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Yeast As a Chassis for Developing Functional Assays to Study Human P53
Published on: August 4, 2019
Germline and Somatic Genetic Variants in the p53 Pathway Interact to Affect Cancer Risk, Progression, and Drug
Ping Zhang1, Isaac Kitchen-Smith1, Lingyun Xiong1
1Ludwig Institute for Cancer Research, University of Oxford, Nuffield Department of Clinical Medicine, Old Road Campus Research Building, Oxford, United Kingdom.
Abstract:
Insights into oncogenesis derived from cancer susceptibility loci (SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, although both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of prosurvival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies. SIGNIFICANCE: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets.
Insights
Cancer susceptibility single nucleotide polymorphisms (SNPs) interact with TP53 mutations to influence cancer risk and progression. Targeting the KITLG/c-KIT pathway offers a novel therapeutic strategy for cancer patients.
Area of Science:
- Oncology
- Genetics
- Molecular Biology
Background:
- Cancer susceptibility loci, specifically single nucleotide polymorphisms (SNPs), offer potential for precision oncology but their interactions with somatic mutations are poorly understood.
- The p53 tumor suppressor pathway is crucial in tumorigenesis, yet the cooperative effects of germline and somatic variations on its activity remain unclear.
- Understanding these interactions is vital for developing targeted cancer therapies.
Purpose of the Study:
- To investigate the hypothesis that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and therapeutic response.
- To identify novel therapeutic targets by analyzing the interplay between germline SNPs and somatic driver mutations.
Main Methods:
- Integration of germline cancer susceptibility datasets with tumor data containing somatically acquired genetic variations.
- Focus on a specific cancer risk SNP (rs78378222) known to influence p53 activity.
- Analysis of p53 target gene expression (KITLG) and its modulation by pharmacologic inhibition of the c-KIT signal.
Main Results:
- Evidence supporting the hypothesis that germline variants and somatic TP53 status cooperate to affect cancer.
- Identification of a cluster of cancer risk SNPs leading to increased KITLG expression and reduced p53-mediated responses to genotoxic therapies.
- Demonstration that pharmacologic inhibition of the c-KIT signal can reverse these effects.
Conclusions:
- Cancer susceptibility SNPs can interact with cancer driver genes, like TP53, to influence cancer progression.
- The KITLG/c-KIT signaling pathway represents a novel therapeutic target for combinatorial therapies.
- These findings pave the way for more personalized and effective cancer treatment strategies.
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