Unsupervised Hierarchical Clustering Analysis Research Articles

#2490 Analyzing the morphology of mesothelial cells when exposed to peritoneal dialysis solutions

Abstract Background and Aims Glucose remains the predominant osmotic agent in peritoneal dialysis (PD), yet its prolonged use is associated with an inevitable decline in peritoneal filtration capacity. Persistent contact with glucose during dialysis can induce significant morphological and functional changes in the peritoneum. In this study, we explore the morphological alterations in mesothelial cells exposed to both conventional glucose-based PD solutions and an innovative biocompatible PD solution (XyloCore) containing L-carnitine and Xylitol. Method Met5A mesothelial cells were seeded and cultured on a polyester filter (with a pore size of 0.4 micrometers, Transwell, 12 well type, Millipore) utilizing a full medium. The impact of PD solutions, differentiating between glucose-based and XyloCore, was assessed on cells cultivated on transwells. These cells were exposed to PD solutions on the apical side and to culture medium on the basal side. The cells were then employed for proteomic and metabolomic assessments and were also fixed and scrutinized through scanning electron microscopy (SEM). Results Through unsupervised hierarchical clustering analysis, discernable proteomic distinctions emerged between wild-type (WT) cells (control) and cells exposed to either glucose-based PD solution or XyloCore. In SEM analysis, control cells exhibited a distinct flat epithelial appearance. Contrastingly, subjecting WT cells to treatment with a glucose-based PD solution induced significant alterations in cellular morphology. Notably, cells displayed elongated shapes, loosening of cell-cell contacts, and a consistent denuding of the culture surface. In contrast, XyloCore maintained a better cellular morphology and mitigated cell detachment. Conclusion Preserving the integrity of the mesothelial barrier is crucial for maintaining peritoneal ultrafiltration capacity. The findings suggest that glucose-based PD solutions trigger early morphological changes in cell shape and cell-cell contacts, likely stemming from alterations in cytoskeleton or adhesion molecules. The exploration of new osmotic agents in clinical practice holds paramount significance for the future of peritoneal dialysis.

Comprehensive analysis of macrophage-related genes in prostate cancer by integrated analysis of single-cell and bulk RNA sequencing.

Macrophages, as essential components of the tumor immune microenvironment (TIME), could promote growth and invasion in many cancers. However, the role of macrophages in tumor microenvironment (TME) and immunotherapy in PCa is largely unexplored at present. Here, we investigated the roles of macrophage-related genes in molecular stratification, prognosis, TME, and immunotherapeutic response in PCa. Public databases provided single-cell RNA sequencing (scRNA-seq) and bulk RNAseq data. Using the Seurat R package, scRNA-seq data was processed and macrophage clusters were identified automatically and manually. Using the CellChat R package, intercellular communication analysis revealed that tumor-associated macrophages (TAMs) interact with other cells in the PCa TME primarily through MIF - (CD74+CXCR4) and MIF - (CD74+CD44) ligand-receptor pairs. We constructed coexpression networks of macrophages using the WGCNA to identify macrophage-related genes. Using the R package ConsensusClusterPlus, unsupervised hierarchical clustering analysis identified two distinct macrophage-associated subtypes, which have significantly different pathway activation status, TIME, and immunotherapeutic efficacy. Next, an 8-gene macrophage-related risk signature (MRS) was established through the LASSO Cox regression analysis with 10-fold cross-validation, and the performance of the MRS was validated in eight external PCa cohorts. The high-risk group had more active immune-related functions, more infiltrating immune cells, higher HLA and immune checkpoint gene expression, higher immune scores, and lower TIDE scores. Finally, the NCF4 gene has been identified as the hub gene in MRS using the "mgeneSim" function.

Abstract 4001: Monocyte transcriptome profiles associated with clinical response in patients with B-cell non-Hodgkin’s lymphoma receiving CD19-directed CAR-T therapy

