The DARC side of genetics in cancer: Breast cancer disparities.

Highlighting the Distinguished Speakers Symposium on "The Future of Human Genetics and Genomics," this collection of articles is based on presentations at the ASHG 2023 Annual Meeting in Washington, DC, in celebration of all our field has accomplished in the past 75 years, since the founding of ASHG in 1948.

Transient inhibition of type I interferon enhances CD8 + T cell stemness and vaccine protection.

Developing vaccines that promote CD8 + T cell memory is a challenge for infectious disease and cancer immunotherapy. TCF-1 + stem cell-like memory T (T SCM ) cells are important determinants of long-lived memory. Yet, the developmental requirements for T SCM formation are unclear. Here, we identify the temporal window for type I interferon (IFN-I) receptor (IFNAR) blockade to drive T SCM cell generation. T SCM cells were transcriptionally distinct and emerged from a transitional precursor of exhausted (T PEX ) cellular state concomitant with viral clearance. T SCM differentiation correlated with T cell retention within the lymph node paracortex, due to increased CXCR3 chemokine abundance which disrupted gradient formation. These affects were due a counterintuitive increase in IFNψ, which controlled cell location. Combining IFNAR inhibition with mRNA-LNP vaccination promoted specific T SCM differentiation and enhanced protection against chronic infection. These finding propose a new approach to vaccine design whereby modulation of inflammation promotes memory formation and function. HIGHLIGHTS: Early, transient inhibition of the type I interferon (IFN) receptor (IFNAR) during acute viral infection promotes stem cell-like memory T (T SCM ) cell differentiation without establishing chronic infection. T SCM and precursor of exhausted (T PEX ) cellular states are distinguished transcriptionally and by cell surface markers. Developmentally, T SCM cell differentiation occurs via a transition from a T PEX state coinciding with viral clearance. Transient IFNAR blockade increases IFNψ production to modulate the ligands of CXCR3 and couple T SCM differentiation to cell retention within the T cell paracortex of the lymph node. Specific promotion of T SCM cell differentiation with nucleoside-modified mRNA-LNP vaccination elicits enhanced protection against chronic viral challenge.

ACR Appropriateness Criteria® Dizziness and Ataxia: 2023 Update.

Diagnostic evaluation of a patient with dizziness or vertigo is complicated by a lack of standardized nomenclature, significant overlap in symptom descriptions, and the subjective nature of the patient's symptoms. Although dizziness is an imprecise term often used by patients to describe a feeling of being off-balance, in many cases dizziness can be subcategorized based on symptomatology as vertigo (false sense of motion or spinning), disequilibrium (imbalance with gait instability), presyncope (nearly fainting or blacking out), or lightheadedness (nonspecific). As such, current diagnostic paradigms focus on timing, triggers, and associated symptoms rather than subjective descriptions of dizziness type. Regardless, these factors complicate the selection of appropriate diagnostic imaging in patients presenting with dizziness or vertigo. This document serves to aid providers in this selection by using a framework of definable clinical variants. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

ACR Appropriateness Criteria® Cerebrovascular Diseases-Stroke and Stroke-Related Conditions.

Cerebrovascular disease encompasses a vast array of conditions. The imaging recommendations for stroke-related conditions involving noninflammatory steno-occlusive arterial and venous cerebrovascular disease including carotid stenosis, carotid dissection, intracranial large vessel occlusion, and cerebral venous sinus thrombosis are encompassed by this document. Additional imaging recommendations regarding complications of these conditions including intraparenchymal hemorrhage and completed ischemic strokes are also discussed. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Updates in Medical and Surgical Weight Loss.

The number of individuals with obesity is at an all-time high, and the rate of obesity continues to climb each year. Obesity is a chronic disease with widespread effects throughout the body. Midwives and perinatal care providers need an understanding of the etiology, pathophysiology, and interventions for obesity. A review of evidence-based diet and lifestyle modifications, medications, and surgical procedures is presented.

Stakeholder Perceptions of Animal Welfare as a Component of Sustainable Beef Programs in the United States-A Pilot Study.

