Evidence map›Paper›PMID 40204712›Full record

ArticleCell death discovery2025

Development of a breast cancer invasion score to predict tumor aggressiveness and prognosis via PI3K/AKT/mTOR pathway analysis.

Xiujuan Li, Ya Zhang, Jianping Gong, Wenjia Liu, Hanchen Zhao, Wei Xue, Zhaojun Ren, Jun Bao, Ziao Lin

Abstract read
In one paragraph

Article in Cell death discovery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

9 authors.

Xiujuan Li *Department of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210000, China.ORCID http://orcid.org/0000-0001-5324-0655
Ya Zhang *Shanghai Key Laboratory of Maternal and Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.ORCID http://orcid.org/0000-0002-9717-911X
Jianping Gong *Department of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210000, China.
Wenjia LiuOmixScience Research Institute, OmixScience Co., Ltd., Hangzhou, 311199, China.
Hanchen ZhaoOmixScience Research Institute, OmixScience Co., Ltd., Hangzhou, 311199, China.
Wei XueOmixScience Research Institute, OmixScience Co., Ltd., Hangzhou, 311199, China.
Zhaojun RenDepartment of Pathology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, 210000, China. renzhaojun18@126.com.ORCID http://orcid.org/0000-0003-2376-5156
Jun BaoDepartment of Medical Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210000, China. 2336093491@qq.com.ORCID http://orcid.org/0009-0000-4934-6123
Ziao LinOmixScience Research Institute, OmixScience Co., Ltd., Hangzhou, 311199, China. ziaolin@zju.edu.cn.ORCID http://orcid.org/0009-0003-7436-1415

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invasiveness is a key indicator of tumor malignancy and is often linked to poor prognosis in breast cancer (BC). To explore the diverse characteristics of invasive cells, single-cell RNA sequencing (scRNA-seq) data from three ductal carcinoma stages were analyzed, classifying samples into invasion and non-invasion groups. Nine genes (MCTS1, PGK1, PCMT1, C8orf76, TMEM242, QPRT, SLC16A2, AFG1L, and SPINK8) were identified as key discriminators between these groups. A breast cancer invasion score (BCIS) model was developed using LASSO Cox regression, revealed that high BCIS correlated with poorer overall survival in TCGA-BRCA patients and was validated across GSE20685 and METABRIC datasets (five-year and ten-year survival). Functional experiments demonstrated that knockdown of PGK1 or PCMT1 inhibited tumor cell proliferation and reduced the phosphorylation levels of mTORC, P70S6K, S6, and AKT, indicating suppression of the PI3K/AKT/mTOR pathways. High-BCIS tumors exhibited enrichment in protein secretion and PI3K/AKT/mTOR pathways, associated with aggressiveness and therapy resistance. This study introduced the BCIS score, distinguishing invasion from non-invasion cells, linked to PI3K/AKT/mTOR pathways, offering insights into BRCA prognosis and tumor aggressiveness.

Identifiers

PMID40204712
PMCPMC11982538

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Registered trials

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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.