Evidence map›Paper›PMID 32028173›Full record

ArticleBreast (Edinburgh, Scotland)2020

Targeted next-generation sequencing identifies genomic abnormalities potentially driving the prognosis of early-stage invasive lobular breast carcinoma patients stratified according to a validated clinico-pathological model.

Luisa Carbognin, Michele Simbolo, Anna Caliò, Caterina Vicentini, Pietro Delfino, Isabella Sperduti, Matteo Fassan, Francesco Schettini, Maria Vittoria Dieci, Gaia Griguolo and 12 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Breast (Edinburgh, Scotland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 48% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
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

22 authors at 6 institutions in 1 country.

Luisa CarbogninUniversity of Verona, Verona, Italy; Division of Gynecologic Oncology, Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italy.
Michele SimboloDepartment of Diagnostics and Public Health, University of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Anna CaliòDepartment of Diagnostics and Public Health, University of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Caterina VicentiniARC-Net Research Centre and Department of Pathology, University of Verona, Verona, Italy.
Pietro DelfinoDepartment of Diagnostics and Public Health, University of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Isabella SperdutiBiostatistics, 'Regina Elena' National Cancer Institute, Roma, Italy.
Matteo FassanDepartment of Medicine (DIMED), Surgical Pathology Unit, University of Padova, Padova, Italy.
Francesco SchettiniMedical Oncology, Federico II University, Napoli, Italy.
Maria Vittoria DieciDivision of Medical Oncology 2, Istituto Oncologico Veneto, IRCCS, Padova, Italy; Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy.
Gaia GriguoloDivision of Medical Oncology 2, Istituto Oncologico Veneto, IRCCS, Padova, Italy; Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy.
Sara PilottoUniversity of Verona, Verona, Italy; U.O.C. Medical Oncology, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Elena FiorioU.O.C. Medical Oncology, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Grazia ArpinoMedical Oncology, Federico II University, Napoli, Italy.
Valentina GuarneriDivision of Medical Oncology 2, Istituto Oncologico Veneto, IRCCS, Padova, Italy; Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy.
Sabino De PlacidoMedical Oncology, Federico II University, Napoli, Italy.
Pierfranco ConteDivision of Medical Oncology 2, Istituto Oncologico Veneto, IRCCS, Padova, Italy; Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy.
Erminia ManfrinDepartment of Diagnostics and Public Health, University of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Matteo BrunelliDepartment of Diagnostics and Public Health, University of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy.
Giovanni ScambiaDivision of Gynecologic Oncology, Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, Roma, Italy.
Aldo ScarpaDepartment of Diagnostics and Public Health, University of Verona, Azienda Ospedaliera Universitaria Integrata, Verona, Italy; ARC-Net Research Centre and Department of Pathology, University of Verona, Verona, Italy.
Giampaolo TortoraOncologia Medica, Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica Del Sacro Cuore, Roma, Italy.
Emilio BriaOncologia Medica, Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica Del Sacro Cuore, Roma, Italy. Electronic address: emilio.bria@unicatt.it.
University of Verona · ITUniversity of Padua · ITFederico II University Hospital · ITUniversità Cattolica del Sacro Cuore · ITAgostino Gemelli University Polyclinic · ITAzienda Ospedaliera Universitaria Integrata Verona · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe clinico-pathological and molecular factors that drive the prognosis of invasive lobular breast carcinoma (ILC) are not entirely explored. In this regard, the development and validation of a prognostic model for ILC and the investigation of the distribution of molecular abnormalities (focusing on CDK4/6 alterations) according to prognosis were the aims of this study. PATIENTS AND

methodsTwo clinico-pathological multi-center data-sets of early-stage ILC patients (Training/Validation Set, TS/VS) were gathered. A 3-class model was developed according to the multivariate analysis for disease-free-survival (DFS) and externally validated. Mutational, copy number variation and transcriptomic analyses by targeted next generation sequencing (NGS) were performed (and validated with quantitative PCR) in an explorative cohort of patients with poor and good prognosis.

resultsData from overall 773 patients (TS/VS: 491/282) were gathered. The developed model significantly discriminated low/intermediate/high risk in the TS (10-years DFS: 76.3%/67.6%/39.8%, respectively, p<0.0001) and in the VS (p<0.0001). In the explorative cohort for molecular analysis (34 patients), CDK4 gain was present exclusively in the poor prognosis group (35.0%, p = 0.03; OR 7.98, 95%CI 1.51-42.1, p = 0.014). Moreover, CDK4 and 6 overexpression showed a trend toward an association with poor prognosis (OR 2.7, 95%CI 0.4-18.1, p = 0.3; OR 3.29, 95%CI 0.56-19.25, p = 0.18).

conclusionsA risk stratification model, able to accurately separate early-stage ILC patients' prognosis into different risk classes according to clinico-pathological variables, allowed to investigate potential biomarkers of prognosis with targeted NGS. CDK4 gain is suggested for future validation as a prognostic biomarker and a potential therapeutic opportunity in ILC patients.

Indexed as

High-Throughput Nucleotide SequencingSequence Analysis, DNABiomarkers, TumorBreast NeoplasmsCarcinoma, LobularCyclin-Dependent Kinase 4Cyclin-Dependent Kinase 6DNA Copy Number VariationsFemaleGene Expression ProfilingHumansMiddle AgedMultivariate AnalysisPrognosisRetrospective StudiesRiskBiomarkers, TumorCDK4 protein, humanCDK6 protein, humanCyclin-Dependent Kinase 4Cyclin-Dependent Kinase 6Breast cancerCDK4LobularNext-generation sequencingPrognosisTranscriptome analysis

Identifiers

PMID32028173
PMCPMC7375560
OpenAlexW3003346347

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.