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 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
Breast Cancer Research
Published in: Breast Cancer Research 1/2020

01-12-2020 | Breast Cancer | Research article

Secreted breast tumor interstitial fluid microRNAs and their target genes are associated with triple-negative breast cancer, tumor grade, and immune infiltration

Authors: Thilde Terkelsen, Francesco Russo, Pavel Gromov, Vilde Drageset Haakensen, Søren Brunak, Irina Gromova, Anders Krogh, Elena Papaleo

Published in: Breast Cancer Research | Issue 1/2020

Login to get access

Abstract

Background

Studies on tumor-secreted microRNAs point to a functional role of these in cellular communication and reprogramming of the tumor microenvironment. Uptake of tumor-secreted microRNAs by neighboring cells may result in the silencing of mRNA targets and, in turn, modulation of the transcriptome. Studying miRNAs externalized from tumors could improve cancer patient diagnosis and disease monitoring and help to pinpoint which miRNA-gene interactions are central for tumor properties such as invasiveness and metastasis.

Methods

Using a bioinformatics approach, we analyzed the profiles of secreted tumor and normal interstitial fluid (IF) microRNAs, from women with breast cancer (BC). We carried out differential abundance analysis (DAA), to obtain miRNAs, which were enriched or depleted in IFs, from patients with different clinical traits. Subsequently, miRNA family enrichment analysis was performed to assess whether any families were over-represented in the specific sets. We identified dysregulated genes in tumor tissues from the same cohort of patients and constructed weighted gene co-expression networks, to extract sets of co-expressed genes and co-abundant miRNAs. Lastly, we integrated miRNAs and mRNAs to obtain interaction networks and supported our findings using prediction tools and cancer gene databases.

Results

Network analysis showed co-expressed genes and miRNA regulators, associated with tumor lymphocyte infiltration. All of the genes were involved in immune system processes, and many had previously been associated with cancer immunity. A subset of these, BTLA, CXCL13, IL7R, LAMP3, and LTB, was linked to the presence of tertiary lymphoid structures and high endothelial venules within tumors. Co-abundant tumor interstitial fluid miRNAs within this network, including miR-146a and miR-494, were annotated as negative regulators of immune-stimulatory responses. One co-expression network encompassed differences between BC subtypes. Genes differentially co-expressed between luminal B and triple-negative breast cancer (TNBC) were connected with sphingolipid metabolism and predicted to be co-regulated by miR-23a. Co-expressed genes and TIF miRNAs associated with tumor grade were BTRC, CHST1, miR-10a/b, miR-107, miR-301a, and miR-454.

