Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
Breast Cancer Research and Treatment
Published in: Breast Cancer Research and Treatment 1/2019

01-05-2019 | Breast Cancer | Preclinical study

An eight-lncRNA signature predicts survival of breast cancer patients: a comprehensive study based on weighted gene co-expression network analysis and competing endogenous RNA network

Authors: Min Sun, Di Wu, Ke Zhou, Heng Li, Xingrui Gong, Qiong Wei, Mengyu Du, Peijie Lei, Jin Zha, Hongrui Zhu, Xinsheng Gu, Dong Huang

Published in: Breast Cancer Research and Treatment | Issue 1/2019

Login to get access

Abstract

Purpose

To identify a lncRNA signature to predict survival of breast cancer (BRCA) patients.

Methods

A total of 1222 BRCA case and control datasets were downloaded from the TCGA database. The weighted gene co-expression network analysis of differentially expressed mRNAs was performed to generate the modules associated with BRCA overall survival status and further construct a hub on competing endogenous RNA (ceRNA) network. LncRNA signatures for predicting survival of BRCA patients were generated using univariate survival analyses and a multivariate Cox hazard model analysis and validated and characterized for prognostic performance measured using receiver operating characteristic (ROC) curves.

Results

A prognostic score model of eight lncRNAs signature was identified as Prognostic score = (0.121 × EXPAC007731.1) + (0.108 × EXPAL513123.1) + (0.105 × EXPC10orf126) + (0.065 × EXPWT1-AS) + (− 0.126 × EXPADAMTS9-AS1) + (− 0.130 × EXPSRGAP3-AS2) + (0.116 × EXPTLR8-AS1) + (0.060 × EXPHOTAIR) with median score 1.088. Higher scores predicted higher risk. The lncRNAs signature was an independent prognostic factor associated with overall survival. The area under the ROC curves (AUC) of the signature was 0.979, 0.844, 0.99 and 0.997 by logistic regression, support vector machine, decision tree and random forest models, respectively, and the AUCs in predicting 1- to 10-year survival were between 0.656 and 0.748 in the test dataset from TCGA database.

