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Lintermans, B.

Publications and source records attributed to Lintermans, B..

2 recordsLinked to original sources

Biases in the Parsortix system observed with pancreatic cancer cell lines

Pancreatic cancer has a 5-year survival rate of merely 12%. The high rate of late-stage diagnoses underscores the need for reliable biomarkers for early detection and disease monitoring. Circulating tumor cells (CTCs) have emerged as a promising biomarker, yet their detection remains challenging due to their rarity and phenotypic diversity. This study evaluates the Parsortix(R) system, a microfluidic device designed to enrich CTCs based on size and deformability, using pancreatic cancer cell lines. As increasing evidence indicates that during epithelial to mesenchymal transition (EMT) a cells deformability increases, we evaluated to what extent the Parsortix(R) system was biased towards epithelial cancer cells. First, the EMT stage of three pancreatic cancer cell lines, CAPAN-1, PANC-1 and MIA PaCa-2, was assessed using immunocytochemistry, flow cytometry and proteomics. CAPAN-1 cells were classified as epithelial, MIA PaCa-2 cells exhibited a mesenchymal-like phenotype, and PANC-1 cells demonstrated a hybrid phenotype. Then, by spiking these cells into blood samples, we determined the Parsortix(R) systems ability to recover the cancer cells. Our results indicated that epithelial and hybrid phenotypes are more efficiently captured (62.6 {+/-} 18.5% and 65.4 {+/-} 11.1%) than mesenchymal cancer cells (32.8 {+/-} 10.2%). To confirm these findings, spike-in experiments were repeated using an EMT inducible cell line. Again, significantly lower recovery rates were found for the cells in a mesenchymal-like state (31.5 {+/-} 6.4%) compared to those in an epithelial state (47.56 {+/-} 7.2%). In conclusion, the Parsortix(R) system may underestimate the presence of mesenchymal CTCs.

cancer biology↗

An interactive mass spectrometry atlas of histone posttranslational modifications in T-cell acute leukemia

The holistic nature of omics studies makes them ideally suited to generate hypotheses on health and disease. Sequencing-based genomics and mass spectrometry (MS)-based proteomics are linked through epigenetic regulation mechanisms. However, epigenomics is currently mainly focused on DNA methylation status using sequencing technologies, while studying histone posttranslational modifications (hPTMs) using MS is lagging, partly because reuse of raw data is impractical. Yet, targeting hPTMs using epidrugs is an established promising research avenue in cancer treatment. Therefore, we here present the most comprehensive MS-based preprocessed hPTM atlas to date, including 21 T-cell acute lymphoblastic leukemia (T-ALL) cell lines. We present the data in an intuitive and browsable single licensed Progenesis QIP project and provide all essential quality metrics, allowing users to assess the quality of the data, edit individual peptides, try novel annotation algorithms and export both peptide and protein data for downstream analyses, exemplified by the PeptidoformViz tool. This data resource sets the stage for generalizing MS-based histone analysis and provides the first reusable histone dataset for epidrug development.

cancer biology↗