Identification Of Phenotypes Research Articles

Morphology, Phenotype, and Molecular Identification of Clinical and Environmental Fusarium solani Species Complex Isolates from Malaysia.

Fusarium infections in humans (fusariosis) and in economically important plants involve species of several Fusarium species complexes. Species of the Fusarium solani species complex (FSSC) are the most frequent cause of human fusariosis. The FSSC comprises more than 60 closely related species that can be separated into three major clades by multi-locus sequence typing (MLST) using translation elongation factor 1-alpha (TEF1-α) and RNA polymerase II (RPB2) DNA sequences. The MLST nomenclature for clade 3 of the FSSC assigns numbers to species types (e.g., FSSC 2) and lowercase letters to identify unique haplotypes. The aim of this study was to analyse the genotypic and phenotypic characteristics of 15 environmental and 15 clinical FSSC isolates from Malaysia. MLST was used for the genotypic characterisation of FSSC isolates from various locations within Malaysia, which was complemented by their morphological characterisation on potato dextrose and carnation leaf agar. MLST identified eight different FSSC species: thirteen Fusarium keratoplasticum (i.e., FSSC 2), six Fusarium suttonianum (FSSC 20), five Fusarium falciforme (FSSC 3+4), two Fusarium cyanescens (FSSC 27), and one each of Fusarium petroliphilum (FSSC 1), Fusarium waltergamsii (FSSC 7), Fusarium sp. (FSSC 12), and Fusarium striatum (FSSC 21). Consistent with previous reports from Malaysia, most (11 of 15) clinical FSSC isolates were F. keratoplasticum and the majority (9 of 15) of environmental isolates were F. suttonianum (5) or F. falciforme (4) strains. The taxonomic relationships of the isolates were resolved phylogenetically. The eight Fusarium species also showed distinct morphological characteristics, but these were less clearly defined and reached across species boundaries. Although TEF1-α and RPB2 sequences were sufficient for the species identification of most FSSC isolates, a more precise MLST scheme needs to be established to reliably assign individual isolates of the species-rich FSSC to their geographically-, epidemiologically-, and host-associated sub-lineages.

BnaCRCs with domestication preference positively correlate with the seed-setting rate of canola.

Canola (Brassica napus) is an important oil crop worldwide. The seed-setting rate (SS) is a critical factor in determining its yield, and the development of pistils affects pollination and seed sets. However, research on seed-setting defects has been limited owing to difficulties in the identification of phenotypes, mutations, and complex genetic mechanisms. In this study, we found a stigma defect (sd) mutant in B. napus, which had no nectary. The SS of sd mutants in the field was approximately 93.4% lower than that of the wild type. Scanning and transmission electron microscopy imaging of sd mutants showed a low density of stigma papillary cells and stigma papillary cell vacuoles that disappeared 16 h after flowering. Genetic analysis of segregated populations showed that two recessive nuclear genes are responsible for the mutant phenotype of sd. Based on re-sequencing and map-based cloning, we reduced the candidate sites on ChrA07 (BnaSSA07) and ChrC06 (BnaSSC06) to 30 and 67 kb, including six and eight predicted genes, respectively. Gene analyses showed that a pair of CRABS CLAW (CRC) homeologous genes at BnaSSA07 and BnaSSC06 were associated with the development of carpel and nectary. BnaSSA07.CRC and BnaSSC06.CRC candidate genes were found to be expressed in flower organs only, with significant differences in their expression in the pistils of the near-isogenic lines. DNA sequencing showed transposon insertions in the upstream region and intron of the candidate gene BnaSSA07.crc. We also found that BnaSSC06.crc exists widely in the natural population and we give possible reasons for its widespread existence.

The associations between myositis autoantibodies and clinical presentations in dermatomyositis.

