A Novel Aging-Related Prognostic lncRNA Signature Correlated with Immune Cell Infiltration and Response to Immunotherapy in Breast Cancer

Breast cancer (BC) is among the most universal malignant tumors in women worldwide. Aging is a complex phenomenon, caused by a variety of factors, that plays a significant role in tumor development. Consequently, it is crucial to screen for prognostic aging-related long non-coding RNAs (lncRNAs) in BC. The BC samples from the breast-invasive carcinoma cohort were downloaded from The Cancer Genome Atlas (TCGA) database. The differential expression of aging-related lncRNAs (DEarlncRNAs) was screened by Pearson correlation analysis. Univariate Cox regression, LASSO–Cox analysis, and multivariate Cox analysis were performed to construct an aging-related lncRNA signature. The signature was validated in the GSE20685 dataset from the Gene Expression Omnibus (GEO) database. Subsequently, a nomogram was constructed to predict survival in BC patients. The accuracy of prediction performance was assessed through the time-dependent receiver operating characteristic (ROC) curves, Kaplan–Meier analysis, principal component analyses, decision curve analysis, calibration curve, and concordance index. Finally, differences in tumor mutational burden, tumor-infiltrating immune cells, and patients’ response to chemotherapy and immunotherapy between the high- and low-risk score groups were explored. Analysis of the TCGA cohort revealed a six aging-related lncRNA signature consisting of MCF2L-AS1, USP30-AS1, OTUD6B-AS1, MAPT-AS1, PRR34-AS1, and DLGAP1-AS1. The time-dependent ROC curve proved the optimal predictability for prognosis in BC patients with areas under curves (AUCs) of 0.753, 0.772, and 0.722 in 1, 3, and 5 years, respectively. Patients in the low-risk group had better overall survival and significantly lower total tumor mutational burden. Meanwhile, the high-risk group had a lower proportion of tumor-killing immune cells. The low-risk group could benefit more from immunotherapy and some chemotherapeutics than the high-risk group. The aging-related lncRNA signature can provide new perspectives and methods for early BC diagnosis and therapeutic targets, especially tumor immunotherapy.

[1]  Lingmin Xie,et al.  A Novel Cuproptosis-Related Prognostic Gene Signature and Validation of Differential Expression in Clear Cell Renal Cell Carcinoma , 2022, Genes.

[2]  E. Bullmore,et al.  Immune targets for therapeutic development in depression: towards precision medicine , 2022, Nature reviews. Drug discovery.

[3]  Weijie Hu,et al.  Identification of an Aging-Related Gene Signature in Predicting Prognosis and Indicating Tumor Immune Microenvironment in Breast Cancer , 2021, Frontiers in Oncology.

[4]  Wenfeng Li,et al.  Construction and validation of a novel aging‐related gene signature and prognostic nomogram for predicting the overall survival in ovarian cancer , 2021, Cancer medicine.

[5]  Yongmei Yin,et al.  The Advancing Roles of Exosomes in Breast Cancer , 2021, Frontiers in Cell and Developmental Biology.

[6]  Mingchen Xiong,et al.  Identification and Validation of m6A-Related lncRNA Signature as Potential Predictive Biomarkers in Breast Cancer , 2021, Frontiers in Oncology.

[7]  N. Xu,et al.  USP30-AS1 contributes to mitochondrial quality control in glioblastoma cells. , 2021, Biochemical and biophysical research communications.

[8]  Wen-Cheng Kong,et al.  LncRNA MCF2L-AS1 aggravates the malignant development of colorectal cancer via targeting miR-105-5p/RAB22A axis , 2021, BMC Cancer.

[9]  Hua Lu,et al.  LncRNA RNA Component of Mitochondrial RNA-Processing Endoribonuclease Promotes AKT-Dependent Breast Cancer Growth and Migration by Trapping MicroRNA-206 , 2021, Frontiers in Cell and Developmental Biology.

[10]  Qifeng Li,et al.  LncRNA DLGAP1‐AS1 accelerates glioblastoma cell proliferation through targeting miR‐515‐5p/ROCK1/NFE2L1 axis and activating Wnt signaling pathway , 2021, Brain and behavior.

[11]  Xi Chen,et al.  Construction of a Ferroptosis-Related Nine-lncRNA Signature for Predicting Prognosis and Immune Response in Hepatocellular Carcinoma , 2021, Frontiers in Immunology.

[12]  Yuan Zhang,et al.  Identification of a Ferroptosis-Related Signature Model Including mRNAs and lncRNAs for Predicting Prognosis and Immune Activity in Hepatocellular Carcinoma , 2021, Frontiers in Oncology.

