Potential biomarker panels in overall breast cancer management: Advancements by multilevel diagnostics

Personalized Medicine

Volumn 13, Issue 5, 2016, Pages 469-484

  Girotra, Shantanu ^a   Yeghiazaryan, Kristina ^a   Golubnitschaja, Olga ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

breast cancer; cancer stem cells; circulating tumor cells; omics; personalized medicine; predictive diagnostics; prognosis; stratification; targeted therapy; validated biomarker

Indexed keywords

ANTINEOPLASTIC AGENT; TUMOR MARKER;

AMINO ACID METABOLISM; BREAST CANCER; CANCER GENETICS; CANCER PROGNOSIS; CANCER SCREENING; CANCER SUSCEPTIBILITY; CELL DENSITY; CIRCULATING TUMOR CELL; DISEASE FREE SURVIVAL; DISEASE MARKER; EPIGENETICS; GENE CONTROL; GENE EXPRESSION PROFILING; GENE REARRANGEMENT; GENETIC POLYMORPHISM; GENOMICS; HUMAN; METABOLOMICS; OVERALL SURVIVAL; PERIPHERAL LYMPHOCYTE; PERSONALIZED MEDICINE; PHARMACOGENETICS; PHENOTYPE; PRIORITY JOURNAL; PROTEOMICS; REVIEW; SIGNAL TRANSDUCTION; SINGLE NUCLEOTIDE POLYMORPHISM; TRIPLE NEGATIVE BREAST CANCER;

EID: 84992116179     PISSN: 17410541     EISSN: 1744828X     Source Type: Journal    
DOI: 10.2217/pme-2016-0020     Document Type: Review

References (195)

1. Golubnitschaja O, Debald M, Yeghiazaryan K et al. Breast cancer epidemic in the early 21st century: evaluation of risk factors, cumulative questionnaires and recommendations for preventive measures. Tumor Biol. Doi:10. 1007/s13277-016-5168-x (2016) (In press).
2. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J. Clin. 65(2), 87-108 (2015).
3. Ekwueme DU, Guy GP, Rim SH et al. Health and economic impact of breast cancer mortality in young women, 1970-2008. Am. J. Prev. Med. 46(1), 71-79 (2014).
4. Reis-Filho JS, Pusztai L. Gene expression profiling in breast cancer: classification, prognostication, prediction. Lancet 378(9805), 1812-1823 (2011).
5. Marmot MG, Altman DG, Cameron DA, Dewar JA, Thompson SG, Wilcox M. The benefits and harms of breast cancer screening: an independent review. Br. J. Cancer 108(11), 2205-2240 (2013).
6. Golubnitschaja O, Yeghiazaryan K, Costigliola V et al. Risk assessment, disease prevention and personalised treatments in breast cancer: is clinically qualified integrative approach in the horizon EPMA J. 4(1), 6 (2013).
7. Luengo-fernandez R, Leal J, Gray A, Sullivan R. Economic burden of cancer across the European Union: a populationbased cost analysis. Lancet Oncol. 14(12), 1165-1174 (2013).
8. Meneses K, Azuero A, Hassey L, Mcnees P, Pisu M. Does economic burden influence quality of life in breast cancer survivors Gynecol. Oncol. 124(3), 437-443 (2012).
9. Wang L, Xiao Y, Ping Y et al. Integrating multi-omics for uncovering the architecture of cross-talking pathways in breast cancer. PLoS ONE 9(8), e104282 (2014).
10. Tun NM, Villani G, Ong K, Yoe L, Bo ZM. Risk of having BRCA1 mutation in high-risk women with triple-negative breast cancer: a meta-analysis. Clin. Genet. 85(1), 43-48 (2014).
11. Garrisi VM, Tommasi S, Facchiano A et al. Proteomic profile in familial breast cancer patients. Clin. Biochem. 46(3), 259-265 (2013).
12. Rhee JK, Kim K, Chae H et al. Integrated analysis of genome-wide DNA methylation and gene expression profiles in molecular subtypes of breast cancer. Nucleic Acids Res. 41(18), 8464-8474 (2013).
13. Xu H, Eirew P, Mullaly SC, Aparicio S. The omics of triplenegative breast cancers. Clin. Chem. 60(1), 122-133 (2014).
14. Muellner MK, Mair B, Ibrahim Y et al. Targeting a cell state common to triple-negative breast cancers. Mol. Syst. Biol. 11(1), 789 (2015).
15. Chen S. An "omics" approach to determine the mechanisms of acquired aromatase inhibitor resistance. OMICS 15(6), 347-352 (2011).
16. Kim D, Li R, Dudek SM, Ritchie MD. Predicting censored survival data based on the interactions between metadimensional omics data in breast cancer. J. Biomed. Inform. 56, 220-228 (2015).
17. Pauling JK, Christensen AG, Batra R et al. Elucidation of epithelial-mesenchymal transition-related pathways in triple-negative breast cancer cell line model by multi-omics interactome analysis. Integr. Biol. (Camb. ) 6(11) 1058-1068 (2014).
18. Ternès N, Arnedos M, Koscielny S, Michiels S, Lanoy E. Statistical methods applied to omics data: predicting response to neoadjuvant therapy in breast cancer. Curr. Opin. Oncol. 26(6), 576-583 (2014).
19. Desmedt C, Voet T, Sotiriou C, Campbell PJ. Nextgeneration sequencing in breast cancer: first take home messages. Curr. Opin. Oncol. 24(6), 597-604 (2012).
