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Relationship: 2729

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Increase chromosomal aberrations leads to Increase,miRNA levels

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes. Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
DNA damage and mutations leading to Metastatic Breast Cancer non-adjacent High High Usha Adiga (send email) Under development: Not open for comment. Do not cite Under Development

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER.  More help
Term Scientific Term Evidence Link
human Homo sapiens High NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Mixed High

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help
Term Evidence
All life stages Not Specified

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

KER :Increased, chromosomal aberration leads to microRNA  expression, increased

  Upstream event: increased, chromosomal aberration

Downstream event: increased miRNA expression

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER.  For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings.  Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Animal studies,cell line studies and human studies were searched,

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

The first report linking a chromosomal breakpoint with the genomic location of miRNAs was published a couple of decades ago (Gauwerky et al.,1989). A masked t(8;17) translocation resulted in a high activation of the MYC OG: MYC from chromosome 8 was truncated at the end of the first exon (which is noncoding), and the coding region joined the regulatory elements of a gene located on chromosome 17, called BCL3 (B cell leukemia/lymphoma 3). Despite extensive genomic search, BCL3 remained an elusive entity until the identification of the human miRNAs. Fifteen years after the initial discovery, the miR-142 gene was found to be located 50 nt from the t(8;17) break involving chromosome 17 and MYC, meaning that the regulatory elements of this miRNA are likely involved in the overexpression of MYC (Calin, G.A., et al. 2002). The clinical consequences were dramatic for the patient, leading to aggressive acute prolymphocytic leukemia  (Gauwerky et al.,1989). Apart from the involvement in the t(8;17) breakpoint of B cell acute leukemia, miR-142-3p and miR-142-5p are also within the 17q23 minimal amplicon described in breast cancer (Barlund, M., et al. 2000) and near the FRA17B site, a target for HPV16 integration in cervical tumors (Calin, G.A., et al. 2004).

Biological Plausibility
Addresses the biological rationale for a connection between KEupstream and KEdownstream.  This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured.   More help

Chromosomal translocations alter PCG loci through two main mechanisms (Russo, G., et al. 1988). The first is the juxtaposition of promoter/enhancer elements from one gene to the intact coding region of another gene, while the second is the recombination of the coding regions of two different genes. The former is more frequently found in B and T cell lymphomas and leukemias and the latter in human myeloid leukemias and soft-tissue sarcomas. The translocations that alter miRNA loci can be classified by analogy with these mechanisms . At least five different situations can be postulated, the last three of which have yet to be identified in human cancers: (a) juxtaposition of promoter/enhancer elements from miRNA genes to a PCG ORF with overexpression of the protein [e.g., t(8;17)(q24;q22)]; (b) disruption of the region of interaction between the target PCG and the interactor miRNA with the disruption of the repression and the overexpression of the protein (e.g., 12q15 translocations involving HMGA2 gene); (c) juxtaposition of promoter/enhancer elements from PCG to a miRNA gene with overexpression of the noncoding gene; (d) juxtaposition of promoter/enhancer elements from miRNA to another miRNA gene with overexpression of the noncoding gene (termed “promoter swapping”); and (e) miRNA gene–to–miRNA gene fusion with the consequent production of a “new” cluster of coexpressed or independently expressed miRNAs.

Uncertainties and Inconsistencies
Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

The contribution of microRNAs (miR) to the pathogenesis of mantle cell lymphoma (MCL) is not well known. The expression of 86 mature miRs mapped to frequently altered genomic regions in MCL in CD5+ /CD5 normal B cells, reactive lymph nodes, and purified tumor cells of 17 leukemic MCL, 12 nodal MCL, and 8MCL cell lines were investigated. Genomic alterations of the tumors were studied by single nucleotide polymorphism arrays and comparative genomic hybridization. Leukemic and nodal tumors showed a high number of differentially expressed miRs compared with purified normal B cells, but only some of them were commonly deregulated in both tumor types. An unsupervised analysis of miR expression profile in purified leukemic MCL cells revealed two clusters of tumors characterized by different mutational status of the immunoglobulin genes, proliferation signature, and number of genomic alterations. The expression of most miRs was not related to copy number changes in their respective chromosomal loci. Only the levels of miRs included in the miR-17-92 cluster were significantly related to genetic alterations at 13q31. Moreover, overexpression of miR-17-5p/miR-20a from this cluster was associated with high MYC mRNA levels in tumors with a more aggressive behavior. In conclusion, the miR expression pattern of MCL is deregulated in comparison with normal lymphoid cells and distinguishes two subgroups of tumors with different biological features.

