Evidence mapPaperPMID 40884685Full record

ReviewMolecular diagnosis & therapy2025

Evolutionary Overview and Future Perspectives: ESR1 Mutations, Liquid Biopsy, and Artificial Intelligence for a New Era of Personalized Medicine in ER+ Breast Cancer.

Serafina Martella, Giacomo Cusumano, Thilini Hemali Senevirathne, Dimitrios Stylianakis, Enrico Palmas, Nerina Denaro, Chiara Tommasi, Mario Scartozzi, Lorenzo Gerratana, Cinzia Solinas

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular diagnosis & therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Exploration of targeted anti-tumor therapy · 2026
    Review
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.

Serafina Martella *Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy. seramartella@gmail.com.
Giacomo Cusumano *Thoracic Surgery Unit, Policlinico-San Marco Hospital, University of Catania, 95124, Catania, Italy.
Thilini Hemali SenevirathneFaculty of Science, Katholieke Universiteit Leuven, Kasteelpark Arenberg, Leuven, Belgium.
Dimitrios StylianakisUniversity Hospital and University of Crete, School of Medicine, 70013, Iraklion, Greece.
Enrico PalmasMedical Oncology, AOU Cagliari, Policlinico Duilio Casula, Monserrato, CA, Italy.
Nerina DenaroMedical Oncology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
Chiara TommasiMedical Oncology and Breast Unit, University Hospital of Parma, 43126, Parma, Italy.
Mario ScartozziMedical Oncology, AOU Cagliari, Monserrato, Italy.
Lorenzo GerratanaDepartment of Medical Oncology, CRO Aviano, National Cancer Institute, IRCCS, Aviano, Italy.
Cinzia SolinasMedical Oncology, AOU Cagliari, Policlinico Duilio Casula, Monserrato, CA, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ESR1 gene mutations represent one of the main mechanisms of acquired resistance to endocrine therapy (ET) in estrogen receptor-positive (ER+) breast cancer. The introduction of liquid biopsy as a minimally invasive technique for analyzing circulating tumor DNA (ctDNA) has opened new avenues for real-time mutation monitoring and personalized treatment strategies. This review explores the clinical relevance of ESR1 mutations in endocrine resistance, the potential of liquid biopsy for early detection and monitoring, and the integration of advanced sequencing technologies and artificial intelligence to improve diagnostic accuracy. Preclinical and clinical studies on key mutations (D538G, Y537S) were analyzed, emerging technologies [(next-generation sequencing (NGS), digital droplet PCR (ddPCR), Cancer Personalized Profiling by deep Sequencing (CAPP-Seq), Targeted Digital Sequencing (TARDIS)] were compared, and survival data from seven major studies were summarized to assess the impact of ESR1 mutations on progression-free survival (PFS) and overall survival (OS). The results show that these mutations, particularly those affecting the ligand-binding domain, are associated with reduced efficacy of aromatase inhibitors and increased tumor aggressiveness. Liquid biopsy proves useful for early detection of resistance mutations and dynamic disease monitoring, but its clinical implementation is limited by low ctDNA levels, technological variability, and the lack of standardized clinical cut-offs. Integration with tissue biopsy, radiomics, and artificial intelligence (AI)-based platforms enhances its clinical utility and prognostic value. In conclusion, liquid biopsy, when combined with advanced technologies and predictive tools, represents an innovative resource for the personalized management of ER+ breast cancer, with the potential to guide timely therapeutic interventions and improve long-term survival.

Indexed as

Artificial IntelligenceBreast NeoplasmsEstrogen Receptor alphaMutationPrecision MedicineBiomarkers, TumorCirculating Tumor DNADrug Resistance, NeoplasmFemaleHigh-Throughput Nucleotide SequencingHumansLiquid BiopsyBiomarkers, TumorCirculating Tumor DNAESR1 protein, humanEstrogen Receptor alpha

Identifiers

PMID40884685

What Socratic holds

Textmetadata
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.