CoChat
Sign Up
Cited by 91Chronic Lymphocytic Leukemia ResearchLymphoma Diagnosis and TreatmentRNA modifications and cancer

Small nucleolar RNAs as new biomarkers in chronic lymphocytic leukemia

Open access
Ronchetti, Domenica, Mosca, Laura, Cutrona, Giovanna, Tuana, Giacomo, Gentile, Massimo, Fabris, Sonia, Agnelli, Luca, Ciceri, Gabriella +11 more·2013·BMC Medical Genomics
DOI 10.1186/1755-8794-6-27PMC PMC3766210
Open this paper in CoChat — free accountOpen PDF

Abstract

Background: Small nucleolar RNAs (snoRNAs) and small Cajal body-specific RNAs are non-coding RNAs involved in the maturation of other RNA molecules. Alterations of sno/scaRNA expression may play a role in cancerogenesis. This study elucidates the patterns of sno/scaRNA expression in 211 chronic lymphocytic leukemia (CLL) patients (Binet stage A) also in comparison with those of different normal B-cell subsets. Methods: The patterns of sno/scaRNA expression in highly purified CD19+ B-cells of 211 CLL patients and in 18 normal B-cell samples - 6 from peripheral blood, and 12 from tonsils (4 germinal center, 2 marginal zone, 3 switched memory and 3 naïve B-cells) - were analyzed on the Affymetrix GeneChip® Human Gene 1.0 ST array. Results: CLLs display a sno/scaRNAs expression profile similar to normal memory, naïve and marginal-zone B-cells, with the exception of a few down-regulated transcripts (SNORA31, -6, -62, and -71C). Our analyses also suggest some heterogeneity in the pattern of sno/scaRNAs expression which is apparently unrelated to the major biological (ZAP-70 and CD38), molecular (IGHV mutation) and cytogenetic markers. Moreover, we found that SNORA70F was significantly down-regulated in poor prognostic subgroups and this phenomenon was associated with the down-regulation of its host gene COBLL1. Finally, we generated an independent model based on SNORA74A and SNORD116-18 expression, which appears to distinguish two different prognostic CLL groups. Conclusions: These data extend the view of sno/scaRNAs deregulation in cancer and may contribute to discover novel biomarkers associated with the disease and potentially useful to predict the clinical outcome of early stage CLL patients.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/1755-8794-6-27

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Members of SNORD115 and SNORD116 clusters have been reported upregulated in patients with multiple myeloma, chronic lymphocytic leukemia, or acute lymphoblastic leukemia.

    “Members of SNORD115 and SNORD116 clusters have been also reported upregulated in patients with multiple myeloma, chronic lymphocytic leukemia (Ronchetti et al., 2013; Ronchetti et al., 2012), or acute lymphoblastic leukemia (Vendramini et al., 2014).”

    From Small nucleolar RNAs in plasma extracellular vesicles and their discriminatory power as diagnostic biomarkers of Alzheimer's disease (2021) · cites this paper as Ronchetti et al., 2013

    The Results section on high-risk CLL reports higher SNORD116-18 expression in a subgroup of CLL patients, compared with a lower-expression subgroup. It does not establish that SNORD116 members are generally upregulated in CLL patients relative to healthy cells, and it does not report SNORD115 upregulation in CLL. The multiple-myeloma and acute-lymphoblastic-leukemia portions are not attributed specifically to this paper. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 48

