Evidence map›Paper›PMID 36845727›Full record

ArticleFrontiers in oncology2023

A novel ferroptosis-related gene signature for predicting prognosis in multiple myeloma.

Dandan Gao, Rui Liu, Yang Lv, Yuandong Feng, Fei Hong, Xuezhu Xu, Jinsong Hu, Aili He, Yun Yang

Abstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Research Progress on Ferroptosis in Multiple Myeloma.Current treatment options in oncology · 2024
    Review
  10. Article
  11. Article
  12. 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

9 authors.

Dandan GaoDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Rui LiuDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Yang LvDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Yuandong FengDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Fei HongDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Xuezhu XuDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Jinsong HuDepartment of Cell Biology and Genetics, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Aili HeDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Yun YangDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Multiple myeloma (MM) is a highly malignant hematological tumor with a poor overall survival (OS). Due to the high heterogeneity of MM, it is necessary to explore novel markers for the prognosis prediction for MM patients. Ferroptosis is a form of regulated cell death, playing a critical role in tumorigenesis and cancer progression. However, the predictive role of ferroptosis-related genes (FRGs) in MM prognosis remains unknown. Methods: This study collected 107 FRGs previously reported and utilized the least absolute shrinkage and selection operator (LASSO) cox regression model to construct a multi-genes risk signature model upon FRGs. The ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA) were carried out to evaluate immune infiltration level. Drug sensitivity was assessed based on the Genomics of Drug Sensitivity in Cancer database (GDSC). Then the synergy effect was determined with Cell counting kit-8 (CCK-8) assay and SynergyFinder software. Results: A 6-gene prognostic risk signature model was constructed, and MM patients were divided into high and low risk groups. Kaplan-Meier survival curves showed that patients in the high risk group had significantly reduced OS compared with patients in the low risk group. Besides, the risk score was an independent predictor for OS. Receiver operating characteristic (ROC) curve analysis confirmed the predictive capacity of the risk signature. Combination of risk score and ISS stage had better prediction performance. Enrichment analysis revealed immune response, MYC, mTOR, proteasome and oxidative phosphorylation were enriched in high risk MM patients. We found high risk MM patients had lower immune scores and immune infiltration levels. Moreover, further analysis found that MM patients in high risk group were sensitive to bortezomib and lenalidomide. At last, the results of the Conclusion: This study provides novel insights into roles of ferroptosis in MM prognosis prediction, immune levels and drug sensitivity, which complements and improves current grading systems.

Indexed as

drug sensitivityferroptosismultiple myelomarisk signaturetumor immunity

Identifiers

PMID36845727
PMCPMC9950937

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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.