Conclusions

The eight-lncRNA signature could serve as an independent biomarker for prediction of overall survival of BRCA. The lncRNA-miRNA-mRNA ceRNA network is a good tool to identify lncRNAs that is correlated with overall survival of BRCA.
Appendix
Available only for authorised users
Literature
1.
DeSantis CE, Ma J, Goding Sauer A, Newman LA, Jemal A (2017) Breast cancer statistics, 2017, racial disparity in mortality by state. CA 67(6):439–448
2.
Li G, Hu J, Hu G (2017) Biomarker studies in early detection and prognosis of breast cancer. Adv Exp Med Biol 1026:27–39PubMedCrossRef
3.
Kaklamani V (2006) A genetic signature can predict prognosis and response to therapy in breast cancer: oncotype DX. Expert Rev Mol Diagn 6(6):803–809PubMedCrossRef
4.
Mook S, Schmidt MK, Weigelt B, Kreike B, Eekhout I, van de Vijver MJ, Glas AM, Floore A, Rutgers EJ, van ‘t Veer LJ (2010) The 70-gene prognosis signature predicts early metastasis in breast cancer patients between 55 and 70 years of age. Ann Oncol 21(4):717–722PubMedCrossRef
5.
Bueno-de-Mesquita JM, Linn SC, Keijzer R, Wesseling J, Nuyten DS, van Krimpen C, Meijers C, de Graaf PW, Bos MM, Hart AA et al (2009) Validation of 70-gene prognosis signature in node-negative breast cancer. Breast Cancer Res Treat 117(3):483–495PubMedCrossRef
6.
Weigelt B, Hu Z, He X, Livasy C, Carey LA, Ewend MG, Glas AM, Perou CM, van ‘t Veer LJ (2005) Molecular portraits and 70-gene prognosis signature are preserved throughout the metastatic process of breast cancer. Cancer Res 65(20):9155–9158PubMedCrossRef
7.
Kondo M, Hoshi SL, Ishiguro H, Toi M (2012) Economic evaluation of the 70-gene prognosis-signature (MammaPrint(R)) in hormone receptor-positive, lymph node-negative, human epidermal growth factor receptor type 2-negative early stage breast cancer in Japan. Breast Cancer Res Treat 133(2):759–768PubMedCrossRef
8.
Hironaka-Mitsuhashi A, Matsuzaki J, Takahashi RU, Yoshida M, Nezu Y, Yamamoto Y, Shiino S, Kinoshita T, Ushijima T, Hiraoka N et al (2017) A tissue microRNA signature that predicts the prognosis of breast cancer in young women. PLoS ONE 12(11):e0187638PubMedPubMedCentralCrossRef
9.
Zhou J, Liu M, Chen Y, Xu S, Guo Y, Zhao L (2019) Cucurbitacin B suppresses proliferation of pancreatic cancer cells by ceRNA: Effect of miR-146b-5p and lncRNA-AFAP1-AS1. J Cell Physiol 234(4):4655–4667PubMedCrossRef
10.
Dianat-Moghadam H, Heydarifard M, Jahanban-Esfahlan R, Panahi Y, Hamishehkar H, Pouremamali F, Rahbarghazi R, Nouri M (2018) Cancer stem cells-emanated therapy resistance: implications for liposomal drug delivery systems. J Control Release 288:62–83PubMedCrossRef
11.
Torres-Garcia W, Domenech M (2017) Hedgehog-mesenchyme gene signature identifies bi-modal prognosis in luminal and basal breast cancer sub-types. Mol Biosyst 13(12):2615–2624PubMedPubMedCentralCrossRef
12.
13.
14.
An Y, Furber KL, Ji S (2017) Pseudogenes regulate parental gene expression via ceRNA network. J Cell Mol Med 21(1):185–192PubMedCrossRef
15.
16.
Zhou S, Wang L, Yang Q, Liu H, Meng Q, Jiang L, Wang S, Jiang W (2018) Systematical analysis of lncRNA-mRNA competing endogenous RNA network in breast cancer subtypes. Breast Cancer Res Treat 169(2):267–275PubMedCrossRef
17.
Zheng L, Zhang Z, Zhang S, Guo Q, Zhang F, Gao L, Ni H, Guo X, Xiang C, Xi T (2018) RNA binding protein RNPC1 inhibits breast cancer cell metastasis via activating STARD13-correlated ceRNA network. Mol Pharm 15(6):2123–2132PubMedCrossRef
18.
19.
Yuan N, Zhang G, Bie F, Ma M, Ma Y, Jiang X, Wang Y, Hao X (2017) Integrative analysis of lncRNAs and miRNAs with coding RNAs associated with ceRNA crosstalk network in triple negative breast cancer. Onco Targets Ther 10:5883–5897PubMedPubMedCentralCrossRef
20.
Li C, Zheng L, Xin Y, Tan Z, Zhang Y, Meng X, Wang Z, Xi T (2017) The competing endogenous RNA network of CYP4Z1 and pseudogene CYP4Z2P exerts an anti-apoptotic function in breast cancer. FEBS Lett 591(7):991–1000PubMedCrossRef