  1. Chiorazzi N Rai KR Ferrarini M Chronic lymphocytic leukemia N Engl J Med 2005 352 804 815 10.1056/NEJMra041720 15728813 · DOI
  2. Zwiebel JA Cheson BD Chronic lymphocytic leukemia: staging and prognostic factors Semin Oncol 1998 25 42 59 9482526
  3. Rai KR Sawitsky A Cronkite EP Chanana AD Levy RN Pasternack BS Clinical staging of chronic lymphocytic leukemia Blood 1975 46 219 234 27789434
  4. Binet JL Vaugier G Dighiero G D’Athis P Charron D Investigation of a new parameter in chronic lymphocytic leukemia: the percentage of large peripheral lymphocytes determined by the hemalog D. Prognostic significance Am J Med 1977 63 683 688 10.1016/0002-9343(77)90152-8 930943 · DOI
  5. Kay NE Shanafelt TD Prognostic factors in chronic lymphocytic leukemia Curr Hematol Malig Rep 2007 2 49 55 10.1007/s11899-007-0007-1 20425388 · DOI
  6. Crespo M Bosch F Villamor N Bellosillo B Colomer D Rozman M Marce S Lopez-Guillermo A Campo E Montserrat E ZAP-70 expression as a surrogate for immunoglobulin-variable-region mutations in chronic lymphocytic leukemia N Engl J Med 2003 348 1764 1775 10.1056/NEJMoa023143 12724482 · DOI
  7. Damle RN Wasil T Fais F Ghiotto F Valetto A Allen SL Buchbinder A Budman D Dittmar K Kolitz J Lichtman SM Schulman P Vinciguerra VP Rai KR Ferrarini M Chiorazzi N Ig V gene mutation status and CD38 expression as novel prognostic indicators in chronic lymphocytic leukemia Blood 1999 94 1840 1847 10477712
  8. Hamblin TJ Davis Z Gardiner A Oscier DG Stevenson FK Unmutated Ig V(H) genes are associated with a more aggressive form of chronic lymphocytic leukemia Blood 1999 94 1848 1854 10477713
  9. Byrd JC Smith L Hackbarth ML Flinn IW Young D Proffitt JH Heerema NA Interphase cytogenetic abnormalities in chronic lymphocytic leukemia may predict response to rituximab Cancer Res 2003 63 36 38 12517774
  10. Dohner H Fischer K Bentz M Hansen K Benner A Cabot G Diehl D Schlenk R Coy J Stilgenbauer S p53 Gene deletion predicts for poor survival and non-response to therapy with purine analogs in chronic B-cell leukemias Blood 1995 85 1580 1589 7888675
  11. Dohner H Stilgenbauer S Benner A Leupolt E Krober A Bullinger L Dohner K Bentz M Lichter P Genomic aberrations and survival in chronic lymphocytic leukemia N Engl J Med 2000 343 1910 1916 10.1056/NEJM200012283432602 11136261 · DOI
  12. Haferlach C Dicker F Schnittger S Kern W Haferlach T Comprehensive genetic characterization of CLL: a study on 506 cases analysed with chromosome banding analysis, interphase FISH, IgV(H) status and immunophenotyping Leukemia 2007 21 2442 2451 10.1038/sj.leu.2404935 17805327 · DOI
  13. Stilgenbauer S Bullinger L Lichter P Dohner H Genetics of chronic lymphocytic leukemia: genomic aberrations and V(H) gene mutation status in pathogenesis and clinical course Leukemia 2002 16 993 1007 10.1038/sj.leu.2402537 12040431 · DOI
  14. Taft RJ Pang KC Mercer TR Dinger M Mattick JS Non-coding RNAs: regulators of disease J Pathol 2010 220 126 139 10.1002/path.2638 19882673 · DOI
  15. Kiss T Small nucleolar RNAs: an abundant group of noncoding RNAs with diverse cellular functions Cell 2002 109 145 148 10.1016/S0092-8674(02)00718-3 12007400 · DOI
  16. Williams GT Farzaneh F Are snoRNAs and snoRNA host genes new players in cancer? Nat Rev Cancer 2012 12 84 88 22257949
  17. Chu L Su MY Maggi LB Jr Lu L Mullins C Crosby S Huang G Chng WJ Vij R Tomasson MH Multiple myeloma-associated chromosomal translocation activates orphan snoRNA ACA11 to suppress oxidative stress J Clin Invest 2012 122 2793 2806 10.1172/JCI63051 22751105 PMC3408744 · DOI
  18. Lopez-Corral L Mateos MV Corchete LA Sarasquete ME la RJ D De AF Lahuerta JJ Garcia-Sanz R San Miguel JF Gutierrez NC Genomic analysis of high risk smoldering multiple myeloma Haematologica 2012 97 1439 1443 10.3324/haematol.2011.060780 22331267 PMC3436247 · DOI
