Evidence map›Paper›PMID 34853298›Full record

ArticleNature communications2021

Tumor evolution selectively inactivates the core microRNA machinery for immune evasion.

Tian-Yu Song, Min Long, Hai-Xin Zhao, Miao-Wen Zou, Hong-Jie Fan, Yang Liu, Chen-Lu Geng, Min-Fang Song, Yu-Feng Liu, Jun-Yi Chen and 6 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

17 citing papers in PubMed, 20 citations in OpenAlex.

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  7. Clinical Relevance ofInternational journal of molecular sciences · 2025
    Article
  8. Article
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  10. A tumor-conditional IL-15 safely synergizes with immunotherapy to enhance antitumor immune responses.Molecular therapy : the journal of the American Society of Gene Therapy · 2024
    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

16 authors at 3 institutions in 1 country.

Tian-Yu Song *Gene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.ORCID 0000-0001-9834-6795
Min Long *Gene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Hai-Xin Zhao *Oncology and Immunology Unit, WuXi Biology, WuXi AppTec (Shanghai) Co, Ltd, Shanghai, China.
Miao-Wen ZouGene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.ORCID 0000-0003-4179-2844
Hong-Jie FanGene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Yang LiuGene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Chen-Lu GengGene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Min-Fang SongGene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Yu-Feng LiuGene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Jun-Yi ChenGene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Yu-Lin YangOncology and Immunology Unit, WuXi Biology, WuXi AppTec (Shanghai) Co, Ltd, Shanghai, China.
Wen-Rong ZhouOncology and Immunology Unit, WuXi Biology, WuXi AppTec (Shanghai) Co, Ltd, Shanghai, China.
Da-Wei HuangOncology and Immunology Unit, WuXi Biology, WuXi AppTec (Shanghai) Co, Ltd, Shanghai, China.
Bo PengGene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
Zhen-Gang PengOncology and Immunology Unit, WuXi Biology, WuXi AppTec (Shanghai) Co, Ltd, Shanghai, China.
Yong CangGene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, China. cangyong@shanghaitech.edu.cn.ORCID 0000-0002-1148-7008
ShanghaiTech University · CNWuXi AppTec (China) · CNChinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer cells acquire genetic heterogeneity to escape from immune surveillance during tumor evolution, but a systematic approach to distinguish driver from passenger mutations is lacking. Here we investigate the impact of different immune pressure on tumor clonal dynamics and immune evasion mechanism, by combining massive parallel sequencing of immune edited tumors and CRISPR library screens in syngeneic mouse tumor model and co-culture system. We find that the core microRNA (miRNA) biogenesis and targeting machinery maintains the sensitivity of cancer cells to PD-1-independent T cell-mediated cytotoxicity. Genetic inactivation of the machinery or re-introduction of ANKRD52 frequent patient mutations dampens the JAK-STAT-interferon-γ signaling and antigen presentation in cancer cells, largely by abolishing miR-155-targeted silencing of suppressor of cytokine signaling 1 (SOCS1). Expression of each miRNA machinery component strongly correlates with intratumoral T cell infiltration in nearly all human cancer types. Our data indicate that the evolutionarily conserved miRNA pathway can be exploited by cancer cells to escape from T cell-mediated elimination and immunotherapy.

Indexed as

Immune EvasionNeoplasmsAnimalsCell Line, TumorChemokinesGenetic HeterogeneityHumansImmunotherapyInterferon-gammaMiceMice, Inbred C57BLMice, NudeMicroRNAsPhosphoprotein PhosphatasesProgrammed Cell Death 1 ReceptorSignal TransductionChemokinesInterferon-gammaMicroRNAsMIRN155 microRNA, humanPDCD1 protein, humanPdcd1 protein, mousePhosphoprotein PhosphatasesProgrammed Cell Death 1 ReceptorSuppressor of Cytokine Signaling 1 Protein

Identifiers

PMID34853298
PMCPMC8636623
OpenAlexW3215036364

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.