Abstract Background Although CAR T-cell therapy has achieved remarkable response in patients (pts) with B-cell non-Hodgkin’s lymphoma (NHL), 20-30% of pts still have primary refractory disease (PD1), and another 30-40% relapse (PD2). We and others have shown that monocytes can modulate T-cell functions and impact clinical response to chemoimmunotherapy in NHL. Given that monocytes nadir and recovery kinetics differ from lymphocytes post lymphodepletion chemotherapy, we hypothesize that monocyte phenotype at peak CAR-T expansion and in the early month post CAR-T can modulate immune responses. Methods scRNAseq were performed on peripheral blood mononuclear cells of NHL pts prior to lymphodepletion chemotherapy (pre), at peak CAR-T expansion (peak), and one month following CAR-T (M1). Seurat v4.3.0 was used for unsupervised hierarchical clustering analysis. Lugano criteria was used to determine clinical responses which were categorized as CR (complete remission), PD1, or PD2. Results We analyzed 129,981 monocytes from 77 samples of 32 pts (16 CR, 4 PD1, 12 PD2) and 5 healthy controls. Unsupervised hierarchical clustering analysis identified 13 monocyte clusters: 4 classical monocyte (CM) clusters with transcriptome profiles for enriched signaling in IL-6, TGFβ, EMT, and p53; 2 intermediate monocyte (IM) clusters enriched for IL-1 or CD38 signaling; 2 non-classical monocytes (NM), one with increased CD36 expression; 3 monocytic MDSC clusters with enrichment of TGFβ, SIRPα, and HIF1α signaling; and 2 lymphoma-associated monocytes, expressing CD163 or CD169. At Pre and Peak, the distribution of the monocyte clusters was similar in pts with CR, PD2, or PD1, with only a slight decrease in the percent of NM in the PD2 group at Pre and slight increase of CD36 NM in PD1 at Peak. Compared to Pre, all pts had increased percent of CD36 NM and IL-1 IM at Peak. Interestingly, while the distribution of monocyte clusters was similar at Pre and Peak across clinical responses, GSEA showed that monocytes in CR pts, compared to PD1 and PD2, had gene expression enrichment of MYC target V2 pathway at Pre and TGFβ pathway at Peak. At M1, pts in PD1 had increased percent of p53 and TGFβ CM and decreased percent of NM. In contrast, pts with CR had decreased percent of IL-6 CM, p53 CM, TGFβ CM, IL-1 IM and increased percent of NM. Notably, as pts with CR and PD2 may appear similar clinically at M1, pts with PD2, compared to CR, have increased IL-6 CM, IL-1 IM, and decreased NM. In addition, GSEA showed that PD2 pts had increased IFNα response. Our results demonstrate that monocyte phenotype differences at Pre and Peak could be associated with CAR-T clinical response, and that persistent inflammatory monocyte signaling at M1 in pts with clinical response is associated with relapse. These data suggest a role for development of monocyte biomarkers to predict response and therapeutic targeting. Citation Format: Andre de Menezes Silva Corraes, Panwen Wang, Radhika Bansal, Henan Zhang, Zuoyi Shao, Kevin Regan, Eider Moreno Cortes, Arushi Khurana, Nora Bennani, Yucai Wang, Paul Hampel, Jonas Paludo, Patrick Johnston, Hemant Murthy, Madiha Iqbal, Stephen Ansell, Javier Munoz, Allison Rosenthal, Mohamed Kharfan-Dabaja, Januario Castro, Saad Kenderian, Haidong Dong, Ying Li, Yi Lin. Monocyte transcriptome profiles associated with clinical response in patients with B-cell non-Hodgkin’s lymphoma receiving CD19-directed CAR-T therapy [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 4001.

Abstract 3766: Utilizing whole-transcriptome digital spatial profiling for glioblastoma clinical biomarker discovery

Abstract Objective: IDH-wildtype glioblastoma (GBM) is the most aggressive brain tumor in adults. Notable for substantial inter- and intra-tumoral heterogeneity, GBM is highly resistant to standard-of-care treatment. Emerging spatial omics technologies, such as GeoMx Digital Spatial Profiling (DSP), offer novel approaches to interrogate the molecular features of regionally defined cellular ecosystems in cancer. Here, we leverage DSP to study whole-transcriptome gene expression signatures in a spatially defined manner across five IDH-wildtype GBMs. Methods: Formalin-fixed paraffin-embedded tumors were assessed histologically and three spatially distinct areas from each tumor were used to construct a custom “spatial” tissue microarray. From each set of three areas, we identified nine spatially distinct regions of interest (ROIs) for bulk transcriptomic analysis according to two histopathological features: distribution (cellular tumor core or tumor periphery) and vascular proximity (near or far). We evaluated normalized target expression data statistically using linear mixed modeling (LMM) with Benjamini-Hochberg correction. Results: 44 profiled ROIs and 8531 transcriptomic targets were analyzed following quality control trimming. 3D principal component analysis and unsupervised hierarchical clustering analysis showed clustering according to tumor specimen as well as distribution (core versus periphery), thereby substantiating the presence of inter- and intra-tumoral transcriptional heterogeneity. LMM-based differential gene expression analysis identified distinct molecular signatures when comparing core and periphery. Specifically, we observed elevated log2-transformed expression of migration and proliferation markers including LAMC1 (p=0.00297) and FABP7 (p=0.00434) in core ROIs and neurodevelopmental markers including NTRK2 (p=0.00734) and DAAM2 (p=0.00263) in periphery ROIs. Additionally, reactome analysis demonstrated considerable enrichment for the aberrant programmed cell death pathway (R-HSA-9645723, coverage=71.84%) in core ROIs and the MHC class II antigen presentation pathway (R-HSA-2132295, coverage=69.11%) in periphery ROIs. Interestingly, differential gene expression analysis did not reveal any biologically significant targets when subsetting for vascular proximity within cellular tumor core ROIs. However, reactome analysis of this regional subset demonstrated upregulation of various cellular proliferation pathways (G2/M transition, APC/C activity, DNA synthesis, etc.) within vessel-near ROIs when compared with vessel-far ROIs. Conclusions: We preliminarily characterize the molecular heterogeneity of GBM using a spatially guided approach. Ongoing analyses are focused on dataset validation, mixed cell deconvolution, further regional genotyping, and potential biomarkers. Citation Format: Adam Luo, Kelly Casella, Shivang Sharma, Ezra Baraban, Calixto-Hope Lucas, Eugene Shenderov. Utilizing whole-transcriptome digital spatial profiling for glioblastoma clinical biomarker discovery [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 3766.

