Teng‐Kuei Hsu

The TP53 tumor suppressor gene is frequently mutated in human cancers. An analysis of five data platforms in 10,225 patient samples from 32 cancers reported by The Cancer Genome Atlas (TCGA) enables comprehensive assessment of p53 pathway involvement in these cancers. More than 91% of TP53-mutant cancers exhibit second allele loss by mutation, chromosomal deletion, or copy-neutral loss of heterozygosity. TP53 mutations are associated with enhanced chromosomal instability, including increased amplification of oncogenes and deep deletion of tumor suppressor genes. Tumors with TP53 mutations differ from their non-mutated counterparts in RNA, miRNA, and protein expression patterns, with mutant TP53 tumors displaying enhanced expression of cell cycle progression genes and proteins. A mutant TP53 RNA expression signature shows significant correlation with reduced survival in 11 cancer types. Thus, TP53 mutation has profound effects on tumor cell genomic structure, expression, and clinical outlook.

Abstract TP53 is the most frequently altered gene in head and neck squamous cell carcinoma, with mutations occurring in over two-thirds of cases, but the prognostic significance of these mutations remains elusive. In the current study, we evaluated a novel computational approach termed evolutionary action (EAp53) to stratify patients with tumors harboring TP53 mutations as high or low risk, and validated this system in both in vivo and in vitro models. Patients with high-risk TP53 mutations had the poorest survival outcomes and the shortest time to the development of distant metastases. Tumor cells expressing high-risk TP53 mutations were more invasive and tumorigenic and they exhibited a higher incidence of lung metastases. We also documented an association between the presence of high-risk mutations and decreased expression of TP53 target genes, highlighting key cellular pathways that are likely to be dysregulated by this subset of p53 mutations that confer particularly aggressive tumor behavior. Overall, our work validated EAp53 as a novel computational tool that may be useful in clinical prognosis of tumors harboring p53 mutations. Cancer Res; 75(7); 1527–36. ©2015 AACR.

(Cell Reports 28, 1370–1384.e1–e5; July 30, 2019) In the originally published version of this article, The Cancer Genome Atlas (TCGA) Network was listed as an author because all of the analyses were based on TCGA data. However, because this paper was not officially authorized by the TCGA Network, we have now removed The Cancer Genome Atlas Network as an author. The authors regret this error. Integrated Analysis of TP53 Gene and Pathway Alterations in The Cancer Genome AtlasDonehower et al.Cell ReportsJuly 30, 2019In BriefDonehower et al. performed a comprehensive analysis of the effects of TP53 gene mutation in 32 cancer types and 10,225 patients from The Cancer Genome Atlas (TCGA). Data synthesized from five different analysis platforms show how mutant TP53 increases genomic instability and induces major pathway signaling changes in cancer cells. Full-Text PDF Open Access

Genome-wide association studies (GWAS) and whole-exome sequencing (WES) generate massive amounts of genomic variant information, and a major challenge is to identify which variations drive disease or contribute to phenotypic traits. Because the majority of known disease-causing mutations are exonic non-synonymous single nucleotide variations (nsSNVs), most studies focus on whether these nsSNVs affect protein function. Computational studies show that the impact of nsSNVs on protein function reflects sequence homology and structural information and predict the impact through statistical methods, machine learning techniques, or models of protein evolution. Here, we review impact prediction methods and discuss their underlying principles, their advantages and limitations, and how they compare to and complement one another. Finally, we present current applications and future directions for these methods in biological research and medical genetics.

Although cisplatin has played a role in "standard-of-care" multimodality therapy for patients with advanced squamous cell carcinoma of the head and neck (HNSCC), the rate of treatment failure remains particularly high for patients receiving cisplatin whose tumors have mutations in the TP53 gene. We found that cisplatin treatment of HNSCC cells with mutant TP53 leads to arrest of cells in the G2 phase of the cell cycle, leading us to hypothesize that the wee-1 kinase inhibitor MK-1775 would abrogate the cisplatin-induced G2 block and thereby sensitize isogenic HNSCC cells with mutant TP53 or lacking p53 expression to cisplatin. We tested this hypothesis using clonogenic survival assays, flow cytometry, and in vivo tumor growth delay experiments with an orthotopic nude mouse model of oral tongue cancer. We also used a novel TP53 mutation classification scheme to identify which TP53 mutations are associated with limited tumor responses to cisplatin treatment. Clonogenic survival analyses indicate that nanomolar concentration of MK-1775 sensitizes HNSCC cells with high-risk mutant p53 to cisplatin. Consistent with its ability to chemosensitize, MK-1775 abrogated the cisplatin-induced G2 block in p53-defective cells leading to mitotic arrest associated with a senescence-like phenotype. Furthermore, MK-1775 enhanced the efficacy of cisplatin in vivo in tumors harboring TP53 mutations. These results indicate that HNSCC cells expressing high-risk p53 mutations are significantly sensitized to cisplatin therapy by the selective wee-1 kinase inhibitor, supporting the clinical evaluation of MK-1775 in combination with cisplatin for the treatment of patients with TP53 mutant HNSCC.