Repetitive Sequence Transcription in Breast Cancer: Comparison
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Please note this is a comparison between Version 2 by Vivi Li and Version 1 by Claudia Coronnello.

Repetitive sequences represent about half of the human genome. They are actively transcribed and play a role during development and in epigenetic regulation. The altered activity of repetitive sequences can lead to genomic instability and they can contribute to the establishment or the progression of degenerative diseases and cancer transformation. Increased levels of heterochromatic repetitive satellite-coded RNAs in mammary glands induce breast tumor formation in mice, altering the BRCA1-associated protein networks that are required for the proper stabilization of DNA replication forks that in turn lead to genomic instability. In humans, patients with breast cancer that express high levels of RNA derived from alpha satellite have an increased risk of developing multiple cancers.

  • breast cancer
  • repetitive sequences
  • HERV
  • endogenous retrovirus
  • satellite repeats
  • centromeres
  • telomeres
  • SVA
  • LINE1
  • transposons

1. Breast Cancer Classification

Breast cancer is still the leading cause of mortality among the female population in developed countries. In post-menopausal women, it accounts for 23% of all cancer deaths [1]. Breast cancers can be classified following anatomical, histological and molecular features [1], and their classification is a dynamic process, as stated in the last World Health Organization classification of tumors of the breast [2], and novel entities are added to the classification year by year following the increase in the knowledge of the disease [3]. Breast cancer is as a heterogeneous disease with different clinical and pathological features, variable therapeutic approaches and responses and with different outcomes even within the same class of breast cancer, suggesting that the current classifications are far from exhaustive. In order to follow the original classification of the cohort used in this sentudry [4[4][5],5], the breast cancer specimens have been classified as: luminal-A, luminal-B (HER2-negative), luminal-B (HER2-positive), HER2-enriched and triple-negative breast cancers. This classification is based on immunohistochemical-relevant markers and was recommended by the St. Gallen Expert Consensus [6] and it has become a standard in routine clinical analysis since then [6,7,8][6][7][8]. For detail reviews, please refer to Hennigs et al. [8] and Prat et al. [9].

2. Non-Coding RNA in Mammals

The mammalian genome is pervasively transcribed and only a small portion of the transcriptional output has protein-coding potential [10]. The non-coding RNAs (ncRNAs) can be categorized using sizes and function, such as small-nuclear RNAs (snRNAs), small-nucleolar RNAs (snoRNAs), long non-coding RNAs (lncRNAs) and many others. The most well-studied class of ncRNAs is probably represented by microRNAs (miRNAs). Many studies have identified or suggested their role in human health and diseases, aging [11], cancer [12[12][13],13], diagnostic or prognostic purposes [14,15][14][15] and as therapeutic agents [16], either per se or in complex networks of cross regulation by the name of competing endogenous RNAs (ceRNAs) [17,18,19,20,21,22,23,24][17][18][19][20][21][22][23][24]. An abundant class of ncRNAs with variable functions that are still not fully understood is represented by transcripts arising from non-coding DNA sequences that are repeated along the genome in multiple copies. Even if the transcription from a single copy can be negligible, the sum of transcripts arising from thousands or millions of copies can be massive. A detailed description of them is given in the following paragraphs.

