Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence.

Clinical research relies on high-quality patient data, however, obtaining big data sets is costly and access to existing data is often hindered by privacy and regulatory concerns. Synthetic data generation holds the promise of effectively bypassing these boundaries allowing for simplified data accessibility and the prospect of synthetic control cohorts. We employed two different methodologies of generative artificial intelligence - CTAB-GAN+ and normalizing flows (NFlow) - to synthesize patient data derived from 1606 patients with acute myeloid leukemia, a heterogeneous hematological malignancy, that were treated within four multicenter clinical trials. Both generative models accurately captured distributions of demographic, laboratory, molecular and cytogenetic variables, as well as patient outcomes yielding high performance scores regarding fidelity and usability of both synthetic cohorts (n = 1606 each). Survival analysis demonstrated close resemblance of survival curves between original and synthetic cohorts. Inter-variable relationships were preserved in univariable outcome analysis enabling explorative analysis in our synthetic data. Additionally, training sample privacy is safeguarded mitigating possible patient re-identification, which we quantified using Hamming distances. We provide not only a proof-of-concept for synthetic data generation in multimodal clinical data for rare diseases, but also full public access to synthetic data sets to foster further research.

Integrated analysis of transcriptome and epigenome reveals ENSR00000272060 as a potential biomarker in gastric cancer.

Background: Enhancer RNAs (eRNAs) are involved in gene expression regulation. Although functional roles of eRNAs in the pathophysiology of neoplasms have been reported, their involvement in gastric cancer (GC) is less known. Materials & methods: A network-based integrative approach was utilized for analyzing transcriptome and epigenome alterations in GC, and an eRNA was selected for experimental validation. Survival analysis and clinicopathological associations were also performed. Results: A hub eRNA, ENSR00000272060, showed significantly increased expression in tumor versus nontumor tissues, as well as an association with clinicopathological features. A seven-gene prognostic model was also constructed. Conclusion: The constructed network provides a comprehensive understanding of the underlying processes implicated in the progression of GC, along with a starting point from which to derive potential diagnostic/prognostic biomarkers.

What is this summary about? We provide an overview of a study on genetic materials related to stomach cancer. This study could help identify factors that change the progress of this disease. We used genetic information from a specific disease database. One of the genetic materials that was assessed is eRNA. It was examined in some samples of gastric cancer. We analyzed gastric tissues to confirm our findings. The goal of this study was to find out whether we could identify a disease-related eRNA. What were the results? We found an eRNA that showed genetic differences between examined samples. It was also related to the stage of the disease. What do the results mean? The results show that there is a difference in the amount of examined eRNA between samples. It suggests that we may be able to use it to detect the disease earlier.

CCR2 macrophage response determines the functional outcome following cardiomyocyte transplantation.

BACKGROUND: The immune response is a crucial factor for mediating the benefit of cardiac cell therapies. Our previous research showed that cardiomyocyte transplantation alters the cardiac immune response and, when combined with short-term pharmacological CCR2 inhibition, resulted in diminished functional benefit. However, the specific role of innate immune cells, especially CCR2 macrophages on the outcome of cardiomyocyte transplantation, is unclear. METHODS: We compared the cellular, molecular, and functional outcome following cardiomyocyte transplantation in wildtype and T cell- and B cell-deficient Rag2del mice. The cardiac inflammatory response was assessed using flow cytometry. Gene expression profile was assessed using single-cell and bulk RNA sequencing. Cardiac function and morphology were determined using magnetic resonance tomography and immunohistochemistry respectively. RESULTS: Compared to wildtype mice, Rag2del mice show an increased innate immune response at steady state and disparate macrophage response after MI. Subsequent single-cell analyses after MI showed differences in macrophage development and a lower prevalence of CCR2 expressing macrophages. Cardiomyocyte transplantation increased NK cells and monocytes, while reducing CCR2-MHC-IIlo macrophages. Consequently, it led to increased mRNA levels of genes involved in extracellular remodelling, poor graft survival, and no functional improvement. Using machine learning-based feature selection, Mfge8 and Ccl7 were identified as the primary targets underlying these effects in the heart. CONCLUSIONS: Our results demonstrate that the improved functional outcome following cardiomyocyte transplantation is dependent on a specific CCR2 macrophage response. This work highlights the need to study the role of the immune response for cardiomyocyte cell therapy for successful clinical translation.

