Evidence map›Paper›PMID 30167082›Full record

ArticleOncotarget2018

Genomic alterations at the basis of treatment resistance in metastatic breast cancer: clinical applications.

Angela Toss, Federico Piacentini, Laura Cortesi, Lucia Artuso, Isabella Bernardis, Sandra Parenti, Elena Tenedini, Guido Ficarra, Antonino Maiorana, Anna Iannone and 5 more

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.4field-weighted citation impact, top 44% 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

13 citing papers in PubMed, 16 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

15 authors at 3 institutions in 2 countries.

Angela TossDepartment of Oncology and Haematology, Azienda Ospedaliero-Universitaria Policlinico di Modena, Modena, Italy.
Federico PiacentiniDepartment of Oncology and Haematology, Azienda Ospedaliero-Universitaria Policlinico di Modena, Modena, Italy.
Laura CortesiDepartment of Oncology and Haematology, Azienda Ospedaliero-Universitaria Policlinico di Modena, Modena, Italy.
Lucia ArtusoCenter for Genome Research, University of Modena and Reggio Emilia, Modena, Italy.
Isabella BernardisCenter for Genome Research, University of Modena and Reggio Emilia, Modena, Italy.
Sandra ParentiCenter for Genome Research, University of Modena and Reggio Emilia, Modena, Italy.
Elena TenediniCenter for Genome Research, University of Modena and Reggio Emilia, Modena, Italy.
Guido FicarraDepartment of Pathology, Azienda Ospedaliero-Universitaria Policlinico di Modena, Modena, Italy.
Antonino MaioranaDepartment of Pathology, Azienda Ospedaliero-Universitaria Policlinico di Modena, Modena, Italy.
Anna IannoneDepartment of Diagnostics, Clinical and Public Health Medicine, University of Modena and Reggio Emilia, Modena, Italy.
Claudia OmariniDepartment of Oncology and Haematology, Azienda Ospedaliero-Universitaria Policlinico di Modena, Modena, Italy.
Luca MoscettiDepartment of Oncology and Haematology, Azienda Ospedaliero-Universitaria Policlinico di Modena, Modena, Italy.
Massimo CristofanilliDepartment of Medicine-Hematology and Oncology, Robert H Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Massimo Federico *Center for Genome Research, University of Modena and Reggio Emilia, Modena, Italy.
Enrico Tagliafico *Department of Diagnostics, Clinical and Public Health Medicine, University of Modena and Reggio Emilia, Modena, Italy.
Policlinico di Modena · ITUniversity of Modena and Reggio Emilia · ITNorthwestern University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The standard of care for breast cancer has gradually evolved from empirical treatments based on clinical-pathological characteristics to the use of targeted approaches based on the molecular profile of the tumor. Consequently, an increasing number of molecularly targeted drugs have been developed. These drugs target specific alterations, called driver mutations, which confer a survival advantage to cancer cells. To date, the main challenge remains the identification of predictive biomarkers for the selection of the optimal treatment. On this basis, we evaluated a panel of 25 genes involved in the mechanisms of targeted treatment resistance, in 16 primary breast cancers and their matched recurrences, developed during treatment. Overall, we found a detection rate of mutations higher than that described in the literature. In particular, the most frequently mutated genes were ERBB2 and those involved in the PI3K/AKT/mTOR and the MAPK signaling pathways. The study revealed substantial discordances between primary tumors and metastases, stressing the need for analysis of metastatic tissues at recurrence. We observed that 85.7% of patients with an early-stage or locally advanced primary tumor showed at least one mutation in the primary tumor. This finding could explain the subsequent relapse and might therefore justify more targeted adjuvant treatments. Finally, the mutations detected in 50% of relapsed tissues could have guided subsequent treatment choices in a different way. This study demonstrates that mutation events may be present at diagnosis or arise during cancer treatment. As a result, profiling primary and metastatic tumor tissues may be a major step in defining optimal treatments.

Indexed as

breast cancermolecular characterizationnext-generation sequencingsomatic mutationstreatment resistance

Identifiers

PMID30167082
PMCPMC6114971
OpenAlexW2885700779

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.