3. Repetitive DNA Sequence Classification

A multifaceted category of ncRNAs, of growing interest due to their roles in human health and diseases, is represented by the transcripts arising from repetitive DNA sequences (RS), i.e., DNA sequences that are present in multiple copies in the genomes, with low or nonexistent coding potential. RS represent about 45% of the human genome and are differentially transcribed in many tissues [25]. In mammals, RS have many roles in development and epigenetic regulation, but also in diseases such as cancer transformation [26,27,28,29,30][26][27][28][29][30] and degenerative diseases [31], but they are notoriously difficult to study [32]. Due to their nature, length and origin, RS can be roughly classified as: (i) Satellite repeats: a tandem array of simple or complex sequence repeats, abundant in heterochromatic regions, including alpha satellite repeats that represent the main DNA component of human centromeres. (ii) Long interspersed nuclear elements (LINEs): retrotransposons devoid of long terminal repeats (non-LTR) including some that are still able to retrotranspose. (iii) Small interspersed nuclear elements (SINEs): non-autonomous retrotransposons including the Alu elements in humans, which are often involved in genomic rearrangements. (iv) Integrated LTR retroviruses, mainly represented by the human endogenous retrovirus (HERV) families. (v) Additionally, the families of DNA transposons, that are usually not active in humans (Figure 1). The role of RS is starting to be properly understood. E.g., in the human brain LINE-1 retrotransposons are actively transcribed and mobilized and they are suggested to play a role in shaping the adult human brain [33], there is also a suggested role of RS in a model of aging of human brain [34].

4. Repetitive DNA Sequence and Cancer

Increased levels of heterochromatic repetitive satellite-coded RNAs in mammary glands induce breast tumor formation in mice, altering the BRCA1-associated protein networks that are required for the proper stabilization of DNA replication forks that in turn lead to genomic instability [35]. In humans, patients with breast cancer that express high levels of RNA derived from alpha satellite have an increased risk of developing multiple cancers [36].
It is known that LINE-1-encoded retrotranscription activity is widespread and its inhibition can reduce the rate of proliferation and promote the differentiation of breast cancer cells [37]. LINE-1 (and Alu) hypomethylation, suggesting an increased transcription in cancer cells and thus their mobilization, has been associated with the HER2-enriched subtype of breast cancer with worst prognosis [38,39,40][38][39][40]. In the transgenic mice of a well-defined model of breast cancer progression, LINE-1 is upregulated at a very early stage of tumorigenesis [41]. Indeed, the altered expression patterns of LINE-1-coded ORF1 and ORF2 proteins, with differences in overall patient survival, have been reported in invasive breast cancers [42]. In specific cases, pesticide exposure induces LINE-1 reactivation, suggesting the role of LINE transcription in pesticide-induced breast cancer progression [43], and MET-LINE-1 chimeric transcripts identify a subgroup of aggressive triple-negative breast cancers [44]. Overall, it has been suggested that LINE-1 may contribute to the origin or progression of breast cancers [45].
There are many reports regarding Alu and other SINE elements within or surrounding BRCA1 and BRCA2 genes essential to genomic rearrangements or genetic mutations leading to etiopathogenic, prognostic or predisposing mutations of breast cancers, both in somatic and germ lines [46,47,48,49,50,51][46][47][48][49][50][51]; indeed, the demethylation of Alu sequences may induce, at the same time, both transcription and rearrangements of Alu sequences. Thus, Alu transcription is a marker of increased susceptibility to Alu-mediated genomic rearrangement or genetic mutation at Alu sites. Looking for a direct effect of Alu transcription, it is noteworthy that heterogeneous nuclear ribonucleoprotein C (HNRNPC) is essential in breast cancer cell survival by inhibiting the double-stranded-RNA (dsRNA)-induced interferon response. Indeed, dsRNA in this setting is highly enriched in Alu sequences [52], suggesting that an overexpression of Alu sequences is characteristic of many breast cancers and may have lethal effects in cancer cells if not controlled.
There is significant evidence regarding the use of HERV-K-coded proteins as tumor markers and immunologic targets [52,53,54,55,56,57,58][52][53][54][55][56][57][58] and in influencing cancer stemness [59]. It has even been suggested that they could act as etiological agents [60,61][60][61]. Indeed, the expression of HERV-K is upregulated and associated with the basal-like breast cancer phenotype [62] and a HERV-derived long non-coding RNAs (namely, TROJAN) promotes triple-negative breast cancer progression [63]. HERV can directly contribute to cancer progression by activating the ERK pathway and inducing migration and invasion [64]; it has been even suggested that the activation of HERV-K may be essential for the tumorigenesis and metastasis of breast cancer [65]. Indeed, HERV-K-derived RNAs and antibodies against HERV-K-coded proteins are elevated in the blood of patients at an early stage of breast cancer [66].
