Application of platelet transcriptomics for assessing treatment effectiveness and predicting long-term platelet counts recovery in aplastic anemia

J Thromb Haemost. 2024 Nov 13:S1538-7836(24)00649-4. doi: 10.1016/j.jtha.2024.10.032. Online ahead of print.

Abstract

Background: Aplastic anemia (AA) is a bone marrow failure disease for which the means of assessing and predicting the therapeutic effectiveness are still relatively limited. Thrombocytopenia is often the earliest and most severe symptom in patients newly diagnosed with AA (Dx-AA). While clinical consideration is usually given to the quantitative changes in platelets during treatment, there is little focus on the resolution of the molecular characteristics of platelets in AA.

Objectives: To investigate the changes in platelet molecular characteristics throughout the treatment process of AA, and to explore the use of transcriptomics for monitoring and predicting treatment outcomes.

Methods: We comprehensively analyzed platelet transcriptomic changes in AA patients at initial diagnosis and different stages of treatment effectiveness using bulk transcriptome sequencing.

Results: Genes associated with cell proliferation, erythroid function, and amino acid transport were elevated in Dx-AA. Conversely, genes linked to histones, thrombosis, mitochondrial energy metabolism, and signaling pathways were significantly downregulated. 60.6% of the differentially expressed genes were substantially restored following complete remission. Furthermore, through the examination of longitudinal samples, we identified recovery ascending genes (RAG) that could serve as viable biomarkers for assessing treatment effectiveness in AA. Besides, we observed that higher expression levels of RAG may predict superior long-term platelet counts recovery six months in advance in patients with partial response.

Conclusions: The platelet transcriptome undergoes profound changes and can serve as a potential indicator for assessing treatment effectiveness and predicting long-term platelet counts recovery in AA.

Keywords: Aplastic anemia; Platelets; Prognostic; RNA-seq; Transcriptome.