The myositis autoantibodies have been widely used clinically in recent years for the identification of an autoantibody-associated clinical phenotype in dermatomyositis (DM) patients. However, correlations between myositis autoantibodies and clinical presentations in different populations are lacking, especially in Taiwan. To investigate the correlations among cutaneous manifestations, myositis autoantibodies, and systemic diseases, including interstitial lung disease (ILD) and internal malignancy. A retrospective study of patients with histopathologically confirmed cutaneous manifestations of DM was conducted during 2005 to 2020 in Taiwan. A commercial line blot immunoassay technique was used to detect myositis autoantibodies. A total of 88 DM patients were enrolled, with a mean age of onset of 49.4 years old. The most common systemic features were myositis (56.8%, 50/88), internal malignancy (22.7%, 20/88), dysphagia (19.3%, 17/88), and ILD (17%, 15/88). Among the enrolled patients, 32 patients received serum myositis autoantibodies examination. The most common autoantibodies were ANA (50.7%, 37/73), followed by anti-TIF1-γ (34.4%, 11/32) and anti-MDA5 (31.3%, 10/32) antibodies. Patients with Gottron sign (OR 5.6), arthritis (OR 23.35), or the presence of anti-MDA5 antibody (OR 11.14) were more susceptible to progressing to ILD, whereas patients with pruritus (OR 1.04), dysphagia (OR 6.73), and the presence of ANA (OR 6.29) had significantly higher risks of developing internal malignancies. Physicians should pay special attention to certain clinical features, which can help with the early detection of systemic diseases. Cancer screening and myositis autoantibodies examination should be conducted in all DM patients if applicable.

MACHINE LEARNING FOR THE IDENTIFICATION AND CLASSIFICATION OF CLINICAL PHENOTYPES IN PATIENTS WITH AN IMPLANTABLE CARDIOVERTER-DEFIBRILLATOR: TOWARDS PERSONALISED ICD PATIENT CARE

Current care for patients with an implantable cardioverter defibrillator (ICD) does not take into account heterogeneity among ICD patients. Data-driven, unsupervised cluster analysis enables identification of clinical phenotypes that may exhibit distinct trajectories of disease progression, benefit from the ICD and risk for adverse events. Such clinical phenotyping could facilitate personalised care tailored to individual risk of ICD patients.

Refining the risk of HTLV-1-associated myelopathy in people living with HTLV-1: identification of a HAM-like phenotype in a proportion of asymptomatic carriers

Up to 3.8% of human T-lymphotropic virus type-1 (HTLV-1)-infected asymptomatic carriers (AC) eventually develop HTLV-1-associated myelopathy (HAM). HAM occurs in patients with high (> 1%) HTLV proviral load (PVL). However, this cut-off includes more than 50% of ACs and therefore the risk needs to be refined. As HAM is additionally characterised by an inflammatory response to HTLV-1, markers of T cell activation (TCA), β2-microglobulin (β2M) and neuronal damage were accessed for the identification of ACs at high risk of HAM. Retrospective analysis of cross-sectional and longitudinal routine clinical data examining differences in TCA (CD4/CD25, CD4/HLA-DR, CD8/CD25 & CD8/HLA-DR), β2M and neurofilament light (NfL) in plasma in ACs with high or low PVL and patients with HAM. Comparison between 74 low PVL ACs, 84 high PVL ACs and 58 patients with HAM revealed a significant, stepwise, increase in TCA and β2M. Construction of receiver operating characteristic (ROC) curves for each of these blood tests generated a profile that correctly identifies 88% of patients with HAM along with 6% of ACs. The 10 ACs with this ‘HAM-like’ profile had increased levels of NfL in plasma and two developed myelopathy during follow-up, compared to none of the 148 without this viral-immune-phenotype. A viral-immuno-phenotype resembling that seen in patients with HAM identifies asymptomatic carriers who are at increased risk of developing HAM and have markers of subclinical neuronal damage.

Genetic Mapping and Identification of the Gibberellin 3-Oxidase Gene GA3ox Leading to a GA-Deficient Dwarf Phenotype in Pumpkin (Cucurbita moschata D.)

Plant height is an important indicator in the ideal plant model and contributes to optimizing yield and lodging resistance. The emergence of a dwarfing phenotype provides an opportunity for plant height improvement. In a previous study, we identified a dwarf mutant Si1 in pumpkin (Cucurbita moschata D.) obtained by ethyl methane sulfonate (EMS) mutagenesis of the inbred line N87. Phenotype identification for Si1 revealed a decrease in cell size and shorter internodes than those of wild type. Genetic analysis revealed that the dwarf mutant trait was controlled by a single recessive gene, CmaSI1. By bulked segregant analysis (BSA) and subsequent fine mapping, we mapped the CmaSI1 locus to a 463 kb region on chromosome 8 that contained 28 annotated genes in the F2 population. Only one nonsynonymous single nucleotide polymorphism (SNP) in CmoCh08G006170 was obtained according to whole-genome resequencing of the two parents. CmoCh08G006170, a homolog of Arabidopsis gibberellin 3-beta hydroxylase (GA3ox), is a key enzyme in the regulation of bioactive gibberellins (GAs). RNA-seq analysis and qRT-PCR showed that the expression level of CmoCh08G006170 in stems of Si1 was changed compared with that of wild type. The dwarf phenotype could be restored by exogenous GA3 treatment, suggesting that Si1 is a GA-deficient mutant. The above results demonstrated that CmoCh08G006170 may be the candidate gene controlling the dwarf phenotype. This study provides an important theoretical basis for the genetic regulation of vine length and crop breeding in pumpkin.

