An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs.

BACKGROUND: Neuroblastoma is a common pediatric cancer, where preclinical studies suggest that a mesenchymal-like gene expression program contributes to chemotherapy resistance. However, clinical outcomes remain poor, implying we need a better understanding of the relationship between patient tumor heterogeneity and preclinical models. RESULTS: Here, we generate single-cell RNA-seq maps of neuroblastoma cell lines, patient-derived xenograft models (PDX), and a genetically engineered mouse model (GEMM). We develop an unsupervised machine learning approach ("automatic consensus nonnegative matrix factorization" (acNMF)) to compare the gene expression programs found in preclinical models to a large cohort of patient tumors. We confirm a weakly expressed, mesenchymal-like program in otherwise adrenergic cancer cells in some pre-treated high-risk patient tumors, but this appears distinct from the presumptive drug-resistance mesenchymal programs evident in cell lines. Surprisingly, however, this weak-mesenchymal-like program is maintained in PDX and could be chemotherapy-induced in our GEMM after only 24 h, suggesting an uncharacterized therapy-escape mechanism. CONCLUSIONS: Collectively, our findings improve the understanding of how neuroblastoma patient tumor heterogeneity is reflected in preclinical models, provides a comprehensive integrated resource, and a generalizable set of computational methodologies for the joint analysis of clinical and pre-clinical single-cell RNA-seq datasets.

An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs.

Neuroblastoma is a common pediatric cancer, where preclinical studies suggest that a mesenchymal-like gene expression program contributes to chemotherapy resistance. However, clinical outcomes remain poor, implying we need a better understanding of the relationship between patient tumor heterogeneity and preclinical models. Here, we generated single-cell RNA-seq maps of neuroblastoma cell lines, patient-derived xenograft models (PDX), and a genetically engineered mouse model (GEMM). We developed an unsupervised machine learning approach ('automatic consensus nonnegative matrix factorization' (acNMF)) to compare the gene expression programs found in preclinical models to a large cohort of patient tumors. We confirmed a weakly expressed, mesenchymal-like program in otherwise adrenergic cancer cells in some pre-treated high-risk patient tumors, but this appears distinct from the presumptive drug-resistance mesenchymal programs evident in cell lines. Surprisingly however, this weak-mesenchymal-like program was maintained in PDX and could be chemotherapy-induced in our GEMM after only 24 hours, suggesting an uncharacterized therapy-escape mechanism. Collectively, our findings improve the understanding of how neuroblastoma patient tumor heterogeneity is reflected in preclinical models, provides a comprehensive integrated resource, and a generalizable set of computational methodologies for the joint analysis of clinical and pre-clinical single-cell RNA-seq datasets.

Bone morphogenetic protein (BMP) signaling determines neuroblastoma cell fate and sensitivity to retinoic acid.

Retinoic acid (RA) is a standard-of-care neuroblastoma drug thought to be effective by inducing differentiation. Curiously, RA has little effect on primary human tumors during upfront treatment but can eliminate neuroblastoma cells from the bone marrow during post-chemo consolidation therapy-a discrepancy that has never been explained. To investigate this, we treated a large cohort of neuroblastoma cell lines with RA and observed that the most RA-sensitive cells predominantly undergo apoptosis or senescence, rather than differentiation. We conducted genome-wide CRISPR knockout screens under RA treatment, which identified BMP signaling as controlling the apoptosis/senescence vs differentiation cell fate decision and determining RA's overall potency. We then discovered that BMP signaling activity is markedly higher in neuroblastoma patient samples at bone marrow metastatic sites, providing a plausible explanation for RA's ability to clear neuroblastoma cells specifically from the bone marrow, seemingly mimicking interactions between BMP and RA during normal development.

Comparison of the ABC and ACMG systems for variant classification.

