芝麻 (2022-07-28 09:52):
#paper doi: 10.1016/j.tranon.2021.101016. Epub 2021 Jan 16. PMID: 33465745; PMCID: PMC7815805. Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type. Transl Oncol. 肿瘤转移是肿瘤患者的主要死亡威胁之一,而对一部分转移瘤患者,仅凭形态学观察无法确定肿瘤的原发部位,这样的转移瘤被临床称为原发灶不明转移瘤(Cancer of unknown primary, CUP)因为CUP具有较高的转移侵袭性,且没有可识别的起源部位,医生在选择治疗方案时会有的困扰,因此CUP的精准治疗是肿瘤临床的一个挑战。2021年,Jim Abraham 和同事在超过20000个癌症样本中,结合基因组突变和转录组表达特征两类数据进行基于机器学习的模型训练,并且先后尝试了超过300个不同的机器学习模型,最后在19555个样本的独立验证集中达到了97%的正确率
Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type
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Abstract:
Cancer of Unknown Primary (CUP) occurs in 3-5% of patients when standard histological diagnostic tests are unable to determine the origin of metastatic cancer. Typically, a CUP diagnosis is treated empirically and has very poor outcomes, with median overall survival less than one year. Gene expression profiling alone has been used to identify the tissue of origin but struggles with low neoplastic percentage in metastatic sites which is where identification is often most needed. MI GPSai, a Genomic Prevalence Score, uses DNA sequencing and whole transcriptome data coupled with machine learning to aid in the diagnosis of cancer. The algorithm trained on genomic data from 34,352 cases and genomic and transcriptomic data from 23,137 cases and was validated on 19,555 cases. MI GPSai predicted the tumor type in the labeled data set with an accuracy of over 94% on 93% of cases while deliberating amongst 21 possible categories of cancer. When also considering the second highest prediction, the accuracy increases to 97%. Additionally, MI GPSai rendered a prediction for 71.7% of CUP cases. Pathologist evaluation of discrepancies between submitted diagnosis and MI GPSai predictions resulted in change of diagnosis in 41.3% of the time. MI GPSai provides clinically meaningful information in a large proportion of CUP cases and inclusion of MI GPSai in clinical routine could improve diagnostic fidelity. Moreover, all genomic markers essential for therapy selection are assessed in this assay, maximizing the clinical utility for patients within a single test.
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