Conclusion

Integration of IF miRNAs and mRNAs unveiled networks associated with patient clinicopathological traits, and underlined molecular mechanisms, specific to BC sub-groups. Our results highlight the benefits of an integrative approach to biomarker discovery, placing secreted miRNAs within a biological context.
Appendix
Available only for authorised users
Literature
1.
Walters S, Maringe C, Butler J, Rachet B, Barrett-Lee P, Bergh J, et al. Breast cancer survival and stage at diagnosis in Australia, Canada, Denmark, Norway, Sweden and the UK, 2000-2007: a population-based study. Br J Cancer. 2013;108(5):1195–208.PubMedPubMedCentral
2.
Ali HR, Provenzano E, Dawson SJ, Blows FM, Liu B, Shah M, et al. Association between CD8+ T-cell infiltration and breast cancer survival in 12,439 patients. Ann Oncol. 2014;25(8):1536–43.PubMed
3.
DeSantis CE, Fedewa SA, Goding Sauer A, Kramer JL, Smith RA, Jemal A. Breast cancer statistics, 2015: convergence of incidence rates between black and white women. CA Cancer J Clin. 2016;66(1):31–42.PubMed
4.
Appierto V, Di Cosimo S, Reduzzi C, Pala V, Cappelletti V, Daidone MG. How to study and overcome tumor heterogeneity with circulating biomarkers: the breast cancer case. Semin Cancer Biol. 2017;44:106–16.PubMed
5.
6.
Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–52.PubMed
7.
Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27(8):1160–7.PubMedPubMedCentral
8.
Fallahpour S, Navaneelan T, De P, Borgo A. Breast cancer survival by molecular subtype: a population-based analysis of cancer registry data. CMAJ Open. 2017;5(3):E734–E9.PubMedPubMedCentral
9.
Howlader N, Cronin KA, Kurian AW, Andridge R. Differences in breast cancer survival by molecular subtypes in the United States. Cancer Epidemiol Biomark Prev. 2018;27(6):619–26.
10.
Cortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet. 2014;384(9938):164–72.PubMed
11.
Prat A, Adamo B, Cheang MC, Anders CK, Carey LA, Perou CM. Molecular characterization of basal-like and non-basal-like triple-negative breast cancer. Oncologist. 2013;18(2):123–33.PubMedPubMedCentral
12.
Kodahl AR, Lyng MB, Binder H, Cold S, Gravgaard K, Knoop AS, et al. Novel circulating microRNA signature as a potential non-invasive multi-marker test in ER-positive early-stage breast cancer: a case control study. Mol Oncol. 2014;8(5):874–83.PubMedPubMedCentral
13.
Schwarzenbach H, Nishida N, Calin GA, Pantel K. Clinical relevance of circulating cell-free microRNAs in cancer. Nat Rev Clin Oncol. 2014;11(3):145–56.PubMed
14.
Matsuzaki J, Ochiya T. Circulating microRNAs and extracellular vesicles as potential cancer biomarkers: a systematic review. Int J Clin Oncol. 2017;22(3):413–20.PubMed
15.
Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci U S A. 2008;105(30):10513–8.PubMedPubMedCentral
16.
Wang J, Zhang KY, Liu SM, Sen S. Tumor-associated circulating microRNAs as biomarkers of cancer. Molecules. 2014;19(2):1912–38.PubMedPubMedCentral
17.
Chen X, Liang H, Zhang J, Zen K, Zhang CY. Secreted microRNAs: a new form of intercellular communication. Trends Cell Biol. 2012;22(3):125–32.PubMed
18.
Turchinovich A, Samatov TR, Tonevitsky AG, Burwinkel B. Circulating miRNAs: cell-cell communication function? Front Genet. 2013;4:119.PubMedPubMedCentral
19.
20.
Aleckovic M, Kang Y. Regulation of cancer metastasis by cell-free miRNAs. Biochim Biophys Acta. 2015;1855(1):24–42.PubMed
21.
Chen TS, Lai RC, Lee MM, Choo AB, Lee CN, Lim SK. Mesenchymal stem cell secretes microparticles enriched in pre-microRNAs. Nucleic Acids Res. 2010;38(1):215–24.PubMed
22.
Melo SA, Sugimoto H, O’Connell JT, Kato N, Villanueva A, Vidal A, et al. Cancer exosomes perform cell-independent microRNA biogenesis and promote tumorigenesis. Cancer Cell. 2014;26(5):707–21.PubMedPubMedCentral
23.
Pigati L, Yaddanapudi SC, Iyengar R, Kim DJ, Hearn SA, Danforth D, et al. Selective release of microRNA species from normal and malignant mammary epithelial cells. PLoS One. 2010;5(10):e13515.PubMedPubMedCentral
24.
Singh R, Pochampally R, Watabe K, Lu Z, Mo YY. Exosome-mediated transfer of miR-10b promotes cell invasion in breast cancer. Mol Cancer. 2014;13:256.PubMedPubMedCentral
25.
Arroyo JD, Chevillet JR, Kroh EM, Ruf IK, Pritchard CC, Gibson DF, et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc Natl Acad Sci U S A. 2011;108(12):5003–8.PubMedPubMedCentral
26.
Vickers KC, Palmisano BT, Shoucri BM, Shamburek RD, Remaley AT. MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nat Cell Biol. 2011;13(4):423–33.PubMedPubMedCentral
27.
28.
29.
Hamilton MP, Rajapakshe K, Hartig SM, Reva B, McLellan MD, Kandoth C, et al. Identification of a pan-cancer oncogenic microRNA superfamily anchored by a central core seed motif. Nat Commun. 2013;4:2730.PubMed
30.
Le MT, Hamar P, Guo C, Basar E, Perdigao-Henriques R, Balaj L, et al. miR-200-containing extracellular vesicles promote breast cancer cell metastasis. J Clin Invest. 2014;124(12):5109–28.PubMedPubMedCentral
31.
Fong MY, Zhou W, Liu L, Alontaga AY, Chandra M, Ashby J, et al. Breast-cancer-secreted miR-122 reprograms glucose metabolism in premetastatic niche to promote metastasis. Nat Cell Biol. 2015;17(2):183–94.PubMedPubMedCentral
32.
Yotsukura S, Mamitsuka H. Evaluation of serum-based cancer biomarkers: a brief review from a clinical and computational viewpoint. Crit Rev Oncol Hematol. 2015;93(2):103–15.PubMed
33.
Tiberio P, Callari M, Angeloni V, Daidone MG, Appierto V. Challenges in using circulating miRNAs as cancer biomarkers. Biomed Res Int. 2015;2015:731479.PubMedPubMedCentral
34.
