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How Mobile Elements in “Junk” DNA Promote Cancer – Part 1: Transposon-mediated Tumorigenesis

Author, Writer and Curator: Stephen J. Williams, Ph.D.

How Mobile Elements in “Junk” DNA Promote Cancer – Part 1 Transposon-mediated Tumorigenesis

Word Cloud by Daniel Menzin

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Landscape of Somatic Retrotransposition in Human Cancers. Science (2012); Vol. 337:967-971. (1)

Sequencing of the human genome via massive programs such as the Cancer Genome Atlas Program (CGAP) and the Encyclopedia of DNA Elements (ENCODE) consortium in conjunction with considerable bioinformatics efforts led by the National Center for Biotechnology Information (NCBI) have unlocked a myriad of yet unclassified genes (for good review see (2).  The project encompasses 32 institutions worldwide which, so far, have generated 1640 data sets, initially depending on microarray platforms but now moving to the more cost effective new sequencing technology.  Initially the ENCODE project focused on three types of cells: an immature white blood cell line GM12878, leukemic line K562, and an approved human embryonic cell line H1-hESC.  The analysis was rapidly expanded to another 140 cell types.  DNA sequencing had revealed 20,687 known coding regions with hints of 50 more coding regions.  Another 11,224 DNA stretches were classified as pseudogenes.  The ENCODE project reveals that many genes encode for an RNA, not protein product, so called regulatory RNAs.

However some of the most recent and interesting results focus on the noncoding regions of the human genome, previously discarded as uninteresting or “junk” DNA .  Only 2% of the human genome contains coding regions while 98% of this noncoding part of the genome is actually found to be highly active “with about 4 million constantly communicating switches” (3).  Some of these “switches” in the noncoding portion contain small, repetitive elements which are mobile throughout the genome, and can control gene expression and/or predispose to disease such as cancer.  These mobile elements, found in almost all organisms, are classified as transposable elements (TE), inserting themselves into far-reaching regions of the genome.  Retro-transposons are capable of generating new insertions through RNA intermediates.  These transposable elements are normally kept immobile by epigenetic mechanisms(4-6) however some TEs can escape epigenetic repression and insert in areas of the genome, a process described as insertional mutagenesis as the process can lead to gene alterations seen in disease(7).  In addition, this insertional mutagenesis can lead to the transformation of cells and, as described in Post 2, act as a model system to determine drivers of oncogenesis. This insertional mutagenesis is a different mechanism of genetic alteration and rearrangement seen in cancer like recombination and fusion of gene fragments as seen with the Philadelphia chromosome and BCR/ABL fusion protein (8).  The mechanism of transposition and putative effects leading to mutagenesis are described in the following figure:

Image

Figure.  Insertional mutagenesis based on transposon-mediated mechanism.  A) Basic structure of  transposon contains gene/sequence flanked by two inverted repeats (IR) and/or direct repeats (DR).  An enzyme, the transposase (red hexagon) binds and cuts at the IR/DR and transposon is pasted at another site in DNA, containing an insertion site.  B)   Multiple transpositions may results in oncogenic events by inserting in promoters leading to altered expression of genes driving oncogenesis or inserting within coding regions and inactivating tumor suppressors or activating oncogenes.  Deep sequencing of the resultant tumor genomes ( based on nested PCR from IR/DRs) may reveal common insertion sites (CIS) and oncogenic mutations could be identified.

