NPJ Precision Oncology最新文献

A multi-modal deep learning model for prediction of Ki-67 for meningiomas using pretreatment MR images.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-01-21 DOI: 10.1038/s41698-025-00811-1

Chaoyue Chen, Yanjie Zhao, Linrui Cai, Haoze Jiang, Yuen Teng, Yang Zhang, Shuangyi Zhang, Junkai Zheng, Fumin Zhao, Zhouyang Huang, Xiaolong Xu, Xin Zan, Jianfeng Xu, Lei Zhang, Jianguo Xu

{"title":"A multi-modal deep learning model for prediction of Ki-67 for meningiomas using pretreatment MR images.","authors":"Chaoyue Chen, Yanjie Zhao, Linrui Cai, Haoze Jiang, Yuen Teng, Yang Zhang, Shuangyi Zhang, Junkai Zheng, Fumin Zhao, Zhouyang Huang, Xiaolong Xu, Xin Zan, Jianfeng Xu, Lei Zhang, Jianguo Xu","doi":"10.1038/s41698-025-00811-1","DOIUrl":"https://doi.org/10.1038/s41698-025-00811-1","url":null,"abstract":"This study developed and validated a deep learning network using baseline magnetic resonance imaging (MRI) to predict Ki-67 status in meningioma patients. A total of 1239 patients were retrospectively recruited from three hospitals between January 2010 and December 2023, forming training, internal validation, and two external validation cohorts. A representation learning framework was utilized for modeling, and performance was assessed against existing methods. Furthermore, Kaplan-Meier survival analysis was conducted to investigate whether the model could be used for tumor growth prediction. The model achieved superior results, with areas under the curve (AUCs) of 0.797 for internal testing and 0.808 for generalization, alongside 0.756 and 0.727 for 3- and 5-year tumor growth predictions, respectively. The prediction was significantly associated with the growth of asymptomatic small meningiomas. Overall, the model provides an effective tool for early prediction of Ki-67 and tumor volume growth, aiding in individualized patient management.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"21"},"PeriodicalIF":6.8,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143009033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrins identified as potential prognostic markers in osteosarcoma through multi-omics and multi-dataset analysis.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-01-17 DOI: 10.1038/s41698-024-00794-5

Lei Cui, Shuai Zhao, Hai Long Teng, Biao Yang, Qian Liu, An Qin

引用次数: 0

Defective homologous recombination and genomic instability predict increased responsiveness to carbon ion radiotherapy in pancreatic cancer.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-01-17 DOI: 10.1038/s41698-025-00800-4

Brock J Sishc, Janapriya Saha, Elizabeth M Alves, Lianghao Ding, Huiming Lu, Shih-Ya Wang, Katy L Swancutt, James H Nicholson, Angelica Facoetti, Arnold Pompos, Mario Ciocca, Todd A Aguilera, Michael D Story, Anthony J Davis

{"title":"Defective homologous recombination and genomic instability predict increased responsiveness to carbon ion radiotherapy in pancreatic cancer.","authors":"Brock J Sishc, Janapriya Saha, Elizabeth M Alves, Lianghao Ding, Huiming Lu, Shih-Ya Wang, Katy L Swancutt, James H Nicholson, Angelica Facoetti, Arnold Pompos, Mario Ciocca, Todd A Aguilera, Michael D Story, Anthony J Davis","doi":"10.1038/s41698-025-00800-4","DOIUrl":"https://doi.org/10.1038/s41698-025-00800-4","url":null,"abstract":"Pancreatic ductal adenocarcinoma (PDAC) is notably resistant to conventional chemotherapy and radiation treatment. However, clinical trials indicate that carbon ion radiotherapy (CIRT) with concurrent gemcitabine is effective for unresectable locally advanced PDAC. This study aimed to identify patient characteristics predictive of CIRT response. We utilized a panel of human PDAC cell lines with diverse genetic profiles to determine their sensitivity to CIRT compared to γ-rays, assessing relative biological effectiveness (RBE) at 10% survival, which ranged from 1.96 to 3.04. Increased radiosensitivity was linked to impaired DNA double-strand break (DSB) repair, particularly in cell lines with deficiencies in the homologous recombination (HR) repair pathway and/or elevated genomic instability from replication stress. Furthermore, pretreatment with the HR inhibitor B02 significantly enhanced CIRT sensitivity in a radioresistant PDAC cell line when irradiated in the spread-out Bragg peak but not at the entry position of the beam. These findings suggest that PDAC tumors with HR pathway mutations or high replication stress are more likely to benefit from CIRT while minimizing normal tissue toxicity.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"20"},"PeriodicalIF":6.8,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11742413/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143009034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of post-treatment recurrence in early-stage breast cancer using deep-learning with mid-infrared chemical histopathological imaging.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-01-17 DOI: 10.1038/s41698-024-00772-x