20. Ahsan H, Halpern J, Kibriya MG et al. A genome-wide association study of early-onset breast cancer identifies PFKM as a novel breast cancer gene and supports a common genetic spectrum for breast cancer at any age. Cancer Epidemiol. Biomarkers Prev. 23(4), 658-669 (2014).
21. Lindström S, Thompson DJ, Paterson AD et al. Genomewide association study identifies multiple loci associated with both mammographic density and breast cancer risk. Nat. Commun. 5, 5303 (2014).
22. Michailidou K, Beesley J, Lindstrom S et al. Genome-wide association analysis of more than 120, 000 individuals identifies 15 new susceptibility loci for breast cancer. Nat. Genet. 47(4), 373-380 (2015).
23. Hsiung CN, Chu HW, Huang YL et al. Functional variants at the 21q22. 3 locus involved in breast cancer progression identified by screening of genome-wide estrogen response elements. Breast Cancer Res. 16(5), 455 (2014).
24. Purrington KS, Slager S, Eccles D et al. Genome-wide association study identifies 25 known breast cancer susceptibility loci as risk factors for triple-negative breast cancer. Carcinogenesis 35(5), 1012-1019 (2014).
25. Rich TA, Woodson AH, Litton J, Arun B. Hereditary breast cancer syndromes and genetic testing. J. Surg. Oncol. 111(1), 66-80 (2015).
26. Abu-khalf M, Pusztai L. Influence of genomics on adjuvant treatments for pre-invasive and invasive breast cancer. Breast 22(Suppl. 2), S83-S87 (2013).
27. Fostira F, Tsitlaidou M, Papadimitriou C et al. Prevalence of BRCA1 mutations among 403 women with triple-negative breast cancer: implications for genetic screening selection criteria: a Hellenic Cooperative Oncology Group Study. Breast Cancer Res. Treat. 134(1), 353-362 (2012).
28. Zhong Q, Peng HL, Zhao X, Zhang L, Hwang WT. Effects of BRCA1-and BRCA2-related mutations on ovarian and breast cancer survival: a meta-analysis. Clin. Cancer Res. 21(1), 211-220 (2015).
29. Silwal-pandit L, Vollan HK, Chin SF et al. TP53 mutation spectrum in breast cancer is subtype specific and has distinct prognostic relevance. Clin. Cancer Res. 20(13), 3569-3580 (2014).
30. He JM, Pu YD, Wu YJ et al. Association between dietary intake of folate and MTHFR and MTR genotype with risk of breast cancer. Genet. Mol. Res. 13(4), 8925-8931 (2014).
31. Liang H, Yan Y, Li T et al. Methylenetetrahydrofolate reductase polymorphisms and breast cancer risk in Chinese population: a meta-analysis of 22 case-control studies. Tumour Biol. 35(2), 1695-1701 (2014).
32. Wang ZG, Cui W, Yang LF, Zhu YQ, Wei WH. Association of dietary intake of folate and MTHFR genotype with breast cancer risk. Genet. Mol. Res. 13(3), 5446-5451 (2014).
33. Li K, Li W, Dong X. Association of 677 CT (rs1801133) and 1298 AC (rs1801131) polymorphisms in the MTHFR gene and breast cancer susceptibility: a meta-analysis based on 57 individual studies. PLoS ONE 9(6), e71290 (2014).
34. Diakite B, Tazzite A, Hamzi K, Jouhadi H, Nadifi S. Methylenetetrahydrofolate reductase C677T polymorphism and breast cancer risk in Moroccan women. Afr. Health Sci. 12(2), 204-209 (2012).
35. Awwad N, Yousef AM, Abuhaliema A, Abdalla I, Yousef M. Relationship between genetic polymorphisms in MTHFR (C677T, A1298C and their Haplotypes) and the incidence of breast cancer among Jordanian females-case-control study. Asian Pac. J. Cancer Prev. 16(12), 5007-5011 (2015).
36. Qi X, Ma X, Yang X et al. Methylenetetrahydrofolate reductase polymorphisms and breast cancer risk: a metaanalysis from 41 studies with 16, 480 cases and 22, 388 controls. Breast Cancer Res. Treat. 123(2), 499-506 (2010).
37. Xie H, Xia K, Rong H, Chen X. Genetic polymorphism in hOGG1 is associated with triple-negative breast cancer risk in Chinese Han women. Breast 22(5), 707-712 (2013).
38. Zhang N, Huo Q, Wang X et al. A genetic variant in p63 (rs17506395) is associated with breast cancer susceptibility and prognosis. Gene 535(2), 170-176 (2014).
39. Krzelak A, Forma E, Jówiak P et al. Metallothionein 2A genetic polymorphisms and risk of ductal breast cancer. Clin. Exp. Med. 14(1), 107-113 (2014).
40. Karakas B, Colak D, Kaya N et al. Prevalence of PIK3CA mutations and the SNP rs17849079 in Arab breast cancer patients. Cancer Biol. Ther. 14(10), 888-896 (2013).
41. Park HS, Jang MH, Kim EJ et al. High EGFR gene copy number predicts poor outcome in triple-negative breast cancer. Mod. Pathol. 27(9), 1212-1222 (2014).
42. Park YH, Jung HH, Do IG et al. A seven-gene signature can predict distant recurrence in patients with triple-negative breast cancers who receive adjuvant chemotherapy following surgery. Int. J. Cancer 136(8), 1976-1984 (2015).
43. Holm C, Rayala S, Jirström K, Stål O, Kumar R, Landberg G. Association between Pak1 expression and subcellular localization and tamoxifen resistance in breast cancer patients. J. Natl Cancer Inst. 98(10), 671-680 (2006).
