Evidence map›Paper›PMID 35551660›Full record

ReviewCancer treatment and research2022

Lag3: From Bench to Bedside.

Francesca Aroldi, Reem Saleh, Insiya Jafferji, Carmelia Barreto, Chantal Saberian, Mark R Middleton

Abstract readReview
PubMed Publisher
In one paragraph

Review in Cancer treatment and research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
8.4field-weighted citation impact, top 2% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
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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 at 3 institutions in 3 countries.

Francesca AroldiDepartment of Oncology, The University of Oxford, OX 37LE, Oxford, England. dssafrancesca.aroldi@gmail.com.
Reem SalehPeter MacCallum Cancer Centre, Tumor Suppression and Cancer Sex Disparity Laboratory, Melbourne, VIC, 3000, Australia.
Insiya JafferjiDepartment of Immunology, The University of Texas MD Anderson Cancer Centre, Houston, TX, 77030, USA.
Carmelia BarretoInvestigational Cancer Therapeutics (A Phase I Program), The University of Texas MD Anderson Cancer Centre, Houston, TX, 77030, USA.
Chantal SaberianMelanoma Medical Oncology, The University of Texas MD Anderson Cancer Centre, Houston, TX, 77030, USA.
Mark R MiddletonDepartment of Oncology, The University of Oxford, OX 37LE, Oxford, England.
The University of Texas MD Anderson Cancer Center · USUniversity of Oxford · GBPeter MacCallum Cancer Centre · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The introduction of immune checkpoint inhibitors represented a breakthrough treatment for metastatic melanoma, but the effect of these agents is not limited to a single cancer type. Promising results have been reported in various solid tumors, for example, lung cancer. The success of these drugs depends on the activation of tumor-infiltrating lymphocytes and primary and acquired resistance have been reported alongside a high rate of immune-related adverse events when agents targeting different immune checkpoints are given in combination. Numerous other targets have been investigated to overcome the resistance, improve the activity, and reduce the toxicity of checkpoint inhibitor therapy. Among these, the most promising is Lymphocyte-activation gene 3 (LAG-3), a transmembrane protein involved in cytokine release and inhibitory signaling in T cells. Preclinical data showed that LAG-3 is a negative regulator of both CD4

Indexed as

MelanomaProgrammed Cell Death 1 ReceptorCD8-Positive T-LymphocytesHumansLymphocytes, Tumor-InfiltratingProgrammed Cell Death 1 Receptor

Identifiers

PMID35551660
OpenAlexW4285306252

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.