Clinical Translational Research Research Articles

Ophthalmological research in Germany: evaluation by an international expert panel

To evaluate the research performance in ophthalmology in Germany based on the findings of the recent research map of the German Ophthalmological Society ( DOG) and to suggest strategies for future improvements on anational level both to DOG as well as to politics. The focus is on preclinical and translational clinical research. International expert panel evaluation and discussion organized by the Task Force Research of the German Ophthalmological Society (DOG). The international view on the German ophthalmological research landscape was generally positive. The value for money relationship was judged as very good. As Germany is facing an aging society and vision impairment will create an ever-increasing socioeconomic burden, the reviewers suggested several lines of future activities: an increased activity of securing intellectual property, more lay audience lobbying, intensified collaboration and critical mass building between "lighthouses" of ophthalmic research in Germany, as well as the establishment of aGerman national eye institute equivalent. The ophthalmological research performance in Germany was rated to be very good by an international expert panel. Nonetheless significant improvements were requested in the fields of translation (clinical trials, IP), synergy between specialized institutions and governmental funding for aGerman center for eye research.

Exosomes: the next-generation therapeutic platform for ischemic stroke

Abstract Current therapeutic strategies for ischemic stroke fall short of the desired objective of neurological functional recovery. Therefore, there is an urgent need to develop new methods for the treatment of this condition. Exosomes are natural cell-derived vesicles that mediate signal transduction between cells under physiological and pathological conditions. They have low immunogenicity, good stability, high delivery efficiency, and the ability to cross the blood-brain barrier. These physiological properties of exosomes have the potential to lead to new breakthroughs in the treatment of ischemic stroke. The rapid development of nanotechnology has advanced the application of engineered exosomes, which can effectively improve targeting ability, enhance therapeutic efficacy, and minimize the dosages needed. Advances in technology have also driven clinical translational research on exosomes. In this review, we describe the therapeutic effects of exosomes anc their positive roles in current treatment strategies for ischemic stroke, including their anti-inflammation, anti-apoptosis, autophagy-regulation, angiogenesis, neurogenesis, and glial scar formation reduction effects. However, it is worth noting that, despite their significant therapeutic potential, there remains a dearth of standardized characterization methods and efficient isolation techniques capable of producing highly purified exosomes. Future optimization strategies should prioritize the exploration of suitable isolation techniques and the establishment of unified workflows to effectively harness exosomes for diagnostic or therapeutic applications in ischemic stroke. Ultimately, our review aims to summarize our understanding of exosome-based treatment prospects in ischemic stroke and foster innovative ideas for the development of exosome-based therapies.

Abstract PO1-15-07: Subtyping-directed precision treatment refines traditional one-size-fits-all therapy in HR+/HER2- breast cancer: a sub-study of the MULAN umbrella trial