The ABC and ACMG variant classification systems were compared by asking mainly European clinical laboratories to classify variants in 10 challenging cases using both systems, and to state if the variant in question would be reported as a relevant result or not as a measure of clinical utility. In contrast to the ABC system, the ACMG system was not made to guide variant reporting but to determine the likelihood of pathogenicity. Nevertheless, this comparison is justified since the ACMG class determines variant reporting in many laboratories. Forty-three laboratories participated in the survey. In seven cases, the classification system used did not influence the reporting likelihood when variants labeled as "maybe report" after ACMG-based classification were included. In three cases of population frequent but disease-associated variants, there was a difference in favor of reporting after ABC classification. A possible reason is that ABC step C (standard variant comments) allows a variant to be reported in one clinical setting but not another, e.g., based on Bayesian-based likelihood calculation of clinical relevance. Finally, the selection of ACMG criteria was compared between 36 laboratories. When excluding criteria used by less than four laboratories (<10%), the average concordance rate was 46%. Taken together, ABC-based classification is more clear-cut than ACMG-based classification since molecular and clinical information is handled separately, and variant reporting can be adapted to the clinical question and phenotype. Furthermore, variants do not get a clinically inappropriate label, like pathogenic when not pathogenic in a clinical context, or variant of unknown significance when the significance is known.

Gender differences in learning and study strategies impact medical students' preclinical and USMLE step 1 examination performance.

BACKGROUND: Evaluation of students' learning strategies can enhance academic support. Few studies have investigated differences in learning strategies between male and female students as well as their impact on United States Medical Licensing Examination® (USMLE) Step 1 and preclinical performance. METHODS: The Learning and Study Strategies Inventory (LASSI) was administered to the classes of 2019-2024 (female (n = 350) and male (n = 262)). Students' performance on preclinical first-year (M1) courses, preclinical second-year (M2) courses, and USMLE Step 1 was recorded. An independent t-test evaluated differences between females and males on each LASSI scale. A Pearson product moment correlation determined which LASSI scales correlated with preclinical performance and USMLE Step 1 examinations. RESULTS: Of the 10 LASSI scales, Anxiety, Attention, Information Processing, Selecting Main Idea, Test Strategies and Using Academic Resources showed significant differences between genders. Females reported higher levels of Anxiety (p < 0.001), which significantly influenced their performance. While males and females scored similarly in Concentration, Motivation, and Time Management, these scales were significant predictors of performance variation in females. Test Strategies was the largest contributor to performance variation for all students, regardless of gender. CONCLUSION: Gender differences in learning influence performance on STEP1. Consideration of this study's results will allow for targeted interventions for academic success.

CYP3A5 unexpectedly regulates glucose metabolism through the AKT-TXNIP-GLUT1 axis in pancreatic cancer.

CYP3A5 is a cytochrome P450 (CYP) enzyme that metabolizes drugs and contributes to drug resistance in cancer. However, it remains unclear whether CYP3A5 directly influences cancer progression. In this report, we demonstrate that CYP3A5 regulates glucose metabolism in pancreatic ductal adenocarcinoma. Multi-omics analysis showed that CYP3A5 knockdown results in a decrease in various glucose-related metabolites through its effect on glucose transport. A mechanistic study revealed that CYP3A5 enriches the glucose transporter GLUT1 at the plasma membrane by restricting the translation of TXNIP, a negative regulator of GLUT1. Notably, CYP3A5-generated reactive oxygen species were proved to be responsible for attenuating the AKT-4EBP1-TXNIP signaling pathway. CYP3A5 contributes to cell migration by maintaining high glucose uptake in pancreatic cancer. Taken together, our results, for the first time, reveal a role of CYP3A5 in glucose metabolism in pancreatic ductal adenocarcinoma and identify a novel mechanism that is a potential therapeutic target.

Factors Influencing Recovery From Pediatric Stroke Based on Discussions From a UK-Based Online Stroke Community: Qualitative Thematic Study.