Immune profiles of pre-frail people living with HIV-1: a prospective longitudinal study

BackgroundPeople living with HIV (PLWH) are at risk of frailty, which is predictive for death. As an overactivity of the immune system is thought to fuel frailty, we characterized the immune activation profiles linked to frailty.MethodsWe quantified twenty-seven activation markers in forty-six virological responders (four females and forty-two males; median age, 74 years; median duration of infection, 24 years; median duration of undetectability, 13 years), whose frailty was determined according to the Fried criteria. T cell and NK cell activation was evaluated by flow cytometry, using a panel of cell surface markers. Soluble markers of inflammation, and monocyte activation and endothelial activation were measured by ELISA. The participants’ immune activation was profiled by an unsupervised double hierarchical clustering analysis. We used ANOVA p-values to rank immunomarkers most related to Fried score. A Linear Discriminant Analysis (LDA) was performed to link immune activation markers to frailty.Results41% of the participants were pre-frail, including 24% with a Fried score of 1, and 17% with a Fried score of 2. ANOVA identified the 14 markers of T cell, monocyte, NK cell, endothelial activation, and inflammation the most linked to Fried 3 classes. The LDA performed with these 14 markers was capable of discriminating volunteers according to their Fried score. Two out of the 5 immune activation profiles revealed by the hierarchical clustering were linked to and predictive of pre-frailty. These two profiles were characterized by a low percentage of CD4 T cells and a high percentage of CD8 T cells, activated CD4 T cells, CD8 T cells, and NK cells, and inflammation.ConclusionsWe identified a particular immune activation profile associated with pre-frailty in PLWH. Profiling participants at risk of developing frailty might help to tailor the screening and prevention of medical complications fueled by loss of robustness. Further studies will indicate whether this frailty signature is specific or not of HIV infection, and whether it also precedes frailty in the general population.

Exploring congestion endotypes and their distinct clinical outcomes among ICU patients: A post-hoc analysis

BackgroundIn the intensive care unit (ICU) patients, fluid overload and congestion are associated with worse outcomes. Because of the heterogeneity of ICU patients, we hypothesized that there may exist different endotypes of congestion. The aim of this study was to identify endotypes of congestion and their association with outcomes. MethodsWe conducted an unsupervised hierarchical clustering analysis on 145 patients admitted to ICU to identify endotypes. We measured several parameters related to clinical context, volume status, filling pressure, and venous congestion. These parameters included NT-proBNP, central venous pressure (CVP), the mitral E/e' ratio, the systolic/diastolic ratio of hepatic veins' flow velocity, the mean diameter of the inferior vena cava (IVC) and its variations, stroke volume changes following passive leg raising, the portal vein pulsatility index, and the venous renal impedance index. ResultsThree distinct endotypes were identified: (1) “hemodynamic congestion” endotype (n = 75) with moderate alterations of ventricular function, increased CVP and left filling pressure values, and moderate fluid overload; (2) “volume overload congestion” endotype (n = 50); with normal cardiac function and filling pressure despite high positive fluid balance (fluid overload); (3) “systemic congestion” endotype (n = 20) with severe alterations of left and right ventricular functions, increased CVP and left ventricular filling pressure values. These endotypes vary significantly in ICU admission reasons, acute kidney injury rates, mortality, and length of ICU/hospital stay. ConclusionsOur analysis revealed three unique congestion endotypes in ICU patients, each with distinct pathophysiological features and outcomes. These endotypes are identifiable through key ultrasonographic characteristics at the bedside. Clinical trial govNCT04680728.

Identification of immune characteristic biomarkers and therapeutic targets in cuproptosis for sepsis by integrated bioinformatics analysis and single-cell RNA sequencing analysis