Cardiac cell therapies for the treatment of acute myocardial infarction in mice: systematic review and meta-analysis.

Backgound Aims: This meta-analysis aims at summarizing the whole body of research on cell therapies for acute myocardial infarction (MI) in the mouse model to bring forward ongoing research in this field of regenerative medicine. Despite rather modest effects in clinical trials, pre-clinical studies continue to report beneficial effects of cardiac cell therapies for cardiac repair following acute ischemic injury. Results: The authors' meta-analysis of data from 166 mouse studies comprising 257 experimental groups demonstrated a significant improvement in left ventricular ejection fraction of 10.21% after cell therapy compared with control animals. Subgroup analysis indicated that second-generation cell therapies such as cardiac progenitor cells and pluripotent stem cell derivatives had the highest therapeutic potential for minimizing myocardial damage post-MI. Conclusions: Whereas the vision of functional tissue replacement has been replaced by the concept of regional scar modulation in most of the investigated studies, rather basic methods for assessing cardiac function were most frequently used. Hence, future studies will highly benefit from integrating methods for assessment of regional wall properties to evolve a deeper understanding of how to modulate cardiac healing after acute MI.

Construction of a three-component regulatory network of transcribed ultraconserved regions for the identification of prognostic biomarkers in gastric cancer.

Altered expression and functional roles of the transcribed ultraconserved regions (T-UCRs), as genomic sequences with 100% conservation between the genomes of human, mouse, and rat, in the pathophysiology of neoplasms has already been investigated. Nevertheless, the relevance of the functions for T-UCRs in gastric cancer (GC) is still the subject of inquiry. In the current study, we first used a genome-wide profiling approach to analyze the expression of T-UCRs in GC patients. Then, we constructed a three-component regulatory network and investigated potential diagnostic and prognostic values of the T-UCRs. The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) dataset was used as a resource for the RNA-sequencing data. FeatureCounts was utilized to quantify the number of reads mapped to each T-UCR. Differential expression analysis was then conducted using DESeq2. In the following, interactions between T-UCRs, microRNAs (miRNAs), and messenger RNAs (mRNAs) were combined into a three-component network. Enrichment analyses were performed and a protein-protein interaction (PPI) network was constructed. The R Survival package was utilized to identify survival-related significantly differentially expressed T-UCRs (DET-UCRs). Using an in-house cohort of GC tissues, expression of two DET-UCRs was furthermore experimentally verified. Our results showed that several T-UCRs were dysregulated in TCGA-STAD tumoral samples compared to nontumoral counterparts. The three-component network was constructed which composed of DET-UCRs, miRNAs, and mRNAs nodes. Functional enrichment and PPI network analyses revealed important enriched signaling pathways and gene ontologies such as "pathway in cancer" and regulation of cell proliferation and apoptosis. Five T-UCRs were significantly correlated with the overall survival of GC patients. While no expression of uc.232 was observed in our in-house cohort of GC tissues, uc.343 showed an increased expression, although not statistically significant, in gastric tumoral tissues. The constructed three-component regulatory network of T-UCRs in GC presents a comprehensive understanding of the underlying gene expression regulation processes involved in tumor development and can serve as a basis to investigate potential prognostic biomarkers and therapeutic targets.

OMOP CDM Can Facilitate Data-Driven Studies for Cancer Prediction: A Systematic Review.

