Evidence map›Paper›PMID 40895564›Full record

ArticleFrontiers in immunology2025

Analysis of m7G-related signatures in the tumor immune microenvironment and identification of clinical prognostic regulators in ovarian cancer.

Kunyu Wang, You Wu, Miao Ao, Wei Mao, Haixia Luo, Yan Song, Bin Li

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Kunyu Wang *Department of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
You Wu *Department of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Miao Ao *Department of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Wei MaoDepartment of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Haixia LuoDepartment of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yan SongDepartment of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Bin LiDepartment of Gynecology Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer (OV) is the most lethal gynecological malignancy in the world. At present, the effect of m7G modification-related genes on the development of ovarian cancer remains unclear. We performed consensus clustering of ovarian cancer samples based on the expression of 24 m7G modification-related genes, and obtained 2 subtypes. There were some differences in immune cell infiltration between the two subtypes. Furthermore, enrichment analysis showed that differential genes were mainly enriched in several pathways and biological processes, including positive translation regulation and TRAPP complex. Multivariate cox regression analysis confirmed two genes (DCP2 and NUDT16) related to prognosis for the construction of risk score prediction models. The risk map of survival status showed that the high-risk samples had a shorter survival time (p<0.05). Risk score was an independent prognostic factor for OV and correlated with immunotherapy response. We also performed network analysis for DCP2 and NUDT16. We further explored the effects of the genes on cellular function and prognosis. In conclusion, this study provided a new perspective for the development mechanism of ovarian cancer.

Indexed as

Biomarkers, TumorOvarian NeoplasmsTumor MicroenvironmentFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansPrognosisPyrophosphatasesBiomarkers, TumorPyrophosphatasesDCP2immune microenvironmentm7GNUDT16ovarian cancer

Identifiers

PMID40895564
PMCPMC12390964

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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.