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A comparative biometric analysis indicates Clqtn/5 plays a role in ocular growth
No full textMany people suffer from hyperopia (farsightedness), a condition characterized by refractive error where light is not focused on the retina that causes blurred vision. Most of hyperopia cases result from microphthalmia, a condition resulting in smaller eyes as characterized by reduced axial length; however, the cellular and molecular basis of this condition is poorly understood. This study aims to investigate three genes when mutated are implicated in microphthalmia (Mfrp, Prss56, Adiporl) and to assess a prospective microphthalmia gene,Clqtnf5, at an early developmental timepoint (postnatal day 18. The genes were investigated through ocular biometric measurements of strains carrying mutant alleles of these genes. Measurements included axial length, corneal radius of curvature, and posterior ocular surface area. Our results reveal microphthalmia in all models examined and establishes C 1 qtnf5 as a gene that influences ocular growth at early stages of development
Characterizing the dynamics and cell state specificity of DNA methylation and demethylation at the BRCA1 promoter
No full textTriple-negative breast cancer (TNBC) remains a formidable health challenge, particularly for historically understudied populations such as Black women in the United States, in which individuals are at a three-fold risk of developing this aggressive subtype, and 30% more likely to succumb to its effects, compared to non-Hispanic white women with the same diagnosis. In a 2022 study Menghi et al. investigated a mechanism for chemotherapy resistance in TNBC with homologous recombination deficiency (HRD) uncovering the integral role of reversible BRCA1 promoter hypermethylation in platinum-based therapy resistance. Here, we report on the dynamics and cell state specificity of both the gain and loss of BRCA1 promoter methylation in a 353 bp region in the core promoter region, the only differentially methylated region between BRCA1 mutated versus BRCA1 methylated cancer genomes.
Utilizing a unique model system that induces methylation in cis in induced pluripotent stem cell lines (iPSCs) but not in transformed cell lines, we noted that methylation occurs in a processive manner from the 3’ untranslated region (UTR) and stabilizes at a heterozygous state at approximately 100 days.
Employing patient-derived xenograft (PDX) mouse models treated with regiments of chemotherapeutic agents and a noteworthy longitudinal series from a patient who underwent treatment we account for a significant pattern of demethylation at CpG sites in the promoter region that may correlate with BRCA1 re-expression that accounts for enhanced DNA repair and adaptative resistance to therapies in the clinical setting
Bone marrow transplantation increases sulfatase activity in somatic tissues in a multiple sulfatase deficiency mouse model.
Get PDFBACKGROUND: Multiple Sulfatase Deficiency (MSD) is an ultra-rare autosomal recessive disorder characterized by deficient enzymatic activity of all known sulfatases. MSD patients frequently carry two loss of function mutations in the SUMF1 gene, encoding a formylglycine-generating enzyme (FGE) that activates 17 different sulfatases. MSD patients show common features of other lysosomal diseases like mucopolysaccharidosis and metachromatic leukodystrophy, including neurologic impairments, developmental delay, and visceromegaly. There are currently no approved therapies for MSD patients. Hematopoietic stem cell transplant (HSCT) has been applied with success in the treatment of certain lysosomal diseases. In HSCT, donor-derived myeloid cells are a continuous source of active sulfatase enzymes that can be taken up by sulfatase-deficient host cells. Thus, HSCT could be a potential approach for the treatment of MSD.
METHODS: To test this hypothesis, we used a clinically relevant mouse model for MSD, B6-Sumf1
RESULTS: After 10 months post-transplant, flow cytometric analysis shows an average of 90% of circulating leukocytes of donor origin (Sumf1
CONCLUSIONS: Our results indicate that HSCT could be a suitable approach to treat MSD-pathology affecting peripheral organs, however that benefit to CNS pathology might be limited
Comprehensive metabolomic analysis identifies key biomarkers and modulators of immunotherapy response in NSCLC patients.