Selection of Acetic Acid Bacterial Strains and Vinegar Production From Local Maltese Food Sources.

This study investigates the isolation, identification, and fermentation performance of autochthonous acetic acid bacteria (AAB) from local niche habitats on the Island of Gozo (Malta) and their further use for vinegar production, employing local raw materials. The bacteria were isolated from grapevine berries and vinegar produced in the cottage industry. Following phenotype and genotype identification, the AAB were ascribed to the genera Acetobacter, Gluconobacter, and Komagataeibacter. A mixture of selected AAB was tested as an inoculum for vinegar production in bench fermenters, under different conditions and substrates, namely, grapes, honey, figs, onions, prickly pear, and tomatoes. The bench fermenters were operated under semi-continuous fermentation where working volumes were maintained by discharging and subsequent recharging accordingly to maintain the acidity in fermenters by adding 30–50 g/l of acetic acid for optimal Acetobacteraceae performance. Finally, the vinegar products obtained from the different substrates were evaluated for their quality, including organoleptic properties, which showed the superior quality of wood-treated vinegar samples with respect to neat vinegar samples.

Neuromyelitis Optica Spectrum Disorder: From Basic Research to Clinical Perspectives.

Neuromyelitis optica spectrum disorder (NMOSD) is an inflammatory disease of the central nervous system characterized by relapses and autoimmunity caused by antibodies against the astrocyte water channel protein aquaporin-4. Over the past decade, there have been significant advances in the biologic knowledge of NMOSD, which resulted in the IDENTIFICATION of variable disease phenotypes, biomarkers, and complex inflammatory cascades involved in disease pathogenesis. Ongoing clinical trials are looking at new treatments targeting NMOSD relapses. This review aims to provide an update on recent studies regarding issues related to NMOSD, including the pathophysiology of the disease, the potential use of serum and cerebrospinal fluid cytokines as disease biomarkers, the clinical utilization of ocular coherence tomography, and the comparison of different animal models of NMOSD.

Clinical Phenotypes and Mortality Biomarkers: A Study Focused on COVID-19 Patients with Neurological Diseases in Intensive Care Units.

Purpose: To identify clinical phenotypes and biomarkers for best mortality prediction considering age, symptoms and comorbidities in COVID-19 patients with chronic neurological diseases in intensive care units (ICUs). Subjects and Methods: Data included 1252 COVID-19 patients admitted to ICUs in Cuba between January and August 2021. A k-means algorithm based on unsupervised learning was used to identify clinical patterns related to symptoms, comorbidities and age. The Stable Sparse Classifiers procedure (SSC) was employed for predicting mortality. The classification performance was assessed using the area under the receiver operating curve (AUC). Results: Six phenotypes using a modified v-fold cross validation for the k-means algorithm were identified: phenotype class 1, mean age 72.3 years (ys)—hypertension and coronary artery disease, alongside typical COVID-19 symptoms; class 2, mean age 63 ys—asthma, cough and fever; class 3, mean age 74.5 ys—hypertension, diabetes and cough; class 4, mean age 67.8 ys—hypertension and no symptoms; class 5, mean age 53 ys—cough and no comorbidities; class 6, mean age 60 ys—without symptoms or comorbidities. The chronic neurological disease (CND) percentage was distributed in the six phenotypes, predominantly in phenotypes of classes 3 (24.72%) and 4 (35,39%); χ² (5) 11.0129 p = 0.051134. The cerebrovascular disease was concentrated in classes 3 and 4; χ² (5) = 36.63, p = 0.000001. The mortality rate totaled 325 (25.79%), of which 56 (17.23%) had chronic neurological diseases. The highest in-hospital mortality rates were found in phenotypes 1 (37.22%) and 3 (33.98%). The SSC revealed that a neurological symptom (ageusia), together with two neurological diseases (cerebrovascular disease and Parkinson’s disease), and in addition to ICU days, age and specific symptoms (fever, cough, dyspnea and chilliness) as well as particular comorbidities (hypertension, diabetes and asthma) indicated the best prediction performance (AUC = 0.67). Conclusions: The identification of clinical phenotypes and mortality biomarkers using practical variables and robust statistical methodologies make several noteworthy contributions to basic and experimental investigations for distinguishing the COVID-19 clinical spectrum and predicting mortality.

