Citations

Dysregulated actin cytoskeleton gives rise to aberrant cell motility and metastatic spread of tumor cells. This study evaluates the effect of overexpression of wild-type versus functional mutants of MRTF-A on migration and invasion of breast cancer (BC) cells. Our studies indicate that SRF's interaction is critical for MRTF-A-induced promotion of both two-dimensional and three-dimensional cell migration, while the SAP-domain function is important selectively for three-dimensional cell migration. Increased MRTF-A activity is associated with more effective membrane protrusion, a phenotype that is attributed predominantly to SRF's interaction with MRTF. We demonstrate formin-family protein mDia2 as an important mediator of MRTF-stimulated actin polymerization at the leading edge and cell migration. Multiplexed quantitative immunohistochemistry and transcriptome analyses of clinical BC specimens further demonstrate a positive correlation between nuclear localization of MRTF with malignant traits of cancer cells and enrichment of MRTF–SRF gene signature in pair-matched distant metastases versus primary tumors. In conclusion, this study establishes a novel mechanism of MRTF-dependent regulation of cell migration and provides evidence for the association between MRTF activity and increased malignancy in human BC, justifying future development of specific small molecule inhibitors of the MRTF-SRF transcriptional complex as potential therapeutic agents in BC.

Abstract Purpose: Metastatic castration-resistant prostate cancer (mCRPC) resistant to androgen receptor signaling inhibitors (ARSI) is often lethal. Liquid biopsy biomarkers for this deadly form of disease remain under investigation, and underpinning mechanisms remain ill-understood. Experimental Design: We applied targeted cell-free DNA (cfDNA) sequencing to 126 patients with mCRPC from three academic cancer centers and separately performed genome-wide cfDNA methylation sequencing on 43 plasma samples collected prior to the initiation of first-line ARSI treatment. To analyze the genome-wide sequencing data, we performed nucleosome positioning and differential methylated region analysis. We additionally analyzed single-cell and bulk RNA sequencing data from 14 and 80 patients with mCRPC, respectively, to develop and validate a stem-like signature, which we inferred from cfDNA. Results: Targeted cfDNA sequencing detected AR/enhancer alterations prior to first-line ARSIs that correlated with significantly worse progression-free survival (P = 0.01; HR = 2.12) and overall survival (P = 0.02; HR = 2.48). Plasma methylome analysis revealed that AR/enhancer lethal mCRPC patients have significantly higher promoter-level hypomethylation than AR/enhancer wild-type mCRPC patients (P < 0.0001). Moreover, gene ontology and CytoTRACE analysis of nucleosomally more accessible transcription factors in cfDNA revealed enrichment for stemness-associated transcription factors in patients with lethal mCRPC. The resulting stemness signature was then validated in a completely held-out cohort of 80 patients with mCRPC profiled by tumor RNA sequencing. Conclusions: We analyzed a total of 220 patients with mCRPC, validated the importance of cell-free AR/enhancer alterations as a prognostic biomarker in lethal mCRPC, and showed that the underlying mechanism for lethality involves reprogramming developmental states toward increased stemness. See related commentary by Nawfal et al., p. 7

Abstract Introduction Men with African ancestry have the highest incidence and mortality rates of prostate cancer (PCa) worldwide. Methods This study aimed to identify differentially methylated genes between tumor vs. adjacent normal and aggressive vs. indolent PCa in 121 African American patients. Epigenome‐wide DNA methylation patterns in tumor DNA were assessed using the human Illumina Methylation EPIC V1 array. Results Around 5,139 differentially methylated CpG‐sites (q < 0.01, lΔβl > 0.2) were identified when comparing normal vs. tumor, with an overall trend of hypermethylation in prostate tumors. Multiple representative differentially methylated regions (DMRs), including immune‐related genes, such as CD40 , Galectin3 , OX40L , and STING , were detected in prostate tumors when compared to adjacent normal tissues. Based on an epigenetic clock model, we observed that tumors’ total number of stem cell divisions and the stem cell division rate were significantly higher than adjacent normal tissues. Regarding PCa aggressiveness, 2,061 differentially methylated CpG‐sites (q < 0.05, lΔβl > .05) were identified when the grade group (GG)1 was compared with GG4/5. Among these 2,061 CpG sites, 155 probes were consistently significant in more than one comparison. Among these genes, several immune system genes, such as COL18A1 , S100A2 , ITGA4 , HLA‐C , and ADCYAP1 , have previously been linked to tumor progression in PCa. Conclusion Several differentially methylated genes involved in immune‐oncologic pathways associated with disease risk or aggressiveness were identified. In addition, 261 African American‐specific differentially methylated genes related to the risk of PCa were identified. These results can shedlight on potential mechanisms contributing to PCa disparities in the African American Population.

