ArticleNature communications2022
Circulating microbial content in myeloid malignancy patients is associated with disease subtypes and patient outcomes.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 38 citations in OpenAlex.
- Microbiota-Inflammation Crosstalk in Myeloproliferative Neoplasms: MPN-Specific Human Data, Mechanistic Plausibility and Translational Priorities.Biomedicines · 2026Review
- Benchmarking methods for extracting microbial signal from host-dominated metatranscriptomes.Briefings in bioinformatics · 2026Article
- Multifeature sequencing-based liquid biopsy for cancer diagnosis and monitoring.Genome medicine · 2026Review
- The circulating metatranscriptome in acute myeloid leukemia patients: an RNA-seq reanalysis.Frontiers in microbiomes · 2026Article
- Review
- Microbial Crosstalk with Therapy: Pharmacomicrobiomics in AML-One Step Closer to Personalized Medicine.Biomedicines · 2025Review
- Article
- Brain Tumors and Beyond: Multi-Compartment Microbiome and Mycobiome Analysis.International journal of molecular sciences · 2025Article
- Distinct microbiome composition and reduced interactions in patients with pancreatic cancer.Frontiers in microbiology · 2025Article
- Host-microbe-cancer interactions on-a-chip.Frontiers in bioengineering and biotechnology · 2025Review
- Intestinal microbiome and myelodysplastic syndromes: Current state of knowledge and perspectives for future.Seminars in hematology · 2024Review
- A View of Myeloid Transformation through the Hallmarks of Cancer.Blood cancer discovery · 2024Review
- Star wars against leukemia: attacking the clones.Leukemia · 2024Review
- Applications of artificial intelligence to myeloproliferative neoplasms: a narrative review.Expert review of hematology · 2024Review
- Gut Microbiota Disruption in Hematologic Cancer Therapy: Molecular Insights and Implications for Treatment Efficacy.International journal of molecular sciences · 2024Review
- Intratumoral Microbiome: Foe or Friend in Reshaping the Tumor Microenvironment Landscape?Cells · 2024Review
- Blood Microbiota and Its Products: Mechanisms of Interference with Host Cells and Clinical Outcomes.Hematology reports · 2024Review
- A review of machine learning methods for cancer characterization from microbiome data.NPJ precision oncology · 2024Review
- Circulating microbiome DNA as biomarkers for early diagnosis and recurrence of lung cancer.Cell reports. Medicine · 2024Article
- Gut Microbiota Composition Correlates with Disease Severity in Myelodysplastic Syndrome.International journal of hematology-oncology and stem cell research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 4 institutions in 3 countries.
Funding
Abstract
Although recent work has described the microbiome in solid tumors, microbial content in hematological malignancies is not well-characterized. Here we analyze existing deep DNA sequence data from the blood and bone marrow of 1870 patients with myeloid malignancies, along with healthy controls, for bacterial, fungal, and viral content. After strict quality filtering, we find evidence for dysbiosis in disease cases, and distinct microbial signatures among disease subtypes. We also find that microbial content is associated with host gene mutations and with myeloblast cell percentages. In patients with low-risk myelodysplastic syndrome, we provide evidence that Epstein-Barr virus status refines risk stratification into more precise categories than the current standard. Motivated by these observations, we construct machine-learning classifiers that can discriminate among disease subtypes based solely on bacterial content. Our study highlights the association between the circulating microbiome and patient outcome, and its relationship with disease subtype.
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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.