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Breast Cancer Research
Published in: Breast Cancer Research 1/2022

Open Access 01-12-2022 | Breast Cancer | Research

Krüppel-like factor 7 influences translation and pathways involved in ribosomal biogenesis in breast cancer

Authors: Anne-Marie Lüchtenborg, Patrick Metzger, Miguel Cosenza Contreras, Victor Oria, Martin L. Biniossek, Franziska Lindner, Klemens Fröhlich, Ambrus Malyi, Thalia Erbes, Nicole Gensch, Jochen Maurer, Andreas Thomsen, Melanie Boerries, Oliver Schilling, Martin Werner, Peter Bronsert

Published in: Breast Cancer Research | Issue 1/2022

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Abstract

Background

Ribosomal biogenesis and ribosomal proteins have attracted attention in the context of tumor biology in recent years. Instead of being mere translational machineries, ribosomes might play an active role in tumor initiation and progression. Despite its importance, regulation of ribosomal biogenesis is still not completely understood.

Methods

Using Gene Set Enrichment Analysis of RNA sequencing and proteomical mass spectrometry data in breast cancer cells expressing Krüppel-like factor 7 (KLF7), we identified processes altered by this transcription factor. In silico analyses of a cohort of breast cancer patients in The Cancer Genome Atlas confirmed our finding. We further verified the role of KLF7 the identified ribosomal processes in in vitro assays of mammary carcinoma cell lines and analyses of breast cancer patients’ tissue slices.

Results

We identified the transcription factor Krüppel-like factor 7 (KLF7) as a regulator of ribosomal biogenesis and translation in breast cancer cells and tissue. Highly significant overlapping processes related to ribosomal biogenesis were identified in proteomics and transcriptomics data and confirmed in patients’ breast cancer RNA Seq data. Further, nucleoli, the sites of ribosomal biogenesis, were morphologically altered and quantitatively increased in KLF7-expressing cells. Pre-rRNA processing was identified as one potential process affected by KLF7. In addition, an increase in global translation independent from proliferation and transcription was observed upon exogenous KLF7 expression in vitro. Importantly, in a cohort of breast cancer patients, KLF7-expression levels correlated with aggressiveness of the intrinsic breast cancer subtype and tumor grading. Moreover, KLF7 correlated with nucleolar characteristics in human breast tumor tissue, indicating a role for KLF7 in ribosomal biogenesis.

