Evidence map›Paper›PMID 37688492›Full record

ArticleBiomolecules & biomedicine2024

Comprehensive analysis of a NAD+ metabolism-derived gene signature to predict the prognosis and immune landscape in endometrial cancer.

Dan Hu, JunHong Du, YueMei Cheng, YiJuan Xing, RuiFen He, XiaoLei Liang, HongLi Li, YongXiu Yang

Open access · diamondAbstract read
In one paragraph

Article in Biomolecules & biomedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Review
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.

Dan HuThe First School of Clinical Medicine, Lanzhou University, Lanzhou, China; Key Laboratory for Gynecologic Oncology Gansu Province, Lanzhou, China.
JunHong DuThe First School of Clinical Medicine, Lanzhou University, Lanzhou, China; Key Laboratory for Gynecologic Oncology Gansu Province, Lanzhou, China.
YueMei ChengThe First School of Clinical Medicine, Lanzhou University, Lanzhou, China; Key Laboratory for Gynecologic Oncology Gansu Province, Lanzhou, China.
YiJuan XingThe First School of Clinical Medicine, Lanzhou University, Lanzhou, China; Key Laboratory for Gynecologic Oncology Gansu Province, Lanzhou, China.
RuiFen HeThe First School of Clinical Medicine, Lanzhou University, Lanzhou, China; Key Laboratory for Gynecologic Oncology Gansu Province, Lanzhou, China.
XiaoLei LiangDepartment of Gynecology, The First Hospital of Lanzhou University, Lanzhou, China; Key Laboratory for Gynecologic Oncology Gansu Province, Lanzhou, China.
HongLi LiDepartment of Gynecology, The First Hospital of Lanzhou University, Lanzhou, China; Key Laboratory for Gynecologic Oncology Gansu Province, Lanzhou, China.
YongXiu YangDepartment of Gynecology, The First Hospital of Lanzhou University, Lanzhou, China; Key Laboratory for Gynecologic Oncology Gansu Province, Lanzhou, China.
Lanzhou University · CNFirst Hospital of Lanzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a crucial regulator influencing tumor progression, nicotinamide adenine dinucleotide (NAD+) is widely acknowledged. However, its role in endometrial cancer (EC) is not completely understood. In this study, we aimed to develop an NAD+metabolic-related genes (NMRGs) risk signature that could reflect the prognosis of EC patients and their responsiveness to immunotherapy and chemotherapy. Data from The Cancer Genome Atlas (TCGA) databases and the Molecular Signatures Database (MSigDB) confirmed two distinct NMRG subtypes in EC patients using consensus clustering, and a risk score was constructed utilizing an NAD+-related prognostic signature depending on the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Receiver operating characteristic (ROC) curves were employed to assess the model's precision. Additionally, we used Gene Set Enrichment Analysis (GSEA) to predict the biological signaling pathways that might be involved. We also explored the role of the risk score in immune cell infiltration, tumor mutation burden (TMB), immunotherapy, and chemotherapy. Our study established a prognostic risk signature based on six NMRGs, and we observed that the high-risk group was associated with a poorer prognosis. Furthermore, we identified a strong correlation between the high-risk group and several pathways, including DNA replication, cell cycle, and mismatch repair. Lastly, our findings highlighted the influence of NMRGs on the regulation of immune infiltration in EC. Therefore, this signature holds potential value in predicting the prognosis of EC patients and guiding their management, including decisions regarding immunotherapy and chemotherapy, ultimately improving the accuracy of EC patient care.

Indexed as

Endometrial NeoplasmsNADCell CycleCell DivisionFemaleHumansPrognosisNAD

Identifiers

PMID37688492
PMCPMC10950339
OpenAlexW4386518269

What Socratic 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 Socratic graph.