44. Bostner J, Ahnström waltersson M, Fornander T, Skoog L, Nordenskjöld B, Stål O. Amplification of CCND1 and PAK1 as predictors of recurrence and tamoxifen resistance in postmenopausal breast cancer. Oncogene 26(49), 6997-7005 (2007).
45. Lu X, Mazur SJ, Lin T, Appella E, Xu Y. The pluripotency factor nanog promotes breast cancer tumorigenesis and metastasis. Oncogene 33(20), 2655-2664 (2014).
46. Wang D, Lu P, Zhang H et al. Oct-4 and Nanog promote the epithelial-mesenchymal transition of breast cancer stem cells and are associated with poor prognosis in breast cancer patients. Oncotarget 5(21), 10803-10815 (2014).
47. Yin ZQ, Liu JJ, Xu YC et al. A 41-gene signature derived from breast cancer stem cells as a predictor of survival. J. Exp. Clin. Cancer Res. 33(1), 49 (2014).
48. Meldi KM, Figueroa ME. Epigenetic deregulation in myeloid malignancies. Transl. Res. 165(1), 102-114 (2015).
49. Jovanovic J, R∅nneberg JA, Tost J, Kristensen V. The epigenetics of breast cancer. Mol. Oncol. 4(3), 242-254 (2010).
50. Locke WJ, Zotenko E, Stirzaker C et al. Coordinated epigenetic remodelling of transcriptional networks occurs during early breast carcinogenesis. Clin. Epigenetics 7(1), 52 (2015).
51. Gyrffy B, Bottai G, Fleischer T et al. Aberrant DNA methylation impacts gene expression and prognosis in breast cancer subtypes. Int. J. Cancer 138(1), 87-97 (2016).
52. Li Y, Melnikov AA, Levenson V et al. A seven-gene CpGisland methylation panel predicts breast cancer progression. BMC Cancer 15, 417 (2015).
53. Li Z, Guo X, Wu Y et al. Methylation profiling of 48 candidate genes in tumor and matched normal tissues from breast cancer patients. Breast Cancer Res. Treat. 149(3), 767-779 (2015).
54. Müller BM, Jana L, Kasajima A et al. Differential expression of histone deacetylases HDAC1, 2 and 3 in human breast cancer-overexpression of HDAC2 and HDAC3 is associated with clinicopathological indicators of disease progression. BMC Cancer 13(1), 215 (2013).
55. Seo J, Min SK, Park HR et al. Expression of histone deacetylases HDAC1, HDAC2, HDAC3, HDAC6 in invasive ductal carcinomas of the breast. J. Breast Cancer 17(4), 323-331 (2014).
56. Park SY, Jun JA, Jeong KJ et al. Histone deacetylases 1, 6 and 8 are critical for invasion in breast cancer. Oncol. Rep. 25(6), 1677-1681 (2011).
57. Yokoyama Y, Matsumoto A, Hieda M et al. Loss of histone H4K20 trimethylation predicts poor prognosis in breast cancer and is associated with invasive activity. Breast Cancer Res. 16(3), R66 (2014).
58. Healey MA, Hu R, Beck AH et al. Association of H3K9me3 and H3K27me3 repressive histone marks with breast cancer subtypes in the Nurses' Health Study. Breast Cancer Res. Treat. 147(3), 639-651 (2014).
59. Zhang L, Deng L, Chen F et al. Inhibition of histone H3K79 methylation selectively inhibits proliferation, self-renewal and metastatic potential of breast cancer. Oncotarget 5(21), 10665-10677 (2014).
60. Feng Q, Zhang Z, Shea MJ et al. An epigenomic approach to therapy for tamoxifen-resistant breast cancer. Cell Res. 24(7), 809-819 (2014).
61. Timms KM, Abkevich V, Hughes E et al. Association of BRCA1/2 defects with genomic scores predictive of DNA damage repair deficiency among breast cancer subtypes. Breast Cancer Res. 16(6), 475 (2014).
62. Gupta S, Jaworska-Bieniek K, Narod SA, Lubinski J, Wojdacz TK, Jakubowska A. Methylation of the BRCA1 promoter in peripheral blood DNA is associated with triplenegative and medullary breast cancer. Breast Cancer Res. Treat. 148(3), 615-622 (2014).
63. Xu Y, Diao L, Chen Y et al. Promoter methylation of BRCA1 in triple-negative breast cancer predicts sensitivity to adjuvant chemotherapy. Ann. Oncol. 24(6), 1498-1505 (2013).
64. Yamashita N, Tokunaga E, Kitao H et al. Epigenetic inactivation of BRCA1 through promoter hypermethylation and its clinical importance in triple-negative breast cancer. Clin. Breast Cancer 15(6), 498-504 (2015).
65. Ramos EA, Grochoski M, Braun-Prado K et al. Epigenetic changes of CXCR4 and its ligand CXCL12 as prognostic factors for sporadic breast cancer. PLoS ONE 6(12), e29461 (2011).
66. Wendt MK, Cooper AN, Dwinell MB. Epigenetic silencing of CXCL12 increases the metastatic potential of mammary carcinoma cells. Oncogene 27(10), 1461-1471 (2008).
67. Fridrichova I, Smolkova B, Kajabova V et al. CXCL12 and ADAM23 hypermethylation are associated with advanced breast cancers. Transl. Res. 165(6), 717-730 (2015).
68. Verbisck NV, Costa ET, Costa FF et al. ADAM23 negatively modulates alpha(v)beta(3) integrin activation during metastasis. Cancer Res. 69(13), 5546-5552 (2009).
69. Costa FF, Verbisck NV, Salim AC et al. Epigenetic silencing of the adhesion molecule ADAM23 is highly frequent in breast tumors. Oncogene 23(7), 1481-8 (2004).
