By Michelle Perron
TP53, the tumor suppressor gene known as the "guardian of the genome," can mount a potent defense against cancers. When this gene is mutated, that defense collapses, potentially leading to tumor development.
Researchers have been studying TP53 for years and their work has led to greater understanding of TP53 activity. A comprehensive study published recently in Cell Reports (2019; https://doi.org/10.1016/j.celrep.2019.07.001) provides new information about the gene's expression and the clinical outlook associated with its mutation.
The p53 tumor suppressor protein is a transcription factor that inhibits cell division or survival in response to stresses. As multiple authors have described, TP53 acts as a fail-safe mechanism of cellular defenses against cancer. For many cancers, mutations in TP53 have been linked to a poorer prognosis. However, many variables can affect outcomes in patients with a TP53 mutation. Researchers in this new study sought to identify a more accurate readout of p53 function in human cancers that would not be based strictly on mutation of the TP53 gene and might lead to more accurate prognostic predictions.
The team, led by Larry Donehower, PhD, incorporated an approach similar to that of The Cancer Genome Atlas (TCGA) network, which has simultaneously examined tumors of many cancer types on five independent data platforms. Donehower is Professor of Molecular Virology and Microbiology at Baylor College of Medicine in Houston and a member of the faculty of the Human Genome Sequencing Center at Baylor College of Medicine. The TCGA network contributed to the acquisition of patient samples and the generation of data underlying the study.
The team at Baylor analyzed TP53 mutations in whole exome sequences of 10,225 TCGA patients across 32 cancer types. In this group, they identified 3,786 patients with TP53 mutations. Patients with some cancer types had high frequencies of TP53 mutation (>90%) while other cancer types exhibited few or no TP53 mutations.
The Baylor team's study integrated two data platforms (TCGA exome sequencing and copy number determination) to analyze individual TP53 alleles in both wild-type and mutant TP53 tumors. They found that more than 91 percent of tumors with TP53 mutations had structural loss of both functional TP53 alleles. These results indicate that a strong selection for loss of function of both TP53 alleles exists, Donehower said. "This is further confirmation of TP53 as a classic recessive tumor suppressor."
Another important determination in this study is in the area of genomic stability. Genomic instability is a central characteristic of most cancers, and TP53 is believed to prevent this instability. The Baylor team's analysis confirmed that TP53 mutation does affect genomic stability, global RNA, miRNA, and protein expression across most cancer types.
"Our examination of TCGA cancer types revealed that 19 of 23 examined cancer types had significantly enhanced copy number instability in the mutant TP53 cohort relative to their wild-type TP53 counterparts," the researchers wrote. "This global copy number instability was closely associated with increased amplification of known oncogenes and deep depletion of known tumor suppressors." Increased changes in cancer driver gene copy number are likely to be one mechanism by which TP53 mutation may result in cancers with poorer prognosis.
The final conclusion of the study is perhaps the most impactful because it is related to prognosis. Analysis of the mutant TP53 cancers across the RNA, miRNA, and protein expression data platforms consistently showed strong enhancement of pathways regulating cell-cycle progression, the authors wrote. They found that TP53 mutation status was only weakly predictive of overall survival across most cancers, but a p53 signature based on relative RNA expression of four genes consistently upregulated in mutant TP53 cancers was much more prognostically predictive. They found that 11 of 24 TCGA cancers showed significantly poorer survival with the high p53 signature, and that no cancer types showed poorer survival with a low p53 signature.
"We developed a normalization approach for each of 11 cancer types that would facilitate prognostic predictions on samples from individual patients entering the clinic," the authors wrote. "Thus, we believe this four-gene RNA expression signature could serve as an improved prognostic marker and a better indicator of the absence of p53 functionality in some cancer types."
While the authors conceded that many of their discoveries on TP53 mutation status in human cancers have been reported previously, Donehower noted that earlier studies were performed in a single cancer type with one or two data collection methods. The authors pointed out that the massive dataset provided by TCGA, along with collection of data by five distinct data platforms, has provided a richer, more comprehensive look at the genes and pathways affected in cancers with TP53 mutations.
Donehower said this research may also contribute to prognostic predictions. "This paper is mostly reinforcing what we already know, but we believe in a much more comprehensive way," he explained. "One contribution is that we have enhanced our understanding of mechanisms for how p53 is mutated and what cell signaling pathways are activated when this occurs. More importantly, and perhaps more helpful from an oncologist's point of view, we can look at the expression signature of a cancer and predict prognosis better than that obtained merely from TP53 mutation status."
Michelle Perron is a contributing writer.