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ヒトゲノムに欠けている配列を活用して癌を診断する

Ilias Georgakopoulos-Soares ^1,2,3, Ofer Yizhar-Barnea ^4,5, Ioannis Mouratidis ^6,7

¹Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA. izg5139@psu.edu.
²Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA. izg5139@psu.edu.
³Institute for Personalized Medicine, Department of Molecular and Precision Medicine, The Pennsylvania State University College of Medicine, Hershey, PA, USA. izg5139@psu.edu.
⁴Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.
⁵Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA.
⁶Institute for Personalized Medicine, Department of Molecular and Precision Medicine, The Pennsylvania State University College of Medicine, Hershey, PA, USA.
⁷Huck Institutes of the Life Sciences, Penn State University, University Park, PA, USA.
⁸The Gene Lay Institute of Immunology and Inflammation, Brigham and Women's Hospital, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
⁹Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.
¹⁰Division of Gynecologic Oncology, University of California San Francisco, San Francisco, CA, USA.
¹¹Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.
¹²Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA.
¹³Division of Oncology, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USA.
¹⁴Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA.
¹⁵Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, USA.
¹⁶Division of Hematology/Oncology, Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
¹⁷Helen Diller Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA.
¹⁸Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, USA.
¹⁹Department of Urology, University of California San Francisco, San Francisco, CA, USA.
²⁰Third Department of Internal Medicine, Sotiria Hospital, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece.
²¹Department of Pathology, Yale School of Medicine, New Haven, CT, USA.
²²Breast Oncology, Dana-Farber Brigham Cancer Center, Boston, MA, USA.
²³Kaiser Permanente, Oakland, CA, USA.
²⁴The Gene Lay Institute of Immunology and Inflammation, Brigham and Women's Hospital, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. mhemberg@bwh.harvard.edu.
²⁵Wellcome Sanger Institute, Hinxton, Cambridge, UK. mhemberg@bwh.harvard.edu.
²⁶Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA. nadav.ahituv@ucsf.edu.
²⁷Institute for Human Genetics, University of California San Francisco, San Francisco, CA, USA. nadav.ahituv@ucsf.edu.
²⁸Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA. nadav.ahituv@ucsf.edu.

⁰Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA. izg5139@psu.edu.

Communications Medicine +

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2025年8月21日

PubMedで要約を見る

まとめ

腫瘍変異の短いDNA配列であるネオマーを用いた新しい予測モデルは細胞フリーDNAを用いて初期段階を含む様々な癌を正確に検出しますこのツールは癌のサブタイプと制御変異を特定し診断の感度と特異性を改善します

科学分野

ゲノミクス
分子生物学
癌研究

背景

細胞フリーDNA (cfDNA) 分析は,がんの診断,治療,生存に希望を示しています.
既存のcfDNA診断方法は,正確性と範囲に影響を与える技術的な制限に直面しています.

研究の目的

cfDNAを用いた癌検出のための新しい予測モデルを開発する.
特定のDNAシグネチャーを特定します腫瘍に関連した変異と関連しています

主な方法

13〜17の核酸DNA配列として定義されたネオマーを用いた予測モデルを開発した.
ネオメアは健康な個体ではほとんど存在せず,腫瘍特有の変異によって生じる.
21種類のがんゲノムと465のcfDNA全ゲノム配列を分析した.

主要な成果

ネオマーベースの分類器は初期段階を含むがんを正確に検出し,サブタイプを区別しました.
最先端の方法と比較して,新細胞は腫瘍の種類を区別する上でより高い精度を示した.
cfDNAから肺癌と卵巣がんを正確に検出し,AUCは0. 89- 0. 94であった.
レポーターアッセイによって遺伝子調節活動に影響を与える癌に関連した変異を特定した.

結論

癌の診断に敏感で特定でシンプルなツールとしてネオメアを特定しました
ネオメアアプローチは,遺伝子調節要素内の癌に関連した変異を検出できます.
この方法は,非侵襲的な癌検出と特徴づけのためのcfDNAの可能性を高めます.

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