Lysosomal sialidase NEU1, its intracellular properties, deficiency, and use as a therapeutic agent.

Neuraminidase 1 (NEU1) is a lysosomal sialidase that cleaves terminal α-linked sialic acid residues from sialylglycans. NEU1 is biosynthesized in the rough endoplasmic reticulum (RER) lumen as an N-glycosylated protein to associate with its protective protein/cathepsin A (CTSA) and then form a lysosomal multienzyme complex (LMC) also containing ß-galactosidase 1 (GLB1). Unlike other mammalian sialidases, including NEU2 to NEU4, NEU1 transport to lysosomes requires association of NEU1 with CTSA, binding of the CTSA carrying terminal mannose 6-phosphate (M6P)-type N-glycan with M6P receptor (M6PR), and intralysosomal NEU1 activation at acidic pH. In contrast, overexpression of the single NEU1 gene in mammalian cells causes intracellular NEU1 protein crystallization in the RER due to self-aggregation when intracellular CTSA is reduced to a relatively low level. Sialidosis (SiD) and galactosialidosis (GS) are autosomal recessive lysosomal storage diseases caused by the gene mutations of NEU1 and CTSA, respectively. These incurable diseases associate with the NEU1 deficiency, excessive accumulation of sialylglycans in neurovisceral organs, and systemic manifestations. We established a novel GS model mouse carrying homozygotic Ctsa IVS6 + 1 g/a mutation causing partial exon 6 skipping with simultaneous deficiency of Ctsa and Neu1. Symptoms developed in the GS mice like those in juvenile/adult GS patients, such as myoclonic seizures, suppressed behavior, gargoyle-like face, edema, proctoptosis due to Neu1 deficiency, and sialylglycan accumulation associated with neurovisceral inflammation. We developed a modified NEU1 (modNEU1), which does not form protein crystals but is transported to lysosomes by co-expressed CTSA. In vivo gene therapy for GS and SiD utilizing a single adeno-associated virus (AAV) carrying modNEU1 and CTSA genes under dual promoter control will be created.

Translational research: from basic research to regional biomedical entrepreneurship.

This paper examines the effect of translational research on knowledge production and biomedical entrepreneurship across U.S. regions. Researchers have earlier investigated the outputs of translational research by focusing on academic publications. Little attention has been paid to linking translational research to biomedical entrepreneurship. We construct an analytical model based on the knowledge spillover theory of entrepreneurship and the entrepreneurial ecosystem approach to examine the relationship between translational research, biomedical patents, clinical trials, and biomedical entrepreneurship. We test the model across 381 U.S. metropolitan statistical areas using 10 years of panel data related to the NIH Clinical and Translational Science Awards (CTSA) program. CTSA appears to increase the number of biomedical patents and biomedical entrepreneurship as proxied by the NIH Small Business Innovation Research (SBIR) grants. However, the magnitudes of the effects are relatively small. Path analysis shows that the effect of translational research on regional biomedical entrepreneurship is not strongly conveyed through biomedical patents or clinical trials.

Leptin Modulates the Metastasis of Canine Inflammatory Mammary Adenocarcinoma Cells Through Downregulation of Lysosomal Protective Protein Cathepsin A (CTSA).

Canine malignant mammary gland tumors present with a poor prognosis due to metastasis to other organs, such as lung and lymph node metastases. Unlike in human studies where obesity has been shown to increase the risk of breast cancer, this has not been well studied in veterinary science. In our preliminary study, we discovered that leptin downregulated cathepsin A, which is responsible for lysosomal-associated membrane protein 2a (LAMP2a) degradation. LAMP2a is a rate-limiting factor in chaperone-mediated autophagy and is highly active in malignant cancers. Therefore, in this study, alterations in metastatic capacity through cathepsin A by leptin, which are secreted at high levels in the blood of obese patients, were investigated. We used a canine inflammatory mammary gland adenocarcinoma (CHMp) cell line cultured with RPMI-1640 and 10% fetal bovine serum. The samples were then subjected to real-time polymerase chain reaction, Western blot, immunocytochemistry, and lysosome isolation to investigate and visualize the metastasis and chaperone-mediated autophagy-related proteins. Results showed that leptin downregulated cathepsin A expression at both transcript and protein levels, whereas LAMP2a, the rate-limiting factor of chaperone-mediated autophagy, was upregulated by inhibition of LAMP2a degradation. Furthermore, leptin promoted LAMP2a multimerization through the lysosomal mTORC2 (mTOR complex 2)/PH domain and leucine rich repeat protein phosphatase 1 (PHLPP1)/AKT1 (Serine/threonine-protein kinase 1) pathway. These findings suggest that targeting leptin receptors can alleviate mammary gland cancer cell metastasis in dogs.

