DigitalCommons@The Texas Medical Center
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Surface Marker Identification to Capture Live Circulating Tumor Cells in Metastatic Triple-Negative Breast Cancer
No full textMetastatic triple-negative breast cancer (TNBC) is highly aggressive and lacks targeted therapies. Circulating tumor cells (CTC) are invaluable for monitoring metastatic tumor progression and treatment response but are difficult to capture because of their rarity and heterogeneity. Surface-based staining for live CTCs is essential to preserve RNA quality in single cells, but current markers tend to perform poorly on more mesenchymal tumor cells such as TNBCs. To enhance live TNBC CTC detection, we developed a workflow for live CTC capture and single-cell RNA sequencing (scRNA-seq). Using a mouse model of metastatic TNBC, we identified four new CTC surface markers, AHNAK2, CAVIN1, ODR4, and TRIML2, which specifically stain tumor cells. Combining antibodies against these markers improved CTC detection rates in multiple TNBC mouse models and patient samples. Also, combining these new markers with traditional CTC surface markers enhanced detection sensitivity, achieving the highest CTC coverage. This approach identifies diverse CTC populations, while preserving RNA quality for scRNA-seq, which is essential for understanding and therapeutically targeting metastatic breast cancer. The use of these newly identified CTC markers significantly enhances both detection and live capture of CTCs, paving the way for more effective use of liquid biopsy to monitor patient prognosis and treatment response in clinical settings. Significance:
CTCs are a powerful indicator of cancer metastasis; however, their scarcity makes them difficult to isolate. Current markers favor epithelial CTCs over mesenchymal populations. Our workflow for live CTC capture and sequencing enables discovery of new markers for both epithelial and mesenchymal CTCs. When combined with existing markers, we improve live CTC capture for more holistic studies of the metastatic process and offer a scalable method for discovering CTC markers
Associations of Arsenic Exposure and Folate in Maternal Leukocyte DNA Methylation: A Case-Control Study of Mothers With Spina-Bifida Affected Children
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Psychometric Properties of a Novel Affective Bias Task and Its Application in Clinical and Nonclinical Populations
No full textTo mitigate limitations in self-reported mood assessments, we introduce a novel affective bias task (ABT). The task quantifies instantaneous emotional state by leveraging the phenomenon of affective bias, in which people interpret external emotional stimuli in a manner consistent with their current emotional state. This study establishes task stability in measuring and tracking depressive symptoms in clinical and non-clinical populations. Initial assessment in a large non-clinical sample established normative ratings. Depressive symptoms were tracked relative to task performance in a non-clinical sample, as well as in a clinical cohort undergoing surgical evaluation for severe epilepsy. In both cohorts, a stronger negative affective bias was associated with higher Beck Depression Inventory (BDI-II) scores. The ABT exhibits high stability and interrater reliability, as well as construct validity in predicting depression levels in both cohorts, suggesting the task as a reliable proxy for mood and a diagnostic tool for detecting depressive symptoms
Linkage Disequilibrium Score Regression Identifies Genetic Correlations Between Hepatocellular Carcinoma and Clinically Relevant Traits
No full textHepatocellular carcinoma (HCC) mortality is increasing globally, partly due to the growing prevalence of nonviral liver diseases. Genome-wide association studies (GWAS) have identified genetic variants associated with HCC development. Leveraging GWAS summary statistics and linkage disequilibrium score regression (LDSR), we investigated disease co-development with hepatitis C virus-negative (HCV-negative) HCC to provide unique insights into HCC etiology and prioritize relationships for further causal inquiry. We utilized the LDSR statistical framework to estimate the genetic correlation and heritability between HCV-negative HCC with 901 epidemiologic, behavioral, and clinical traits from the United Kingdom Biobank (UKBB). First, we set the threshold for observed scale heritability of each trait at 0.02 to ensure reliable inferences with adequate study power. Next, we observed significant positive genetic correlations between HCV-negative HCC and blood-based biomarkers of liver injury (ALT, GGT) and allostatic load (including glycated hemoglobin, blood pressure, and total albumin). We also identified a positive genetic correlation between HCV-negative HCC and diseases associated with metabolic dysfunction-associated steatotic liver disease (MASLD), including diabetes, hypertension, chronic ischemic heart disease, and others. Taken together, our results help to identify polygenic and pleiotropic signals related to different phenotypic traits associated with HCC and support further exploration of the predictive power of blood-based biomarkers identified in this study for inferring HCC development among HCV-negative individuals
Efficient Database Translation
No full textUnderstand the concept and utility of database translation. Identify key differences in indexing and syntax across major biomedical databases. Apply practical strategies for translating search strategies between databases