Abstract Background: The standard approach of using one-size-fits-all endocrine therapy for hormone receptor-positive and HER2-negative (HR+/HER2-) breast cancers has faced significant challenges due to variations in treatment response among individuals. Consequently, there is still an urgent need to understand the molecular biology of HR+/HER2- breast cancer and explore precision treatment strategy. Methods: We established a multiomics cohort (n = 351), multicenter real-world clinical cohorts (n = 643), a prospective clinical cohort (MULAN trial), and a drug-testing platform containing patient-derived organoids (n = 126) and patient-derived tumor fragments (n = 49) of HR+/HER2- breast cancers. Integrating "bench" and “bedside” data, we conducted comprehensive preclinical and clinical translational research on precision strategies in HR+/HER2- breast cancer. Results: We implemented a comprehensive classification system for HR+/HER2- breast cancer, comprising four distinct subtypes. We further demonstrated the efficacy and mechanisms of subtyping-directed precision treatment strategies through clinical cohort studies, omics analysis and functional assays: endocrine therapy alone for the canonical luminal subtype; the addition of CDK4/6 inhibitor and PARP inhibitor for the proliferative subtype; the immunotherapy for the immunogenic subtype; and tyrosine kinase inhibitors for the receptor tyrosine kinase-driven subtype. Using clinically applicable subtyping methods, we validated that matched precision treatment strategies outperformed unmatched approaches in a real-world cohort, almost doubling the median progression-free survival time for patients with refractory advanced HR+/HER2- breast cancer (9.83 months [95% CI, 5.74-13.93] vs 4.77 months [95% CI, 3.35-6.18]; hazard ratio 0.64 [95% CI, 0.41-0.99]). Importantly, the first-stage analysis of the MULAN phase II umbrella clinical trial (NCT04355858) verified the higher objective response rate (88.9%, 95%CI: 51.7%-99.7%) of the subtyping-directed precision treatment. Conclusion: Our study emphasizes the superiority of subtyping-directed precision treatment strategies for HR+/HER2- breast cancer, refines traditional “one-size-fits-all” therapy, and facilitates the translation of precision treatment strategies from bench to bedside. Overall study design Part 1 Subtype Molecular Characteristics: Molecular features of the four subtypes of HR+/HER2- breast cancer. Part 2 Multidimensional Efficacy Validation: Integrating data from a multiomics cohort, real-world study, drug testing platform and prospective clinical research to validate the subtyping-directed precision treatment strategy in HR+/HER2- breast cancer. Part 3 Subtyping-directed Precision Treatment Strategy: Integrating clinical cohort studies, omics analysis and functional assays revealed the heterogeneity of treatment response in HR+/HER2- breast cancer, and proposed a subtyping-directed precision treatment strategy. CIN, chromosomal instability; RTK, receptor tyrosine kinase; CNA, copy-number alteration; ER, estrogen receptor; HR, hormone receptor; HER2, human epidermal growth factor receptor 2. Citation Format: Xiu-Zhi Zhu, Xi Jin, Hu-Yun-Long Zhang, Xiyu Liu, Yi-Fan Zhou, Yi-Yu Chen, Tong Fu, Ming-Liang Jin, Ya-Xin Zhao, Yi-Fan Xie, Ruo-Xi Wang, Zhong-Hua Wang, Lei Fan, Yi-Zhou Jiang, Zhi-Ming Shao. Subtyping-directed precision treatment refines traditional one-size-fits-all therapy in HR+/HER2- breast cancer: a sub-study of the MULAN umbrella trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-15-07.

Can diet change the natural history of gastrointestinal diseases?

Belatedly, gastroenterologists have begun to pay attention to the role of diet in the exacerbation of gastrointestinal symptoms in many digestive disorders-a recognition that has spurred both high-quality clinical trials and translational research into this area. It has become clear that multiple mechanisms acting either in isolation or together can induce gut symptoms and that appropriate interventions can lead to significant relief. What this review will explore is not the role of diet in the production of certain symptoms or symptom clusters, but rather whether a dietary intervention can beneficially alter the natural history of a gastrointestinal disease-a much more demanding expectation. Yet there are examples of where a diet, if sustained, can have a long-term impact on at least some of those affected by conditions such as eosinophilic esophagitis, celiac disease, food allergy, and constipation.

Ovarian Cancer Clinical Trial Translational Endpoints Research Award (DOD)

Ovarian Cancer Clinical Trial Translational Endpoints Research Award (DOD)

A bibliometric analysis of miRNAs in rheumatoid arthritis from 2001 to 2022: Research hotspots and trends.

MicroRNAs (miRNAs) are widely recognized in the pathogenesis of autoimmune disease. As a key regulatory factor, miRNAs have introduced new biomarkers for the early diagnosis of rheumatoid arthritis (RA) and provided a favorable research direction for the development of novel therapeutic targets. This study aimed to explore the hotspots of miRNA research related to RA published from different countries, organizations, and authors. From 2001 to 2022, publications on miRNA related to RA were identified in the Web of Science database. The total and annual number of publishments, citations, impact factor, H-index, productive authors, and involved journals were collected for quantitative and qualitative comparisons. A total of 29 countries/regions in the world have participated in the research of miRNAs and RA over the past two decades, and China (760, 53.18%) and the United States (233, 16.31%) account for the majority of the total publications. China dominated in total citation (17881) and H-index (62). A total of 507 academic journals have published articles in related fields, and Frontiers in Immunology published the most (53, 3.71%). Chih-hsin Tang of the China Medical University has published the most papers (16, 1.2%). Stanczyk (2008) published the most cited article Altered expression of miRNAs in synovial fibroblasts and synovial tissue in rheumatoid arthritis in Arthritis and Rheumatism, with 660 citations. Inflammation is the high-frequency keyword outside of RA and miRNAs, and related researches have mainly focused on miR-146a and miR-155. In the past two decades, extensive and continuous research has been conducted to investigate the role of miRNAs in RA, and miRNAs are widely recognized in the pathogenesis of RA. Related research has mainly focused on miR-146a and miR-155 that have shown promising results as key factors in RA experimental models. Focusing on clinical applications and translational research may be the future research direction and hotspot based on molecular biology basic research and mechanism exploration.

