Abstract
BackgroundGene expression is highly variable across tissues of multi-cellular organisms, influencing the codon usage of the tissue-specific transcriptome. Cancer disrupts the gene expression pattern of healthy tissue resulting in altered codon usage preferences. The topic of codon usage changes as they relate to codon demand, and tRNA supply in cancer is of growing interest.MethodsWe analyzed transcriptome-weighted codon and codon pair usage based on The Cancer Genome Atlas (TCGA) RNA-seq data from 6427 solid tumor samples and 632 normal tissue samples. This dataset represents 32 cancer types affecting 11 distinct tissues. Our analysis focused on tissues that give rise to multiple solid tumor types and cancer types that are present in multiple tissues.ResultsWe identified distinct patterns of synonymous codon usage changes for different cancer types affecting the same tissue. For example, a substantial increase in GGT-glycine was observed in invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), and mixed invasive ductal and lobular carcinoma (IDLC) of the breast. Change in synonymous codon preference favoring GGT correlated with change in synonymous codon preference against GGC in IDC and IDLC, but not in ILC. Furthermore, we examined the codon usage changes between paired healthy/tumor tissue from the same patient. Using clinical data from TCGA, we conducted a survival analysis of patients based on the degree of change between healthy and tumor-specific codon usage, revealing an association between larger changes and increased mortality. We have also created a database that contains cancer-specific codon and codon pair usage data for cancer types derived from TCGA, which represents a comprehensive tool for codon-usage-oriented cancer research.ConclusionsBased on data from TCGA, we have highlighted tumor type-specific signatures of codon and codon pair usage. Paired data revealed variable changes to codon usage patterns, which must be considered when designing personalized cancer treatments. The associated database, CancerCoCoPUTs, represents a comprehensive resource for codon and codon pair usage in cancer and is available at https://dnahive.fda.gov/review/cancercocoputs/. These findings are important to understand the relationship between tRNA supply and codon demand in cancer states and could help guide the development of new cancer therapeutics.
Highlights
Gene expression is highly variable across tissues of multi-cellular organisms, influencing the codon usage of the tissue-specific transcriptome
We examined codon and codon pair usage for each tissue to better understand the relationships between cancer types and their respective normal tissues
4 subtypes of lung adenocarcinoma (LUAD) are more similar to each other than they are to normal lung tissue or to lung squamous cell carcinoma (LUSC) according to both dendrograms; normal bladder tissue is the most similar to normal endometrial tissue than to any other tissue, and transitional cell carcinoma of the bladder is most similar to endometrial adenocarcinomas than other tissues; normal liver and normal bile duct tissue are more similar to each other, but hepatocellular carcinoma and cholangiocarcinoma do not cluster together
Summary
Gene expression is highly variable across tissues of multi-cellular organisms, influencing the codon usage of the tissue-specific transcriptome. Cancer disrupts the gene expression pattern of healthy tissue resulting in altered codon usage preferences. The topic of codon usage changes as they relate to codon demand, and tRNA supply in cancer is of growing interest. Since 2006, with the advent of next-generation sequencing, RNA-seq has been leveraged to investigate the transcriptome of cancer cells [1]. Genetic sequencing has identified many somatic mutations that are predictive of cancer development, progression, and the alteration of downstream pathways [3]. A multitude of studies have focused on specific mutations and their impact on the cancer phenotype, the tumor suppressor gene p53 and oncogenes of the Ras family [4,5,6,7]. Other noteworthy cancer-related genes that have been extensively studied include breast cancer type 1 susceptibility protein (BRCA1) and breast cancer type 2 susceptibility protein (BRCA2), adenomatous polyposis coli (APC), and epidermal growth factor receptor (EGFR) in various types of breast, colorectal, and lung cancer, respectively [8,9,10]
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