Evidence map›Paper›PMID 38831187›Full record

ArticleDiscover oncology2024

Identification and evaluation of a six-lncRNA prognostic signature for multiple myeloma.

Lu Xu, Zhihao Xie, Huanlin Jiang, Erpeng Wang, Min Hu, Qianlei Huang, Xinbao Hao

Abstract read
In one paragraph

Article in Discover oncology, 2024. 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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Lu XuDepartment of Hematology, The First Affiliated Hospital of Hainan Medical College, Haikou, 570102, China. xulu2324@163.com.
Zhihao XieDepartment of Hematology, The First Affiliated Hospital of Hainan Medical College, Haikou, 570102, China.
Huanlin JiangCity Hospital of Qingdao, Qingdao, 266011, China.
Erpeng WangNanfang Medical University, Guangzhou, 510515, China.
Min HuDepartment of Hematology, The First Affiliated Hospital of Hainan Medical College, Haikou, 570102, China.
Qianlei HuangDepartment of Hematology, The First Affiliated Hospital of Hainan Medical College, Haikou, 570102, China.
Xinbao HaoDepartment of Hematology, The First Affiliated Hospital of Hainan Medical College, Haikou, 570102, China. haoxinbao@tsinghua.org.cn.

Funding

Hainan Province Clinical Medical Center Construction Project [2022]276Hainan Provincial Natural Science Foundation of China 820QN401Hainan Provincial Natural Science Foundation of China 822QN468Health Science and Technology Innovation Joint Project of Hainan Province, China WSJK2024MS231Science and Technology special fund of Hainan Province, China ZDYF2024SHFZ114
6 · The paper itself

Abstract

purposeMultiple myeloma (MM) is the second most common hematologic malignancy, and there is no cure for this disease. This study aimed to explore the prognostic value of long noncoding RNAs (lncRNAs) in MM and to reveal related immune and chemotherapy resistance mechanisms.

methodsIn this study, lncRNA profiles from the Multiple Myeloma Research Foundation (MMRF) and Gene Expression Omnibus (GEO) databases were analyzed to identify lncRNAs linked to MM patient survival. A risk assessment model stratified patients into high- and low-risk groups, and survival was evaluated. Additionally, a triple-ceRNA (lncRNA-miRNA-mRNA) network was constructed, and functional analysis was performed. The research also involved immune function analysis and chemotherapy drug sensitivity assessment using oncoPredict and the GDSC dataset.

resultsWe identified 422 lncRNAs significantly associated with overall survival in MM patients and ultimately focused on the 6 with the highest prognostic value. These lncRNAs were used to develop a risk score formula that stratified patients into high- and low-risk groups. Kaplan-Meier analysis revealed shorter survival in high-risk patients. We integrated this lncRNA signature with clinical parameters to construct a nomogram for predicting MM prognosis. Additionally, a triple-ceRNA network was constructed to reveal potential miRNA targets, coding genes related to these lncRNAs and significantly enriched pathways. Immune checkpoint gene expression and immune cell composition were also analyzed in relation to the lncRNA risk score. Finally, using the oncoPredict tool, we observed that high-risk patients exhibited decreased sensitivity to key MM chemotherapeutics, suggesting that lncRNA profiles are linked to chemotherapy resistance.

Indexed as

BiomarkerceRNACompeting endogenous RNALong noncoding RNAMultiple myelomaPrognosis

Identifiers

PMID38831187
PMCPMC11147969

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