The prognostic significance of lysosomal protective protein (cathepsin A) in breast ductal carcinoma in situ.

AIMS: Cathepsin A (CTSA) is a key regulatory enzyme for galactoside metabolism. Additionally, it has a distinct proteolytic activity and plays a role in tumour progression. CTSA is differentially expressed at the mRNA level between breast ductal carcinoma in situ (DCIS) and invasive breast carcinoma (IBC). In this study, we aimed to characterise CTSA protein expression in DCIS and evaluate its prognostic significance. METHODS AND RESULTS: A large cohort of DCIS [n = 776 for pure DCIS and n = 239 for DCIS associated with IBC (DCIS/IBC)] prepared as a tissue microarray was immunohistochemically stained for CTSA. High CTSA expression was observed in 48% of pure DCIS. High expression was associated with features of poor DCIS prognosis, including younger age at diagnosis (<50 years), higher nuclear grade, hormone receptor negativity, HER2 positivity, high proliferative index and high hypoxia inducible factor 1 alpha expression. High CTSA expression was associated with shorter recurrence-free interval (RFI) (P = 0.0001). In multivariate survival analysis for patients treated with breast conserving surgery, CTSA was an independent predictor of shorter RFI (P = 0.015). DCIS associated with IBC showed higher CTSA expression than pure DCIS (P = 0.04). In the DCIS/IBC cohort, CTSA expression was higher in the invasive component than the DCIS component (P < 0.0001). CONCLUSION: CTSA is not only associated with aggressive behaviour and poor outcome in DCIS but also a potential marker to predict co-existing invasion in DCIS.

Characterization, expression signatures and microbial binding analysis of cathepsin A in turbot, Scophthalmus maximus L.(SmCTSA).

Mucosal immune system is one of the most vital components in the innate immunity and constitutes the first line of host defense against bacterial infections, especially for the teleost, which live in the pathogen-rich aquatic environment. Cathepsins, a superfamily of hydrolytic enzymes produced and enclosed within lysosomes, play multiple roles at physiological and pathological states. In this regard, we sought here to identify Cathepsin A in turbot (SmCTSA), characterize its mucosal expression patterns following Vibrio anguillarum and Streptococcus iniae infections in mucosal tissues, and explore its binding ability with three microbial ligands for the first time. The SmCTSA was 2631 bp long containing a 1422 bp open reading frame (ORF) that encoded 473 amino acids. Phylogenetic analysis revealed that SmCTSA showed the closest relationship to half-smooth tongue sole (Cynoglossus semilaevis). In addition, SmCTSA was ubiquitously expressed in all examined healthy tissues, with high expression levels in head kidney (HK) and intestine, while the lowest expression level in blood. Moreover, SmCTSA was significantly differentially expressed at least two timepoints in each mucosal tissue, suggesting its potential important roles in innate immune responses of turbot. Finally, in vitro assays showed that recombinant SmCTSA bound Lipopolysaccharide (LPS) with high affinity, and lipoteichoic acid (LTA) and peptidoglycan (PGN) with relatively low affinity. This study provides valuable data for understanding the roles of ctsa in the host defense against bacterial infections.

Social network analysis of biomedical research collaboration networks in a CTSA institution.