  19. Teittinen KJ Laiho A Uusimaki A Pursiheimo JP Gyenesei A Lohi O Expression of small nucleolar RNAs in leukemic cells Cell Oncol (Dordr) 2013 36 55 63 10.1007/s13402-012-0113-5 23229394 PMC13012689 · DOI
  20. Valleron W Laprevotte E Gautier EF Quelen C Demur C Delabesse E Agirre X Prosper F Kiss T Brousset P Specific small nucleolar RNA expression profiles in acute leukemia Leukemia 2012 26 2052 2060 10.1038/leu.2012.111 22522792 · DOI
  21. Valleron W Ysebaert L Berquet L Fataccioli V Quelen C Martin A Parrens M Lamant L De LL Gisselbrecht C Gaulard P Brousset P Small nucleolar RNA expression profiling identifies potential prognostic markers in peripheral T-cell lymphoma Blood 2012 8 3997 4005 22990019
  22. Cheson BD Bennett JM Grever M Kay N Keating MJ O’Brien S Rai KR National cancer institute-sponsored working group guidelines for chronic lymphocytic leukemia: revised guidelines for diagnosis and treatment Blood 1996 87 4990 4997 8652811
  23. Cutrona G Colombo M Matis S Reverberi D Dono M Tarantino V Chiorazzi N Ferrarini M B lymphocytes in humans express ZAP-70 when activated in vivo Eur J Immunol 2006 36 558 569 10.1002/eji.200526355 16482508 · DOI
  24. Cutrona G Colombo M Matis S Fabbi M Spriano M Callea V Vigna E Gentile M Zupo S Chiorazzi N Morabito F Ferrarini M Clonal heterogeneity in chronic lymphocytic leukemia cells: superior response to surface IgM cross-linking in CD38, ZAP-70-positive cells Haematologica 2008 93 413 422 10.3324/haematol.11646 18287138 · DOI
  25. Fabris S Mosca L Todoerti K Cutrona G Lionetti M Intini D Matis S Colombo M Agnelli L Gentile M Spriano M Callea V Festini G Molica S Lambertenghi DG Morabito F Ferrarini M Neri A Molecular and transcriptional characterization of 17p loss in B-cell chronic lymphocytic leukemia Genes Chromosomes Cancer 2008 47 781 793 10.1002/gcc.20579 18521849 · DOI
  26. Maura F Cutrona G Fabris S Colombo M Tuana G Agnelli L Matis S Lionetti M Gentile M Recchia AG Di RF Musolino C Ilariucci F Di RN Pesce E Molica S Federico M Cortelezzi A Morabito F Ferrarini M Relevance of stereotyped B-cell receptors in the context of the molecular, cytogenetic and clinical features of chronic lymphocytic leukemia PLoS One 2011 6 e24313 10.1371/journal.pone.0024313 21897877 PMC3163661 · DOI
  27. Morabito F Cutrona G Gentile M Matis S Todoerti K Colombo M Sonaglio C Fabris S Reverberi D Megna M Spriano M Lucia E Rossi E Callea V Mazzone C Festini G Zupo S Molica S Neri A Ferrarini M Definition of progression risk based on combinations of cellular and molecular markers in patients with binet stage a chronic lymphocytic leukaemia Br J Haematol 2009 146 44 53 10.1111/j.1365-2141.2009.07703.x 19438486 · DOI
  28. Irizarry RA Hobbs B Collin F Beazer-Barclay YD Antonellis KJ Scherf U Speed TP Exploration, normalization, and summaries of high density oligonucleotide array probe level data Biostatistics 2003 4 249 264 10.1093/biostatistics/4.2.249 12925520 · DOI · Paper page
  29. Dai M Wang P Boyd AD Kostov G Athey B Jones EG Bunney WE Myers RM Speed TP Akil H Watson SJ Meng F Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data Nucleic Acids Res 2005 33 e175 10.1093/nar/gni179 16284200 PMC1283542 · DOI
  30. Sandberg R Larsson O Improved precision and accuracy for microarrays using updated probe set definitions BMC Bioinforma 2007 8 48 10.1186/1471-2105-8-48 PMC1805763 17288599 · DOI
  31. Tusher VG Tibshirani R Chu G Significance analysis of microarrays applied to the ionizing radiation response Proc Natl Acad Sci USA 2001 98 5116 5121 10.1073/pnas.091062498 11309499 PMC33173 · DOI · Paper page
  32. Schadt EE Li C Ellis B Wong WH Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data J Cell Biochem Suppl 2001 37 120 125 11842437
  33. Xie J Zhang M Zhou T Hua X Tang L Wu W Sno/scaRNAbase: a curated database for small nucleolar RNAs and cajal body-specific RNAs Nucleic Acids Res 2007 35 D183 D187 10.1093/nar/gkl873 17099227 PMC1669756 · DOI