DNA transposons are the less active and less well-studied class of RS in humans. Nevertheless, few reports suggest their role in breast cancer [67]; however, they were not investigated further. In addition, a mechanism of BRCA1 mutation in three unrelated French breast/ovarian cancer families, that can be generated by an abortive integration of the human Tigger1 DNA transposon, has been postulated [68].
Cells 11 02522 g001 550
Figure 1. Repetitive sequences (RS) represent about half of the human genome. The panel reports RS activities associated with breast cancer. In orange: Satellite repeats [35,36][35][36]. In red: Long interspersed nuclear elements (LINEs) [37,42,45][37][42][45]. In yellow: Small interspersed nuclear elements (SINEs) [46,47,48,49,50,51][46][47][48][49][50][51]. In blue: Human endogenous retrovirus (HERV) [62,63,64,66][62][63][64][66]. In green: DNA transposons [68].

References

  1. Akram, M.; Iqbal, M.; Daniyal, M.; Khan, A.U. Awareness and Current Knowledge of Breast Cancer. Biol. Res. 2017, 50, 33.
  2. Tan, P.H.; Ellis, I.; Allison, K.; Brogi, E.; Fox, S.B.; Lakhani, S.; Lazar, A.J.; Morris, E.A.; Sahin, A.; Salgado, R.; et al. The 2019 World Health Organization Classification of Tumours of the Breast. Histopathology 2020, 77, 181–185.
  3. Di Napoli, A.; Jain, P.; Duranti, E.; Margolskee, E.; Arancio, W.; Facchetti, F.; Alobeid, B.; Santanelli di Pompeo, F.; Mansukhani, M.; Bhagat, G. Targeted next Generation Sequencing of Breast Implant-Associated Anaplastic Large Cell Lymphoma Reveals Mutations in JAK/STAT Signalling Pathway Genes, TP53 and DNMT3A. Br. J. Haematol. 2018, 180, 741–744.
  4. Xu, S.; Kong, D.; Chen, Q.; Ping, Y.; Pang, D. Oncogenic Long Noncoding RNA Landscape in Breast Cancer. Mol. Cancer 2017, 16, 129.
  5. Pang, B.; Wang, Q.; Ning, S.; Wu, J.; Zhang, X.; Chen, Y.; Xu, S. Landscape of Tumor Suppressor Long Noncoding RNAs in Breast Cancer. J. Exp. Clin. Cancer Res. 2019, 38, 79.
  6. Goldhirsch, A.; Wood, W.C.; Coates, A.S.; Gelber, R.D.; Thürlimann, B.; Senn, H.J. Strategies for Subtypes-Dealing with the Diversity of Breast Cancer: Highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann. Oncol. 2011, 22, 1736–1747.
  7. Goldhirsch, A.; Winer, E.P.; Coates, A.S.; Gelber, R.D.; Piccart-Gebhart, M.; Thürlimann, B.; Senn, H.J.; Albain, K.S.; André, F.; Bergh, J.; et al. Personalizing the Treatment of Women with Early Breast Cancer: Highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann. Oncol. 2013, 24, 2206–2223.
  8. Hennigs, A.; Riedel, F.; Gondos, A.; Sinn, P.; Schirmacher, P.; Marmé, F.; Jäger, D.; Kauczor, H.U.; Stieber, A.; Lindel, K.; et al. Prognosis of Breast Cancer Molecular Subtypes in Routine Clinical Care: A Large Prospective Cohort Study. BMC Cancer 2016, 16, 734.
