Evidence map›Paper›PMID 31780779›Full record

ArticleBritish journal of cancer2020

Clinical relevance of TP53 hotspot mutations in high-grade serous ovarian cancers.

Musaffe Tuna, Zhenlin Ju, Kosuke Yoshihara, Christopher I Amos, Janos L Tanyi, Gordon B Mills

Abstract read
In one paragraph

Article in British journal of cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

62 citing papers in PubMed.

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  15. Germline-Somatic Interactions in BRCA-Associated Cancers: Unique Molecular Profiles and Clinical Outcomes Linking ATM to TP53 Synthetic Essentiality.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
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  20. Review

2 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Musaffe TunaDepartment of Medicine, Baylor College of Medicine, Houston, TX, USA. mtuna9@gmail.com.
Zhenlin JuDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Kosuke YoshiharaDepartment of Obstetrics and Gynecology, Niigata University, Niigata, Japan.
Christopher I AmosDepartment of Medicine, Baylor College of Medicine, Houston, TX, USA.
Janos L TanyiDepartment of Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Gordon B MillsPrecision Oncology, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.

Funding

Precision approaches to refining TP53-associated cancer riskR01CA242218 · NCI · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI AMOS, CHRISTOPHER I., GARBER, JUDY E. · 2019 to 2023
$8.5M
U.T. M. D. Anderson Cancer Center SPORE in Ovarian CancerP50CA217685 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI SOOD, ANIL K · 2017 to 2021
$7.9M
Integrative bioinformatics and functional characterization of oncogenic driver aberrations in cancerU01CA217842 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DENEEN, BENJAMIN, MILLS, GORDON B. · 2017 to 2021
$3.6M
Statistical methods and tools for cancer risk prediction in families with germline mutations in TP53R01CA239342 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI WANG, WENYI · 2019 to 2022
$1.5M
NCI NIH HHS P50 CA217685NCI NIH HHS R01 CA239342NCI NIH HHS R01 CA242218NCI NIH HHS U01 CA217842
6 · The paper itself

Abstract

backgroundMutation of TP53 is the most frequent genetic alteration in high-grade serous ovarian cancer (HGSOC). The impact of hotspot mutations of TP53 and protein levels on patient outcomes in HGSOC has not been fully elucidated.

methodsThe study population (n = 791) comprised of HGSOC samples with TP53 mutation from TCGA and other publicly available data. Univariate and multivariate cox proportional hazards regression analyses were used to select variables that were correlated with patient survival.

resultsWe assessed the effects of TP53 mutations based on type and individual hotspot mutations on patient outcomes in HGSOC. Only hotspot mutations were associated with outcomes. Three hotspot mutations: G266, Y163C, and R282, in aggregate were associated with a worsened overall and recurrence-free survival compared with other hotspot mutations (p < 0.0001 and p = 0.001), other non-hotspot missense mutations (p < 0.0001 and p = 0.008), truncated mutations (p < 0.0001 and p = 0.001), and all other mutations (p < 0.0001 and p = 0.001). Specific hotspot mutations were associated with different protein expression patterns consistent with different functions.

conclusionsThis study provides evidence that individual TP53 hotspot mutations have different impact on HGSOC patient outcomes and potentially TP53 function. Thus the status of particular TP53 aberrations could influence response to therapy and selection of therapeutic agents.

Indexed as

Carcinoma, Ovarian EpithelialDisease-Free SurvivalFemaleGain of Function MutationHumansLoss of Function MutationMiddle AgedMutationNeoplasm GradingNeoplasm StagingOvarian NeoplasmsPrognosisProportional Hazards ModelsSurvival RateTumor Suppressor Protein p53TP53 protein, humanTumor Suppressor Protein p53

Identifiers

PMID31780779
PMCPMC7000721

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.