Citations

Hypoplastic left heart syndrome (HLHS) is a severe congenital heart disease (CHD) with a likely oligogenic etiology, but our understanding of the genetic complexities and pathogenic mechanisms leading to HLHS is limited. We performed whole genome sequencing (WGS) on 183 HLHS patient-parent trios to identify candidate genes, which were functionally tested in the Drosophila heart model. Bioinformatic analysis of WGS data from an index family of a HLHS proband born to consanguineous parents prioritized 9 candidate genes with rare, predicted damaging homozygous variants. Of them, cardiac-specific knockdown (KD) of mitochondrial MICOS complex subunit dCHCHD3/6 resulted in drastically compromised heart contractility, diminished levels of sarcomeric actin and myosin, reduced cardiac ATP levels, and mitochondrial fission-fusion defects. These defects were similar to those inflicted by cardiac KD of ATP synthase subunits of the electron transport chain (ETC), consistent with the MICOS complex’s role in maintaining cristae morphology and ETC assembly. Five additional HLHS probands harbored rare, predicted damaging variants in CHCHD3 or CHCHD6 . Hypothesizing an oligogenic basis for HLHS, we tested 60 additional prioritized candidate genes from these patients for genetic interactions with CHCHD3/6 in sensitized fly hearts. Moderate KD of CHCHD3/6 in combination with Cdk12 (activator of RNA polymerase II), RNF149 ( goliath , E3 ubiquitin ligase), or SPTBN1 ( β-Spectrin, scaffolding protein) caused synergistic heart defects, suggesting the likely involvement of diverse pathways in HLHS. Further elucidation of novel candidate genes and genetic interactions of potentially disease-contributing pathways is expected to lead to a better understanding of HLHS and other CHDs.

Abstract Background and Aims The iBox is a validated prognostication system predicting long-term kidney allograft failure. Recently, it received regulatory endorsement by EMA, for surrogate endpoint for clinical trials. As the iBox system was primarily built using a deep phenotyped cohort, there is a need for proof of validity in extended clinical scenarios, geographic distinct medico-economic cohorts and transplant allocation systems. Method 10,851 transplant recipients were included from 17 academic medical centers from France, Belgium, Spain, Germany, Finland, United States, Brazil and Argentina. We applied to these cohorts the iBox algorithm that integrates eight independent prognostic factors including the time from transplantation to risk evaluation, functional parameters (eGFR, proteinuria), allograft histological lesions (IFTA, g+ptc, i+t, cg Banff scores), and circulating anti-HLA DSA. We stratified the performances of the iBox according to several real-life scenarios, including: 1) iBox + different eGFR formulas (MDRD186, MDRD175, CKD-Epi); 2) iBox + urinary dipstick; 3) iBox Functional + Structural (absence of DSA measurements); 4) iBox functional + Immunological (absence of histology); 5) iBox in response to treatment in T-cell mediated rejection (TCMR); 6) iBox for in response to treatment antibody mediated rejection (ABMR) clinical trials. The performances of the iBox system were assessed with the discrimination (C-index) and calibration. Results The derivation cohort included 4,000 recipients from France, and the international external validation cohort included 6,851 recipients from Europe (France, Belgium, Spain, Germany, Finland n = 4,643), the United States (n = 1,537) and South America (Brazil, Argentina n = 671). The mean recipient age was 50.26 years (14.05) with a median follow-up after evaluations of 5.41 years [IQR: 3.26 to 7]. 1336 patients (12.31%) lost their graft during the study follow-up. The performances of the iBox were confirmed in the different real-life setting with the following C-Index: 1) iBox + different eGFR formulas (MDRD186, MDRD175, CKD-Epi) 0.81; 2) iBox + urinary dipstick 0.80; 3) iBox Functional + Structural (histology) 0.80 (derivation) and 0.84 (validation); 4) iBox functional + Immunological 0.80 (derivation) and 0.83 (validation); 5) iBox in response to treatment in T-cell mediated rejection 0.81; 6) iBox for in response to treatment antibody mediated rejection trials 0.81. The score showed an accurate calibration in every scenario. Conclusion The iBoxEXTENDED trial confirms in various medico-economic settings the performances transportability and surrogacy of the iBox system, further reinforcing its use as a surrogate end point for clinical trials including TCMR and ABMR.

