based compound-binding protein identification (PROCID), which combines our direct analysis workflow of proximity-labeled proteins (Spot-ID) with the HaloTag system to efficiently identify the dynamic proteomic landscape of drug-binding proteins. We successfully identified well-known dasatinib-binding proteins (ABL1, ABL2) and confirmed the unapproved dasatinib-binding kinases (e.g., BTK and CSK) in a live chronic myeloid leukemia cell line. PROCID also identified the DNA helicase protein SMARCA2 as a dasatinib-binding protein, and the ATPase domain was confirmed to be the binding site of dasatinib using a proximity ligation assay (PLA) and in cellulo biotinylation assay. PROCID thus provides a robust method to identify unknown drug-interacting proteins in live cells that expedites the mode of action of the drug.

As a companion and hunting dog, height, length, length to height ratio (LHR) and body-weight are the vital economic traits for Jindo dog. Human selection and targeted breeding have produced an extraordinary diversity in these traits. Therefore, the identification of causative markers, genes and pathways that help us to understand the genetic basis of this variability is essential for their selection purposes. Here, we performed a genome-wide association study (GWAS) combined with enrichment analysis on 757 dogs using 118,879 SNPs. The genomic heritability (h2) was 0.33 for height and 0.28 for weight trait in Jindo. At p-value &lt, 5 × 10−5, ten, six, thirteen and eleven SNPs on different chromosomes were significantly associated with height, length, LHR and body-weight traits, respectively. Based on our results, HHIP, LCORL and NCAPG for height, IGFI and FGFR3 for length, DLK1 and EFEMP1 for LHR and PTPN2, IGFI and RASAL2 for weight can be the potential candidate genes because of the significant SNPs located in their intronic or upstream regions. The gene-set enrichment analysis highlighted here nine and seven overlapping significant (p &lt, 0.05) gene ontology (GO) terms and pathways among traits. Interestingly, the highlighted pathways were related to hormone synthesis, secretion and signalling were generally involved in the metabolism, growth and development process. Our data provide an insight into the significant genes and pathways if verified further, which will have a significant effect on the breeding of the Jindo dog’s population.

Cell-free DNA (cfDNA) has the potential to inform tumor subtype classification and help guide clinical precision oncology. Here we develop Griffin, a framework for profiling nucleosome protection and accessibility from cfDNA to study the phenotype of tumors using as low as 0.1x coverage whole genome sequencing data. Griffin employs a GC correction procedure tailored to variable cfDNA fragment sizes, which generates a better representation of chromatin accessibility and improves the accuracy of cancer detection and tumor subtype classification. We demonstrate estrogen receptor subtyping from cfDNA in metastatic breast cancer. We predict estrogen receptor subtype in 139 patients with at least 5% detectable circulating tumor DNA with an area under the receive operator characteristic curve (AUC) of 0.89 and validate performance in independent cohorts (AUC = 0.96). In summary, Griffin is a framework for accurate tumor subtyping and can be generalizable to other cancer types for precision oncology applications.

The purpose of this study is to compare Soviet aid to North Korea (DPRK) in the 1950s and 1960s with Soviet aid to North Vietnam (DRV) during the same period. With the data collected from various sources, this study compares the aid and identifies the meaning of it from the perspectives of patron-client state relationships. Relatively, more aid was given to North Korea in the mid-1950s and more to North Vietnam in the late- 1960s and both countries were given similar aid in the late 1950s and early 1960s. This was due to the fluctuation in the strategic value of the two countries to the Soviet Union particularly by the confrontations with the US-supported respective southern states and the compliance behavior of the recipient countries.

This study examines the levels of trust and trustworthiness in northeast Asia, including the northeast, southeast, and central regions of China as well as South Korea. Trust and trustworthiness were measured using a simulated two-tier supply chain experiment. The retailer obtains a demand forecast and reports a value to the supplier; then the supplier determines the production based on the retailer’s report. The retailer has an incentive to inflate the report to guarantee sufficient production, whereas the supplier is motivated to deflate the retailer’s report to avoid overproduction. Two participants took part in the experiment together every time: one played as a retailer, and one played as a supplier. In total, 160 participants joined the experiment: 40 from Liaoning (northeast China), 40 from Zhejiang (southeast China), 40 from Hubei (central China), and 40 from South Korea. The results showed that trust in Hubei was relatively high among the investigated regions and country, whereas no difference was found in the level of trustworthiness. Additionally, the trust level was steady through the entire cooperation stages. In contrast, the trustworthiness level was lower in the early stage than in the late stage in Liaoning and Hubei but not in Zhejiang and South Korea. Besides, trust and trustworthiness in Hubei were higher than in Liaoning and South Korea in the middle cooperation stage, and trust in Hubei was higher than trust in Zhejiang in the late cooperation stage.

