代谢组学
肺癌
医学
新辅助治疗
肿瘤科
内科学
癌症
生物信息学
生物
乳腺癌
作者
Jian Shen,Na Sun,Philipp Zens,Thomas Kunzke,Achim Buck,Verena M. Prade,Jun Wang,Qian Wang,Ronggui Hu,Annette Feuchtinger,Sabina Berezowska,Axel Walch
摘要
The response to neoadjuvant chemotherapy (NAC) differs substantially among individual patients with non-small cell lung cancer (NSCLC). Major pathological response (MPR) is a histomorphological read-out used to assess treatment response and prognosis in patients NSCLC after NAC. Although spatial metabolomics is a promising tool for evaluating metabolic phenotypes, it has not yet been utilized to assess therapy responses in patients with NSCLC. We evaluated the potential application of spatial metabolomics in cancer tissues to assess the response to NAC, using a metabolic classifier that utilizes mass spectrometry imaging combined with machine learning.
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