Germline Hla Heterozygosity Is Associated With Decreased Lung Cancer Risk
No full textHeterozygosity at human leukocyte antigen (HLA) loci may improve lung cancer immunosurveillance by increasing recognition of the tumor by the immune system. Previous studies utilizing data from population-level biobanks, such as the United Kingdom Biobank and FinnGen, have identified an association between germline HLA class-II heterozygosity and reduced lung cancer risk in smokers. In the present study, we evaluate the association between HLA heterozygosity and lung cancer in a large case-control study (15,302 cases; 14,580 controls) with imputed HLA allele-type information, comparing differences in HLA heterozygosity between smokers and non-smokers, amongst lung cancer subtypes, and at 2- and 4-digit HLA allele resolution. We identify a strong protective association of HLA-II heterozygosity in smokers compared to non-smokers, particularly at the HLA-DPB1 and HLA-DPA1 loci, and provide subtype-specific resolution. Finally, analysis of the additive effects of HLA allele heterozygosity in smokers identified significant associations with several 4-digit HLA alleles, including HLA-B*08:01, HLA-A*01:01, HLA-C*07:01, HLA-DQA1*05:01, HLA-DRB1*03:01, and HLA-C*03:04. Our study provides additional evidence, with added histologic subtype information, that germline HLA-II heterozygosity is inversely associated with lung cancer risk
Application of a Natural Language Processing Algorithm to Early Asthma Ascertainment for Adults in the Era of Electronic Health Records
No full textBackground: The natural language processing (NLP) algorithm for predetermined asthma criteria (NLP-PAC) was successfully developed and validated for automatically ascertaining pediatric asthma from electronic health record (EHRs) systems. A scalable, efficient, and automated tool for ascertaining adult asthma status from EHRs remains nonexistent.
Objective: We validated NLP-PAC enabling ascertainment and early identification of adult asthma status in their EHRs.
Methods: We applied the validated NLP-PAC to EHRs of a convenient sample (adult cohorts who participated in our previous population-based studies) in which a reference standard (ie, asthma status defined by manual chart review) is available. The performance of NLP-PAC was assessed by determining criterion validity against manual chart review and construct validity before and after the new EHR (Epic) system was implemented in 2018.
Results: The cohort consisted of 1,898 subjects, with 43% male and a median age at time of last follow-up of 65 years (interquartile range, 55-76). Manual chart review and NLP-PAC identified 97 (5.1%) and 98 (5.1%) subjects with asthma, respectively, with 89 subjects commonly identified by both methods. The sensitivity, specificity, positive predictive value, and negative predictive value of NLP-PAC were 92%, 99%, 91%, and 99%, respectively, before the new EHR system was implement, which remained similar after introducing the system (95%, 88%, 96%, and 85%, respectively). The risk factors for asthma identified either by NLP-PAC or manual chart review were similar.
Conclusion: Automatic asthma ascertainment for adults based on EHR data is feasible with our NLP algorithm, offering immense scientific and clinical value for large-scale clinical research and population management for adult asthma care
Resolution of a Human Chromosomal Mystery: Evolutionary Complexity Revealed
No full textThe human complement of chromosomes differs from our closest primate relatives by virtue of a unique chromosome fusion event. In this issue of Cell Genomics, Yang et al. provide the first detailed analysis of the site of chromosome fusion and reconstruct the complex evolutionary relationships among the genomic elements within the human fusion site and their related sequences in our great ape relatives
Modulation of Stemness and Differentiation Regulators by Valproic Acid in Medulloblastoma Neurospheres
Full text linkChanges in epigenetic processes such as histone acetylation are proposed as key events influencing cancer cell function and the initiation and progression of pediatric brain tumors. Valproic acid (VPA) is an antiepileptic drug that acts partially by inhibiting histone deacetylases (HDACs) and could be repurposed as an epigenetic anticancer therapy. Here, we show that VPA reduced medulloblastoma (MB) cell viability and led to cell cycle arrest. These effects were accompanied by enhanced H3K9 histone acetylation (H3K9ac) and decreased expression of the MYC oncogene. VPA impaired the expansion of MB neurospheres enriched in stemness markers and reduced MYC while increasing TP53 expression in these neurospheres. In addition, VPA induced morphological changes consistent with neuronal differentiation and the increased expression of differentiation marker genes TUBB3 and ENO2. The expression of stemness genes SOX2, NES, and PRTG was differentially affected by VPA in MB cells with different TP53 status. VPA increased H3K9 occupancy of the promoter region of TP53. Among the genes regulated by VPA, the stemness regulators MYC and NES showed an association with patient survival in specific MB subgroups. Our results indicate that VPA may exert antitumor effects in MB by influencing histone acetylation, which may result in the modulation of stemness, neuronal differentiation, and the expression of genes associated with patient prognosis in specific molecular subgroups. Importantly, the actions of VPA in MB cells and neurospheres include a reduction in the expression of MYC and an increase in TP53