Evidence map›Paper›PMID 27997533›Full record

ArticlePLoS medicine2016

Exploratory Analysis of TP53 Mutations in Circulating Tumour DNA as Biomarkers of Treatment Response for Patients with Relapsed High-Grade Serous Ovarian Carcinoma: A Retrospective Study.

Christine A Parkinson, Davina Gale, Anna M Piskorz, Heather Biggs, Charlotte Hodgkin, Helen Addley, Sue Freeman, Penelope Moyle, Evis Sala, Karen Sayal and 7 more

Open access · goldAbstract read
In one paragraph

Article in PLoS medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 168 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
168citing papers in PubMed, 2 pooled it
11.0field-weighted citation impact, top 1% of its field
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

168 citing papers in PubMed, 2 syntheses or guidelines pooled it, 295 citations in OpenAlex.

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108 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

17 authors at 2 institutions in 1 country.

Christine A ParkinsonCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.
Davina GaleCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.
Anna M PiskorzCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.
Heather BiggsDepartment of Oncology, Hutchison/MRC Research Centre, University of Cambridge, Cambridge, United Kingdom.
Charlotte HodgkinDepartment of Oncology, Hutchison/MRC Research Centre, University of Cambridge, Cambridge, United Kingdom.ORCID http://orcid.org/0000-0002-2240-1740
Helen AddleyCambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom.
Sue FreemanCambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom.
Penelope MoyleCambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom.
Evis SalaCambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom.
Karen SayalCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.
Karen HoskingDepartment of Oncology, Hutchison/MRC Research Centre, University of Cambridge, Cambridge, United Kingdom.
Ioannis GounarisCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.
Mercedes Jimenez-LinanCambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom.ORCID http://orcid.org/0000-0002-8164-5462
Helena M EarlDepartment of Oncology, Hutchison/MRC Research Centre, University of Cambridge, Cambridge, United Kingdom.
Wendi QianCambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom.ORCID http://orcid.org/0000-0002-4238-3471
Nitzan RosenfeldCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.
James D BrentonCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.
University of Cambridge · GBCambridge University Hospitals NHS Foundation Trust · GB

Funding

Cancer Research UK 15601Cancer Research UK 20240Cancer Research UK 22905Cancer Research UK A15601Cancer Research UK A18072Cancer Research UK A20240Wellcome Trust
6 · The paper itself

Abstract

backgroundCirculating tumour DNA (ctDNA) carrying tumour-specific sequence alterations may provide a minimally invasive means to dynamically assess tumour burden and response to treatment in cancer patients. Somatic TP53 mutations are a defining feature of high-grade serous ovarian carcinoma (HGSOC). We tested whether these mutations could be used as personalised markers to monitor tumour burden and early changes as a predictor of response and time to progression (TTP). METHODS AND

findingsWe performed a retrospective analysis of serial plasma samples collected during routine clinical visits from 40 patients with HGSOC undergoing heterogeneous standard of care treatment. Patient-specific TP53 assays were developed for 31 unique mutations identified in formalin-fixed paraffin-embedded tumour DNA from these patients. These assays were used to quantify ctDNA in 318 plasma samples using microfluidic digital PCR. The TP53 mutant allele fraction (TP53MAF) was compared to serum CA-125, the current gold-standard response marker for HGSOC in blood, as well as to disease volume on computed tomography scans by volumetric analysis. Changes after one cycle of treatment were compared with TTP. The median TP53MAF prior to treatment in 51 relapsed treatment courses was 8% (interquartile range [IQR] 1.2%-22%) compared to 0.7% (IQR 0.3%-2.0%) for seven untreated newly diagnosed stage IIIC/IV patients. TP53MAF correlated with volumetric measurements (Pearson r = 0.59, p < 0.001), and this correlation improved when patients with ascites were excluded (r = 0.82). The ratio of TP53MAF to volume of disease was higher in relapsed patients (0.04% per cm3) than in untreated patients (0.0008% per cm3, p = 0.004). In nearly all relapsed patients with disease volume > 32 cm3, ctDNA was detected at ≥20 amplifiable copies per millilitre of plasma. In 49 treatment courses for relapsed disease, pre-treatment TP53MAF concentration, but not CA-125, was associated with TTP. Response to chemotherapy was seen earlier with ctDNA, with a median time to nadir of 37 d (IQR 28-54) compared with a median time to nadir of 84 d (IQR 42-116) for CA-125. In 32 relapsed treatment courses evaluable for response after one cycle of chemotherapy, a decrease in TP53MAF of >60% was an independent predictor of TTP in multivariable analysis (hazard ratio 0.22, 95% CI 0.07-0.67, p = 0.008). Conversely, a decrease in TP53MAF of ≤60% was associated with poor response and identified cases with TTP < 6 mo with 71% sensitivity (95% CI 42%-92%) and 88% specificity (95% CI 64%-99%). Specificity was improved when patients with recent drainage of ascites were excluded. Ascites drainage led to a reduction of TP53MAF concentration. The limitations of this study include retrospective design, small sample size, and heterogeneity of treatment within the cohort.

conclusionsIn this retrospective study, we demonstrated that ctDNA is correlated with volume of disease at the start of treatment in women with HGSOC and that a decrease of ≤60% in TP53MAF after one cycle of chemotherapy was associated with shorter TTP. These results provide evidence that ctDNA has the potential to be a highly specific early molecular response marker in HGSOC and warrants further investigation in larger cohorts receiving uniform treatment.

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorCarcinomaDNA, NeoplasmFemaleHumansMiddle AgedMutationNeoplastic Cells, CirculatingOvarian NeoplasmsRetrospective StudiesTumor Suppressor Protein p53Biomarkers, TumorDNA, NeoplasmTP53 protein, humanTumor Suppressor Protein p53

Identifiers

PMID27997533
PMCPMC5172526
OpenAlexW2561358247

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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.