Biology subjects

Cloos, J.

Publications and source records attributed to Cloos, J..

3 recordsLinked to original sources

bioRxiv2025

CytoScan: Automated detection of technical anomalies for cytometry quality control

Studies evaluating cellular phenotypes by cytometry techniques are increasingly facing analytical challenges due to the multitudes of samples and parameters that are evaluated concurrently. Spurious technical effects resulting from a lack of standardization can affect marker distributions and further complicate multi-sample analyses. User-friendly tools for exploratory data analysis to identify such technical effects in large datasets are lacking. To fill this gap, we present a novel R package, CytoScan, that evaluates inter-measurement variation in cytometry datasets and allows for detecting anomalous measurements after data acquisition. CytoScan can detect two types of anomalies: files with limited similarity to others within a dataset (outliers) and files with limited similarity to previously acquired high-quality reference data (novelties). Using simulations of skewed marker distributions and real-life technical effects we demonstrate that CytoScan can accurately detect such anomalies. CytoScan can be applied to large cytometry datasets on consumer-grade hardware with informative visualizations, providing accessible quality-control for more reliable analyses.

bioinformatics↗

bioRxiv2024

Repurposing CD19-directed immunotherapies for pediatric t(8;21) acute myeloid leukemia

In contrast to patients with B cell precursor acute lymphoblastic leukemia (BCP-ALL), patients with acute myeloid leukemia (AML) have not yet benefited from recent advances in targeted immunotherapy. Repurposing immunotherapies that have been successfully used to target other hematological malignancies could, in case of a shared target antigen, represent a promising opportunity to expand the immunotherapeutic options for AML. Here, we evaluated the expression of CD19 in a large pediatric AML cohort, assessed the ex vivo AML killing efficacy of CD19-directed immunotherapies, and characterized the bone marrow immune microenvironment in pediatric AML, BCP-ALL, and non-leukemic controls. Out of 167 newly diagnosed de novo pediatric AML patients, 18 patients (11%) had CD19+ AML, with 61% carrying the translocation t(8;21)(q22;q22). Among CD19+ samples, we observed a continuum of CD19 expression levels on AML cells. In individuals exhibiting unimodal and high CD19 expression, the antigen was consistently present on nearly all CD34+CD38- and CD34+CD38+ subpopulations. In ex vivo AML-T cell co-cultures, blinatumomab demonstrated substantial AML killing, with an efficacy similar to BCP-ALL. In addition, CAR T cells could effectively eliminate CD19+ AML cells ex vivo. Furthermore, our immunogenomic assessment of the bone marrow immune microenvironment of newly diagnosed pediatric t(8;21) AML revealed that T- and NK cells had a less exhausted and senescent phenotype in comparison to pediatric BCP-ALL. Altogether, our study underscores the promise of CD19-directed immunotherapies for the treatment of pediatric CD19+ AML.

immunology↗

bioRxiv2020

DPHL: A pan-human protein mass spectrometry library for robust biomarker discovery using Data-Independent Acquisition and Parallel Reaction Monitoring

To answer the increasing need for detecting and validating protein biomarkers in clinical specimens, proteomic techniques are required that support the fast, reproducible and quantitative analysis of large clinical sample cohorts. Targeted mass spectrometry techniques, specifically SRM, PRM and the massively parallel SWATH/DIA technique have emerged as a powerful method for biomarker research. For optimal performance, they require prior knowledge about the fragment ion spectra of targeted peptides. In this report, we describe a mass spectrometric (MS) pipeline and spectral resource to support data-independent acquisition (DIA) and parallel reaction monitoring (PRM) based biomarker studies. To build the spectral resource we integrated common open-source MS computational tools to assemble an open source computational workflow based on Docker. It was then applied to generate a comprehensive DIA pan-human library (DPHL) from 1,096 data dependent acquisition (DDA) MS raw files, and it comprises 242,476 unique peptide sequences from 14,782 protein groups and 10,943 SwissProt-annotated proteins expressed in 16 types of cancer samples. In particular, tissue specimens from patients with prostate cancer, cervical cancer, colorectal cancer, hepatocellular carcinoma, gastric cancer, lung adenocarcinoma, squamous cell lung carcinoma, diseased thyroid, glioblastoma multiforme, sarcoma and diffuse large B-cell lymphoma (DLBCL), as well as plasma samples from a range of hematologic malignancies were collected from multiple clinics in China, the Netherlands and Singapore and included in the resource. This extensive spectral resource was then applied to a prostate cancer cohort of 17 patients, consisting of 8 patients with prostate cancer (PCa) and 9 with benign prostate hyperplasia (BPH), respectively. Data analysis of DIA data from these samples identified differential expressions of FASN, TPP1 and SPON2 in prostate tumors. Thereafter, PRM validation was applied to a larger PCa cohort of 57 patients and the differential expressions of FASN, TPP1 and SPON2 in prostate tumors were validated. As a second application, the DPHL spectral resource was applied to a patient cohort consisting of samples from 19 DLBCL patients and 18 healthy individuals. Differential expressions of CRP, CD44 and SAA1 between DLBCL cases and healthy controls were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supported that DIA-PRM MS pipeline enables robust protein biomarker discoveries.

bioinformatics↗