The current generation of sequencing technologies has led to significant advances in identifying novel disease-associated mutations and generated large amounts of data in a high-throughput manner. Such data in conjunction with clinical routine data are proven to be highly useful in deriving population-level and patient-level predictions, especially in the field of cancer precision medicine. However, data harmonization across multiple national and international clinical sites is an essential step for the assessment of events and outcomes associated with patients, which is currently not adequately addressed. The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is an internationally established research data repository introduced by the Observational Health Data Science and Informatics (OHDSI) community to overcome this issue. To address the needs of cancer research, the genomic vocabulary extension was introduced in 2020 to support the standardization of subsequent data analysis. In this review, we evaluate the current potential of the OMOP CDM to be applicable in cancer prediction and how comprehensively the genomic vocabulary extension of the OMOP can serve current needs of AI-based predictions. For this, we systematically screened the literature for articles that use the OMOP CDM in predictive analyses in cancer and investigated the underlying predictive models/tools. Interestingly, we found 248 articles, of which most use the OMOP for harmonizing their data, but only 5 make use of predictive algorithms on OMOP-based data and fulfill our criteria. The studies present multicentric investigations, in which the OMOP played an essential role in discovering and optimizing machine learning (ML)-based models. Ultimately, the use of the OMOP CDM leads to standardized data-driven studies for multiple clinical sites and enables a more solid basis utilizing, e.g., ML models that can be reused and combined in early prediction, diagnosis, and improvement of personalized cancer care and biomarker discovery.

The Effects of Hypoxic Preconditioned Murine Mesenchymal Stem Cells on Post-Infarct Arrhythmias in the Mouse Model.

Ventricular arrhythmias associated with myocardial infarction (MI) have a significant impact on mortality in patients following heart attack. Therefore, targeted reduction of arrhythmia represents a therapeutic approach for the prevention and treatment of severe events after infarction. Recent research transplanting mesenchymal stem cells (MSC) showed their potential in MI therapy. Our study aimed to investigate the effects of MSC injection on post-infarction arrhythmia. We used our murine double infarction model, which we previously established, to more closely mimic the clinical situation and intramyocardially injected hypoxic pre-conditioned murine MSC to the infarction border. Thereafter, various types of arrhythmias were recorded and analyzed. We observed a homogenous distribution of all types of arrhythmias after the first infarction, without any significant differences between the groups. Yet, MSC therapy after double infarction led to a highly significant reduction in simple and complex arrhythmias. Moreover, RNA-sequencing of samples from stem cell treated mice after re-infarction demonstrated a significant decline in most arrhythmias with reduced inflammatory pathways. Additionally, following stem-cell therapy we found numerous highly expressed genes to be either linked to lowering the risk of heart failure, cardiomyopathy or sudden cardiac death. Moreover, genes known to be associated with arrhythmogenesis and key mutations underlying arrhythmias were downregulated. In summary, our stem-cell therapy led to a reduction in cardiac arrhythmias after MI and showed a downregulation of already established inflammatory pathways. Furthermore, our study reveals gene regulation pathways that have a potentially direct influence on arrhythmogenesis after myocardial infarction.

Personalized Cell Therapy for Patients with Peripheral Arterial Diseases in the Context of Genetic Alterations: Artificial Intelligence-Based Responder and Non-Responder Prediction.

Stem/progenitor cell transplantation is a potential novel therapeutic strategy to induce angiogenesis in ischemic tissue, which can prevent major amputation in patients with advanced peripheral artery disease (PAD). Thus, clinicians can use cell therapies worldwide to treat PAD. However, some cell therapy studies did not report beneficial outcomes. Clinical researchers have suggested that classical risk factors and comorbidities may adversely affect the efficacy of cell therapy. Some studies have indicated that the response to stem cell therapy varies among patients, even in those harboring limited risk factors. This suggests the role of undetermined risk factors, including genetic alterations, somatic mutations, and clonal hematopoiesis. Personalized stem cell-based therapy can be developed by analyzing individual risk factors. These approaches must consider several clinical biomarkers and perform studies (such as genome-wide association studies (GWAS)) on disease-related genetic traits and integrate the findings with those of transcriptome-wide association studies (TWAS) and whole-genome sequencing in PAD. Additional unbiased analyses with state-of-the-art computational methods, such as machine learning-based patient stratification, are suited for predictions in clinical investigations. The integration of these complex approaches into a unified analysis procedure for the identification of responders and non-responders before stem cell therapy, which can decrease treatment expenditure, is a major challenge for increasing the efficacy of therapies.