525 A Library-CTSI Collaboration to Support Researcher Compliance with the 2023 NIH Policy for Data Management and Sharing

OBJECTIVES/GOALS: Seeking ways to support teams in the preparation for and the implementation of the new National Institutes of Health (NIH) Policy for Data Management and Sharing (DMSP), the integrated Translational Health Research Institute of Virginia (iTHRIV) partnered with the UVA Health Sciences Library to develop training and resources for researchers. METHODS/STUDY POPULATION: Health sciences librarians and iTHRIV (an NIH-NCATS supported Clinical Translational Research Institute) convened a Working Group, inviting representatives from central and unit-specific research support offices (e.g. the Comprehensive Cancer Center), research compliance, regulatory affairs, sponsored programs, institutional review boards, libraries, and data science to review and discuss the DMSP requirements. After an initial orientation to the policy, the group reviewed existing public resources and solicited feedback about steps to best support UVA researchers in compliance. Leveraging the broad expertise of the group, the team provides guidance to researchers on writing the DMS plan and choosing a data repository, and provides tools and templates to support implementation of the policy. RESULTS/ANTICIPATED RESULTS: A library-created website provided policy guidance, including links to NIH-hosted information, resources created by other institutions, and new UVA-specific templates and suggested proposal language. Librarians led a webinar on the new policy and UVA resources which included a speaker from UVA regulatory affairs to describe the new DMSP requirements, and a tour of the new guide. The guide has been viewed over 5000 times to date and librarians have provided consultations and training to individuals and departments. Current plans include developing a user satisfaction survey, reviewing DMSP feedback from submitted proposals, and incorporating lessons learned into the website and future training. DISCUSSION/SIGNIFICANCE: The collaboration between iTHRIV and the Health Sciences Library to support the NIH Data Management and Sharing Policy was a successful partnership that provided leadership at the institutional level to communicate with and engage researchers and utilized the library’s web presence, expertise, and service model to provide direct support.

Development and validation of novel retina biomarkers and artificial intelligence models for Behçet disease uveitis prediction

ObjectiveThe aim of this study was to develop and validate quantitative diagnostic biomarkers and artificial intelligence (AI) models for Behçet disease uveitis (BU). MethodsWe conducted a single-center retrospective study using AI-based algorithms to evaluate OCT angiography (OCTA) fundus scans from 62 BU patients and 61 healthy individuals. ResultsFrom the 837 radiomic features derived from the OCTA scans, the top 20 features were utilized for AI modeling. The neural network (NN) model displayed the highest area under the receiver operating characteristic curve (AUC) of 0.900 in the test set. The integration of clinical data further enhanced the model's performance, leading to an AUC of 0.908 in the temporal validation cohort. ConclusionOur research demonstrates that the radiomic score and the clinical integrated score can independently serve as diagnostic biomarkers for BU for future potential clinical translational research. SignificanceThe AI models we developed show great promise for clinical and translational research, marking progress towards fulfilling the demand for quantitative imaging biomarkers in BU diagnosis. However, further validation and evaluation are crucial to confirm their real-world applicability in clinical settings.

Abstract 7315: Collaboration between NIDCR and NCI promotes innovative research in head and neck cancers