In a bioinformatics study Eunjung Lee et al.(1), in collaboration with the Cancer Genome Atlas Research Network, the authors had analyzed 43 high-coverage whole-genome sequencing datasets from five cancer types to determine transposable element insertion sites.  Using a novel computational method, the authors had identified 194 high-confidence somatic TE insertion sites present in cancers of epithelial origin such as colorectal, prostate and ovarian, but not in brain or blood cancers.  Sixty four of the 194 detected somatic TE insertions were located within 62 annotated genes. Genes with TE insertion in colon cancers have commonly high mutation rates and enriched genes were associated with cell adhesion functions (CDH12, ROBO2,NRXN3, FPR2, COL1A1, NEGR1, NTM and CTNNA2) or tumor suppressor functions (NELL1m ROBO2, DBC1, and PARK2).  None of the somatic events were located within coding regions, with the TE sequences being detected in untranslated regions (UTR) or intronic regions.  Previous studies had shown insertion in these regions (UTR or intronic) can disrupts gene expression (9). Interestingly, most of the genes with insertion sites were down-regulated, suggested by a recent paper showing that local changes in methylation status of transposable elements can drive retro-transposition (10,11).  Indeed, the authors found that somatic insertions are biased toward the hypomethylated regions in cancer cell DNA.  The authors also confirmed that the insertion sites were unique to cancer and were somatic insertions, not germline (germline: arising during embryonic development) in origin by analyzing 44 normal genomes (41 normal blood samples from cancer patients and three healthy individuals).

The authors conclude:

“that some TE insertions provide a selective advantage during tumorigenesis,

rather than being merely passenger events that precede clonal expansion(1).”

The authors also suggest that more bioinformatics studies, which utilize the expansive genomic and epigenetic databases, could determine functional consequences of such transposable elements in cancerThe following Post will describe how use of transposon-mediated insertional mutagenesis is leading to discoveries of the drivers (main genetic events) leading to oncogenesis.

1.            Lee, E., Iskow, R., Yang, L., Gokcumen, O., Haseley, P., Luquette, L. J., 3rd, Lohr, J. G., Harris, C. C., Ding, L., Wilson, R. K., Wheeler, D. A., Gibbs, R. A., Kucherlapati, R., Lee, C., Kharchenko, P. V., and Park, P. J. (2012) Science 337, 967-971

2.            Pennisi, E. (2012) Science 337, 1159, 1161

3.            Park, A. (2012) Don’t Trash These Genes. “Junk DNA may lead to valuable cures. in Time, Time, Inc., New York, N.Y.

4.            Maksakova, I. A., Mager, D. L., and Reiss, D. (2008) Cellular and molecular life sciences : CMLS 65, 3329-3347

5.            Slotkin, R. K., and Martienssen, R. (2007) Nature reviews. Genetics 8, 272-285

6.            Yang, N., and Kazazian, H. H., Jr. (2006) Nature structural & molecular biology 13, 763-771

7.            Hancks, D. C., and Kazazian, H. H., Jr. (2012) Current opinion in genetics & development 22, 191-203

8.            Sattler, M., and Griffin, J. D. (2001) International journal of hematology 73, 278-291

9.            Han, J. S., Szak, S. T., and Boeke, J. D. (2004) Nature 429, 268-274

10.          Reichmann, J., Crichton, J. H., Madej, M. J., Taggart, M., Gautier, P., Garcia-Perez, J. L., Meehan, R. R., and Adams, I. R. (2012) PLoS computational biology 8, e1002486

11.          Byun, H. M., Heo, K., Mitchell, K. J., and Yang, A. S. (2012) Journal of biomedical science 19, 13

Other research paper on ENCODE and Cancer were published on this Scientific Web site as follows:

Expanding the Genetic Alphabet and linking the genome to the metabolome

Junk DNA codes for valuable miRNAs: non-coding DNA controls Diabetes

ENCODE Findings as Consortium

Reveals from ENCODE project will invite high synergistic collaborations to discover specific targets

ENCODE: the key to unlocking the secrets of complex genetic diseases

Impact of evolutionary selection on functional regions: The imprint of evolutionary selection on ENCODE regulatory elements is manifested between species and within human populations

Metabolite Identification Combining Genetic and Metabolic Information: Genetic association links unknown metabolites to functionally related genes

Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

Commentary on Dr. Baker’s post “Junk DNA codes for valuable miRNAs: non-coding DNA controls Diabetes”

Cancer Genomics – Leading the Way by Cancer Genomics Program at UC Santa Cruz

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