Dataset Information

Computational analysis of TP53 mutational landscape unveils key prognostic signatures and distinct pathobiological pathways in head and neck squamous cell cancer.

ABSTRACT:

Background

Mutations of the tumour-suppressor gene TP53 are the most frequent somatic genomic alterations in head and neck squamous cell carcinoma (HNSCC). However, it is not yet clear whether specific TP53 mutations bear distinct clinical and pathophysiological significance in different HNSCC subgroups.

Methods

A systematic bioinformatics appraisal of TP53 mutations was performed on 415 HNSCC cases available on The Cancer Genome Atlas (TCGA). The following features were analysed and correlated with known clinicopathological variables: mutational profile of TP53, location (within secondary structure and predicted domains of p53 protein) and well-known hotspot mutations. Interactome-genome-transcriptome network analysis highlighted different gene networks. An algorithm was generated to develop a new prognostic classification system based on patients' overall survival.

Results

TP53 mutations in HNSCCs exhibited distinct differences in different anatomical sites. The mutational profile of TP53 was an independent prognostic factor in HNSCC. High risk of death mutations, identified by our novel classification algorithm, was an independent prognostic factor in TCGA HNSCC database. Finally, network analysis suggested that distinct p53 molecular pathways exist in a site- and mutation-specific manner.

Conclusions

The mutational profile of TP53 may serve as an independent prognostic factor in HNSCC patients, and is associated with distinctive site-specific biological networks.

SUBMITTER: Caponio VCA

PROVIDER: S-EPMC7553957 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:For TP53-mutated head and neck squamous cell carcinomas (HNSCCs), the codon and specific amino acid sequence change resulting from a patient's mutation can be prognostic. Thus, developing a framework to predict patient survival for specific mutations in TP53 would be valuable. There are many bioinformatics and functional methods for predicting the phenotypic impact of genetic variation, but their overall clinical value remains unclear. Here, we assess the ability of 15 different methods to predict HNSCC patient survival from TP53 mutation, using TP53 mutation and clinical data from patients enrolled in E4393 by the Eastern Cooperative Oncology Group (ECOG), which investigated whether TP53 mutations in surgical margins were predictive of disease recurrence. These methods include: server-based computational tools SIFT, PolyPhen-2, and Align-GVGD; our in-house POSE and VEST algorithms; the rules devised in Poeta et al. with and without considerations for splice-site mutations; location of mutation in the DNA-bound TP53 protein structure; and a functional assay measuring WAF1 transactivation in TP53-mutated yeast. We assessed method performance using overall survival (OS) and progression-free survival (PFS) from 420 HNSCC patients, of whom 224 had TP53 mutations. Each mutation was categorized as "disruptive" or "non-disruptive". For each method, we compared the outcome between the disruptive group vs. the non-disruptive group. The rules devised by Poeta et al. with or without our splice-site modification were observed to be superior to others. While the differences in OS (disruptive vs. non-disruptive) appear to be marginally significant (Poeta rules + splice rules, P = 0.089; Poeta rules, P = 0.053), both algorithms identified the disruptive group as having significantly worse PFS outcome (Poeta rules + splice rules, P = 0.011; Poeta rules, P = 0.027). In general, prognostic performance was low among assessed methods. Further studies are required to develop and validate methods that can predict functional and clinical significance of TP53 mutations in HNSCC patients.

Project description:BackgroundRecurrence and/or metastasis occurs in more than half of patients with head and neck squamous cell carcinoma (HNSCC), and these events pose the greatest threats to long-term survival. We set out to identify genetic alterations that underlie recurrent/metastatic HNSCC.MethodsWhole-exome sequencing (WES) was performed on genomic DNA extracted from fresh-frozen whole blood and patient-matched tumor pairs from 13 HNSCC patients with synchronous lymph node metastases and 10 patients with metachronous recurrent tumors. Mutational concordance within and between tumor pairs was used to analyze the spatiotemporal evolution of HNSCC in individual patients and to identify potential therapeutic targets for functional evaluation.ResultsApproximately 86% and 60% of single somatic nucleotide variants (SSNVs) identified in synchronous nodal metastases and metachronous recurrent tumors, respectively, were transmitted from the primary index tumor. Genes that were mutated in more than one metastatic or recurrent tumor, but not in the respective primary tumors, include C17orf104, inositol 1,4,5-trisphosphate receptor, type 3 (ITPR3), and discoidin domain receptor tyrosine kinase 2 (DDR2). Select DDR2 mutations have been shown to confer enhanced sensitivity to SRC-family kinase (SFK) inhibitors in other malignancies. Similarly, HNSCC cell lines harboring endogenous and engineered DDR2 mutations were more sensitive to the SFK inhibitor dasatinib than those with WT DDR2.ConclusionIn this WES study of patient-matched tumor pairs in HNSCC, we found synchronous lymph node metastases to be genetically more similar to their paired index primary tumors than metachronous recurrent tumors. This study outlines a compendium of somatic mutations in primary, metastatic, and/or recurrent HNSCC cancers, with potential implications for precision medicine approaches.FundingNational Cancer Institute, American Cancer Society, Agency for Science, Technology and Research of Singapore, and Gilead Sciences Inc.