Conclusion

In mammary carcinoma, KLF7 is involved in ribosomal biogenesis. Alterations of ribosomal biogenesis has far reaching quantitative and qualitative implications for the proteome of the cancer cells. This might influence the aggressiveness of cancer cells.
Appendix
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Literature
1.
Li CH, Karantza V, Aktan G, Lala M. Current treatment landscape for patients with locally recurrent inoperable or metastatic triple-negative breast cancer: a systematic literature review. Breast Cancer Res. 2019;21:1–14.CrossRef
2.
Sulima SO, Kampen KR, Vereecke S, Pepe D, Fancello L, Verbeeck J, et al. Ribosomal lesions promote oncogenic mutagenesis. Cancer Res. 2019;79:320–7.PubMedCrossRef
3.
Pelletier J, Thomas G, Volarević S. Ribosome biogenesis in cancer: new players and therapeutic avenues. Nat Rev Cancer. 2018;18:51–63.PubMedCrossRef
4.
Shi Z, Fujii K, Kovary KM, Genuth NR, Röst HL, Teruel MN, et al. Heterogeneous ribosomes preferentially translate distinct subpools of mRNAs genome-wide. Mol Cell. 2017;67:71-83.e7.PubMedPubMedCentralCrossRef
5.
6.
Yakhni M, Briat A, El Guerrab A, Furtado L, Kwiatkowski F, Miot-Noirault E, et al. Homoharringtonine, an approved anti-leukemia drug, suppresses triple negative breast cancer growth through a rapid reduction of anti-apoptotic protein abundance. Am J Cancer Res. 2019;9:1043–60.PubMedPubMedCentral
7.
Derenzini M, Montanaro L, Treré D. What the nucleolus says to a tumour pathologist. Histopathology. 2009;54:753–62.PubMedCrossRef
8.
Fuhrman SA, Lasky LC, Limas C. Prognostic significance of morphologic parameters in renal cell carcinoma. Am J Surg Pathol. 1982;6:655–63.PubMedCrossRef
9.
Kondrashov N, Pusic A, Stumpf CR, Shimizu K, Hsieh AC, Xue S, et al. Ribosome-mediated specificity in Hox mRNA translation and vertebrate tissue patterning. Cell. 2011;145:383–97.PubMedPubMedCentralCrossRef
10.
Orsolic I, Jurada D, Pullen N, Oren M, Eliopoulos AG, Volarevic S. The relationship between the nucleolus and cancer: current evidence and emerging paradigms. Semin Cancer Biol. 2016;37–38:36–50.PubMedCrossRef
11.
Draptchinskaia N, Gustavsson P, Andersson B, Pettersson M, Willig T-N, Dianzani I, et al. The gene encoding ribosomal protein S19 is mutated in Diamond-Blackfan anaemia. Nat Genet. 1999;21:169–75.PubMedCrossRef
12.
13.
Dave B, Granados-Principal S, Zhu R, Benz S, Rabizadeh S, Soon-Shiong P, et al. Targeting RPL39 and MLF2 reduces tumor initiation and metastasis in breast cancer by inhibiting nitric oxide synthase signaling. PNAS. 2014;111:8838–43.PubMedPubMedCentralCrossRef
14.
Fang E, Zhang X. Identification of breast cancer hub genes and analysis of prognostic values using integrated bioinformatics analysis. Cancer Biomark. 2017;21:373–81.PubMedCrossRef
15.
Dave B, Gonzalez DD, Liu Z-B, Li X, Wong H, Granados S, et al. Role of RPL39 in metaplastic breast cancer. J Natl Cancer Inst. 2017;109:djw292.PubMedCentralCrossRef
16.
Fancello L, Kampen KR, Hofman IJF, Verbeeck J, Keersmaecker KD. The ribosomal protein gene RPL5 is a haploinsufficient tumor suppressor in multiple cancer types. Oncotarget. 2017;8:14462–78.PubMedPubMedCentralCrossRef
17.
Ebright RY, Lee S, Wittner BS, Niederhoffer KL, Nicholson BT, Bardia A, et al. Deregulation of ribosomal protein expression and translation promotes breast cancer metastasis. Science. 2020;367:1468–73.PubMedPubMedCentralCrossRef
18.
Guimaraes JC, Zavolan M. Patterns of ribosomal protein expression specify normal and malignant human cells. Genome Biol. 2016;17:1–13.CrossRef
19.
20.
Gupta R, Malvi P, Parajuli KR, Janostiak R, Bugide S, Cai G, et al. KLF7 promotes pancreatic cancer growth and metastasis by up-regulating ISG expression and maintaining Golgi complex integrity. PNAS Natl Acad Sci. 2020;117:12341–51.CrossRef
21.
Yang J, Xie K, Wang Z, Li C. Elevated KLF7 levels may serve as a prognostic signature and might contribute to progression of squamous carcinoma. FEBS Open Bio. 2020;10:1577–86.PubMedPubMedCentralCrossRef
22.
Pontén F, Jirström K, Uhlen M. The Human Protein Atlas—a tool for pathology. J Pathol. 2008;216:387–93.PubMedCrossRef
23.
Kajimura D, Dragomir C, Ramirez F, Laub F. Identification of genes regulated by transcription factor KLF7 in differentiating olfactory sensory neurons. Gene. 2007;388:34–42.PubMedCrossRef
24.