BACKGROUND: The incidence of stroke in children is low, and pediatric stroke rehabilitation services are less developed than adult ones. Survivors of pediatric stroke have a long poststroke life expectancy and therefore have the potential to experience impairments from their stroke for many years. However, there are relatively few studies characterizing these impairments and what factors facilitate or counteract recovery. OBJECTIVE: This study aims to characterize the main barriers to and facilitators of recovery from pediatric stroke. A secondary aim was to explore whether these factors last into adulthood, whether they change, or if new factors impacting recovery emerge in adulthood. METHODS: We performed a qualitative thematic analysis based on posts from a population of participants from a UK-based online stroke community, active between 2004 and 2011. The analysis focused on users who talked about their experiences with pediatric stroke, as identified by a previous study. The posts were read by 3 authors, and factors influencing recovery from pediatric stroke were mapped into 4 areas: medical, physical, emotional, and social. Factors influencing recovery were divided into short-term and long-term factors. RESULTS: There were 425 posts relating to 52 survivors of pediatric stroke. Some survivors of stroke posted for themselves, while others were talked about by a third party (mostly parents; 31/35, 89% mothers). In total, 79% (41/52) of survivors of stroke were aged ≤18 years and 21% (11/52) were aged >18 years at the time of posting. Medical factors included comorbidities as a barrier to recovery. Medical interventions, such as speech and language therapy and physiotherapy, were also deemed useful. Exercise, particularly swimming, was deemed a facilitator. Among physical factors, fatigue and chronic pain could persist decades after a stroke, with both reported as a barrier to feeling fully recovered. Tiredness could worsen existing stroke-related impairments. Other long-standing impairments were memory loss, confusion, and dizziness. Among emotional factors, fear and uncertainty were short-term barriers, while positivity was a major facilitator in both short- and long-term recovery. Anxiety, grief, and behavioral problems hindered recovery. The social barriers were loneliness, exclusion, and hidden disabilities not being acknowledged by third parties. A good support network and third-party support facilitated recovery. Educational services were important in reintegrating survivors into society. Participants reported that worrying about losing financial support, such as disability allowances, and difficulties in obtaining travel insurance and driving licenses impacted recovery. CONCLUSIONS: The lived experience of survivors of pediatric stroke includes long-term hidden disabilities and barriers to rehabilitation. These are present in different settings, such as health care, schools, workplaces, and driving centers. Greater awareness of these issues by relevant professional groups may help ameliorate them.

Comparison of diagnostic spectrum between inflammation of unknown origin and fever of unknown origin: A systematic review and meta-analysis.

BACKGROUND: Patients with inflammation of unknown origin (IUO) and fever of unknown origin (FUO) are commonly considered a single population. Differences in underlying causes between both groups may steer the diagnostic work-up. METHODS: PubMed, Embase, Web of Science, and ClinicalTrials.gov were searched from July 2009 through December 2023. Studies including both FUO and IUO patients with a sample size of ≥20 were considered. The primary outcome was the difference in the rate of patients affected by predefined diagnostic categories according to meeting FUO or IUO criteria. Data were pooled using random-effects models. RESULTS: A total of 8 studies met criteria for inclusion, with a total of 1452 patients (466 with IUO and 986 with FUO). The median rate of IUO patients among the included studies was 32 % (range 25-39 %). Patients with IUO had a lower likelihood of infection (OR 0.59 [95 % CI; 0.36-0.95]; I2 0 %). There were no significant differences in the rate of noninfectious inflammatory disorders, malignancies, miscellaneous disorders, or remaining undiagnosed. Comparison of diagnostic subgroups revealed that IUO patients were less likely to have systemic autoinflammatory disorders (OR 0.17 [95 % CI, 0.05-0.58]; I2 42 %) and more likely to have vasculitis (OR 2.04 [95 % CI, 1.23-3.38]; I2 21 %) and rheumatoid arthritis or spondylarthritis (OR 3.52 [95 % CI, 1.16-10.69]; I2 0 %). CONCLUSION: Based on our findings, there is little reason to assume that FUO and IUO patients would benefit from a different initial diagnostic approach.

Nuclear Medicine Imaging Tools in Fever of Unknown Origin: Time for a Revisit and Appropriate Use Criteria.

Fever of unknown origin (FUO) is a clinical conundrum for patients and clinicians alike, and imaging studies are often performed as part of the diagnostic workup of these patients. Recently, the Society of Nuclear Medicine and Molecular Imaging convened and approved a guideline on the use of nuclear medicine tools for FUO. The guidelines support the use of 2-18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) in adults and children with FUO. 18F-FDG PET/CT allows detection and localization of foci of hypermetabolic lesions with high sensitivity because of the 18F-FDG uptake in glycolytically active cells that may represent inflammation, infection, or neoplasia. Clinicians should consider and insurers should cover 18F-FDG PET/CT when evaluating patients with FUO, particularly when other clinical clues and preliminary studies are unrevealing.