Abstract Aims Hospitalized patients with heart failure (HF) are a heterogeneous population, with multiple phenotypes proposed. Prior studies have not examined the biological phenotypes of critically ill patients with HF admitted to the contemporary cardiac intensive care unit (CICU). We aimed to leverage unsupervised machine learning to identify previously unknown HF phenotypes in a large and diverse cohort of patients with HF admitted to the CICU. Methods We screened 6008 Mayo Clinic CICU patients with an admission diagnosis of HF from 2007 to 2018 and included those without missing values for common laboratory tests. Consensus k-means clustering was performed based on 10 common admission laboratory values (potassium, chloride, anion gap, blood urea nitrogen, haemoglobin, red blood cell distribution width, mean corpuscular volume, platelet count, white blood cell count and neutrophil-to-lymphocyte ratio). In-hospital mortality was evaluated using logistic regression, and 1 year mortality was evaluated using Cox proportional hazard models after multivariable adjustment. Results Among 4877 CICU patients with HF who had complete admission laboratory data (mean age 69.4 years, 38.4% females), we identified five clusters with divergent demographics, comorbidities, laboratory values, admission diagnoses and use of critical care therapies. We labelled these clusters based on the characteristic laboratory profile of each group: uncomplicated (25.7%), iron-deficient (14.5%), cardiorenal (18.4%), inflamed (22.3%) and hypoperfused (19.2%). In-hospital mortality occurred in 10.7% and differed between the phenotypes: uncomplicated, 2.7% (reference); iron-deficient, 8.1% [adjusted odds ratio (OR) 2.18 (1.38–3.48), P &lt; 0.001]; cardiorenal, 10.3% [adjusted OR 2.11 (1.37–3.32), P &lt; 0.001]; inflamed, 12.5% [adjusted OR 1.79 (1.18–2.76), P = 0.007]; and hypoperfused, 21.9% [adjusted OR 4.32 (2.89–6.62), P &lt; 0.001]. These differences in mortality between phenotypes were consistent when patients were stratified based on demographics, aetiology, admission diagnoses, mortality risk scores, shock severity and systolic function. One-year mortality occurred in 31.5% and differed between the phenotypes: uncomplicated, 11.9% (reference); inflamed, 26.8% [adjusted hazard ratio (HR) 1.56 (1.27–1.92), P &lt; 0.001]; iron-deficient, 33.8% [adjusted HR 2.47 (2.00–3.04), P &lt; 0.001]; cardiorenal, 41.2% [adjusted HR 2.41 (1.97–2.95), P &lt; 0.001]; and hypoperfused, 52.3% [adjusted HR 3.43 (2.82–4.18), P &lt; 0.001]. Similar findings were observed for post-discharge 1 year mortality. Conclusions Unsupervised machine learning clustering can identify multiple distinct clinical HF phenotypes within the CICU population that display differing mortality profiles both in-hospital and at 1 year. Mortality was lowest for the uncomplicated HF phenotype and highest for the hypoperfused phenotype. The inflamed phenotype had comparatively higher in-hospital mortality yet lower post-discharge mortality, suggesting divergent short-term and long-term prognosis.

Objectives: Nonoperative management vs. early reconstruction for partial tears of the medial ulnar collateral ligament (MUCL) remains controversial, with the most common treatment options for partial tears consisting of rest, rehab, platelet rich plasma (PRP), and/or surgical intervention. However, whether the improved outcomes reported for treatments such as MUCL reconstruction (UCLR) or nonoperative management with a series of PRP injections justifies their increased upfront costs remains unknown. Thus, the purpose of this study was to compare the cost-effectiveness of an initial trial of physical therapy alone, an initial trial of physical therapy plus a series of PRP injections, and early UCLR to determine the preferred cost-effective treatment strategy for baseball pitchers with partial tears of the MUCL. Methods: A Markov Chain Monte Carlo probabilistic model was developed to evaluate the outcomes and costs of 1,000 simulated pitchers undergoing nonoperative management with and without PRP vs. early UCLR for partial MUCL tears. Utility values, RTP rates, and transition probabilities were derived from the published literature. Costs were determined based on the typical patient undergoing each treatment strategy at our institution. Outcome measures included costs, acquired playing-years (PYs), and the incremental cost-effectiveness ratio (ICER). Results: Mean total costs resulting from nonoperative management without PRP, nonoperative management with PRP, and early UCLR were $22,520, $24,800, and $43,992, respectively. On average, early UCLR produced an additional 4.0 PYs over the 10-year time horizon relative to nonoperative management, resulting in an ICER of $5,395/PY, which falls well below the $50,000 willingness-to-pay threshold (WTP). Overall, early UCLR was determined the preferred cost-effective strategy in 77.5% of pitchers included in the microsimulation model, with nonoperative management with PRP determined the preferred strategy in 15% of pitchers and nonoperative management alone in 7.5% of pitchers. Conclusions: Based on Monte Carlo microsimulation and probabilistic sensitivity analysis, early UCLR was demonstrated to be more cost-effective than an initial trial of nonoperative management for partial tears of the MUCL for the majority of high-level baseball pitchers. It is important to note that this model does not consider the unique experiences, goals, situations, career trajectory, and pitching horizons of individual patients, and thus a shared decision-making discussion should be conducted regarding optimal initial treatment for partial MUCL tears. This is particularly true as many athletes can successfully be treated non-operatively, which generally results in a quicker return to play when successful compared to surgery.