Abigail Keogan, Thi Nguyet Que Nguyen, Pascaline Bouzy, Nicholas Stone, Karin Jirstrom, Arman Rahman, William M Gallagher, Aidan D Meade

{"title":"Prediction of post-treatment recurrence in early-stage breast cancer using deep-learning with mid-infrared chemical histopathological imaging.","authors":"Abigail Keogan, Thi Nguyet Que Nguyen, Pascaline Bouzy, Nicholas Stone, Karin Jirstrom, Arman Rahman, William M Gallagher, Aidan D Meade","doi":"10.1038/s41698-024-00772-x","DOIUrl":"https://doi.org/10.1038/s41698-024-00772-x","url":null,"abstract":"Predicting long-term recurrence of disease in breast cancer (BC) patients remains a significant challenge for patients with early stage disease who are at low to intermediate risk of relapse as determined using current clinical tools. Prognostic assays which utilize bulk transcriptomics ignore the spatial context of the cellular material and are, therefore, of limited value in the development of mechanistic models. In this study, Fourier-transform infrared (FTIR) chemical images of BC tissue were used to train deep learning models to predict future disease recurrence. A number of deep learning models were employed, with champion models employing two-dimensional and two-dimensional-separable convolutional networks found to have predictive performance of a ROC AUC of approximately 0.64, which compares well to other clinically used prognostic assays in this space. All-digital chemical imaging may therefore provide a label-free platform for histopathological prognosis in breast cancer, opening new horizons for future deployment of these technologies.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"18"},"PeriodicalIF":6.8,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143009089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Diversity of TCR repertoire predicts recurrence after CRT followed by durvalumab in patients with NSCLC.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-01-15 DOI: 10.1038/s41698-024-00781-w

Masayuki Shirasawa, Tatsuya Yoshida, Takaji Matsutani, Yuki Takeyasu, Naoko Goto, Shigehiro Yagishita, Shigehisa Kitano, Hiroaki Kuroda, Toyoaki Hida, Takayasu Kurata, Yuichiro Ohe

{"title":"Diversity of TCR repertoire predicts recurrence after CRT followed by durvalumab in patients with NSCLC.","authors":"Masayuki Shirasawa, Tatsuya Yoshida, Takaji Matsutani, Yuki Takeyasu, Naoko Goto, Shigehiro Yagishita, Shigehisa Kitano, Hiroaki Kuroda, Toyoaki Hida, Takayasu Kurata, Yuichiro Ohe","doi":"10.1038/s41698-024-00781-w","DOIUrl":"https://doi.org/10.1038/s41698-024-00781-w","url":null,"abstract":"Chemoradiotherapy (CRT) followed by durvalumab is standard for unresectable locally advanced non-small-cell lung cancer (LA-NSCLC). This study assesses how CRT alters the T-cell receptor (TCR) repertoire in CD8 + PD-1 + T-cells and its impact on clinical outcomes. This prospective study, conducted from November 2019 to May 2021 at three institutions in Japan, evaluated the diversity of TCR repertoire (DE50) in PD-1 + CD8 + T-cells and CD8 + T-cell phenotypes in peripheral blood before and after CRT. Forty patients treated with CRT were included. The diversity and usage of TCR beta variable chains (TRBV) and 14 junctional chains (TRBJ) were significantly and positively correlated before and after CRT. Regarding the DE50, the progression-free survival (PFS) of patients with DE50High before CRT was significantly greater than that of those with DE50Low (NR vs. NR months, HR 0.17, p = 0.01). The diversity of TCR repertoire might more accurately predict the efficacy of CRT followed by durvalumab therapy.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"17"},"PeriodicalIF":6.8,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11735630/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143009035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing the NGS-based discrimination of multiple lung cancers from the perspective of evolution.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-01-14 DOI: 10.1038/s41698-024-00786-5