  9. Prat, A.; Pineda, E.; Adamo, B.; Galván, P.; Fernández, A.; Gaba, L.; Díez, M.; Viladot, M.; Arance, A.; Muñoz, M. Clinical Implications of the Intrinsic Molecular Subtypes of Breast Cancer. Breast 2015, 24, S26–S35.
  10. Clark, M.B.; Amaral, P.P.; Schlesinger, F.J.; Dinger, M.E.; Taft, R.J.; Rinn, J.L.; Ponting, C.P.; Stadler, P.F.; Morris, K.V.; Morillon, A.; et al. The Reality of Pervasive Transcription. PLoS Biol. 2011, 9, e1000625.
  11. Arancio, W.; Coronnello, C. Repetitive Sequences in Aging. Aging 2021, 13, 10816–10817.
  12. Hirschberger, S.; Hinske, L.C.; Kreth, S. MiRNAs: Dynamic Regulators of Immune Cell Functions in Inflammation and Cancer. Cancer Lett. 2018, 431, 11–21.
  13. Li, M.; Cui, X.; Guan, H. MicroRNAs: Pivotal Regulators in Acute Myeloid Leukemia. Ann. Hematol. 2020, 99, 399–412.
  14. Liu, J.; Ke, F.; Chen, T.; Zhou, Q.; Weng, L.; Tan, J.; Shen, W.; Li, L.; Zhou, J.; Xu, C.; et al. MicroRNAs That Regulate PTEN as Potential Biomarkers in Colorectal Cancer: A Systematic Review. J. Cancer Res. Clin. Oncol. 2020, 146, 809–820.
  15. Arancio, W.; Calogero Amato, M.; Magliozzo, M.; Pizzolanti, G.; Vesco, R.; Giordano, C. Serum MiRNAs in Women Affected by Hyperandrogenic Polycystic Ovary Syndrome: The Potential Role of MiR-155 as a Biomarker for Monitoring the Estroprogestinic Treatment. Gynecol. Endocrinol. 2018, 34, 704–708.
  16. Hashemi, A.; Gorji-bahri, G. MicroRNA: Promising Roles in Cancer Therapy. Curr. Pharm. Biotechnol. 2020, 21, 1186–1203.
  17. Lou, W.; Ding, B.; Fu, P. Pseudogene-Derived LncRNAs and Their MiRNA Sponging Mechanism in Human Cancer. Front. Cell Dev. Biol. 2020, 8, 85.
  18. Arancio, W.; Carina, V.; Pizzolanti, G.; Tomasello, L.; Pitrone, M.; Baiamonte, C.; Amato, M.C.; Giordano, C. Anaplastic Thyroid Carcinoma: A CeRNA Analysis Pointed to a Crosstalk between SOX2, TP53, and MicroRNA Biogenesis. Int. J. Endocrinol. 2015, 2015, 439370.
  19. Poliseno, L.; Pandolfi, P.P. PTEN CeRNA Networks in Human Cancer. Methods 2015, 77–78, 41–50.
  20. Arancio, W.; Genovese, S.I.; Bongiovanni, L.; Tripodo, C. A CeRNA Approach May Unveil Unexpected Contributors to Deletion Syndromes, the Model of 5q-Syndrome. Oncoscience 2015, 2, 872–879.
  21. Arancio, W.; Giordano, C.; Pizzolanti, G. A CeRNA Analysis on LMNA Gene Focusing on the Hutchinson-Gilford Progeria Syndrome. J. Clin. Bioinform. 2013, 3, 2.
  22. Arancio, W. A Bioinformatics Analysis of Lamin-A Regulatory Network: A Perspective on Epigenetic Involvement in Hutchinson-Gilford Progeria Syndrome. Rejuvenation Res. 2012, 15, 123–127.