Surinova S, Schiess R, Huttenhain R, Cerciello F, Wollscheid B, Aebersold R. On the development of plasma protein biomarkers. J Proteome Res. 2011;10(1):5–16.PubMed
35.
Drucker E, Krapfenbauer K. Pitfalls and limitations in translation from biomarker discovery to clinical utility in predictive and personalised medicine. EPMA J. 2013;4(1):7.PubMedPubMedCentral
36.
Hanahan D, Coussens LM. Accessories to the crime: functions of cells recruited to the tumor microenvironment. Cancer Cell. 2012;21(3):309–22.PubMed
37.
Gromov P, Gromova I. Characterization of the tumor secretome from tumor interstitial fluid (TIF). Methods Mol Biol. 2016;1459:231–47.PubMed
38.
Gromov P, Gromova I, Olsen CJ, Timmermans-Wielenga V, Talman ML, Serizawa RR, et al. Tumor interstitial fluid - a treasure trove of cancer biomarkers. Biochim Biophys Acta. 2013;1834(11):2259–70.PubMed
39.
Wagner M, Wiig H. Tumor interstitial fluid formation, characterization, and clinical implications. Front Oncol. 2015;5:115.PubMedPubMedCentral
40.
Shekhar MP, Werdell J, Santner SJ, Pauley RJ, Tait L. Breast stroma plays a dominant regulatory role in breast epithelial growth and differentiation: implications for tumor development and progression. Cancer Res. 2001;61(4):1320–6.PubMed
41.
Ma XJ, Dahiya S, Richardson E, Erlander M, Sgroi DC. Gene expression profiling of the tumor microenvironment during breast cancer progression. Breast Cancer Res. 2009;11(1):R7.PubMedPubMedCentral
42.
Espinoza JA, Jabeen S, Batra R, Papaleo E, Haakensen V, Timmermans Wielenga V, et al. Cytokine profiling of tumor interstitial fluid of the breast and its relationship with lymphocyte infiltration and clinicopathological characteristics. Oncoimmunology. 2016;5(12):e1248015.PubMedPubMedCentral
43.
Salgado R, Denkert C, Demaria S, Sirtaine N, Klauschen F, Pruneri G, et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann Oncol. 2015;26(2):259–71.PubMed
44.
Denkert C, von Minckwitz G, Darb-Esfahani S, Lederer B, Heppner BI, Weber KE, et al. Tumour-infiltrating lymphocytes and prognosis in different subtypes of breast cancer: a pooled analysis of 3771 patients treated with neoadjuvant therapy. Lancet Oncol. 2018;19(1):40–50.PubMed
45.
Ghebeh H, Mohammed S, Al-Omair A, Qattan A, Lehe C, Al-Qudaihi G, et al. The B7-H1 (PD-L1) T lymphocyte-inhibitory molecule is expressed in breast cancer patients with infiltrating ductal carcinoma: correlation with important high-risk prognostic factors. Neoplasia. 2006;8(3):190–8.PubMedPubMedCentral
46.
Muenst S, Soysal SD, Gao F, Obermann EC, Oertli D, Gillanders WE. The presence of programmed death 1 (PD-1)-positive tumor-infiltrating lymphocytes is associated with poor prognosis in human breast cancer. Breast Cancer Res Treat. 2013;139(3):667–76.PubMed
47.
Tang F, Zheng P. Tumor cells versus host immune cells: whose PD-L1 contributes to PD-1/PD-L1 blockade mediated cancer immunotherapy? Cell Biosci. 2018;8:34.PubMedPubMedCentral
48.
Fridman WH, Pages F, Sautes-Fridman C, Galon J. The immune contexture in human tumours: impact on clinical outcome. Nat Rev Cancer. 2012;12(4):298–306.PubMed
49.
Halvorsen AR, Helland A, Gromov P, Wielenga VT, Talman MM, Brunner N, et al. Profiling of microRNAs in tumor interstitial fluid of breast tumors - a novel resource to identify biomarkers for prognostic classification and detection of cancer. Mol Oncol. 2017;11(2):220–34.PubMed
50.
Jabeen S, Espinoza JA, Torland LA, Zucknick M, Kumar S, Haakensen VD, et al. Noninvasive profiling of serum cytokines in breast cancer patients and clinicopathological characteristics. Oncoimmunology. 2019;8(2):e1537691.PubMed
51.
Esposito A, Criscitiello C, Curigliano G. Highlights from the 14th St Gallen International Breast Cancer Conference 2015 in Vienna: dealing with classification, prognostication, and prediction refinement to personalize the treatment of patients with early breast cancer. Ecancermedicalscience. 2015;9:518.PubMedPubMedCentral
52.
Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics. 2007;8(1):118–27.PubMed
53.
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47.PubMedPubMedCentral
54.
Wickham H. ggplot2: elegant graphics for data analysis; 2016.
55.
Maechler M, Rousseeuw P, Struyf A, Hubert M, Hornik K, Studer M, Roudier P, Gonzalez J. cluster: cluster analysis basics and extensions. R package version 201; 2016.
56.
Tibshirani R, Walther G, Hastie T. Estimating the number of clusters in a data set via the gap statistic. J R Stat Soc Ser B (Statistical Methodology). 2001;63(2):411–23.
57.
Murtagh FaL P. Ward’s hierarchical agglomerative clustering method: which algorithms implement Ward’s criterion? J Classif. 2014;31(3):274–95.
58.
Agarwal V, Bell GW, Nam JW, Bartel DP. Predicting effective microRNA target sites in mammalian mRNAs. Elife. 2015;4:274–95.
59.
Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008;9:559.PubMedPubMedCentral
60.
Li T, Wernersson R, Hansen RB, Horn H, Mercer J, Slodkowicz G, Workman CT, Rigina O, Rapacki K, Stærfeldt HH, Brunak S, Jensen TS, Lage K. A scored human protein–protein interaction network to catalyze genomic interpretation. Nat Methods. 2017;14(1):61.PubMed
61.
Li JR, Tong CY, Sung TJ, Kang TY, Zhou XJ, Liu CC. CMEP: a database for circulating microRNA expression profiling. Bioinformatics. 2019;35:3127–32.
62.
Yang Z, Wu L, Wang A, Tang W, Zhao Y, Zhao H, et al. dbDEMC 2.0: updated database of differentially expressed miRNAs in human cancers. Nucleic Acids Res. 2017;45(D1):D812–D8.PubMed
63.
Xie B, Ding Q, Han H, Wu D. miRCancer: a microRNA-cancer association database constructed by text mining on literature. Bioinformatics. 2013;29(5):638–44.PubMed
