A cloud-based resource for genome coordinate-based exploration and large-scale analysis of chromosome aberrations and gene fusions in cancer.

Cytogenetic analysis provides important information on the genetic mechanisms of cancer. The Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer (Mitelman DB) is the largest catalog of acquired chromosome aberrations, presently comprising >70 000 cases across multiple cancer types. Although this resource has enabled the identification of chromosome abnormalities leading to specific cancers and cancer mechanisms, a large-scale, systematic analysis of these aberrations and their downstream implications has been difficult due to the lack of a standard, automated mapping from aberrations to genomic coordinates. We previously introduced CytoConverter as a tool that automates such conversions. CytoConverter has now been updated with improved interpretation of karyotypes and has been integrated with the Mitelman DB, providing a comprehensive mapping of the 70 000+ cases to genomic coordinates, as well as visualization of the frequencies of chromosomal gains and losses. Importantly, all CytoConverter-generated genomic coordinates are publicly available in Google BigQuery, a cloud-based data warehouse, facilitating data exploration and integration with other datasets hosted by the Institute for Systems Biology Cancer Gateway in the Cloud (ISB-CGC) Resource. We demonstrate the use of BigQuery for integrative analysis of Mitelman DB with other cancer datasets, including a comparison of the frequency of imbalances identified in Mitelman DB cases with those found in The Cancer Genome Atlas (TCGA) copy number datasets. This solution provides opportunities to leverage the power of cloud computing for low-cost, scalable, and integrated analysis of chromosome aberrations and gene fusions in cancer.

Perceptions of US Medical Students on Artificial Intelligence in Medicine: Mixed Methods Survey Study.

BACKGROUND: Given the rapidity with which artificial intelligence is gaining momentum in clinical medicine, current physician leaders have called for more incorporation of artificial intelligence topics into undergraduate medical education. This is to prepare future physicians to better work together with artificial intelligence technology. However, the first step in curriculum development is to survey the needs of end users. There has not been a study to determine which media and which topics are most preferred by US medical students to learn about the topic of artificial intelligence in medicine. OBJECTIVE: We aimed to survey US medical students on the need to incorporate artificial intelligence in undergraduate medical education and their preferred means to do so to assist with future education initiatives. METHODS: A mixed methods survey comprising both specific questions and a write-in response section was sent through Qualtrics to US medical students in May 2021. Likert scale questions were used to first assess various perceptions of artificial intelligence in medicine. Specific questions were posed regarding learning format and topics in artificial intelligence. RESULTS: We surveyed 390 US medical students with an average age of 26 (SD 3) years from 17 different medical programs (the estimated response rate was 3.5%). A majority (355/388, 91.5%) of respondents agreed that training in artificial intelligence concepts during medical school would be useful for their future. While 79.4% (308/388) were excited to use artificial intelligence technologies, 91.2% (353/387) either reported that their medical schools did not offer resources or were unsure if they did so. Short lectures (264/378, 69.8%), formal electives (180/378, 47.6%), and Q and A panels (167/378, 44.2%) were identified as preferred formats, while fundamental concepts of artificial intelligence (247/379, 65.2%), when to use artificial intelligence in medicine (227/379, 59.9%), and pros and cons of using artificial intelligence (224/379, 59.1%) were the most preferred topics for enhancing their training. CONCLUSIONS: The results of this study indicate that current US medical students recognize the importance of artificial intelligence in medicine and acknowledge that current formal education and resources to study artificial intelligence-related topics are limited in most US medical schools. Respondents also indicated that a hybrid formal/flexible format would be most appropriate for incorporating artificial intelligence as a topic in US medical schools. Based on these data, we conclude that there is a definitive knowledge gap in artificial intelligence education within current medical education in the US. Further, the results suggest there is a disparity in opinions on the specific format and topics to be introduced.

Patchy metal nanoparticles with polymers: controllable growth and two-way self-assembly.