No full textAlthough immune checkpoint inhibitors (ICIs) have revolutionized immuno-oncology with effective clinical responses, only 30 to 40 % of patients respond to ICIs, highlighting the need for reliable biomarkers to predict and enhance therapeutic outcomes. This study investigated how amino acid, glycolysis, and bile acid metabolism affect ICI efficacy in non-small cell lung cancer (NSCLC) patients. Through targeted metabolomic profiling and machine learning analysis, we identified amino acid metabolism as a key factor, with histidine (His) linked to favorable outcomes and homocysteine (HCys), phenylalanine (Phe), and sarcosine (Sar) linked to poor outcomes. Importantly, the His/HCys+Phe+Sar ratio emerges as a robust biomarker. Furthermore, we emphasize the role of glycolysis-related metabolites, particularly lactate. Elevated lactate levels post-immunotherapy treatment correlate with poorer outcomes, underscoring lactate as a potential indicator of treatment efficacy. Moreover, specific bile acids, glycochenodeoxycholic acid (GCDCA) and taurolithocholic acid (TLCA), are associated with better survival and therapeutic response. Particularly, TLCA enhances T cell activation and anti-tumor immunity, suggesting its utility as a predictive biomarker and therapeutic agent. We also suggest a connection between gut microbiota and TLCA levels, with the Eubacterium genus modulating this relationship. Therefore, modulating specific metabolic pathways-particularly amino acid, glycolysis, and bile acid metabolism-could predict and enhance the efficacy of ICI therapy in NSCLC patients, with potential implications for personalized treatment strategies in immuno-oncology. ONE SENTENCE SUMMARY: Our study identifies metabolic biomarkers and pathways that could predict and enhance the outcomes of immune checkpoint inhibitor therapy in NSCLC patients
Oncogenic composite mutations can be predicted by co-mutations and their chromosomal location.
Get PDFGenetic heterogeneity in tumors can show a remarkable selectivity when two or more independent genetic events occur in the same gene. This phenomenon, called composite mutation, points toward a selective pressure, which frequently causes therapy resistance to mutation-specific drugs. Since composite mutations have been described to occur in sub-clonal populations, they are not always captured through biopsy sampling. Here, we provide a proof of concept to predict composite mutations to anticipate which patients might be at risk for sub-clonally driven therapy resistance. We found that composite mutations occur in 5% of cancer patients, mostly affecting the PIK3CA, EGFR, BRAF, and KRAS genes, which are common precision medicine targets. Furthermore, we found a strong and significant relationship between the frequencies of composite mutations with commonly co-occurring mutations in a non-composite context. We also found that co-mutations are significantly enriched on the same chromosome. These observations were independently confirmed using cell line data. Finally, we show the feasibility of predicting compositive mutations based on their co-mutations (AUC 0.62, 0.81, 0.82, and 0.91 for EGFR, PIK3CA, KRAS, and BRAF, respectively). This prediction model could help to stratify patients who are at risk of developing therapy resistance-causing mutations
Using paired-end read orientations to assess technical biases in capture Hi-C.
Get PDFHi-C and capture Hi-C (CHi-C) both leverage paired-end sequencing of chimeric fragments to gauge the strength of interactions based on the total number of paired-end reads mapped to a common pair of restriction fragments. Mapped paired-end reads can have four relative orientations, depending on the genomic positions and strands of the two reads. We assigned one paired-end read orientation to each of the four possible re-ligations that can occur between two given restriction fragments. In a large hematopoietic cell dataset, we determined the read pair counts of interactions separately for each orientation. Interactions with imbalances in the counts occur much more often than expected by chance for both Hi-C and CHi-C. Based on such imbalances, we identified target restriction fragments enriched at only one instead of both ends. By matching them to the baits used for the experiments, we confirmed our assignment of paired-end read orientations and gained insights that can inform bait design. An analysis of unbaited fragments shows that, beyond bait effects, other known types of technical biases are reflected in count imbalances. Taking advantage of distance-dependent contact frequencies, we assessed the impact of such biases. Our results have the potential to improve the design and interpretation of CHi-C experiments
Schizophrenia-Like Deficits and Impaired Glutamate/Gamma-aminobutyric acid Homeostasis in Zfp804a Conditional Knockout Mice.
No full textBACKGROUND AND HYPOTHESIS: Zinc finger protein 804A (ZNF804A) was the first genome-wide associated susceptibility gene for schizophrenia (SCZ) and played an essential role in the pathophysiology of SCZ by influencing neurodevelopment regulation, neurite outgrowth, synaptic plasticity, and RNA translational control; however, the exact molecular mechanism remains unclear.
STUDY DESIGN: A nervous-system-specific Zfp804a (ZNF804A murine gene) conditional knockout (cKO) mouse model was generated using clustered regularly interspaced short palindromic repeat/Cas9 technology and the Cre/loxP method.
RESULTS: Multiple and complex SCZ-like behaviors, such as anxiety, depression, and impaired cognition, were observed in Zfp804a cKO mice. Molecular biological methods and targeted metabolomics assay validated that Zfp804a cKO mice displayed altered SATB2 (a cortical superficial neuron marker) expression in the cortex; aberrant NeuN, cleaved caspase 3, and DLG4 (markers of mature neurons, apoptosis, and postsynapse, respectively) expressions in the hippocampus and a loss of glutamate (Glu)/γ-aminobutyric acid (GABA) homeostasis with abnormal GAD67 (Gad1) expression in the hippocampus. Clozapine partly ameliorated some SCZ-like behaviors, reversed the disequilibrium of the Glu/GABA ratio, and recovered the expression of GAD67 in cKO mice.
