Xudong Jin , Jinhua Rong , Shen Peng , You Xiao , Ruting Wang , Yixuan Gu , Wenhao Ji , Xiancong Huang , Weimin Mao
{"title":"综合代谢组学和脂质组学揭示非小细胞肺癌伴脑转移的血浆标志物。","authors":"Xudong Jin , Jinhua Rong , Shen Peng , You Xiao , Ruting Wang , Yixuan Gu , Wenhao Ji , Xiancong Huang , Weimin Mao","doi":"10.1016/j.cca.2025.120399","DOIUrl":null,"url":null,"abstract":"<div><div>Brain metastasis (BM) is a fatal complication of non-small cell lung cancer (NSCLC). The lack of non-invasion methods for early diagnosis and risk stratification is the major cause for the poor prognosis of NSCLC with BM. The metabolic state of BM has a significant change characterized with high reactive oxygen species accumulation and the subsequent antioxidant metabolic response. We sought to screen plasma markers based on metabolomics and lipidomics for the early diagnosis and prognostic evaluation of NSCLC patients with BM. Plasma samples collected from 48 NSCLC patients with BM and 49 gender- and age- matched primary lung cancer (PLC) patients were randomly divided into train set and test set, then analyzations of metabolomics and lipidomics were performed using liquid chromatography-tandem mass spectrometry (LC-MS). Differential metabolites and lipids were discovered from the train set. A diagnostic biomarker panel was constructed using logistic regression. The test set were utilized to validate the accuracy of the diagnostic model. Furthermore, a risk score was established to stratify risk for NSCLC patients. There were 34 differential metabolites and 35 differential lipids annotated in the train set. The diagnostic biomarker panel consisting of homocysteine, ascorbic acid, LPC (22:0) and LPC (20:0) is able to discriminate BM from PLC with an excellent performance. The risk score based on protocatechuic acid and LPC (20:0) could efficiently stratify risk for NSCLC patients with BM. Our study reports plasma biomarkers and predictive models for the early diagnosis and prognostic evaluation of NSCLC patients with BM.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"576 ","pages":"Article 120399"},"PeriodicalIF":2.9000,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated metabolomics and lipidomics reveal plasma markers of non-small cell lung cancer with brain metastasis\",\"authors\":\"Xudong Jin , Jinhua Rong , Shen Peng , You Xiao , Ruting Wang , Yixuan Gu , Wenhao Ji , Xiancong Huang , Weimin Mao\",\"doi\":\"10.1016/j.cca.2025.120399\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Brain metastasis (BM) is a fatal complication of non-small cell lung cancer (NSCLC). The lack of non-invasion methods for early diagnosis and risk stratification is the major cause for the poor prognosis of NSCLC with BM. The metabolic state of BM has a significant change characterized with high reactive oxygen species accumulation and the subsequent antioxidant metabolic response. We sought to screen plasma markers based on metabolomics and lipidomics for the early diagnosis and prognostic evaluation of NSCLC patients with BM. Plasma samples collected from 48 NSCLC patients with BM and 49 gender- and age- matched primary lung cancer (PLC) patients were randomly divided into train set and test set, then analyzations of metabolomics and lipidomics were performed using liquid chromatography-tandem mass spectrometry (LC-MS). Differential metabolites and lipids were discovered from the train set. A diagnostic biomarker panel was constructed using logistic regression. The test set were utilized to validate the accuracy of the diagnostic model. Furthermore, a risk score was established to stratify risk for NSCLC patients. There were 34 differential metabolites and 35 differential lipids annotated in the train set. The diagnostic biomarker panel consisting of homocysteine, ascorbic acid, LPC (22:0) and LPC (20:0) is able to discriminate BM from PLC with an excellent performance. The risk score based on protocatechuic acid and LPC (20:0) could efficiently stratify risk for NSCLC patients with BM. Our study reports plasma biomarkers and predictive models for the early diagnosis and prognostic evaluation of NSCLC patients with BM.</div></div>\",\"PeriodicalId\":10205,\"journal\":{\"name\":\"Clinica Chimica Acta\",\"volume\":\"576 \",\"pages\":\"Article 120399\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-05-27\",\"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/S0009898125002785\",\"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/S0009898125002785","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
Integrated metabolomics and lipidomics reveal plasma markers of non-small cell lung cancer with brain metastasis
Brain metastasis (BM) is a fatal complication of non-small cell lung cancer (NSCLC). The lack of non-invasion methods for early diagnosis and risk stratification is the major cause for the poor prognosis of NSCLC with BM. The metabolic state of BM has a significant change characterized with high reactive oxygen species accumulation and the subsequent antioxidant metabolic response. We sought to screen plasma markers based on metabolomics and lipidomics for the early diagnosis and prognostic evaluation of NSCLC patients with BM. Plasma samples collected from 48 NSCLC patients with BM and 49 gender- and age- matched primary lung cancer (PLC) patients were randomly divided into train set and test set, then analyzations of metabolomics and lipidomics were performed using liquid chromatography-tandem mass spectrometry (LC-MS). Differential metabolites and lipids were discovered from the train set. A diagnostic biomarker panel was constructed using logistic regression. The test set were utilized to validate the accuracy of the diagnostic model. Furthermore, a risk score was established to stratify risk for NSCLC patients. There were 34 differential metabolites and 35 differential lipids annotated in the train set. The diagnostic biomarker panel consisting of homocysteine, ascorbic acid, LPC (22:0) and LPC (20:0) is able to discriminate BM from PLC with an excellent performance. The risk score based on protocatechuic acid and LPC (20:0) could efficiently stratify risk for NSCLC patients with BM. Our study reports plasma biomarkers and predictive models for the early diagnosis and prognostic evaluation of NSCLC patients with BM.
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.