64.
Paladini L, Fabris L, Bottai G, Raschioni C, Calin GA, Santarpia L. Targeting microRNAs as key modulators of tumor immune response. J Exp Clin Cancer Res. 2016;35:103.PubMedPubMedCentral
65.
Mansoori B, Mohammadi A, Shirjang S, Baradaran B. MicroRNAs in the diagnosis and treatment of cancer. Immunol Investig. 2017;46(8):880–97.
66.
Curtale G. MiRNAs at the crossroads between innate immunity and cancer: focus on macrophages. Cells. 2018;7(2).
67.
Chou CH, Shrestha S, Yang CD, Chang NW, Lin YL, Liao KW, et al. miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res. 2018;46(D1):D296–302.PubMed
68.
Paraskevopoulou MD, Georgakilas G, Kostoulas N, Vlachos IS, Vergoulis T, Reczko M, et al. DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows. Nucleic Acids Res. 2013;41(Web Server issue):W169–73.PubMedPubMedCentral
69.
Tsang JS, Ebert MS, van Oudenaarden A. Genome-wide dissection of microRNA functions and cotargeting networks using gene set signatures. Mol Cell. 2010;38(1):140–53.PubMedPubMedCentral
70.
Krek A, Grun D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, et al. Combinatorial microRNA target predictions. Nat Genet. 2005;37(5):495–500.PubMed
71.
Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E. The role of site accessibility in microRNA target recognition. Nat Genet. 2007;39(10):1278–84.PubMed
72.
Miranda KC, Huynh T, Tay Y, Ang YS, Tam WL, Thomson AM, et al. A pattern-based method for the identification of microRNA binding sites and their corresponding heteroduplexes. Cell. 2006;126(6):1203–17.PubMed
73.
Liu W, Wang X. Prediction of functional microRNA targets by integrative modeling of microRNA binding and target expression data. Genome Biol. 2019;20(1):18.PubMedPubMedCentral
74.
Lu TP, Lee CY, Tsai MH, Chiu YC, Hsiao CK, Lai LC, et al. miRSystem: an integrated system for characterizing enriched functions and pathways of microRNA targets. PLoS One. 2012;7(8):e42390.PubMedPubMedCentral
75.
Tate JG, Bamford S, Jubb HC, Sondka Z, Beare DM, Bindal N, et al. COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Res. 2019;47(D1):D941–D7.PubMed
76.
Lever J, Zhao EY, Grewal J, Jones MR, Jones SJM. CancerMine: a literature-mined resource for drivers, oncogenes and tumor suppressors in cancer. Nat Methods. 2019;16(6):505–7.PubMed
77.
Rogers MF, Shihab HA, Mort M, Cooper DN, Gaunt TR, Campbell C. FATHMM-XF: accurate prediction of pathogenic point mutations via extended features. Bioinformatics. 2018;34(3):511–3.PubMed
78.
Ventura A, Young AG, Winslow MM, Lintault L, Meissner A, Erkeland SJ, et al. Targeted deletion reveals essential and overlapping functions of the miR-17 through 92 family of miRNA clusters. Cell. 2008;132(5):875–86.PubMedPubMedCentral
79.
Kamanu TK, Radovanovic A, Archer JA, Bajic VB. Exploration of miRNA families for hypotheses generation. Sci Rep. 2013;3:2940.PubMedPubMedCentral
80.
81.
Chang YY, Kuo WH, Hung JH, Lee CY, Lee YH, Chang YC, et al. Deregulated microRNAs in triple-negative breast cancer revealed by deep sequencing. Mol Cancer. 2015;14:36.PubMedPubMedCentral
82.
Oztemur Y, Bekmez T, Aydos A, Yulug IG, Bozkurt B, Dedeoglu BG. A ranking-based meta-analysis reveals let-7 family as a meta-signature for grade classification in breast cancer. PLoS One. 2015;10(5):e0126837.PubMedPubMedCentral
83.
Olive V, Jiang I, He L. mir-17-92, a cluster of miRNAs in the midst of the cancer network. Int J Biochem Cell Biol. 2010;42(8):1348–54.PubMedPubMedCentral
84.
Li M, Guan X, Sun Y, Mi J, Shu X, Liu F, et al. miR-92a family and their target genes in tumorigenesis and metastasis. Exp Cell Res. 2014;323(1):1–6.PubMed
85.
Ren R, Tyryshkin K, Graham CH, Koti M, Siemens DR. Comprehensive immune transcriptomic analysis in bladder cancer reveals subtype specific immune gene expression patterns of prognostic relevance. Oncotarget. 2017;8(41):70982–1001.PubMedPubMedCentral
86.
Guarnieri AL, Towers CG, Drasin DJ, Oliphant MUJ, Andrysik Z, Hotz TJ, et al. The miR-106b-25 cluster mediates breast tumor initiation through activation of NOTCH1 via direct repression of NEDD4L. Oncogene. 2018;37(28):3879–93.PubMedPubMedCentral
87.
Zhao F, Gong X, Liu A, Lv X, Hu B, Zhang H. Downregulation of Nedd4L predicts poor prognosis, promotes tumor growth and inhibits MAPK/ERK signal pathway in hepatocellular carcinoma. Biochem Biophys Res Commun. 2018;495(1):1136–43.PubMed
88.
89.
Schwab I, Nimmerjahn F. Intravenous immunoglobulin therapy: how does IgG modulate the immune system? Nat Rev Immunol. 2013;13(3):176–89.PubMed
90.
91.
Wang WT, Han C, Sun YM, Chen ZH, Fang K, Huang W, et al. Activation of the lysosome-associated membrane protein LAMP5 by DOT1L serves as a bodyguard for MLL fusion oncoproteins to evade degradation in leukemia. Clin Cancer Res. 2019;25(9):2795–808.PubMed
92.
Doane AS, Danso M, Lal P, Donaton M, Zhang L, Hudis C, et al. An estrogen receptor-negative breast cancer subset characterized by a hormonally regulated transcriptional program and response to androgen. Oncogene. 2006;25(28):3994–4008.PubMed
93.
Chen X, Iliopoulos D, Zhang Q, Tang Q, Greenblatt MB, Hatziapostolou M, et al. XBP1 promotes triple-negative breast cancer by controlling the HIF1alpha pathway. Nature. 2014;508(7494):103–7.PubMedPubMedCentral
94.
Sidiropoulos KG, White NM, Bui A, Ding Q, Boulos P, Pampalakis G, et al. Kallikrein-related peptidase 5 induces miRNA-mediated anti-oncogenic pathways in breast cancer. Oncoscience. 2014;1(11):709–24.PubMedPubMedCentral
95.
