Abstract
The genetic alterations that underlie cancer development are highly tissue-specific with the majority of driving alterations occurring in only a few cancer types and with alterations common to multiple cancer types often showing a tissue-specific functional impact. This tissue-specificity means that the biology of normal tissues carries important information regarding the pathophysiology of the associated cancers, information that can be leveraged to improve the power and accuracy of cancer genomic analyses. Research exploring the use of normal tissue data for the analysis of cancer genomics has primarily focused on the paired analysis of tumor and adjacent normal samples. Efforts to leverage the general characteristics of normal tissue for cancer analysis has received less attention with most investigations focusing on understanding the tissue-specific factors that lead to individual genomic alterations or dysregulated pathways within a single cancer type. To address this gap and support scenarios where adjacent normal tissue samples are not available, we explored the genome-wide association between the transcriptomes of 21 solid human cancers and their associated normal tissues as profiled in healthy individuals. While the average gene expression profiles of normal and cancerous tissue may appear distinct, with normal tissues more similar to other normal tissues than to the associated cancer types, when transformed into relative expression values, i.e., the ratio of expression in one tissue or cancer relative to the mean in other tissues or cancers, the close association between gene activity in normal tissues and related cancers is revealed. As we demonstrate through an analysis of tumor data from The Cancer Genome Atlas and normal tissue data from the Human Protein Atlas, this association between tissue-specific and cancer-specific expression values can be leveraged to improve the prognostic modeling of cancer, the comparative analysis of different cancer types, and the analysis of cancer and normal tissue pairs.
Highlights
The biology of human cancer is highly tissue and cell type-specific [1,2,3,4,5]
Examples of driver genes that are altered in multiple cancer types but have a tissue-specific functional impact include BRCA1/BRCA2, which are impacted by germ-line mutation but lead to cancer primarily in estrogen-sensitive tissues [9], and BRAF, which can be effectively inhibited in BRAFmutated melanoma but not in BRAF-mutated colon cancer [10]
Most research exploring the joint analysis of normal tissue and cancer genomic data has focused on the analysis of tumor and adjacent normal samples
Summary
The biology of human cancer is highly tissue and cell type-specific [1,2,3,4,5]. Most cancer driver genes are altered in only a small number of cancer types and, for drivers that are broadly mutated, the impact of the alteration often varies significantly between tissue types. Examples of driver genes that are altered in multiple cancer types but have a tissue-specific functional impact include BRCA1/BRCA2, which are impacted by germ-line mutation but lead to cancer primarily in estrogen-sensitive tissues (e.g., breast and ovaries) [9], and BRAF, which can be effectively inhibited in BRAFmutated melanoma but not in BRAF-mutated colon cancer [10]. Examples of cell extrinsic factors include exposure to estrogen in breast and ovarian tissue and the consequent vulnerability to BRCA1/BRCA2 mutations, and exposure to UV radiation in melanoma which leads to both increased sensitivity to the alteration of nucleotide excision repair genes and to an increase in the number of neoantigens and improved response to immunotherapy [4]
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