Evidence map›Paper›PMID 38357948›Full record

ArticleCurrent medicinal chemistry2024

Prediction Model for Therapeutic Responses in Ovarian Cancer Patients using Paclitaxel-resistant Immune-related lncRNAs.

Xin Li, Huiqiang Liu, Fanchen Wang, Jia Yuan, Wencai Guan, Guoxiong Xu

Abstract read
In one paragraph

Article in Current medicinal chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xin LiResearch Center for Clinical Medicine, Jinshan Hospital of Fudan University, Shanghai, 201508, China.
Huiqiang LiuResearch Center for Clinical Medicine, Jinshan Hospital of Fudan University, Shanghai, 201508, China.
Fanchen WangResearch Center for Clinical Medicine, Jinshan Hospital of Fudan University, Shanghai, 201508, China.
Jia YuanResearch Center for Clinical Medicine, Jinshan Hospital of Fudan University, Shanghai, 201508, China.
Wencai GuanResearch Center for Clinical Medicine, Jinshan Hospital of Fudan University, Shanghai, 201508, China.
Guoxiong XuResearch Center for Clinical Medicine, Jinshan Hospital of Fudan University, Shanghai, 201508, China.ORCID 0000-0002-9074-8754

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOvarian cancer (OC) is the deadliest malignant tumor in women with a poor prognosis due to drug resistance and lack of prediction tools for therapeutic responses to anti- cancer drugs.

objectiveThe objective of this study was to launch a prediction model for therapeutic responses in OC patients.

methodsThe RNA-seq technique was used to identify differentially expressed paclitaxel (PTX)- resistant lncRNAs (DE-lncRNAs). The Cancer Genome Atlas (TCGA)-OV and ImmPort database were used to obtain immune-related lncRNAs (ir-lncRNAs). Univariate, multivariate, and LASSO Cox regression analyses were performed to construct the prediction model. Kaplan- meier plotter, Principal Component Analysis (PCA), nomogram, immune function analysis, and therapeutic response were applied with Genomics of Drug Sensitivity in Cancer (GDSC), CIBERSORT, and TCGA databases. The biological functions were evaluated in the CCLE database and OC cells.

resultsThe RNA-seq defined 186 DE-lncRNAs between PTX-resistant A2780-PTX and PTXsensitive A2780 cells. Through the analysis of the TCGA-OV database, 225 ir-lncRNAs were identified. Analyzing 186 DE-lncRNAs and 225 ir-lncRNAs using univariate, multivariate, and LASSO Cox regression analyses, 9 PTX-resistant immune-related lncRNAs (DEir-lncRNAs) acted as biomarkers were discovered as potential biomarkers in the prediction model. Single-cell RNA sequencing (scRNA-seq) data of OC confirmed the relevance of DEir-lncRNAs in immune responsiveness. Patients with a low prediction score had a promising prognosis, whereas patients with a high prediction score were more prone to evade immunotherapy and chemotherapy and had poor prognosis.

conclusionThe novel prediction model with 9 DEir-lncRNAs is a valuable tool for predicting immunotherapeutic and chemotherapeutic responses and prognosis of patients with OC.

Indexed as

Drug Resistance, NeoplasmOvarian NeoplasmsPaclitaxelRNA, Long NoncodingAntineoplastic Agents, PhytogenicFemaleHumansAntineoplastic Agents, PhytogenicPaclitaxelRNA, Long NoncodingBiomarkerchemoresistanceDEir-lncRNAsimmunotherapynon-coding RNApredicting toolscRNA- seq.

Identifiers

PMID38357948
PMCPMC11340295

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