Citations

AbstractObjectiveThe goal of the current study is to advance efforts to increase the quality of care for childhood anxiety disorder (CADs) through (1) detailing the content of community‐based treatment sessions, (2) exploring the validity of therapist surveys, (3) examining the influence of setting differences, and (4) testing the effects of a technology‐based training on use of nonexposure strategies.MethodsThirteen therapists were randomly assigned to technology‐based training in the use of exposure therapy or treatment as usual (TAU) for CADs. Therapeutic techniques were coded from 125 community‐based treatment sessions.ResultsConsistent with survey responses community therapists spent the majority of session time reviewing symptoms (34% of session time), implementing nonexposure cognitive behavioral therapy (CBT; 36%), and rarely engaged in exposure (3%). An integrated behavioral health setting was associated with greater endorsement of exposure on survey, p < 0.05, although this difference was not significant in session recordings, p = 0.14. Multilevel models indicated that technology‐based training that has been shown to increase exposure, also decreased use of nonexposure CBT techniques (2% vs. 29%, p < 0.001).ConclusionThe study supports the validity of survey‐based findings that community‐based care for CADs consists of non‐exposure CBT techniques. Efforts should be invested in dissemination of within‐session exposure.

Platelet-rich plasma (PRP) is a revolutionary treatment that harnesses the regenerative power of the body's own platelets to promote healing and tissue regeneration. While PRP therapy has emerged as a promising option for augmenting biologic healing in the shoulder, the complexity of shoulder disorders makes it difficult to draw definitive conclusions about the efficacy of PRP across different conditions and stages of disease. Our comprehensive review of twenty-four studies highlights the current state of PRP therapy in shoulder pathologies, revealing a wide variety of number of patients, control groups and results. Despite these challenges, the regenerative potential of PRP therapy is moderate in some conditions, with numerous studies demonstrating the positive effects. In conclusion, the authors of this study recommend the use of PRP therapy for adhesive capsulitis and rotator cuff repair of medium to large tears. However, they do not recommend the use of PRP for subacromial impingement or rotator cuff tears. It is up to the clinician's discretion to decide whether PRP therapy is appropriate for individual cases. However, there is still insufficient evidence to support the inclusion of PRP therapy in treatment protocols for other shoulder disorders. Therefore, further research is needed to fully explore the potential of PRP therapy in the treatment of various shoulder conditions.

Abstract Background: Ovarian endometrioid carcinoma (OEC) is an uncommon, understudied histotype that is distinguished from other histotypes by unique genomic features and high hormone receptor expression. There is growing interest in the biological relevance of subtyping using immunohistochemistry (IHC). Methods: Women with primary invasive OEC diagnosed from 1989 to 2010 were retrospectively identified from the population-based Alberta Cancer Registry, Canada. Pathology slide review and IHC staining for Napsin A, TP53, and WT1 were used to reduce histologic misclassification, resulting in N=166 participants (low-stage N=138, high-stage N=28), excluding those who received neo-adjuvant chemotherapy. The following markers were stained and scored on tissue microarrays: TP53 (normal/abnormal), PMS2/MSH6 (mismatch repair proficient [MMRp]/deficient [MMRd]), PGR (loss/retained), and CTNNB1 (nuclear/cytoplasmic). Using a hierarchical decision tree by stage group (low/high), we categorized tumors as TP53 abnormal, MMRd, PGR loss, nuclear CTNNB1, and no specific immunohistochemical profile (NSIP). Distributions and five-year disease specific survival (DSS) was estimated for each group; hazard ratios (HRs) adjusted for age were estimated using Cox regression with NSIP as referent group. Results: Among low-stage cases, five-year survival was as follows: 80% for TP53 abnormal (N=10, 7%), 87% for MMRd (N=15, 11%), 80% for PGR loss (N=10, 7%), 98% for nuclear CTNNB1 (N=63, 46%), and 95% for NSIP group (N=40, 29%). Overall, IHC group was associated with DSS among low stage cases (LRT p-value=0.006), and the group with nuclear CTNNB1 had a small but statistically significant DSS advantage (HR=0.089, 95% CI 0.011-0.742, p=0.025). TP53 and PGR loss suggested shorter DSS than the referent NSIP group, but not statistically significantly so (HR=1.26 and 3.08, respectively). Among high-stage cases, five-year DSS was as follows: 57% for TP53 abnormal (N=7, 25%), 75% for MMRd (N=8, 29%), 33% for nuclear CTNNB1 (N=3, 11%), and 17% for NSIP (N=10, 36%). There were no high-stage cases in the PGR-loss group. Nuclear CTNNB1 group had a shorter DSS among high-stage cases, but this was not statistically significantly so (HR=1.16, p=0.85). Conclusion: Pending replication in additional datasets, results suggest that OEC cases in nuclear CTNNB1 or NSIP IHC groups may have a favorable prognosis in which de-escalation of therapy can be considered. In addition, abnormal TP53 and loss of PGR may identify a high-risk subset of low-stage OEC. Citation Format: Brooke Jorgensen, Stacey Winham, Julie Cunningham, Sebastian Armasu, Chen Wang, Hunter Atkinson, Bryan McCauley, Linda Kelemen, Martin Koebel, Ellen Goode. Towards a combined immunohistochemistry-based subtyping of ovarian endometrioid carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6499.