Ecological Effects of Daily Antiseptic Treatment on Microbial Composition of Saliva-Grown Microcosm Biofilms and Selection of Resistant Phenotypes.

Antiseptics are widely used in dental practice and included in numerous over-the-counter oral care products. However, the effects of routine antiseptic use on microbial composition of oral biofilms and on the emergence of resistant phenotypes remain unclear. Microcosm biofilms were inoculated from saliva samples of four donors and cultured in the Amsterdam Active Attachment biofilm model for 3 days. Then, they were treated two times daily with chlorhexidine digluconate (CHX) or cetylpyridinium chloride (CPC) for a period of 7 days. Ecological changes upon these multiple antiseptic treatments were evaluated by semiconductor-based sequencing of bacterial 16S rRNA genes and identification of amplicon sequence variants (ASVs). Furthermore, culture-based approaches were used for colony-forming units (CFU) assay, identification of antiseptic-resistant phenotypes using an agar dilution method, and evaluation of their antibiotic susceptibilities. Both CHX and CPC showed only slight effects on CFU and could not inhibit biofilm growth despite the two times daily treatment for 7 days. Both antiseptics showed significant ecological effects on the microbial compositions of the surviving microbiota, whereby CHX led to enrichment of rather caries-associated saccharolytic taxa and CPC led to enrichment of rather gingivitis-associated proteolytic taxa. Antiseptic-resistant phenotypes were isolated on antiseptic-containing agar plates, which also exhibited phenotypic resistance to various antibiotics. Our results highlight the need for further research into potential detrimental effects of antiseptics on the microbial composition of oral biofilms and on the spread of antimicrobial resistance in the context of their frequent use in oral healthcare.

P-024 Identification of spermatogenic infertility phenotypes using next generation sequencing

Abstract Study question Can next generation sequencing (NGS) contribute to diagnoses male idiopathic infertility? Summary answer A male factor gene panel identifies pathogenic variants associated to spermatogenic failure in oligozoospermia and cryptozoospermia patients. What is known already In 50% of cases, infertility is due to a male factor problem. Although the causes of male infertility are heterogeneous, genetic causes account for approximately 30% of cases. Some phenotypes have been associated with specific genetic disorders such as chromosomal abnormalities and chromosome Y microdeletions. However, current genetic studies explain only 4% of cases, whilst most cases of male factor infertility remain without a clear diagnosis. Therefore, new techniques that explain the cause of male infertility are needed. Advances in NGS allowed us to study a large number of genes involved in spermatogenesis process in patients with idiopathic infertility. Study design, size, duration A retrospective study was performed from July 2020 until May 2021. A total of 30 patients with abnormal seminal count parameters (oligozoospermic and cryptozoospermic) were included in the male factor gene panel study. Patients carrying Y-chromosome microdeletions or abnormal karyotype were excluded. The control group included 20 normozoospermic healthy donors selected on the basis of normal semen parameters according to the WHO criteria (2010). Participants/materials, setting, methods Genomic DNA extraction from blood-EDTA of the patients was performed using the commercial MagMax DNA MultiSample Ultra kit and the King-Fisher automated extractor (ThermoFisher®). Next Generation Sequencing (NGS) was done using a panel with 426 genes involved in the spermatogenesis process. Panel sequencing for identification of genetic variants was performed using Nextera Enrichment technology (Illumina®). FASTAQ data were processed using BWA and GATK algorithms. VCF files were analyzed using Variant Interpreter software. Main results and the role of chance After data analysis, we observed that eight of the thirty patients studied were carriers of mutations in least one of the genes included in the panel (8/30, 26.7%). We identified the following pathogenic variants: a missense mutation (Phe1052Val) and a deletion (Phe508del) of CFTR gene (2/30, 6.6%), two frameshifts (Asp128GlufsTer34 and Lys1299Ter) of CEP290 (2/30, 6.6%), a missense mutation (Tyr284Cys) of GNRHR gene (1/30, 3.3%), a missense mutation (Tyr416Cys) of SCN5A gene (1/30, 3.3%), a deletion (Ser83del) of NANOS1 gene (1/30, 3.3%), a stop gained in splice region Arg341Ter of TEX14 gene (1/30, 3.3%), a splicing donor c.362 + 2T>C of ESR2 gene (1/30, 3.3%) and a missense mutation (Ser321Leu) of DNAH5 gene (1/30, 3.3%), which are related to spermatogenesis failure. Additionally, some variants classified as benign have been identified, which are not associated with pathogenicity. All the variants identified are related with male infertility, affecting spermatogenesis process, such as congenital bilateral absence of the vas deferens (CFTR), reproductive system syndrome (CEP190), endocrine disorder (GNRHR, hypogonadotropic hypogonadism), testis expressed (SCN5A), spermatogenic failure (NANOS1, TEX14 and ESR2) and syndromic infertility (DNAH5). Nevertheless, no pathogenic mutations associated to spermatogenic failure were observed in the control group. Limitations, reasons for caution The main limitation of this study is the small number of patients included. Further studies including a higher number of males with idiopathic infertility are warranted to confidently link the genetic variants included in our gene panel to spermatogenic failure. Wider implications of the findings The gene list included in our panel represents a step-forward in the diagnosis screening of males with altered sperm parameters. Our results may add in the knowledge of male factor infertility in order to provide etiologic factors towards a personalized treatment and adequate genetic counselling. Trial registration number Not applicable