21.
Wang Z, Jensen MA, Zenklusen JC (2016) A practical guide to the cancer genome atlas (TCGA). Methods Mol Biol 1418:111–141PubMedCrossRef
22.
Tomczak K, Czerwinska P, Wiznerowicz M (2015) The cancer genome atlas (TCGA): an immeasurable source of knowledge. Contemp Oncol (Pozn) 19(1A):A68–A77
23.
Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinform 9:559CrossRef
24.
Zhang B, Horvath S (2005) A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol 4:17CrossRef
25.
26.
Harris MA, Clark J, Ireland A, Lomax J, Ashburner M, Foulger R, Eilbeck K, Lewis S, Marshall B, Mungall C et al (2004) The gene ontology (GO) database and informatics resource. Nucleic Acids Res 32(Database issue):D258–D261PubMed
27.
28.
Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP et al (2015) STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res 43:D447–D452CrossRefPubMed
29.
Cline MS, Smoot M, Cerami E, Kuchinsky A, Landys N, Workman C, Christmas R, Avila-Campilo I, Creech M, Gross B et al (2007) Integration of biological networks and gene expression data using cytoscape. Nat Protoc 2(10):2366–2382PubMedPubMedCentralCrossRef
30.
Chou CH, Shrestha S, Yang CD, Chang NW, Lin YL, Liao KW, Huang WC, Sun TH, Tu SJ, Lee WH et al (2018) miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res 46(D1):D296–D302PubMedCrossRef
31.
Ding K, Li W, Zou Z, Zou X, Wang C (2014) CCNB1 is a prognostic biomarker for ER+ breast cancer. Med Hypotheses 83(3):359–364PubMedCrossRef
32.
Feng W, Li HC, Xu K, Chen YF, Pan LY, Mei Y, Cai H, Jiang YM, Chen T, Feng DX (2016) SHCBP1 is over-expressed in breast cancer and is important in the proliferation and apoptosis of the human malignant breast cancer cell line. Gene 587(1):91–97PubMedCrossRef
33.
Alshareeda AT, Negm OH, Green AR, Nolan CC, Tighe P, Albarakati N, Sultana R, Madhusudan S, Ellis IO, Rakha EA (2015) KPNA2 is a nuclear export protein that contributes to aberrant localisation of key proteins and poor prognosis of breast cancer. Br J Cancer 112(12):1929–1937PubMedPubMedCentralCrossRef
34.
Tormo E, Adam-Artigues A, Ballester S, Pineda B, Zazo S, Gonzalez-Alonso P, Albanell J, Rovira A, Rojo F, Lluch A et al (2017) The role of miR-26a and miR-30b in HER2+ breast cancer trastuzumab resistance and regulation of the CCNE2 gene. Sci Rep 7:41309PubMedPubMedCentralCrossRef
35.
Pegoraro S, Ros G, Ciani Y, Sgarra R, Piazza S, Manfioletti G (2015) A novel HMGA1-CCNE2-YAP axis regulates breast cancer aggressiveness. Oncotarget 6(22):19087–19101PubMedPubMedCentralCrossRef
36.
Taghavi A, Akbari ME, Hashemi-Bahremani M, Nafissi N, Khalilnezhad A, Poorhosseini SM, Hashemi-Gorji F, Yassaee VR (2016) Gene expression profiling of the 8q22-24 position in human breast cancer: TSPYL5, MTDH, ATAD2 and CCNE2 genes are implicated in oncogenesis, while WISP1 and EXT1 genes may predict a risk of metastasis. Oncol Lett 12(5):3845–3855PubMedPubMedCentralCrossRef
37.
Klopocki E, Kristiansen G, Wild PJ, Klaman I, Castanos-Velez E, Singer G, Stohr R, Simon R, Sauter G, Leibiger H et al (2004) Loss of SFRP1 is associated with breast cancer progression and poor prognosis in early stage tumors. Int J Oncol 25(3):641–649PubMed
38.
Bernemann C, Hulsewig C, Ruckert C, Schafer S, Blumel L, Hempel G, Gotte M, Greve B, Barth PJ, Kiesel L et al (2014) Influence of secreted frizzled receptor protein 1 (SFRP1) on neoadjuvant chemotherapy in triple negative breast cancer does not rely on WNT signaling. Mol Cancer 13:174PubMedPubMedCentralCrossRef
39.
Xiao C, Wu CH, Hu HZ (2016) LncRNA UCA1 promotes epithelial-mesenchymal transition (EMT) of breast cancer cells via enhancing Wnt/beta-catenin signaling pathway. Eur Rev Med Pharmacol Sci 20(13):2819–2824PubMed
40.