BACKGROUND: The popularity of social networks has triggered a number of research efforts on network analyses of research collaborations in the Clinical and Translational Science Award (CTSA) community. Those studies mainly focus on the general understanding of collaboration networks by measuring common network metrics. More fundamental questions about collaborations still remain unanswered such as recognizing "influential" nodes and identifying potential new collaborations that are most rewarding. METHODS: We analyzed biomedical research collaboration networks (RCNs) constructed from a dataset of research grants collected at a CTSA institution (i.e., University of Arkansas for Medical Sciences (UAMS)) in a comprehensive and systematic manner. First, our analysis covers the full spectrum of a RCN study: from network modeling to network characteristics measurement, from key nodes recognition to potential links (collaborations) suggestion. Second, our analysis employs non-conventional model and techniques including a weighted network model for representing collaboration strength, rank aggregation for detecting important nodes, and Random Walk with Restart (RWR) for suggesting new research collaborations. RESULTS: By applying our models and techniques to RCNs at UAMS prior to and after the CTSA, we have gained valuable insights that not only reveal the temporal evolution of the network dynamics but also assess the effectiveness of the CTSA and its impact on a research institution. We find that collaboration networks at UAMS are not scale-free but small-world. Quantitative measures have been obtained to evident that the RCNs at UAMS are moving towards favoring multidisciplinary research. Moreover, our link prediction model creates the basis of collaboration recommendations with an impressive accuracy (AUC: 0.990, MAP@3: 1.48 and MAP@5: 1.522). Last but not least, an open-source visual analytical tool for RCNs is being developed and released through Github. CONCLUSIONS: Through this study, we have developed a set of techniques and tools for analyzing research collaboration networks and conducted a comprehensive case study focusing on a CTSA institution. Our findings demonstrate the promising future of these techniques and tools in understanding the generative mechanisms of research collaborations and helping identify beneficial collaborations to members in the research community.

Proteomics analysis of serum and urine identifies VCP and CTSA as potential biomarkers associated with multiple myeloma.

AIMS: We analyzed the differentially expressed proteins (DEPs) in serum and urine in order to provide new potential biomarkers for MM. METHODS: Data-Independent Acquisition-based proteomics of serum and urine was performed to identify potential biomarkers for MM patients. Then we performed Western Blotting (WB), ELISA along with their ROC curve analysis to confirm DEPs. RESULTS: A total of 1653 proteins in serum and 4519 proteins in urine were identified using Data-Dependent Acquisition method. VCP was the only protein that showed significant differences in different comparison groups in both serum and urine. Pathway analysis revealed that protein processing in the endoplasmic reticulum was the most relevant pathway associated with MM. Furthermore, the increased expression of HSP90B1, VCP, CTSA, HYOU1, PDIA4, and RAB7A was detected by WB. The results of ELISA indicated that a combination of VCP and CTSA provided a high area under curve (AUC) value of 0.883 (95 % CI, 0.769-0.997, p < 0.001) to diagnose NDMM. The combination of VCP, CTSA, ALB, and HGB exhibited better performance (AUC = 0.981), with 100 % specificity and 86.7 % sensitivity. CONCLUSION: These findings suggest VCP and CTSA exhibit potential as biomarkers for MM, which may be helpful in the molecular mechanisms and pathogenesis upon further investigation.

Understanding enterprise data warehouses to support clinical and translational research: impact, sustainability, demand management, and accessibility.

OBJECTIVES: Healthcare organizations, including Clinical and Translational Science Awards (CTSA) hubs funded by the National Institutes of Health, seek to enable secondary use of electronic health record (EHR) data through an enterprise data warehouse for research (EDW4R), but optimal approaches are unknown. In this qualitative study, our goal was to understand EDW4R impact, sustainability, demand management, and accessibility. MATERIALS AND METHODS: We engaged a convenience sample of informatics leaders from CTSA hubs (n = 21) for semi-structured interviews and completed a directed content analysis of interview transcripts. RESULTS: EDW4R have created institutional capacity for single- and multi-center studies, democratized access to EHR data for investigators from multiple disciplines, and enabled the learning health system. Bibliometrics have been challenging due to investigator non-compliance, but one hub's requirement to link all study protocols with funding records enabled quantifying an EDW4R's multi-million dollar impact. Sustainability of EDW4R has relied on multiple funding sources with a general shift away from the CTSA grant toward institutional and industry support. To address EDW4R demand, institutions have expanded staff, used different governance approaches, and provided investigator self-service tools. EDW4R accessibility can benefit from improved tools incorporating user-centered design, increased data literacy among scientists, expansion of informaticians in the workforce, and growth of team science. DISCUSSION: As investigator demand for EDW4R has increased, approaches to tracking impact, ensuring sustainability, and improving accessibility of EDW4R resources have varied. CONCLUSION: This study adds to understanding of how informatics leaders seek to support investigators using EDW4R across the CTSA consortium and potentially elsewhere.