Abstract The Oral and Salivary Cancer Biology Program at National Institute of Dental and Craniofacial Research (NIDCR) supports research activities that improve early detection and treatment of cancers of the oral cavity, pharynx, and salivary glands. We promote basic science research on the regulatory pathways and transformation process of pre-cancerous lesions to primary and metastatic tumors, as well as translational science activities to develop novel technologies and therapeutics for the diagnosis, prognosis, and treatment of cancers. NIDCR and National Cancer Institute (NCI) have established long-term collaborations to promote and co-manage awards funded through The Immuno-Oncology Translational Network (IOTN) of the Cancer Moonshot program, Specialized Programs of Research Excellence (SPOREs), and Early Detection Research Network (EDRN) program. NIDCR and NCI have co-developed Notice of Special Interest (NOSI) and Request for Application (RFA) on Advancing Head and Neck Cancer Early Detection Research (AHEAD), which co-funded seven research projects to discover and develop molecular signatures of early detection and diagnosis of HPV positive and negative head and neck cancer (HNC). To further strengthen NIDCR and NCI collaboration, we jointly organized the symposium to promote HNC early detection and biomarker identification at the American Head and Neck Society (AHNS) 11th International Conference on Head and Neck Cancer in July 2023. In addition, NIDCR has organized a symposium to promote HNC research at the 2024 annual meeting of American Association for Dental, Oral, and Craniofacial Research (AADOCR) to celebrate the 75th anniversary of NIDCR. This AADOCR symposium will feature the collaboration between NIDCR with NCI in the Cancer Moonshot program focusing on immunoprevention and immunotherapy, HNC early detection and biomarker research in AHEAD and EDRN, and investigation of HPV positive and negative HNC and clinical translational research under SPORE. At this 2024 AACR annual meeting, NIDCR and NCI program directors will present the collaborations and funding opportunities between NIDCR and NCI, focusing on early cancer detections and biomarker discovery and validation. Collaboration between NIDCR with NCI provides a unique opportunity to promote basic, translational, and clinical research in advancing HNC early detection to benefit cancer patients. Citation Format: Zhong Chen, Wendy Wang. Collaboration between NIDCR and NCI promotes innovative research in head and neck cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7315.

Comprehensive proteomics of CSF, plasma, and urine identify DDC and other biomarkers of early Parkinson’s disease

Parkinson’s disease (PD) starts at the molecular and cellular level long before motor symptoms appear, yet there are no early-stage molecular biomarkers for diagnosis, prognosis prediction, or monitoring therapeutic response. This lack of biomarkers greatly impedes patient care and translational research—l-DOPA remains the standard of care more than 50 years after its introduction. Here, we performed a large-scale, multi-tissue, and multi-platform proteomics study to identify new biomarkers for early diagnosis and disease monitoring in PD. We analyzed 4877 cerebrospinal fluid, blood plasma, and urine samples from participants across seven cohorts using three orthogonal proteomics methods: Olink proximity extension assay, SomaScan aptamer precipitation assay, and liquid chromatography–mass spectrometry proteomics. We discovered that hundreds of proteins were upregulated in the CSF, blood, or urine of PD patients, prodromal PD patients with DAT deficit and REM sleep behavior disorder or anosmia, and non-manifesting genetic carriers of LRRK2 and GBA mutations. We nominate multiple novel hits across our analyses as promising markers of early PD, including DOPA decarboxylase (DDC), also known as l-aromatic acid decarboxylase (AADC), sulfatase-modifying factor 1 (SUMF1), dipeptidyl peptidase 2/7 (DPP7), glutamyl aminopeptidase (ENPEP), WAP four-disulfide core domain 2 (WFDC2), and others. DDC, which catalyzes the final step in dopamine synthesis, particularly stands out as a novel hit with a compelling mechanistic link to PD pathogenesis. DDC is consistently upregulated in the CSF and urine of treatment-naïve PD, prodromal PD, and GBA or LRRK2 carrier participants by all three proteomics methods. We show that CSF DDC levels correlate with clinical symptom severity in treatment-naïve PD patients and can be used to accurately diagnose PD and prodromal PD. This suggests that urine and CSF DDC could be a promising diagnostic and prognostic marker with utility in both clinical care and translational research.

Systemic lupus erythematosus: one year in review 2024.

Systemic lupus erythematosus (SLE) is classically regarded as the landmark of systemic autoimmune diseases, characterised by protean, multi-systemic manifestations and a highly variable clinical course.Over the last years, both clinical and translational clinical research efforts led to significant steps forward in management and treatment of SLE. However, numerous aspects of SLE, from pathogenesis to treatment, still remain challenging, and several unmet needs persist for both patients and physicians. Following the previous annual reviews of this series, herewith, we aim to report the most relevant new updates on SLE, issued in 2023. In particular, we focused on biomarkers, clinical aspects and outcomes, comorbidities, as well as new treatment targets and real-world evidence.

