NPJ Precision Oncology最新文献_第9页

Potential of pre-diagnostic metabolomics for colorectal cancer risk assessment or early detection 诊断前代谢组学在结直肠癌风险评估或早期检测方面的潜力。

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2024-10-27 DOI: 10.1038/s41698-024-00732-5

Teresa Seum, Clara Frick, Rafael Cardoso, Megha Bhardwaj, Michael Hoffmeister, Hermann Brenner

{"title":"Potential of pre-diagnostic metabolomics for colorectal cancer risk assessment or early detection","authors":"Teresa Seum, Clara Frick, Rafael Cardoso, Megha Bhardwaj, Michael Hoffmeister, Hermann Brenner","doi":"10.1038/s41698-024-00732-5","DOIUrl":"10.1038/s41698-024-00732-5","url":null,"abstract":"This systematic review investigates the efficacy of metabolite biomarkers for risk assessment or early detection of colorectal cancer (CRC) and its precursors, focusing on pre-diagnostic biospecimens. Searches in PubMed, Web of Science, and SCOPUS through December 2023 identified relevant prospective studies. Relevant data were extracted, and the risk of bias was assessed with the QUADAS-2 tool. Among the 26 studies included, significant heterogeneity existed for case numbers, metabolite identification, and validation approaches. Thirteen studies evaluated individual metabolites, mainly lipids, while eleven studies derived metabolite panels, and two studies did both. Nine panels were internally validated, resulting in an area under the curve (AUC) ranging from 0.69 to 0.95 for CRC precursors and 0.72 to 1.0 for CRC. External validation was limited to one panel (AUC = 0.72). Metabolite panels and lipid-based biomarkers show promise for CRC risk assessment and early detection but require standardization and extensive validation for clinical use.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":" ","pages":"1-13"},"PeriodicalIF":6.8,"publicationDate":"2024-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11514036/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142505055","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

ALYREF recruits ELAVL1 to promote colorectal tumorigenesis via facilitating RNA m5C recognition and nuclear export ALYREF 通过促进 RNA m5C 识别和核输出，招募 ELAVL1 以促进结直肠肿瘤发生。

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2024-10-25 DOI: 10.1038/s41698-024-00737-0

Longhua Zhong, Jingxun Wu, Bingqian Zhou, Jiapeng Kang, Xicheng Wang, Feng Ye, Xiaoting Lin

{"title":"ALYREF recruits ELAVL1 to promote colorectal tumorigenesis via facilitating RNA m5C recognition and nuclear export","authors":"Longhua Zhong, Jingxun Wu, Bingqian Zhou, Jiapeng Kang, Xicheng Wang, Feng Ye, Xiaoting Lin","doi":"10.1038/s41698-024-00737-0","DOIUrl":"10.1038/s41698-024-00737-0","url":null,"abstract":"ALYREF can recognize 5-methylcytosine (m5C) decoration throughout RNAs to regulate RNA metabolism. However, its implications in cancer and precise regulatory mechanisms remain largely elusive. Here, we demonstrated that ALYREF supported colorectal cancer (CRC) growth and migration. Integrated analysis of ALYREF-RIP-Bis-seq and transcriptome profiles identified ribosomal protein S6 kinase B2 (RPS6KB2) and regulatory-associated protein of mTOR (RPTOR) as ALYREF’s possible downstream effectors. Mechanistically, ALYREF formed a complex with ELAV like RNA binding protein 1 (ELAVL1) to cooperatively promote m5C recognition and nuclear export of the two mRNAs. Moreover, ALYREF protein was highly expressed in tumor tissues of CRC patients, which predicted their poor prognosis. E2F transcription factor 6 (E2F6)-mediated transactivation gave a molecular insight into ALYREF overexpression. Collectively, ALYREF recruits ELAVL1 to collaboratively facilitate m5C recognition and nuclear export of RPS6KB2 and RPTOR transcripts for colorectal tumorigenesis, providing RNA m5C methylation as promising therapeutic targets and prognostic biomarkers for CRC.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":" ","pages":"1-13"},"PeriodicalIF":6.8,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11512073/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142516512","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

