Co-evolution of tumor and immune cells during progression of multiple myeloma.
Ruiyang LiuQingsong GaoSteven M FoltzJared S FowlesLijun YaoJulia Tianjiao WangSong CaoHua SunMichael C WendlSunantha SethuramanAmila WeerasingheMichael P RettigErik P StorrsChristopher J YoonMatthew A WyczalkowskiJoshua F McMichaelDaniel R KohnenJustin KingScott R GoldsmithJulie O'NealRobert S FultonCatrina C FronickTimothy J LeyReyka G JayasingheMark A FialaStephen T OhJohn F DipersioRavi VijLi DingPublished in: Nature communications (2021)
Multiple myeloma (MM) is characterized by the uncontrolled proliferation of plasma cells. Despite recent treatment advances, it is still incurable as disease progression is not fully understood. To investigate MM and its immune environment, we apply single cell RNA and linked-read whole genome sequencing to profile 29 longitudinal samples at different disease stages from 14 patients. Here, we collect 17,267 plasma cells and 57,719 immune cells, discovering patient-specific plasma cell profiles and immune cell expression changes. Patients with the same genetic alterations tend to have both plasma cells and immune cells clustered together. By integrating bulk genomics and single cell mapping, we track plasma cell subpopulations across disease stages and find three patterns: stability (from precancer to diagnosis), and gain or loss (from diagnosis to relapse). In multiple patients, we detect "B cell-featured" plasma cell subpopulations that cluster closely with B cells, implicating their cell of origin. We validate AP-1 complex differential expression (JUN and FOS) in plasma cell subpopulations using CyTOF-based protein assays, and integrated analysis of single-cell RNA and CyTOF data reveals AP-1 downstream targets (IL6 and IL1B) potentially leading to inflammation regulation. Our work represents a longitudinal investigation for tumor and microenvironment during MM progression and paves the way for expanding treatment options.
Keyphrases
- single cell
- rna seq
- high throughput
- induced apoptosis
- cell therapy
- multiple myeloma
- end stage renal disease
- newly diagnosed
- ejection fraction
- stem cells
- transcription factor
- prognostic factors
- poor prognosis
- mass spectrometry
- peritoneal dialysis
- high resolution
- mesenchymal stem cells
- cross sectional
- deep learning
- electronic health record
- long non coding rna
- binding protein
- single molecule
- small molecule
- amino acid
- replacement therapy