CONCLUSIONS: Zfp804a cKO mice reproducing SCZ-like pathological and behavioral phenotypes were successfully developed. A novel mechanism was determined in which Zfp804a caused Glu/GABA imbalance and reduced GAD67 expression, which was partly recovered by clozapine treatment. These findings underscore the role of altered gene expression in understanding the pathogenesis of SCZ and provide a reliable SCZ model for future therapeutic interventions and biomarker discovery
Lessons learned from 20 years of preclinical testing in pediatric cancers.
Get PDFPrograms for preclinical testing of targeted cancer agents in murine models of childhood cancers have been supported by the National Cancer Institute (NCI) since 2004. These programs were established to work collaboratively with industry partners to address the paucity of targeted agents for pediatric cancers compared with the large number of agents developed and approved for malignancies primarily affecting adults. The distinctive biology of pediatric cancers and the relatively small numbers of pediatric cancer patients are major challenges for pediatric oncology drug development. These factors are exacerbated by the division of cancers into multiple subtypes that are further sub-classified by their genomic properties. The imbalance between the large number of candidate agents and small patient populations requires careful prioritization of agents developed for adult cancers for clinical evaluation in children with cancer. The NCI-supported preclinical pediatric programs have published positive and negative results of efficacy testing for over 100 agents to aid the pediatric research community in identifying the most promising candidates to move forward for clinical testing in pediatric oncology. Here, we review and summarize lessons learned from two decades of experience with the design and execution of preclinical trials of antineoplastic agents in murine models of childhood cancers
Emerging CRISPR Therapies for Precision Gene Editing and Modulation in the Cardiovascular Clinic.
No full textPURPOSE OF REVIEW: Outline the growing suite of novel genome editing tools powered by CRISPR-Cas9 technology that are rapidly advancing towards the clinic for the treatment of cardiovascular disorders.
RECENT FINDINGS: A diversity of new genome editors and modulators are being developed for therapies across myriad human diseases. Recent breakthroughs have improved the efficacy, safety, specificity, and delivery of CRISPR-mediated therapies that could impact heart disease in the next decade, though several challenges remain. Many iterations of the original CRISPR system have been developed seeking to leverage its vast therapeutic potential. As examples, nuclease-free editing, precision single-nucleotide editing, gene expression regulation, and epigenomic modifications are now feasible with the current CRISPR-mediated suite of enzymes. These emerging tools will be indispensable for the development of novel cardiovascular therapeutics as demonstrated by recent successes in both basic research laboratories and pre-clinical models. Here, we provide an overview of current and emerging CRISPR-mediated technologies as they pertain to the cardiovascular system, highlighting successful implementations and future challenges
Performance of the Winning Algorithms of the RSNA 2022 Cervical Spine Fracture Detection Challenge.
No full textPurpose To evaluate and report the performance of the winning algorithms of the Radiological Society of North America Cervical Spine Fracture AI Challenge. Materials and Methods The competition was open to the public on Kaggle from July 28 to October 27, 2022. A sample of 3112 CT scans with and without cervical spine fractures (CSFx) were assembled from multiple sites (12 institutions across six continents) and prepared for the competition. The test set had 1093 scans (private test set: n = 789; mean age, 53.40 years ± 22.86 [SD]; 509 males; public test set: n = 304; mean age, 52.51 years ± 20.73; 189 males) and 847 fractures. The eight top-performing artificial intelligence (AI) algorithms were retrospectively evaluated, and the area under the receiver operating characteristic curve (AUC) value, F1 score, sensitivity, and specificity were calculated. Results A total of 1108 contestants composing 883 teams worldwide participated in the competition. The top eight AI models showed high performance, with a mean AUC value of 0.96 (95% CI: 0.95, 0.96), mean F1 score of 90% (95% CI: 90%, 91%), mean sensitivity of 88% (95% Cl: 86%, 90%), and mean specificity of 94% (95% CI: 93%, 96%). The highest values reported for previous models were an AUC of 0.85, F1 score of 81%, sensitivity of 76%, and specificity of 97%. Conclusion The competition successfully facilitated the development of AI models that could detect and localize CSFx on CT scans with high performance outcomes, which appear to exceed known values of previously reported models. Further study is needed to evaluate the generalizability of these models in a clinical environment