Citations

The NCCN Guidelines for Prostate Cancer Early Detection provide recommendations for individuals with a prostate who opt to participate in an early detection program after receiving the appropriate counseling on the pros and cons. These NCCN Guidelines Insights provide a summary of recent updates to the NCCN Guidelines with regard to the testing protocol, use of multiparametric MRI, and management of negative biopsy results to optimize the detection of clinically significant prostate cancer and minimize the detection of indolent disease.

Abstract Background In the United States, rare disease (RD) is defined as a condition that affects fewer than 200,000 individuals. Collectively, RD affects an estimated 30 million Americans. A significant portion of RD has an underlying genetic cause; however, this may go undiagnosed. To better serve these patients, the Mayo Clinic Program for Rare and Undiagnosed Diseases (PRaUD) was created under the auspices of the Center for Individualized Medicine (CIM) aiming to integrate genomics into subspecialty practice including targeted genetic testing, research, and education. Methods Patients were identified by subspecialty healthcare providers from 11 clinical divisions/departments. Targeted multi-gene panels or custom exome/genome-based panels were utilized. To support the goals of PRaUD, a new clinical service model, the Genetic Testing and Counseling (GTAC) unit, was established to improve access and increase efficiency for genetic test facilitation. The GTAC unit includes genetic counselors, genetic counseling assistants, genetic nurses, and a medical geneticist. Patients receive abbreviated point-of-care genetic counseling and testing through a partnership with subspecialty providers. Results Implementation of PRaUD began in 2018 and GTAC unit launched in 2020 to support program expansion. Currently, 29 RD clinical indications are included in 11 specialty divisions/departments with over 142 referring providers. To date, 1,152 patients have been evaluated with an overall solve rate of 14.1% and as high as 66.7% depending on the phenotype. Noteworthy, 42.7% of the solved or likely solved patients underwent changes in medical management and outcome based on genetic test results. Conclusion Implementation of PRaUD and GTAC have enabled subspecialty practices advance expertise in RD where genetic counselors have not historically been embedded in practice. Democratizing access to genetic testing and counseling can broaden the reach of patients with RD and increase the diagnostic yield of such indications leading to better medical management as well as expanding research opportunities.

Currently available bioinformatics tools to identify BGCs from metagenomic sequencing data are limited in their predictive capability or ease of use to even computationally oriented researchers. We present an automated computational pipeline called TaxiBGC, which predicts experimentally characterized BGCs (and infers their known SMs) in shotgun metagenomes by first considering the microbial species source.

ABSTRACT Model organism (MO) research provides a basic understanding of biology and disease due to the evolutionary conservation of the molecular and cellular language of life. MOs have been used to identify and understand the function of orthologous genes, proteins, cells and tissues involved in biological processes, to develop and evaluate techniques and methods, and to perform whole-organism-based chemical screens to test drug efficacy and toxicity. However, a growing richness of datasets and the rising power of computation raise an important question: How do we maximize the value of MOs? In-depth discussions in over 50 virtual presentations organized by the National Institutes of Health across more than 10 weeks yielded important suggestions for improving the rigor, validation, reproducibility and translatability of MO research. The effort clarified challenges and opportunities for developing and integrating tools and resources. Maintenance of critical existing infrastructure and the implementation of suggested improvements will play important roles in maintaining productivity and facilitating the validation of animal models of human biology and disease.

ObjectiveTo identify differences in multimorbidity and individual comorbidities among individuals with rheumatoid arthritis (RA), separated by race and ethnicity.MethodsThis case–control study within OptumLabs Data Warehouse from 2010 to 2019 matched RA cases (defined by 2 codes plus prescription of an RA drug) to non‐RA controls 1:1 on age, sex, race and ethnicity, region, index date of RA, and insurance coverage duration. We defined multimorbidity as the presence of ≥2 or ≥5 validated comorbidities. Logistic regression models calculated adjusted odds of multimorbidity with 95% confidence intervals (95% CIs) within each race and ethnicity.ResultsWe identified 154,391 RA cases and 154,391 controls (mean age 59.6, 76% female). Black enrollees had the most multimorbidity ≥2/≥5 (73.1%, 34.3%); Asian enrollees had the least (52.4%, 17.3%). Adjusted odds of multimorbidity ≥2 and ≥5 in RA cases versus controls was 2.19 (95% CI 2.16–2.23) and 2.06 (95% CI 2.02–2.09), respectively. This increase was similar across race and ethnicity. However, we observed elevated occurrence of certain comorbidities by race and ethnicity versus controls (P < 0.001), including renal disease in White enrollees (4.7% versus 3.2%) and valvular heart disease in Black and White enrollees (3.2% and 2.8% versus 2.6% and 2.2%).ConclusionMultimorbidity is a problem for all RA patients. Targeted identification of certain comorbidities by race and ethnicity may be a helpful approach to mitigate multimorbidity.

