Evidence map›Paper›PMID 40765576›Full record

ArticleInternational journal of women's health2025

Partial Response Achieved in a Case of Metastatic Triple-Negative Breast Cancer Based on the Patient-Derived Tumor Organoids.

Yang Liu, Shuai Liang, Jian Li

Abstract readCase Reports
In one paragraph

Article in International journal of women's health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

3 authors.

Yang LiuDepartment of Breast Surgery, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, People's Republic of China.ORCID 0009-0000-8010-3904
Shuai LiangDepartment of Breast Surgery, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, People's Republic of China.
Jian LiDepartment of Breast Surgery, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The prognosis of triple-negative breast cancer (TNBC) is dismal due to aggressive behaviors. Emergence of patient-derived tumor organoids (PDTOs) allows for biomarker identification and drug screening to identify potential drugs at the patient-specific level. Here, we described a case of metastatic TNBC who obtained partial response in the liver metastatic lesions after treatment with sacituzumab govitecan that was identified highly sensitive by the PDTOs. Case Presentation: A 50-year-old woman visited our hospital for re-examination due to over 9 years after surgery for the left breast cancer. In February 2024, she experienced liver metastasis. In combination with medical history and immunohistochemistry results, metastatic TNBC was diagnosed. Based on the PDTO drug sensitivity testing, the patient was treated with highly sensitive sacituzumab govitecan. After 6 cycles of treatment, liver metastatic lesions were reduced partially. Conclusion: In our case of TNBC, partial response is achieved in the liver metastatic lesions after treatment based on the PDTOs, unveiling that the PDTO, a potential companion tool for selection of treatment options, can facilitate the personalized treatment in metastatic TNBC patients to improve the prognosis.

Indexed as

liver metastasispatient-derived tumor organoidspersonalized treatmentsacituzumab govitecantriple-negative breast cancer

Identifiers

PMID40765576
PMCPMC12323790

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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.