TP53 alterations of hormone-naïve prostate cancer in the Chinese population

Abstract

Background: Prostate cancer (PCa) shows racial disparity in clinical and genomic characteristics, and Asian patients with PCa often present with more aggressive phenotypes at diagnosis. The ability of TP53 to serve as a prognostic biomarker of PCa has been well studied in Western populations. However, no studies to date have examined the role of TP53 in the disparities of primary hormone-naïve prostate cancer (HNPC) between Chinese and Western populations.

Methods: We collected prostate tumors and matched normal tissues or blood samples to perform targeted next-generation sequencing of 94 Chinese primary localized HNPC samples, and correlated these genomic profiles with clinical outcomes. The OncoKB knowledge database was used to identify and classify actionable alterations.

Results: The aberrations of PTEN, CDK12, and SPOP in Chinese HNPC samples were similar to those in the Western samples. However, we demonstrated an association of a high frequency of TP53 alterations (21/94) with a relatively higher percentage of alterations in the Wnt signaling pathway (15/94) in Chinese HNPC. Additionally, we highlighted alterations of LRP1B as accounting for a high proportion of PCa and found more frequent alterations in CDH1 in Chinese PCa. Of these, only CDH1 alteration was associated with rapid biochemical recurrence (BCR). However, we verified that TP53 status was at the core of the genomic alteration landscape in Chinese HNPC with putative driver mutations because of the strong connections with other signaling pathways. The mutually exclusive relationship between alterations in TP53 and Wnt/CTNNB1 further molecularly characterizes subsets of prostate cancers. Moreover, the alteration of KMT2C was more likely to co-occur with TP53 alteration, indicating a more aggressive phenotype of PCa, which was associated with sensitivity to treatment with poly ADT-ribose polymerase (PARP) inhibitors.

Conclusions: Detection of TP53 alterations has clinical utility for guiding precision cancer therapy for HNPC, especially in the Chinese population.

Fig. 1. Significant genomic alterations in PCa.

a Frequency of genomic alterations. All the type of ERG fusions were TMPRSS2-ERG fusions, the other TMPRSS2 fusion occurred between TMPRSS2 and KLF12, PDE9A, MIR99AHG, and SLC5A4. b Mutational signatures of TP53 in prostate cancer. TAD Transactivation domain, DBD DNA-binding domain, OD Oligomerization domain.

Fig. 2. Landscape of genomic alterations in PCa.

a Oncoprint of selected cancer-relative alterations, pathways in PCa, separated by the status of TP53. b Co-occurrence or mutual exclusivity between the most commonly mutated genes.

Fig. 3. Alterations of genes in the cancer-related pathway found in PCa.

a Mutational signatures of APC/CTNNB1. ARM Armadillo/beta-catenin-like repeat. b Mutational signatures of BRCA 1/2 and ATM. HELC helical domain, OB oligosaccharide-binding domain, zf-C3HC4 Zinc finger, C3HC4 type, BRCT_assoc Serine-rich domain associated with BRCT, EIN3 Ethylene insensitive 3 domain, BRCT BRCA1 c-terminus domain, TAN Telomere-length maintenance and DNA damage repair, FAT FRAP-ATM-TRRAP domain, PI3_I4K phosphatidylinositol 3- and 4-kinase, FATC FAT c-terminal domain. c Mutational signatures of SPOP. MATH MATH domain, BTB Broad Complex, Tramtrack and Bric a brac/poxvirus and zinc finger domain. d Mutational signatures of CDH1. Cadherin_pro Caderin prodomain like, Cadherin_C Cadherin cytoplasmic region. e Mutational signatures of LRP1B.

Fig. 4. Landscape of actionable alterations with OncoKB recommendations in PCa.

a The upper pie-plot indicates the frequency of patients with TP53mut PCa (N = 21) or TP53wt PCa (N = 73) who were identified with translational targets in our cohort. The lower pie-plot shows the distribution of OncoKB levels for translational targets in patients with TP53mut or TP53wt PCa. b The flow diagram in the left part shows the list of translational targets for each OncoKB recommendation level in TP53 mutant group, and the right part presents for TP53 wild-type PCa. The colors of the curving belts represent different signaling pathways, and the widths of the belts indicate different frequencies for each target at every level. c The panel shows the comparison of actionable alteration frequencies between TP53mut and TP53wt PCa.