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

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 i...

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Main Authors: Xiujuan Li, Ya Zhang, Jianping Gong, Wenjia Liu, Hanchen Zhao, Wei Xue, Zhaojun Ren, Jun Bao, Ziao Lin
Format: Article
Language:English
Published: Nature Publishing Group 2025-04-01
Series:Cell Death Discovery
Online Access:https://doi.org/10.1038/s41420-025-02422-y
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author Xiujuan Li
Ya Zhang
Jianping Gong
Wenjia Liu
Hanchen Zhao
Wei Xue
Zhaojun Ren
Jun Bao
Ziao Lin
author_facet Xiujuan Li
Ya Zhang
Jianping Gong
Wenjia Liu
Hanchen Zhao
Wei Xue
Zhaojun Ren
Jun Bao
Ziao Lin
author_sort Xiujuan Li
collection DOAJ
description 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.
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spelling doaj-art-9341c1cd5ab6434d84e97183a4fe37f02025-08-20T02:17:04ZengNature Publishing GroupCell Death Discovery2058-77162025-04-0111111610.1038/s41420-025-02422-yDevelopment of a breast cancer invasion score to predict tumor aggressiveness and prognosis via PI3K/AKT/mTOR pathway analysisXiujuan Li0Ya Zhang1Jianping Gong2Wenjia Liu3Hanchen Zhao4Wei Xue5Zhaojun Ren6Jun Bao7Ziao Lin8Department of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical UniversityShanghai 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 UniversityDepartment of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical UniversityOmixScience Research Institute, OmixScience Co., Ltd.OmixScience Research Institute, OmixScience Co., Ltd.OmixScience Research Institute, OmixScience Co., Ltd.Department of Pathology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalDepartment of Medical Oncology, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical UniversityOmixScience Research Institute, OmixScience Co., Ltd.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.https://doi.org/10.1038/s41420-025-02422-y
spellingShingle Xiujuan Li
Ya Zhang
Jianping Gong
Wenjia Liu
Hanchen Zhao
Wei Xue
Zhaojun Ren
Jun Bao
Ziao Lin
Development of a breast cancer invasion score to predict tumor aggressiveness and prognosis via PI3K/AKT/mTOR pathway analysis
Cell Death Discovery
title Development of a breast cancer invasion score to predict tumor aggressiveness and prognosis via PI3K/AKT/mTOR pathway analysis
title_full Development of a breast cancer invasion score to predict tumor aggressiveness and prognosis via PI3K/AKT/mTOR pathway analysis
title_fullStr Development of a breast cancer invasion score to predict tumor aggressiveness and prognosis via PI3K/AKT/mTOR pathway analysis
title_full_unstemmed Development of a breast cancer invasion score to predict tumor aggressiveness and prognosis via PI3K/AKT/mTOR pathway analysis
title_short Development of a breast cancer invasion score to predict tumor aggressiveness and prognosis via PI3K/AKT/mTOR pathway analysis
title_sort development of a breast cancer invasion score to predict tumor aggressiveness and prognosis via pi3k akt mtor pathway analysis
url https://doi.org/10.1038/s41420-025-02422-y
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