Deng J, Yang M, Jiang R, An N, Wang X, Liu B (2017) Long non-coding RNA HOTAIR regulates the proliferation, Self-renewal capacity, tumor formation and migration of the cancer stem-like cell (CSC) subpopulation enriched from breast cancer cells. PLoS ONE 12(1):e0170860PubMedPubMedCentralCrossRef
41.
Xue X, Yang YA, Zhang A, Fong KW, Kim J, Song B, Li S, Zhao JC, Yu J (2016) LncRNA HOTAIR enhances ER signaling and confers tamoxifen resistance in breast cancer. Oncogene 35(21):2746–2755PubMedCrossRef
42.
Sorensen KP, Thomassen M, Tan Q, Bak M, Cold S, Burton M, Larsen MJ, Kruse TA (2013) Long non-coding RNA HOTAIR is an independent prognostic marker of metastasis in estrogen receptor-positive primary breast cancer. Breast Cancer Res Treat 142(3):529–536PubMedCrossRef
43.
Pan Y, Zhang J, Fu H, Shen L (2016) miR-144 functions as a tumor suppressor in breast cancer through inhibiting ZEB1/2-mediated epithelial mesenchymal transition process. Onco Targets Ther 9:6247–6255PubMedPubMedCentralCrossRef
44.
Yin Y, Cai J, Meng F, Sui C, Jiang Y (2018) MiR-144 suppresses proliferation, invasion, and migration of breast cancer cells through inhibiting CEP55. Cancer Biol Ther 19(4):306–315PubMedPubMedCentralCrossRef
45.
Ye ZB, Ma G, Zhao YH, Xiao Y, Zhan Y, Jing C, Gao K, Liu ZH, Yu SJ (2015) miR-429 inhibits migration and invasion of breast cancer cells in vitro. Int J Oncol 46(2):531–538PubMedCrossRef
46.
Li D, Wang H, Song H, Xu H, Zhao B, Wu C, Hu J, Wu T, Xie D, Zhao J et al (2017) The microRNAs miR-200b-3p and miR-429-5p target the LIMK1/CFL1 pathway to inhibit growth and motility of breast cancer cells. Oncotarget 8(49):85276–85289PubMedPubMedCentral
47.
Wang C, Ju H, Shen C, Tong Z (2015) miR-429 mediates delta-tocotrienol-induced apoptosis in triple-negative breast cancer cells by targeting XIAP. Int J Clin Exp Med 8(9):15648–15656PubMedPubMedCentral
48.
Olgun G, Sahin O, Tastan O (2018) Discovering lncRNA mediated sponge interactions in breast cancer molecular subtypes. BMC Genom 19(1):650CrossRef
49.
Chen J, Xu J, Li Y, Zhang J, Chen H, Lu J, Wang Z, Zhao X, Xu K, Li X et al (2017) Competing endogenous RNA network analysis identifies critical genes among the different breast cancer subtypes. Oncotarget 8(6):10171–10184PubMed
50.
Xiao B, Zhang W, Chen L, Hang J, Wang L, Zhang R, Liao Y, Chen J, Ma Q, Sun Z et al (2018) Analysis of the miRNA-mRNA-lncRNA network in human estrogen receptor-positive and estrogen receptor-negative breast cancer based on TCGA data. Gene 658:28–35PubMedCrossRef
51.
Wu Q, Guo L, Jiang F, Li L, Li Z, Chen F (2015) Analysis of the miRNA-mRNA-lncRNA networks in ER + and ER- breast cancer cell lines. J Cell Mol Med 19(12):2874–2887PubMedPubMedCentralCrossRef
52.
Paci P, Colombo T, Farina L (2014) Computational analysis identifies a sponge interaction network between long non-coding RNAs and messenger RNAs in human breast cancer. BMC Syst Biol 8:83PubMedPubMedCentralCrossRef
53.
Han L, Zhang HC, Li L, Li CX, Di X, Qu X (2018) Downregulation of long noncoding RNA HOTAIR and EZH2 Induces apoptosis and inhibits proliferation, invasion, and migration of human breast cancer cells. Cancer Biother Radiopharm 33(6):241–251PubMedCrossRef
54.
Zhao W, Geng D, Li S, Chen Z, Sun M (2018) LncRNA HOTAIR influences cell growth, migration, invasion, and apoptosis via the miR-20a-5p/HMGA2 axis in breast cancer. Cancer Med 7(3):842–855PubMedPubMedCentralCrossRef
55.
Ozes AR, Miller DF, Ozes ON, Fang F, Liu Y, Matei D, Huang T, Nephew KP (2016) NF-kappaB-HOTAIR axis links DNA damage response, chemoresistance and cellular senescence in ovarian cancer. Oncogene 35(41):5350–5361PubMedPubMedCentralCrossRef
56.
Battistelli C, Cicchini C, Santangelo L, Tramontano A, Grassi L, Gonzalez FJ, de Nonno V, Grassi G, Amicone L, Tripodi M (2017) The snail repressor recruits EZH2 to specific genomic sites through the enrollment of the lncRNA HOTAIR in epithelial-to-mesenchymal transition. Oncogene 36(7):942–955PubMedCrossRef
57.