70. Ramos EA, Camargo AA, Braun K et al. Simultaneous CXCL12 and ESR1 CpG island hypermethylation correlates with poor prognosis in sporadic breast cancer. BMC Cancer 10(1), 23 (2010).
71. Kloten V, Becker B, Winner K et al. Promoter hypermethylation of the tumor-suppressor genes ITIH5, DKK3, RASSF1A as novel biomarkers for blood-based breast cancer screening. Breast Cancer Res. 15(1), R4 (2013).
72. Kuchiba A, Iwasaki M, Ono H et al. Global methylation levels in peripheral blood leukocyte DNA by LUMA and breast cancer: a case-control study in Japanese women. Br. J. Cancer 110(11), 2765-2771 (2014).
73. Hon GC, Hawkins RD, Caballero OL et al. Global DNA hypomethylation coupled to repressive chromatin domain formation and gene silencing in breast cancer. Genome Res. 22(2), 246-258 (2012).
74. Choi JY, James SR, Link PA et al. Association between global DNA hypomethylation in leukocytes and risk of breast cancer. Carcinogenesis 30(11), 1889-1897 (2009).
75. Legendre C, Gooden GC, Johnson K, Martinez RA, Liang WS, Salhia B. Whole-genome bisulfite sequencing of cell-free DNA identifies signature associated with metastatic breast cancer. Clin. Epigenetics 7(1), 100 (2015).
76. Bernardino J, Roux C, Almeida A et al. DNA hypomethylation in breast cancer: an independent parameter of tumor progression Cancer Genet Cytogenet. 97(2), 83-89 (1997).
77. Krishnan P, Ghosh S, Wang B et al. Next generation sequencing profiling identifies miR-574-3p and miR-660-5p as potential novel prognostic markers for breast cancer. BMC Genomics 16(1), 735 (2015).
78. Mcguire A, Brown JA, Kerin MJ. Metastatic breast cancer: the potential of miRNA for diagnosis and treatment monitoring. Cancer Metastasis Rev. 34(1), 145-155 (2015).
79. Takahashi RU, Miyazaki H, Ochiya T. The roles of microRNAs in breast cancer. Cancers (Basel). 7(2), 598-616 (2015).
80. Chen J, Yao D, Li Y et al. Serum microRNA expression levels can predict lymph node metastasis in patients with earlystage cervical squamous cell carcinoma. Int. J. Mol. Med. 32(3), 557-567 (2013).
81. Zhang HL, Qin XJ, Cao DL et al. An elevated serum miR-141 level in patients with bone-metastatic prostate cancer is correlated with more bone lesions. Asian J. Androl. 15(2), 231-235 (2013).
82. Kim SY, Jeon TY, Choi CI et al. Validation of circulating miRNA biomarkers for predicting lymph node metastasis in gastric cancer. J. Mol. Diagn. 15(5), 661-669 (2013).
83. Toiyama Y, Hur K, Tanaka K et al. Serum miR-200c is a novel prognostic and metastasis-predictive biomarker in patients with colorectal cancer. Ann. Surg. 259(4), 735-743 (2014).
84. Ma L, Teruya-feldstein J, Weinberg RA. Tumour invasion and metastasis initiated by microRNA-10b in breast cancer. Nature 449(7163), 682-688 (2007).
85. Cizeron-clairac G, Lallemand F, Vacher S, Lidereau R, Bieche I, Callens C. MiR-190b, the highest up-regulated miRNA in ER-positive compared with ER-negative breast tumors, a new biomarker in breast cancers BMC Cancer 15, 499 (2015).
86. Niu J, Xue A, Chi Y et al. Induction of miRNA-181a by genotoxic treatments promotes chemotherapeutic resistance and metastasis in breast cancer. Oncogene 35(10), 1302-1313 (2016).
87. Kodahl AR, Lyng MB, Binder H et al. Novel circulating microRNA signature as a potential non-invasive multimarker test in ER-positive early-stage breast cancer: a case control study. Mol. Oncol. 8(5), 874-883 (2014).
88. Lin X, Chen L, Yao Y et al. CCL18-mediated downregulation of miR98 and miR27b promotes breast cancer metastasis. Oncotarget 6(24), 20485-20499 (2015).
89. Krishnan P, Ghosh S, Wang B et al. Next generation sequencing profiling identifies miR-574-3p and miR-660-5p as potential novel prognostic markers for breast cancer. BMC Genomics 16(1), 735 (2015).
90. Wu Q, Lu Z, Li H, Lu J, Guo L, Ge Q. Next-generation sequencing of microRNAs for breast cancer detection. J. Biomed. Biotechnol. 2011, 597145 (2011).
91. Erbes T, Hirschfeld M, Rücker G et al. Feasibility of urinary microRNA detection in breast cancer patients and its potential as an innovative non-invasive biomarker. BMC Cancer 15, 193 (2015).
92. Mishra S, Srivastava AK, Suman S, Kumar V, Shukla Y. Circulating miRNAs revealed as surrogate molecular signatures for the early detection of breast cancer. Cancer Lett. 369(1), 67-75 (2015).
93. Kinkorová J. Biobanks in the era of personalized medicine: objectives, challenges, innovation. EPMA J. 7, 1 (2015).
94. Christodoulatos GS, Dalamaga M. Micro-RNAs as clinical biomarkers and therapeutic targets in breast cancer: quo vadis World J. Clin. Oncol. 5(2), 71-81 (2014).
