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Steenbergen, R. D. M.

Publications and source records attributed to Steenbergen, R. D. M..

2 recordsLinked to original sources

Ouro-seq: Improved Recovery of Full-Length circRNAs from Samples with Limited RNA Content

Circular RNAs (circRNAs) are an emerging class of RNAs with biomarker potential, but their detection in liquid biopsies is challenging due to low abundance. We developed Ouro-seq, a novel long-read sequencing protocol optimized for full-length circRNA recovery. Applied to urine, cervico-vaginal self-samples from cervical cancer patients, and plasma from lung cancer patients and controls, Ouro-seq recovered 2-5 times more and substantially longer circRNA molecules than conventional methods. Plasma contained predominantly exonic circRNAs, while urine and cervico-vaginal samples were dominated by previously undercharacterized intergenic circRNAs. We also identified extensive alternative circularization and splicing events. Functional analysis revealed distinct specialization patterns: exonic circRNAs showed enhanced miRNA sponging potential, while circRNAs from unplaced genomic scaffolds demonstrated greater peptide-coding capacity. This study establishes Ouro-seq as a valuable tool for comprehensive circRNA characterization in low-yield clinical samples and advances circRNA biology understanding with potential biomarker discovery and disease monitoring applications. MotivationWhile circular RNAs (circRNAs) constitute a minor fraction of total RNA, they may play critical roles in cancer development. CircRNA concentrations are typically too low for detection by Oxford Nanopore Long-Read Sequencing (LRS), particularly in samples with limited RNA content, such as liquid biopsies. Consequently, LRS-based circRNA analysis from liquid biopsies remains unexplored. To overcome these technical limitations, we developed an optimized circRNA enrichment method utilizing short-amplicon suppression, enabling circRNA profiling from urine, plasma, and cervico-vaginal samples.

cancer biology↗

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↗