This study aimed to investigate how stakeholders in the United States beef industry incorporate animal welfare into their sustainability programs. A survey was administered online to the U.S. Roundtable for Sustainable Beef membership. Twenty-seven surveys were analyzed. Most respondents (n = 26, 96%) had sustainability programs that incorporated animal welfare. Most respondents believed that welfare positively impacted environmental (n = 25/26, 96%), economic (n = 25/26, 96%), and social (n = 26/26, 100%) sustainability. The thematic analysis of five free response questions identified ten themes: Animal Care, Regulations and Guidelines, Responsibility, Consumers and Stakeholders, Performance and Efficiency, Financial Impact, Connectedness, Critical Component, Animal-based Outcomes, and Employees. When asked to define welfare, the most common themes were Animal Care and Regulations and Guidelines. When asked why welfare was a component of their sustainability program, the top factors from a provided list were: cattle health (n = 20, 74%), cattle performance (n = 12, 44%), and consumer perceptions (n = 12, 44%). Findings suggest a widespread recognition of animal welfare's importance within sustainable beef production.

1,25-Dihydroxyvitamin D3 Suppresses Prognostic Survival Biomarkers Associated with Cell Cycle and Actin Organization in a Non-Malignant African American Prostate Cell Line.

Vitamin D3 is a steroid hormone that confers anti-tumorigenic properties in prostate cells. Serum vitamin D3 deficiency has been associated with advanced prostate cancer (PCa), particularly affecting African American (AA) men. Therefore, elucidating the pleiotropic effects of vitamin D on signaling pathways, essential to maintaining non-malignancy, may provide additional drug targets to mitigate disparate outcomes for men with PCa, especially AA men. We conducted RNA sequencing on an AA non-malignant prostate cell line, RC-77N/E, comparing untreated cells to those treated with 10 nM of vitamin D3 metabolite, 1α,25(OH)2D3, at 24 h. Differential gene expression analysis revealed 1601 significant genes affected by 1α,25(OH)2D3 treatment. Pathway enrichment analysis predicted 1α,25(OH)2D3- mediated repression of prostate cancer, cell proliferation, actin cytoskeletal, and actin-related signaling pathways (p < 0.05). Prioritizing genes with vitamin D response elements and associating expression levels with overall survival (OS) in The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA PRAD) cohort, we identified ANLN (Anillin) and ECT2 (Epithelial Cell Transforming 2) as potential prognostic PCa biomarkers. Both genes were strongly correlated and significantly downregulated by 1α,25(OH)2D3 treatment, where low expression was statistically associated with better overall survival outcomes in the TCGA PRAD public cohort. Increased ANLN and ECT2 mRNA gene expression was significantly associated with PCa, and Gleason scores using both the TCGA cohort (p < 0.05) and an AA non-malignant/tumor-matched cohort. Our findings suggest 1α,25(OH)2D3 regulation of these biomarkers may be significant for PCa prevention. In addition, 1α,25(OH)2D3 could be used as an adjuvant treatment targeting actin cytoskeleton signaling and actin cytoskeleton-related signaling pathways, particularly among AA men.

Preslaughter factors affecting mobility, blood parameters, bruising, and muscle pH of finished beef cattle in the United States.