AbstractPurposeThe present study reviews the available scientific literature on artificial intelligence (AI)‐assisted ultrasound‐guided regional anaesthesia (UGRA) and evaluates the reported intraprocedural parameters and postprocedural outcomes.MethodsA literature search was performed on 19 September 2023, using the Medline, EMBASE, CINAHL, Cochrane Library and Google Scholar databases by experts in electronic searching. All study designs were considered with no restrictions regarding patient characteristics or cohort size. Outcomes assessed included the accuracy of AI‐model tracking, success at the first attempt, differences in outcomes between AI‐assisted and unassisted UGRA, operator feedback and case‐report data.ResultsA joint adaptive median binary pattern (JAMBP) has been applied to improve the tracking procedure, while a particle filter (PF) is involved in feature extraction. JAMBP combined with PF was most accurate on all images for landmark identification, with accuracy scores of 0.83, 0.93 and 0.93 on original, preprocessed and filtered images, respectively. Evaluation of first‐attempt success of spinal needle insertion revealed first‐attempt success in most patients. When comparing AI application versus UGRA alone, a significant statistical difference (p < 0.05) was found for correct block view, correct structure identification and decrease in mean injection time, needle track adjustments and bone encounters in favour of having AI assistance. Assessment of operator feedback revealed that expert and nonexpert operator feedback was overall positive.ConclusionAI appears promising to enhance UGRA as well as to positively influence operator training. AI application of UGRA may improve the identification of anatomical structures and provide guidance for needle placement, reducing the risk of complications and improving patient outcomes.Level of EvidenceLevel IV.

Abstract Background This investigator-initiated phase II trial aimed to evaluate the efficacy of cabozantinib in combination with nivolumab and ipilimumab (CaboNivoIpi) in previously treated patients with radioactive iodine-refractory differentiated thyroid cancer. Methods Eligible patients with radioactive iodine-refractory differentiated thyroid cancer who progressed on 1 prior line of vascular endothelial growth factor receptor-targeted therapy received a 2-week run-in of cabozantinib monotherapy followed by CaboNivoIpi for 4 cycles (cycle length = 6 weeks), followed by cabozantinib plus nivolumab (cycle length = 4 weeks) until disease progression. The primary endpoint was objective response rate (ORR) within the first 6 months of treatment. A Simon optimal 2-stage design allowed for an interim analysis after accrual of 10 evaluable patients. At least 5 responses were needed to proceed to stage 2. Results Among 11 patients enrolled, the median age was 69 years. Prior vascular endothelial growth factor receptor-targeted therapies included lenvatinib, pazopanib, and sorafenib plus everolimus. Median follow-up was 13.4 months. Among 10 evaluable patients, ORR within the first 6 months of treatment was 10% (1 partial response). Median progression-free survival was 9 months (95% CI, 3.0–not reached) and median overall survival was 19.2 months (95% CI, 4.6–not reached). Grade 3/4 treatment-related adverse events (AEs) were noted in 55% (6/11) and grade 5 AEs in 18% (2/11) of patients. The most common treatment-related AE was hypertension. The study did not reach its prespecified efficacy threshold. Conclusion CaboNivoIpi had low ORRs and a high rate of grade ≥3 treatment-related AEs. Clinical Trial Registration NCT03914300

