Evidence map›Paper›PMID 36544142›Full record

ArticleJournal of translational medicine2022

A combination of molecular and clinical parameters provides a new strategy for high-grade serous ovarian cancer patient management.

Melissa Bradbury, Eva Borràs, Marta Vilar, Josep Castellví, José Luis Sánchez-Iglesias, Assumpció Pérez-Benavente, Antonio Gil-Moreno, Anna Santamaria, Eduard Sabidó

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

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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

9 authors at 3 institutions in 1 country.

Melissa BradburyCentre de Regulació Genòmica, Barcelona Institute of Science and Technology (BIST), Dr Aiguader 88, 08003, Barcelona, Spain.
Eva BorràsCentre de Regulació Genòmica, Barcelona Institute of Science and Technology (BIST), Dr Aiguader 88, 08003, Barcelona, Spain.
Marta VilarCentre de Regulació Genòmica, Barcelona Institute of Science and Technology (BIST), Dr Aiguader 88, 08003, Barcelona, Spain.
Josep CastellvíDepartment of Pathology, Hospital Universitari Vall d'Hebron, Vall d'Hebron Barcelona Hospital Campus, Passeig Vall d'Hebron 119-129, 08035, Barcelona, Spain.
José Luis Sánchez-IglesiasBiomedical Research Group in Gynecology, Vall d'Hebron Institut de Recerca, Universitat Autònoma de Barcelona, Vall, d'Hebron Barcelona Hospital Campus, Passeig Vall d'Hebron 119-129, 08035, Barcelona, Spain.
Assumpció Pérez-BenaventeBiomedical Research Group in Gynecology, Vall d'Hebron Institut de Recerca, Universitat Autònoma de Barcelona, Vall, d'Hebron Barcelona Hospital Campus, Passeig Vall d'Hebron 119-129, 08035, Barcelona, Spain.
Antonio Gil-MorenoBiomedical Research Group in Gynecology, Vall d'Hebron Institut de Recerca, Universitat Autònoma de Barcelona, Vall, d'Hebron Barcelona Hospital Campus, Passeig Vall d'Hebron 119-129, 08035, Barcelona, Spain.
Anna Santamaria *Biomedical Research Group in Gynecology, Vall d'Hebron Institut de Recerca, Universitat Autònoma de Barcelona, Vall, d'Hebron Barcelona Hospital Campus, Passeig Vall d'Hebron 119-129, 08035, Barcelona, Spain. anna.santamaria@vhir.org.
Eduard Sabidó *Centre de Regulació Genòmica, Barcelona Institute of Science and Technology (BIST), Dr Aiguader 88, 08003, Barcelona, Spain. eduard.sabido@crg.cat.ORCID 0000-0001-6506-7714
Universitat Autònoma de Barcelona · ESUniversitat Pompeu Fabra · ESVall d'Hebron Hospital Universitari · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh-grade serous carcinoma (HGSC) is the most common and deadly subtype of ovarian cancer. Although most patients will initially respond to first-line treatment with a combination of surgery and platinum-based chemotherapy, up to a quarter will be resistant to treatment. We aimed to identify a new strategy to improve HGSC patient management at the time of cancer diagnosis (HGSC-1LTR).

methodsA total of 109 ready-available formalin-fixed paraffin-embedded HGSC tissues obtained at the time of HGSC diagnosis were selected for proteomic analysis. Clinical data, treatment approach and outcomes were collected for all patients. An initial discovery cohort (n = 21) were divided into chemoresistant and chemosensitive groups and evaluated using discovery mass-spectrometry (MS)-based proteomics. Proteins showing differential abundance between groups were verified in a verification cohort (n = 88) using targeted MS-based proteomics. A logistic regression model was used to select those proteins able to correctly classify patients into chemoresistant and chemosensitive. The classification performance of the protein and clinical data combinations were assessed through the generation of receiver operating characteristic (ROC) curves.

resultsUsing the HGSC-1LTR strategy we have identified a molecular signature (TKT, LAMC1 and FUCO) that combined with ready available clinical data (patients' age, menopausal status, serum CA125 levels, and treatment approach) is able to predict patient response to first-line treatment with an AUC: 0.82 (95% CI 0.72-0.92).

conclusionsWe have established a new strategy that combines molecular and clinical parameters to predict the response to first-line treatment in HGSC patients (HGSC-1LTR). This strategy can allow the identification of chemoresistance at the time of diagnosis providing the optimization of therapeutic decision making and the evaluation of alternative treatment strategies. Thus, advancing towards the improvement of patient outcome and the individualization of HGSC patients' care.

Indexed as

Cystadenocarcinoma, SerousOvarian NeoplasmsBiomarkers, TumorFemaleHumansProteinsProteomicsBiomarkers, TumorProteinsBiomarkerHigh-grade serous ovarian cancerPredictionProteomicsTreatment

Identifiers

PMID36544142
PMCPMC9773449
OpenAlexW4312129939

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.