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未来の科学の夢絵画展、文科大臣賞に愛知の石野さん (朝日新聞)

文部科学大臣賞の「はばのかわるエスカレーター」=愛知県岡崎市立六名小5年、石野雅宜さん画 [PR] 子どもが自由な発想で夢を描く「第42回未来の科学の夢絵画展」...

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Risk stratification of cervical lesions using capture sequencing and machine learning method based on HPV and human integrated genomic profiles.

著者 Tian R , Cui Z , He D , Tian X , Gao Q , Ma X , Yang JR , Wu J , Das BC , Severinov K , Hitzeroth II , Debata PR , Xu W , Zhong H , Fan W , Chen Y , Jin Z , Cao C , Yu M , Xie W , Huang Z , Bao Y , Xie H , Yao S , Hu Z
Carcinogenesis.2019 May 17 ; ():.
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From initial HPV infection and precursor stages, the development of cervical cancer takes decades. High-sensitivity HPV DNA testing is currently recommended as primary screening method for cervical cancer, while better triage methodologies are encouraged to provide accurate risk management for HPV positive women. Given that virus-driven genomic variation accumulates during cervical carcinogenesis, we designed a 39 Mb custom capture panel targeting 17 HPV types and 522 mutant genes related to cervical cancer. Using capture-based next-generation sequencing, HPV integration status, somatic mutation and copy number variation were analyzed on 34 paired samples, including 10 cases of HPV infection (HPV+), 10 cases of CIN1 and 14 cases of CIN2+ (CIN2: n=1; CIN2-3: n=3; CIN3: n=9; SCC: n=1). Finally, the Machine Learning Algorithm-Random Forest was applied to build the risk stratification model for cervical precursor lesions based on CIN2+ enriched biomarkers. Generally, HPV integration events (11 in HPV+, 25 in CIN1 and 56 in CIN2+), non-synonymous mutations (2 in CIN1, 12 in CIN2+) and copy number variations (19.1 in HPV+, 29.4 in CIN1 and 127 in CIN2+) increased from HPV+ to CIN2+. Interestingly, "common" deletion of mitochondrial chromosome was significantly observed in CIN2+ (P value=0.009). Together, CIN2+ enriched biomarkers, classified as HPV information, Mutation, Amplification, Deletion and mitochondrial change, successfully predicted CIN2+ with average accuracy probability score of 0.814, and Amplification and Deletion ranked as the most important features. Our custom capture sequencing combined with machine learning method effectively stratified the risk of cervical lesions and provided valuable integrated triage strategies.
PMID: 31102403 [PubMed - as supplied by publisher]
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