[13]  K. Cao,et al.  Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis , 2021, Frontiers in Immunology.

[14]  Qian Xu,et al.  An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Lung Adenocarcinoma , 2021, Frontiers in Cell and Developmental Biology.

[15]  P. Gao,et al.  New insights into long non-coding RNAs in breast cancer: Biological functions and therapeutic prospects. , 2021, Experimental and molecular pathology.

[16]  Shouguo Li,et al.  Long noncoding RNA MCF2L‐AS1 promotes the cancer stem cell‐like traits in non‐small cell lung cancer cells through regulating miR‐873‐5p level , 2021, Environmental toxicology.

[17]  Zhuochao Liu,et al.  Development and Validation of a Hypoxia-Associated Prognostic Signature Related to Osteosarcoma Metastasis and Immune Infiltration , 2021, Frontiers in Cell and Developmental Biology.

[18]  M. Aslam.  Clinical laboratory medicine measurements correlation analysis under uncertainty , 2021, Annals of clinical biochemistry.

[19]  Mikolaj Ogrodnik,et al.  Cellular aging beyond cellular senescence: Markers of senescence prior to cell cycle arrest in vitro and in vivo , 2021, Aging cell.

[20]  Shihao Guo,et al.  The aging-related risk signature in colorectal cancer , 2021, Aging.

[21]  Ran Xu,et al.  Systematic profiling of ferroptosis gene signatures predicts prognostic factors in esophageal squamous cell carcinoma , 2021, Molecular therapy oncolytics.

[22]  J. Guo,et al.  PRR34-AS1 sponges miR-498 to facilitate TOMM20 and ITGA6 mediated tumor progression in HCC. , 2021, Experimental and molecular pathology.

[23]  Shiguang Zhao,et al.  A Six-lncRNA Signature for Immunophenotype Prediction of Glioblastoma Multiforme , 2021, Frontiers in Genetics.

[24]  Anping Li,et al.  Immune signature-based risk stratification and prediction of immune checkpoint inhibitor’s efficacy for lung adenocarcinoma , 2021, Cancer Immunology, Immunotherapy.

[25]  A. Jemal,et al.  Cancer Statistics, 2021 , 2021, CA: a cancer journal for clinicians.

[26]  M. Piccart,et al.  Immunotherapy for early breast cancer: too soon, too superficial, or just right? , 2020, Annals of oncology : official journal of the European Society for Medical Oncology.

[27]  Yanqin Sun,et al.  New insights into long non-coding RNAs in non-small cell lung cancer. , 2020, Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie.

[28]  Zhuolun Sun,et al.  An autophagy-related long non-coding RNA prognostic signature accurately predicts survival outcomes in bladder urothelial carcinoma patients , 2020, Aging.

[29]  Yan Wang,et al.  The Long Non-coding RNA LINC01705 Regulates the Development of Breast Cancer by Sponging miR-186-5p to Mediate TPR Expression as a Competitive Endogenous RNA , 2020, Frontiers in Genetics.

[30]  Yi-Hong Luo,et al.  Establishment and validation of a novel autophagy-related gene signature for patients with breast cancer. , 2020, Gene.

[31]  Yingchao Li,et al.  The long noncoding RNA OTUD6B-AS1 enhances cell proliferation and the invasion of hepatocellular carcinoma cells through modulating GSKIP/Wnt/β-catenin signalling via the sequestration of miR-664b-3p. , 2020, Experimental cell research.

[32]  S. Joshi,et al.  Long non-coding RNA profiling of pediatric Medulloblastoma , 2020, BMC Medical Genomics.

[33]  Luzhe Sun,et al.  Age-associated genes in human mammary gland drive human breast cancer progression , 2020, Breast Cancer Research.

[34]  Haoying Yu,et al.  Circular RNAs: Promising Molecular Biomarkers of Human Aging-Related Diseases via Functioning as an miRNA Sponge , 2020, Molecular therapy. Methods & clinical development.

[35]  F. Jin,et al.  Immune-related lncRNAs as predictors of survival in breast cancer: a prognostic signature , 2020, Journal of translational medicine.

[36]  F. Bernassola,et al.  DHA Affects Microtubule Dynamics Through Reduction of Phospho-TCTP Levels and Enhances the Antiproliferative Effect of T-DM1 in Trastuzumab-Resistant HER2-Positive Breast Cancer Cell Lines , 2020, Cells.

[37]  A. Jemal,et al.  Cancer statistics, 2020 , 2020, CA: a cancer journal for clinicians.