Banff scoring of kidney allograft biopsies: “Manual” application vs software-assisted sign-out

Abstract Objectives Pathologists interpreting kidney allograft biopsies using the Banff system usually start by recording component scores (eg, i, t, cg) using histopathologic criteria committed to memory. Component scores are then melded into diagnoses using the same manual/mental processes. This approach to complex Banff rules during routine sign-out produces a lack of fidelity and needs improvement. Methods We constructed a web-based “smart template” (software-assisted sign-out) system that uniquely starts with upstream Banff-defined additional diagnostic parameters (eg, infection) and histopathologic criteria (eg, percent interstitial inflammation) collectively referred to as feeder data that is then translated into component scores and integrated into final diagnoses using software-encoded decision trees. Results Software-assisted sign-out enables pathologists to (1) accurately and uniformly apply Banff rules, thereby eliminating human inconsistencies (present in 25% of the cohort); (2) document areas of improvement; (3) show improved correlation with function; (4) examine t-Distributed Stochastic Neighbor Embedding clustering for diagnosis stratification; and (5) ready upstream incorporation of artificial intelligence–assisted scoring of biopsies. Conclusions Compared with the legacy approach, software-assisted sign-out improves Banff accuracy and fidelity, more closely correlates with kidney function, is practical for routine clinical work and translational research studies, facilitates downstream integration with nonpathology data, and readies biopsy scoring for artificial intelligence algorithms.

A transformer-based pyramid network for coronary calcified plaque segmentation in intravascular optical coherence tomography images

Characterizing coronary calcified plaque (CCP) provides essential insight into diagnosis and treatment of atherosclerosis. Intravascular optical coherence tomography (OCT) offers significant advantages for detecting CCP and even automated segmentation with recent advances in deep learning techniques. Most of current methods have achieved promising results by adopting existing convolution neural networks (CNNs) in computer vision domain. However, their performance can be detrimentally affected by unseen plaque patterns and artifacts due to inherent limitation of CNNs in contextual reasoning. To overcome this obstacle, we proposed a Transformer-based pyramid network called AFS-TPNet for robust, end-to-end segmentation of CCP from OCT images. Its encoder is built upon CSWin Transformer architecture, allowing for better perceptual understanding of calcified arteries at a higher semantic level. Specifically, an augmented feature split (AFS) module and residual convolutional position encoding (RCPE) mechanism are designed to effectively enhance the capability of Transformer in capturing both fine-grained features and global contexts. Extensive experiments showed that AFS-TPNet trained using Lovasz Loss achieved superior performance in segmentation CCP under various contexts, surpassing prior state-of-the-art CNN and Transformer architectures by more than 6.58% intersection over union (IoU) score. The application of this promising method to extract CCP features is expected to enhance clinical intervention and translational research using OCT.

ARDaC Common Data Model Facilitates Data Dissemination and Enables Data Commons for Modern Clinical Studies.

Modern clinical studies collect longitudinal and multimodal data about participants, treatments and responses, biospecimens, and molecular and multiomics data. Such rich and complex data requires new common data models (CDM) to support data dissemination and research collaboration. We have developed the ARDaC CDM for the Alcoholic Hepatitis Network (AlcHepNet) Research Data Commons (ARDaC) to support clinical studies and translational research in the national AlcHepNet consortium. The ARDaC CDM bridges the gap between the data models used by the AlcHepNet electronic data capture platform (REDCap) and the Genomic Data Commons (GDC) data model used by the Gen3 data commons framework. It extends the GDC data model for clinical studies; facilitates the harmonization of research data across consortia and programs; and supports the development of the ARDaC. ARDaC CDM is designed as a general and extensible CDM for addressing the needs of modern clinical studies. The ARDaC CDM is available at https://dev.ardac.org/DD.

Tetrahedral DNA loaded siCCR2 restrains M1 macrophage polarization to ameliorate pulmonary fibrosis in chemoradiation-induced murine model