Background: Cell-free DNA (cfDNA) is released from dying cells, including tumor cells, and can be isolated from peripheral blood for studying cancer. In the bloodstream, cfDNA is protected from degradation by nucleosomes and other DNA binding proteins, leading to a coverage pattern that reflects the genomic organization in the cells-of-origin. Recent work has shown that it is possible to use this pattern to predict gene and transcription factor activity in cancer cells. This is known as nucleosome profiling. Breast cancer is among the most common causes of cancer, accounting for 23% of cancer diagnoses and 14% of cancer-related deaths among women worldwide. Targeted therapy is guided by tumor subtype, including the expression of three key receptors: ER, PR and HER2. Typically, subtyping involves a tumor biopsy and immunohistochemistry. However, in late-stage cancer, surgical biopsies for disease monitoring are difficult to obtain. Accurate subtype determination is critical to address hormone subtype switches during metastasis or treatment resistance. cfDNA offers an alternative, non-invasive method for identifying tumor subtypes through nucleosome profiling and, to the best of our knowledge, has not been shown for breast cancer. Methods: We developed a method, called Griffin, to examine nucleosome protection and genome accessibility by quantifying cfDNA fragments around accessible sites. Unlike previous methods, Griffin uses fragment length-based GC correction to remove GC biases that obscure signals. We used ATAC-seq data from TCGA to identify differentially accessible sites between ER positive and negative breast cancers. We developed a machine learning classifier that predicts ER subtype based upon the signals at these differentially accessible sites. Results: We then tested Griffin by examining differentially accessible sites in ultra-low pass sequencing (ULP-WGS, 0.1X) of several hundred cfDNA samples from patients with ER positive or negative breast cancer. We found that overall, differential sites were more accessible in the cfDNA of their respective subtypes. Additionally, we found that site accessibility within patient cfDNA samples was correlated to the cfDNA tumor fraction. We built and tested a prediction model with cross-validation, which revealed an accuracy of >80% for correctly classifying tumor status as ER positive or negative from this ULP-WGS dataset. Conclusion: This study has several novel aspects compared to prior nucleosome profiling approaches. First, we use fragment-based GC correction which reduces sample variability and allows us to observe previously obscured signals. Second, we demonstrated that signals are correlated to tumor fraction. And finally, we applied this method to cost-effective and scalable ULP-WGS of breast cancer and demonstrated the ability to predict breast cancer ER subtype in these samples. Citation Format: Anna-Lisa Doebley, Hanna Liao, Caroline Kikawa, Eden Cruikshank, Minjeong Ko, Anna Hoge, Joseph Hiatt, Navonil De Sarkar, Viktor A. Adalsteinsson, Paz Polak, David MacPherson, Peter S. Nelson, Heather A. Parsons, Daniel Stover, Gavin Ha. Griffin: A method for nucleosome profiling and breast cancer subtype prediction from ultra-low pass whole genome sequencing of cell-free DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB022.

Tumours evolve through time and space. Computational techniques have been developed to infer their evolutionary dynamics from DNA sequencing data. A growing number of studies have used these approaches to link molecular cancer evolution to clinical progression and response to therapy. There has not yet been a systematic evaluation of methods for reconstructing tumour subclonality, in part due to the underlying mathematical and biological complexity and to difficulties in creating gold-standards. To fill this gap, we systematically elucidated the key algorithmic problems in subclonal reconstruction and developed mathematically valid quantitative metrics for evaluating them. We then created approaches to simulate realistic tumour genomes, harbouring all known mutation types and processes both clonally and subclonally. We then simulated 580 tumour genomes for reconstruction, varying tumour read-depth and benchmarking somatic variant detection and subclonal reconstruction strategies. The inference of tumour phylogenies is rapidly becoming standard practice in cancer genome analysis; this study creates a baseline for its evaluation.