We report a new design of polymer-patched gold nanoparticles (AuNPs) with controllable interparticle interactions in terms of their direction and strength. Patchy AuNPs (pAuNPs) are prepared through hydrophobicity-driven surface dewetting under deficient ligand exchange conditions. Using the exposed surface on pAuNPs as seeds, a highly controllable growth of AuNPs is carried out via seed-mediated growth while retaining the size of polymer domains. As guided by ligands, these pAuNPs can self-assemble directionally in two ways along the exposed surface (head-to-head) or the polymer-patched surface of pAuNPs (tail-to-tail). Control of the surface asymmetry/coverage on pAuNPs provides an important tool in balancing interparticle interactions (attraction vs. repulsion) that further tunes assembled nanostructures as clusters and nanochains. The self-assembly pathway plays a key role in determining the interparticle distance and therefore plasmon coupling of pAuNPs. Our results demonstrate a new paradigm in the directional self-assembly of anisotropic building blocks for hierarchical nanomaterials with interesting optical properties.

Circulating microbial content in myeloid malignancy patients is associated with disease subtypes and patient outcomes.

Although recent work has described the microbiome in solid tumors, microbial content in hematological malignancies is not well-characterized. Here we analyze existing deep DNA sequence data from the blood and bone marrow of 1870 patients with myeloid malignancies, along with healthy controls, for bacterial, fungal, and viral content. After strict quality filtering, we find evidence for dysbiosis in disease cases, and distinct microbial signatures among disease subtypes. We also find that microbial content is associated with host gene mutations and with myeloblast cell percentages. In patients with low-risk myelodysplastic syndrome, we provide evidence that Epstein-Barr virus status refines risk stratification into more precise categories than the current standard. Motivated by these observations, we construct machine-learning classifiers that can discriminate among disease subtypes based solely on bacterial content. Our study highlights the association between the circulating microbiome and patient outcome, and its relationship with disease subtype.

53BP1 regulates heterochromatin through liquid phase separation.

Human 53BP1 is primarily known as a key player in regulating DNA double strand break (DSB) repair choice; however, its involvement in other biological process is less well understood. Here, we report a previously uncharacterized function of 53BP1 at heterochromatin, where it undergoes liquid-liquid phase separation (LLPS) with the heterochromatin protein HP1α in a mutually dependent manner. Deletion of 53BP1 results in a reduction in heterochromatin centers and the de-repression of heterochromatic tandem repetitive DNA. We identify domains and residues of 53BP1 required for its LLPS, which overlap with, but are distinct from, those involved in DSB repair. Further, 53BP1 mutants deficient in DSB repair, but proficient in LLPS, rescue heterochromatin de-repression and protect cells from stress-induced DNA damage and senescence. Our study suggests that in addition to DSB repair modulation, 53BP1 contributes to the maintenance of heterochromatin integrity and genome stability through LLPS.

The Uneven Later Work Course: Intersectional Gender, Age, Race, and Class Disparities.

OBJECTIVES: Later adult work attachments and exits are in flux, suggesting the need for understanding both the range of contemporary population-level pathways of work and nonwork and variations by overlapping social locations. We document patterned continuity and change in monthly work attachments and analyze the intersecting effects of age, gender, education, and race/ethnicity. METHODS: We capitalize on massive microlevel 16-month panel data from the Current Population Survey from 2008 through 2016 to empirically identify patterned pathways of monthly states: working full-time, long hours, part-time; being self-employed or unemployed; not working because of a disability, due to family care or other reasons, or because one defines oneself as retired. RESULTS: Analyses of 346,488 American women and men aged 50-75 years reveal patterned elasticity in the timing and nature of work attachments in the form of six distinctive pathways. Our intersectional analyses illustrate divergences and disparities: advantages for educated White men, disadvantages for low-educated Black men and women through their early 60s, and intersecting effects of gender, education, and race/ethnicity during the later work course across age groups. We find convergence across social markers by the 70s. DISCUSSION: This research highlights the importance of intersectional analysis, recasting the gendered work course in later adulthood into a framework of even greater complexities within mutually shaping categories of race/ethnicity, class, and age. Older Americans experience patterned, uneven pathways around work and nonwork. We recommend additional scholarship on the dynamics of constrained and disparate choices unfolding across multiple intersecting social locations.

Exonic variants undergoing allele-specific selection in cancers.