Santuario-Facio SK, Cardona-Huerta S, Perez-Paramo YX, Trevino V, Hernandez-Cabrera F, Rojas-Martinez A, et al. A new gene expression signature for triple negative breast cancer using frozen fresh tissue before neoadjuvant chemotherapy. Mol Med. 2017;23:101–11.PubMedPubMedCentral
96.
Yoshimaru T, Ono M, Bando Y, Chen YA, Mizuguchi K, Shima H, et al. A-kinase anchoring protein BIG3 coordinates oestrogen signalling in breast cancer cells. Nat Commun. 2017;8:15427.PubMedPubMedCentral
97.
Bouchard-Fortier A, Provencher L, Blanchette C, Diorio C. Prognostic and predictive value of low estrogen receptor expression in breast cancer. Curr Oncol. 2017;24(2):e106–e14.PubMedPubMedCentral
98.
Glynn RW, Miller N, Mahon S, Kerin MJ. Expression levels of HER2/neu and those of collocated genes at 17q12-21, in breast cancer. Oncol Rep. 2012;28(1):365–9.PubMed
99.
Sanchez Calle A, Kawamura Y, Yamamoto Y, Takeshita F, Ochiya T. Emerging roles of long non-coding RNA in cancer. Cancer Sci. 2018;109(7):2093–100.PubMedPubMedCentral
100.
Li J, Han L, Roebuck P, Diao L, Liu L, Yuan Y, et al. TANRIC: an interactive open platform to explore the function of lncRNAs in cancer. Cancer Res. 2015;75(18):3728–37.PubMedPubMedCentral
101.
Pian C, Zhang G, Chen Z, Chen Y, Zhang J, Yang T, et al. LncRNApred: classification of long non-oding RNAs and protein-coding transcripts by the Ensemble algorithm with a new hybrid feature. PLoS One. 2016;11(5):e0154567.PubMedPubMedCentral
102.
Zhang X, Li T, Wang J, Li J, Chen L, Liu C. Identification of cancer-related long non-coding RNAs using XGBoost with high accuracy. Front Genet. 2019;10:735.PubMedPubMedCentral
103.
Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45(D1):D362–D8.PubMed
104.
Akter S, Choi TG, Nguyen MN, Matondo A, Kim JH, Jo YH, et al. Prognostic value of a 92-probe signature in breast cancer. Oncotarget. 2015;6(17):15662–80.PubMedPubMedCentral
105.
Bastien RR, Rodriguez-Lescure A, Ebbert MT, Prat A, Munarriz B, Rowe L, et al. PAM50 breast cancer subtyping by RT-qPCR and concordance with standard clinical molecular markers. BMC Med Genet. 2012;5:44.
106.
Bernhardt SM, Dasari P, Walsh D, Townsend AR, Price TJ, Ingman WV. Hormonal modulation of breast cancer gene expression: implications for intrinsic subtyping in premenopausal women. Front Oncol. 2016;6:241.PubMedPubMedCentral
107.
Jiang G, Zhang S, Yazdanparast A, Li M, Pawar AV, Liu Y, et al. Comprehensive comparison of molecular portraits between cell lines and tumors in breast cancer. BMC Genomics. 2016;17(Suppl 7):525.PubMedPubMedCentral
108.
Heneghan HM, Miller N, Lowery AJ, Sweeney KJ, Newell J, Kerin MJ. Circulating microRNAs as novel minimally invasive biomarkers for breast cancer. Ann Surg. 2010;251(3):499–505.PubMed
109.
Eichelser C, Stuckrath I, Muller V, Milde-Langosch K, Wikman H, Pantel K, et al. Increased serum levels of circulating exosomal microRNA-373 in receptor-negative breast cancer patients. Oncotarget. 2014;5(20):9650–63.PubMedPubMedCentral
110.
Shin VY, Siu JM, Cheuk I, Ng EK, Kwong A. Circulating cell-free miRNAs as biomarker for triple-negative breast cancer. Br J Cancer. 2015;112(11):1751–9.PubMedPubMedCentral
111.
Sieuwerts AM, Mostert B, Bolt-de Vries J, Peeters D, de Jongh FE, Stouthard JM, et al. mRNA and microRNA expression profiles in circulating tumor cells and primary tumors of metastatic breast cancer patients. Clin Cancer Res. 2011;17(11):3600–18.PubMed
112.
Antolin S, Calvo L, Blanco-Calvo M, Santiago MP, Lorenzo-Patino MJ, Haz-Conde M, et al. Circulating miR-200c and miR-141 and outcomes in patients with breast cancer. BMC Cancer. 2015;15:297.PubMedPubMedCentral
113.
Kleivi Sahlberg K, Bottai G, Naume B, Burwinkel B, Calin GA, Borresen-Dale AL, et al. A serum microRNA signature predicts tumor relapse and survival in triple-negative breast cancer patients. Clin Cancer Res. 2015;21(5):1207–14.PubMed
114.
Zhang L, Xu Y, Jin X, Wang Z, Wu Y, Zhao D, et al. A circulating miRNA signature as a diagnostic biomarker for non-invasive early detection of breast cancer. Breast Cancer Res Treat. 2015;154(2):423–34.PubMed
115.
van Schooneveld E, Wouters MC, Van der Auwera I, Peeters DJ, Wildiers H, Van Dam PA, et al. Expression profiling of cancerous and normal breast tissues identifies microRNAs that are differentially expressed in serum from patients with (metastatic) breast cancer and healthy volunteers. Breast Cancer Res. 2012;14(1):R34.PubMedPubMedCentral
116.
Kedmi M, Ben-Chetrit N, Korner C, Mancini M, Ben-Moshe NB, Lauriola M, et al. EGF induces microRNAs that target suppressors of cell migration: miR-15b targets MTSS1 in breast cancer. Sci Signal. 2015;8(368):ra29.PubMed
117.
Gruszka R, Zakrzewska M. The oncogenic relevance of miR-17-92 cluster and its paralogous miR-106b-25 and miR-106a-363 clusters in brain tumors. Int J Mol Sci. 2018;19(3):879.
118.
Mogilyansky E, Rigoutsos I. The miR-17/92 cluster: a comprehensive update on its genomics, genetics, functions and increasingly important and numerous roles in health and disease. Cell Death Differ. 2013;20(12):1603–14.PubMedPubMedCentral
119.
Gu R, Huang S, Huang W, Li Y, Liu H, Yang L, et al. MicroRNA-17 family as novel biomarkers for cancer diagnosis: a meta-analysis based on 19 articles. Tumour Biol. 2016;37(5):6403–11.PubMed
120.
Liu F, Zhang F, Li X, Liu Q, Liu W, Song P, et al. Prognostic role of miR-17-92 family in human cancers: evaluation of multiple prognostic outcomes. Oncotarget. 2017;8(40):69125–38.PubMedPubMedCentral
121.
Yu Z, Willmarth NE, Zhou J, Katiyar S, Wang M, Liu Y, et al. microRNA 17/20 inhibits cellular invasion and tumor metastasis in breast cancer by heterotypic signaling. Proc Natl Acad Sci U S A. 2010;107(18):8231–6.PubMedPubMedCentral