  34. Chiorazzi N Ferrarini M Cellular origin(s) of chronic lymphocytic leukemia: cautionary notes and additional considerations and possibilities Blood 2011 117 1781 1791 10.1182/blood-2010-07-155663 21148333 PMC3056635 · DOI
  35. Seifert M Sellmann L Bloehdorn J Wein F Stilgenbauer S Durig J Kuppers R Cellular origin and pathophysiology of chronic lymphocytic leukemia J Exp Med 2012 209 2183 2198 10.1084/jem.20120833 23091163 PMC3501361 · DOI
  36. Amson R Pece S Marine JC Di Fiore PP Telerman A TPT1/ TCTP-regulated pathways in phenotypic reprogramming Trends Cell Biol 2013 23 37 46 10.1016/j.tcb.2012.10.002 23122550 · DOI
  37. Friedrichs B Siegel S Reimer R Barsoum A Coggin J Jr Kabelitz D Heidorn K Schulte C Schmitz N Zeis M High expression of the immature laminin receptor protein correlates with mutated IGVH status and predicts a favorable prognosis in chronic lymphocytic leukemia Leuk Res 2011 35 721 729 10.1016/j.leukres.2010.10.002 21055809 · DOI
  38. Abruzzo LV Barron LL Anderson K Newman RJ Wierda WG O’Brien S Ferrajoli A Luthra M Talwalkar S Luthra R Jones D Keating MJ Coombes KR Identification and validation of biomarkers of IgV(H) mutation status in chronic lymphocytic leukemia using microfluidics quantitative real-time polymerase chain reaction technology J Mol Diagn 2007 9 546 555 10.2353/jmoldx.2007.070001 17690214 PMC1975107 · DOI
  39. Mansouri L Gunnarsson R Sutton LA Ameur A Hooper SD Mayrhofer M Juliusson G Isaksson A Gyllensten U Rosenquist R Next generation RNA-sequencing in prognostic subsets of chronic lymphocytic leukemia Am J Hematol 2012 87 737 740 10.1002/ajh.23227 22674506 · DOI
  40. Carroll EA Gerrelli D Gasca S Berg E Beier DR Copp AJ Klingensmith J Cordon-bleu is a conserved gene involved in neural tube formation Dev Biol 2003 262 16 31 10.1016/S0012-1606(03)00323-3 14512015 · DOI
  41. Gordon GJ Bueno R Sugarbaker DJ Genes associated with prognosis after surgery for malignant pleural mesothelioma promote tumor cell survival in vitro BMC Cancer 2011 11 169 10.1186/1471-2407-11-169 21569526 PMC3112160 · DOI
  42. Gaidano G Foa R La-Favera R Molecular pathogenesis of chronic lymphocytic leukemia J Clin Invest 2012 122 3432 3438 10.1172/JCI64101 23023714 PMC3461921 · DOI
  43. Bortolin ML Kiss T Human U19 intron-encoded snoRNA is processed from a long primary transcript that possesses little potential for protein coding RNA 1998 4 445 454 9630250 PMC1369630
  44. Salton M Elkon R Borodina T Davydov A Yaspo ML Halperin E Shiloh Y Matrin 3 binds and stabilizes mRNA PLoS One 2011 6 e23882 10.1371/journal.pone.0023882 21858232 PMC3157474 · DOI
  45. Runte M Huttenhofer A Gross S Kiefmann M Horsthemke B Buiting K The IC-SNURF-SNRPN transcript serves as a host for multiple small nucleolar RNA species and as an antisense RNA for UBE3A Hum Mol Genet 2001 10 2687 2700 10.1093/hmg/10.23.2687 11726556 · DOI
  46. Kishore S Khanna A Zhang Z Hui J Balwierz PJ Stefan M Beach C Nicholls RD Zavolan M Stamm S The snoRNA MBII-52 (SNORD 115) is processed into smaller RNAs and regulates alternative splicing Hum Mol Genet 2010 19 1153 1164 10.1093/hmg/ddp585 20053671 PMC2838533 · DOI
  47. Bazeley PS Shepelev V Talebizadeh Z Butler MG Fedorova L Filatov V Fedorov A snoTARGET shows that human orphan snoRNA targets locate close to alternative splice junctions Gene 2008 408 172 179 10.1016/j.gene.2007.10.037 18160232 PMC6800007 · DOI
  48. Wang L Lawrence MS Wan Y Stojanov P Sougnez C Stevenson K Werner L Sivachenko A DeLuca DS Zhang L Zhang W Vartanov AR Fernandes SM Goldstein NR Folco EG Cibulskis K Tesar B Sievers QL Shefler E Gabriel S SF3B1 And other novel cancer genes in chronic lymphocytic leukemia N Engl J Med 2011 365 2497 2506 10.1056/NEJMoa1109016 22150006 PMC3685413 · DOI