BACKGROUND: Allelic imbalance (AI) in tumors is caused by chromosomal and sub-chromosomal gains and losses. RESULTS: We evaluated AI at 109,086 germline exonic SNP loci in four cancer types, and identified a set of SNPs that demonstrate strong tumor allele specificity in AI events. Further analyses demonstrated that these alleles show consistently different frequencies in the cancer population compared to the healthy population and are significantly enriched for predicted protein-damaging variants. Moreover, genes harboring SNPs that demonstrate allele specificity are enriched for cancer-related biological processes and are more likely to be essential in cancer cells. CONCLUSIONS: In summary, our study provides a unique and complementary method to identify genes and variants that are relevant to carcinogenesis.

Mitochondrial DNA Content Is Linked to Cardiovascular Disease Patient Phenotypes.

Background We sought to determine whether mitochondrial DNA (mtDNA) content can be used as markers for 12 key phenotypes among cardiovascular disease patients, and whether these markers are valid across patients with diverse ancestries. Methods and Results DNA was collected from the peripheral blood of 996 cardiovascular disease patients at the Cleveland Clinic. The mtDNA copy number and DNA-level variation were assessed from whole-genome sequence. Patients were also ascertained retrospectively for histories of 10 clinical events, as well as for maximum stenosis and extent of disease at baseline. Self-reported race and maternal ancestry inferred from mtDNA sequence were recorded. MtDNA copy number and overall mtDNA rare variant load were significantly lower in patients with histories of various adverse clinical events, and mtDNA copy number was inversely correlated with extent of disease. Strong associations were also found between absence of rare variants in the genes MT-ATP6 and MT-COII and patient histories of hyperlipidemia and myocardial infarction, respectively. Importantly, associations were not ancestry dependent. Conclusions This study provides evidence that mtDNA copy number in circulation is associated with a variety of cardiovascular disease patient phenotypes. Results also suggest a protective role for some rare inherited mtDNA variants. Overall, the study supports the potential of mtDNA content and abundance as biomarkers in heart disease, in a manner that is valid across diverse ancestries.

5-Fluorouracil Enhances the Antitumor Activity of the Glutaminase Inhibitor CB-839 against PIK3CA-Mutant Colorectal Cancers.

PIK3CA encodes the p110α catalytic subunit of PI3K and is frequently mutated in human cancers, including ∼30% of colorectal cancer. Oncogenic mutations in PIK3CA render colorectal cancers more dependent on glutamine. Here we report that the glutaminase inhibitor CB-839 preferentially inhibits xenograft growth of PIK3CA-mutant, but not wild-type (WT), colorectal cancers. Moreover, the combination of CB-839 and 5-fluorouracil (5-FU) induces PIK3CA-mutant tumor regression in xenograft models. CB-839 treatment increased reactive oxygen species and caused nuclear translocation of Nrf2, which in turn upregulated mRNA expression of uridine phosphorylase 1 (UPP1). UPP1 facilitated the conversion of 5-FU to its active compound, thereby enhancing the inhibition of thymidylate synthase. Consistently, knockout of UPP1 abrogated the tumor inhibitory effect of combined CB-839 and 5-FU administration. A phase I clinical trial showed that the combination of CB-839 and capecitabine, a prodrug of 5-FU, was well tolerated at biologically-active doses. Although not designed to test efficacy, an exploratory analysis of the phase I data showed a trend that PIK3CA-mutant patients with colorectal cancer might derive greater benefit from this treatment strategy as compared with PIK3CA WT patients with colorectal cancer. These results effectively demonstrate that targeting glutamine metabolism may be an effective approach for treating patients with PIK3CA-mutant colorectal cancers and warrants further clinical evaluation. SIGNIFICANCE: Preclinical and clinical trial data suggest that the combination of CB-839 with capecitabine could serve as an effective treatment for PIK3CA-mutant colorectal cancers.

An in vitro model maintaining taxon-specific functional activities of the gut microbiome.

In vitro gut microbiome models could provide timely and cost-efficient solutions to study microbiome responses to drugs. For this purpose, in vitro models that maintain the functional and compositional profiles of in vivo gut microbiomes would be extremely valuable. Here, we present a 96-deep well plate-based culturing model (MiPro) that maintains the functional and compositional profiles of individual gut microbiomes, as assessed by metaproteomics, while allowing a four-fold increase in viable bacteria counts. Comparison of taxon-specific functions between pre- and post-culture microbiomes shows a Pearson's correlation coefficient r of 0.83 ± 0.03. In addition, we show a high degree of correlation between gut microbiome responses to metformin in the MiPro model and those in mice fed a high-fat diet. We propose MiPro as an in vitro gut microbiome model for scalable investigation of drug-microbiome interactions such as during high-throughput drug screening.