  23. Arancio, W. CeRNA Analysis of SARS-CoV-2. Arch. Virol. 2021, 166, 271–274.
  24. Bertolazzi, G.; Cipollina, C.; Benos, P.V.; Tumminello, M.; Coronnello, C. MiR-1207-5p Can Contribute to Dysregulation of Inflammatory Response in COVID-19 via Targeting SARS-CoV-2 RNA. Front. Cell. Infect. Microbiol. 2020, 10, 586592.
  25. Faulkner, G.J.; Kimura, Y.; Daub, C.O.; Wani, S.; Plessy, C.; Irvine, K.M.; Schroder, K.; Cloonan, N.; Steptoe, A.L.; Lassmann, T.; et al. The Regulated Retrotransposon Transcriptome of Mammalian Cells. Nat. Genet. 2009, 41, 563–571.
  26. Clayton, E.A.; Wang, L.; Rishishwar, L.; Wang, J.; McDonald, J.F.; Jordan, I.K. Patterns of Transposable Element Expression and Insertion in Cancer. Front. Mol. Biosci. 2016, 3, 76.
  27. Sciamanna, I.; De Luca, C.; Spadafora, C. The Reverse Transcriptase Encoded by LINE-1 Retrotransposons in the Genesis, Progression, and Therapy of Cancer. Front. Chem. 2016, 4, 6.
  28. Ohms, S.; Lee, S.H.; Rangasamy, D. LINE-1 Retrotransposons and Let-7 MiRNA: Partners in the Pathogenesis of Cancer? Front. Genet. 2014, 5, 338.
  29. Tubio, J.M.C.; Li, Y.; Ju, Y.S.; Martincorena, I.; Cooke, S.L.; Tojo, M.; Gundem, G.; Pipinikas, C.P.; Zamora, J.; Raine, K.; et al. Extensive Transduction of Nonrepetitive DNA Mediated by L1 Retrotransposition in Cancer Genomes. Science 2014, 345, 1251343.
  30. Di Ruocco, F.; Basso, V.; Rivoire, M.; Mehlen, P.; Ambati, J.; De Falco, S.; Tarallo, V. Alu RNA Accumulation Induces Epithelial-to-Mesenchymal Transition by Modulating MiR-566 and Is Associated with Cancer Progression. Oncogene 2018, 37, 627–637.
  31. Padeken, J.; Zeller, P.; Gasser, S.M. Repeat DNA in Genome Organization and Stability. Curr. Opin. Genet. Dev. 2015, 31, 12–19.
  32. Treangen, T.J.; Salzberg, S.L. Repetitive DNA and Next-Generation Sequencing: Computational Challenges and Solutions. Nat. Rev. Genet. 2012, 13, 36–46.
  33. Coufal, N.G.; Garcia-Perez, J.L.; Peng, G.E.; Yeo, G.W.; Mu, Y.; Lovci, M.T.; Morell, M.; O’Shea, K.S.; Moran, J.V.; Gage, F.H. L1 Retrotransposition in Human Neural Progenitor Cells. Nature 2009, 460, 1127–1131.
  34. Arancio, W. Progerin Expression Induces a Significant Downregulation of Transcription from Human Repetitive Sequences in IPSC-Derived Dopaminergic Neurons. GeroScience 2019, 41, 39–49.
  35. Zhu, Q.; Hoong, N.; Aslanian, A.; Hara, T.; Benner, C.; Heinz, S.; Miga, K.H.; Ke, E.; Verma, S.; Soroczynski, J.; et al. Heterochromatin-Encoded Satellite RNAs Induce Breast Cancer. Mol. Cell 2018, 70, 842–853.e7.
  36. Kakizawa, N.; Suzuki, K.; Abe, I.; Endo, Y.; Tamaki, S.; Ishikawa, H.; Watanabe, F.; Ichida, K.; Saito, M.; Futsuhara, K.; et al. High Relative Levels of Satellite Alpha Transcripts Predict Increased Risk of Bilateral Breast Cancer and Multiple Primary Cancer in Patients with Breast Cancer and Lacking BRCA-Related Clinical Features. Oncol. Rep. 2019, 42, 857–865.