Idiopathic pulmonary fibrosis (IPF) is a chronic lethal disease in the absence of demonstrated efficacy for preventing progression. Although macrophage-mediated alveolitis is determined to participate in myofibrotic transition during disease development, the paradigm of continuous macrophage polarization is still under-explored due to lack of proper animal models. Here, by integrating 2.5U/kg intratracheal Bleomycin administration and 10Gy thorax irradiation at day 7, we generated a murine model with continuous alveolitis-mediated fibrosis, which mimics most of the clinical features of our involved IPF patients. In combination with data from scRNA-seq of patients and a murine IPF model, a decisive role of CCL2/CCR2 axis in driving M1 macrophage polarization was revealed, and M1 macrophage was further confirmed to boost alveolitis in leading myofibroblast activation. Multiple sticky-end tetrahedral framework nucleic acids conjunct with quadruple ccr2-siRNA (FNA-siCCR2) was synthesized in targeting M1 macrophages. FNA-siCCR2 successfully blocked macrophage accumulation in pulmonary parenchyma of the IPF murine model, thus preventing myofibroblast activation and leading to the disease remitting. Overall, our studies lay the groundwork to develop a novel IPF murine model, reveal M1 macrophages as potential therapeutic targets, and establish new treatment strategy by using FNA-siCCR2, which are highly relevant to clinical scenarios and translational research in the field of IPF.

The clinical implication and translational research of OSCC differentiation.

The clinical value and molecular characteristics of tumor differentiation in oral squamous cell carcinoma (OSCC) remain unclear. There is a lack of a related molecular classification prediction system based on pathological images for precision medicine. Integration of epidemiology, genomics, experiments, and deep learning to clarify the clinical value and molecular characteristics, and develop a novel OSCC molecular classification prediction system. Large-scale epidemiology data (n = 118,817) demonstrated OSCC differentiation was a significant prognosis indicator (p < 0.001), and well-differentiated OSCC was more chemo-resistant than poorly differentiated OSCC. These results were confirmed in the TCGA database and in vitro. Furthermore, we found chemo-resistant related pathways and cell cycle-related pathways were up-regulated in well- and poorly differentiated OSCC, respectively. Based on the characteristics of OSCC differentiation, a molecular grade of OSCC was obtained and combined with pathological images to establish a novel prediction system through deep learning, named ShuffleNetV2-based Molecular Grade of OSCC (SMGO). Importantly, our independent multi-center cohort of OSCC (n = 340) confirmed the high accuracy of SMGO. OSCC differentiation was a significant indicator of prognosis and chemotherapy selection. Importantly, SMGO could be an indispensable reference for OSCC differentiation and assist the decision-making of chemotherapy.

Recent advances in targeted drug delivery for the treatment of glioblastoma.

Glioblastoma multiforme (GBM) is one of the highly malignant brain tumors characterized by significant morbidity and mortality. Despite the recent advancements in the treatment of GBM, major challenges persist in achieving controlled drug delivery to tumors. The management of GBM poses considerable difficulties primarily due to unresolved issues in the blood-brain barrier (BBB)/blood-brain tumor barrier (BBTB) and GBM microenvironment. These factors limit the uptake of anti-cancer drugs by the tumor, thus limiting the therapeutic options. Current breakthroughs in nanotechnology provide new prospects concerning unconventional drug delivery approaches for GBM treatment. Specifically, swimming nanorobots show great potential in active targeted delivery, owing to their autonomous propulsion and improved navigation capacities across biological barriers, which further facilitate the development of GBM-targeted strategies. This review presents an overview of technological progress in different drug administration methods for GBM. Additionally, the limitations in clinical translation and future research prospects in this field are also discussed. This review aims to provide a comprehensive guideline for researchers and offer perspectives on further development of new drug delivery therapies to combat GBM.

Empowering the Participant Voice (EPV): Design and implementation of collaborative infrastructure to collect research participant experience feedback at scale.

Empowering the Participant Voice (EPV) is an NCATS-funded six-CTSA collaboration to develop, demonstrate, and disseminate a low-cost infrastructure for collecting timely feedback from research participants, fostering trust, and providing data for improving clinical translational research. EPV leverages the validated Research Participant Perception Survey (RPPS) and the popular REDCap electronic data-capture platform. This report describes the development of infrastructure designed to overcome identified institutional barriers to routinely collecting participant feedback using RPPS and demonstration use cases. Sites engaged local stakeholders iteratively, incorporating feedback about anticipated value and potential concerns into project design. The team defined common standards and operations, developed software, and produced a detailed planning and implementation Guide. By May 2023, 2,575 participants diverse in age, race, ethnicity, and sex had responded to approximately 13,850 survey invitations (18.6%); 29% of responses included free-text comments. EPV infrastructure enabled sites to routinely access local and multi-site research participant experience data on an interactive analytics dashboard. The EPV learning collaborative continues to test initiatives to improve survey reach and optimize infrastructure and process. Broad uptake of EPV will expand the evidence base, enable hypothesis generation, and drive research-on-research locally and nationally to enhance the clinical research enterprise.

