In one paragraphArticle in Journal for immunotherapy of cancer, 2026. 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 itWhat 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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
12 authors.
Yarui Ma *State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID http://orcid.org/0000-0002-0770-6618 Qi Zhang *State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID http://orcid.org/0009-0002-7020-5960 Zhewen Wei *Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID http://orcid.org/0000-0001-5468-1508 Zhendiao Zhou *State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID http://orcid.org/0000-0002-6220-1137 Xue WangState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID http://orcid.org/0009-0006-0205-2244 Chungui XuState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID http://orcid.org/0009-0004-9053-7414 Xiu LiuState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID http://orcid.org/0000-0001-8993-013X Shitong MinState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID http://orcid.org/0000-0002-4182-639X Peng WangState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID http://orcid.org/0009-0001-5436-8754 Fangqing YuanState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID http://orcid.org/0009-0003-8706-7792 Yuchen JiaoState Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China william327@126.com jiaoyuchen@cicams.ac.cn.ORCID http://orcid.org/0000-0001-7917-8810 Guangwen YuanDepartment of Gynecologic Oncology National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China william327@126.com jiaoyuchen@cicams.ac.cn.ORCID http://orcid.org/0000-0001-8480-3596 Funding
No grant is acknowledged in the PubMed record.
6 · The paper itselfAbstract
backgroundGlucose restriction is a hallmark of the tumor microenvironment (TME), yet how tumor cells adapt to this metabolic stress and the impact of metabolic reprogramming on the TME remains incompletely understood.
methodsA genome-wide CRISPR knockout positive screen was performed to identify key mediators of cellular adaptation to glucose restriction. Using biochemistry, molecular biology, metabolomics and confocal immunofluorescent microscopy to elucidate the underlying molecular mechanisms. Additionally, single-cell RNA sequencing and orthotopic tumor models were used to characterize TME remodeling and assess therapeutic efficacy.
resultsWe identified zinc and ring finger 3 (ZNRF3) as a key mediator of cellular adaptation to glucose restriction through genome-wide CRISPR/Cas9 screening. Multiple tumor cells adaptively survived in glucose-restricted conditions with downregulated ZNRF3. Mechanistically, low glucose suppresses ZNRF3 expression, leading to Wnt pathway activation and subsequent transcriptional repression of stearoyl-CoA desaturase (SCD). This metabolic rewiring enhances antitumor immunity by increasing T-cell infiltration and cytotoxicity. In multiple preclinical models, dietary glucose restriction synergizes with immune checkpoint blockade to suppress tumor growth.
conclusionThese findings establish the ZNRF3-Wnt-SCD axis as a metabolic checkpoint controlling tumor cell fate under glucose restriction and provide a rationale for combining dietary intervention with immunotherapy.
Indexed as
GlucoseImmunotherapyLipid MetabolismMetabolic ReprogrammingWnt Signaling PathwayAnimalsHumansMiceTumor MicroenvironmentGlucoseImmune Checkpoint InhibitorImmunotherapyNutritionTumor Burden
Identifiers
PMID42236114
PMCPMC13239590
What OpenQuestion holds
Textmetadata
LicenceCC BY-NC
Read underepoch 390