Research Paper Volume 16, Issue 1 pp 402—430

Deciphering the prognostic significance of anoikis-related lncRNAs in invasive breast cancer: from comprehensive bioinformatics analysis to functional experimental validation

Wenge Dong1, , Jiejing Li1, , Zhigang Zhuang1, ,

  • 1 Department of Breast Surgery, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China

Received: July 26, 2023       Accepted: November 6, 2023       Published: January 5, 2024      

https://doi.org/10.18632/aging.205376
How to Cite

Copyright: © 2024 Dong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

The global prevalence of breast cancer necessitates the development of innovative prognostic markers and therapeutic strategies. This study investigated the prognostic implications of anoikis-related long non-coding RNAs (ARLs) in invasive breast cancer (IBC), which is an area that has not been extensively explored. By integrating the RNA sequence transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database and employing advanced regression analyses, we devised a novel prognostic model based on ARL scores. ARL scores correlated with diverse clinicopathological parameters, cellular pathways, distinct mutation patterns, and immune responses, thereby affecting both immune cell infiltration and anticipated responses to chemotherapy and immunotherapy. Additionally, the overexpression of a specific lncRNA, AL133467.1, significantly impeded the proliferation and migration, as well as possibly the anoikis resistance of breast cancer cells. These findings highlight the potential of the ARL signature as a robust prognostic tool and a promising basis for personalized IBC treatment strategies.

Abbreviations

lncRNA: long non-coding RNA; ARL: anoikis-related lncRNA; IBC: invasive breast cancer; TCGA: The Cancer Genome Atlas; DEL: differentially expressed lncRNA; DEG: differentially expressed gene; ARG: anoikis-related gene; LASSO: Least Absolute Shrinkage and Selection Operator; PCA: principal component analysis; ROC: receiver operating characteristic; DCA: decision curve analysis; GSVA: gene set variation analysis; GSEA: gene set enrichment analysis; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; FDR: false discovery rate; TCIA: The Cancer Immunome Atlas; MEM: minimum Eagle’s medium; DEME: Dulbecco’s modified Eagle medium; LUAD: lung adenocarcinoma; LUSC: lung squamous cell carcinoma; COAD: colon adenocarcinoma; COADREAD: colon adenocarcinoma/rectum adenocarcinoma esophageal carcinoma; BRCA: breast invasive carcinoma; KICH: kidney chromophobe; CHOL: cholangiocarcinoma; KIPAN: pan-kidney; GBM: glioblastoma multiforme; KIRC: kidney renal clear cell carcinoma; HNSC: head and neck squamous cell carcinoma; SKCM: skin cutaneous melanoma; OV: ovarian serous cystadenocarcinoma; HSC: hematopoietic stem cell; MPP: multipotent progenitor; CLP: common lymphoid progenitor.