Abstract 3129
Background
The tumor suppressor TP53 is the most frequently mutated gene in solid tumors. Although TP53 decides cell fate and governs initiation of apoptosis, inhibitors targeting mutant TP53 did not yet reached clinical use. Our goal was to identify new potential therapeutic targets in TP53 mutant solid tumors by in silico analysis of multiple large, independent next-generation sequencing and gene chip datasets.
Methods
First, gene expression and mutation data from multiple solid tumors were collected from TCGA and METABRIC databases. Samples were separated based on TP53 mutation status, mutational type and tumor type to identify targetable genes. Differential gene expression was compared using Mann-Whitney test between the mutated (disruptive mutations only) and wild type patient cohorts across all genes. Then, the prognostic value of identified genes was validated in a gene chip-based dataset obtained from the GEO repository. Survival analysis was performed using Cox proportional hazards regression. Significance threshold was set at p < 0.01. Finally, False Discovery Rate was computed to correct for multiple hypothesis testing.
Results
The TCGA dataset include 9,720 patients (21 different cancer types), the Metabric dataset (breast cancer) 1,399 patients, and the GEO dataset (breast, lung, and brain tumors) 7,386 patients. Only genes with higher expression in the TP53 mutant cohort were selected and the list of the top targets was further filtered to include only druggable kinases. The best performing kinases include MPS1 (p = 2.9E-58, FC = 2.82), PLK1 (p = 2.6E-55, FC = 2.55), MELK (p = 5.2E-54, FC = 2.81), and AURKB (p = 2E-53, FC = 3.23). Each of these kinases had a significant prognostic power as well. Of the top 2 (MPS1 and PLK1), both have multiple inhibitors available (for other indications) with PLK1 closest to the clinical use.
Conclusions
Our results suggest that MPS1 (monopolar spindle 1 kinase) and PLK1 (polo like kinase 1) kinases are the strongest druggable targets in TP53 mutant solid tumors.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Semmelweis University.
Funding
National Research, Development and Innovation Office, Hungary.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
1122 - Platelets from metastatic cancer patients have increased aggregation and activation
Presenter: Meera Chauhan
Session: Poster Display session 3
Resources:
Abstract
2671 - Luminal B breast cancer prognosis prediction by comprehensive analysis of Homeobox genes
Presenter: Ayako Nakashoji
Session: Poster Display session 3
Resources:
Abstract
2650 - Long non-coding RNA E2F4as promotes tumor progression and predicts patient prognosis in human ovarian cancer
Presenter: Sun-Ae Park
Session: Poster Display session 3
Resources:
Abstract
1462 - FGF19 promotes esophageal squamous cell carcinoma progression by inhibiting autophagy
Presenter: Lisha Ying
Session: Poster Display session 3
Resources:
Abstract
5787 - Proof of concept on the role of ex vivo lung cancer spheroids, cytokines expression and PBMCs profiling in monitoring disease history and response to treatments.
Presenter: Raimondo Di Liello
Session: Poster Display session 3
Resources:
Abstract
5253 - Circulating microRNAs related to DNA damage response as predictors of survival in metastatic non- small cell lung cancer patients treated with platinum-based chemotherapy
Presenter: Dimitris Mavroudis
Session: Poster Display session 3
Resources:
Abstract
5286 - Prognostic value of CTCs in advanced NSCLC patients treated with platinum-based chemotherapy
Presenter: Silvia Calabuig-Fariñas
Session: Poster Display session 3
Resources:
Abstract
5781 - Exosomes in NSCLC as a source of biomarkers
Presenter: Elena Duréndez
Session: Poster Display session 3
Resources:
Abstract
1447 - The role of Pim-1 in the development and progression of papillary thyroid carcinoma
Presenter: Xin Zhu
Session: Poster Display session 3
Resources:
Abstract
1323 - Development and Validation of a RNA-Seq Based Prognostic Signature in Neuroblastoma
Presenter: Jian-Guo Zhou
Session: Poster Display session 3
Resources:
Abstract