95. Fkih M'hamed I, Privat M, Ponelle F, Penault-llorca F, Kenani A, Bignon YJ. Identification of miR-10b, miR-26a, miR-146a and miR-153 as potential triple-negative breast cancer biomarkers. Cell. Oncol. (Dordr. ). 38(6), 433-442 (2015).
96. Taylor MA, Sossey-Alaoui K, Thompson CL, Danielpour D, Schiemann WP. TGF-upregulates miR-181a expression to promote breast cancer metastasis. J. Clin. Invest. 123(1), 150-163 (2013).
97. Guo LJ, Zhang QY. Decreased serum miR-181a is a potential new tool for breast cancer screening. Int. J. Mol. Med. 30(3), 680-686 (2012).
98. Miller TE, Ghoshal K, Ramaswamy B et al. MicroRNA-221/222 confers tamoxifen resistance in breast cancer by targeting p27Kip1. J. Biol. Chem. 283(44), 29897-29903 (2008).
99. Wei Y, Lai X, Yu S et al. Exosomal miR-221/222 enhances tamoxifen resistance in recipient ER-positive breast cancer cells. Breast Cancer Res. Treat. 147(2), 423-431 (2014).
100. Adachi R, Horiuchi S, Sakurazawa Y, Hasegawa T, Sato K, Sakamaki T. ErbB2 down-regulates microRNA-205 in breast cancer. Biochem. Biophys. Res. Commun. 411 (4), 804-808 (2011).
101. Bockhorn J, Yee K, Chang YF et al. MicroRNA-30c targets cytoskeleton genes involved in breast cancer cell invasion. Breast Cancer Res. Treat. 137(2), 373-382 (2013).
102. Dobson JR, Taipaleenmäki H, Hu YJ et al. hsa-mir-30c promotes the invasive phenotype of metastatic breast cancer cells by targeting NOV/CCN3. Cancer Cell Int. 14(1), 73 (2014).
103. Ebrahimi F, Gopalan V, Smith RA, Lam AK. miR-126 in human cancers: clinical roles and current perspectives. Exp. Mol. Pathol. 96(1), 98-107 (2014).
104. Wang CZ, Yuan P, Li Y. MiR-126 regulated breast cancer cell invasion by targeting ADAM9. Int. J. Clin. Exp. Pathol. 8(6), 6547-6553 (2015).
105. Zhang Y, Yang P, Sun T et al. miR-126 and miR-126 repress recruitment of mesenchymal stem cells and inflammatory monocytes to inhibit breast cancer metastasis. Nat. Cell. Biol. 15(3), 284-294 (2013).
106. Shinden Y, Iguchi T, Akiyoshi S et al. miR-29b is an indicator of prognosis in breast cancer patients. Mol. Clin. Oncol. 3(4), 919-923 (2015).
107. Song B, Wang C, Liu J et al. MicroRNA-21 regulates breast cancer invasion partly by targeting tissue inhibitor of metalloproteinase 3 expression. J. Exp. Clin. Cancer Res. 29(1), 29 (2010).
108. Wang Y, Zhang Y, Pan C, Ma F, Zhang S. Prediction of poor prognosis in breast cancer patients based on microRNA-21 expression: a meta-analysis. PLoS ONE 10(2), e0118647 (2010).
109. Pan F, Mao H, Deng L, Li G, Geng P. Prognostic and clinicopathological significance of microRNA-21 overexpression in breast cancer: a meta-analysis. Int. J. Clin. Exp. Pathol. 7(9), 5622-5633 (2014).
110. Si ML, Zhu S, Wu H, Lu Z, Wu F, Mo YY. miR-21-mediated tumor growth. Oncogene 26(19), 2799-2803 (2007).
111. Si H, Sun X, Chen Y et al. Circulating microRNA-92a and microRNA-21 as novel minimally invasive biomarkers for primary breast cancer. J. Cancer Res. Clin. Oncol. 139(2), 223-229 (2013).
112. Qian B, Katsaros D, Lu L et al. High miR-21 expression in breast cancer associated with poor disease-free survival in early stage disease and high TGF-beta1. Breast Cancer Res. Treat. 117(1), 131-140 (2009).
113. Zeng H, Fang C, Nam S, Cai Q, Long X. The clinicopathological significance of microRNA-155 in breast cancer: a meta-analysis. Biomed. Res. Int. 2014, 724209 (2014).
114. Kong W, He L, Richards EJ et al. Upregulation of miRNA-155 promotes tumour angiogenesis by targeting VHL and is associated with poor prognosis and triplenegative breast cancer. Oncogene 33(6), 679-689 (2014).
115. Zheng SR, Guo GL, Zhang W et al. Clinical significance of miR-155 expression in breast cancer and effects of miR-155 ASO on cell viability and apoptosis. Oncol. Rep. 27(4), 1149-1155 (2012).
116. Erbes T, Hirschfeld M, Rücker G et al. Feasibility of urinary microRNA detection in breast cancer patients and its potential as an innovative non-invasive biomarker. BMC Cancer 15, 193 (2015).
117. Shaker O, Maher M, Nassar Y, Morcos G, Gad Z. Role of microRNAs-29b-2,-155,-197 and-205 as diagnostic biomarkers in serum of breast cancer females. Gene 560(1), 77-82 (2015).
118. Zhang CM, Zhao J, Deng HY. MiR-155 promotes proliferation of human breast cancer MCF-7 cells through targeting tumor protein 53-induced nuclear protein 1. J. Biomed. Sci. 20(1), 79 (2013).
119. Mattiske S, Suetani RJ, Neilsen PM, Callen DF. The oncogenic role of miR-155 in breast cancer. Cancer Epidemiol. Biomarkers Prev. 21(8), 1236-1243 (2012).
