Evidence map›Paper›PMID 39450552›Full record

ReviewInternational journal of molecular medicine2025

Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review).

Wenhui Hao, Barani Kumar Rajendran, Tingting Cui, Jiayi Sun, Yingchun Zhao, Thirunavukkarasu Palaniyandi, Masilamani Selvam

Abstract readReview
In one paragraph

Review in International journal of molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. 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

7 authors.

Wenhui Hao *Xinjiang Key Laboratory of Molecular Biology for Endemic Diseases, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang 830017, P.R. China.
Barani Kumar Rajendran *Department of Pathology, Yale School of Medicine, Yale University, New Haven, CT 06510, USA.
Tingting CuiXinjiang Key Laboratory of Molecular Biology for Endemic Diseases, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang 830017, P.R. China.
Jiayi SunXinjiang Key Laboratory of Molecular Biology for Endemic Diseases, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang 830017, P.R. China.
Yingchun ZhaoXinjiang Key Laboratory of Molecular Biology for Endemic Diseases, School of Basic Medical Sciences, Xinjiang Medical University, Urumqi, Xinjiang 830017, P.R. China.
Thirunavukkarasu PalaniyandiDepartment of Biotechnology, Dr. M.G.R Educational and Research Institute, Chennai 600095, India.
Masilamani SelvamDepartment of Biotechnology, Sathyabama Institute of Science and Technology, Chennai 600119, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the modern era of medicine, prognosis and treatment, options for a number of cancer types including breast cancer have been improved by the identification of cancer‑specific biomarkers. The availability of high‑throughput sequencing and analysis platforms, the growth of publicly available cancer databases and molecular and histological profiling facilitate the development of new drugs through a precision medicine approach. However, only a fraction of patients with breast cancer with few actionable mutations typically benefit from the precision medicine approach. In the present review, the current development in breast cancer driver gene identification, actionable breast cancer mutations, as well as the available therapeutic options, challenges and applications of breast precision oncology are systematically described. Breast cancer driver mutation‑based precision oncology helps to screen key drivers involved in disease development and progression, drug sensitivity and the genes responsible for drug resistance. Advances in precision oncology will provide more targeted therapeutic options for patients with breast cancer, improving disease‑free survival and potentially leading to significant successes in breast cancer treatment in the near future. Identification of driver mutations has allowed new targeted therapeutic approaches in combination with standard chemo‑ and immunotherapies in breast cancer. Developing new driver mutation identification strategies will help to define new therapeutic targets and improve the overall and disease‑free survival of patients with breast cancer through efficient medicine.

Indexed as

Breast NeoplasmsMutationPrecision MedicineBiomarkers, TumorFemaleHumansMolecular Targeted TherapyBiomarkers, Tumorbreast cancercancer heterogeneitydriver mutationsgenomicsimmunotherapyonco‑predictionpersonalized medicineprecision oncologytargeted therapy

Identifiers

PMID39450552
PMCPMC11537269

What OpenQuestion holds

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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.