Development and validation of a gene expression-based Breast Cancer Purity Score 开发并验证基于基因表达的乳腺癌纯度评分。

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2024-10-24 DOI: 10.1038/s41698-024-00730-7

Marco Barreca, Matteo Dugo, Barbara Galbardi, Balázs Győrffy, NA-PHER2 consortium, NeoTRIP consortium, Pinuccia Valagussa, Daniela Besozzi, Giuseppe Viale, Giampaolo Bianchini, Luca Gianni, Maurizio Callari

{"title":"Development and validation of a gene expression-based Breast Cancer Purity Score","authors":"Marco Barreca, Matteo Dugo, Barbara Galbardi, Balázs Győrffy, NA-PHER2 consortium, NeoTRIP consortium, Pinuccia Valagussa, Daniela Besozzi, Giuseppe Viale, Giampaolo Bianchini, Luca Gianni, Maurizio Callari","doi":"10.1038/s41698-024-00730-7","DOIUrl":"10.1038/s41698-024-00730-7","url":null,"abstract":"The prevalence of malignant cells in clinical specimens, or tumour purity, is affected by both intrinsic biological factors and extrinsic sampling bias. Molecular characterization of large clinical cohorts is typically performed on bulk samples; data analysis and interpretation can be biased by tumour purity variability. Transcription-based strategies to estimate tumour purity have been proposed, but no breast cancer specific method is available yet. We interrogated over 6000 expression profiles from 10 breast cancer datasets to develop and validate a 9-gene Breast Cancer Purity Score (BCPS). BCPS outperformed existing methods for estimating tumour content. Adjusting transcriptomic profiles using the BCPS reduces sampling bias and aids data interpretation. BCPS-estimated tumour purity improved prognostication in luminal breast cancer, correlated with pathologic complete response in on-treatment biopsies from triple-negative breast cancer patients undergoing neoadjuvant treatment and effectively stratified the risk of relapse in HER2+ residual disease post-neoadjuvant treatment.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":" ","pages":"1-11"},"PeriodicalIF":6.8,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11502849/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142505052","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

Large language model use in clinical oncology 大语言模型在临床肿瘤学中的应用。

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2024-10-23 DOI: 10.1038/s41698-024-00733-4

Nicolas Carl, Franziska Schramm, Sarah Haggenmüller, Jakob Nikolas Kather, Martin J. Hetz, Christoph Wies, Maurice Stephan Michel, Frederik Wessels, Titus J. Brinker

{"title":"Large language model use in clinical oncology","authors":"Nicolas Carl, Franziska Schramm, Sarah Haggenmüller, Jakob Nikolas Kather, Martin J. Hetz, Christoph Wies, Maurice Stephan Michel, Frederik Wessels, Titus J. Brinker","doi":"10.1038/s41698-024-00733-4","DOIUrl":"10.1038/s41698-024-00733-4","url":null,"abstract":"Large language models (LLMs) are undergoing intensive research for various healthcare domains. This systematic review and meta-analysis assesses current applications, methodologies, and the performance of LLMs in clinical oncology. A mixed-methods approach was used to extract, summarize, and compare methodological approaches and outcomes. This review includes 34 studies. LLMs are primarily evaluated on their ability to answer oncologic questions across various domains. The meta-analysis highlights a significant performance variance, influenced by diverse methodologies and evaluation criteria. Furthermore, differences in inherent model capabilities, prompting strategies, and oncological subdomains contribute to heterogeneity. The lack of use of standardized and LLM-specific reporting protocols leads to methodological disparities, which must be addressed to ensure comparability in LLM research and ultimately leverage the reliable integration of LLM technologies into clinical practice.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":" ","pages":"1-17"},"PeriodicalIF":6.8,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11499929/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142505054","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