122.
Li H, Bian C, Liao L, Li J, Zhao RC. miR-17-5p promotes human breast cancer cell migration and invasion through suppression of HBP1. Breast Cancer Res Treat. 2011;126(3):565–75.PubMed
123.
Gaziel-Sovran A, Segura MF, Di Micco R, Collins MK, Hanniford D, Vega-Saenz de Miera E, et al. miR-30b/30d regulation of GalNAc transferases enhances invasion and immunosuppression during metastasis. Cancer Cell. 2011;20(1):104–18.PubMedPubMedCentral
124.
Gwak JM, Kim HJ, Kim EJ, Chung YR, Yun S, Seo AN, et al. MicroRNA-9 is associated with epithelial-mesenchymal transition, breast cancer stem cell phenotype, and tumor progression in breast cancer. Breast Cancer Res Treat. 2014;147(1):39–49.PubMed
125.
Yang X, Zhong X, Tanyi JL, Shen J, Xu C, Gao P, et al. mir-30d regulates multiple genes in the autophagy pathway and impairs autophagy process in human cancer cells. Biochem Biophys Res Commun. 2013;431(3):617–22.PubMed
126.
Ouzounova M, Vuong T, Ancey PB, Ferrand M, Durand G, Le-Calvez Kelm F, et al. MicroRNA miR-30 family regulates non-attachment growth of breast cancer cells. BMC Genomics. 2013;14:139.PubMedPubMedCentral
127.
Zou JX, Duan Z, Wang J, Sokolov A, Xu J, Chen CZ, et al. Kinesin family deregulation coordinated by bromodomain protein ANCCA and histone methyltransferase MLL for breast cancer cell growth, survival, and tamoxifen resistance. Mol Cancer Res. 2014;12(4):539–49.PubMedPubMedCentral
128.
Charafe-Jauffret E, Ginestier C, Monville F, Finetti P, Adelaide J, Cervera N, et al. Gene expression profiling of breast cell lines identifies potential new basal markers. Oncogene. 2006;25(15):2273–84.PubMed
129.
Moon HG, Hwang KT, Kim JA, Kim HS, Lee MJ, Jung EM, et al. NFIB is a potential target for estrogen receptor-negative breast cancers. Mol Oncol. 2011;5(6):538–44.PubMedPubMedCentral
130.
Joosse SA, Hannemann J, Spotter J, Bauche A, Andreas A, Muller V, et al. Changes in keratin expression during metastatic progression of breast cancer: impact on the detection of circulating tumor cells. Clin Cancer Res. 2012;18(4):993–1003.PubMed
131.
Chaudhary S, Krishna BM, Mishra SK. A novel FOXA1/ESR1 interacting pathway: a study of oncomine breast cancer microarrays. Oncol Lett. 2017;14(2):1247–64.PubMedPubMedCentral
132.
Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012;486(7403):346–52.PubMedPubMedCentral
133.
Elsheikh S, Green AR, Aleskandarany MA, Grainge M, Paish CE, Lambros MB, et al. CCND1 amplification and cyclin D1 expression in breast cancer and their relation with proteomic subgroups and patient outcome. Breast Cancer Res Treat. 2008;109(2):325–35.PubMed
134.
Holm K, Staaf J, Jonsson G, Vallon-Christersson J, Gunnarsson H, Arason A, et al. Characterisation of amplification patterns and target genes at chromosome 11q13 in CCND1-amplified sporadic and familial breast tumours. Breast Cancer Res Treat. 2012;133(2):583–94.PubMed
135.
Feng YH, Chen WY, Kuo YH, Tung CL, Tsao CJ, Shiau AL, et al. Elovl6 is a poor prognostic predictor in breast cancer. Oncol Lett. 2016;12(1):207–12.PubMedPubMedCentral
136.
Doria ML, Ribeiro AS, Wang J, Cotrim CZ, Domingues P, Williams C, et al. Fatty acid and phospholipid biosynthetic pathways are regulated throughout mammary epithelial cell differentiation and correlate to breast cancer survival. FASEB J. 2014;28(10):4247–64.PubMed
137.
Riento K, Zhang Q, Clark J, Begum F, Stephens E, Wakelam MJ, et al. Flotillin proteins recruit sphingosine to membranes and maintain cellular sphingosine-1-phosphate levels. PLoS One. 2018;13(5):e0197401.PubMedPubMedCentral
138.
Ma F, Li W, Liu C, Li W, Yu H, Lei B, et al. MiR-23a promotes TGF-beta1-induced EMT and tumor metastasis in breast cancer cells by directly targeting CDH1 and activating Wnt/beta-catenin signaling. Oncotarget. 2017;8(41):69538–50.PubMedPubMedCentral
139.
Papadaki C, Stratigos M, Markakis G, Spiliotaki M, Mastrostamatis G, Nikolaou C, et al. Circulating microRNAs in the early prediction of disease recurrence in primary breast cancer. Breast Cancer Res. 2018;20(1):72.PubMedPubMedCentral
140.
Wang N, Tan HY, Feng YG, Zhang C, Chen F, Feng Y. microRNA-23a in human cancer: its roles, mechanisms and therapeutic relevance. Cancers (Basel). 2018;11(1):7.
141.
Parikh P, Palazzo JP, Rose LJ, Daskalakis C, Weigel RJ. GATA-3 expression as a predictor of hormone response in breast cancer. J Am Coll Surg. 2005;200(5):705–10.PubMed
142.
Eeckhoute J, Keeton EK, Lupien M, Krum SA, Carroll JS, Brown M. Positive cross-regulatory loop ties GATA-3 to estrogen receptor alpha expression in breast cancer. Cancer Res. 2007;67(13):6477–83.PubMed
143.
Mohammed H, D’Santos C, Serandour AA, Ali HR, Brown GD, Atkins A, et al. Endogenous purification reveals GREB1 as a key estrogen receptor regulatory factor. Cell Rep. 2013;3(2):342–9.PubMedPubMedCentral
144.
Mathe A, Wong-Brown M, Morten B, Forbes JF, Braye SG, Avery-Kiejda KA, et al. Novel genes associated with lymph node metastasis in triple negative breast cancer. Sci Rep. 2015;5:15832.PubMedPubMedCentral
145.
Shepherd JH, Uray IP, Mazumdar A, Tsimelzon A, Savage M, Hilsenbeck SG, et al. The SOX11 transcription factor is a critical regulator of basal-like breast cancer growth, invasion, and basal-like gene expression. Oncotarget. 2016;7(11):13106–21.PubMedPubMedCentral
146.
Moelans CB, de Weger RA, van Diest PJ. Absence of chromosome 17 polysomy in breast cancer: analysis by CEP17 chromogenic in situ hybridization and multiplex ligation-dependent probe amplification. Breast Cancer Res Treat. 2010;120(1):1–7.PubMed
