Replacing Bone Marrow Diagnostics With Peripheral Blood Analysis in MPN Patients
Key claim: Peripheral blood profiling of circulating hematopoietic stem and progenitor cells via single-cell RNA sequencing may accurately diagnose and subtype MPNs, potentially replacing invasive bone marrow biopsy.
Abstract
This observational, multi-center study aims to collect data to develop a novel, minimally invasive diagnostic tool for myeloproliferative neoplasms (MPN) based on peripheral blood (PB) profiling of circulating hematopoietic stem and progenitor cells (cHSPCs) using single-cell RNA sequencing (scRNA-seq). Current diagnostic practice relies on bone marrow (BM) biopsy, procedures that is invasive, technically demanding, and may be inconclusive in early or prefibrotic disease stages.
Our prior work established a reference atlas of healthy cHSPC subtypes and a computational pipeline capable of identifying disease-specific transcriptional changes by quantifying deviations from this reference. This study will assess whether PB-based genomic profiling can accurately distinguish MPN from non-clonal cytoses, including secondary erythrocytosis or thrombocytosis.
Patients referred for bone marrow biopsy due to suspected myeloproliferative neoplasm (MPN) will undergo PB collection for genomic profiling. The study’s primary objective is to develop a PB-based test by comparing the developed test diagnoses to the conventional BM-based diagnostics. Secondary objectives include evaluating its potential for MPN subtype classification, risk stratification, as well as assessing its ability to reduce the need for BM biopsies.
Why this matters
Bone marrow biopsy currently anchors diagnosis, subtyping, and fibrosis grading across PV, ET, and PMF, but is invasive and operator-dependent. A validated peripheral blood scRNA-seq pipeline using circulating HSPCs could enable non-invasive subtype assignment and serial monitoring across all classical MPNs, complementing emerging non-invasive fibrosis modalities (CCR2 PET-CT, 18F-FAPI PET/MRI, pSWE) and potentially reshaping how subtype-specific natural history and transformation are tracked.