Identification of Multidimensional Phenotypes Using Cluster Analysis in Sarcoid Uveitis Patients

To identify multidimensional phenotypes of sarcoid uveitis patients. Retrospective cohort. Consecutive patients with biopsy-proven, presumed, or probable sarcoid uveitis between December 2003 and December 2020 in Lyon were recruited. Data were collected from the clinical notes, and consisted in laboratory and imaging findings, systemic treatments and outcome. Systemic sarcoidosis was diagnosed according to the Abad's modified criteria and uveitis was classified according to the Standardization of Uveitis Nomenclature. A hierarchical cluster analysis was performed. The main outcome measure was identification of different phenotypes of sarcoid uveitis patients. A total of 299 patients were included. Three clusters were identified: (1) younger non-Caucasian patients who presented acute (75.3%), anterior (55.6%) uveitis, and systemic manifestations (87.8%), requiring oral corticosteroids (75.3%) along with immunosuppressive therapy (17.2%) and who were more prone to experience complete visual recovery (84.1%); (2) middle-aged Caucasian patients who presented chronic (91.7%), panuveitis (79.5%), and isolated uveitis at diagnosis (74.8%), requiring systemic treatment with corticosteroids (74.0%) but less frequently immunosuppressive therapy (9.8%) and a worse prognosis (45.3% complete visual recovery); and (3) middle-aged Caucasian patients, without preferential chronic or acute uveitis, isolated uveitis at diagnosis (81.4%), more homogenous in terms of eye involvement repartition, requiring less corticosteroids or immunosuppressive therapy (respectively 54.1% and 13.1%) and having a prognosis close to cluster 2 patients (55.3% complete visual recovery). This retrospective study suggested the existence of several phenotypes of sarcoid uveitis patients with different progressions and prognoses. Further studies are needed to determine the genetic and environmental factors that could explain these results.

Identification of a Distinct Platelet Phenotype in the Elderly: ADP Hypersensitivity Coexists With Platelet PAR (Protease-Activated Receptor)-1 and PAR-4-Mediated Thrombin Resistance.

Thrombin (via PAR [protease-activated receptor]-1 and PAR-4) and ADP (via P2Y12 receptors) are potent endogenous platelet activators implicated in the development of cardiovascular disease. We aimed to assess whether platelet pathways alter with aging. We characterized platelet activity in community-dwelling volunteers (n=174) in the following age groups: (1) 20 to 30 (young); (2) 40 to 55 (middle-aged); (3) ≥70 years (elderly). Platelet activity was assessed by aggregometry; flow cytometry (surface markers [P-selectin: alpha granule release, CD63: dense granule release, PAC-1: measure of conformationally active GPIIb/IIIa at the fibrinogen binding site]) measured under basal conditions and after agonist stimulation [ADP, thrombin, PAR-1 agonist or PAR-4 agonist]); receptor cleavage and quantification; fluorometry; calcium flux; ELISA. The elderly had higher basal platelet activation than the young, evidenced by increased expression of P-selectin, CD63, and PAC-1, which correlated with increasing inflammation (IL [interleukin]-1β/IL-6). The elderly demonstrated higher P2Y12 receptor density, with greater ADP-induced platelet aggregation (P<0.05). However, elderly subjects were resistant to thrombin, achieving less activation in response to thrombin (higher EC50) and to selective stimulation of both PAR-1 and PAR-4, with higher basal PAR-1/PAR-4 cleavage and less inducible PAR-1/PAR-4 cleavage (all P<0.05). Thrombin resistance was attributable to a combination of reduced thrombin orienting receptor GPIbα (glycoprotein Ibα), reduced secondary ADP contribution to thrombin-mediated activation, and blunted calcium flux. D-Dimer, a marker of in situ thrombin generation, correlated with platelet activation in the circulation, ex vivo thrombin resistance, and circulating inflammatory mediators (TNF [tumor necrosis factor]-α/IL-6). Aging is associated with a distinctive platelet phenotype of increased basal activation, ADP hyperreactivity, and thrombin resistance. In situ thrombin generation associated with systemic inflammation may be novel target to prevent cardiovascular disease in the elderly.