Cited by

Sorted by citations

Authors
Ronchetti, D., Mosca, L., Cutrona, G., Tuana, G., Gentile, M., Fabris, S., Agnelli, L., Ciceri, G., Matis, S., Massucco, C., Colombo, M., Reverberi, D., Recchia, A. G., Bossio, S., Negrini, M., Tassone, P., Morabito, F., Ferrarini, M., & Neri, A.
Affiliations
  • University of Milan (IT)
  • Ospedale Policlinico San Martino (IT)
  • Azienda Ospedaliera di Cosenza (IT)
  • University of Ferrara (IT)
  • Magna Graecia University (IT)
Corresponding author
Neri, Antonino
ORCID
Venue
BMC Medical Genomics
Publisher
Springer Science and Business Media LLC
Published
2013-09-03
Volume
6
Issue
1
Pages
27-27
ISSN
1755-8794 (ISSN-L)
DOI
10.1186/1755-8794-6-27
PMC
PMC3766210
OpenAlex
W2053084152
Cited by
91
References
1
Citations by year
2026: 1 · 2025: 5 · 2024: 6 · 2023: 6 · 2022: 9 · 2021: 15 · 2020: 8 · 2019: 5 · 2018: 7 · 2017: 6 · 2016: 7 · 2015: 8 · 2014: 8
FWCI
3.77
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Medical Genomics (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Institutional Research Information System University of Ferrara (University of Ferrara) (submittedVersion)
  • Archive of Doctoral Theses and Digital Collections (University of Calabria) (submittedVersion)
Funders
  • Ministero dell’Istruzione, dell’Università e della Ricerca (2009PKMYA2)
  • Associazione Italiana per la Ricerca sul Cancro (2010/15, 9980, 2010-15, AIRC 5xmille, IG10492, 5 x mille, IG-10136)
Topics
  • Health Sciences › Medicine › Genetics › Chronic Lymphocytic Leukemia Research
  • Health Sciences › Medicine › Pathology and Forensic Medicine › Lymphoma Diagnosis and Treatment
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA modifications and cancer
Keywords
small nucleolar RNA, chronic lymphocytic leukemia, prognostic factors, B cell subsets, tonsil, CD19+ B cells, disease heterogeneity, clinical outcome prediction
MeSH terms
Cell Nucleus, Humans, Neoplasm Staging, Prognosis, Risk, Transcription, Genetic, Biomarkers, Tumor, Leukemia, Lymphocytic, Chronic, B-Cell, B-Lymphocyte Subsets, RNA, Small Nucleolar, Gene Expression Profiling

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review