Laub F, Lei L, Sumiyoshi H, Kajimura D, Dragomir C, Smaldone S, et al. Transcription factor KLF7 is important for neuronal morphogenesis in selected regions of the nervous system. Mol Cell Biol. 2005;25:5699–711.PubMedPubMedCentralCrossRef
25.
Schuettpelz LG, Gopalan PK, Giuste FO, Romine MP, van Os R, Link DC. Kruppel-like factor 7 overexpression suppresses hematopoietic stem and progenitor cell function. Blood. 2012;120:2981–9.PubMedPubMedCentralCrossRef
26.
Wang X, Shen QW, Wang J, Zhang Z, Feng F, Chen T, et al. KLF7 regulates satellite cell quiescence in response to extracellular signaling. Stem Cells. 2016;34:1310–20.PubMedCrossRef
27.
28.
Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15–21.PubMedCrossRef
29.
R Development Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2008.
30.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004;5:R80.PubMedPubMedCentralCrossRef
31.
Love M, Anders S, Huber W. Differential analysis of count data—the DESeq2 package. 2014.
32.
Luo W, Friedman MS, Shedden K, Hankenson KD, Woolf PJ. GAGE: generally applicable gene set enrichment for pathway analysis. BMC Bioinform. 2009;10:161.CrossRef
33.
34.
Blake JA, Christie KR, Dolan ME, Drabkin HJ, Hill DP, Ni L, et al. Gene ontology consortium: going forward. Nucleic Acids Res. 2015;43:D1049–56.CrossRef
35.
Kamburov A, Galicka H, Lehrach H, Herwig R. ConsensusPathDB: assembling a more complete picture of cell biology. 2012;2797.
36.
Kamburov A, Stelzl U, Lehrach H, Herwig R. The ConsensusPathDB interaction database: 2013 update. Nucleic Acids Res. 2013;41:D793-800.PubMedCrossRef
37.
38.
Fabregat A, Jupe S, Matthews L, Sidiropoulos K, Gillespie M, Garapati P, et al. The reactome pathway knowledgebase. Nucleic Acids Res. 2018;46:D649–55.PubMedCrossRef
39.
Baumert HM, Metzger E, Fahrner M, George J, Thomas RK, Schilling O, et al. Depletion of histone methyltransferase KMT9 inhibits lung cancer cell proliferation by inducing non-apoptotic cell death. Cancer Cell Int. 2020;20:52.PubMedPubMedCentralCrossRef
40.
Oria VO, Bronsert P, Thomsen AR, Föll MC, Zamboglou C, Hannibal L, et al. Proteome profiling of primary pancreatic ductal adenocarcinomas undergoing additive chemoradiation link ALDH1A1 to early local recurrence and chemoradiation resistance. Transl Oncol. 2018;11:1307–22.PubMedPubMedCentralCrossRef
41.
Colaprico A, Silva TC, Olsen C, Garofano L, Cava C, Garolini D, et al. TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data. Nucleic Acids Res. 2016;44:e71.PubMedCrossRef
42.
Castro F, Dirks WG, Fähnrich S, Hotz-Wagenblatt A, Pawlita M, Schmitt M. High-throughput SNP-based authentication of human cell lines. Int J Cancer. 2013;132:308–14.PubMedCrossRef
43.
Goldhirsch A, Wood WC, Coates AS, Gelber RD, 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;22:1736–47.PubMedPubMedCentralCrossRef
44.
Bankhead P, Loughrey MB, Fernández JA, Dombrowski Y, McArt DG, Dunne PD, et al. QuPath: open source software for digital pathology image analysis. Sci Rep. 2017;7:16878.PubMedPubMedCentralCrossRef
45.
46.
Liu Y, Beyer A, Aebersold R. On the dependency of cellular protein levels on mRNA abundance. Cell. 2016;165:535–50.PubMedCrossRef
47.
Lempiäinen H, Shore D. Growth control and ribosome biogenesis. Curr Opin Cell Biol. 2009;21:855–63.PubMedCrossRef
48.
Sollner-Webb B, Tower J. Transcription of cloned eukaryotic ribosomal RNA genes. Annu Rev Biochem Annu Rev. 1986;55:801–30.CrossRef
49.
Donati G, Montanaro L, Derenzini M. Ribosome biogenesis and control of cell proliferation: p53 is not alone. Cancer Res. 2012;72:1602–7.PubMedCrossRef
50.
Ploton D, Menager M, Jeannesson P, Himber G, Pigeon F, Adnet JJ. Improvement in the staining and in the visualization of the argyrophilic proteins of the nucleolar organizer region at the optical level. Histochem J. 1986;18:5–14.PubMedCrossRef
51.
52.
53.
Stamatopoulou V, Parisot P, De Vleeschouwer C, Lafontaine DLJ. Use of the iNo score to discriminate normal from altered nucleolar morphology, with applications in basic cell biology and potential in human disease diagnostics. Nat Protoc. 2018;13:2387–406.PubMedCrossRef
54.
Kolb HC, Finn MG, Sharpless KB. Click chemistry: diverse chemical function from a few good reactions. Angew Chem Int Ed. 2001;40:2004–21.CrossRef
55.
Sletten EM, Bertozzi CR. Bioorthogonal chemistry: fishing for selectivity in a sea of functionality. Angew Chem Int Ed. 2009;48:6974–98.CrossRef
56.