BackgroundCuproptosis is a copper-dependent cell death that is connected to the development and immune response of multiple diseases. However, the function of cuproptosis in the immune characteristics of sepsis remains unclear. MethodWe obtained two sepsis datasets (GSE9960 and GSE134347) from the GEO database and classified the raw data with R packages. Cuproptosis-related genes were manually curated, and differentially expressed cuproptosis-related genes (DECuGs) were identified. Afterwards, we applied enrichment analysis and identified key DECuGs by performing machine learning techniques. Then, the immune cell infiltrations and correlation between DECuGs and immunocyte features were created by the CIBERSORT algorithm. Subsequently, unsupervised hierarchical clustering analysis was performed based on key DECuGs. We then constructed a ceRNA network based on key DECuGs by using multi-step computational strategies and predicted potential drugs in the DrugBank database. Finally, the role of these key genes in immune cells was validated at the single-cell RNA level between septic patients and healthy controls. ResultsOverall, 16 DECuGs were obtained, and most of them had lower expression levels in sepsis samples. Afterwards, we obtained six key DECuGs by performing machine learning. Then, the LIPT1-T-cell CD4 memory resting was the most positively correlated DECuG–immunocyte pair. Subsequently, two different subclusters were identified by six DECuGs. Bioinformatics analysis revealed that there were different immune characteristics between the two subclusters. Moreover, we identified the key lncRNA OIP5-AS1 within the ceRNA network and obtained 4 drugs that may represent novel drugs for sepsis. Finally, these key DECuGs were statistically significantly dysregulated in another validation set and showed a major distribution in monocytes, T cells, B cells, NK cells and platelets at the single-cell RNA level. ConclusionThese findings suggest that cuproptosis might promote the progression of sepsis by affecting the immune system and metabolic dysfunction, which provides a new direction for understanding potential pathogenic processes and therapeutic targets in sepsis.

Burden of cardiometabolic risk factors and vascular health

Cardiometabolic risk factors diabetes, obesity, and hypertension are highly prevalent and contribute to increased cardiovascular disease (CVD). Endothelial dysfunction precedes CVD development. The current study aimed to investigate the EC transcriptome among individuals with varying degree of cardiometabolic risk. Adult participants without CVD and various degrees of cardiometabolic risk factor burden (hypertension, diabetes, obesity) were included. Participants underwent brachial vein EC harvesting followed by RNA sequencing. To evaluate the association between cardiometabolic comorbidity burden and outcome transcripts we performed linear regression with multivariable models, adjusting for age, sex, and race/ethnicity. A total of 18 individuals were included in the present analysis (mean age 47 ± 14, 44% female, and 61% White adults). Endothelial cell RNA sequencing revealed 588 differentially expressed transcripts (p-adj <0.05) with excellent discrimination in unsupervised hierarchical clustering analysis. Gene ontology enrichment analysis revealed upregulated pathways associated with T-cell activation (NES = 2.22, p<0.001), leukocyte differentiation (NES= 2.16, p<0.001), leukocyte migration (NES= 2.12, p<0.001), regulation of cell-cell adhesion (NES= 1.91, p=0.006). Downregulated pathways of interest included endothelial cell proliferation (NES= -1.68, p=0.03) and response to interleukin-1 (NES= -1.61, p=0.04). Upregulated genes included VCAM1, CEACAM1, ADAM 17, and CD99L2, all with a log-2-fold change >3 and p-adj <0.05. These genes demonstrated a graded increase in mean normalized counts with increasing number of risk factors. We demonstrate a proinflammatory and pro-adhesive EC transcriptome associated with increased cardiometabolic risk factor burden offering insight into a potential mechanism linking these risk factors with the development of CVD.

Gene expression alterations predict the pathological complete response in triple-negative breast cancer exploratory analysis of the NACATRINE trial

This exploratory analysis of the Neoadjuvant Carboplatin in Triple Negative Breast Cancer (NACATRINE) study aimed to identify the biomarkers of pathological complete response (pCR) in patients with triple-negative breast cancer (TNBC) treated with neoadjuvant chemotherapy (NAC) within the context of a clinical trial. The NACATRINE trial is a phase II, single-center, randomized, open-label clinical trial that investigated the addition of carboplatin to sequential anthracycline- and taxane-based NAC for TNBC. We evaluated the gene expression in untreated samples to investigate its association with pCR, overall survival (OS), and disease-free survival (DFS). RNA was extracted from the tissue biopsy, and the nCounter Breast Cancer panel was used to analyze gene expression. Of the 66 patients included in the gene expression profiling analysis, 24 (36.4%) achieved pCR and 42 (63.6%) had residual disease. In unsupervised hierarchical clustering analyses, differentially expressed genes between patients with and without pCR were identified irrespective of the treatment (24 genes), carboplatin (37 genes), and non-carboplatin (27 genes) arms. In receiver operating characteristic (ROC) curve analysis, 10 genes in the carboplatin arm (area under the ROC curve [AUC], 0.936) and three genes in the non-carboplatin arm (AUC, 0.939) were considered to be potential pCR-associated biomarkers. We identified genes that were associated with improvements in OS and DFS in addition to being related to pCR. We successfully identified gene expression signatures associated with pCR in pretreatment samples of patients with TNBC treated with NAC. Further investigation of these biomarkers is warranted.

Radiographic characteristics-based classification system for percutaneous endoscopic lumbar discectomy surgical approach selection in patients with L5-S1 disc herniation: a hierarchical clustering analysis.