Abstract Purpose: Benign breast disease (BBD) is viewed as a non-obligate precursor stage in the development of breast cancer (BC). Transcriptome profiling using RNA sequencing (RNA-seq) of bulk formalin-fixed paraffin-embedded (FFPE) tissue blocks has been routinely used in BC research. However, RNA-seq of heterogeneous bulk samples represents an averaged expression profile across all cell mixtures. Downstream analyses, such as biomarker discovery, are likely confounded by differences in cell proportions. There is a lack of research in optimizing strategies for cell type deconvolution especially for FFPE samples. We evaluated and optimized strategies for cell type deconvolution using existing single cell RNA-seq (scRNA-seq) and single nucleus RNA-seq (snRNA-seq) breast tissue references, and applied these to a cohort of BBD FFPE samples to assess risk of subsequent BC. Methods: 7 scRNA-seq and 3 snRNA-seq public samples from women’s breast tissue were normalized using SCTransform, then integrated using Harmony to form a complete reference set. Bioinformatics evaluations examined the performance of existing statistical and deep learning-based deconvolution methods. Computational simulations were conducted to evaluate those methods on three scenarios: 1) baseline; 2) incomplete reference set; 3) FFPE artifacts. FFPE artifacts were simulated based on a generalized additive model using 7 in-house paired FFPE-fresh frozen samples. Finally, we applied the best performing method to our BBD cohort of 62 samples. Differential expression analysis adjusting for cell proportions was performed to identify transcriptomic aberrations in BBD cases. Results: snRNA-seq was more sensitive in capturing adipocytes, while scRNA-seq was more sensitive in detecting lymphocytes in breast tissue. The median number of detectable genes per cell was higher for scRNA-seq than snRNA-seq before integration (1264 vs 558). Marker gene-based regression methods (e.g. CIBERSORT) displayed higher variance and lower bias compared to methods directly using scRNA-seq data (e.g. SCDC). Incomplete reference data led to increased bias and little effect on variance. FFPE artifacts had a higher impact on performance compared to incomplete reference data. Overall, Scaden, a deep learning-based method, was the top performing method across all simulation scenarios and was especially robust to FFPE artifacts. 59 differential expressed genes (DEGs) were identified with fold change &gt; 1.5 and p value &lt; 0.01. DEGs involved in BC, e.g. S100A8, WNT4 and HIST1H3H, would be left out if cell proportions were not properly adjusted. Conclusions: We constructed the first complete single cell reference data for women’s breast tissue and benchmarked existing cell type deconvolution methods. Compared to analyses not adjusting for cell proportions, we observed substantial differences in perturbed genes and pathways associated with BC risk for BBD patients. Citation Format: Yuanhang Liu, Chen Wang, Stacey J. Winham, Aditya Bhagwate, Robert A. Vierkant, Julie M. Cunningham, Bryan M. McCauley, William A. Jons, Derek C. Radisky, Amy C. Degnim. Deconvolution of cell type composition in FFPE tissue: Application to benign breast disease. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4291.

