475: A Cell Line Fitness Score Predicts Cancer Risk in Li-Fraumeni Syndrome

[00:00:03] People can carry a disease causing change in the same gene and still show very different clinical pictures from mild to severe. Some meet the clinical criteria for a hereditary cancer syndrome, others do not. The gene is TP53. The syndrome is called Li Fraumeni syndrome and it brings a lifelong increased risk of many solid tumors as well as cancers of the blood. [00:00:27] So why would the same gene behave so differently? And could a measurement made in cells in a dish help tell which carriers face the higher risk? [00:00:38] The answer matters for a practical reason. A cancer surveillance protocol has been shown to significantly improve long term survival in people with Li Fraumeni syndrome. To adjust such measures to the actual risk, estimating different levels of cancer risk is of critical importance. [00:00:55] Today's study asks whether a single number measured in laboratory screen of thousands of TP53 mutations can help make that adjustment. [00:01:09] This is base by base. Every episode is built with AI tools from a real open Access paper curated by a human and every claim is checked against the paper before we publish. You'll find this episode's fact check score on our website. [00:01:23] Now back to the story. [00:01:31] Celebrate the work of Judith Penkert, Annika Grossenig, Christian Kratz and colleagues from Hanover Medical School in Germany who have advanced our understanding of cancer risk in Li Fraumeni syndrome. This base by base episode is based on their Open Access research letter Deep CRISPR Mutagenesis predicts cancer risk in Li Fraumeni Syndrome, published in the American Journal of human genetics in 2026. [00:02:00] Begin with the gene TP53 encodes a transcription factor also called TP53. It controls genes involved in the cell cycle in apoptosis, which is programmed cell death, and in senescence. It also touches stem cell differentiation, metabolism and DNA repair. About 50% of all human cancers carry somatic TP53 mutations. [00:02:24] When a disease causing variant is in the germline instead or is a postzygotic somatic mosaic, the result is Li Fraumeni syndrome. [00:02:34] The increasing use of genetic sequencing in clinical medicine has revealed a wider picture. Carriers of pathogenic or likely pathogenic TP53 variants show a range of mild to severe clinical phenotypes. They do not always meet the clinical genetic testing criteria called the CHOMPRIT criteria. This led to a classification called the Lie Fraumeni spectrum. [00:02:58] Carriers who meet the criteria are said to have Lie Fraumeni syndrome. Carriers who do not are said to have attenuated Lie Fraumeni syndrome. [00:03:09] What decides where a carrier falls? Several things are known to matter. There are genetic modifiers and environmental factors such as genotoxic cancer therapies. There are the neoantigenic properties of the variant and there is the function of the variant itself itself. Null variants predicted to make no protein at all and other severely impaired variants are significantly associated with the full syndrome. Variants with milder functional disruption are associated with the attenuated form. So the question becomes how to measure that disruption. Well, This is where an earlier study comes in. It used deep crispr mutagenesis to map the functional diversity of mutations in the DNA binding domain of TP52. [00:03:57] A total of 9,225 different mutations were introduced into a colorectal cancer cell line. The mutant cells were then treated with different TP53 activators. [00:04:08] Cells with benign variants underwent apoptosis and died. Cells with pathogenic variants survived next generation sequencing counted which mutants survived and the result for each one was expressed as a relative fitness score. Synonymous mutations which do not change were mostly benign with a median score of -1 nonsense mutations, frameshift insertions or deletions and in frame deletions were mostly pathogenic with a median score of 1. [00:04:41] Missense variants which swap a single amino acid, spread across a broad range of scores. [00:04:49] The Hanover team turned to patients. They analyzed a cohort of 728 individuals with Li Fraumeni syndrome from 24548 families enrolled in the German Cancer Predisposition syndrome registry. For 437 individuals from 168 families, three things were available the underlying TP53 variant proven or inferred from the pedigree, its relative fitness score and survival data. [00:05:20] The question was whether the score could predict cancer risk. [00:05:30] To compare carriers, the authors used Kaplan Meier analysis of cancer free survival time, the time each person lived before a first cancer. They estimated an optimal cut point for the score based on time to first malignancy. That cut point was 0.673. The result was carriers of variance scoring 0.673 or higher developed cancer significantly earlier than carriers of variance scoring below it. [00:06:00] How large was the difference? A score below the cut point was associated with significantly longer cancer free survival with a hazard ratio of 0.41. The 95% confidence interval ran from 0.25 to 0.66. The P value was 0.0002. [00:06:21] In this analysis, a lower score went with a later first cancer. [00:06:28] There was an obvious objection. Null variants are already known to carry a high cancer risk. Perhaps they alone were driving the curves. So the authors ran a separate analysis without them. Among the remaining 407 individuals whose variants are predicted to produce an altered protein, the pattern held the hazard ratio was 0.43 with a P value of 0.0005. [00:06:54] None of these individuals had been pretreated with genoto therapies and sex did not influence the results. [00:07:03] The authors then looked at families across all 168 families with an available score and sufficient clinical data. They asked whether the score predicts clinical severity within the Li Fraumeni spectrum. Families with a score of 0.673 or higher MET the definition of the full syndrome in 110 out of 148 families, that is 74.3%. [00:07:28] Among families with a lower score, only 3 out of 20 met it, 15%. [00:07:38] As a ratio, families with a high score were about five times as likely to meet the full definition. A relative risk of 5.0 families with a low score were more likely to meet the criteria of the attenuated form. [00:07:52] The authors suggest that these scores can be incorporated into future variant classification algorithms. [00:07:58] The aim is to identify variants with atypical penetrance and so enable tailored cancer surveillance. They also see a broader deep CRISPR mutagenesis can be used to predict the clinical severity of a genetic condition. [00:08:15] The authors list three limitations. [00:08:17] First, the differences in cancer free survival were not validated in independent cohorts, although the cohort was large and the differences were substantial and biologically plausible. The second, the scores were established in a single colorectal cell line and cell type specificity cannot be ruled out. [00:08:36] Third, scores are currently not available for mutant proteins with changes outside the DNA binding domain. [00:08:47] So here is where this leaves us. A laboratory screen scored thousands of TP53 mutations by whether cells carrying them survived. [00:08:56] In 437 people with Lai Frumeni Syndrome, a score of 0.673 or higher was associated with an earlier first cancer, and families with high scores more often met the criteria for the full syndrome. The letter is dedicated in memory of Joseph F. Frumeni Jr. What would it take for a cell score like this to guide the surveillance plan of a real. [00:09:24] This episode was based on an Open Access article under the CCBY 4.0 license. You can find a direct link to the paper and the license in our episode description. If you enjoyed this, follow or subscribe in your podcast app and leave a five star rating. If you'd like to support our work, use the donation link in the description. Thanks for listening and join us next time as we explore more science base by base.