Evidence map›Paper›PMID 31409707›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

Enhanced adaptive immune responses in lung adenocarcinoma through natural killer cell stimulation.

Leah Schmidt, Banu Eskiocak, Ryan Kohn, Celeste Dang, Nikhil S Joshi, Michel DuPage, Da-Yae Lee, Tyler Jacks

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 5% 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

51 citing papers in PubMed, 1 synthesis or guideline pooled it, 79 citations in OpenAlex.

  1. Pooled it
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  11. Value of a BRAFFrontiers in endocrinology · 2025
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  18. MCM4 acts as a biomarker for LUAD prognosis.Journal of cellular and molecular medicine · 2023
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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

8 authors at 2 institutions in 1 country.

Leah SchmidtKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139.
Banu EskiocakKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139.
Ryan KohnKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139.
Celeste DangKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139.
Nikhil S JoshiKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139.
Michel DuPageKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139.
Da-Yae LeeKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139.
Tyler JacksKoch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139; tjacks@mit.edu.
Massachusetts Institute of Technology · USHoward Hughes Medical Institute · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
VIRUS PRODUCTION COREP30CA014051 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI MATTHEW G. VANDER HEIDEN · 1985 to 2026
$93.9M
PRE-DOCTORAL TRAINING IN THE BIOLOGICAL SCIENCEST32GM007287 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BELL, STEPHEN P., KEATING, AMY E · 1985 to 2019
$40.8M
Tumor-Stroma Interacions in the Tumor MicroenvironmentU54CA126515 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI WEINBERG, ROBERT A · 2006 to 2010
$6.5M
(PQB3) Investigating innate immunosurveillance of oncogene-induced danger signalsR01CA185020 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI JACKS, TYLER E. · 2014 to 2017
$1.3M
Howard Hughes Medical InstituteNCATS NIH HHS UL1 TR001863NCI NIH HHS P30 CA014051NCI NIH HHS R01 CA185020NCI NIH HHS U54 CA126515NIGMS NIH HHS T32 GM007287
6 · The paper itself

Abstract

Natural killer (NK) cells inhibit tumor development in mouse models and their presence in tumors correlates with patient survival. However, tumor-associated NK cells become dysfunctional; thus, stimulation of NK cells in cancer is emerging as an attractive immunotherapeutic strategy. In a mouse model of lung adenocarcinoma, NK cells localized to tumor stroma with immature phenotypes and low functional capacity. To test their responsiveness within established disease, we engineered a system for inducible expression of activating ligands in tumors. After stimulation, NK cells localized inside tumors, with increased cytokine production capacity. Strikingly, T cells were also recruited to tumors in an NK cell-dependent manner, and exhibited higher functionality. In neoantigen-expressing tumors, NK cell stimulation enhanced the number and function of tumor-specific T cells and, in long-term settings, reduced tumor growth. Thus, even in established disease NK cells can be activated to contribute to antitumor immunity, supporting their potential as an important target in cancer immunotherapy.

Indexed as

Adaptive ImmunityAdenocarcinoma of LungAnimalsBiomarkersCell Line, TumorChemokine CCL5Cytotoxicity, ImmunologicDisease Models, AnimalHumansImmunohistochemistryImmunophenotypingKiller Cells, NaturalLymphocyte ActivationMicePhenotypeT-Lymphocyte SubsetsBiomarkersCCL5 protein, humanChemokine CCL5adaptive immune responseantitumor immunityimmunotherapylung adenocarcinomanatural killer cells

Identifiers

PMID31409707
PMCPMC6717259
OpenAlexW2967988243

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.