  37. Patnala, R.; Lee, S.H.; Dahlstrom, J.E.; Ohms, S.; Chen, L.; Dheen, S.T.; Rangasamy, D. Inhibition of LINE-1 Retrotransposon-Encoded Reverse Transcriptase Modulates the Expression of Cell Differentiation Genes in Breast Cancer Cells. Breast Cancer Res. Treat. 2014, 143, 239–253.
  38. Park, S.Y.; Seo, A.N.; Jung, H.Y.; Gwak, J.M.; Jung, N.; Cho, N.Y.; Kang, G.H. Alu and LINE-1 Hypomethylation Is Associated with HER2 Enriched Subtype of Breast Cancer. PLoS ONE 2014, 9, e100429.
  39. Van Hoesel, A.Q.; Van De Velde, C.J.H.; Kuppen, P.J.K.; Liefers, G.J.; Putter, H.; Sato, Y.; Elashoff, D.A.; Turner, R.R.; Shamonki, J.M.; De Kruijf, E.M.; et al. Hypomethylation of LINE-1 in Primary Tumor Has Poor Prognosis in Young Breast Cancer Patients: A Retrospective Cohort Study. Breast Cancer Res. Treat. 2012, 134, 1103–1114.
  40. Harris, C.R.; Normart, R.; Yang, Q.; Stevenson, E.; Haffty, B.G.; Ganesan, S.; Cordon-Cardo, C.; Levine, A.J.; Tang, L.H. Association of Nuclear Localization of a Long Interspersed Nuclear Element-1 Protein in Breast Tumors with Poor Prognostic Outcomes. Genes and Cancer 2010, 1, 115–124.
  41. Gualtieri, A.; Andreola, F.; Sciamanna, I.; Sinibaldi-Vallebona, P.; Serafino, A.; Spadafora, C. Increased Expression and Copy Number Amplification of LINE-1 and SINE B1 Retrotransposable Elements in Murine Mammary Carcinoma Progression. Oncotarget 2013, 4, 1882–1893.
  42. Chen, L.; Dahlstrom, J.E.; Chandra, A.; Board, P.; Rangasamy, D. Prognostic Value of LINE-1 Retrotransposon Expression and Its Subcellular Localization in Breast Cancer. Breast Cancer Res. Treat. 2012, 136, 129–142.
  43. Miret, N.; Zappia, C.D.; Altamirano, G.; Pontillo, C.; Zárate, L.; Gómez, A.; Lasagna, M.; Cocca, C.; Kass, L.; Monczor, F.; et al. AhR Ligands Reactivate LINE-1 Retrotransposon in Triple-Negative Breast Cancer Cells MDA-MB-231 and Non-Tumorigenic Mammary Epithelial Cells NMuMG. Biochem. Pharmacol. 2020, 175, 113904.
  44. Miglio, U.; Berrino, E.; Panero, M.; Ferrero, G.; Coscujuela Tarrero, L.; Miano, V.; Dell’Aglio, C.; Sarotto, I.; Annaratone, L.; Marchiò, C.; et al. The Expression of LINE1-MET Chimeric Transcript Identifies a Subgroup of Aggressive Breast Cancers. Int. J. Cancer 2018, 143, 2838–2848.
  45. Bratthauer, G.L.; Cardiff, R.D.; Fanning, T.G. Expression of LINE-1 Retrotransposons in Human Breast Cancer. Cancer 1994, 73, 2333–2336.
  46. Wang, Y.; Bernhardy, A.J.; Nacson, J.; Krais, J.J.; Tan, Y.F.; Nicolas, E.; Radke, M.R.; Handorf, E.; Llop-Guevara, A.; Balmaña, J.; et al. BRCA1 Intronic Alu Elements Drive Gene Rearrangements and PARP Inhibitor Resistance. Nat. Commun. 2019, 10, 5661.