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references.  More help
Modulating Factor (MF) MF Specification Effect(s) on the KER Reference(s)

UV rays,cisplatin, doxorubicin, IR

Impaired DNA repair Altered miRNA expression

Pothof et al., 2009,Galluzzi et al., 2010, Saleh et.al.,2011;Suzuki et al.,2009

Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help

Detailed investigation of the 13q14.3 deletions showed that both members of an miRNA cluster, miR-15a and miR-16-1, are deleted or downregulated in approximately 68% of CLL cases as compared with healthy donors (Calin, G.A., et al. 2002). Furthermore, a rare mutation lowering the expression of these genes was identified in two CLL patients including one from a family with individuals having CLL and breast cancer, and was found to be associated with the loss of the normal allele in the leukemic cells (Calin, G.A., et al. 2005). It was shown that the levels of both miR-15 and miR-16 inversely correlate with the BCL-2 protein expression and that BCL-2 repression by these miRNAs induces apoptosis in leukemia cells (Cimmino, A., et al. 2005).

Levels of miR-16 were decreased in NZB lymphoid tissue, and exogenous miR-16 delivered to an NZB malignant B-1 cell line resulted in cell cycle alterations and increased apoptosis. Linkage of the miR-15a/miR-16-1 complex to the development of CLL in this spontaneous mouse model suggests that the altered expression of these genes is the molecular lesion in CLL (Raveche, E.S., et al. 2007).

The only miRNA found to be overexpressed in any type of solid tumor analyzed (breast, colon, lung, prostate, stomach, and endocrine pancreas tumors, glioblastomas, and uterine leiomyomas) is miR-21 (Volinia, S., et al. 2006, Ciafre, S.A., et al. 2005; . Krichevsky et al.,2003; Wang, T., et al. 2007). This gene is located in the 3′UTR of the vacuole membrane protein 1 (VMP1) gene at chromosome 17q23.2, a region frequently found amplified in neuroblastomas and breast, colon, and lung cancers. Knockdown of miR-21 in glioblastoma cell lines induces a caspase-mediated apoptosis, further supporting the oncogenic role of this miRNA (Chan, et al.,2005).

Time-scale
Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help

Studies performed in solid cancer cell lines showed that miR-16 negatively regulated cellular growth and cell cycle progression. miR-16–downregulated transcripts were enriched with genes whose silencing by small interfering RNAs causes an accumulation of cells in G0/G1. Simultaneous silencing of these genes was more effective at blocking cell cycle progression than was disruption of the individual genes. Thus, miR-16 coordinately regulates targets that may act in concert to control cell cycle progression (Linsley, P.S., et al. 2007)

Known Feedforward/Feedback loops influencing this KER
Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Not mentioned.

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

Not specific through any particular life stage or gender

References

List of the literature that was cited for this KER description. More help

Bärlund, M., Monni, O., Kononen, J., Cornelison, R., Torhorst, J., Sauter, G., ... & Kallioniemi, A. (2000). Multiple genes at 17q23 undergo amplification and overexpression in breast cancer. Cancer research60(19), 5340-5344.

 

Calin, G. A., Dumitru, C. D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., ... & Croce, C. M. (2002). Frequent deletions and down-regulation of micro-RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proceedings of the national academy of sciences99(24), 15524-15529.

Calin, G. A., Sevignani, C., Dumitru, C. D., Hyslop, T., Noch, E., Yendamuri, S., ... & Croce, C. M. (2004). Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proceedings of the National Academy of Sciences101(9), 2999-3004.

Calin, G. A., Ferracin, M., Cimmino, A., Di Leva, G., Shimizu, M., Wojcik, S. E., ... & Croce, C. M. (2005). A MicroRNA signature associated with prognosis and progression in chronic lymphocytic leukemia. New England Journal of Medicine353(17), 1793-1801.

Calin, G. A., & Croce, C. M. (2006). MicroRNAs and chromosomal abnormalities in cancer cells. Oncogene25(46), 6202-6210.

Chan, J. A., Krichevsky, A. M., & Kosik, K. S. (2005). MicroRNA-21 is an antiapoptotic factor in human glioblastoma cells. Cancer research65(14), 6029-6033.

Chim, C. S., Wong, K. Y., Qi, Y., Loong, F., Lam, W. L., Wong, L. G., ... & Liang, R. (2010). Epigenetic inactivation of the miR-34a in hematological malignancies. Carcinogenesis31(4), 745-750.

Ciafre, S. A., Galardi, S., Mangiola, A., Ferracin, M., Liu, C. G., Sabatino, G., ... & Farace, M. G. (2005). Extensive modulation of a set of microRNAs in primary glioblastoma. Biochemical and biophysical research communications334(4), 1351-1358.