147.
Ding Y, Zhang Y, Xu C, Tao QH, Chen YG. HECT domain-containing E3 ubiquitin ligase NEDD4L negatively regulates Wnt signaling by targeting dishevelled for proteasomal degradation. J Biol Chem. 2013;288(12):8289–98.PubMedPubMedCentral
148.
Zhan T, Rindtorff N, Boutros M. Wnt signaling in cancer. Oncogene. 2017;36(11):1461–73.PubMed
149.
Castañeda-Patlán MC, Fuentes-García G, Robles-Flores M. Wnt Signaling as a master regulator of immune tolerance in a tumor microenvironment. Cell Signalling-Thermodynamics Mol Control. 2018.
150.
Sakashita H, Inoue H, Akamine S, Ishida T, Inase N, Shirao K, et al. Identification of the NEDD4L gene as a prognostic marker by integrated microarray analysis of copy number and gene expression profiling in non-small cell lung cancer. Ann Surg Oncol. 2013;20(Suppl 3):S590–8.PubMed
151.
Martin TA, Jiang WG. Loss of tight junction barrier function and its role in cancer metastasis. Biochim Biophys Acta. 2009;1788(4):872–91.PubMed
152.
Cunliffe HE, Jiang Y, Fornace KM, Yang F, Meltzer PS. PAR6B is required for tight junction formation and activated PKCzeta localization in breast cancer. Am J Cancer Res. 2012;2(5):478–91.PubMedPubMedCentral
153.
Chatterjee SJ, McCaffrey L. Emerging role of cell polarity proteins in breast cancer progression and metastasis. Breast Cancer (Dove Med Press). 2014;6:15–27.
154.
Krijgsman O, Roepman P, Zwart W, Carroll JS, Tian S, de Snoo FA, et al. A diagnostic gene profile for molecular subtyping of breast cancer associated with treatment response. Breast Cancer Res Treat. 2012;133(1):37–47.PubMed
155.
Marques E, Englund JI, Tervonen TA, Virkunen E, Laakso M, Myllynen M, et al. Par6G suppresses cell proliferation and is targeted by loss-of-function mutations in multiple cancers. Oncogene. 2016;35(11):1386–98.PubMed
156.
McGuire A, Brown JA, Kerin MJ. Metastatic breast cancer: the potential of miRNA for diagnosis and treatment monitoring. Cancer Metastasis Rev. 2015;34(1):145–55.PubMedPubMedCentral
157.
Li XY, Luo QF, Wei CK, Li DF, Li J, Fang L. MiRNA-107 inhibits proliferation and migration by targeting CDK8 in breast cancer. Int J Clin Exp Med. 2014;7(1):32–40.PubMedPubMedCentral
158.
Stuckrath I, Rack B, Janni W, Jager B, Pantel K, Schwarzenbach H. Aberrant plasma levels of circulating miR-16, miR-107, miR-130a and miR-146a are associated with lymph node metastasis and receptor status of breast cancer patients. Oncotarget. 2015;6(15):13387–401.PubMedPubMedCentral
159.
Fuchs SY, Spiegelman VS, Kumar KG. The many faces of beta-TrCP E3 ubiquitin ligases: reflections in the magic mirror of cancer. Oncogene. 2004;23(11):2028–36.PubMed
160.
Herrero-Ruiz J, Mora-Santos M, Giraldez S, Saez C, Japon MA, Tortolero M, et al. betaTrCP controls the lysosome-mediated degradation of CDK1, whose accumulation correlates with tumor malignancy. Oncotarget. 2014;5(17):7563–74.PubMedPubMedCentral
161.
Liang J, Wang WF, Xie S, Zhang XL, Qi WF, Zhou XP, et al. Expression of beta-transducin repeat-containing E3 ubiquitin protein ligase in human glioma and its correlation with prognosis. Oncol Lett. 2015;9(6):2651–6.PubMedPubMedCentral
162.
Mu N, Gu J, Huang T, Zhang C, Shu Z, Li M, et al. A novel NF-kappaB/YY1/microRNA-10a regulatory circuit in fibroblast-like synoviocytes regulates inflammation in rheumatoid arthritis. Sci Rep. 2016;6:20059.PubMedPubMedCentral
163.
Yang S, Zhang H, Guo L, Zhao Y, Chen F. Reconstructing the coding and non-coding RNA regulatory networks of miRNAs and mRNAs in breast cancer. Gene. 2014;548(1):6–13.PubMed
164.
Martinez P, Vergoten G, Colomb F, Bobowski M, Steenackers A, Carpentier M, et al. Over-sulfated glycosaminoglycans are alternative selectin ligands: insights into molecular interactions and possible role in breast cancer metastasis. Clin Exp Metastasis. 2013;30(7):919–31.PubMed
165.
Zhao X, Graves C, Ames SJ, Fisher DE, Spanjaard RA. Mechanism of regulation and suppression of melanoma invasiveness by novel retinoic acid receptor-gamma target gene carbohydrate sulfotransferase 10. Cancer Res. 2009;69(12):5218–25.PubMed
166.
Fernandez-Vega I, Garcia-Suarez O, Garcia B, Crespo A, Astudillo A, Quiros LM. Heparan sulfate proteoglycans undergo differential expression alterations in right sided colorectal cancer, depending on their metastatic character. BMC Cancer. 2015;15:742.PubMedPubMedCentral
167.
Shi W, Gerster K, Alajez NM, Tsang J, Waldron L, Pintilie M, et al. MicroRNA-301 mediates proliferation and invasion in human breast cancer. Cancer Res. 2011;71(8):2926–37.PubMed
168.
Cao ZG, Li JJ, Yao L, Huang YN, Liu YR, Hu X, et al. High expression of microRNA-454 is associated with poor prognosis in triple-negative breast cancer. Oncotarget. 2016;7(40):64900–9.PubMedPubMedCentral
169.
Lu L, Mao X, Shi P, He B, Xu K, Zhang S, et al. MicroRNAs in the prognosis of triple-negative breast cancer: a systematic review and meta-analysis. Medicine (Baltimore). 2017;96(22):e7085.
170.
Breuer K, Foroushani AK, Laird MR, Chen C, Sribnaia A, Lo R, et al. InnateDB: systems biology of innate immunity and beyond--recent updates and continuing curation. Nucleic Acids Res. 2013;41(Database issue):D1228–33.PubMed
171.
Roederer M, Quaye L, Mangino M, Beddall MH, Mahnke Y, Chattopadhyay P, et al. The genetic architecture of the human immune system: a bioresource for autoimmunity and disease pathogenesis. Cell. 2015;161(2):387–403.PubMedPubMedCentral
172.
Gurusamy D, Clever D, Eil R, Restifo NP. Novel “elements” of immune suppression within the tumor microenvironment. Cancer Immunol Res. 2017;5(6):426–33.PubMedPubMedCentral