No classification system exists for aiding the selection of surgical approaches in L5-S1 disc herniation when undergoing percutaneous endoscopic lumbar discectomy (PELD). We aimed to identify radiographic subtypes to aid the selection of percutaneous endoscopic transforaminal discectomy (PETD) and percutaneous endoscopic interlaminar discectomy (PEID) in patients with L5-S1 disc herniation via unsupervised hierarchical clustering analysis. In this retrospective case-control study, we gathered 296 anteroposterior and lateral lumbar spine radiographs (dataset 1) from Tianjin Hospital between January 2016 and October 2021 for clustering analyses. Additionally, we analyzed 111 patients who underwent PEID or PETD for L5-S1 disc herniation at Tianjin Hospital from January 2016 to August 2022. We included patients with radicular leg pain or back pain associated with intra-canal disc herniation who failed in conservative treatments over 6 weeks. First, pair-wise Spearman correlation coefficients were calculated among plain radiographic metrics in dataset 1 to reveal the association among these radiographic metrics. Second, hierarchical clustering analysis was conducted to unsupervised cluster the plain films into several subtypes. Last, for each radiographic subtype, the intraoperative blood loss (IBL), operation time (OT), total operating room time (TORT) along with visual analogue scale (VAS) and Oswestry Disability Index (ODI) were compared between patients underwent PETD or PEID with age as covariates. This study yielded 3 main findings: (I) iliac height (IH) was negatively correlated with intervertebral foramen width (IFW), intervertebral foramen height (IFH), and intertransverse height (ITH) (R=-0.50, -0.42, and -0.46, all P<0.001), ITH was positively correlated with IFW and IFH (R=0.40 and 0.53, all P<0.001); (II) 2 lumbosacral radiographic subtypes were identified via hierarchical clustering analysis; (III) relative to subtype 1, the patients identified as subtype 2 exhibited lesser IBL, shorter OT, and shorter TORT following PETD (t=2.92, P=0.006; t=2.65, P=0.012; t=3.17, P=0.003). The morphology pattern of the lumbosacral region affect the ease of different PELD procedures when performing percutaneous discectomy at the segment of L5-S1. Without considering the type of disc herniation, this classification system might aid spine surgeons in the selection of an appropriate surgical approach.

Imipramine Treatment Alters Sphingomyelin, Cholesterol, and Glycerophospholipid Metabolism in Isolated Macrophage Lysosomes.

Lysosomes are degradative organelles that facilitate the removal and recycling of potentially cytotoxic materials and mediate a variety of other cellular processes, such as nutrient sensing, intracellular signaling, and lipid metabolism. Due to these central roles, lysosome dysfunction can lead to deleterious outcomes, including the accumulation of cytotoxic material, inflammation, and cell death. We previously reported that cationic amphiphilic drugs, such as imipramine, alter pH and lipid metabolism within macrophage lysosomes. Therefore, the ability for imipramine to induce changes to the lipid content of isolated macrophage lysosomes was investigated, focusing on sphingomyelin, cholesterol, and glycerophospholipid metabolism as these lipid classes have important roles in inflammation and disease. The lysosomes were isolated from control and imipramine-treated macrophages using density gradient ultracentrifugation, and mass spectrometry was used to measure the changes in their lipid composition. An unsupervised hierarchical cluster analysis revealed a clear differentiation between the imipramine-treated and control lysosomes. There was a significant overall increase in the abundance of specific lipids mostly composed of cholesterol esters, sphingomyelins, and phosphatidylcholines, while lysophosphatidylcholines and ceramides were overall decreased. These results support the conclusion that imipramine's ability to change the lysosomal pH inhibits multiple pH-sensitive enzymes in macrophage lysosomes.

Self-Supporting Human Acute Myeloid Leukemia (AML) Bone Marrow Organoids Established from Patient-Derived Xenografts Mimic the Human AML Microenvironment, with Distinct Cytokine Kinetics Correlating with Dynamic Cell Proliferation and Metabolic Shifts

