Correlació MLEE – identificació fenotípica.

We were attentive to the importance of defining genomic regions where the

methylation levels are unique. Large epigenetic changes that occur in specific regions

of the genome might be of additional significance.

So, we analysed particular patterns in the distribution of the elderly AML DMRs

across genomic positions. We made two main observations: 1) most chromosomes

had comparable amounts of hyperMRs and hypoMRs, except for chromosomes 16

and 17 where the number of hypermethylations in samples of cluster of elderly AML

was clearly high (Figure 4.5.4A) and 2) there was a tendency of the hyperMRs to be

located in the tips of chromosomes (Figure 4.5.4B).

The higher methylation levels of the samples from the cluster of the elderly were

more striking in chromosome 17. This was the chromosome with the highest number

of hyperMRs (109 of the 979, 11%) and many of these regions were located in the

q25.3 band (Figure 4.5.4B, box). This was an unusual concentration of

hypermethylation on the tip of chr17 in which 35 hyperMRs (35/109, 32%, Table 4.5.1)

were concentrated in about 2.4Mb (highest density area in the blue box of Figure

4.5.4B).

Within this area, there were 2 major regions strongly hypermethylated, the

regions related to neighboring genes ACTG1/KIAA1447 and to RPTOR/CHMP6.

These were the 4 genes that had the highest number of hypermethylated regions from

the cluster of elderly associated to them. There were 9 hyperMRs per each pair of

genes (ACTG1/KIAA1447 and RPTOR/CHMP6) and each of these regions related at

least to 3CpGs.

Figure 4.5.4 Distribution of DMRs of the cluster of elderly AML across

chromosomes.

(A) The bar graph reports the number of DMRs from the cluster of elderly vs cluster of young in each

chromosome (comparison of hierarchical clusters in Figure 4.5.1). These were classified as

hypermethylated (hyperMRs, in red) or hypomethylated (hypoMRs, in blue) according to the methylation

level in the cluster of elderly AML. (B) The graph shows the hyperMRs plotted according to their genomic

position from the start of the short arm to the end of the long arm (oriented left to right) of chromosomes

1 to 22. The density plots represent the number of hyperMRs calculated by partitioning the genome in

0.2Mb regions. Chromosome 17q25.3 band was highlighted with a blue box. The scale of genomic regions

is given in Mb. Red region of chromosome ideograms marks the centromeres.

Table 4.5.1 HyperMRs of the

cluster

of

elderly

AML

concentrated in chr17 q25.3.

The table shows genomic positions of 35

regions obtained with the bumphunter

algorithm as hypermethylated in the cluster

of elderly (Figure 4.5.1) and the genes

correlated to each region. These are

spanning the region chr17:77901030-

80292252 (using assembly hg19). Each

gene association was calculated by

GREAT125 _{with the predefined association}

rule: Basal + extension: 5kb upstream, 1kb

downstream, 1Mb maximum extension and

curated regulatory domains included. The

distance of each gene to the region CpGs

is given in parentheses.

When examined in detail different CpGs across this 2.4Mb region have different

factors that correlate with their methylation levels. Some CpGs seem strongly affected

by mutations and other clearly more related to patients’ age. As an example of this, we

show the regions of the 3 adjacent genes KIAA1447, ACTG1 and FSCN2 (Figure

4.5.5). Some CpGs were clearly different between the 2 hierarchical clusters

(examples in boxes A and B), while others were particularly hypomethylated in

DNMT3A/NPM1/FLT3 mutated samples (example in box C) and/or very strongly

Figure

4.5.5

Distinct

methylation

profiles

of

elderly

in

the

KIAA1447/ACTG1/FSCN2 region.

DNA-methylation from the CpGs in the tip of the long arm of chromosome 17 using beta-values scaled

from unmethylated (-5, blue) to fully methylated (5, red). In the depiction the 273 AML samples from the

two cohorts (TCGA and SAL) are in horizontal and positions of CpGs according to GRCh37/hg19 are in

vertical. The CpG islands of the genomic region are marked with blue boxes. Patients are annotated

according to the group of the 1st _{division of hierarchical clustering (cluster of elderly, purple annotation, or}

young, orange annotation, Figure 4.5.1), age group according to patient chronological age (elderly for ≥65

years old, black annotated, or young for <65 years old, yellow annotation) and mutation information for 2

relevant high rate mutated groups (IDH1/2, red annotation, and triple mutated DNMT3A/NPM1/FLT3, blue

annotation).

The particular hypermethylation pattern of the tip of chr17 overlapped several

genes that were part of endocytosis and phagocytosis processes (see gene

enrichment in Figure 4.5.3), with emphasis on functions in actin organization. The

ACTG1 codes for the gama-actin in the cellular cytoskeletons and is one of the genes

in the biological process enrichment phagocytosis of the hyperMRs136_{. Gama-actin is}

also important for cell adhesion, being involved with the cadherins/protocadherins and

found many other DMRs). The third gene FSCN2 (Fascin Actin-Bundling Protein 2,

Retinal) codes a protein with an actin-binding function which is expressed only in retina

and blood136_.

Interestingly, in their study Bullinger and colleagues in 2010137 _{connected the}

hypermethylation in this region of the chr17 long arm overlapping the neighboring

genes KIAA1447 and ACTG1 to poor survival in AML (these confirmations are marked

with * in Table 4.5.2B, next chapter). Not much is known about KIAA1447, an alias of

BAHCC1 (BAH Domain And Coiled-Coil Containing 1). This is a gene encoding a

protein with a chromatin binding domain, interacting with the chromatin silencing

complex for transcription regulation136_.

Furthermore, BAIAP2 is the gene that encodes BAI1 Associated Protein 2, a

protein that functions as an insulin receptor tyrosine kinase substrate in the brain136_{. It}

interacts with CDC42, being necessary for the CDC42-mediated reorganization of the

actin cytoskeleton and whose RNAi phenotype is a reduction of endocytosis.

Moreover, CHMP6 is also involved in endocytosis and is in this genomic region136_.

CHMP6 is a probable core component of the endosomal sorting required for transport

complex III which is involved in multivesicular bodies formation and sorting of

endosomal cargo proteins136_.

Besides BAIAP2, in this region were two other genes of proteins involved in

metabolism, namely in insulin response, RPTOR and FASN. The gene RPTOR codes

for the protein Regulatory Associated Protein Of MTOR Complex 1136_{. RPTOR or}

RAPTOR is involved in the control of the mammalian target of rapamycin complex 1

(mTORC1) activity which regulates cell growth, survival, and autophagy/longevity in

response to nutrient and hormonal signals136_{. A DMR overlapping RPTOR was found}

in the most recent paper reporting DMRs with correlations to survival probability (using

this TCGA methylation data)138_{. They advanced this gene to have one of the 8 DMRs}

signature that could be used as a prognostic marker and have a crucial role in AML.

In turn, FASN codes for the Fatty acid synthase, which main function is to

catalyze the synthesis of palmitate from acetyl-CoA and malonyl-CoA and is a

In document Diversitat fenotípica i genotípica del gènere "Aeromonas" (página 172-200)