Evidence map›Paper›PMID 34811507›Full record

ReviewBritish journal of cancer2022

Toward platelet transcriptomics in cancer diagnosis, prognosis and therapy.

Anandi Krishnan, Sally Thomas

Open access · greenAbstract readReview
In one paragraph

Review in British journal of cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

18 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. [Prognostic analysis of childhood T-lymphoblastic lymphoma treated with leukemia regimen].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2024
    Article
  11. Article
  12. Article
  13. Heterogeneity of platelets and their responses.Research and practice in thrombosis and haemostasis · 2024
    Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 2 countries.

Anandi KrishnanDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA. anandi.krishnan@stanford.edu.ORCID http://orcid.org/0000-0002-0962-2215
Sally ThomasDepartment of Oncology and Metabolism, University of Sheffield Medical School, Sheffield, UK.ORCID http://orcid.org/0000-0002-0027-0815
Sheffield Teaching Hospitals NHS Foundation Trust · GBStanford Medicine · US

Funding

Stanford Center for Clinical & Translational Education and Research (Spectrum)UL1TR003142 · NCATS · STANFORD UNIVERSITY · PI O'HARA, RUTH M · 2019 to 2023
$45.0M
Integrated Clinical and Transcriptomic Profiling to Characterize Disease PhenotypeK08HG010061 · NHGRI · STANFORD UNIVERSITY · PI KRISHNAN, ANANDI · 2018 to 2022
$955k
Object Storage for Secure Data SharingS10OD025082 · OD · STANFORD UNIVERSITY · PI DATTA, SOMALEE · 2018 to 2018
$593k
NCATS NIH HHS UL1 TR003142NHGRI NIH HHS K08 HG010061NIH HHS S10 OD025082U.S. Department of Health & Human Services | National Institutes of Health (NIH) 3UL1TR001085-04S1
6 · The paper itself

Abstract

Widespread adoption of next-generation techniques such as RNA-sequencing (RNA-seq) has enabled research examining the transcriptome of anucleate blood platelets in health and disease, thus revealing a rich platelet transcriptomic signature that is reprogrammed in response to disease. Platelet signatures not only capture information from parent megakaryocytes and progenitor hematopoietic stem cells but also the bone marrow microenvironment, and underlying disease states. In cancer, the substantive body of research in patients with solid tumours has identified distinct signatures in 'tumour-educated platelets', reflecting influences of the tumour, stroma and vasculature on splicing, sequestration of tumour-derived RNAs, and potentially cytokine and microvesicle influences on megakaryocytes. More recently, platelet RNA expression has emerged as a highly sensitive approach to profiling chronic progressive haematologic malignancies, where the combination of large data cohorts and machine-learning algorithms enables precise feature selection and potential prognostication. Despite these advances, however, our ability to translate platelet transcriptomics toward clinical diagnostic and prognostic efforts remains limited. In this Perspective, we present a few actionable steps for our basic, translational and clinical research communities in advancing the utility of the platelet transcriptome as a highly sensitive biomarker in cancer and collectively enable efforts toward clinical translation and patient benefit.

Indexed as

Gene Expression ProfilingTranscriptomeTumor MicroenvironmentAnimalsBlood PlateletsHumansNeoplasms

Identifiers

PMID34811507
PMCPMC8810955
OpenAlexW3215774169

What Socratic 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 Socratic graph.