Background: Observational studies suggested that dementia risk in patients with rheumatoid arthritis (RA) is higher than in the general population. Objective: To examine the associations of RA with cognitive decline and dementia, and neuroimaging biomarkers of aging, Alzheimer’s disease, and vascular pathology in adult participants in the Mayo Clinic Study of Aging (MCSA). Methods: Participants with RA were matched 1:3 on age, sex, education, and baseline cognitive diagnosis to participants without RA. RA cases with MRI were also matched with non-cases with available MRI. All available imaging studies (i.e., amyloid and FDG PET, sMRI, and FLAIR) were included. The study included 104 participants with RA and 312 without RA (mean age (standard deviation, SD) 75.0 (10.4) years, 33% male and average follow-up (SD) 4.2 (3.8) years). Results: Groups were similar in cognitive decline and risk of incident dementia. Among participants with neuroimaging, participants with RA (n = 33) and without RA (n = 98) had similar amyloid burden and neurodegeneration measures, including regions sensitive to aging and dementia, but greater mean white matter hyperintensity volume relative to the total intracranial volume (mean (SD)% : 1.12 (0.57)% versus 0.76 (0.69)% of TIV, p = 0.01), and had higher mean (SD) number of cortical infarctions (0.24 (0.44) versus 0.05 (0.33), p = 0.02). Conclusion: Although cognitive decline and dementia risk were similar in participants with and without RA, participants with RA had more abnormal cerebrovascular pathology on neuroimaging. Future studies should examine the mechanisms underlying these changes and potential implications for prognostication and prevention of cognitive decline in RA.

Objective To identify clusters of comorbidities in patients with rheumatoid arthritis (RA) using 4 methods and to compare to patients without RA. Methods In this retrospective, population‐based study, residents of 8 Minnesota counties with prevalent RA as of January 1, 2015 were identified. Age‐, sex‐, and county‐matched non‐RA comparators were selected from the same underlying population. Diagnostic codes were retrieved for 5 years before January 1, 2015. Using 2 codes ≥30 days apart, 44 previously defined morbidities and 11 nonoverlapping chronic disease categories based on Clinical Classifications Software were defined. Unsupervised machine learning methods of interest included hierarchical clustering, factor analysis, K‐means clustering, and network analysis. Results Two groups of 1,643 patients with and without RA (72% female; mean age 63.1 years in both groups) were studied. Clustering of comorbidities revealed strong associations among mental/behavioral comorbidities and among cardiovascular risk factors and diseases. The clusters were associated with age and sex. Differences between the 4 clustering methods were driven by comorbidities that are rare and those that were weakly associated with other comorbidities. Common comorbidities tended to group together consistently across approaches. The instability of clusters when using different random seeds or bootstrap sampling impugns the usefulness and reliability of these methods. Clusters of common comorbidities between RA and non‐RA cohorts were similar. Conclusion Despite the higher comorbidity burden in patients with RA compared to the general population, clustering comorbidities did not identify substantial differences in comorbidity patterns between the RA and non‐RA cohorts. The instability of clustering methods suggests caution when interpreting clustering using 1 method.

e16200 Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. Indoleamine-2,3-dioxygenase (IDO) is an intracellular enzyme expressed by HCC which helps to orchestrate immune suppression within the tumor microenvironment (TME) and may contribute to primary and acquired resistance of PD-(L)1 inhibitors. BMS-986205 is a novel oral drug that potently and selectively inhibits IDO1. This Phase I/II study is evaluating the safety and tolerability of the combination of BMS-986205 and nivolumab as first-line therapy in HCC. Methods: Patients (pts) ≥18y with untreated, unresectable/metastatic HCC received BMS-986205 in combination with nivolumab. A fixed dose of Nivolumab 240mg/m2 IV was administered on Day 1 of each 14-day cycle. BMS-986205 was an oral tablet administered daily; a total of two dose levels (50-100mg) were given to determine dose limiting toxicities (DLT) during the dose-escalation Phase I of the study. Safety was assessed using CTCAE v5.0 criteria, and efficacy was assessed by objective response rate (ORR) using RECIST v1.1 criteria. Secondary objectives included preliminary data on disease control rate (DCR), duration of response (DOR), ORR using immune RECIST criteria (iRECIST), progression free survival (PFS) and overall survival (OS). Results: Here we report the results of the dose escalation cohort. Eight pts were treated with median age 69y [60-76]; 75% male; and PS 0 (3 pts) or 1 (5 pts). Pts were White (62.5%), Asian (25%), and African American (12.5%). Six of 8 pts had underlying viral hepatitis (5 hepatitis C, 1 hepatitis B), and all pts were Child Pugh A at enrollment with median baseline alpha-fetoprotein (AFP) level 41.8 [3.8–917.2]; 4 pts received prior local therapies. A total of 91 cycles of therapy were administered; 2 pts received 27 and 43 cycles of treatment each. Six pts were evaluable for DLT; 2 pts were replaced for DLT assessment due to insufficient dose administered, unrelated to toxicity. No DLTs were observed at either the 50 or 100mg dose of BMS-986205. There were 24 treatment-related adverse events (TRAEs), 4 of which were Grade 3 events; there were no Grade 4-5 events. The most common TRAEs of all grades were AST elevation and ALT elevation in 3 pts, and diarrhea, maculopapular rash and increased alkaline phosphatase in 2 pts each. Grade 3 events were diarrhea and AST elevation (1 pt), and hyperglycemia and pancreatitis requiring treatment discontinuation (1 pt). Eight pts were evaluable for efficacy with best response of partial response in 1 pt (12.5%) and stable disease in 3 pts (37.5%), yielding a DCR of 50%. Median PFS was 8.5 weeks; median OS has not been reached. Conclusions: Combination BMS-986205 and nivolumab showed a manageable safety profile with durable benefit as 1st line therapy in a meaningful subset of patients with unresectable/metastatic HCC. Clinical trial information: NCT03695250.