The development of a hiPSC-based platform to identify tissue-dependencies of IDH1 R132H

The application of patient-derived (PD) in vitro tumor models represents the classical strategy for clinical translational oncology research. Using these cellular heterogeneous cultures for the isolation of cancer stem cells (CSCs), suggested to be the main driver for disease malignancy, relies on the use of surrogate biomarkers or is based on CSC-enriching culture conditions. However, the ability of those strategies to exclusively and efficiently enrich for CSC pool has been questioned. Here we present an alternative in vitro CSC model based on the oncogenic transformation of single clone-derived human induced pluripotent stem cells (hiPSC). Hotspot mutations in the DNA encoding for the R132 codon of the enzyme isocitrate dehydrogenase 1 (IDH1) and codon R175 of p53 are commonly occurring molecular features of different tumors and were selected for our transformation strategy. By choosing p53 mutant glial tumors as our model disease, we show that in vitro therapy discovery tests on IDH1-engineered synthetic CSCs (sCSCs) can identify kinases-targeting chemotherapeutics that preferentially target tumor cells expressing corresponding genetic alteration. In contrast, neural stem cells (NSCs) derived from the IDH1R132H overexpressing hiPSCs increase their resistance to the tested interventions indicating glial–to-neural tissue-dependent differences of IDH1R132H. Taken together, we provide proof for the potential of our sCSC technology as a potent addition to biomarker-driven drug development projects or studies on tumor therapy resistance. Moreover, follow-up projects such as comparing in vitro drug sensitivity profiles of hiPSC-derived tissue progenitors of different lineages, might help to understand a variety of tissue-related functions of IDH1 mutations.

Abstract C057: Methylome-wide profiling of early-onset colorectal cancer in underrepresented populations

Abstract Colorectal cancer (CRC) is the third leading cause of death from cancer in both men and women in the United States. Late onset colorectal cancer (LOCRC) or CRC diagnosed in older adults &amp;gt;50 years old has continued to decline while early onset colorectal cancer (EOCRC) or colorectal cancer in patients under the age of 50 continues to rise at an alarming rate since the mid-1990s. In fact, EOCRC is now the second most common cancer and the third leading cause of cancer mortality in people &amp;lt;50 years of age in the USA. The incidence of EOCRC has been on the rise over the past four decades and is expected to increase by &amp;gt;140% by 2030. Notably, Blacks and Hispanics are disproportionately affected with the EOCRC diagnosis. Despite this, minority patients remain underrepresented in clinical trials and translational research. It has been proposed that environmental exposures including westernized diet, metabolic factors, and the microbiome might be responsible for the rise in incidence of EOCRC. Epigenetic modifications are well-known mechanisms by which the environment can modulate gene expression without changing the DNA sequence. One such modification is DNA methylation, which controls DNA accessibility, chromatin formation, and gene transcriptional activity. Unfortunately, however, little is known about the role of DNA methylation in EOCRC and much less is understood of EOCRC in minority populations. Therefore, we identified a unique cohort of 11 EOCRC patients within the Baylor College of Medicine/Harris Health System which is comprised of majority minority EOCRC population (7- Hispanic, 2 Non-Hispanic (NH) Black, and 1 NH-White EOCRC patients). Using whole-genome bisulfite sequencing, we comprehensively characterized the DNA methylome at single-base resolution in our 11 EOCRC patient samples. Our analyses revealed distinct EOCRC methylation patterns including both global hypomethylation and promoter-specific hypermethylation, which were not previously captured in The Cancer Genome Atlas (TCGA) Analyses. Among the differentially methylated regions (DMRs), we discovered that DNA and RNA transcription pathways were enriched in EOCRCs at advanced stage. Furthermore, we identify differential DMRs patterns among ethnicities. Taken together, our work supports a pathogenic role for DNA methylation in EOCRC. We are the first group to take this comprehensive unbiased approach to analyze the methylome in an underrepresented EOCRC cohort of patients. Citation Format: Karen Riggins, Jason Sheng Li, Benjamin Musher, Li Yang, Patricia Castro, Wedad Alfarkh, Neda Zarrin-Kamah, Michael Scheurer, Chad Creighton, Wei Li, Lanlan Shen. Methylome-wide profiling of early-onset colorectal cancer in underrepresented populations [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C057.