The snATAC + snRNA platform allows epigenomic profiling of open chromatin and gene expression with single-cell resolution. The most critical assay step is to isolate high-quality nuclei to proceed with droplet-base single nuclei isolation and barcoding. With the increasing popularity of multiomic profiling in various fields, there is a need for optimized and reliable nuclei isolation methods, mainly for human tissue samples. Herein we compared different nuclei isolation methods for cell suspensions, such as peripheral blood mononuclear cells (PBMC, n = 18) and a solid tumor type, ovarian cancer (OC, n = 18), derived from debulking surgery. Nuclei morphology and sequencing output parameters were used to evaluate the quality of preparation. Our results show that NP-40 detergent-based nuclei isolation yields better sequencing results than collagenase tissue dissociation for OC, significantly impacting cell type identification and analysis. Given the utility of applying such techniques to frozen samples, we also tested frozen preparation and digestion (n = 6). A paired comparison between frozen and fresh samples validated the quality of both specimens. Finally, we demonstrate the reproducibility of scRNA and snATAC + snRNA platform, by comparing the gene expression profiling of PBMC. Our results highlight how the choice of nuclei isolation methods is critical for obtaining quality data in multiomic assays. It also shows that the measurement of expression between scRNA and snRNA is comparable and effective for cell type identification.

e17535 Background: High-grade serous ovarian carcinoma (HGSOC) is the most frequent and deadliest type of ovarian cancer (OC). With the recent advances in transcriptomic and epigenomic profiling of cancer at single cell resolution, it has become clear that intra-tumor heterogeneity driven by genetic and epigenetic factors may be the basis of drug resistance. Current treatments are not homogeneously effective against all the cancer cell subpopulations, thus enabling resistance. With single cell sequencing technology, characterization of cell signatures and regulatory mechanisms may translate to prognostic markers and novel drug targets. Methods: The transcriptomic and epigenomic landscape of HGSOC was mapped for five tumor samples from debulking surgeries and one tissue patient-derived xenograft (PDX) using the 10X genomics sequencing platform. This strategy permits the combination of single cell ATAC-seq and single cell RNA-seq within the same nucleus (Multiome). Isolation of nuclei, library preparation and sequencing were performed following 10X genomics protocols. Sample quality and library quality were assessed by nuclear morphology and fragment size analysis, respectively. Sequenced reads were mapped to the human genome and downstream analysis including copy number variant prediction, pathway enrichment, motif enrichment and gene regulatory network analysis were performed. The sampled patients continue to be followed for clinical outcomes, such as response to therapy. Clinical data including patient age, grade, and stage of cancer, debulking status, CA-125 levels, and neoadjuvant status, were used in conjunction with the genomics data to characterize patient specific molecular regulatory signatures. Results: Cells from the six samples (total N= 26,421) were projected via UMAP. Immune and stromal cells were shown to cluster by cell-type while cancer cells clustered by patient. Cancer cells were identified as cycling cells, ciliated cells, cells with enrichment of the JAK-STAT signaling pathway, and cells exhibiting cancer stemness signatures. Transcription factor motifs and binding-site enrichment in open chromatin regions reveal transcription regulation-based subpopulations. Using the combined gene expression and open chromatin information from these cells, there is potential to uncover the genetic regulatory network(s) that drives treatment resistance. Conclusions: With single cell technology, specific clusters of cancer and tumor microenvironment cells can be classified. Beyond characterizing patient specific signatures, multiome enables the discovery of genomic, transcriptomic and epigenomic signatures that provide insight in tumor progression and treatment resistance.

