Evidence map›Paper›PMID 35145297›Full record

ReviewNature immunology2022

Immunogenic cell stress and death.

Guido Kroemer, Claudia Galassi, Laurence Zitvogel, Lorenzo Galluzzi

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 683 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
683citing papers in PubMed, 1 pooled it
101.0field-weighted citation impact, top 1% 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

683 citing papers in PubMed, 1 synthesis or guideline pooled it, 1,224 citations in OpenAlex.

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623 more citing papers are in PubMed but not listed here.

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

4 authors at 2 institutions in 3 countries.

Guido Kroemer *Equipe labellisée par la Ligue contre le cancer, Centre de Recherche des Cordeliers, INSERM U1138, Sorbonne Université, Université de Paris, Institut Universitaire de France, Paris, France. kroemer@orange.fr.ORCID http://orcid.org/0000-0002-9334-4405
Claudia GalassiDepartment of Radiation Oncology, Weill Cornell Medical College, New York, NY, USA.
Laurence ZitvogelGustave Roussy Comprehensive Cancer Institute, Villejuif, France.
Lorenzo Galluzzi *Department of Radiation Oncology, Weill Cornell Medical College, New York, NY, USA. deadoc80@gmail.com.ORCID http://orcid.org/0000-0003-2257-8500
Cornell University · USInserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dying mammalian cells emit numerous signals that interact with the host to dictate the immunological correlates of cellular stress and death. In the absence of reactive antigenic determinants (which is generally the case for healthy cells), such signals may drive inflammation but cannot engage adaptive immunity. Conversely, when cells exhibit sufficient antigenicity, as in the case of infected or malignant cells, their death can culminate with adaptive immune responses that are executed by cytotoxic T lymphocytes and elicit immunological memory. Suggesting a key role for immunogenic cell death (ICD) in immunosurveillance, both pathogens and cancer cells evolved strategies to prevent the recognition of cell death as immunogenic. Intriguingly, normal cells succumbing to conditions that promote the formation of post-translational neoantigens (for example, oxidative stress) can also drive at least some degree of antigen-specific immunity, pointing to a novel implication of ICD in the etiology of non-infectious, non-malignant disorders linked to autoreactivity.

Indexed as

NeoplasmsAdaptive ImmunityAnimalsAntigensCell DeathImmunogenic Cell DeathMammalsAntigens

Identifiers

PMID35145297
OpenAlexW4211133027

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.