1. DNA Methylation in
Young Women
Breast Cancer
PEDRO PENZUTI PACHECO
SUPERVISORS: DR. WAYNE XU, DR. MARSHALL PITZ

2. Background
 Breast Cancer (BC) is the leading cause of death from cancers for women
under 40 years old [1]. Age has repeatedly shown to be an independent
predictor of poor outcome [2].
 Is YWBC a unique disease? Or is it just the fact that YWBC is enriched with more
aggressive BC types?
 We briefly analyzed somatic mutation The Cancer Genome Atlas (TCGA) data
and found no significant difference between the two cohorts.
 Are there epigenomic factors that can differentiate between the two?
[1] (Leclere et al., 2013)
[2] Nixon AJ, Neuburg D, Hayes et al., 1994

3. Hypothesis
 Are there differences in DNA methylation
patterns between young and old women with
BC?
 If so, what are they?
 Could these help explain what drives the
aggressiveness of BC in young women?

4. Methods
 TCGA Methylation Data
 133 young patients (< 45 years old); 643 old patients (≥ 45 years old)
 Illumina Array Platform
 Level 3
 Curated
 Machine learning as the regression method.
 RLScore
 Data is split in half: training and test data.
 Methylation site and gene function analysis.
 Utilized annotation file to trace back methylation and gene location.
 Ingenuity Pathway Analysis to investigate.

5. RLScore
Patients
n = 776
Young,< 45 y.o
n = 133
Old, ≥ 45 y.o
n = 643
Training Group
383 patients
Test Group
393 patients
Obtain
differentiation
criteria
Train the
algorithm
Methylation Sites:
485,587.00 Test the
algorithm

6. Differentiating Methylation Sites
 17 sites were found to be differentially methylated in the young vs old
groups.
 4 in particular deserve to be highlighted
Location Hyper or
Hypomethylated
Gene Regulatory
Feature
chr6:33588617-
33589909
Hypomethylated IP3R3 or ITPR3 Promoter
Associated
chr19:940723-942490 Hypermethylated ARID3A or BRIGHT Unclassified
chr3:147077115-
147077672
Hypermethylated ? ?
chr2:20068428-
20068907
Hypermethylated ? ?

7. IP3R3 / ITPR3
Coupling between type III IP3 receptor (IP3R3) and Big
Potassium voltage- and Calcium-dependent (BKCA)
channel have shown to stimulate BC cell proliferation [3].
Increased expression of IP3R3 is associated with
increased aggressiveness of colon cancer and decreased
long-term survival [4].
[3]:Mound A, Rodat-Despoix L, Bougarn S, Ouadid-Ahidouch H, Matifat F. Molecular interaction and functional coupling between type 3
inositol 1,4,5-trisphosphate receptor and BKCa channel stimulate breast cancer cell proliferation.
[4]:Fonslow, Bryan R Stein, Benjamin D Webb et al. The type III inositol 1,4,5-trisphosphate receptor is associated with aggressiveness of
colorectal carcinoma
Source: genecards.org

8. ARID3A
[5] Samyesudhas SJ, Roy L, Cowden Dahl KD. Differential expression of ARID3B in normal adult tissue and carcinomas.
[6] Bobbs A, Gellerman K, Hallas WM, Joseph S, Yang C, Kurkewich J, et al. ARID3B Directly Regulates Ovarian Cancer Promoting Genes.
[7] Oguz Erdogan AS1, Ozdemirler N, Oyken M, Alper M, Erson-Bensan AE. ARID3B expression in primary breast cancers and breast cancer-derived cell
lines.
Source: genecards.org
 First report showing ARID3A being implicated with BC.
 ARID3B has shown to be differentially expressed in neuroblastoma and ovarian
cancer [5].
 More recently, it has shown to regulate Ovarian Cancer promoting genes. ARID3B
regulates target genes in the Wnt pathway that promote adhesion of ovarian
cancer cells [6].

9. Conclusions and Future Perspective
 We utilized a machine learning approach to try to identify methylation
sites associated with YWBC.
 There are significant differences in the methylation patterns between
young and old women.
 Some of the methylated sites in young women could help explain the
aggressiveness of the tumors found in this group of patients.
 Investigate ITPR3, ARID3A and all the other 13 sites in more depth.
 Optimize the algorithm.

10. Acknowledgements