5512 Background: The multicenter, open-label, randomized phase 2 NCI-9944 study (NCT02595892) demonstrated that addition of ATR inhibitor (ATRi) berzosertib to gemcitabine increased progression-free survival (PFS) compared to gemcitabine alone (HR = 0.57, one-sided log-rank p = 0.044, which met the one-sided significance level of 0.1 used for sample size calculation). Final overall survival (OS) and corresponding biomarker analyses are reported here. Methods: Patients (pts) with platinum-resistant high-grade serous ovarian cancer and unlimited previous lines of cytotoxic therapy in the platinum-sensitive setting but no more than one line of cytotoxic therapy in the platinum-resistant setting, were randomized 1:1 to gemcitabine/berzosertib versus gemcitabine alone. Randomization was stratified based on platinum free interval (PFI), PFI≤3 months versus > 3 months. Crossover from gemcitabine to gemcitabine/berzosertib was allowed upon disease progression by RECIST 1.1. OS was a secondary endpoint while preplanned exploratory correlative studies included assessment of DNA repair pathways and replication stress (RS) alterations by targeted gene sequencing and/or immunohistochemistry (IHC). Results: Seventy pts were randomly assigned to treatment with gemcitabine/berzosertib (34 pts) or gemcitabine alone (36 pts); 15 pts crossed over from gemcitabine to gemcitabine/berzosertib. At the final OS analysis (92.9% maturity), median follow-up was 53.2 weeks in the gemcitabine/berzosertib and 43 weeks in the gemcitabine alone groups. Median OS in the intent-to-treat (ITT) population was 59.4 weeks in the gemcitabine/berzosertib group versus 43.0 weeks in the gemcitabine alone group (HR 0.79, 90% CI 0.52-1.2, one-sided p = 0.18). However, when patients who crossed over to gemcitabine/berzosertib were excluded from analysis, a significant OS benefit was observed with gemcitabine/berzosertib (HR 0.60, 90%CI 0.37−0.97); HR was 0.26 (90% CI 0.1−0.7) in pts with PFI≤3 months and 0.89 (90%CI 0.50−1.59) in pts with PFI > 3 months. Furthermore, significant OS benefit was observed in pts with RS-low tumors (HR 0.39, 90%CI 0.17−0.91, defined as tumors harboring no genomic RS alterations related to loss of RB pathway regulation and/or oncogene-induced RS) but not in pts with RS-high tumors (HR 0.74, 90%CI 0.35−1.56). Additional targeted gene sequencing and IHC analyses as well as analyses adjusting for patient crossover will be reported at the meeting. Conclusions: In the ITT population, gemcitabine/berzosertib did not significantly improve OS versus gemcitabine alone. Pts with PFI≤3 months and pts with RS-low tumors may derive a survival advantage from addition of berzosertib to gemcitabine in the platinum-resistant setting. Clinical trial information: NCT02595892 .

Abstract Objective To compare the performance of a newly developed race-free kidney recipient specific glomerular filtration rate (GFR) equation with the three current main equations for measuring GFR in kidney transplant recipients. Design Development and validation study Setting 17 cohorts in Europe, the United States, and Australia (14 transplant centres, three clinical trials). Participants 15 489 adults (3622 in development cohort (Necker, Saint Louis, and Toulouse hospitals, France), 11 867 in multiple external validation cohorts) who received kidney transplants between 1 January 2000 and 1 January 2021. Main outcome measure The main outcome measure was GFR, measured according to local practice. Performance of the GFR equations was assessed using P 30 (proportion of estimated GFR (eGFR) within 30% of measured GFR (mGFR)) and correct classification (agreement between eGFR and mGFR according to GFR stages). The race-free equation, based on creatinine level, age, and sex, was developed using additive and multiplicative linear regressions, and its performance was compared with the three current main GFR equations: Modification of Diet in Renal Disease (MDRD) equation, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation, and race-free CKD-EPI 2021 equation. Results The study included 15 489 participants, with 50 464 mGFR and eGFR values. The mean GFR was 53.18 mL/min/1.73m 2 (SD 17.23) in the development cohort and 55.90 mL/min/1.73m 2 (19.69) in the external validation cohorts. Among the current GFR equations, the race-free CKD-EPI 2021 equation showed the lowest performance compared with the MDRD and CKD-EPI 2009 equations. When race was included in the kidney recipient specific GFR equation, performance did not increase. The race-free kidney recipient specific GFR equation showed significantly improved performance compared with the race-free CKD-EPI 2021 equation and performed well in the external validation cohorts (P 30 ranging from 73.0% to 91.3%). The race-free kidney recipient specific GFR equation performed well in several subpopulations of kidney transplant recipients stratified by race (P 30 73.0-91.3%), sex (72.7-91.4%), age (70.3-92.0%), body mass index (64.5-100%), donor type (58.5-92.9%), donor age (68.3-94.3%), treatment (78.5-85.2%), creatinine level (72.8-91.3%), GFR measurement method (73.0-91.3%), and timing of GFR measurement post-transplant (72.9-95.5%). An online application was developed that estimates GFR based on recipient’s creatinine level, age, and sex ( https://transplant-prediction-system.shinyapps.io/eGFR_equation_KTX/ ). Conclusion A new race-free kidney recipient specific GFR equation was developed and validated using multiple, large, international cohorts of kidney transplant recipients. The equation showed high accuracy and outperformed the race-free CKD-EPI 2021 equation that was developed in individuals with native kidneys. Trial registration ClinicalTrials.gov NCT05229939 .

