Jingjing Ma , Di Wang , Xiangyu Li , Yaqi Zhang , Qiming Tang , Yun Ding , Xiao Li , Bo Jin , Ruben Y. Luo , Sheeno Thyparambil , Zhi Han , C.James Chou , Ashlee Zhou , James Schilling , Zhiguang Lin , Yan Ma , Qing Li , Mengxue Zhang , Karl G. Sylvester , Seema Nagpal , Bobin Chen
{"title":"脑脊液代谢途径改变作为原发性中枢神经系统淋巴瘤的诊断生物标志物","authors":"Jingjing Ma , Di Wang , Xiangyu Li , Yaqi Zhang , Qiming Tang , Yun Ding , Xiao Li , Bo Jin , Ruben Y. Luo , Sheeno Thyparambil , Zhi Han , C.James Chou , Ashlee Zhou , James Schilling , Zhiguang Lin , Yan Ma , Qing Li , Mengxue Zhang , Karl G. Sylvester , Seema Nagpal , Bobin Chen","doi":"10.1016/j.cca.2025.120377","DOIUrl":null,"url":null,"abstract":"<div><div>Primary Central Nervous System Lymphoma (PCNSL) is a rare and aggressive type of hematological malignancy that can pose diagnostic challenges. Early detection is critical for effective treatment and better patient outcomes. The goal of this study was to assess the potential of metabolic pathway alterations as diagnostic and differential biomarker. We conducted a metabolomics analysis from GEO transcriptomic datasets on brain/lymph nodes. Enriched and significant pathways were validated from patient’s CSF samples from PCNSL, metastatic cancers and non-malignant controls, with mass spectrometry. Next, we utilized machine learning models to assess the separation performance of PCNSLs from other patients and develop diagnostic and differential diagnosis panels. Key metabolic pathways were discovered from GEO datasets analysis and significantly enriched in the CSF of PCNSL. Porphyrin metabolism and fatty acid-related pathways were significantly enriched from diagnostic panel and AUC was 0.88. Additionally, aminoacyl-tRNA biosynthesis, glutathione metabolism, and several amino acid pathways were significantly enriched from differential panel and the AUC was 0.95. Our study highlights the diagnostic biomarker potential of metabolic pathway alterations in CSF for PCNSL, which could lead to the development of non-invasive and reliable diagnostic tool for PCNSL.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"575 ","pages":"Article 120377"},"PeriodicalIF":2.9000,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Metabolic pathway alterations in cerebrospinal fluid as diagnostic biomarkers for primary central nervous system lymphoma\",\"authors\":\"Jingjing Ma , Di Wang , Xiangyu Li , Yaqi Zhang , Qiming Tang , Yun Ding , Xiao Li , Bo Jin , Ruben Y. Luo , Sheeno Thyparambil , Zhi Han , C.James Chou , Ashlee Zhou , James Schilling , Zhiguang Lin , Yan Ma , Qing Li , Mengxue Zhang , Karl G. Sylvester , Seema Nagpal , Bobin Chen\",\"doi\":\"10.1016/j.cca.2025.120377\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Primary Central Nervous System Lymphoma (PCNSL) is a rare and aggressive type of hematological malignancy that can pose diagnostic challenges. Early detection is critical for effective treatment and better patient outcomes. The goal of this study was to assess the potential of metabolic pathway alterations as diagnostic and differential biomarker. We conducted a metabolomics analysis from GEO transcriptomic datasets on brain/lymph nodes. Enriched and significant pathways were validated from patient’s CSF samples from PCNSL, metastatic cancers and non-malignant controls, with mass spectrometry. Next, we utilized machine learning models to assess the separation performance of PCNSLs from other patients and develop diagnostic and differential diagnosis panels. Key metabolic pathways were discovered from GEO datasets analysis and significantly enriched in the CSF of PCNSL. Porphyrin metabolism and fatty acid-related pathways were significantly enriched from diagnostic panel and AUC was 0.88. Additionally, aminoacyl-tRNA biosynthesis, glutathione metabolism, and several amino acid pathways were significantly enriched from differential panel and the AUC was 0.95. Our study highlights the diagnostic biomarker potential of metabolic pathway alterations in CSF for PCNSL, which could lead to the development of non-invasive and reliable diagnostic tool for PCNSL.</div></div>\",\"PeriodicalId\":10205,\"journal\":{\"name\":\"Clinica Chimica Acta\",\"volume\":\"575 \",\"pages\":\"Article 120377\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinica Chimica Acta\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0009898125002566\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICAL LABORATORY TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinica Chimica Acta","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0009898125002566","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
Metabolic pathway alterations in cerebrospinal fluid as diagnostic biomarkers for primary central nervous system lymphoma
Primary Central Nervous System Lymphoma (PCNSL) is a rare and aggressive type of hematological malignancy that can pose diagnostic challenges. Early detection is critical for effective treatment and better patient outcomes. The goal of this study was to assess the potential of metabolic pathway alterations as diagnostic and differential biomarker. We conducted a metabolomics analysis from GEO transcriptomic datasets on brain/lymph nodes. Enriched and significant pathways were validated from patient’s CSF samples from PCNSL, metastatic cancers and non-malignant controls, with mass spectrometry. Next, we utilized machine learning models to assess the separation performance of PCNSLs from other patients and develop diagnostic and differential diagnosis panels. Key metabolic pathways were discovered from GEO datasets analysis and significantly enriched in the CSF of PCNSL. Porphyrin metabolism and fatty acid-related pathways were significantly enriched from diagnostic panel and AUC was 0.88. Additionally, aminoacyl-tRNA biosynthesis, glutathione metabolism, and several amino acid pathways were significantly enriched from differential panel and the AUC was 0.95. Our study highlights the diagnostic biomarker potential of metabolic pathway alterations in CSF for PCNSL, which could lead to the development of non-invasive and reliable diagnostic tool for PCNSL.
期刊介绍:
The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC)
Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells.
The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.