Ziyang Wang, Xiaoqiu Yuan, Kunkun Sun, Fang Wu, Ke Liu, Yiruo Jin, Olga Chervova, Yuntao Nie, Airong Yang, Yichen Jin, Jing Li, Yun Li, Fan Yang, Jun Wang, Stephan Beck, David Carbone, Guanchao Jiang, Kezhong Chen

{"title":"Optimizing the NGS-based discrimination of multiple lung cancers from the perspective of evolution.","authors":"Ziyang Wang, Xiaoqiu Yuan, Kunkun Sun, Fang Wu, Ke Liu, Yiruo Jin, Olga Chervova, Yuntao Nie, Airong Yang, Yichen Jin, Jing Li, Yun Li, Fan Yang, Jun Wang, Stephan Beck, David Carbone, Guanchao Jiang, Kezhong Chen","doi":"10.1038/s41698-024-00786-5","DOIUrl":"10.1038/s41698-024-00786-5","url":null,"abstract":"Next-generation sequencing (NGS) offers a promising approach for differentiating multiple primary lung cancers (MPLC) from intrapulmonary metastasis (IPM), though panel selection and clonal interpretation remain challenging. Whole-exome sequencing (WES) data from 80 lung cancer samples were utilized to simulate MPLC and IPM, with various sequenced panels constructed through gene subsampling. Two clonal interpretation approaches primarily applied in clinical practice, MoleA (based on shared mutation comparison) and MoleB (based on probability calculation), were subsequently evaluated. ROC analysis highlighted MoleB's superior performance, especially with the NCCNplus panel (AUC = 0.950 ± 0.002) and pancancer MoleA (AUC = 0.792 ± 0.004). In two independent cohorts (WES cohort, N = 42 and non-WES cohort, N = 94), NGS-based methodologies effectively stratified disease-free survival, with NCCNplus MoleB further predicting prognosis. Phylogenetic analysis further revealed evolutionary distinctions between MPLC and IPM, establishing an optimized NGS-based framework for differentiating multiple lung cancers.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"14"},"PeriodicalIF":6.8,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11733135/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142984535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A targetable OSGIN1 - AMPK - SLC2A3 axis controls the vulnerability of ovarian cancer to ferroptosis.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-01-14 DOI: 10.1038/s41698-024-00791-8

Mengqi Deng, Fan Tang, Xiangyu Chang, Yanqin Zhang, Penglin Liu, Xuechao Ji, Yubo Zhang, Ruiye Yang, Junyi Jiang, Junqi He, Jinwei Miao

{"title":"A targetable OSGIN1 - AMPK - SLC2A3 axis controls the vulnerability of ovarian cancer to ferroptosis.","authors":"Mengqi Deng, Fan Tang, Xiangyu Chang, Yanqin Zhang, Penglin Liu, Xuechao Ji, Yubo Zhang, Ruiye Yang, Junyi Jiang, Junqi He, Jinwei Miao","doi":"10.1038/s41698-024-00791-8","DOIUrl":"10.1038/s41698-024-00791-8","url":null,"abstract":"Despite advances in various chemotherapy regimens, current therapeutic options are limited for ovarian cancer patients. Oxidative stress-induced growth inhibitor 1 (OSGIN1), which is a tumor suppressor gene known to regulate the cellular stress response and apoptosis, is associated with ovarian cancer development. However, the underlying mechanisms involved in ferroptosis regulation have not been elucidated. Thus, this study aimed to investigate the effect and underlying regulatory mechanism of the OSGIN1 gene on ovarian cancer cells. Our results demonstrated that loss of the OSGIN1 gene promoted ovarian cancer growth and conferred resistance to drug-induced ferroptosis. Mechanistically, the loss of OSGIN1 activates AMPK signaling through ATM, leading to the upregulation of SLC2A3, which protects cells from ferroptosis and renders them insensitive to ferroptosis inducers. Notably, an SLC2A3-neutralizing antibody enhances the ferroptosis-inducing and anticancer effects of sorafenib on ovarian cancer patient-derived xenograft tumors. Overall, anti-SLC2A3 therapy is a promising method to improve ovarian cancer treatment by targeting ferroptosis.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"15"},"PeriodicalIF":6.8,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11733211/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142984381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Genomic landscape and comparative analysis of tissue and liquid-based NGS in Taiwanese anaplastic thyroid carcinoma. 台湾非典型甲状腺癌的基因组图谱及组织和液体 NGS 比较分析