Abstract 6113: Spatially resolved biomarker detection on single cells in TRACERx using multiplex imaging

Abstract Introduction. Studying cell-to-cell variation within the tumour’s native context is crucial for fully understanding tumour heterogeneity and its impact on disease progression and therapy response. Tumour cells and their surrounding stromal cells can be spatially profiled using multiplex imaging with a growing number of detectable proteins. The methods currently used for identification of cell phenotypes from multiplex imaging data have been initially developed for cells in suspension. Therefore, more accurate and robust approaches are required to account for spatial signal overlap and to automatically detect the presence of biomarkers in spatial proteomics. Methods. We performed imaging mass cytometry on 221 tumour and adjacent normal regions from 81 untreated, non-small cell lung cancer patients in the TRACERx study. Two antibody panels with 35 markers were applied to include a range of phenotypic, functional, and structural biomarkers. Single cells were segmented using deep learning-based approaches, and the measured biomarker intensities per cell were further used to identify cell types and functional states. Results. We developed a computational approach optimised for spatial proteomics for identification of cell types and functional states and automated detection of the presence of biomarkers on single cells. First, we demonstrated that current approaches for cell phenotyping lack reproducibility with subsampling and can produce ambiguous clusters of cells from different cell types. Using a multi-tiered analytical approach in combination with statistical tools, we showed reproducibility between technical and biological replicates. We estimated the performance using orthogonal measurements from flow cytometry and immunohistochemistry from matched tumour samples. This approach has been automated with a scalable and portable Nextflow-based implementation. Conclusions. We developed a streamlined approach that overcame limitations of current methods and quantified single-cell biomarker presence using multiplex imaging with TRACERx. Implemented as open-source, portable and customisable, this pipeline for spatially resolved TME characterisation will allow the study of drug targets expression within their spatial context for a better understanding of therapy efficacy. Citation Format: Mihaela Angelova, Katey Enfield, Alastair Magness, Emma Colliver, Masako Shimato, Claudia Lee, David A. Moore, Febe Van Maldegem, Philip Hobson, Dina Levi, James L. Reading, Crispin T. Hiley, Julian Downward, Erik Sahai, Charles Swanton. Spatially resolved biomarker detection on single cells in TRACERx using multiplex imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6113.

Abstract 3921: Precise spatial multiplexing for immune profiling in clinical FFPE tumor samples with ChipCytometry࣪

Abstract Highly multiplexed spatial biomarker analysis has the potential to inform the discovery of novel biomarkers and treatments with the potential to improve clinical outcomes. Clinical diagnoses and treatment decisions have traditionally been made with spatially resolved techniques like immunohistochemistry, that offer a wealth of information about cellular morphology and the spatial context of cells but are limited to a single plex. Newer technologies, such as single-cell RNA sequencing, identify cell subpopulations within tissue but do not capture their spatial distribution or intercellular interactions in situ. Here we present the analysis of clinical FFPE tumor samples using ChipCytometry, a novel precise spatial multiplexing technology that offers high-plex biomarker analysis, without compromising spatial context. ChipCytometry combines iterative immuno-fluorescent staining with high-dynamic range imaging to facilitate quantitative phenotyping with single-cell resolution. Standard FCS files are generated from multichannel OME-TIFF images, enabling identification of cellular phenotypes via flow cytometry-like hierarchical gating. In this study, we identify and quantify immune and epithelial cell phenotypes and subtypes in melanoma and non-small cell lung cancer FFPE samples. The results show precise expression levels for each marker in the assay in each individual cell in the sample, while maintaining spatial information about each cell. Spatial analysis of the samples reveals quantifiable heterogeneity of immune cell infiltration within the tumor samples, demonstrating the utility of the ChipCytometry platform for the in-depth immune profiling in clinical FFPE samples. -Bruker Confidential- Citation Format: Kevin Gamber, Arne Christians, Jennifer Brooks, Karen Kwarta, Crystal Winkeler. Precise spatial multiplexing for immune profiling in clinical FFPE tumor samples with ChipCytometry࣪ [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3921.

