Evidence map›Paper›PMID 41896856›Full record

ArticleBMC medicine2026

Age-related genomic characterization and therapeutic targets in Chinese breast cancer: insights from prospective targeted sequencing and clinical data analysis.

Xin-Yi Sui, Xiao-Qing Song, Xi-Yu Liu, Zhi-Ming Shao, Xin Hu, Chao Chen, Lei Fan

Abstract read
In one paragraph

Article in BMC medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xin-Yi Sui *Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
Xiao-Qing Song *Department of Surgical Oncology, Zhejiang University Medical School Affiliated Sir Run Run Shaw Hospital, Hangzhou, China.
Xi-Yu LiuKey Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
Zhi-Ming ShaoKey Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
Xin HuKey Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China. xinhu@fudan.edu.cn.
Chao ChenKey Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China. chao_chen@fudan.edu.cn.
Lei FanKey Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai, China. teddyfl@163.com.

Funding

Ministry of Science and Technology of the People's Republic of China SQ2023YFF0600039National Key Research and Development Program of China 2023YFC3402504National Natural Science Foundation of China 82002799National Natural Science Foundation of China 82403922National Natural Science Foundation of China 82473273National Natural Science Foundation of China 82473499National Natural Science Foundation of China 82503988Natural Science Foundation of Shanghai Municipality 20ZR1412400Science and Technology Commission of Shanghai Municipality 22Y11912800
6 · The paper itself

Abstract

backgroundIn China, breast cancer occurs at a much younger age and has a higher recurrence and mortality rate. However, with changes in lifestyle, there has been a trend towards an older age of breast cancer incidence in Chinese women. There is a paucity of large-scale next-generation sequencing cohorts for the analysis of genomic characterization in these populations and the identification of potential therapeutic targets.

methodsTo address this gap, we performed prospective targeted sequencing of tumor and blood samples from Chinese patients and collected detailed clinical information. We then categorized patients into two groups based on age (< 40 years, n = 637; ≥ 40 years, n = 3442) and proceeded to provide comprehensive descriptions of somatic and germline mutations in both groups.

resultsThe somatic mutation analysis revealed that PIK3CA, FOXA1, and TBX3 mutations were more prevalent in elderly patients. By leveraging the aforementioned mutational characteristics, we employed our institution's FUTURE-SUPER clinical trial, an umbrella study targeting metastatic breast cancer, to confirm the potential benefits of PI3K-AKT-mTOR pathway inhibitors among elderly patients with breast cancer. Furthermore, TP53 and ERBB2 were more likely to be co-mutated in young women. Patients with TP53 and ERBB2 co-mutation tend to have a poorer prognosis, but through investigation of the SPARK cohort, patients carrying the TP53 and ERBB2 co-mutation are more likely to benefit from immune checkpoint inhibitor combination with tyrosine kinase inhibitor therapy. In our study, we observed a higher frequency of mutations in the DNA homology-dependent recombination pathway in young patients with breast cancer, which was associated with an elevated Ki67 index. Additionally, we confirmed a significant prevalence of germline breast cancer susceptibility gene 1 (gBRCA1) mutations in young patients, whereas germline checkpoint kinase 2 (gCHEK2) mutations are more common in elderly patients.

conclusionsOur study, which makes use of the largest Chinese breast cancer sequencing cohort, sought to characterize the age-related genomic profile of breast cancer patients and identify novel therapeutic opportunities for individuals with breast cancer.

Indexed as

Breast NeoplasmsAdultAgedAge FactorsChinaClass I Phosphatidylinositol 3-KinasesEast Asian PeopleFemaleGenomicsHigh-Throughput Nucleotide SequencingHumansMiddle AgedMutationProspective StudiesClass I Phosphatidylinositol 3-KinasesAge-related mutational profileBreast cancerCancer genetics

Identifiers

PMID41896856
PMCPMC13147738

What OpenQuestion 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 OpenQuestion graph.