Local and global predictors of synapse elimination during motor learning.

During learning, synaptic connections between excitatory neurons in the brain display considerable dynamism, with new connections being added and old connections eliminated. Synapse elimination offers an opportunity to understand the features of synapses that the brain deems dispensable. However, with limited observations of synaptic activity and plasticity in vivo, the features of synapses subjected to elimination remain poorly understood. Here, we examined the functional basis of synapse elimination in the apical dendrites of L2/3 neurons in the primary motor cortex throughout motor learning. We found no evidence that synapse elimination is facilitated by a lack of activity or other local forms of plasticity. Instead, eliminated synapses display asynchronous activity with nearby synapses, suggesting that functional synaptic clustering is a critical component of synapse survival. In addition, eliminated synapses show delayed activity timing with respect to postsynaptic output. Thus, synaptic inputs that fail to be co-active with their neighboring synapses or are mistimed with neuronal output are targeted for elimination.

Exploring the Types of Social Support Exchanged by Survivors of Pediatric Stroke and Their Families in an Online Peer Support Community: Qualitative Thematic Analysis.

BACKGROUND: Pediatric stroke is relatively rare and underresearched, and there is little awareness of its occurrence in wider society. There is a paucity of literature on the effectiveness of interventions to improve rehabilitation and the services available to survivors. Access to online health communities through the internet may be a means of support for patients with pediatric stroke and their families during recovery; however, little research has been done in this area. OBJECTIVE: This study aims to identify the types of social support provided by an online peer support group to survivors of pediatric stroke and their families. METHODS: This was a qualitative thematic analysis of posts from a pediatric stroke population on a UK online stroke community active between 2004 and 2011. The population was split into 2 groups based on whether stroke survivors were aged ≤18 years or aged >18 years at the time of posting. The posts were read by 2 authors who used the adapted Social Support Behavior Code to analyze the types of social support exchanged. RESULTS: A total of 52 participants who experienced a pediatric stroke were identified, who posted a total of 425 messages to the community. About 41 survivors were aged ≤18 years at the time of posting and were written about by others (31/35 were mothers), while 11 were aged >18 years and were writing about themselves. Survivors and their families joined together in discussion threads. Support was offered and received by all participants, regardless of age. Of all 425 posts, 193 (45.4%) contained at least 1 instance of social support. All 5 types of social support were identified: informational, emotional, network, esteem support, and tangible aid. Informational and emotional support were most commonly exchanged. Emotional support was offered more often than informational support among participants aged ≤18 years at the time of posting; this finding was reversed in the group aged >18 years. Network support and esteem support were less commonly exchanged. Notably, the access subcategory of network support was not exchanged with the community. Tangible aid was the least commonly offered type of support. The exchanged social support provided insight into rehabilitation interventions and the unmet needs of pediatric stroke survivors. CONCLUSIONS: We found evidence of engagement of childhood stroke survivors and their families in an online stroke community, with peer support being exchanged between both long- and short-term survivors of pediatric stroke. Engagement of long-term survivors of pediatric stroke through the online community was key, as they were able to offer informational support from lived experience. Further interventional research is needed to assess health and rehabilitation outcomes from engagement with online support groups. Research is also needed to ensure safe, nurturing online communities.

Development of a Consensus-Based List of Potential Quality Indicators for Fever and Inflammation of Unknown Origin.

With a growing emphasis on value-based reimbursement, developing quality indicators for infectious diseases has gained attention. Quality indicators for fever of unknown origin and inflammation of unknown origin are lacking. An assembled group of international experts developed 12 quality measures for these conditions, which could be validated with additional study.

A CRISPR-drug perturbational map for identifying compounds to combine with commonly used chemotherapeutics.