120. Liu J, Mao Q, Liu Y, Hao X, Zhang S, Zhang J. Analysis of miR-205 and miR-155 expression in the blood of breast cancer patients. Chin. J. Cancer Res. 25(1), 46-54 (2013).
121. Jung EJ, Santarpia L, Kim J et al. Plasma microRNA 210 levels correlate with sensitivity to trastuzumab and tumor presence in breast cancer patients. Cancer 118(10), 2603-2614 (2012).
122. Rothé F, Ignatiadis M, Chaboteaux C et al. Global microRNA expression profiling identifies miR-210 associated with tumor proliferation, invasion and poor clinical outcome in breast cancer. PLoS ONE 6(6), e20980 (2011).
123. Toyama T, Kondo N, Endo Y et al. High expression of microRNA-210 is an independent factor indicating a poor prognosis in Japanese triple-negative breast cancer patients. Jpn J. Clin. Oncol. 42(4), 256-263 (2012).
124. Hong L, Yang J, Han Y, Lu Q, Cao J, Syed L. High expression of miR-210 predicts poor survival in patients with breast cancer: a meta-analysis. Gene 507(2), 135-138 (2012).
125. Pérez-Rivas LG, Jerez JM, Carmona R et al. A microRNA signature associated with early recurrence in breast cancer. PLoS ONE 9(3), e91884 (2014).
126. Debald M, Yeghiazaryan K, Cebioglu M, Kuhn W, Schild HH, Golubnitschaja O. 'Suspect molecular signature' in blood as the indicator of undiagnosed breast cancer, cancer risk and targeted prevention. EPMA J. 4(1), 22 (2013).
127. Coumans JV, Gau D, Poljak A, Wasinger V, Roy P, Moens PD. Profilin-1 overexpression in MDA-MB-231 breast cancer cells is associated with alterations in proteomics biomarkers of cell proliferation, survival, motility as revealed by global proteomics analyses. OMICS 18(12), 778-791 (2014).
128. Ding Z, Joy M, Bhargava R et al. Profilin-1 downregulation has contrasting effects on early vs late steps of breast cancer metastasis. Oncogene 33(16), 2065-2074 (2014).
129. Zou L, Ding Z, Roy P. Profilin-1 overexpression inhibits proliferation of MDA-MB-231 breast cancer cells partly through p27kip1 upregulation. J. Cell. Physiol. 223(3), 623-629 (2010).
130. Bae YH, Ding Z, Zou L, Wells A, Gertler F, Roy P. Loss of profilin-1 expression enhances breast cancer cell motility by Ena/VASP proteins. J. Cell. Physiol. 219(2), 354-364 (2009).
131. Sakwe AM, Koumangoye R, Guillory B, Ochieng J. Annexin A6 contributes to the invasiveness of breast carcinoma cells by influencing the organization and localization of functional focal adhesions. Exp. Cell. Res. 317(6), 823-837 (2011).
132. Karihtala P, Auvinen P, Kauppila S, Haapasaari KM, Jukkola-vuorinen A, Soini Y. Vimentin, zeb1 and Sip1 are up-regulated in triple-negative and basal-like breast cancers: association with an aggressive tumour phenotype. Breast Cancer Res. Treat. 138(1), 81-90 (2013).
133. Wu QW, Yang QM, Huang YF et al. Expression and clinical significance of matrix metalloproteinase-9 in lymphatic invasiveness and metastasis of breast cancer. PLoS ONE 9(5), e97804 (2014).
134. Heo DS, Choi H, Yeom MY, Song BJ, Oh SJ. Serum levels of matrix metalloproteinase-9 predict lymph node metastasis in breast cancer patients. Oncol. Rep. 31(4), 1567-1572 (2014).
135. Yousef EM, Tahir MR, St-Pierre Y, Gaboury LA. MMP-9 expression varies according to molecular subtypes of breast cancer. BMC Cancer 14(1), 609 (2014).
136. Liu NQ, Stingl C, Look MP et al. Comparative proteome analysis revealing an 11-protein signature for aggressive triple negative breast cancer. J. Natl Cancer Inst. 106(2), 376 (2014).
137. Schirosi L, De Summa S, Tommasi S et al. Immunoprofile from tissue microarrays to stratify familial breast cancer patients. Oncotarget 6(29), 27865-27879 (2015).
138. Tenori L, Oakman C, Morris PG et al. Serum metabolomic profiles evaluated after surgery may identify patients with oestrogen receptor negative early breast cancer at increased risk of disease recurrence. Results from a retrospective study. Mol. Oncol. 9(1), 128-139 (2015).
139. Kim SK, Jung WH, Koo JS. Differential expression of enzymes associated with serine/glycine metabolism in different breast cancer subtypes. PLoS ONE 9(6), e101004 (2014).
140. Antonov A, Agostini M, Morello M, Minieri M, Melino G, Amelio I. Bioinformatics analysis of the serine and glycine pathway in cancer cells. Oncotarget 5(22), 11004-11013 (2014).
141. Cao MD, Lamichhane S, Lundgren S et al. Metabolic characterization of triple negative breast cancer. BMC Cancer 14(1), 941 (2014).
142. Cui Y, Shu XO, Gao YT et al. Urinary prostaglandin E2 metabolite and breast cancer risk. Cancer Epidemiol. Biomarkers Prev. 23(12), 2866-2873 (2014).
143. Fawzy MS, Aly NM, Shalaby SM, El-Sawy WH, Abdul-Maksoud RS. Cyclooxygenase-2 169CG and 8473TC gene polymorphisms and prostaglandin E2 level in breast cancer: a case-control study. Gene 527(2), 601-605 (2013).