Therapeutic approaches to modulate the immune microenvironment in gliomas 调节胶质瘤免疫微环境的治疗方法。

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2024-10-23 DOI: 10.1038/s41698-024-00717-4

Andreas Sarantopoulos, Chibawanye Ene, Elisa Aquilanti

引用次数: 0

The clinical outcome, pathologic spectrum, and genomic landscape for 454 cases of salivary mucoepidermoid carcinoma 454 例唾液粘液表皮样癌的临床结果、病理谱系和基因组图谱。

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2024-10-22 DOI: 10.1038/s41698-024-00735-2

Xi Wang, Jiaying Bai, Jing Yan, Binbin Li

{"title":"The clinical outcome, pathologic spectrum, and genomic landscape for 454 cases of salivary mucoepidermoid carcinoma","authors":"Xi Wang, Jiaying Bai, Jing Yan, Binbin Li","doi":"10.1038/s41698-024-00735-2","DOIUrl":"10.1038/s41698-024-00735-2","url":null,"abstract":"Mucoepidermoid carcinoma (MEC) is the most common malignant salivary tumor. A complete understanding of the high heterogeneity of MEC in histology and genetics would help in accurate diagnosis and treatment. Therefore, We evaluated the clinical features, treatment outcomes, and pathological parameters of 454 MECs and analyzed their genomic features using whole-exome sequencing and whole-transcriptome sequencing. We found that MECs predominantly occurred in females and those in their 4th–5th decades. The parotid gland was the most frequently affected site. All patients underwent complete mass resection with lobectomy; 414 patients were alive without relapse at follow-up, after an average period of 62 months (1–116 months). The disease progressed after initial treatment in 40 patients. The lungs were the most common site of distant metastasis. For classical MECs, histologic gradings of the AFIP, modified Healey, and MSK systems were significantly associated with recurrence and lymph nodal metastasis; these gradings were significantly related to lymph nodal metastasis for the subtypes. Older age, minor salivary gland involvement, clinical symptoms, high TNM stage, high-grade tumor, and improper surgical modality were the main prognostic factors. BAP1 was the most frequently mutated gene in MEC. Mutations in CDKN2A, MET, and TP53 were more frequently found in aggressive tumor phenotypes. MAML2 rearrangement was observed in 42% of patients, and EWSR1 rearrangement in 8%. Specific genetic events (in TP53 and FBXW7) with CRTC1::MAML2 fusion superimposed might be associated with unfavorable prognosis. This study provides new insights into precision therapeutic strategies for MEC.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":" ","pages":"1-13"},"PeriodicalIF":6.8,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11496733/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142505056","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

Development and validation of machine learning models for young-onset colorectal cancer risk stratification 开发和验证用于年轻发病结直肠癌风险分层的机器学习模型。

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2024-10-22 DOI: 10.1038/s41698-024-00719-2

Junhai Zhen, Jiao Li, Fei Liao, Jixiang Zhang, Chuan Liu, Huabing Xie, Cheng Tan, Weiguo Dong