CytoConverter: a web-based tool to convert karyotypes to genomic coordinates.

BACKGROUND: Cytogenetic nomenclature is used to describe chromosomal aberrations (or lack thereof) in a collection of cells, referred to as the cells' karyotype. The nomenclature identifies locations on chromosomes using a system of cytogenetic bands, each with a unique name and region on a chromosome. Each band is microscopically visible after staining, and encompasses a large portion of the chromosome. More modern analyses employ genomic coordinates, which precisely specify a chromosomal location according to its distance from the end of the chromosome. Currently, there is no tool to convert cytogenetic nomenclature into genomic coordinates. Since locations of genes and other genomic features are usually specified by genomic coordinates, a conversion tool will facilitate the identification of the features that are harbored in the regions of chromosomal gain and loss that are implied by a karyotype. RESULTS: Our tool, termed CytoConverter, takes as input either a single karyotype or a file consisting of multiple karyotypes from several individuals. All net chromosomal gains and losses implied by the karyotype are returned in standard genomic coordinates, along with the numbers of cells harboring each aberration if included in the input. CytoConverter also returns graphical output detailing areas of gains and losses of chromosomes and chromosomal segments. CONCLUSIONS: CytoConverter is available as a web-based application at https://jxw773.shinyapps.io/Cytogenetic__software/ and as an R script at https://sourceforge.net/projects/cytoconverter/ . Supplemental Material detailing the underlying algorithms is available.

Psychometric Evaluation of the Wang Pregnancy Stress Scale: Revised for Taiwanese Women.

BACKGROUND AND PURPOSE: Develop and assess psychometric properties of the Wang Pregnancy Stress Scale for measuring stress among pregnant women in Taiwan. METHODS: Data were collected in 3 obstetric and gynecological clinics in Taiwan; 485 pregnant women participated in this study. We used exploratory factor analysis and internal consistency reliability was measured using Cronbach's alpha. RESULTS: A 4-factor structure emerged for the Wang Pregnancy Stress Scale. The internal reliability of the scale as measured by Cronbach's alpha was .898, with standardized alpha .905. CONCLUSIONS: The Wang Pregnancy Stress Scale has high reliability and validity in measuring pregnancy stress that would allow nurses or health care workers to measure women's stress levels during pregnancy. Nurses can use the assessed pregnancy stress to alter intervention of care for their pregnant clients.

Laquinimod reduces neuroaxonal injury through inhibiting microglial activation.

OBJECTIVE: Laquinimod is an emerging oral medication for multiple sclerosis (MS) that reduces brain atrophy and progression of disability in two Phase III clinical trials. The mechanism of these effects is unclear. Persistent activation of microglia occurs in MS and contributes to injury. Thus, we investigated whether laquinimod alters properties of microglia in culture and in experimental autoimmune encephalomyelitis (EAE), and whether this reduces neurodegeneration. METHODS: Microglia were cultured from human brains. EAE was induced in mice. RESULTS: The activation of human microglia increased levels of several pro- and anti-inflammatory cytokines and these elevations were attenuated by pretreatment with laquinimod. Laquinimod prevented the decline in activated microglia of miR124a, a microRNA implicated in maintaining microglia quiescence, and reduced the activity of several signaling pathways (Jun-N-terminal kinase, ribosomal S6 kinase, and AKT/protein kinase B) in activated microglia. In EAE, axonal injury correlated with accumulation of microglia/macrophages in the spinal cord. EAE mice treated with laquinimod before onset of clinical signs subsequently had reduced microglia/macrophage density and axonal injury. Remarkably, when laquinimod treatment was initiated well into the disease course, the progressive demyelination, and axonal loss was halted. Besides inflammatory molecules associated with microglia, the level of inducible nitric oxide (NO) synthase capable of producing free radical toxicity was attenuated by laquinimod in EAE mice. Finally, in coculture where microglia activation caused neuronal death, laquinimod decreased NO levels, and neurotoxicity. INTERPRETATION: Laquinimod is a novel inhibitor of microglial activation that lowers microglia-induced neuronal death in culture and axonal injury/loss in EAE.