Background: The use of telerehabilitation after sports medicine procedures such as an arthroscopic rotator cuff repair (ARCR) and anterior cruciate ligament reconstruction (ACLR) has rapidly increased in recent years; however, the functional outcomes and patient satisfaction with telerehabilitation compared to in-person rehabilitation remain unclear. The purpose of this study was to compare the functional outcomes and patient satisfaction with telerehabilitation to in-person rehabilitation in a randomized controlled trial after two common sports procedures, ARCR and ACLR. Methods: Two randomized controlled trials were conducted involving patients scheduled to undergo ARCR or ACLR by one of six fellowship-trained sports medicine surgeons between October 2020 and November 2021. Each trial had an enrollment goal of 60 patients. Subjects were randomized 1:1 to receive telerehabilitation or in-person rehabilitation postoperatively. Functional outcome and satisfaction metrics were collected at baseline and at post-operative visits and compared between groups. Results: In total, 16 ACLR patients were enrolled, of whom 10 (62.5%) were assigned to in-person rehabilitation and 6 (37.5%) to telerehabilitation. Additionally, 32 ARCR patients were enrolled, of whom 20 (62.5%) were assigned in-person rehabilitation and 12 (37.5%) were assigned telerehabilitation. In total, of the 30 patients assigned to in-person rehabilitation, none reported a crossover to telerehabilitation. Of the 18 patients initially assigned to telerehabilitation, 12 (67%) completed the final follow-up survey, of which 11 (92%) reported a crossover; 9 patients completed in-person rehabilitation and 2 patients completed hybrid in-person and telerehabilitation. Conclusions: Patients preferred in-person rehabilitation compared to telerehabilitation after ACLR and ARCR, as evidenced by the nearly ubiquitous crossover from telerehabilitation to in-person rehabilitation in both studies. Our findings suggest that telerehabilitation protocols still need to be perfected, and that there may be a role for a hybrid in-person and tele-rehab model.

AbstractBackgroundImmune thrombocytopenia (ITP) and Evans syndrome (ES) are manifestations of immune dysregulation. Genetic variants in immune‐related genes have been identified in patients with ITP and especially ES. We aimed to explore familial autoimmunity in patients with ITP and ES to understand possible contributions to chronicity.ProcedureWe assessed family history in two ways: via patient report for ITP and ES and by population‐based analysis using the Utah Population Database (UPDB) for ITP. A total of 266 patients with ITP and 21 patients with ES were identified via chart review, and 252 of the 266 patients with ITP were also identified in the UPDB.ResultsChart review showed familial autoimmunity in 29/182 (15.9%) and 25/84 (29.8%) of patients with newly diagnosed+persistent (nd+p) ITP and chronic ITP (cITP), respectively, (p = .009). The UPDB analysis revealed that autoimmunity in relatives of patients with nd+pITP was higher than in relatives of controls (odds ratio [OR]: 1.69 [1.19–2.41], p = .004), but was not significantly increased in relatives of patients with cITP (OR 1.10 [0.63–1.92], p = .734). Incomplete family history in medical records likely contributed to the observed discrepancy.ConclusionsThe findings suggest that familial autoimmunity may have a stronger association with the development of ITP rather than its duration. Twelve (57.1%) patients with ES reported autoimmunity in their relatives. UPDB analysis was omitted due to the small number of patients with ES. The use of population databases offers a unique opportunity to assess familial health and may provide clues about contributors to immune dysregulation features within families.

Abstract Explorative data analysis (EDA) is a critical step in scientific projects, aiming to uncover valuable insights and patterns within data. Traditionally, EDA involves manual inspection, visualization, and various statistical methods. The advent of artificial intelligence (AI) and machine learning (ML) has the potential to improve EDA, offering more sophisticated approaches that enhance its efficacy. This review explores how AI and ML algorithms can improve feature engineering and selection during EDA, leading to more robust predictive models and data‐driven decisions. Tree‐based models, regularized regression, and clustering algorithms were identified as key techniques. These methods automate feature importance ranking, handle complex interactions, perform feature selection, reveal hidden groupings, and detect anomalies. Real‐world applications include risk prediction in total hip arthroplasty and subgroup identification in scoliosis patients. Recent advances in explainable AI and EDA automation show potential for further improvement. The integration of AI and ML into EDA accelerates tasks and uncovers sophisticated insights. However, effective utilization requires a deep understanding of the algorithms, their assumptions, and limitations, along with domain knowledge for proper interpretation. As data continues to grow, AI will play an increasingly pivotal role in EDA when combined with human expertise, driving more informed, data‐driven decision‐making across various scientific domains. Level of Evidence: Level V ‐ Expert opinion.