Hallmarks of acute myeloid leukemia (AML) include (1) formation of a self-supporting and self-regulating tumor microenvironment (TME) in the bone marrow (BM) rendering pathological niches that orchestrate retention, proliferation and survival of AML blasts, and (2) a dynamic metabolism that promotes therapy resistance and disease progression. Efforts to understand AML biology and enhance current therapies are hampered by the paucity of state-of-the-art human models that can recreate the three-dimensional (3D) BM TME and recapitulate the heterogeneity, complexity, dynamics, and metabolic shifts observed in human disease. Previously, we described the development of the first long-term self-propagating serum- and cytokine-free human BM organoid generated from an AML patient-derived xenograft (PDX) that captured metabolic shifts during AML progression. Here, we characterize the dynamic changes observed in the self-constituted TME with respect to AML proliferation, metabolism, and upon reconstitution of secondary organoids. BM was collected from NSG mice engrafted with human primary AML cells (PDX-AML model) or naïve control mice and seeded into polyurethane scaffolds in serum- and cytokine-free medium at 4e6 cells per scaffold, optimized previously. Scaffolds were recharged with autologous PDX-AML BM on day (D) 13 and cultured until D70. Organoids were assessed for (1) inter- and intra-scaffold AML kinetics, (2) the TME, (3) metabolic composition and (4) propagation into secondary organoids. AML cell kinetics from organoid culture supernatants reflected those of scaffold-extracted populations (n=3). CD33 +CD44 + AML cells expanded and/or were maintained from 7% (D0) to &amp;gt;10% (D70), being &amp;gt;15% at most culture timepoints. Confocal microscopy revealed reconstitution of typical AML-TME niche interactions within organoids, including expression of fibronectin, VCAM-1 and N-Cadherin, and formation of proliferative niches composed of AML cells with heterogeneous Osteopontin- and Osterix-expressing support cells. Human AML-supportive cytokines were consistently observed in organoid supernatants (N=3), with SDF-1, IL-1α, IL-8, GM-CSF, FGF-2 and Osteopontin present throughout the culture; some cytokines had biphasic kinetics with factors critical for TME formation present early (e.g. Osteopontin, GM-CSF), and those required for AML proliferation dominant later (e.g. FLT3L, IL-8), coinciding also with metabolic shifts during culture. Despite the absence of IL-6, single molecule RNA fluorescence in situ hybridization confirmed IL-6 expression by niche-resident AML blasts suggesting autocrine signaling networks beyond those identified in supernatants. Cells from D70 organoids were able to re-establish secondary organoids (n=2) which also exhibited long-term (D70) AML maintenance (&amp;gt;11% blasts), and regenerated the AML TME. Previously, we identified 3 culture stages defined by metabolic shifts: 1) pre/early recharge (D4-D19), (2) intermediate (D25-D40) and, (3) late (from D55) where organoids exhibited highest proliferation. To further characterize these shifts, intracellular metabolites were extracted from organoids (n=5) at D10, D25, D40, D55 and D70, analyzed with gas-chromatography mass spectrometry (GC-MS) and evaluated through unsupervised hierarchical clustering and multivariate analysis. Significance Analysis of Microarrays (SAM) analysis demonstrated dysregulation of alanine, serine, isoleucine, glycolate, hexanoic acid and glycolysis when comparing stage 1 with stage 2, and in isoleucine, leucine, serine, succinate and tryptophan metabolism when comparing stage 2 with stage 3. When proliferative and non-proliferative timepoints were compared, amino acid and glycolysis-driven metabolic switches were identified, typical of AML metabolism. We have characterized a long-term 3D human AML BM biomimicry in serum- and cytokine-free conditions with a self-organizing TME that recapitulates many features of AML BM, including robust human AML cell maintenance within niches, cytokine and metabolic kinetics to support different phases of progression, and the ability to propagate into secondary organoids. This dynamic, physiologically-relevant ex vivo platform can enable studies in human AML pathogenesis/progression and is poised to test novel therapeutics directed towards AML cells, the TME and metabolic targets.

Identified senescence endotypes in aged cartilage are reflected in the blood metabolome

Heterogeneous accumulation of senescent cells expressing the senescence-associated secretory phenotype (SASP) affects tissue homeostasis which leads to diseases, such as osteoarthritis (OA). In this study, we set out to characterize heterogeneity of cellular senescence within aged articular cartilage and explored the presence of corresponding metabolic profiles in blood that could function as representative biomarkers. Hereto, we set out to perform cluster analyses, using a gene-set of 131 senescence genes (N = 57) in a previously established RNA sequencing dataset of aged articular cartilage and a generated metabolic dataset in overlapping blood samples. Using unsupervised hierarchical clustering and pathway analysis, we identified two robust cellular senescent endotypes. Endotype-1 was enriched for cell proliferating pathways, expressing forkhead box protein O4 (FOXO4), RB transcriptional corepressor like 2 (RBL2), and cyclin-dependent kinase inhibitor 1B (CDKN1B); the FOXO mediated cell cycle was identified as possible target for endotype-1 patients. Endotype-2 showed enriched inflammation-associated pathways, expressed by interleukin 6 (IL6), matrix metallopeptidase (MMP)1/3, and vascular endothelial growth factor (VEGF)C and SASP pathways were identified as possible targets for endotype-2 patients. Notably, plasma-based metabolic profiles in overlapping blood samples (N = 21) showed two corresponding metabolic clusters in blood. These non-invasive metabolic profiles could function as biomarkers for patient-tailored targeting of senescence in OA.

Abstract 13847: Biomarker-Based Phenomapping in Chronic Stable HFpEF and Exercise Capacity: An Analysis of the RELAX Trial