Despite many studies of potential delirium biomarkers, delirium pathophysiology remains unclear. Evidence shows that the quality of reporting delirium biomarker studies is sub-optimal. Better reporting of delirium biomarker studies is needed to understand delirium pathophysiology better. To improve robustness, transparency and uniformity of delirium biomarker study reports, the REDEEMS (Reporting Essentials for DElirium bioMarker Studies) guideline was developed by an international group of delirium researchers through a three-stage process, including a systematic review, a three-round Delphi study, and a follow-up consensus meeting. This process resulted in a 9-item guideline to inform delirium fluid biomarker studies. To enhance implementation of the REDEEMS guideline, this Explanation and Elaboration paper provides a detailed explanation of each item. We anticipate that the REDEEMS guideline will help to accelerate our understanding of delirium pathophysiology by improving the reporting of delirium biomarker research and, consequently the capacity to synthesise results across studies.

Abstract Background: Better understanding of prognostic factors in tubo-ovarian high-grade serous carcinoma (HGSC) is critical, as diagnosis confers an aggressive disease course. Variation in tumor DNA methylation shows promise predicting outcome, yet prior studies were largely platform-specific and unable to evaluate multiple molecular features. Methods: We analyzed genome-wide DNA methylation in 1,040 frozen HGSC, including 325 previously reported upon, seeking a multi-platform quantitative methylation signature that we evaluated in relation to clinical features, tumor characteristics, time to recurrence/death, extent of CD8+ tumor-infiltrating lymphocytes (TIL), gene expression molecular subtypes, and gene expression of the ATP-binding cassette transporter TAP1. Results: Methylation signature was associated with shorter time to recurrence, independent of clinical factors (N = 715 new set, hazard ratio (HR), 1.65; 95% confidence interval (CI), 1.10–2.46; P = 0.015; N = 325 published set HR, 2.87; 95% CI, 2.17–3.81; P = 2.2 × 10−13) and remained prognostic after adjustment for gene expression molecular subtype and TAP1 expression (N = 599; HR, 2.22; 95% CI, 1.66–2.95; P = 4.1 × 10−8). Methylation signature was inversely related to CD8+ TIL levels (P = 2.4 × 10−7) and TAP1 expression (P = 0.0011) and was associated with gene expression molecular subtype (P = 5.9 × 10−4) in covariate-adjusted analysis. Conclusions: Multi-center analysis identified a novel quantitative tumor methylation signature of HGSC applicable to numerous commercially available platforms indicative of shorter time to recurrence/death, adjusting for other factors. Along with immune cell composition analysis, these results suggest a role for DNA methylation in the immunosuppressive microenvironment. Impact: This work aids in identification of targetable epigenome processes and stratification of patients for whom tailored treatment may be most beneficial.

Abstract Summary We recently introduced the Gut Microbiome Wellness Index (GMWI), a stool metagenome-based indicator for assessing health by determining the likelihood of disease given the state of one’s gut microbiome. The calculation of our wellness index depends on the relative abundances of health-prevalent and health-scarce species. Encouragingly, GMWI has already been utilized in various studies focusing on differences in the gut microbiome between cases and controls. Herein, we introduce the GMWI-webtool, a user-friendly browser application that computes GMWI, health-prevalent/-scarce species’ relative abundances, and α-diversities from stool shotgun metagenome taxonomic profiles. Users of our interactive online tool can visualize their results and compare them side-by-side with those from our pooled reference dataset of metagenomes, as well as export data in.csv format and high-resolution figures. Availability and implementation GMWI-webtool is freely available here: https://gmwi-webtool.github.io/. Supplementary information Supplementary data are available at Bioinformatics online.