Combination chemotherapy is crucial for successfully treating cancer. However, the enormous number of possible drug combinations means discovering safe and effective combinations remains a significant challenge. To improve this process, we conduct large-scale targeted CRISPR knockout screens in drug-treated cells, creating a genetic map of druggable genes that sensitize cells to commonly used chemotherapeutics. We prioritize neuroblastoma, the most common extracranial pediatric solid tumor, where ~50% of high-risk patients do not survive. Our screen examines all druggable gene knockouts in 18 cell lines (10 neuroblastoma, 8 others) treated with 8 widely used drugs, resulting in 94,320 unique combination-cell line perturbations, which is comparable to the largest existing drug combination screens. Using dense drug-drug rescreening, we find that the top CRISPR-nominated drug combinations are more synergistic than standard-of-care combinations, suggesting existing combinations could be improved. As proof of principle, we discover that inhibition of PRKDC, a component of the non-homologous end-joining pathway, sensitizes high-risk neuroblastoma cells to the standard-of-care drug doxorubicin in vitro and in vivo using patient-derived xenograft (PDX) models. Our findings provide a valuable resource and demonstrate the feasibility of using targeted CRISPR knockout to discover combinations with common chemotherapeutics, a methodology with application across all cancers.

Molecular Imaging of Infections: Emerging Techniques for Pathogen-Specific Diagnosis and Guided Therapy.

Evaluation of patients that may be infected is challenging. Imaging to identify or localize a site of infection is often limited because of the nonspecific nature of the findings on conventional imaging modalities. Available imaging methods lack the ability to determine if antibiotics are reaching the site of infection and are not optimized to follow response to therapy. Positron emission tomography (PET) is a method by which radiolabeled molecules can be used to detect metabolic perturbations or levels of expression of specific targets. The most common PET agent is the glucose analog 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG). 18F-FDG has some applicability to localizing a site of infection, but its lack of specificity limits its usefulness. There is a need for the development of pathogen-specific PET radiotracers to address the imaging shortcomings noted above. Preclinical and clinical progress has been made, but significant challenges remain.

The penetrance of rare variants in cardiomyopathy-associated genes: A cross-sectional approach to estimating penetrance for secondary findings.

Understanding the penetrance of pathogenic variants identified as secondary findings (SFs) is of paramount importance with the growing availability of genetic testing. We estimated penetrance through large-scale analyses of individuals referred for diagnostic sequencing for hypertrophic cardiomyopathy (HCM; 10,400 affected individuals, 1,332 variants) and dilated cardiomyopathy (DCM; 2,564 affected individuals, 663 variants), using a cross-sectional approach comparing allele frequencies against reference populations (293,226 participants from UK Biobank and gnomAD). We generated updated prevalence estimates for HCM (1:543) and DCM (1:220). In aggregate, the penetrance by late adulthood of rare, pathogenic variants (23% for HCM, 35% for DCM) and likely pathogenic variants (7% for HCM, 10% for DCM) was substantial for dominant cardiomyopathy (CM). Penetrance was significantly higher for variant subgroups annotated as loss of function or ultra-rare and for males compared to females for variants in HCM-associated genes. We estimated variant-specific penetrance for 316 recurrent variants most likely to be identified as SFs (found in 51% of HCM- and 17% of DCM-affected individuals). 49 variants were observed at least ten times (14% of affected individuals) in HCM-associated genes. Median penetrance was 14.6% (±14.4% SD). We explore estimates of penetrance by age, sex, and ancestry and simulate the impact of including future cohorts. This dataset reports penetrance of individual variants at scale and will inform the management of individuals undergoing genetic screening for SFs. While most variants had low penetrance and the costs and harms of screening are unclear, some individuals with highly penetrant variants may benefit from SFs.

#AMRrounds: a systematic educational approach for navigating bench to bedside antimicrobial resistance.

Antimicrobial resistance (AMR) continues to serve as a major global health crisis. Clinicians practising in this modern era are faced with ongoing challenges in the therapeutic management of patients suffering from antimicrobial-resistant infections. A strong educational understanding and synergistic application of clinical microbiology, infectious disease and pharmacological concepts can assist the adventuring clinician in the navigation of such cases. Important items include mobilizing laboratory testing for pathogen identification and susceptibility data, harnessing an understanding of intrinsic pathogen resistance, acknowledging epidemiological resistance trends, recognizing acquired AMR mechanisms, and consolidating these considerations when constructing an ideal pharmacological plan. In this article, we outline a novel framework by which to systematically approach clinical AMR, encourage AMR-related education and optimize therapeutic decision-making in AMR-related illnesses.