  47. Staaf, J.; Glodzik, D.; Bosch, A.; Vallon-Christersson, J.; Reuterswärd, C.; Häkkinen, J.; Degasperi, A.; Amarante, T.D.; Saal, L.H.; Hegardt, C.; et al. Whole-Genome Sequencing of Triple-Negative Breast Cancers in a Population-Based Clinical Study. Nat. Med. 2019, 25, 1526–1533.
  48. Felicio, P.S.; Alemar, B.; Coelho, A.S.; Berardinelli, G.N.; Melendez, M.E.; Lengert, A.V.H.; Miche lli, R.D.; Reis, R.M.; Fernandes, G.C.; Ewald, I.P.; et al. Screening and Characterization of BRCA2 c.156_157insAlu in Brazil: Results from 1380 Individuals from the South and Southeast. Cancer Genet. 2018, 228–229, 93–97.
  49. Rizza, R.; Hackmann, K.; Paris, I.; Minucci, A.; De Leo, R.; Schrock, E.; Urbani, A.; Capoluongo, E.; Gelli, G.; Concolino, P. Novel BRCA1 Large Genomic Rearrangements in Italian Breast/Ovarian Cancer Patients. Mol. Diagnosis Ther. 2019, 23, 121–126.
  50. Gallegos-Arreola, M.P.; Figuera, L.E.; Flores-Ramos, L.G.; Puebla-Pérez, A.M.; Zúñiga-González, G.M. Association of the Alu Insertion Polymorphism in the Progesterone Receptor Gene with Breast Cancer in a Mexican Population. Arch. Med. Sci. 2015, 11, 551–560.
  51. Machado, P.M.; Brandão, R.D.; Cavaco, B.M.; Eugénio, J.; Bento, S.; Nave, M.; Rodrigues, P.; Fernandes, A.; Vaz, F. Screening for a BRCA2 Rearrangement in High-Risk Breast/Ovarian Cancer Families: Evidence for a Founder Effect and Analysis of the Associated Phenotypes. J. Clin. Oncol. 2007, 25, 2027–2034.
  52. Wu, Y.; Zhao, W.; Liu, Y.; Tan, X.; Li, X.; Zou, Q.; Xiao, Z.; Xu, H.; Wang, Y.; Yang, X. Function of HNRNPC in Breast Cancer Cells by Controlling the DsRNA-induced Interferon Response. EMBO J. 2018, 37, e99017.
  53. Grabski, D.F.; Hu, Y.; Sharma, M.; Rasmussen, S.K. Close to the Bedside: A Systematic Review of Endogenous Retroviruses and Their Impact in Oncology. J. Surg. Res. 2019, 240, 145–155.
  54. Zhao, J.; Rycaj, K.; Geng, S.; Li, M.; Plummer, J.B.; Yin, B.; Liu, H.; Xu, X.; Zhang, Y.; Yan, Y.; et al. Expression of Human Endogenous Retrovirus Type K Envelope Protein Is a Novel Candidate Prognostic Marker for Human Breast Cancer. Genes Cancer 2011, 2, 914–922.
  55. Wang-Johanning, F.; Radvanyi, L.; Rycaj, K.; Plummer, J.B.; Yan, P.; Sastry, K.J.; Piyathilake, C.J.; Hunt, K.K.; Johanning, G.L. Human Endogenous Retrovirus K Triggers an Antigen-Specific Immune Response in Breast Cancer Patients. Cancer Res. 2008, 68, 5869–5877.
  56. Golan, M.; Hizi, A.; Resau, J.H.; Yaal-Hahoshen, N.; Reichman, H.; Keydar, I.; Tsarfaty, I. Human Endogenous Retrovirus (HERV-K) Reverse Transcriptase as a Breast Cancer Prognostic Marker. Neoplasia 2008, 10, 521–533.
