Comprehensive characterization of stemness-related lncRNAs in triple-negative breast cancer identified a novel prognostic signature related to treatment outcomes, immune landscape analysis and therapeutic guidance: a silico analysis with in vivo experiments

Min Zhang ¹, Fangxu Zhang ², Jianfeng Wang ³

⁰Xiangya Hospital, Central South University, Changsha, 41000, Hunan, People's Republic of China.

Journal of Translational Medicine +

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May 4, 2024

View abstract on PubMed

Summary

This study identifies six stemness-related long non-coding RNAs (SRlncRNAs) as a promising prognostic signature for triple-negative breast cancer (TNBC). This signature can predict patient outcomes and guide personalized treatment strategies.

Area Of Science

Oncology
Genomics
Molecular Biology

Background

Cancer stem cells (CSCs) and long non-coding RNAs (lncRNAs) are critical in triple-negative breast cancer (TNBC) progression, recurrence, and drug resistance.
Identifying reliable prognostic biomarkers is essential for improving TNBC patient outcomes.

Purpose Of The Study

To investigate stemness-related lncRNAs (SRlncRNAs) as potential prognostic indicators for TNBC patients.
To develop and validate a prognostic model based on SRlncRNAs for TNBC.

Main Methods

Utilized TCGA RNA sequencing data and clinical information for TNBC.
Employed Weighted Gene Co-expression Network Analysis (WGCNA) to identify SRGs and SRlncRNAs.
Developed a prognostic model using Cox and LASSO-Cox analyses, validated with Kaplan-Meier and ROC analyses.

Main Results

Identified a six-SRlncRNA signature (AC245100.6, LINC02511, AC092431.1, FRGCA, EMSLR, MIR193BHG) for TNBC prognosis.
Risk scores correlated with plasma cell abundance and showed variability in chemotherapy drug response.
RT-qPCR confirmed abnormal SRlncRNA expression in TNBC stem cells, validating their role.

Conclusions

The SRlncRNA signature serves as a potential prognostic biomarker for TNBC.
The signature offers insights into TNBC biology, signaling pathways, and immune status.
Findings support personalized treatment strategies, including immunotherapy and chemotherapy, for TNBC.

Keywords:

Cancer stem cells Immune microenvironment LncRNAs Personalized treatment Prognostic model Triple-negative breast cancer

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