Screening for inhibitors of microglia to reduce neuroinflammation.

BACKGROUND: Despite the significant role microglia play in the pathology of multiple sclerosis (MS), medications that act within the central nervous system (CNS) to inhibit microglia have not yet been identified as treatment options. OBJECTIVE: We screened 1040 compounds with the aim of identifying inhibitors of microglia to reduce neuroinflammation. METHODS: The NINDs collection of 1040 compounds, where most are therapeutic medications, was tested at 10 µM final concentration on lipopolysaccharide (LPS)-activated human microglia. An ELISA was run on the media to measure the level of TNF-α as an indicator of microglia activity. For compounds that reduce LPS-activated TNF-α levels by over 50%, considered as a potential inhibitor of interest, toxicity tests were conducted to exclude non-specific cytotoxicity. Promising compounds were subjected to further analyses, including toxicity to other CNS cell types, and multiplex assays. RESULTS: Of 1040 compounds tested, 123 reduced TNF-α levels of LPS-activated microglia by over 50%. However, most of these were cytotoxic to microglia at the concentration tested while 54 were assessed to be non-toxic. Of the latter, spironolactone was selected for further analyses. Spironolactone reduced TNF-α levels of activated microglia by 50-60% at 10 µM, and this concentration did not kill microglia, neurons or astrocytes. In multiplex assays, spironolactone reduced several molecules in activated microglia. Finally, during the screening, we identified 9 compounds that elevated further the TNF-α levels in LPS-activated microglia. CONCLUSION: Many of the non-toxic compounds identified in this screen as inhibitors of microglia, including spironolactone, may be explored as viable therapeutic options in MS.

Natural-agent mechanisms and early-phase clinical development.

The evolution of chemoprevention research continues in exciting new directions. Large chemoprevention trials in unselected patients have often been negative, but this trend promises to be reversed by more-focused and novel trial designs emphasizing the identification of molecular targets and predictive biomarkers. Phase 0 designs, blood and tissue-based biomarkers, and surrogate endpoints are examples of important features of new prevention-trial design. Breakthroughs in the identification of novel mechanisms of carcinogenesis have contributed to a better understanding of key signaling pathways in cancer development. There has been substantial progress in elucidating molecular targets of promising synthetic and natural agents such as epigallocatechin gallate, indole-3-carbinol, myo-inositol, and deguelin, raising great optimism that biomarkers predicting efficacy, such as those associated with metformin effects, will be identified. This review will highlight several promising natural agents and how early clinical development may elucidate their role in personalized cancer chemoprevention.

Kinetics of proinflammatory monocytes in a model of multiple sclerosis and its perturbation by laquinimod.

Proinflammatory circulating monocytes have important roles in the pathology of multiple sclerosis (MS) and its animal model, experimental autoimmune encephalomyelitis (EAE). Yet there is limited information on their accumulation in blood during disease, the mechanisms that regulate their infiltration into the central nervous system (CNS), and whether medications affect their biology. We found a significant and prolonged elevation of CD11b(+)CCR2(+)Ly6C(high) proinflammatory monocytes in the blood of mice by the second day of immunization for EAE. At onset of clinical signs, levels of proinflammatory monocytes plummeted to those in naive mice. At day 16, when the majority of mice were at peak disease severity, clinical scores were inversely correlated to the proportion of proinflammatory monocytes in blood, and directly correlated with that in the spinal cord. Treatment with the MS medication laquinimod prevented EAE, correspondent with retention of proinflammatory monocytes in blood. The reduced entry of proinflammatory monocytes into the CNS by laquinimod was attributed to reduction of their levels of CD62L and matrix metalloproteinase-9. Moreover, the spinal cord of laquinimod-treated mice did not have elevated levels of CCR2 and CCL2, which provide chemotactic cues for monocytes. These results shed light on the important role of the trafficking of proinflammatory monocytes into the CNS to promote disease activity, and they identify a mechanism of action of laquinimod in MS.