  57. Wang-Johanning, F.; Frost, A.R.; Jian, B.; Epp, L.; Lu, D.W.; Johanning, G.L. Quantitation of HERV-K Env Gene Expression and Splicing in Human Breast Cancer. Oncogene 2003, 22, 1528–1535.
  58. Wang-Johanning, F.; Frost, A.R.; Johanning, G.L.; Khazaeli, M.B.; LoBuglio, A.F.; Shaw, D.R.; Strong, T.V. Expression of Human Endogenous Retrovirus K Envelope Transcripts in Human Breast Cancer. Clin. Cancer Res. 2001, 7, 1553–1560.
  59. Matteucci, C.; Balestrieri, E.; Argaw-Denboba, A.; Sinibaldi-Vallebona, P. Human Endogenous Retroviruses Role in Cancer Cell Stemness. Semin. Cancer Biol. 2018, 53, 17–30.
  60. Salmons, B.; Lawson, J.S.; Günzburg, W.H. Recent Developments Linking Retroviruses to Human Breast Cancer: Infectious Agent, Enemy within or Both? J. Gen. Virol. 2014, 95, 2589–2593.
  61. Nguyen, T.D.; Davis, J.; Eugenio, R.A.; Liu, Y. Female Sex Hormones Activate Human Endogenous Retrovirus Type K Through the OCT4 Transcription Factor in T47D Breast Cancer Cells. AIDS Res. Hum. Retrovir. 2019, 35, 348–356.
  62. Johanning, G.L.; Malouf, G.G.; Zheng, X.; Esteva, F.J.; Weinstein, J.N.; Wang-Johanning, F.; Su, X. Expression of Human Endogenous Retrovirus-K Is Strongly Associated with the Basal-like Breast Cancer Phenotype. Sci. Rep. 2017, 7, 41960.
  63. Jin, X.; Xu, X.E.; Jiang, Y.Z.; Liu, Y.R.; Sun, W.; Guo, Y.J.; Ren, Y.X.; Zuo, W.J.; Hu, X.; Huang, S.L.; et al. The Endogenous Retrovirus-Derived Long Noncoding RNA TROJAN Promotes Triple-Negative Breast Cancer Progression via ZMYND8 Degradation. Sci. Adv. 2019, 5, eaat9820.
  64. Lemaître, C.; Tsang, J.; Bireau, C.; Heidmann, T.; Dewannieux, M. A Human Endogenous Retrovirus-Derived Gene That Can Contribute to Oncogenesis by Activating the ERK Pathway and Inducing Migration and Invasion. PLoS Pathog. 2017, 13, e1006451.
  65. Zhou, F.; Li, M.; Wei, Y.; Lin, K.; Lu, Y.; Shen, J.; Johanning, G.L.; Wang-Johanning, F. Activation of HERV-K Env Protein Is Essential for Tumorigenesis and Metastasis of Breast Cancer Cells. Oncotarget 2016, 7, 84093–84117.
  66. Wang-Johanning, F.; Li, M.; Esteva, F.J.; Hess, K.R.; Yin, B.; Rycaj, K.; Plummer, J.B.; Garza, J.G.; Ambs, S.; Johanning, G.L. Human Endogenous Retrovirus Type K Antibodies and MRNA as Serum Biomarkers of Early-Stage Breast Cancer. Int. J. Cancer 2014, 134, 587–595.
  67. Jiang, J.C.; Upton, K.R. Human Transposons Are an Abundant Supply of Transcription Factor Binding Sites and Promoter Activities in Breast Cancer Cell Lines. Mob. DNA 2019, 10, 16.
  68. Presneau, N.; Laplace-Marieze, V.; Sylvain, V.; Lortholary, A.; Hardouin, A.; Bernard-Gallon, D.; Bignon, Y.J. New Mechanism of BRCA-1 Mutation by Deletion/Insertion at the Same Nucleotide Position in Three Unrelated French Breast/Ovarian Cancer Families. Hum. Genet. 1998, 103, 334–339.
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