[38]  Haosheng Jin,et al.  Long non-coding RNA DLGAP1-AS1 facilitates tumorigenesis and epithelial–mesenchymal transition in hepatocellular carcinoma via the feedback loop of miR-26a/b-5p/IL-6/JAK2/STAT3 and Wnt/β-catenin pathway , 2020, Cell Death & Disease.

[39]  Astrid Gall,et al.  Ensembl 2020 , 2019, Nucleic Acids Res..

[40]  Kaiyu Qian,et al.  Novel Biomarkers Associated With Progression and Prognosis of Bladder Cancer Identified by Co-expression Analysis , 2019, Front. Oncol..

[41]  Dan Yang,et al.  Identification of crucial genes in abdominal aortic aneurysm by WGCNA , 2019, PeerJ.

[42]  I. Prinz,et al.  Translating gammadelta (γδ) T cells and their receptors into cancer cell therapies , 2019, Nature Reviews Drug Discovery.

[43]  Z. Shao,et al.  Molecular portraits and trastuzumab responsiveness of estrogen receptor-positive, progesterone receptor-positive, and HER2-positive breast cancer , 2019, Theranostics.

[44]  Gao-Min Liu,et al.  Identification of a six-gene signature predicting overall survival for hepatocellular carcinoma , 2019, Cancer Cell International.

[45]  Li Li,et al.  Overexpression of MAPT-AS1 is associated with better patient survival in breast cancer. , 2019, Biochemistry and cell biology = Biochimie et biologie cellulaire.

[46]  A. Alimonti,et al.  Cellular Senescence: Aging, Cancer, and Injury. , 2019, Physiological reviews.

[47]  Soyoung Lee,et al.  The dynamic nature of senescence in cancer , 2019, Nature Cell Biology.

[48]  Ben Van Calster,et al.  Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators. , 2018, European urology.

[49]  M. Irwin,et al.  Cognitive performance in survivors of breast cancer and markers of biological aging , 2018, Cancer.

[50]  Yassen Assenov,et al.  Maftools: efficient and comprehensive analysis of somatic variants in cancer , 2018, Genome research.

[51]  Kongming Wu,et al.  Biomarkers for predicting efficacy of PD-1/PD-L1 inhibitors , 2018, Molecular cancer.

[52]  Christa Boer,et al.  Correlation Coefficients: Appropriate Use and Interpretation , 2018, Anesthesia and analgesia.

[53]  Fan Yang,et al.  Knockdown of LncRNA MAPT-AS1 inhibites proliferation and migration and sensitizes cancer cells to paclitaxel by regulating MAPT expression in ER-negative breast cancers , 2018, Cell & Bioscience.

[54]  J. Taube,et al.  Implications of the tumor immune microenvironment for staging and therapeutics , 2018, Modern Pathology.

[55]  Hans Clevers,et al.  A Living Biobank of Breast Cancer Organoids Captures Disease Heterogeneity , 2018, Cell.

[56]  P. Khavari,et al.  The functions and unique features of long intergenic non-coding RNA , 2017, Nature Reviews Molecular Cell Biology.

[57]  Pornpimol Charoentong,et al.  Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade , 2016, bioRxiv.

[58]  M. Blasco,et al.  Tissue damage and senescence provide critical signals for cellular reprogramming in vivo , 2016, Science.

[59]  K. Smetana,et al.  Ageing as an Important Risk Factor for Cancer. , 2016, Anticancer research.

[60]  Ash A. Alizadeh,et al.  Robust enumeration of cell subsets from tissue expression profiles , 2015, Nature Methods.

[61]  X. Liu,et al.  JMJD3 promotes SAHF formation in senescent WI38 cells by triggering an interplay between demethylation and phosphorylation of RB protein , 2015, Cell Death and Differentiation.

[62]  N. Cox,et al.  Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines , 2014, Genome Biology.

[63]  G. Raj,et al.  How to build and interpret a nomogram for cancer prognosis. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[64]  Yudong D. He,et al.  A Gene-Expression Signature as a Predictor of Survival in Breast Cancer , 2002 .

[65]  Sudhir Srivastava,et al.  Biomarkers in cancer screening: a public health perspective. , 2002, The Journal of nutrition.

[66]  T. He,et al.  SNHG3 promotes migration, invasion, and epithelial-mesenchymal transition of breast cancer cells through the miR-186-5p/ZEB1 axis. , 2021, American journal of translational research.

[67]  Van,et al.  A gene-expression signature as a predictor of survival in breast cancer. , 2002, The New England journal of medicine.