Nature CancerGenomicsPeer-reviewed journal article
A single-cell atlas characterizes dysregulation of the bone marrow immune microenvironment associated with outcomes in multiple myeloma
William PilcheriD, Lijun Yao, Edgar Gonzalez‐KozlovaiD, Yered H. Pita-JuáreziD, Dimitra KaragkouniiD, Chaitanya R. AcharyaiD, Marina E. MichaudiD, Mark HamiltoniD, Shivani NandaiD, Yizhe SongiD, Kazuhito SatoiD, Julia T. WangiD, Sarthak SatpathyiD, Yuling MaiD, Jessica SchulmaniD, Darwin D’souzaiD, Reyka G. JayasingheiD, Denis J. OhlstromiD, Katherine E. FergusoniD, Giulia CheloniiD, Mojtaba BakhtiariiD, Nick PabustaniD, Kai NieiD, Jennifer Ann FoltziD, Isabella Saldarriaga, , Manoj BhasiniD
Abstract
Multiple Myeloma (MM) remains incurable despite advances in treatment options. Although tumor subtypes and specific DNA abnormalities are linked to worse prognosis, the impact of immune dysfunction on disease emergence and/or treatment sensitivity remains unclear. We established a harmonized consortium to generate an Immune Atlas of MM aimed at informing disease etiology, risk stratification, and potential therapeutic strategies. We generated a transcriptome profile of 1,149,344 single cells from the bone marrow of 263 newly diagnosed patients enrolled in the CoMMpass study and characterized immune and hematopoietic cell populations. Associating cell abundances and gene expression with disease progression revealed the presence of a proinflammatory immune senescence-associated secretory phenotype in rapidly progressing patients. Furthermore, signaling analyses suggested active intercellular communication involving APRIL-BCMA, potentially promoting tumor growth and survival. Finally, we demonstrate that integrating immune cell levels with genetic information can significantly improve patient stratification.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 37
- FWCI
- 123.90
- Field percentile
- top 1%
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