期刊
CANCER INVESTIGATION
卷 39, 期 1, 页码 62-72出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/07357907.2020.1843662
关键词
Colorectal cancer; biomarker; FOLFOX response; prediction method
类别
A new supervised learning method IML was used to identify two gene expression subgroups related to FOLFOX resistance in colorectal cancer, showing that different DNA damage repair proteins are involved in these subgroups. The study also found that a subgroup of mesenchymal subtype patients benefited from FOLFOX, suggesting that personalized treatments may be needed for different FOLFOX nonresponder subgroups.
To dissect gene expression subgroups of FOLFOX resistance colorectal cancer(CRC) and predict FOLFOX response, gene expression data of 83 stage IV CRC tumor samples (FOLFOX responder n = 42, non-responder n = 41) are used to develop a novel iterative supervised learning method IML. IML identified two mutually exclusive subgroups of CRC patients that relies on different DNA damage repair proteins and resist FOLFOX. IML was validated in two validation sets (HR = 2.6, p Value = 0.02; HR = 2.36, p value = 0.02). A subgroup of mesenchymal subtype patients benefit from FOLFOX. Different subgroups of FOLFOX nonresponders may need to be treated differently.
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