Cardiomyocyte Transplantation after Myocardial Infarction Alters the Immune Response in the Heart.

We investigated the influence of syngeneic cardiomyocyte transplantation after myocardial infarction (MI) on the immune response and cardiac function. Methods and Results: We show for the first time that the immune response is altered as a result of syngeneic neonatal cardiomyocyte transplantation after MI leading to improved cardiac pump function as observed by magnetic resonance imaging in C57BL/6J mice. Interestingly, there was no improvement in the capillary density as well as infarct area as observed by CD31 and Sirius Red staining, respectively. Flow cytometric analysis revealed a significantly different response of monocyte-derived macrophages and regulatory T cells after cell transplantation. Interestingly, the inhibition of monocyte infiltration accompanied by cardiomyocyte transplantation diminished the positive effect of cell transplantation alone. The number of CD68+ macrophages in the remote area of the heart observed after four weeks was also different between the groups. Transcriptome analysis showed several changes in the gene expression involving circadian regulation, mitochondrial metabolism and immune responses after cardiomyocyte transplantation. Conclusion: Our work shows that cardiomyocyte transplantation alters the immune response after myocardial infarction with the recruited monocytes playing a role in the beneficial effect of cell transplantation. It also paves the way for further optimization of the efficacy of cardiomyocyte transplantation and their successful translation in the clinic.

Hematopoietic stem-cell senescence and myocardial repair - Coronary artery disease genotype/phenotype analysis of post-MI myocardial regeneration response induced by CABG/CD133+ bone marrow hematopoietic stem cell treatment in RCT PERFECT Phase 3.

BACKGROUND: Bone marrow stem cell clonal dysfunction by somatic mutation is suspected to affect post-infarction myocardial regeneration after coronary bypass surgery (CABG). METHODS: Transcriptome and variant expression analysis was studied in the phase 3 PERFECT trial post myocardial infarction CABG and CD133+ bone marrow derived hematopoetic stem cells showing difference in left ventricular ejection fraction (∆LVEF) myocardial regeneration Responders (n=14; ∆LVEF +16% day 180/0) and Non-responders (n=9; ∆LVEF -1.1% day 180/0). Subsequently, the findings have been validated in an independent patient cohort (n=14) as well as in two preclinical mouse models investigating SH2B3/LNK antisense or knockout deficient conditions. FINDINGS: 1. Clinical: R differed from NR in a total of 161 genes in differential expression (n=23, q<0•05) and 872 genes in coexpression analysis (n=23, q<0•05). Machine Learning clustering analysis revealed distinct RvsNR preoperative gene-expression signatures in peripheral blood acorrelated to SH2B3 (p<0.05). Mutation analysis revealed increased specific variants in RvsNR. (R: 48 genes; NR: 224 genes). 2. Preclinical:SH2B3/LNK-silenced hematopoietic stem cell (HSC) clones displayed significant overgrowth of myeloid and immune cells in bone marrow, peripheral blood, and tissue at day 160 after competitive bone-marrow transplantation into mice. SH2B3/LNK-/- mice demonstrated enhanced cardiac repair through augmenting the kinetics of bone marrow-derived endothelial progenitor cells, increased capillary density in ischemic myocardium, and reduced left ventricular fibrosis with preserved cardiac function. 3. VALIDATION: Evaluation analysis in 14 additional patients revealed 85% RvsNR (12/14 patients) prediction accuracy for the identified biomarker signature. INTERPRETATION: Myocardial repair is affected by HSC gene response and somatic mutation. Machine Learning can be utilized to identify and predict pathological HSC response. FUNDING: German Ministry of Research and Education (BMBF): Reference and Translation Center for Cardiac Stem Cell Therapy - FKZ0312138A and FKZ031L0106C, German Ministry of Research and Education (BMBF): Collaborative research center - DFG:SFB738 and Center of Excellence - DFG:EC-REBIRTH), European Social Fonds: ESF/IV-WM-B34-0011/08, ESF/IV-WM-B34-0030/10, and Miltenyi Biotec GmbH, Bergisch-Gladbach, Germany. Japanese Ministry of Health : Health and Labour Sciences Research Grant (H14-trans-001, H17-trans-002) TRIAL REGISTRATION: ClinicalTrials.gov NCT00950274.