{"title":"Development and validation of machine learning models for young-onset colorectal cancer risk stratification","authors":"Junhai Zhen, Jiao Li, Fei Liao, Jixiang Zhang, Chuan Liu, Huabing Xie, Cheng Tan, Weiguo Dong","doi":"10.1038/s41698-024-00719-2","DOIUrl":"10.1038/s41698-024-00719-2","url":null,"abstract":"Incidence of young-onset colorectal cancer (YOCRC, younger than 50) has significantly increased worldwide. The performance of fecal immunochemical test in detecting YOCRC is unsatisfactory. Using routine clinical data, we aimed to develop machine learning (ML) models to identify individuals with high-risk YOCRC who require further colonoscopy. We retrospectively extracted data of 10,874 young individuals. Multiple supervised ML techniques were devised to distinguish individuals with and without CRC, classifiers were trained, internally validated and temporally validated. In internal validation cohort, Random Forest (RF) ML model demonstrated good performance with AUC of 0.859 and highest recall of 0.840. In temporal validation cohort, the RF ML model also exhibited good classification performance, achieving AUC of 0.888 and highest recall of 0.872. RF algorithm-based approach is effective and feasible in YOCRC risk stratification. This could be valuable in assessing the risk of YOCRC so that clinical management, including further colonoscopy, can be subsequently made. (Registration: This study was registered with ClinicalTrials.gov (NCT06342622) on March 15, 2024.).","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":" ","pages":"1-14"},"PeriodicalIF":6.8,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11496529/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142505053","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: Development and interpretation of a multimodal predictive model for prognosis of gastrointestinal stromal tumor 作者更正：胃肠道间质瘤预后多模式预测模型的开发与解读。

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2024-10-21 DOI: 10.1038/s41698-024-00738-z

XianHao Xiao, Xu Han, YeFei Sun, GuoLiang Zheng, Qi Miao, YuLong Zhang, JiaYing Tan, Gang Liu, QianRu He, JianPing Zhou, ZhiChao Zheng, GuiYang Jiang, He Song

引用次数: 0

Phenotypic evaluation of deep learning models for classifying germline variant pathogenicity 用于种系变异致病性分类的深度学习模型的表型评估

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2024-10-19 DOI: 10.1038/s41698-024-00710-x

Ryan D. Chow, Katherine L. Nathanson, Ravi B. Parikh

引用次数: 0

Novel paediatric case of a spinal high-grade astrocytoma with piloid features in a patient with Noonan Syndrome 努南综合征患者脊柱高级别星形细胞瘤的儿科新病例（具有类皮质特征

IF 6.8 1区医学

NPJ Precision Oncology Pub Date : 2024-10-19 DOI: 10.1038/s41698-024-00734-3

Jordan Staunton, Pamela Ajuyah, Angela Harris, Chelsea Mayoh, Marie Wong, Megan Rumford, Patricia J. Sullivan, Paul G. Ekert, Noemi Fuentes-Bolanos, Mark J. Cowley, Loretta M. S. Lau, David S. Ziegler, Paulette Barahona, Neevika Manoharan

{"title":"Novel paediatric case of a spinal high-grade astrocytoma with piloid features in a patient with Noonan Syndrome","authors":"Jordan Staunton, Pamela Ajuyah, Angela Harris, Chelsea Mayoh, Marie Wong, Megan Rumford, Patricia J. Sullivan, Paul G. Ekert, Noemi Fuentes-Bolanos, Mark J. Cowley, Loretta M. S. Lau, David S. Ziegler, Paulette Barahona, Neevika Manoharan","doi":"10.1038/s41698-024-00734-3","DOIUrl":"10.1038/s41698-024-00734-3","url":null,"abstract":"Noonan Syndrome (NS) is associated with an increased risk of low-grade central nervous system tumours in children but only very rarely associated with high-grade gliomas. Here we describe the first reported case of a spinal high-grade astrocytoma with piloid features (HGAP) in a child with NS. This case was a diagnostic and treatment dilemma, prior to whole-genome germline and tumour sequencing, tumour transcriptome sequencing and DNA methylation analysis. The methylation profile matched strongly with HGAP and sequencing identified somatic FGFR1 and NF1 variants and a PTPN11 germline pathogenic variant. Therapeutic targets were identified but also alterations novel to HGAP such as differential expression of VEGFA and PD-L1. The germline PTPN11 finding has not been previously described in individuals with HGAP. This case underscores the power of precision medicine from a diagnostic, therapeutic and clinical management perspective, and describes an association between HGAP and NS which has not previously been reported.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":" ","pages":"1-7"},"PeriodicalIF":6.8,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41698-024-00734-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142451278","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