Cimmino, A., Calin, G. A., Fabbri, M., Iorio, M. V., Ferracin, M., Shimizu, M., ... & Croce, C. M. (2005). miR-15 and miR-16 induce apoptosis by targeting BCL2. Proceedings of the National Academy of Sciences102(39), 13944-13949.

Corthals, S. L., Jongen-Lavrencic, M., de Knegt, Y., Peeters, J. K., Beverloo, H. B., Lokhorst, H. M., & Sonneveld, P. (2010). Micro-RNA-15a and micro-RNA-16 expression and chromosome 13 deletions in multiple myeloma. Leukemia research34(5), 677-681.

Dehan, E., Ben-Dor, A., Liao, W., Lipson, D., Frimer, H., Rienstein, S., ... & Kaminski, N. (2007). Chromosomal aberrations and gene expression profiles in non-small cell lung cancer. Lung cancer56(2), 175-184.

Galluzzi, L., Morselli, E., Vitale, I., Kepp, O., Senovilla, L., Criollo, A., ... & Kroemer, G. (2010). miR-181a and miR-630 regulate cisplatin-induced cancer cell death. Cancer research70(5), 1793-1803.

Gao, X., Zhang, R., Qu, X., Zhao, M., Zhang, S., Wu, H., ... & Chen, L. (2012). MiR-15a, miR-16-1 and miR-17-92 cluster expression are linked to poor prognosis in multiple myeloma. Leukemia research36(12), 1505-1509.

Gatt, M. E., Zhao, J. J., Ebert, M. S., Zhang, Y., Chu, Z., Mani, M., ... & Carrasco, D. R. (2010). MicroRNAs 15a/16-1 function as tumor suppressor genes in multiple myeloma. Blood, 61-65.

 

Gauwerky, C. E., Huebner, K., Isobe, M., Nowell, P. C., & Croce, C. M. (1989). Activation of MYC in a masked t (8; 17) translocation results in an aggressive B-cell leukemia. Proceedings of the National Academy of Sciences86(22), 8867-8871.

Gutiérrez, N. C., Sarasquete, M. E., Misiewicz-Krzeminska, I., Delgado, M., De Las Rivas, J., Ticona, F. V., ... & San Miguel, J. F. (2010). Deregulation of microRNA expression in the different genetic subtypes of multiple myeloma and correlation with gene expression profiling. Leukemia24(3), 629-637.

 

Huang, J. J., Yu, J., Li, J. Y., Liu, Y. T., & Zhong, R. Q. (2012). Circulating microRNA expression is associated with genetic subtype and survival of multiple myeloma. Medical oncology29(4), 2402-2408.

Krichevsky, A. M., King, K. S., Donahue, C. P., Khrapko, K., & Kosik, K. S. (2003). A microRNA array reveals extensive regulation of microRNAs during brain development. Rna9(10), 1274-1281.

Kuehl, W. M., & Bergsagel, P. L. (2012). Molecular pathogenesis of multiple myeloma and its premalignant precursor. The Journal of clinical investigation122(10), 3456-3463.

 

Linsley, P. S., Schelter, J., Burchard, J., Kibukawa, M., Martin, M. M., Bartz, S. R., ... & Lim, L. (2007). Transcripts targeted by the microRNA-16 family cooperatively regulate cell cycle progression. Molecular and cellular biology27(6), 2240-2252.

Lionetti, M., Biasiolo, M., Agnelli, L., Todoerti, K., Mosca, L., Fabris, S., ... & Neri, A. (2009). Identification of microRNA expression patterns and definition of a microRNA/mRNA regulatory network in distinct molecular groups of multiple myeloma. Blood, The Journal of the American Society of Hematology114(25), e20-e26.

Min, D. J., Ezponda, T., Kim, M. K., Will, C. M., Martinez-Garcia, E., Popovic, R., ... & Licht, J. D. (2013). MMSET stimulates myeloma cell growth through microRNA-mediated modulation of c-MYC. Leukemia27(3), 686-694.

Misiewicz-Krzeminska, I., Sarasquete, M. E., Quwaider, D., Krzeminski, P., Ticona, F. V., Paíno, T., ... & Gutiérrez, N. C. (2013). Restoration of microRNA-214 expression reduces growth of myeloma cells through positive regulation of P53 and inhibition of DNA replication. haematologica98(4), 640.

Pichiorri, F., Suh, S. S., Ladetto, M., Kuehl, M., Palumbo, T., Drandi, D., ... & Croce, C. M. (2008). MicroRNAs regulate critical genes associated with multiple myeloma pathogenesis. Proceedings of the National Academy of Sciences105(35), 12885-12890.