Phenotype Identification of HeLa Cells Knockout CDK6 Gene Based on Label-Free Raman Imaging.

Identifying cell phenotypes is essential for understanding the function of biological macromolecules and molecular biology. We developed a noninvasive, label-free, single-cell Raman imaging analysis platform to distinguish between the cell phenotypes of the HeLa cell wild type (WT) and cyclin-dependent kinase 6 (CDK6) gene knockout (KO) type. Via large-scale Raman spectral and imaging analysis, two phenotypes of the HeLa cells were distinguished by their intrinsic biochemical profiles. A significant difference was found between the two cell lines: large lipid droplets formed in the knockout HeLa cells but were not observed in the WT cells, which was confirmed by Oil Red O staining. The band ratio of the Raman spectrum of saturated/unsaturated fatty acids was identified as the Raman spectral marker for HeLa cell WT or gene knockout type differentiation. The interaction between organelles involved in lipid metabolism was revealed by Raman imaging and Lorentz fitting, where the distribution intensity of the mitochondria and the endoplasmic reticulum membrane decreased. At the same time, lysosomes increased after the CDK6 gene knockout. The parameters obtained from Raman spectroscopy are based on hierarchical cluster analysis and one-way ANOVA, enabling highly accurate cell classification.

Simultaneous Mass Spectrometry-Based Apolipoprotein Profiling and Apolipoprotein E Phenotyping in Patients with ASCVD and Mild Cognitive Impairment.

Apolipoprotein E (apoE) occurs on the majority of plasma lipoproteins and plays a major role in the lipid metabolism in the periphery and in the central nervous system. ApoE is a polymorphic protein with three common isoforms, apoE2, apoE3 and apoE4, derived from respective alleles ε2, ε3 and ε4. The aim of this study was to develop a sample pretreatment protocol combined with rapid mass spectrometry (MS)-based assay for simultaneous apolipoprotein profiling and apoE phenotype identification. This assay was validated in 481 samples from patients with stable atherosclerotic cardiovascular disease (ASCVD) and applied to study association with mild cognitive impairment (MCI) in the LIFE Adult study, including overall 690 study subjects. Simultaneous quantification of 8–12 major apolipoproteins including apoA-I, apoB-100 and apoE could be performed within 6.5 min. Phenotyping determined with the developed MS assay had good agreement with the genotyping by real-time fluorescence PCR (97.5%). ApoE2 isoform was associated with the highest total apoE concentration compared to apoE3 and apoE4 (p < 0.001). In the subgroup of diabetic atherosclerotic cardiovascular disease (ASCVD) patients, apoE2 isoform was related to higher apoC-I levels (apoE2 vs. apoE3, p < 0.05), while in the subgroup of ASCVD patients under statin therapy apoE2 was related to lower apoB-100 levels (apoE2 vs. apoE3/apoE4, p < 0.05). A significant difference in apoE concentration observed between mild cognitive impairment (MCI) subjects and controls was confirmed for each apoE phenotype. In conclusion, this study provides evidence for the successful implementation of an MS-based apoE phenotyping assay, which can be used to assess phenotype effects on plasma lipid and apolipoprotein levels.

Stratification of Oligometastatic Prostate Cancer Patients by Liquid Biopsy: Clinical Insights from a Pilot Study.

We propose a pilot, prospective, translational study with the aim of identifying possible molecular markers underlying metastatic prostate cancer (PC) evolution with the use of liquid biopsy. Twenty-eight castrate sensitive, oligometastatic PC patients undergoing bone and/or nodal stereotactic body radiotherapy (SBRT) were recruited. Peripheral blood samples were collected before the commencement of SBRT, then they were processed for circulating cell free DNA (cfDNA) extraction. Deep targeted sequencing was performed using a custom gene panel. The primary endpoint was to identify differences in the molecular contribution between the oligometastatic and polymetastatic evolution of PC to same-first oligo-recurrent disease presentation. Seventy-seven mutations were detected in 25/28 cfDNA samples: ATM in 14 (50%) cases, BRCA2 11 (39%), BRCA1 6 (21%), AR 13 (46%), ETV4, and ETV6 2 (7%). SBRT failure was associated with an increased risk of harboring the BRCA1 mutation (OR 10.5) (p = 0.043). The median cfDNA concentration was 24.02 ng/mL for ATM mutation carriers vs. 40.04 ng/mL for non-carriers (p = 0.039). Real-time molecular characterization of oligometastatic PC may allow for the identification of a true oligometastatic phenotype, with a stable disease over a long time being more likely to benefit from local, curative treatments or the achievement of long-term disease control. A prospective validation of our promising findings is desirable for a better understanding of the real impact of liquid biopsy in detecting tumor aggressiveness and clonal evolution.

