Driver mutations of cancers have typically been identified from protein-coding genes. However, as these protein-coding regions account for only 2% of the whole genome, scientists have started to look into the abyss of the remaining 98% to find further clues into cancer.
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Two related studies, from the Ontario Institute for Cancer Research, published in Nature journal have reported their findings of a common dark matter DNA mutation associated with various types of blood, brain, and liver cancers. The discovery of this dark matter mutation might enable the development of targeted therapies.
What is non-coding DNA?
Although human beings are the most complex organism on planet earth, their modest number of genes does not correspond with this. With 21,000 genes, even the simple, 1mm length worm, C.elegans, has a similar number of genes at 20,000, while the mouse, Mus musculus, has 30,000.
However, humans have a much greater proportion of non-coding DNA concerning other species. This non-coding DNA, also known as dark matter, once thought to offer no functionality, evidently determines species complexity. While 75% of the DNA is read, only a small fraction gives rise to protein-coding genes.
The rest gives rise to non-coding RNA. This RNA is thought to have a major role in gene regulation, although most of their exact functions are still unknown. Their temporal expression and exclusivity to certain tissue types prove they provide specific roles for certain stages in development and tissue differentiation.
However, the unstable nature of these RNAs and their presence in tiny amounts in the cell has made their study difficult.
Dark matter DNA mutations in cancer
The mutation, discovered by the Ontario lead group, is called U1-snRNA. It is an error in the U1 spliceosomal small nuclear RNA, which makes up the spliceosome. The frequent A>C mutations in the 3rd base of U1 snRNA, affect its ability to recognize the 5’ splice site of pre-mRNA. This recognition site has been highly conserved across eukaryotes for nearly 1 billion years, which signifies its importance. The resulting base pair change from A-U to C-G creates new and excessive splice sites in genes.
Aberrant splicing of genes affects their transcription and although the mutation is not in a protein-coding gene, the single error may affect hundreds of proteins down the line. The mutation has been shown to affect the transcription of cancer drivers such as tumor suppressor genes, PTCH1, and oncogenes, GLI2, and CCND2.
The studies investigated tissue samples from medulloblastomas, cerebellar cancer. After sequencing the genomes of 114 medulloblastomas and investigating the non-coding regions, they identified the U1snRNA mutation in 8.8%. They found that the mutation was highly restricted to SHH medulloblastoma, particularly to subtypes SHH delta (present in 97% of adult cases) and SHH⍺ (in 25% of adolescents with additional TP53 mutations).
It was, however, found to be absent in infants. The almost entirely restricted expression of the mutation to SHH delta and SHH⍺ subtypes supports its role in tumor genesis, however, a knockdown of the mutation is required to prove this.
The Ontario group also determined the presence of U1snRNA mutations across different cancers using data from the ‘Pan-Cancer Analysis of Whole Genomes’ (PCAWG) study, a project that has determined common mutations in over 2500 cancers across 37 tumor types.
They found that mutations in U1snRNA were present in chronic lymphocytic leukemia (CLL), hepatocellular carcinoma (HCC), and B-cell non-Hodgkin lymphoma, some of the most common yet difficult to treat cancers. They found mis-splicing of known cancer drivers in samples of HCC and CLL, confirming how these resulting mistranscribed proteins can propagate cancer.
Dark matter to improve cancer diagnosis
Variations in dark matter may enable enhanced diagnostics of different subtypes of cancer, which are otherwise genomically indistinguishable. A study published in ‘PLOS Computational Biology’ has developed a new machine-learning algorithm called ReVeaL, which allows discrimination of these variants to distinguish between subtle blood cancer subtypes.
Likewise, the Ontario group suggested that the U1snRNA mutation could be used as a disease marker for CLL. Furthering the understanding of biomarkers of cancer in this way improves disease etiology to improve patient treatment.
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Advances in driver discovery and cancer treatment
This discovery of dark matter cancer drivers is important for driver research as studies can now investigate a much wider variety of genomic areas, not limited to the protein-coding regions. Dark matter mutations could also become promising novel targets for the treatment of difficult to treat cancers. Especially in cancers that have many mutated proteins.
Current immunotherapies have been suggested as treatment options to target the many mis-spliced and cancer-driving proteins. Inhibition of SF3B1 has also been suggested as it has been shown to kill tumor cells that contain splicing mutations.
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