ArticleClinical cancer research : an official journal of the American Association for Cancer Research2024
Plasma Proteomic Signature Predicts Myeloid Neoplasm Risk.
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- The proteomic architecture of clonal hematopoiesis: a systematic review of niche remodeling and multi-compartment predictors of malignant transformation.Frontiers in medicine · 2026Pooled it
- Spleen-derived circulating intercellular adhesion molecule 2 promotes osteosclerosis in chronic myelofibrosis.Bone research · 2026Article
- ProLM: a plasma proteomics pretrained model for the general population.Nature communications · 2026Article
- Clonal hematopoiesis and its progression to myeloid neoplasms: insights into risk, biology, and therapeutic strategies.Haematologica · 2026Review
- Pre-diagnostic plasma proteomics profile uncovers new biomarkers and mechanistic insights for incident kidney cancer.International journal of surgery (London, England) · 2026Article
- A proteogenomic gene signature defines prognostic subgroups highlighting PI3K/AKT/mTOR signaling pathway as a therapeutic vulnerability in myeloid malignancies.Cell communication and signaling : CCS · 2025Article
- Addressing Health Disparities in Hematologic Malignancies: from Genes to Outreach.Blood cancer discovery · 2025Review
- Pathogenesis and inflammaging in myelodysplastic syndrome.Haematologica · 2025Review
- Plasma protein-based and polygenic risk scores serve complementary roles in predicting inflammatory bowel disease.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2025Article
- CHIPing Away at Proteomics to Find Correlations with Myeloid Neoplasms.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024Article
Corrections and comments
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Authors and funding
18 authors at 4 institutions in 2 countries.
Funding
Abstract
purposeClonal hematopoiesis (CH) is thought to be the origin of myeloid neoplasms (MN). Yet, our understanding of the mechanisms driving CH progression to MN and clinical risk prediction of MN remains limited. The human proteome reflects complex interactions between genetic and epigenetic regulation of biological systems. We hypothesized that the plasma proteome might predict MN risk and inform our understanding of the mechanisms promoting MN development. EXPERIMENTAL
designWe jointly characterized CH and plasma proteomic profiles of 46,237 individuals in the UK Biobank at baseline study entry. During 500,036 person-years of follow-up, 115 individuals developed MN. Cox proportional hazard regression was used to test for an association between plasma protein levels and MN risk.
resultsWe identified 115 proteins associated with MN risk, of which 30% (N = 34) were also associated with CH. These were enriched for known regulators of the innate and adaptive immune system. Plasma proteomics improved the prediction of MN risk (AUC = 0.85; P = 5×10-9) beyond clinical factors and CH (AUC = 0.80). In an independent group (N = 381,485), we used inherited polygenic risk scores (PRS) for plasma protein levels to validate the relevance of these proteins toMNdevelopment. PRS analyses suggest that most MN-associated proteins we identified are not directly causally linked toMN risk, but rather represent downstream markers of pathways regulating the progression of CH to MN.
conclusionsThese data highlight the role of immune cell regulation in the progression of CH to MN and the promise of leveraging multi-omic characterization of CH to improveMN risk stratification. See related commentary by Bhalgat and Taylor, p. 3095.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.