Introduction: Heart failure with preserved ejection fraction (HFpEF) is a heterogenous disease associated with low exercise capacity. Hypothesis: Unsupervised clustering of biomarker data can identify subgroups of individuals with HFpEF and differences in exercise capacity. Methods: The study included participants with chronic, stable HFpEF from the RELAX trial with available serum biomarker data. We used unsupervised hierarchical clustering analysis of 9 serum biomarkers to derive phenogroups of participants with HFpEF. Adjusted linear regression was used to assess the association between cluster membership with peak oxygen consumption (VO2), maximum exercise watts, and VO2 anaerobic threshold. Results: Among 211 participants in the RELAX trial, 3 phenogroups were identified based on the gain in within-inertia. No significant differences were observed in age, sex, or race across phenogroups. Phenogroup 1 (n=136) participants had the lowest burden of CV (cardiovascular) risk factors, including diabetes, anemia, and kidney disease as well as the lowest overall biomarkers levels ( Fig. A ). Phenogroup 2 (n=61) consisted of participants who were older with a higher burden of CV risk factors and fibrosis biomarkers, including galectin-3, collagen-I, and troponin-I levels. Phenogroup 3 (n=14) participants were younger with high burden of CV risk factors and inflammatory biomarkers including aldosterone, CRP, and uric acid. Compared with phenogroup 1, phenogroup 2 and 3 had significantly lower peak VO2, adjusted for traditional CV risk factors [estimate (95% CI): -1.99 (-2.83, -1.16) and -2.31 (-3.66, -0.95), respectively] (Fig. B ). Additionally, phenogroup 3 vs. 1 had lower exercise watts and VO2 anaerobic threshold. Conclusion: Using serum biomarkers, we identified 3 unique phenogroups of patients with chronic, stable HFpEF and significant differences in CV risk factor burden and exercise capacity.

Molecular subtypes, predictive markers and prognosis in small-cell lung carcinoma

AimsA new molecular subtype classification was proposed for small-cell lung carcinoma (SCLC). We aimed to further validate the classification in various SCLC patient samples using immunohistochemistry (IHC) to highlight its...

JS01.3.A EPIGENETICALLY DEFINED ANGIOCENTRIC GLIOMAS MAY LACK ANGIOCENTRIC GROWTH AND INSTEAD SHOW A VARIETY OF GROWTH PATTERNS

Abstract BACKGROUND Angiocentric glioma mainly occurs in children and young adults. It is associated with a good prognosis (CNS WHO grade 1). Molecularly, most angiocentric gliomas have a MYB-QKI fusion. Histologically, angiocentric gliomas were initially defined by angiocentric growth of the tumor cells. However, we noticed that epigenetically defined angiocentric gliomas often get different diagnoses based on their histology as they may lack this angiocentric growth pattern. We therefore wanted to further analyze epigenetically defined angiocentric gliomas and evaluate how reliable these gliomas are histologically diagnosed based on the criteria defined by the WHO. MATERIAL AND METHODS We collected 48 epigenetically defined angiocentric gliomas (37 supratentorial, 11 infratentorial) from 46 patients with sufficient tissue for histological and molecular analyses (DNA methylation analyses; RNA sequencing of a subset). The classification was done using unsupervised hierarchical cluster analyses from DNA methylation data and the brain tumor classifiers v11b4 and v12.5 (www.molecularneuropathology.org). RESULTS Angiocentric gliomas were epigenetically distinct from other gliomas including the diffuse astrocytomas, MYB- or MYBL1-altered. A MYB-QKI fusion was detected in 69% (n = 18/26) of angiocentric gliomas, confirming the diagnosis. Other fusions detected were fusions of MYB with intergenic sites, mainly close to QKI (19%; n = 5/26), and MYBL1-QKI (8%; n = 2/26). Histological workup revealed that 75% of the cases included in this study showed the typical angiocentric growth pattern. However, in many of these tumors this was not very pronounced. Many angiocentric gliomas displayed an unspecific growth pattern or resembled pilocytic astrocytoma or ependymoma. Hence, about 59% of angiocentric gliomas were initially misdiagnosed without molecular analyses (supratentorial 50%, infratentorial 100%). We obtained similar results expanding the cohort with further epigenetically defined angiocentric gliomas for which no tissue for a histological re-evaluation was available (total 68 cases; 50 supratentorial, 12 infratentorial; 65 patients). In this expanded cohort, 54% of cases were initially misdiagnosed (45% of supratentorial and 100% of infratentorial cases). CONCLUSION In summary, we show that angiocentric glioma often does not show the typical angiocentric growth pattern, resulting in different diagnoses in more than 50% of the cases without molecular analyses. Thus, DNA methylation analyses are needed for a reliable diagnosis of this tumor type.

Identification of cholesterol metabolism-related subtypes in nonfunctioning pituitary neuroendocrine tumors and analysis of immune infiltration

