TP53Variations in Human Cancers: New Lessons from the IARC TP53 Database and Genomics Data

Abstract

TP53 gene mutations are one of the most frequent somatic events in cancer. The IARC TP53 Database (http://p53.iarc.fr) is a popular resource that compiles occurrence and phenotype data on TP53 germline and somatic variations linked to human cancer. The deluge of data coming from cancer genomic studies generates new data on TP53 variations and attracts a growing number of database users for the interpretation of TP53 variants. Here, we present the current contents and functionalities of the IARC TP53 Database and perform a systematic analysis of TP53 somatic mutation data extracted from this database and from genomic data repositories. This analysis showed that IARC has more TP53 somatic mutation data than genomic repositories (29,000 vs. 4,000). However, the more complete screening achieved by genomic studies highlighted some overlooked facts about TP53 mutations, such as the presence of a significant number of mutations occurring outside the DNA-binding domain in specific cancer types. We also provide an update on TP53 inherited variants including the ones that should be considered as neutral frequent variations. We thus provide an update of current knowledge on TP53 variations in human cancer as well as inform users on the efficient use of the IARC TP53 Database.

Multidimensional phenotyping of breast cancer cell lines to guide preclinical research

“…Missense mutations can disrupt feedback signaling and/or stabilize the protein, resulting in accumulation within the nucleus (so-called ''over-expression''). An optimized IHC method has recently been developed that shows p53 over-expression in serous ovarian cancer is an accurate predictor of mutation status [31], though the use of IHC as a TP53 mutation surrogate is currently not supported by the WHO/IARC [16,17].…”

“…We therefore sequenced exons 4-10 of TP53 (encodes the DNA-binding domain and contains 99% of human mutations [16,17]) in our cell line cohort, and identified mutations in 18/32 lines (56%; Table-S1). Using nanostring and dIHC data, we then analysed the relationships between TP53 mutation status, RNA and protein expression to see if expression might be a useful surrogate for loss-of-function, and whether this is impacted by protein heterogeneity.…”

“…Targeted mutation analysis of PIK3CA, HRAS, KRAS and BRAF was performed using the Oncocarta Assay (v1.0; Sequenom [15] [16,17]). Comparing our findings to cell line mutation data repositories [18,19] revealed several differences: four instances where we could only detect the wild-type allele but a mutation had been reported previously, possibly indicating LOH at these loci (BT474 (PIK3CA, EGFR), MDAMB231 (BRAF), MDAMB436 (BRAF) and ZR751 (HRAS); MDAMB436, where a BRAF deletion was found by the CCLE but not COSMIC or our study; and two with discordant findings between the CCLE and COSMIC (BRAF mutations in MDAMB361 and MDAMB415).…”

Dysfunctional diversity of p53 proteins in adult acute myeloid leukemia: projections on diagnostic workup and therapy

“…32 AML-related TP53 mutations are mostly missense somatic mutations that embrace some of the most frequent cancer-associated TP53 hotspots, such as the contact mutations at codons 248, 273, and the structural mutation at codon 245. 33 Next-generation sequencing (NGS) studies indicate that mutp53-AML cells display mostly heterozygous mutations. 34 However, the heterozygous status is often unstable, as TP53 mutations are frequently followed by loss of heterozygosity (LOH) during cancer progression.…”

Genetic Analysis of P53 Gene Using Unweighted Pair Group Method With Arithmetic Mean and Neighbor Joining Methods.

“…Since then, p53 has been one of the most intensively studied proteins worldwide, it is mainly due to the evidence that most of human malignancies bear the abovementioned alterations in its signaling pathway. Indeed, genetic mutations inactivating normal p53 functions can be found in various human tumors, with percentages that vary from nearly 50% in ovary cancer to 5.8% in cervical tumors (Bouaoun et al, 2016).…”