Evidence map›Paper›PMID 33732232›Full record

ReviewFrontiers in immunology2021

Lymphoma Heterogeneity Unraveled by Single-Cell Transcriptomics.

Loic Ysebaert, Anne Quillet-Mary, Marie Tosolini, Frederic Pont, Camille Laurent, Jean-Jacques Fournié

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  7. Review
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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

6 authors.

Loic YsebaertCentre de Recherches en Cancérologie de Toulouse, INSERM UMR1037, Toulouse, France.
Anne Quillet-MaryCentre de Recherches en Cancérologie de Toulouse, INSERM UMR1037, Toulouse, France.
Marie TosoliniCentre de Recherches en Cancérologie de Toulouse, INSERM UMR1037, Toulouse, France.
Frederic PontCentre de Recherches en Cancérologie de Toulouse, INSERM UMR1037, Toulouse, France.
Camille LaurentCentre de Recherches en Cancérologie de Toulouse, INSERM UMR1037, Toulouse, France.
Jean-Jacques FourniéCentre de Recherches en Cancérologie de Toulouse, INSERM UMR1037, Toulouse, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-definition transcriptomic studies through single-cell RNA sequencing (scRNA-Seq) have revealed the heterogeneity and functionality of the various microenvironments across numerous solid tumors. Those pioneer studies have highlighted different cellular signatures correlated with clinical response to immune checkpoint inhibitors. scRNA-Seq offers also a unique opportunity to unravel the intimate heterogeneity of the ecosystems across different lymphoma entities. In this review, we will first cover the basics and future developments of the technology, and we will discuss its input in the field of translational lymphoma research, from determination of cell-of-origin and functional diversity, to monitoring of anti-cancer targeted drugs response and toxicities, and how new improvements in both data collection and interpretation will further foster precision medicine in the upcoming years.

Indexed as

Gene Expression ProfilingSingle-Cell AnalysisTranscriptomeBiomarkers, TumorCombined Modality TherapyComputational BiologyHigh-Throughput Nucleotide SequencingHumansLymphomaMolecular Sequence AnnotationPrecision MedicinePrognosisTreatment OutcomeBiomarkers, Tumorbioinformatics analysiscell of origin (COO)lymphomamicroenvironmentsingle-cell RNA sequencing (scRNA-seq)

Identifiers

PMID33732232
PMCPMC7959738

What OpenQuestion holds

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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.