RNA-Based Strategies for Cardiac Reprogramming of Human Mesenchymal Stromal Cells.

Multipotent adult mesenchymal stromal cells (MSCs) could represent an elegant source for the generation of patient-specific cardiomyocytes needed for regenerative medicine, cardiovascular research, and pharmacological studies. However, the differentiation of adult MSC into a cardiac lineage is challenging compared to embryonic stem cells or induced pluripotent stem cells. Here we used non-integrative methods, including microRNA and mRNA, for cardiac reprogramming of adult MSC derived from bone marrow, dental follicle, and adipose tissue. We found that MSC derived from adipose tissue can partly be reprogrammed into the cardiac lineage by transient overexpression of GATA4, TBX5, MEF2C, and MESP1, while cells isolated from bone marrow, and dental follicle exhibit only weak reprogramming efficiency. qRT-PCR and transcriptomic analysis revealed activation of a cardiac-specific gene program and up-regulation of genes known to promote cardiac development. Although we did not observe the formation of fully mature cardiomyocytes, our data suggests that adult MSC have the capability to acquire a cardiac-like phenotype when treated with mRNA coding for transcription factors that regulate heart development. Yet, further optimization of the reprogramming process is mandatory to increase the reprogramming efficiency.

Stem cells and heart disease - Brake or accelerator?

After two decades of intensive research and attempts of clinical translation, stem cell based therapies for cardiac diseases are not getting closer to clinical success. This review tries to unravel the obstacles and focuses on underlying mechanisms as the target for regenerative therapies. At present, the principal outcome in clinical therapy does not reflect experimental evidence. It seems that the scientific obstacle is a lack of integration of knowledge from tissue repair and disease mechanisms. Recent insights from clinical trials delineate mechanisms of stem cell dysfunction and gene defects in repair mechanisms as cause of atherosclerosis and heart disease. These findings require a redirection of current practice of stem cell therapy and a reset using more detailed analysis of stem cell function interfering with disease mechanisms. To accelerate scientific development the authors suggest intensifying unified computational data analysis and shared data knowledge by using open-access data platforms.

Cardiac Function Improvement and Bone Marrow Response -: Outcome Analysis of the Randomized PERFECT Phase III Clinical Trial of Intramyocardial CD133+ Application After Myocardial Infarction.

OBJECTIVE: The phase III clinical trial PERFECT was designed to assess clinical safety and efficacy of intramyocardial CD133+ bone marrow stem cell treatment combined with CABG for induction of cardiac repair. DESIGN: Multicentre, double-blinded, randomised placebo controlled trial. SETTING: The study was conducted across six centres in Germany October 2009 through March 2016 and stopped due slow recruitment after positive interim analysis in March 2015. PARTICIPANTS: Post-infarction patients with chronic ischemia and reduced LVEF (25-50%). INTERVENTIONS: Eighty-two patients were randomised to two groups receiving intramyocardial application of 5ml placebo or a suspension of 0.5-5×106 CD133+. OUTCOME: Primary endpoint was delta (∆) LVEF at 180days (d) compared to baseline measured in MRI. FINDINGS (PRESPECIFIED): Safety (n=77): 180d survival was 100%, MACE n=2, SAE n=49, without difference between placebo and CD133+. Efficacy (n=58): The LVEF improved from baseline LVEF 33.5% by +9.6% at 180d, p=0.001 (n=58). Treatment groups were not different in ∆LVEF (ANCOVA: Placebo +8.8% vs. CD133+ +10.4%, ∆CD133+vs placebo +2.6%, p=0.4). FINDINGS (POST HOC): Responders (R) classified by ∆LVEF≥5% after 180d were 60% of the patients (35/58) in both treatment groups. ∆LVEF in ANCOVA was +17.1% in (R) vs. non-responders (NR) (∆LVEF 0%, n=23). NR were characterized by a preoperative response signature in peripheral blood with reduced CD133+ EPC (RvsNR: p=0.005) and thrombocytes (p=0.004) in contrast to increased Erythropoeitin (p=0.02), and SH2B3 mRNA expression (p=0.073). Actuarial computed mean survival time was 76.9±3.32months (R) vs. +72.3±5.0months (NR), HR 0.3 [Cl 0.07-1.2]; p=0.067.Using a machine learning 20 biomarker response parameters were identified allowing preoperative discrimination with an accuracy of 80% (R) and 84% (NR) after 10-fold cross-validation. INTERPRETATION: The PERFECT trial analysis demonstrates that the regulation of induced cardiac repair is linked to the circulating pool of CD133+ EPC and thrombocytes, associated with SH2B3 gene expression. Based on these findings, responders to cardiac functional improvement may be identified by a peripheral blood biomarker signature. TRIAL REGISTRATION: ClinicalTrials.govNCT00950274.

