Evidence map›Paper›PMID 38956267›Full record

ArticleScientific reports2024

Identification of a novel lactylation-related gene signature predicts the prognosis of multiple myeloma and experiment verification.

Cheng Sun, Wanqiu Zhang, Hao Liu, Yangyang Ding, Jingjing Guo, Shudao Xiong, Zhimin Zhai, Wei Hu

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

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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

27 citing papers in PubMed.

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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

8 authors.

Cheng Sun *College of Pharmacy, Anhui Medical University, Hefei, Anhui, People's Republic of China.
Wanqiu Zhang *Department of Hematology/Hematological Lab, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People's Republic of China.
Hao LiuCollege of Pharmacy, Anhui Medical University, Hefei, Anhui, People's Republic of China.
Yangyang DingDepartment of Hematology/Hematological Lab, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People's Republic of China.
Jingjing GuoDepartment of Hematology/Hematological Lab, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People's Republic of China.
Shudao XiongDepartment of Hematology/Hematological Lab, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People's Republic of China.
Zhimin ZhaiDepartment of Hematology/Hematological Lab, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People's Republic of China. zzzm889@163.com.
Wei HuCollege of Pharmacy, Anhui Medical University, Hefei, Anhui, People's Republic of China. huwei@ahmu.edu.cn.

Funding

National Natural Science Foundation of China 82371575
6 · The paper itself

Abstract

Multiple myeloma (MM) is an incurable hematological malignancy with poor survival. Accumulating evidence reveals that lactylation modification plays a vital role in tumorigenesis. However, research on lactylation-related genes (LRGs) in predicting the prognosis of MM remains limited. Differentially expressed LRGs (DELRGs) between MM and normal samples were investigated from the Gene Expression Omnibus database. Univariate Cox regression and LASSO Cox regression analysis were applied to construct gene signature associated with overall survival. The signature was validated in two external datasets. A nomogram was further constructed and evaluated. Additionally, Enrichment analysis, immune analysis, and drug chemosensitivity analysis between the two groups were investigated. qPCR and immunofluorescence staining were performed to validate the expression and localization of PFN1. CCK-8 and flow cytometry were performed to validate biological function. A total of 9 LRGs (TRIM28, PPIA, SOD1, RRP1B, IARS2, RB1, PFN1, PRCC, and FABP5) were selected to establish the prognostic signature. Kaplan-Meier survival curves showed that high-risk group patients had a remarkably worse prognosis in the training and validation cohorts. A nomogram was constructed based on LRGs signature and clinical characteristics, and showed excellent predictive power by calibration curve and C-index. Moreover, biological pathways, immunologic status, as well as sensitivity to chemotherapy drugs were different between high- and low-risk groups. Additionally, the hub gene PFN1 is highly expressed in MM, knocking down PFN1 induces cell cycle arrest, suppresses cell proliferation and promotes cell apoptosis. In conclusion, our study revealed that LRGs signature is a promising biomarker for MM that can effectively early distinguish high-risk patients and predict prognosis.

Indexed as

Biomarkers, TumorGene Expression Regulation, NeoplasticMultiple MyelomaProfilinsApoptosisCell Line, TumorCell ProliferationFemaleGene Expression ProfilingHumansKaplan-Meier EstimateMaleMiddle AgedNomogramsPrognosisTranscriptomeBiomarkers, TumorPFN1 protein, humanProfilinsLactylation‐related genesMMPFN1Prognostic signature

Identifiers

PMID38956267
PMCPMC11219856

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