Evidence map›Paper›PMID 39246849›Full record

ReviewMolecular and clinical oncology2024

Precision medicine in breast cancer (Review).

Petros Papalexis, Vasiliki Epameinondas Georgakopoulou, Panagiotis V Drossos, Eirini Thymara, Aphrodite Nonni, Andreas C Lazaris, George C Zografos, Demetrios A Spandidos, Nikolaos Kavantzas, Georgia Eleni Thomopoulou

Abstract readReview
In one paragraph

Review in Molecular and clinical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Article
  3. The role ofFrontiers in endocrinology · 2026
    Article
  4. Knowledgeable Language Models as Black-Box Optimizers for Personalized Medicine.... International Conference on Learning Representations · 2026
    Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. 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

10 authors.

Petros PapalexisFirst Department of Pathology, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece.
Vasiliki Epameinondas GeorgakopoulouDepartment of Pathophysiology, Laiko General Hospital, National and Kapodistrian University of Athens, 11527 Athens, Greece.
Panagiotis V DrossosDepartment of Biomedical Sciences, University of West Attica, 12243 Athens, Greece.
Eirini ThymaraFirst Department of Pathology, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece.
Aphrodite NonniFirst Department of Pathology, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece.
Andreas C LazarisFirst Department of Pathology, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece.
George C ZografosDepartment of Propedeutic Surgery, Hippokration Hospital, University of Athens Medical School, 11527 Athens, Greece.
Demetrios A SpandidosLaboratory of Clinical Virology, School of Medicine, University of Crete, 71003 Heraklion, Greece.
Nikolaos KavantzasFirst Department of Pathology, School of Medicine, National and Kapodistrian University of Athens, 11527 Athens, Greece.
Georgia Eleni ThomopoulouCytopathology Department, 'Attikon' University General Hospital, School of Medicine, National and Kapodistrian University of Athens, 12461 Athens, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision medicine in breast cancer is a revolutionary approach that customizes diagnosis and treatment based on individual and tumor characteristics, departing from the traditional one-size-fits-all approach. Breast cancer is diverse, with various subtypes driven by distinct genetic mutations. Understanding this diversity is crucial for tailored treatment strategies that target specific vulnerabilities in each tumor. Genetic testing, particularly for mutations in breast cancer gene (BRCA) DNA repair-associated genes, helps assess hereditary risks and influences treatment decisions. Molecular subtyping guides personalized treatments, such as hormonal therapies for receptor-positive tumors and human epidermal growth factor receptor 2 (HER2)-targeted treatments. Targeted therapies, including those for HER2-positive and hormone receptor-positive breast cancers, offer more effective and precise interventions. Immunotherapy, especially checkpoint inhibitors, shows promise, particularly in certain subtypes such as triple-negative breast cancer, with ongoing research aiming to broaden its effectiveness. Integration of big data and artificial intelligence enhances personalized treatment strategies, while liquid biopsies provide real-time insights into tumor dynamics, aiding in treatment monitoring and modification. Challenges persist, including accessibility and tumor complexity, but emerging technologies and precision prevention offer hope for improved outcomes. Ultimately, precision medicine aims to optimize treatment efficacy, minimize adverse effects and enhance the quality of life for patients with breast cancer.

Indexed as

artificial intelligencebreast cancergeneticsimmunotherapyprecision medicine

Identifiers

PMID39246849
PMCPMC11375768

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.