144. Budhu A, Terunuma A, Zhang G, Hussain SP, Ambs S, Wang XW. Metabolic profiles are principally different between cancers of the liver, pancreas and breast. Int. J. Biol. Sci. 10(9), 966-972 (2014).
145. Budczies J, Pfitzner BM, Györffy B et al. Glutamate enrichment as new diagnostic opportunity in breast cancer. Int. J. Cancer 136(7), 1619-1628 (2015).
146. Budczies J, Brockmöller SF, Müller BM et al. Comparative metabolomics of estrogen receptor positive and estrogen receptor negative breast cancer: alterations in glutamine and beta-alanine metabolism. J. Proteomics 94, 279-288 (2013).
147. Van geldermalsen M, Wang Q, Nagarajah R et al. ASCT2/SLC1A5 controls glutamine uptake and tumour growth in triple-negative basal-like breast cancer. Oncogene doi:10. 1038/onc. 2015. 381 (2015) (Epub ahead of print).
148. McGuirk S, Gravel SP, Deblois G et al. PGC-1 supports glutamine metabolism in breast cancer. Cancer Metab. 1(1), 22 (2013).
149. Drabovich AP, Pavlou MP, Dimitromanolakis A, Diamandis EP. Quantitative analysis of energy metabolic pathways in MCF-7 breast cancer cells by selected reaction monitoring assay. Mol. Cell. Proteomics 11(8), 422-434 (2012).
150. Reader J, Holt D, Fulton A. Prostaglandin E2 EP receptors as therapeutic targets in breast cancer. Cancer Metastasis Rev. 30(3-4), 449-463 (2011).
151. Yin K. Positive correlation between expression level of mitochondrial serine hydroxymethyltransferase and breast cancer grade. Onco Targets Ther. 8, 1069-1074 (2015).
152. Pesta M, Kulda V, Narsanska A, Fichtl J, Topolcan O. May CTC technologies promote better cancer management EPMA J. 6(1), 1 (2015).
153. Wallwiener M, Hartkopf AD, Baccelli I et al. The prognostic impact of circulating tumor cells in subtypes of metastatic breast cancer. Breast Cancer Res. Treat. 137(2), 503-510 (2013).
154. Pearl ML, Dong H, Tulley S et al. Treatment monitoring of patients with epithelial ovarian cancer using invasive circulating tumor cells (iCTCs). Gynecol. Oncol. 137(2), 229-238 (2015).
155. Torphy RJ, Tignanelli CJ, Kamande JW et al. Circulating tumor cells as a biomarker of response to treatment in patient-derived xenograft mouse models of pancreatic adenocarcinoma. PLoS ONE 9(2), e89474 (2014).
156. Hartkopf AD, Wagner P, Wallwiener D, Fehm T, Rothmund R. Changing levels of circulating tumor cells in monitoring chemotherapy response in patients with metastatic breast cancer. Anticancer Res. 31(3), 979-984 (2011).
157. Tinhofer I, Konschak R, Stromberger C et al. Detection of circulating tumor cells for prediction of recurrence after adjuvant chemoradiation in locally advanced squamous cell carcinoma of the head and neck. Ann. Oncol. 25(10), 2042-2047 (2014).
158. Beije N, Jager A, Sleijfer S. Circulating tumor cell enumeration by the CellSearch system: the clinician's guide to breast cancer treatment Cancer Treat. Rev. 41(2), 144-150 (2015).
159. Wang HY, Ahn S, Kim S et al. Detection of circulating tumor cells in patients with breast cancer using the quantitative RT-PCR assay for monitoring of therapy efficacy. Exp. Mol. Pathol. 97(3), 445-452 (2014).
160. Galletti G, Portella L, Tagawa ST, Kirby BJ, Giannakakou P, Nanus DM. Circulating tumor cells in prostate cancer diagnosis and monitoring: an appraisal of clinical potential. Mol. Diagn. Ther. 18(4), 389-402 (2014).
161. Resel Folkersma L, San José Manso L, Galante Romo I, Moreno Sierra J, Olivier Gómez C. Prognostic significance of circulating tumor cell count in patients with metastatic hormone-sensitive prostate cancer. Urology 80(6), 1328-1332 (2012).
162. Tognela A, Spring KJ, Becker T et al. Predictive and prognostic value of circulating tumor cell detection in lung cancer: a clinician's perspective. Crit. Rev. Oncol. Hematol. 93(2), 90-102 (2015).
163. Fu L, Liu F, Fu H et al. Circulating tumor cells correlate with recurrence in stage III small-cell lung cancer after systemic chemoradiotherapy and prophylactic cranial irradiation. Jpn J. Clin. Oncol. 44(10), 948-955 (2014).
164. Tsujiura M, Ichikawa D, Konishi H, Komatsu S, Shiozaki A, Otsuji E. Liquid biopsy of gastric cancer patients: circulating tumor cells and cell-free nucleic acids. World J. Gastroenterol. 20(12), 3265-3286 (2014).
165. Toyoshima K, Hayashi A, Kashiwagi M et al. Analysis of circulating tumor cells derived from advanced gastric cancer. Int. J. Cancer 137(4), 991-998 (2015).
166. Uenosono Y, Arigami T, Kozono T et al. Clinical significance of circulating tumor cells in peripheral blood from patients with gastric cancer. Cancer 119(22), 3984-3991 (2013).
167. Allard WJ, Matera J, Miller MC et al. Tumor cells circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases. Clin. Cancer Res. 10(20), 6897-6904 (2004).
168. Wallwiener M, Riethdorf S, Hartkopf AD et al. Serial enumeration of circulating tumor cells predicts treatment response and prognosis in metastatic breast cancer: a prospective study in 393 patients. BMC Cancer 14(1), 512 (2014).