Gupta RA, Shah N, Wang KC, Kim J, Horlings HM, Wong DJ, Tsai MC, Hung T, Argani P, Rinn JL et al (2010) Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature 464(7291):1071–1076PubMedPubMedCentralCrossRef
58.
Kaneuchi M, Sasaki M, Tanaka Y, Shiina H, Yamada H, Yamamoto R, Sakuragi N, Enokida H, Verma M, Dahiya R (2005) WT1 and WT1-AS genes are inactivated by promoter methylation in ovarian clear cell adenocarcinoma. Cancer 104(9):1924–1930PubMedCrossRef
59.
Du T, Zhang B, Zhang S, Jiang X, Zheng P, Li J, Yan M, Zhu Z, Liu B (2016) Decreased expression of long non-coding RNA WT1-AS promotes cell proliferation and invasion in gastric cancer. Biochim Biophys Acta 1862(1):12–19PubMedCrossRef
60.
Lv L, Chen G, Zhou J, Li J, Gong J (2015) WT1-AS promotes cell apoptosis in hepatocellular carcinoma through down-regulating of WT1. J Exp Clin Cancer Res 34:119PubMedPubMedCentralCrossRef
61.
Wang H, Fu Z, Dai C, Cao J, Liu X, Xu J, Lv M, Gu Y, Zhang J, Hua X et al (2016) LncRNAs expression profiling in normal ovary, benign ovarian cyst and malignant epithelial ovarian cancer. Sci Rep 6:38983PubMedPubMedCentralCrossRef
62.
Zhu N, Hou J, Wu Y, Liu J, Li G, Zhao W, Ma G, Chen B, Song Y (2018) Integrated analysis of a competing endogenous RNA network reveals key lncRNAs as potential prognostic biomarkers for human bladder cancer. Medicine (Baltimore) 97(35):e11887CrossRef
63.
Xing Y, Zhao Z, Zhu Y, Zhao L, Zhu A, Piao D (2018) Comprehensive analysis of differential expression profiles of mRNAs and lncRNAs and identification of a 14-lncRNA prognostic signature for patients with colon adenocarcinoma. Oncol Rep 39(5):2365–2375PubMed
64.
Li Z, Yao Q, Zhao S, Wang Y, Li Y, Wang Z (2017) Comprehensive analysis of differential co-expression patterns reveal transcriptional dysregulation mechanism and identify novel prognostic lncRNAs in esophageal squamous cell carcinoma. Onco Targets Ther 10:3095–3105PubMedPubMedCentralCrossRef
65.
Yang Z, Li H, Wang Z, Yang Y, Niu J, Liu Y, Sun Z, Yin C (2018) Microarray expression profile of long non-coding RNAs in human lung adenocarcinoma. Thorac Cancer 9(10):1312–1322PubMedPubMedCentralCrossRef
66.
Yu F, Quan F, Xu J, Zhang Y, Xie Y, Zhang J, Lan Y, Yuan H, Zhang H, Cheng S et al (2018) Breast cancer prognosis signature: linking risk stratification to disease subtypes. Brief Bioinform
Metadata
Title
An eight-lncRNA signature predicts survival of breast cancer patients: a comprehensive study based on weighted gene co-expression network analysis and competing endogenous RNA network
Authors
Min Sun
Di Wu
Ke Zhou
Heng Li
Xingrui Gong
Qiong Wei
Mengyu Du
Peijie Lei
Jin Zha
Hongrui Zhu
Xinsheng Gu
Dong Huang
Publication date
01-05-2019
Publisher
Springer US
Published in
Breast Cancer Research and Treatment / Issue 1/2019
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI
https://doi.org/10.1007/s10549-019-05147-6

Other articles of this Issue 1/2019

Breast Cancer Research and Treatment 1/2019 Go to the issue

Clinical trial

Retrospectively validating the results of the ACOSOG Z0011 trial in a large Asian Z0011-eligible cohort

Clinical trial

Efficacy of self-administered complex decongestive therapy on breast cancer-related lymphedema: a single-blind randomized controlled trial

Preclinical study

Revealing clonality and subclonality of driver genes for clinical survival benefits in breast cancer

Clinical trial

Dissecting the predictive value of MAPK/AKT/estrogen-receptor phosphorylation axis in primary breast cancer to treatment response for tamoxifen over exemestane: a Translational Report of the Intergroup Exemestane Study (IES)—PathIES

Epidemiology

Cardiac outcomes of trastuzumab therapy in patients with HER2-positive breast cancer and reduced left ventricular ejection fraction

Clinical trial

Factors influencing the use of extended adjuvant endocrine therapy
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine
Image Credits