Decades of work have focused on reducing fear, stress, and discomfort in cattle during the preslaughter phase by improving and promoting animal handling, transportation, and management processes. Even still, there is limited information about the effects of preslaughter factors on animal welfare and meat quality outcomes in finished cattle in the United States. This study aimed to track individual animals through the slaughter process to identify preslaughter factors associated with key welfare and quality outcomes. A total of 454 cattle from one commercial slaughter facility were studied. Preslaughter factors assessed included distance traveled, truck waiting time, lairage density, lairage duration, and season. Animal characteristics, i.e., body weight, breed, and sex, were also recorded. One trained observer scored the mobility of all cattle using the North American Meat Institute's 1-4 scale (i.e., normal to extremely reluctant to move). Exsanguination blood was collected and analyzed for cortisol, creatine kinase, and lactate. Carcass bruising was scored using a modified version of the National Beef Quality Audit's bruise-scoring methodology (i.e., no bruise, one bruise ≤ the size of a deck of cards, one bruise > than the size of a deck of cards, and multiple bruises). Ultimate muscle pH was measured 32 to 36 h postmortem. Multi-predictor models were selected for each outcome variable using Akaike Information Criterion. Continuous outcome variables were analyzed using linear mixed-effect models and categorical outcome variables with mixed-effect logistic regression models. Longer truck waiting times were associated with increased cortisol (P = 0.04) and lactate (P = 0.02) concentrations. Similarly, increased lairage duration was associated with increased creatine kinase concentrations (P = 0.05) and the odds of cattle being bruised (P = 0.03). Less space allowance per animal in lairage was associated with increased odds of cattle having impaired mobility (P = 0.01). There was a seasonal effect for many of the measured outcomes; the summer season was associated with greater lactate concentrations (P < 0.0001), increased odds of impaired mobility (P < 0.0001), and increased odds of carcass bruising (P = 0.003). The findings of this study indicate that many of the preslaughter factors assessed influence critical welfare and meat quality outcomes of finished beef cattle, warranting future research and consideration.

Library size confounds biology in spatial transcriptomics data.

Spatial molecular data has transformed the study of disease microenvironments, though, larger datasets pose an analytics challenge prompting the direct adoption of single-cell RNA-sequencing tools including normalization methods. Here, we demonstrate that library size is associated with tissue structure and that normalizing these effects out using commonly applied scRNA-seq normalization methods will negatively affect spatial domain identification. Spatial data should not be specifically corrected for library size prior to analysis, and algorithms designed for scRNA-seq data should be adopted with caution.

ERG and c-MYC regulate a critical gene network in BCR::ABL1-driven B cell acute lymphoblastic leukemia.

Philadelphia chromosome-positive B cell acute lymphoblastic leukemia (B-ALL), characterized by the BCR::ABL1 fusion gene, remains a poor prognosis cancer needing new therapeutic approaches. Transcriptomic profiling identified up-regulation of oncogenic transcription factors ERG and c-MYC in BCR::ABL1 B-ALL with ERG and c-MYC required for BCR::ABL1 B-ALL in murine and human models. Profiling of ERG- and c-MYC-dependent gene expression and analysis of ChIP-seq data established ERG and c-MYC coordinate a regulatory network in BCR::ABL1 B-ALL that controls expression of genes involved in several biological processes. Prominent was control of ribosome biogenesis, including expression of RNA polymerase I (POL I) subunits, the importance of which was validated by inhibition of BCR::ABL1 cells by POL I inhibitors, including CX-5461, that prevents promoter recruitment and transcription initiation by POL I. Our results reveal an essential ERG- and c-MYC-dependent transcriptional network involved in regulation of metabolic and ribosome biogenesis pathways in BCR::ABL1 B-ALL, from which previously unidentified vulnerabilities and therapeutic targets may emerge.

Even with ChatGPT, race matters.

BACKGROUND: Applications of large language models such as ChatGPT are increasingly being studied. Before these technologies become entrenched, it is crucial to analyze whether they perpetuate racial inequities. METHODS: We asked Open AI's ChatGPT-3.5 and ChatGPT-4 to simplify 750 radiology reports with the prompt "I am a ___ patient. Simplify this radiology report:" while providing the context of the five major racial classifications on the U.S. census: White, Black or African American, American Indian or Alaska Native, Asian, and Native Hawaiian or other Pacific Islander. To ensure an unbiased analysis, the readability scores of the outputs were calculated and compared. RESULTS: Statistically significant differences were found in both models based on the racial context. For ChatGPT-3.5, output for White and Asian was at a significantly higher reading grade level than both Black or African American and American Indian or Alaska Native, among other differences. For ChatGPT-4, output for Asian was at a significantly higher reading grade level than American Indian or Alaska Native and Native Hawaiian or other Pacific Islander, among other differences. CONCLUSION: Here, we tested an application where we would expect no differences in output based on racial classification. Hence, the differences found are alarming and demonstrate that the medical community must remain vigilant to ensure large language models do not provide biased or otherwise harmful outputs.

