Evidence map›Paper›PMID 37635086›Full record

ReviewJournal of clinical and experimental hematopathology : JCEH2023

Follicular lymphoma microenvironment: insights provided by single-cell analysis.

Yoshiaki Abe

Open access · goldAbstract readReview
In one paragraph

Review in Journal of clinical and experimental hematopathology : JCEH, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Highlights: Follicular lymphoma.Journal of clinical and experimental hematopathology : JCEH · 2023
    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

1 author at 1 institution in 1 country.

Yoshiaki AbeDepartment of Hematology, Faculty of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan.
University of Tsukuba · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Follicular lymphoma (FL) is the most frequent indolent lymphoma and is characterized by the abundant infiltration of tumor microenvironment (TME) cells. The activity of TME cells reportedly plays an important role in the biology of FL. TME cells that reside within neoplastic follicles, such as T-follicular helper cells and follicular dendritic cells, have been shown to aid in FL development and progression through interactions with malignant B cells, whereas regulatory T cells have unexpectedly shown an apparently favorable prognostic impact in FL. Unfortunately, the understanding of the FL TME, particularly regarding minor cell subsets, has been hampered by unknown cell heterogeneity. As with other solid and hematologic cancers, novel single-cell analysis technologies have recently been applied to FL research and have uncovered previously unrecognized heterogeneities, not only in malignant B cells but also in TME cells. These reports have greatly increased the resolution of our understanding of the FL TME and, at the same time, raised questions about newly identified TME cells. This review provides an overview of the unique aspects of FL TME cells with a clinical viewpoint and highlights recent discoveries from single-cell analysis, while also suggesting potential future directions.

Indexed as

Lymphoma, FollicularLymphoma, Non-HodgkinDendritic Cells, FollicularHumansPrognosisTumor Microenvironmentcell heterogeneityfollicular lymphomaprognosissingle-cell analysistumor microenvironment

Identifiers

PMID37635086
PMCPMC10628831
OpenAlexW4386202701

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.