Research rigor and reproducibility in research education: A CTSA institutional survey.

We assessed the rigor and reproducibility (R&R) activities of institutions funded by the National Center for Advancing Translational Sciences (NCTSA) through a survey and website search (N = 61). Of 50 institutional responses, 84% reported incorporating some form of R&R training, 68% reported devoted R&R training, 30% monitored R&R practices, and 10% incentivized them. Website searches revealed 9 (15%) freely available training curricula, and 7 (11%) institutional programs specifically created to enhance R&R. NCATS should formally integrate R&R principles into its translational science models and institutional requirements.

A landscape assessment of CTSA evaluators and their work in the CTSA consortium, 2021 survey findings.

This article presents a landscape assessment of the findings from the 2021 Clinical and Translational Science Award (CTSA) Evaluators Survey. This survey was the most recent iteration of a well established, national, peer-led systematic snapshot of the CTSA evaluators, their skillsets, listed evaluation resources, preferred methods, and identified best practices. Three questions guided our study: who are the CTSA evaluators, what competencies do they share and how is their work used within hubs. We describe our survey process (logistics of development, deployment, and differences in historical context with prior instruments); and present its main findings. We provide specific recommendations for evaluation practice in two main categories (National vs Group-level) including, among others, the need for a national, strategic plan for evaluation as well as enhanced mentoring and training of the next generation of evaluators. Although based on the challenges and opportunities currently within the CTSA Consortium, takeaways from this study constitute important lessons with potential for application in other large evaluation consortia. To our knowledge, this is the first time 2021 survey findings are disseminated widely, to increase transparency of the CTSA evaluators' work and to motivate conversations within hub and beyond, as to how best to leverage existent evaluative capacity.

Advancing the Science of Mentorship: Future Directions for Sustainable Implementation and Evaluation of Mentorship Education for the Clinical and Translational Science Workforce.

The Advancing the Science of Mentorship: Future Directions for Sustainable Implementation and Evaluation of Mentorship Education for the Clinical and Translational Science Workforce conference was held in Madison, Wisconsin, in April 2023. The conference provided an engaging and scholarly forum for clinical and translational researchers from diverse backgrounds and career stages (including leaders at Clinical and Translational Science Award (CTSA) hubs and affiliated institutions) with a professional interest and commitment to improving and diversifying workforce development and fostering a climate of inclusive excellence through best practices in mentorship. Outcomes from the conference include an online resource and a new Community of Practice.

Simultaneous submission of seven CTSA proposals: UM1, K12, R25, T32-predoctoral, T32-postdoctoral, and RC2: strategies, evaluation, and lessons learned.

Translation is the process of turning observations in the research laboratory, clinic, and community into interventions that improve people's health. The Clinical and Translational Science Awards (CTSA) program is a National Center for Advancing Translational Sciences (NCATS) initiative to advance translational science and research. Currently, 64 "CTSA hubs" exist across the nation. Since 2006, the Houston-based Center for Clinical Translational Sciences (CCTS) has assembled a well-integrated, high-impact hub in Texas that includes six partner institutions within the state, encompassing ∼23,000 sq. miles and over 16 million residents. To achieve the NCATS goal of "more treatments for all people more quickly," the CCTS promotes diversity and inclusion by integrating underrepresented populations into clinical studies, workforce training, and career development. In May 2023, we submitted the UM1 application and six "companion" proposals: K12, R25, T32-Predoctoral, T32-Postdoctoral, and RC2 (two applications). In October 2023, we received priority scores for the UM1 (22), K12 (25), T32-Predoctoral (20), and T32-Postdoctoral (23), which historically fall within the NCATS funding range. This report describes the grant preparation and submission approach, coupled with data from an internal survey designed to assimilate feedback from principal investigators, writers, reviewers, and administrative specialists. Herein, we share the challenges faced, the approaches developed, and the lessons learned.

Causal associations of MICB, CTSA, and MMP9 proteins with oral cancer: Mendelian randomization study.