Cardiac Cell Therapies for the Treatment of Acute Myocardial Infarction: A Meta-Analysis from Mouse Studies.

AIMS: Stem cell-based regenerative therapies for the treatment of ischemic myocardium are currently a subject of intensive investigation. A variety of cell populations have been demonstrated to be safe and to exert some positive effects in human Phase I and II clinical trials, however conclusive evidence of efficacy is still lacking. While the relevance of animal models for appropriate pre-clinical safety and efficacy testing with regard to application in Phase III studies continues to increase, concerns have been expressed regarding the validity of the mouse model to predict clinical results. Against the background that hundreds of preclinical studies have assessed the efficacy of numerous kinds of cell preparations - including pluripotent stem cells - for cardiac repair, we undertook a systematic re-evaluation of data from the mouse model, which initially paved the way for the first clinical trials in this field. METHODS AND RESULTS: A systematic literature screen was performed to identify publications reporting results of cardiac stem cell therapies for the treatment of myocardial ischemia in the mouse model. Only peer-reviewed and placebo-controlled studies using magnet resonance imaging (MRI) for left ventricular ejection fraction (LVEF) assessment were included. Experimental data from 21 studies involving 583 animals demonstrate a significant improvement in LVEF of 8.59%+/- 2.36; p=.012 (95% CI, 3.7-13.8) compared with control animals. CONCLUSION: The mouse is a valid model to evaluate the efficacy of cell-based advanced therapies for the treatment of ischemic myocardial damage. Further studies are required to understand the mechanisms underlying stem cell based improvement of cardiac function after ischemia.

Ca2+/calmodulin-dependent kinase II contributes to inhibitor of nuclear factor-kappa B kinase complex activation in Helicobacter pylori infection.

Helicobacter pylori, a class I carcinogen, induces a proinflammatory response by activating the transcription factor nuclear factor-kappa B (NF-κB) in gastric epithelial cells. This inflammatory condition could lead to chronic gastritis, which is epidemiologically and biologically linked to the development of gastric cancer. So far, there exists no clear knowledge on how H. pylori induces the NF-κB-mediated inflammatory response. In our study, we investigated the role of Ca(2+) /calmodulin-dependent kinase II (CAMKII), calmodulin, protein kinases C (PKCs) and the CARMA3-Bcl10-MALT1 (CBM) complex in conjunction with H. pylori-induced activation of NF-κB via the inhibitor of nuclear factor-kappa B kinase (IKK) complex. We use specific inhibitors and/or RNA interference to assess the contribution of these components. Our results show that CAMKII and calmodulin contribute to IKK complex activation and thus to the induction of NF-κB in response to H. pylori infection, but not in response to TNF-α. Thus, our findings are specific for H. pylori infected cells. Neither the PKCs α, δ, θ, nor the CBM complex itself is involved in the activation of NF-κB by H. pylori. The contribution of CAMKII and calmodulin, but not PKCs/CBM to the induction of an inflammatory response by H. pylori infection augment the understanding of the molecular mechanism involved and provide potential new disease markers for the diagnosis of gastric inflammatory diseases including gastric cancer.