SUMMARY Many traits are complex, depending non-additively on variant combinations. Even in model systems, such as the yeast S. cerevisiae, carrying out the high-order variant-combination testing needed to dissect complex traits remains a daunting challenge. Here, we describe “X-gene” genetic analysis (XGA), a strategy for engineering and profiling highly combinatorial gene perturbations. We demonstrate XGA on yeast ABC transporters by engineering 5,353 strains, each deleted for a random subset of 16 transporters, and profiling each strain’s resistance to 16 compounds. XGA yielded 85,648 genotype-to-resistance observations, revealing high-order genetic interactions for 13 of the 16 transporters studied. Neural networks yielded intuitive functional models and guided exploration of fluconazole resistance, which was influenced non-additively by five genes. Together, our results showed that highly combinatorial genetic perturbation can functionally dissect complex traits, supporting pursuit of analogous strategies in human cells and other model systems., Graphical Abstract, In Brief Celaj et al. introduce “X-gene” genetic analysis (XGA), a strategy for modeling complex systems by engineering and profiling highly combinatorial genetic perturbations. They apply XGA to 16 yeast ABC transporters, revealing many high-order genetic interactions. Neural network models yielded intuitive functional models and illuminated an ABC transporter influence network, supporting application of XGA to other organisms and processes.

High‐throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome‐scale interaction mapping. Here, we report Barcode Fusion Genetics‐Yeast Two‐Hybrid (BFG‐Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG‐Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein‐pair barcodes that can be quantified via next‐generation sequencing. We applied BFG‐Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG‐Y2H increases the efficiency of protein matrix screening, with quality that is on par with state‐of‐the‐art Y2H methods.

Biogenesis and molecular function are two key subjects in the field of microRNA (miRNA) research. Deep sequencing has become the principal technique in cataloging of miRNA repertoire and generating expression profiles in an unbiased manner. Here, we describe the miRGator v3.0 update (http://mirgator.kobic.re.kr) that compiled the deep sequencing miRNA data available in public and implemented several novel tools to facilitate exploration of massive data. The miR-seq browser supports users to examine short read alignment with the secondary structure and read count information available in concurrent windows. Features such as sequence editing, sorting, ordering, import and export of user data would be of great utility for studying iso-miRs, miRNA editing and modifications. miRNA–target relation is essential for understanding miRNA function. Coexpression analysis of miRNA and target mRNAs, based on miRNA-seq and RNA-seq data from the same sample, is visualized in the heat-map and network views where users can investigate the inverse correlation of gene expression and target relations, compiled from various databases of predicted and validated targets. By keeping datasets and analytic tools up-to-date, miRGator should continue to serve as an integrated resource for biogenesis and functional investigation of miRNAs.

Chromosome translocations and gene fusions are frequent events in the human genome and have been found to cause diverse types of tumor. ChimerDB is a knowledgebase of fusion genes identified from bioinformatics analysis of transcript sequences in the GenBank and various other public resources such as the Sanger cancer genome project (CGP), OMIM, PubMed and the Mitelman’s database. In this updated version, we significantly modified the algorithm of identifying fusion transcripts. Specifically, the new algorithm is more sensitive and has detected 2699 fusion transcripts with high confidence. Furthermore, it can identify interchromosomal translocations as well as the intrachromosomal deletions or inversions of large DNA segments. Importantly, results from the analysis of next-generation sequencing data in the short read archives are incorporated as well. We updated and integrated all contents (GenBank, Sanger CGP, OMIM, PubMed publications and the Mitelman’s database), and the user-interface has been improved to support diverse types of searches and to enhance the user convenience especially in browsing PubMed articles. We also developed a new alignment viewer that should facilitate examining reliability of fusion transcripts and inferring functional significance. We expect ChimerDB 2.0, available at http://ercsb.ewha.ac.kr/fusiongene, to be a valuable tool in identifying biomarkers and drug targets.

Genomic evolution of patient-derived xenografts (PDXs) may lead to their gradual divergence away of their tumors of origin. We previously reported the genomic evolution of the copy number (CN) landscapes of PDXs during their engraftment and passaging1. However, whether PDX models are highly stable throughout passaging2, or can evolve CNAs rapidly1,3, remains controversial. Here, we reassess the genomic evolution of PDXs using DNA-based CN profiles. We find strong evidence for genomic evolution in the DNA-based PDX data: a median of ~10% of the genome is differentially altered between matched primary tumors (PTs) and PDXs across cohorts (range, 0% to 73% across all models). In 24% of the matched PT-PDX samples, over a quarter of the genome is differentially affected by CN alterations. Moreover, in matched analyses of PTs and their derived PDXs at multiple passages, later-passage PDXs are significantly less similar to their parental PTs than earlier-passage PDXs, indicative of genomic divergence. We conclude that PDX models indeed evolve throughout their derivation and propagation, and that the phenotypic consequences of this evolution ought to be assessed in order to determine its relevance to the proper application of these valuable cancer models.