Oral cancer (ORCA) is the most prevalent histological subtype of oral malignancies in which immune modulation is relevant. The goal of this work was to employ Mendelian randomization (MR) to investigate the causal connection between the immune-related proteins MICB, CTSA, MMP9, and ORCA. The Open GWAS database of the Integrative Epidemiology Unit (IEU) was accessed to collect GWAS data for ORCA (ieu-b-4961), MICB (prot-a-1898), CTSA (prot-a-717) and MMP9 (prot-a-1921). From 372,373 samples, the ORCA dataset comprises 7,723,107 single nucleotide polymorphisms (SNPs). MICB, CTSA, and MMP9 all have 10,534,735 SNPs and 3,301 sample sizes. Then, the primary SVMR implementation approaches were weighted mode, simple mode, inverse variance weighted (IVW), weighted median, and MR-Egger. IVW was the most effective technique. A sensitivity study was also carried out to assess the correctness of SVMR data, with special focus devoted to heterogeneity, horizontal pleiotropy, and Leave-One-Out (LOO). MVMR was eventually implemented as well. A Mendelian randomization analysis of the three exposure factors in the dataset (ieu-b-94, ebi-a-GCST012237) was also performed to validate the study results. According to the SVMR results, there was a noteworthy causal interaction between ORCA and MICB (P = 0.0014), MMP9 (P = 0.0343), and CTSA (P = 0.0003). Furthermore, odds ratios (ORs) values revealed that MMP9 (OR = 1.0005) was an ORCA risk factor, whereas MICB (OR = 0.9994) and CTSA (OR = 0.9993) were security factors. The robustness of the SVMR findings was confirmed by the p-values of the heterogeneity and horizontal pleiotropy, both of which were greater than 0.05. The MVMR result did not affect any of the safety or hazard features of these three exposure factors. However, the P value for MMP9 was greater than 0.05, implying that MICB and CTSA may have a greater influence on ORCA than MMP9. The validation outcomes in both datasets harmonized with the findings from previous research, thereby solidifying the reliability of results. Our investigation provided a crucial resource for further research on the subject by demonstrating a causal relationship between ORCA and MICB, CTSA, and MMP9.

FAIR enough: Building an academic data ecosystem to make real-world data available for translational research.

The Stanford Population Health Sciences Data Ecosystem was created to facilitate the use of large datasets containing health records from hundreds of millions of individuals. This necessitated technical solutions optimized for an academic medical center to manage and share high-risk data at scale. Through collaboration with internal and external partners, we have built a Data Ecosystem to host, curate, and share data with hundreds of users in a secure and compliant manner. This platform has enabled us to host unique data assets and serve the needs of researchers across Stanford University, and the technology and approach were designed to be replicable and portable to other institutions. We have found, however, that though these technological advances are necessary, they are not sufficient. Challenges around making data Findable, Accessible, Interoperable, and Reusable remain. Our experience has demonstrated that there is a high demand for access to real-world data, and that if the appropriate tools and structures are in place, translational research can be advanced considerably. Together, technological solutions, management structures, and education to support researcher, data science, and community collaborations offer more impactful processes over the long-term for supporting translational research with real-world data.

Expanding research to provide an evidence base for nutritional interventions for the management of inborn errors of metabolism.

A trans-National Institutes of Health initiative, Nutrition and Dietary Supplement Interventions for Inborn Errors of Metabolism (NDSI-IEM), was launched in 2010 to identify gaps in knowledge regarding the safety and utility of nutritional interventions for the management of inborn errors of metabolism (IEM) that need to be filled with evidence-based research. IEM include inherited biochemical disorders in which specific enzyme defects interfere with the normal metabolism of exogenous (dietary) or endogenous protein, carbohydrate, or fat. For some of these IEM, effective management depends primarily on nutritional interventions. Further research is needed to demonstrate the impact of nutritional interventions on individual health outcomes and on the psychosocial issues identified by patients and their families. A series of meetings and discussions were convened to explore the current United States' funding and regulatory infrastructure and the challenges to the conduct of research for nutritional interventions for the management of IEM. Although the research and regulatory infrastructure are well-established, a collaborative pathway that includes the professional and advocacy rare disease community and federal regulatory and research agencies will be needed to overcome current barriers.

Demographic composition of National Institutes of Health Clinical and Translational Science Awards (CTSA) Program principal investigators, scholars, and trainees.