Abstract Purpose: Preclinical studies in myeloid neoplasms have demonstrated efficacy of bromodomain and extra-terminal protein inhibitors (BETi). However, BETi demonstrates poor single-agent activity in clinical trials. Several studies suggest that combination with other anticancer inhibitors may enhance the efficacy of BETi. Experimental Design: To nominate BETi combination therapies for myeloid neoplasms, we used a chemical screen with therapies currently in clinical cancer development and validated this screen using a panel of myeloid cell line, heterotopic cell line models, and patient-derived xenograft models of disease. We used standard protein and RNA assays to determine the mechanism responsible for synergy in our disease models. Results: We identified PIM inhibitors (PIMi) as therapeutically synergistic with BETi in myeloid leukemia models. Mechanistically, we show that PIM kinase is increased after BETi treatment, and that PIM kinase upregulation is sufficient to induce persistence to BETi and sensitize cells to PIMi. Furthermore, we demonstrate that miR-33a downregulation is the underlying mechanism driving PIM1 upregulation. We also show that GM-CSF hypersensitivity, a hallmark of chronic myelomonocytic leukemia (CMML), represents a molecular signature for sensitivity to combination therapy. Conclusions: Inhibition of PIM kinases is a potential novel strategy for overcoming BETi persistence in myeloid neoplasms. Our data support further clinical investigation of this combination.

OBJECTIVES: To review a contemporary approach to the management of patients with cardiogenic shock (CS). DATA SOURCES: We reviewed salient medical literature regarding CS. STUDY SELECTION: We included professional society scientific statements and clinical studies examining outcomes in patients with CS, with a focus on randomized clinical trials. DATA EXTRACTION: We extracted salient study results and scientific statement recommendations regarding the management of CS. DATA SYNTHESIS: Professional society recommendations were integrated with evaluated studies. CONCLUSIONS: CS results in short-term mortality exceeding 30% despite standard therapy. While acute myocardial infarction (AMI) has been the focus of most CS research, heart failure-related CS now predominates at many centers. CS can present with a wide spectrum of shock severity, including patients who are normotensive despite ongoing hypoperfusion. The Society for Cardiovascular Angiography and Intervention Shock Classification categorizes patients with or at risk of CS according to shock severity, which predicts mortality. The CS population includes a heterogeneous mix of phenotypes defined by ventricular function, hemodynamic profile, biomarkers, and other clinical variables. Integrating the shock severity and CS phenotype with nonmodifiable risk factors for mortality can guide clinical decision-making and prognostication. Identifying and treating the cause of CS is crucial for success, including early culprit vessel revascularization for AMI. Vasopressors and inotropes titrated to restore arterial pressure and perfusion are the cornerstone of initial medical therapy for CS. Temporary mechanical circulatory support (MCS) is indicated for appropriately selected patients as a bridge to recovery, decision, durable MCS, or heart transplant. Randomized controlled trials have not demonstrated better survival with the routine use of temporary MCS in patients with CS. Accordingly, a multidisciplinary team-based approach should be used to tailor the type of hemodynamic support to each individual CS patient’s needs based on shock severity, phenotype, and exit strategy.

The global burden of paediatric and congenital heart disease (PCHD) is substantial. We propose a novel public health framework with recommendations for developing effective and safe PCHD services in low-income and middle-income countries (LMICs). This framework was created by the Global Initiative for Children’s Surgery Cardiac Surgery working group in collaboration with a group of international rexperts in providing paediatric and congenital cardiac care to patients with CHD and rheumatic heart disease (RHD) in LMICs. Effective and safe PCHD care is inaccessible to many, and there is no consensus on the best approaches to provide meaningful access in resource-limited settings, where it is often needed the most. Considering the high inequity in access to care for CHD and RHD, we aimed to create an actionable framework for health practitioners, policy makers and patients that supports treatment and prevention. It was formulated based on rigorous evaluation of available guidelines and standards of care and builds on a consensus process about the competencies needed at each step of the care continuum. We recommend a tier-based framework for PCHD care integrated within existing health systems. Each level of care is expected to meet minimum benchmarks and ensure high-quality and family centred care. We propose that cardiac surgery capabilities should only be developed at the more advanced levels on hospitals that have an established foundation of cardiology and cardiac surgery services, including screening, diagnostics, inpatient and outpatient care, postoperative care and cardiac catheterisation. This approach requires a quality control system and close collaboration between the different levels of care to facilitate the journey and care of every child with heart disease. This effort was designed to guide readers and leaders in taking action, strengthening capacity, evaluating impact, advancing policy and engaging in partnerships to guide facilities providing PCHD care in LMICs.