Silwal-Pandit L, Vollan HK, Chin SF, Rueda OM, McKinney S, Osako T, Quigley DA, Kristensen VN, Aparicio S, Børresen-Dale AL, Caldas C. TP53 mutation spectrum in breast cancer is subtype specific and has distinct prognostic relevance. Clin Cancer Res. 2021;20:3569–80.CrossRef
57.
58.
Destefanis F, Manara V, Bellosta P. Myc as a regulator of ribosome biogenesis and cell competition: a link to cancer. Int J Mol Sci. 2020;21:4037.PubMedCentralCrossRef
59.
Kim S, Li Q, Dang CV, Lee LA. Induction of ribosomal genes and hepatocyte hypertrophy by adenovirus-mediated expression of c-Myc in vivo. Proc Natl Acad Sci U S A. 2000;97:11198–202.PubMedPubMedCentralCrossRef
60.
Pluk H, van Eenennaam H, Rutjes SA, Pruijn GJ, van Venrooij WJ. RNA-protein interactions in the human RNase MRP ribonucleoprotein complex. RNA. 1999;5:512–24.PubMedPubMedCentralCrossRef
61.
Robertson N, Shchepachev V, Wright D, Turowski TW, Spanos C, Helwak A, et al. A disease-linked lncRNA mutation in RNase MRP inhibits ribosome synthesis. Nat Commun. 2022;13:649.PubMedPubMedCentralCrossRef
62.
Rheinbay E, Parasuraman P, Grimsby J, Tiao G, Engreitz JM, Kim J, et al. Recurrent and functional regulatory mutations in breast cancer. Nature. 2017;547:55–60.PubMedPubMedCentralCrossRef
63.
Liu Y, Sun H, Li X, Liu Q, Zhao Y, Li L, et al. Identification of a three-RNA binding proteins (RBPs) signature predicting prognosis for breast cancer. Front Oncol. 2021;11:663556.PubMedPubMedCentralCrossRef
64.
Malcolm JR, Leese NK, Lamond-Warner PI, Brackenbury WJ, White RJ. Widespread association of ERα with RMRP and tRNA genes in MCF-7 cells and breast cancers. Gene. 2022;821:146280.PubMedCrossRef
65.
66.
67.
Winzer K-J, Bellach J, Hufnagl P. Long-term analysis to objectify the tumour grading by means of automated microscopic image analysis of the nucleolar organizer regions (AgNORs) in the case of breast carcinoma. Diagn Pathol. 2013;8:56.PubMedPubMedCentralCrossRef
68.
Ahmed HG, Al-Adhraei MA, Ashankyty IM. Association between AgNORs and immunohistochemical expression of ER, PR, HER2/neu, and p53 in breast carcinoma. Patholog Res Int. 2011.
69.
Donizy P, Biecek P, Halon A, Maciejczyk A, Matkowski R. Nucleoli cytomorphology in cutaneous melanoma cells—a new prognostic approach to an old concept. Diagn Pathol. 2017;12:88.PubMedPubMedCentralCrossRef
70.
Elsharawy KA, Toss MS, Raafat S, Ball G, Green AR, Aleskandarany MA, et al. Prognostic significance of nucleolar assessment in invasive breast cancer. Histopathology. 2020;76:671–84.PubMedCrossRef
71.
Weeks SE, Kammerud SC, Metge BJ, AlSheikh HA, Schneider DA, Chen D, et al. Inhibiting β-catenin disables nucleolar functions in triple-negative breast cancer. Cell Death Dis. 2021;12:242–242.PubMedPubMedCentralCrossRef
72.
Vaklavas C, Blume SW, Grizzle WE. Translational dysregulation in cancer: molecular insights and potential clinical applications in biomarker development. Front Oncol. 2017;7:158.PubMedPubMedCentralCrossRef
73.
Lee LJ, Papadopoli D, Jewer M, Del Rincon S, Topisirovic I, Lawrence MG, et al. Cancer plasticity: the role of mRNA translation. Trends Cancer. 2021;7:134–45.PubMedCrossRef
74.
Rajasekhar VK, Viale A, Socci ND, Wiedmann M, Hu X, Holland EC. Oncogenic Ras and Akt signaling contribute to glioblastoma formation by differential recruitment of existing mRNAs to polysomes. Mol Cell. 2003;12:889–901.PubMedCrossRef
75.
Chen Y-X, Xu Z, Ge X, Hong J-Y, Sanyal S, Lu ZJ, et al. Selective translation by alternative bacterial ribosomes. PNAS Natl Acad Sci. 2020;117:19487–96.CrossRef
76.
77.
Derenzini M, Ceccarelli C, Santini D, Taffurelli M, Treré D. The prognostic value of the AgNOR parameter in human breast cancer depends on the pRb and p53 status. J Clin Pathol. 2004;57:755–61.PubMedPubMedCentralCrossRef
Metadata
Title
Krüppel-like factor 7 influences translation and pathways involved in ribosomal biogenesis in breast cancer
Authors
Anne-Marie Lüchtenborg
Patrick Metzger
Miguel Cosenza Contreras
Victor Oria
Martin L. Biniossek
Franziska Lindner
Klemens Fröhlich
Ambrus Malyi
Thalia Erbes
Nicole Gensch
Jochen Maurer
Andreas Thomsen
Melanie Boerries
Oliver Schilling
Martin Werner
Peter Bronsert
Publication date
01-12-2022
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2022
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-022-01562-8

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