Evidence map›Paper›PMID 39463937›Full record

ArticlebioRxiv : the preprint server for biology2024

TGF-β induces an atypical EMT to evade immune mechanosurveillance in lung adenocarcinoma dormant metastasis.

Zhenghan Wang, Yassmin Elbanna, Inês Godet, Lila Peters, George Lampe, Yanyan Chen, Joao Xavier, Morgan Huse, Joan Massagué

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Zhenghan WangCancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, USA.ORCID 0000-0002-4728-6566
Yassmin ElbannaImmunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Inês GodetCancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Lila PetersCancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
George LampeCancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Yanyan ChenComputational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Joao XavierComputational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID 0000-0003-3592-1689
Morgan HuseImmunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Joan MassaguéCancer Biology and Genetics Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, USA.ORCID 0000-0001-9324-8408

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
The Role of Focal Oncogene Amplifications in Lung CancerP01CA129243 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI Andrea Ventura · 2007 to 2026
$31.2M
The TGF Beta Signaling Pathway in Development and CancerR35CA252978 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI JOAN MASSAGUE · 2020 to 2026
$7.3M
Synaptic Control of Cytotoxic T cell FunctionR01AI087644 · NIAID · SLOAN-KETTERING INST CAN RESEARCH · PI HUSE, MORGAN A · 2010 to 2025
$7.3M
A Mechanoimmunological Basis for Metastatic Site PreferenceR01CA286566 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI Morgan A Huse · 2024 to 2026
$2.8M
Mathematical modeling of metabolism rewiring in cancer eco-evolution and metastasis tropismR01CA266068 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI Joao Xavier · 2023 to 2026
$2.3M
Molecular Imaging in Cancer Biology Training ProgramT32CA254875 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI Jason S. Lewis, Michael H. Overholtzer · 2021 to 2026
$2.1M
NCI NIH HHS P01 CA129243NCI NIH HHS P30 CA008748NCI NIH HHS R01 CA266068NCI NIH HHS R01 CA286566NCI NIH HHS R35 CA252978NCI NIH HHS T32 CA254875NIAID NIH HHS R01 AI087644
6 · The paper itself

Abstract

The heterogeneity of epithelial-to-mesenchymal transition (EMT) programs is manifest in the diverse EMT-like phenotypes occurring during tumor progression. However, little is known about the mechanistic basis and functional role of specific forms of EMT in cancer. Here we address this question in lung adenocarcinoma (LUAD) cells that enter a dormancy period in response to TGF-β upon disseminating to distant sites. LUAD cells with the capacity to enter dormancy are characterized by expression of SOX2 and NKX2-1 primitive progenitor markers. In these cells, TGF-β induces growth inhibition accompanied by a full EMT response that subsequently transitions into an atypical mesenchymal state of round morphology and lacking actin stress fibers. TGF-β induces this transition by driving the expression of the actin-depolymerizing factor gelsolin, which changes a migratory, stress fiber-rich mesenchymal phenotype into a cortical actin-rich, spheroidal state. This transition lowers the biomechanical stiffness of metastatic progenitors, protecting them from killing by mechanosensitive cytotoxic T lymphocytes (CTLs) and natural killer (NK) cells. Inhibiting this actin depolymerization process clears tissues of dormant metastatic cells. Thus, LUAD primitive progenitors undergo an atypical EMT as part of a strategy to evade immune-mediated elimination during dormancy. Our results provide a mechanistic basis and functional role of this atypical EMT response of LUAD metastatic progenitors and further illuminate the role of TGF-β as a crucial driver of immune evasive metastatic dormancy.

Identifiers

PMID39463937
PMCPMC11507679

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.