Using machine learning on real-world data to predict metastatic status.

1550 Background: Real world data (RWD) is increasingly used to inform research, patient care, and population health in oncology; however, using RWD at scale requires accurate methods to identify clinically-relevant attributes. Metastatic status is a highly relevant clinical attribute in cancer patients but it is not routinely captured in structured formats and its determination conventionally requires review and interpretation by certified tumor registrars (CTRs). Clinical diagnoses, treatments, imaging procedures and other clinical variables documented in electronic health records (EHRs) can be used to differentiate metastatic from non-metastatic patients. This study describes an effective machine learning approach in utilizing prevalent and standardized data elements from EHRs across multiple health systems. Methods: 28,043 lung cancer and breast cancer patients from two large health systems within the Syapse Learning Health Network with data sources from CTR abstraction and EHRs were analyzed. Patients were labeled for reference metastatic status by CTRs and split into training (n = 22,434) and testing (n = 5,609) cohorts, with proportionate distribution of cancer type and metastatic status between cohorts. A regularized gradient boosting algorithm, XGBoost, was trained using over 750 variables from the patient records collected at the time of or after the initial cancer diagnosis. Results: Integration of ICD-10-CM codes with antineoplastic treatment history and radiologic imaging procedure orders achieved metastatic status prediction with increases to precision and recall in lung cancer (21% and 32% respectively) and breast cancer (39% and 9% respectively), when compared to the use of only ICD-10-CM diagnosis codes for secondary malignant neoplasms (Table). The addition of treatment and procedure data from different cancer types improved the model classification within individual cancer types. Conclusions: One of the biggest challenges in using RWD for precision oncology is identification of clinically-relevant phenotypes at scale. Here we demonstrate a scalable evidence-based method utilizing structured data for imputing metastatic status with high predictive power from two separate health systems. With further validation, this approach may be generalized to other cancer types, applied to temporal slices of data to identify changes in metastatic status, as well as provide a high-confidence designation of metastatic status for other use cases such as staging.[Table: see text]

VALIDATION OF THE OPTICAL AKTIIA BRACELET IN DIFFERENT BODY POSITIONS FOR THE PERSISTENT MONITORING OF BLOOD PRESSURE

Objective: The diagnosis of hypertension and the adjustment of antihypertensive drugs are evolving from repeated isolated measurements performed at the physician offices to the full phenotyping of patients in real-life conditions. Indeed, epidemiologic data show that prediction of risk is largely improved when blood pressure (BP) is measured out of the doctor’s office. Today, out-of-office measurements of BP are mostly performed by a series of self-measurements done at home over several days (HBPM monitoring), or automatically for 24 hours (ABPM monitoring). None of these approaches allow assessing and tracking the 24 hour hypertensive phenotype of patients in the long term. The aim of this study was to demonstrate that a wearable BP monitor (the CE-marked Aktiia Bracelet) can accurately estimate BP in the most common body positions of daily life and thus become a candidate solution for the long-term BP phenotyping of patients. Design and method: We recruited 91 patients with BP ranging from low to hypertensive levels and compared BP values from the Aktiia Bracelet against auscultatory reference values for four weeks at different body positions according to an extended and adapted ISO 81060-2 protocol. Results: The observed means and standard deviations of differences for systolic BP were of 0.46 ± 7.75 mmHg in the sitting position, -2.44 ± 10.15 mmHg in the lying, -3.02 ± 6.10 mmHg in the sitting with the device on the lap, and -0.62 ± 12.51 mmHg in the standing position. Differences for diastolic BP readings were respectively of 0.39 ± 6.86 mmHg, -1.93 ± 7.65 mmHg, 4.22 ± 6.56 mmHg and -4.85 ± 9.11 mmHg. For the sitting and relax position (for which the ISO 81060–2 performance criteria are applicable) the Aktiia Bracelet met criterion 1 and criterion 2. Conclusions: This study demonstrates that the optical Aktiia Bracelet can accurately estimate BP in the most common body positions compared to auscultation, although precision varies across positions. These findings pave the way to the use of this wearable device for the persistent monitoring of BP, and the further identification of individual BP phenotypes at scale.