Little has been published on the demographic composition of the clinical and translational science research workforce within the Clinical and Translational Science Awards (CTSA) Program despite the well-documented need for greater diversity in the biomedical research workforce. Analyses of workforce demographic reveal that women and members of underrepresented groups remain persistently underrepresented in the CTSA hub and training components principal investigators. In contrast, in the CTSA Program career development and training programs, females have greater representation as participants, and non-Whites were better represented in training programs.

Advancing workforce diversity by leveraging the Clinical and Translational Science Awards (CTSA) program.

Clinical trials continue to disproportionately underrepresent people of color. Increasing representation of diverse backgrounds among clinical research personnel has the potential to yield greater representation in clinical trials and more efficacious medical interventions by addressing medical mistrust. In 2019, North Carolina Central University (NCCU), a Historically Black College and University with a more than 80% underrepresented student population, established the Clinical Research Sciences Program with support from the Clinical and Translational Science Awards (CTSA) program at neighboring Duke University. This program was designed to increase exposure of students from diverse educational, racial, and ethnic backgrounds to the field of clinical research, with a special focus on health equity education. In the first year, the program graduated 11 students from the two-semester certificate program, eight of whom now hold positions as clinical research professionals. This article describes how leveraging the CTSA program helped NCCU build a framework for producing a highly trained, competent, and diverse workforce in clinical research responsive to the call for increased diversity in clinical trial participation.

Quantitative assessment of the impact of standard agreement templates on multisite clinical trial start up time.

Contracting delays remain a challenge to the successful initiation of multisite clinical research in the US. The Clinical and Translational Science Awards (CTSA) Contracts Processing Study showed average contract negotiation duration of > 100 days for industry-sponsored or investigator-initiated contracts. Such delays create enormous costs to sponsors and to patients waiting to use new evidence-based treatments. With support from the National Institutes of Health's National Center for Advancing Translational Sciences, the Accelerated Clinical Trial Agreement (ACTA) was developed by 25 major academic institutions and medical centers engaged in clinical research in collaboration with the University-Industry Demonstration Partnership and with input from pharmaceutical companies. The ACTA also informed the development of subsequent agreements, including the Federal Demonstration Partnership Clinical Trial Subaward Agreement (FDP-CTSA); both ACTA and the FDP-CTSA are largely non-negotiable agreements that represent pre-negotiated compromises in contract terms agreed upon by industry and/or medical center stakeholders. When the involved parties agree to use the CTSA-developed and supported standard agreement templates as a starting point for negotiations, there can be significant time savings for trials. Use of the ACTA resulted in an average savings of 48 days and use of the FDP-CTSA saved an average of 57 days of negotiation duration.

Evaluating the impact of a CTSA program from 2008 to 2021 through bibliometrics, social network analysis, and altmetrics.

Introduction: We evaluate a CTSA program hub by applying bibliometrics, social network analysis (SNA), and altmetrics and examine the changes in research productivity, citation impact, research collaboration, and CTSA-supported research topics since our pilot study in 2017. Methods: The sampled data included North Carolina Translational and Clinical Science Institute (NC TraCS)-supported publications produced between September 2008 and March 2021. We applied measures and metrics from bibliometrics, SNA, and altmetrics to the dataset. In addition, we analyzed research topics and correlations between different metrics. Results: 1154 NC TraCS-supported publications generated over 53,560 citation counts by April 2021. The average cites per year and the relative citation ratio (RCR) mean of these publications improved from 33 and 2.26 in 2017 to 48 and 2.58 in 2021. The number of involved UNC units in the most published authors' collaboration network increased from 7 (2017) to 10 (2021). NC TraCS-supported co-authorship involved 61 NC organizations. PlumX metrics identified articles with the highest altmetrics scores. About 96% NC TraCS-supported publications have above the average SciVal Topic Prominence Percentile; the average approximate potential to translate of the included publication was 54.2%; and 177 publications addressed health disparity issues. Bibliometric measures (e.g., citation counts, RCR) and PlumX metrics (i.e., Citations, Captures, and Social-Media) are positively correlated (p < .05). Conclusion: Bibliometrics, SNA, and altmetrics offer distinctive but related perspectives to examine CTSA research performance and longitudinal growth, especially at the individual program hub level. These perspectives can help CTSAs build program foci.