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-01-14 DOI: 10.1038/s41698-025-00802-2

Chun-Nan Yeh, Shu-Fu Lin, Chia-Ling Wu, Miaw-Jene Liou, I-Wen Chen, Chiao-Ping Chen, Ching-Fu Chang, Qi-An Wang, Chiao-En Wu

{"title":"Genomic landscape and comparative analysis of tissue and liquid-based NGS in Taiwanese anaplastic thyroid carcinoma.","authors":"Chun-Nan Yeh, Shu-Fu Lin, Chia-Ling Wu, Miaw-Jene Liou, I-Wen Chen, Chiao-Ping Chen, Ching-Fu Chang, Qi-An Wang, Chiao-En Wu","doi":"10.1038/s41698-025-00802-2","DOIUrl":"10.1038/s41698-025-00802-2","url":null,"abstract":"Anaplastic thyroid carcinoma (ATC) is an aggressive cancer that requirements rapid diagnosis and multimodal treatment. Next-generation sequencing (NGS) aids in personalized therapies and improved trial enrollment. The role of liquid-based NGS in ATC remains unclear. This study analyzed ATC samples using tissue-based NGS, liquid-based NGS, or both platforms. Genetic alterations showed highly heterogeneity, including mutations in RAS/RAF/MEK/ERK, PI3K/AKT/mTOR, cell cycle regulation, other receptor tyrosine kinases, DNA damage response, mismatch repair, and chromatin remodeling. TP53 (65.4%) and BRAF (30.8%) were the most frequently mutated genes in tissue NGS. In paired samples, the concordance rates were 69.2% for TP53 and 84.6% for BRAF. One of two patients treated with dabrafenib and trametinib showed a copy number gain in post-treatment tissue NGS, potentially indicating resistance. Liquid biopsy provides valuable supplementary information when tissue samples are insufficient. Further studies are necessary to understand resistance mechanisms and develop strategies to overcome them in BRAF-targeted therapy.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"16"},"PeriodicalIF":6.8,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11733018/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142984384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep learning for predicting prognostic consensus molecular subtypes in cervical cancer from histology images.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-01-11 DOI: 10.1038/s41698-024-00778-5

Ruoyu Wang, Gozde N Gunesli, Vilde Eide Skingen, Kari-Anne Frikstad Valen, Heidi Lyng, Lawrence S Young, Nasir Rajpoot

{"title":"Deep learning for predicting prognostic consensus molecular subtypes in cervical cancer from histology images.","authors":"Ruoyu Wang, Gozde N Gunesli, Vilde Eide Skingen, Kari-Anne Frikstad Valen, Heidi Lyng, Lawrence S Young, Nasir Rajpoot","doi":"10.1038/s41698-024-00778-5","DOIUrl":"10.1038/s41698-024-00778-5","url":null,"abstract":"Cervical cancer remains the fourth most common cancer among women worldwide. This study proposes an end-to-end deep learning framework to predict consensus molecular subtypes (CMS) in HPV-positive cervical squamous cell carcinoma (CSCC) from H&E-stained histology slides. Analysing three CSCC cohorts (n = 545), we show our Digital-CMS scores significantly stratify patients by both disease-specific (TCGA p = 0.0022, Oslo p = 0.0495) and disease-free (TCGA p = 0.0495, Oslo p = 0.0282) survival. In addition, our extensive tumour microenvironment analysis reveals differences between the two CMS subtypes, with CMS-C1 tumours exhibit increased lymphocyte presence, while CMS-C2 tumours show high nuclear pleomorphism, elevated neutrophil-to-lymphocyte ratio, and higher malignancy, correlating with poor prognosis. This study introduces a potentially clinically advantageous Digital-CMS score derived from digitised WSIs of routine H&E-stained tissue sections, offers new insights into TME differences impacting patient prognosis and potential therapeutic targets, and identifies histological patterns serving as potential surrogate markers of the CMS subtypes for clinical application.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":"9 1","pages":"11"},"PeriodicalIF":6.8,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11724963/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142971808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Author Correction: Interferon signaling and ferroptosis in tumor immunology and therapy.

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2025-01-11 DOI: 10.1038/s41698-025-00807-x

Wei Hu, Ziqian Zhao, Jianxin Du, Jie Jiang, Minghao Yang, Maojin Tian, Peiqing Zhao

引用次数: 0