Pichiorri, F., Suh, S. S., Rocci, A., De Luca, L., Taccioli, C., Santhanam, R., ... & Croce, C. M. (2010). Downregulation of p53-inducible microRNAs 192, 194, and 215 impairs the p53/MDM2 autoregulatory loop in multiple myeloma development. Cancer cell18(4), 367-381.

Pichiorri, F., De Luca, L., & Aqeilan, R. I. (2011). MicroRNAs: new players in multiple myeloma. Frontiers in genetics2, 22.

Pothof, J., Verkaik, N. S., Van Ijcken, W., Wiemer, E. A., Ta, V. T., Van Der Horst, G. T., ... & Persengiev, S. P. (2009). MicroRNAmediated gene silencing modulates the UVinduced DNAdamage response. The EMBO journal28(14), 2090-2099.

Raveche, E. S., Salerno, E., Scaglione, B. J., Manohar, V., Abbasi, F., Lin, Y. C., ... & Marti, G. E. (2007). Abnormal microRNA-16 locus with synteny to human 13q14 linked to CLL in NZB mice. Blood, The Journal of the American Society of Hematology109(12), 5079-5086.

Rio-Machin, A., Ferreira, B. I., Henry, T., Gómez-López, G., Agirre, X., Alvarez, S., ... & Cigudosa, J. C. (2013). Downregulation of specific miRNAs in hyperdiploid multiple myeloma mimics the oncogenic effect of IgH translocations occurring in the non-hyperdiploid subtype. Leukemia27(4), 925-931.

Roccaro, A. M., Sacco, A., Thompson, B., Leleu, X., Azab, A. K., Azab, F., ... & Ghobrial, I. M. (2009). MicroRNAs 15a and 16 regulate tumor proliferation in multiple myeloma. Blood, The Journal of the American Society of Hematology113(26), 6669-6680.

 

Russo, G., Isobe, M., Pegoraro, L., Finan, J., Nowell, P. C., & Croce, C. M. (1988). Molecular analysis of at (7; 14)(g35; g32) chromosome translocation in a T cell leukemia of a patient with ataxia telangiectasia. Cell53(1), 137-144.

Saleh, A. D., Savage, J. E., Cao, L., Soule, B. P., Ly, D., DeGraff, W., ... & Simone, N. L. (2011). Cellular stress induced alterations in microRNA let-7a and let-7b expression are dependent on p53. PloS one6(10), e24429.

 

Schwindt, H., Akasaka, T., Zühlke-Jenisch, R., Hans, V., Schaller, C., Klapper, W., ... & Deckert, M. (2006). Chromosomal translocations fusing the BCL6 gene to different partner loci are recurrent in primary central nervous system lymphoma and may be associated with aberrant somatic hypermutation or defective class switch recombination. Journal of Neuropathology & Experimental Neurology65(8), 776-782.

Sonoki, T., Iwanaga, E., Mitsuya, H., & Asou, N. (2005). Insertion of microRNA-125b-1, a human homologue of lin-4, into a rearranged immunoglobulin heavy chain gene locus in a patient with precursor B-cell acute lymphoblastic leukemia. Leukemia19(11), 2009-2010.

Suzuki, H. I., Yamagata, K., Sugimoto, K., Iwamoto, T., Kato, S., & Miyazono, K. (2009). Modulation of microRNA processing by p53. Nature460(7254), 529-533.

 

Volinia, S., Calin, G. A., Liu, C. G., Ambs, S., Cimmino, A., Petrocca, F., ... & Croce, C. M. (2006). A microRNA expression signature of human solid tumors defines cancer gene targets. Proceedings of the National Academy of Sciences103(7), 2257-2261.

Wang, T., Zhang, X., Obijuru, L., Laser, J., Aris, V., Lee, P., ... & Wei, J. J. (2007). A micro‐RNA signature associated with race, tumor size, and target gene activity in human uterine leiomyomas. Genes, Chromosomes and Cancer46(4), 336-347.

Wong, K. Y., So, C. C., Loong, F., Chung, L. P., Lam, W. W. L., Liang, R., ... & Chim, C. S. (2011). Epigenetic inactivation of the miR-124-1 in haematological malignancies. PloS one6(4), e19027.

Yang, R. F., Chen, L. J., Li, J. Y., Li, C. M., Xu, J. R., Wu, Y. J., & Lu, H. (2010). microRNA-21 and microRNA-30b expression in multiple myeloma. Zhonghua xue ye xue za zhi= Zhonghua Xueyexue Zazhi31(1), 38-41.

Zhang, X., Wan, G., Berger, F. G., He, X., & Lu, X. (2011). The ATM kinase induces microRNA biogenesis in the DNA damage response. Molecular cell41(4), 371-383.