173.
da Silveira WA, Palma PVB, Sicchieri RD, Villacis RAR, Mandarano LRM, Oliveira TMG, et al. Transcription factor networks derived from breast cancer stem cells control the immune response in the basal subtype. Sci Rep. 2017;7(1):2851.PubMedPubMedCentral
174.
Chifman J, Pullikuth A, Chou JW, Bedognetti D, Miller LD. Conservation of immune gene signatures in solid tumors and prognostic implications. BMC Cancer. 2016;16(1):911.PubMedPubMedCentral
175.
Dedeurwaerder S, Fuks F. DNA methylation markers for breast cancer prognosis: unmasking the immune component. Oncoimmunology. 2012;1(6):962–4.PubMedPubMedCentral
176.
Winslow S, Leandersson K, Edsjo A, Larsson C. Prognostic stromal gene signatures in breast cancer. Breast Cancer Res. 2015;17:23.PubMedPubMedCentral
177.
Liu Z, Li M, Jiang Z, Wang X. A comprehensive immunologic portrait of triple-negative breast cancer. Transl Oncol. 2018;11(2):311–29.PubMedPubMedCentral
178.
Bjordahl RL, Steidl C, Gascoyne RD, Ware CF. Lymphotoxin network pathways shape the tumor microenvironment. Curr Opin Immunol. 2013;25(2):222–9.PubMedPubMedCentral
179.
Martinet L, Filleron T, Le Guellec S, Rochaix P, Garrido I, Girard JP. High endothelial venule blood vessels for tumor-infiltrating lymphocytes are associated with lymphotoxin beta-producing dendritic cells in human breast cancer. J Immunol. 2013;191(4):2001–8.PubMed
180.
Martinet L, Girard JP. Regulation of tumor-associated high-endothelial venules by dendritic cells: a new opportunity to promote lymphocyte infiltration into breast cancer? Oncoimmunology. 2013;2(11):e26470.PubMedPubMedCentral
181.
Sautes-Fridman C, Lawand M, Giraldo NA, Kaplon H, Germain C, Fridman WH, et al. Tertiary lymphoid structures in cancers: prognostic value, regulation, and manipulation for therapeutic intervention. Front Immunol. 2016;7:407.PubMedPubMedCentral
182.
Dieu-Nosjean MC, Goc J, Giraldo NA, Sautes-Fridman C, Fridman WH. Tertiary lymphoid structures in cancer and beyond. Trends Immunol. 2014;35(11):571–80.PubMed
183.
Martinet L, Le Guellec S, Filleron T, Lamant L, Meyer N, Rochaix P, et al. High endothelial venules (HEVs) in human melanoma lesions: major gateways for tumor-infiltrating lymphocytes. Oncoimmunology. 2012;1(6):829–39.PubMedPubMedCentral
184.
Haybaeck J, Zeller N, Wolf MJ, Weber A, Wagner U, Kurrer MO, et al. A lymphotoxin-driven pathway to hepatocellular carcinoma. Cancer Cell. 2009;16(4):295–308.PubMedPubMedCentral
185.
Bhaumik D, Scott GK, Schokrpur S, Patil CK, Campisi J, Benz CC. Expression of microRNA-146 suppresses NF-κB activity with reduction of metastatic potential in breast cancer cells. Oncogene. 2008;27(42):5643–7.PubMedPubMedCentral
186.
Liu YLL, Chen Q, Song Y, Xu S, Ma F, Wang X, Wang J, Yu H, Cao X, Wang Q. MicroRNA-494 is required for the accumulation and functions of tumor-expanded myeloid-derived suppressor cells via targeting of PTEN. J Immunol. 2012;188(11):5500–10.PubMed
187.
Wang D, Liu D, Gao J, Liu M, Liu S, Jiang M, et al. TRAIL-induced miR-146a expression suppresses CXCR4-mediated human breast cancer migration. FEBS J. 2013;280(14):3340–53.PubMed
188.
Song L, Liu D, Wang B, He J, Zhang S, Dai Z, et al. miR-494 suppresses the progression of breast cancer in vitro by targeting CXCR4 through the Wnt/beta-catenin signaling pathway. Oncol Rep. 2015;34(1):525–31.PubMed
189.
Saba R, Sorensen DL, Booth SA. MicroRNA-146a: a dominant, negative regulator of the innate immune response. Front Immunol. 2014;5:578.PubMedPubMedCentral
190.
Zhao JL, Rao DS, Boldin MP, Taganov KD, O’Connell RM, Baltimore D. NF-κB dysregulation in microRNA-146a–deficient mice drives the development of myeloid malignancies. Proc Natl Acad Sci. 2011;108(22):9184–9.PubMedPubMedCentral
191.
Eichmuller SB, Osen W, Mandelboim O, Seliger B. Immune modulatory microRNAs involved in tumor attack and tumor immune escape. J Natl Cancer Inst. 2017;109(10).
192.
Tay JW, James I, Hughes QW, Tiao JY, Baker RI. Identification of reference miRNAs in plasma useful for the study of oestrogen-responsive miRNAs associated with acquired protein S deficiency in pregnancy. BMC Res Notes. 2017;10(1):312.PubMedPubMedCentral
Metadata
Title
Secreted breast tumor interstitial fluid microRNAs and their target genes are associated with triple-negative breast cancer, tumor grade, and immune infiltration
Authors
Thilde Terkelsen
Francesco Russo
Pavel Gromov
Vilde Drageset Haakensen
Søren Brunak
Irina Gromova
Anders Krogh
Elena Papaleo
Publication date
01-12-2020
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2020
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-020-01295-6

Other articles of this Issue 1/2020

Breast Cancer Research 1/2020 Go to the issue

Research article

Phase 2 study of buparlisib (BKM120), a pan-class I PI3K inhibitor, in patients with metastatic triple-negative breast cancer

Research article

EFFECT: a randomized phase II study of efficacy and impact on function of two doses of nab-paclitaxel as first-line treatment in older women with advanced breast cancer

Review

Clinical applications of polygenic breast cancer risk: a critical review and perspectives of an emerging field

Research article

Cathepsin V suppresses GATA3 protein expression in luminal A breast cancer

Research article

Discordance in 21-gene recurrence scores between paired breast cancer samples is inversely associated with patient age

Research article

COVID-19 in breast cancer patients: a cohort at the Institut Curie hospitals in the Paris area
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