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Abstract 1506: Identification of genes with age-dependent expressions in breast cancer patients

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Abstract Age is the number one risk factor for breast cancer development. The breast cancer incidence rate increases with age, following beta distribution, which is approximately linear in range from 30 to 70 years old [1]. Transcriptome alterations have been shown to promote tumorigenesis for many types of cancers. Therefore, we hypothesize that the genes with altered expression during aging may promote breast cancer development. Using TCGA data, we extracted whole transcriptome profiling data of matched normal tissues from 82 female patients with age at diagnosis and menopausal status available. The RSEM estimated raw reads counts data were normalized by library sizes, log2 transformed and further normalized by quantile normalization. Removal of 25% of genes with lowest mean expressions resulted in subsequent analyses on 15,398 genes. We applied simple linear regression to study the association between gene expression level and age at diagnosis on all the 82 patients, and on the 54 post-menopausal patients to reduce the leverage effect of pre-menopausal patients with limited age range. The genes with significant correlation are filtered by the criteria: 1) R2 value is among the highest 5%, 2) absolute value of slope for age is among the highest 5% and 3) adjusted p value for the slope is among the lowest 5%. We identified 210 upregulated and 98 downregulated genes in all patients, as well as 103 upregulated and 164 downregulated genes in post-menopausal patients only. The unions of these genes (258 upregulated and 240 downregulated) are considered as genes affected by age. A combination of methods using moderate hierarchical t test (R/limma) and moderate fitting based on negative binomial distribution (R/DESeq2), with and without Surrogate Variable Analysis for potential confounders (R/SVA), results in identification of 498 upregulated and 256 downregulated genes altered by menopause by comparing post-menopausal to pre-menopausal patients (FDR < 0.05). Exclusion of these menopause affected genes from those genes affected by age (258 upregulated and 240 downregulated) results in 148 upregulated and 189 downregulated genes during aging. Ingenuity Pathway Analysis shows that these genes are significantly enriched for functions associated with tumorigenesis and functions in cancer. In summary, the transcriptome profiling alterations during aging are associated with development of cancer. Functional analyses of some of the age-associated genes are currently underway. Funding: CPRIT Research Training Award (RP140105) Reference: 1. Francesco Pompei and Richard Wilson (2001). Age Distribution of Cancer: The incidence Turnover at Old Age. Human and Ecological Risk Assessment: Vol. 7, No. 6, pp. 1619-1650. Citation Format: Xiang Gu, LuZhe Sun. Identification of genes with age-dependent expressions in breast cancer patients. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1506.
American Association for Cancer Research (AACR)
Title: Abstract 1506: Identification of genes with age-dependent expressions in breast cancer patients
Description:
Abstract Age is the number one risk factor for breast cancer development.
The breast cancer incidence rate increases with age, following beta distribution, which is approximately linear in range from 30 to 70 years old [1].
Transcriptome alterations have been shown to promote tumorigenesis for many types of cancers.
Therefore, we hypothesize that the genes with altered expression during aging may promote breast cancer development.
Using TCGA data, we extracted whole transcriptome profiling data of matched normal tissues from 82 female patients with age at diagnosis and menopausal status available.
The RSEM estimated raw reads counts data were normalized by library sizes, log2 transformed and further normalized by quantile normalization.
Removal of 25% of genes with lowest mean expressions resulted in subsequent analyses on 15,398 genes.
We applied simple linear regression to study the association between gene expression level and age at diagnosis on all the 82 patients, and on the 54 post-menopausal patients to reduce the leverage effect of pre-menopausal patients with limited age range.
The genes with significant correlation are filtered by the criteria: 1) R2 value is among the highest 5%, 2) absolute value of slope for age is among the highest 5% and 3) adjusted p value for the slope is among the lowest 5%.
We identified 210 upregulated and 98 downregulated genes in all patients, as well as 103 upregulated and 164 downregulated genes in post-menopausal patients only.
The unions of these genes (258 upregulated and 240 downregulated) are considered as genes affected by age.
A combination of methods using moderate hierarchical t test (R/limma) and moderate fitting based on negative binomial distribution (R/DESeq2), with and without Surrogate Variable Analysis for potential confounders (R/SVA), results in identification of 498 upregulated and 256 downregulated genes altered by menopause by comparing post-menopausal to pre-menopausal patients (FDR < 0.
05).
Exclusion of these menopause affected genes from those genes affected by age (258 upregulated and 240 downregulated) results in 148 upregulated and 189 downregulated genes during aging.
Ingenuity Pathway Analysis shows that these genes are significantly enriched for functions associated with tumorigenesis and functions in cancer.
In summary, the transcriptome profiling alterations during aging are associated with development of cancer.
Functional analyses of some of the age-associated genes are currently underway.
Funding: CPRIT Research Training Award (RP140105) Reference: 1.
Francesco Pompei and Richard Wilson (2001).
Age Distribution of Cancer: The incidence Turnover at Old Age.
Human and Ecological Risk Assessment: Vol.
7, No.
6, pp.
1619-1650.
Citation Format: Xiang Gu, LuZhe Sun.
Identification of genes with age-dependent expressions in breast cancer patients.
[abstract].
In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA.
Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1506.

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