169. Yokobori T, Iinuma H, Shimamura T et al. Plastin3 is a novel marker for circulating tumor cells undergoing the epithelial-mesenchymal transition and is associated with colorectal cancer prognosis. Cancer Res. 73(7), 2059-2069 (2013).
170. Ueo H, Sugimachi K, Gorges TM et al. Circulating tumour cell-derived plastin3 is a novel marker for predicting longterm prognosis in patients with breast cancer. Br. J. Cancer 112(9), 1519-1526 (2015).
171. Maltoni R, Fici P, Amadori D et al. Circulating tumor cells in early breast cancer: a connection with vascular invasion. Cancer Lett. 367(1), 43-48 (2015).
172. Nadal R, Ortega FG, Salido M et al. CD133 expression in circulating tumor cells from breast cancer patients: potential role in resistance to chemotherapy. Int. J. Cancer 133(10), 2398-2407 (2013).
173. Clarke MF, Dick JE, Dirks PB et al. Cancer stem cells-perspectives on current status and future directions: AACR Workshop on cancer stem cells. Cancer Res. 66(19), 9339-9344 (2006).
174. Mannello F. Understanding breast cancer stem cell heterogeneity: time to move on to a new research paradigm. BMC Med. 11(1), 169 (2013).
175. Al-hajj M, Becker MW, Wicha M, Weissman I, Clarke MF. Therapeutic implications of cancer stem cells. Curr. Opin. Genet. Dev. 14(1), 43-47 (2004).
176. Wicha MS. Cancer stem cells and metastasis: lethal seeds. Clin. Cancer Res. 12(19), 5606-7 (2006).
177. Visvader JE, Lindeman GJ. Cancer stem cells: current status and evolving complexities. Cell Stem Cell 10(6), 717-728 (2012).
178. Shackleton M, Quintana E, Fearon ER, Morrison SJ. Heterogeneity in cancer: cancer stem cells versus clonal evolution. Cell 138(5), 822-829 (2009).
179. Dick JE. Stem cell concepts renew cancer research. Blood 112(13), 4793-4807 (2008).
180. Chen X, Zhang J, Zhang Z, Li H, Cheng W, Liu J. Cancer stem cells, epithelial-mesenchymal transition, drug resistance in high-grade ovarian serous carcinoma. Hum. Pathol. 44(11), 2373-2384 (2013).
181. Li X, Lewis MT, Huang J et al. Intrinsic resistance of Wigenic breast cancer cells to chemotherapy. J. Natl Cancer Inst. 100(9), 672-679 (2008).
182. Chuthapisith S, Eremin J, El-Sheemey M, Eremin O. Breast cancer chemoresistance: emerging importance of cancer stem cells. Surg. Oncol. 19(1), 27-32 (2010).
183. Wang N, Wang Z, Peng C et al. Dietary compound isoliquiritigenin targets GRP78 to chemosensitize breast cancer stem cells via-catenin/ABCG2 signaling. Carcinogenesis 35(11), 2544-2554 (2014).
184. Wang Z, Wang N, Li W et al. Caveolin-1 mediates chemoresistance in breast cancer stem cells via-catenin/ABCG2 signaling pathway. Carcinogenesis 35(10), 2346-2356 (2014).
185. Saha S, Mukherjee S, Mazumdar M et al. Mithramycin A sensitizes therapy-resistant breast cancer stem cells toward genotoxic drug doxorubicin. Transl. Res. 165(5), 558-577 (2015).
186. Bozorgi A, Khazaei M, Khazaei MR. New findings on breast cancer stem cells: a review. J. Breast Cancer 18(4), 303-312 (2015).
187. Duru N, Fan M, Candas D et al. HER2-associated radioresistance of breast cancer stem cells isolated from HER2-negative breast cancer cells. Clin. Cancer Res. 18(24), 6634-6647 (2012).
188. Peitzsch C, Kurth I, Kunz-Schughart L, Baumann M, Dubrovska A. Discovery of the cancer stem cell related determinants of radioresistance. Radiother. Oncol. 108(3), 378-387 (2013).
189. Guo W. Concise review: breast cancer stem cells: regulatory networks, stem cell niches, disease relevance. Stem Cells Transl. Med. 3(8), 942-948 (2014).
190. Camerlingo R, Ferraro GA, De Francesco F et al. The role of CD44/low biomarker for screening, diagnosis and monitoring of breast cancer. Oncol. Rep. 31(3), 1127-1132 (2014).
191. Ricardo S, Vieira AF, Gerhard R et al. Breast cancer stem cell markers CD44, CD24 and ALDH1: expression distribution within intrinsic molecular subtype. J. Clin. Pathol. 64(11), 937-946 (2011).
192. Kang EJ, Jung H, Woo OH et al. Association of aldehyde dehydrogenase 1 expression and biologically aggressive features in breast cancer. Neoplasma 61(3), 352-362 (2014).
193. Yeghiazaryan K, Cebioglu M, Braun M, Kuhn W, Schild HH, Golubnitschaja O. Noninvasive subcellular imaging in breast cancer risk assessment: construction of diagnostic windows. Pers. Med. 8(3), 321-330 (2011).
194. Grech G, Zhan X, Yoo BC et al. EPMA position paper in cancer: current overview and future perspectives. EPMA J. 6(1), 9 (2015).
195. Golubnitschaja O, Costigliola V. General report & recommendations in predictive, preventive and personalised medicine 2012: white paper of the European Association for Predictive, Preventive and Personalised Medicine. EPMA J. 3(1), 14 (2012).