Evidence map›Paper›PMID 29030335›Full record

Trial reportBlood2017

Single-cell RNA-seq reveals a distinct transcriptome signature of aneuploid hematopoietic cells.

Xin Zhao, Shouguo Gao, Zhijie Wu, Sachiko Kajigaya, Xingmin Feng, Qingguo Liu, Danielle M Townsley, James Cooper, Jinguo Chen, Keyvan Keyvanfar and 3 more

Open access · bronzeAbstract readClinical Trial
In one paragraph

Trial report in Blood, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
4.8field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 68 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 1 institution in 2 countries.

Xin ZhaoHematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.ORCID 0000-0003-2874-3300
Shouguo GaoHematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
Zhijie WuHematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
Sachiko KajigayaHematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
Xingmin FengHematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
Qingguo LiuHematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
Danielle M TownsleyHematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
James CooperHematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
Jinguo ChenCenter for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, MD; and.
Keyvan KeyvanfarHematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
Maria Del Pilar Fernandez IbanezHematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
Xujing WangSystems Biology Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
Neal S YoungHematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
National Institutes of Health · US

Funding

Pathogenesis And Treatment Of Aplastic AnemiaZIAHL002315 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI YOUNG, NEAL S · 2009 to 2025
$60.1M
6 · The paper itself

Abstract

Cancer cells frequently exhibit chromosomal abnormalities. Specific cytogenetic aberrations often are predictors of outcome, especially in hematologic neoplasms, such as monosomy 7 in myeloid malignancies. The functional consequences of aneuploidy at the cellular level are difficult to assess because of a lack of convenient markers to distinguish abnormal from diploid cells. We performed single-cell RNA sequencing (scRNA-seq) to study hematopoietic stem and progenitor cells from the bone marrow of 4 healthy donors and 5 patients with bone marrow failure and chromosome gain or loss. In total, transcriptome sequences were obtained from 391 control cells and 588 cells from patients. We characterized normal hematopoiesis as binary differentiation from stem cells to erythroid and myeloid-lymphoid pathways. Aneuploid cells were distinguished from diploid cells in patient samples by computational analyses of read fractions and gene expression of individual chromosomes. We confirmed assignment of aneuploidy to individual cells quantitatively, by copy-number variation, and qualitatively, by loss of heterozygosity. When we projected patients' single cells onto the map of normal hematopoiesis, diverse patterns were observed, broadly reflecting clinical phenotypes. Patients' monosomy 7 cells showed downregulation of genes involved in immune response and DNA damage checkpoint and apoptosis pathways, which may contribute to the clonal expansion of monosomy 7 cells with accumulated gene mutations. scRNA-seq is a powerful technique through which to infer the functional consequences of chromosome gain and loss and explore gene targets for directed therapy.

Indexed as

AneuploidyHematopoietic Stem CellsSequence Analysis, RNAAdultBone Marrow CellsBone Marrow DiseasesCase-Control StudiesChromosome DeletionChromosome DisordersChromosomes, Human, Pair 7FemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedSingle-Cell Analysis

Identifiers

PMID29030335
PMCPMC5746166
OpenAlexW2760824708

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.