ObjectiveThis study aimed to investigate the role of cholesterol metabolism-related genes in nonfunctioning pituitary neuroendocrine tumors (NF-PitNETs) invading the cavernous sinus and analyze the differences in immune cell infiltration between invasive and noninvasive NF-PitNETs.MethodsFirst, a retrospective analysis of single-center clinical data was performed. Second, the immune cell infiltration between invasive and noninvasive NF-PitNETs in the GSE169498 dataset was further analyzed, and statistically different cholesterol metabolism-related gene expression matrices were obtained from the dataset. The hub cholesterol metabolism-related genes in NF-PitNETs were screened by constructing machine learning models. In accordance with the hub gene, 73 cases of NF-PitNETs were clustered into two subtypes, and the functional differences and immune cell infiltration between the two subtypes were further analyzed.ResultsThe clinical data of 146 NF-PitNETs were evaluated, and the results showed that the cholesterol (P = 0.034) between invasive and noninvasive NF-PitNETs significantly differed. After binary logistic analysis, cholesterol was found to be an independent risk factor for cavernous sinus invasion (CSI) in NF-PitNETs. Bioinformatics analysis found three immune cells between invasive and noninvasive NF-PitNETs were statistically significant in the GSE169498 dataset, and 34 cholesterol metabolism-related genes with differences between the two groups were obtained 12 hub genes were selected by crossing the two machine learning algorithm results. Subsequently, cholesterol metabolism-related subgroups, A and B, were obtained by unsupervised hierarchical clustering analysis. The results showed that 12 immune cells infiltrated differentially between the two subgroups. The chi-square test revealed that the two subgroups had statistically significance in the invasive and noninvasive samples (P = 0.001). KEGG enrichment analysis showed that the differentially expressed genes were mainly enriched in the neural ligand–receptor pathway. GSVA analysis showed that the mTORC signaling pathway was upregulated and played an important role in the two-cluster comparison.ConclusionBy clinical data and bioinformatics analysis, cholesterol metabolism-related genes may promote the infiltration abundance of immune cells in NF-PitNETs and the invasion of cavernous sinuses by NF-PitNETs through the mTOR signaling pathway. This study provides a new perspective to explore the pathogenesis of cavernous sinus invasion by NF-PitNETs and determine potential therapeutic targets for this disease.

Second-order calibration-assisted LC-MS method for simultaneous determination of multiple active components and origin difference analysis of vinegar-processed cyperi rhizoma

In this work, a liquid chromatography-mass spectrometry (LC-MS) technique combined with alternating normalization weighted error algorithm (ANWE) method was proposed to realize the simultaneously fast quantification of 9 main active ingredients including isomers and origin difference analysis of vinegar-processed cyperi rhizoma (VCR). Overlapping peaks, similar mass spectra and fragment ions of isomers, and unknown matrix interference were all addressed by the proposed approach, which also yielded quantitatively and qualitatively acceptable results. Their average spiked recoveries range from 83.6% to 103.5%. It is worth mentioning that the proposed method can achieve accurate quantification of isomers α-cyperone and nocatone under simple chromatographic elution conditions. And the quantitative results of PARAFAC and ANWE algorithm were compared. Compared with the LC-MS/MS method, the quantitative results of ANWE-LC-MS method are not significantly different, and the required time is shorter. Meanwhile, the ANWE algorithm was used to resolve the 42 VCR's LC-MS fingerprints and determine the relative concentrations of components. Heatmap analysis reveals the difference in the content of the extracted variables in VCR samples, and the unsupervised hierarchical clustering analysis (HCA) method was used for their origins cluster. In addition, the partial least squares discriminant analysis (PLS-DA) method was adapted for the classification of Guang VCR and Non-Guang VCR accurately and five representative difference marker compounds were screened out with the variable importance in projection (VIP). In a word, this work is anticipated to serve as a reference for the development of quality standards for medications made from VCR or other Chinese herbs, as well as for the study of the origin discrimination.

Identifying key factors in cell fate decisions by machine learning interpretable strategies.

Cell fate decisions and transitions are common in almost all developmental processes. Therefore, it is important to identify the decision-making mechanisms and important individual molecules behind the fate decision processes. In this paper, we propose an interpretable strategy based on systematic perturbation, unsupervised hierarchical cluster analysis (HCA), machine learning (ML), and Shapley additive explanation (SHAP) analysis for inferring the contribution and importance of individual molecules in cell fate decision and transition processes. In order to verify feasibility of the approach, we apply it to the core epithelial to mesenchymal transition (EMT)-metastasis network. The key factors identified in EMT-metastasis are consistent with relevant experimental observations. The approach presented here can be applied to other biological networks to identify important factors related to cell fate decisions and transitions.

Pre-transplant immune profile defined by principal component analysis predicts acute rejection after kidney transplantation.

Acute rejection persists as a frequent complication after kidney transplantation. Defining an at-risk immune profile would allow better preventive approaches. We performed unsupervised hierarchical clustering analysis on pre-transplant immunological phenotype in 1113 renal transplant recipients from the ORLY-EST cohort. We identified three immune profiles correlated with clinical phenotypes. A memory immune cluster was defined by memory CD4+T cell expansion and decreased naïve CD4+T cell. An activated immune cluster was characterized by an increase in CD8+T cells and a decreased CD4/CD8 ratio. A naïve immune cluster was mainly defined by increased naïve CD4+T cells. Patients from the memory immune profile tend to be older and to have diabetes whereas those from the activated immune profile were younger and more likely to have pre-transplant exposure to CMV. Patients from the activated immune profile were more prone to experience acute rejection than those from other clusters [(HR=1.69, 95%IC[1.05-2.70], p=0.030) and (HR=1.85; 95%IC[1.16-3.00], p=0.011). In the activated immune profile, those without previous exposure to CMV (24%) were at very high risk of acute rejection (27 vs 16%, HR=1.85; 95%IC[1.04-3.33], p=0.039). Immune profile determination based on principal component analysis defines clinically different sub-groups and discriminate a population at high-risk of acute rejection.