Spatial omics techniques and data analysis for cancer immunotherapy applications.

In-depth profiling of cancer cells/tissues is expanding our understanding of the genomic, epigenomic, transcriptomic, and proteomic landscape of cancer. However, the complexity of the cancer microenvironment, particularly its immune regulation, has made it difficult to exploit the potential of cancer immunotherapy. High-throughput spatial omics technologies and analysis pipelines have emerged as powerful tools for tackling this challenge. As a result, a potential revolution in cancer diagnosis, prognosis, and treatment is on the horizon. In this review, we discuss the technological advances in spatial profiling of cancer around and beyond the central dogma to harness the full benefits of immunotherapy. We also discuss the promise and challenges of spatial data analysis and interpretation and provide an outlook for the future.

Tumor-Associated Lymphocytes and Breast Cancer Survival in Black and White Women.

This case series evaluates whether differences in immune filtration are associated with breast cancer risk in Black vs White women.

A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information.

Resection and whole brain radiotherapy (WBRT) are standard treatments for brain metastases (BM) but are associated with cognitive side effects. Stereotactic radiosurgery (SRS) uses a targeted approach with less side effects than WBRT. SRS requires precise identification and delineation of BM. While artificial intelligence (AI) algorithms have been developed for this, their clinical adoption is limited due to poor model performance in the clinical setting. The limitations of algorithms are often due to the quality of datasets used for training the AI network. The purpose of this study was to create a large, heterogenous, annotated BM dataset for training and validation of AI models. We present a BM dataset of 200 patients with pretreatment T1, T1 post-contrast, T2, and FLAIR MR images. The dataset includes contrast-enhancing and necrotic 3D segmentations on T1 post-contrast and peritumoral edema 3D segmentations on FLAIR. Our dataset contains 975 contrast-enhancing lesions, many of which are sub centimeter, along with clinical and imaging information. We used a streamlined approach to database-building through a PACS-integrated segmentation workflow.

In situ single-cell profiling sheds light on IFI27 localisation during SARS-CoV-2 infection.

The utilization of single-cell resolved spatial transcriptomics to delineate immune responses during SARS-CoV-2 infection was able to identify M1 macrophages to have elevated expression of IFI27 in areas of infection.

An ASER AI/ML expert panel formative user research study for an interpretable interactive splenic AAST grading graphical user interface prototype.

PURPOSE: The AAST Organ Injury Scale is widely adopted for splenic injury severity but suffers from only moderate inter-rater agreement. This work assesses SpleenPro, a prototype interactive explainable artificial intelligence/machine learning (AI/ML) diagnostic aid to support AAST grading, for effects on radiologist dwell time, agreement, clinical utility, and user acceptance. METHODS: Two trauma radiology ad hoc expert panelists independently performed timed AAST grading on 76 admission CT studies with blunt splenic injury, first without AI/ML assistance, and after a 2-month washout period and randomization, with AI/ML assistance. To evaluate user acceptance, three versions of the SpleenPro user interface with increasing explainability were presented to four independent expert panelists with four example cases each. A structured interview consisting of Likert scales and free responses was conducted, with specific questions regarding dimensions of diagnostic utility (DU); mental support (MS); effort, workload, and frustration (EWF); trust and reliability (TR); and likelihood of future use (LFU). RESULTS: SpleenPro significantly decreased interpretation times for both raters. Weighted Cohen's kappa increased from 0.53 to 0.70 with AI/ML assistance. During user acceptance interviews, increasing explainability was associated with improvement in Likert scores for MS, EWF, TR, and LFU. Expert panelists indicated the need for a combined early notification and grading functionality, PACS integration, and report autopopulation to improve DU. CONCLUSIONS: SpleenPro was useful for improving objectivity of AAST grading and increasing mental support. Formative user research identified generalizable concepts including the need for a combined detection and grading pipeline and integration with the clinical workflow.