{"id":3799,"date":"2023-08-04T17:59:22","date_gmt":"2023-08-04T17:59:22","guid":{"rendered":"https:\/\/dailyai.com\/?p=3799"},"modified":"2023-08-04T18:05:23","modified_gmt":"2023-08-04T18:05:23","slug":"ai-powered-blood-test-detects-cancers-in-single-dna-molecules","status":"publish","type":"post","link":"https:\/\/dailyai.com\/de\/2023\/08\/ai-powered-blood-test-detects-cancers-in-single-dna-molecules\/","title":{"rendered":"KI-gest\u00fctzter Bluttest erkennt Krebserkrankungen in einzelnen DNA-Molek\u00fclen"},"content":{"rendered":"

Forscher des Johns Hopkins Kimmel Cancer Center entwickeln eine neuartige Bluttesttechnologie namens GEMINI (Genomweite Mutationsinzidenz zur nicht-invasiven Erkennung von Krebs).\u00a0<\/b><\/p>\n

Durch die Kombination von genomweiter Sequenzierung einzelner DNA-Molek\u00fcle, die von Tumoren abgesto\u00dfen werden, mit maschinellem Lernen (ML) k\u00f6nnte der Test eine fr\u00fchere Erkennung von Lungenkrebs und anderen Krebsarten erm\u00f6glichen.<\/span><\/p>\n

Der GEMINI-Test analysiert zellfreie DNA-Fragmente (cfDNA), die von Tumoren ausgeschieden werden, und verwendet ML, um Unterschiede in der H\u00e4ufigkeit von Krebs- und Nicht-Krebs-Mutationen im gesamten Genom zu erkennen. H\u00f6here Werte des Modells deuten auf eine h\u00f6here Wahrscheinlichkeit hin, an Krebs zu erkranken.<\/span><\/p>\n

In Labortests wurde GEMINI auf Computertomographie-Bilder angewandt und erkannte \u00fcber 90% Lungenkrebs, sogar in fr\u00fchen Stadien. Die Website <\/span>Studie<\/span><\/a> Die Ergebnisse wurden in Nature Genetics ver\u00f6ffentlicht.\u00a0<\/span><\/p>\n

Die Forscher konzentrierten sich haupts\u00e4chlich auf die Erkennung von Lungenkrebs in Hochrisikopopulationen. <\/span><\/p>\n

Ver\u00e4nderte Mutationsprofile wurden jedoch auch in der cfDNA von Patienten mit Leberkrebs, Melanomen und Lymphomen beobachtet, so dass dieser Ansatz auch bei anderen Krebsarten eingesetzt werden k\u00f6nnte.\u00a0<\/span><\/p>\n

Wie die Forscher GEMINI entwickelt haben<\/span><\/h2>\n

Zur Entwicklung von GEMINI untersuchte das Team die Genomsequenzen von 2.511 Personen aus 25 verschiedenen Krebsarten.\u00a0<\/span><\/p>\n

Verschiedene Tumorarten wiesen unterschiedliche Mutationsprofile auf. Die Forscher fanden heraus, dass genomische Regionen mit einer hohen Mutationsh\u00e4ufigkeit zwischen Tumorgewebe und aus Blut gewonnener cfDNA bei Patienten mit Lungenkrebs, Melanom oder B-Zell-Non-Hodgkin-Lymphom \u00e4hnlich waren.\u00a0<\/span><\/p>\n

Der GEMINI-Test wurde dann auf cfDNA von 365 Personen mit hohem Lungenkrebsrisiko angewandt und ergab bei Personen mit Krebs h\u00f6here Werte als bei Personen ohne Krebs.\u00a0<\/span><\/p>\n

Die Forscher untersuchten auch die Integration von GEMINI mit einem fr\u00fcheren Test, der als DELFI (DNA evaluation of fragments for early interception) bekannt ist,<\/span><\/p>\n

Insgesamt identifizierten GEMINI und DELFI bei 89 Proben in 91% der F\u00e4lle den Krebs korrekt.<\/span><\/p>\n

\"ML-Krebs\"
Maschinelles Lernen half den Forschern bei der Analyse von Krebsmarkern in Zellen. Quelle: Natur<\/a>.<\/figcaption><\/figure>\n

Bemerkenswert ist, dass der GEMINI-Test bei sieben Patienten, bei denen zum Zeitpunkt der Blutentnahme kein Tumor nachweisbar war, bereits Jahre vor der Standarddiagnose Anomalien in den cfDNA-Mutationsprofilen feststellte.\u00a0<\/span><\/p>\n

Sechs von ihnen wurden mit GEMINI positiv getestet, und 231 bis 1.868 Tage nach der Probenentnahme wurde bei ihnen Lungenkrebs diagnostiziert.<\/span><\/p>\n

Aufschl\u00fcsselung der Studie<\/span><\/h2>\n
    \n
  1. Blutentnahme<\/b>: Einer Person, bei der ein Krebsrisiko bestehen k\u00f6nnte, wird eine Blutprobe entnommen. Diese Probe enth\u00e4lt cfDNA, winzige DNA-Fragmente, die von Zellen im K\u00f6rper, einschlie\u00dflich potenzieller Tumorzellen, ausgeschieden wurden.<\/span><\/li>\n
  2. DNA-Extraktion und Sequenzierung<\/b>: Die cfDNA wird aus der Blutprobe extrahiert und dann sequenziert. Das bedeutet, dass die Wissenschaftler die Reihenfolge der \"Bausteine\", aus denen die DNA besteht, aufzeichnen. Dies hilft ihnen, Ver\u00e4nderungen oder Mutationen in der DNA zu erkennen.<\/span><\/li>\n
  3. Analyse von DNA-Ver\u00e4nderungen<\/b>: Jedes einzelne DNA-Molek\u00fcl wird auf Sequenzver\u00e4nderungen untersucht, so dass die Forscher Mutationsprofile f\u00fcr das gesamte Genom erstellen k\u00f6nnen. Im Wesentlichen suchen sie nach Mustern in den Mutationen, die auf das Vorhandensein von Krebs hindeuten k\u00f6nnten.<\/span><\/li>\n
  4. Maschinelles Lernen<\/b>: Ein maschinelles Lernmodell, das darauf trainiert wurde, den Unterschied zwischen krebsartigen und nicht krebsartigen Mutationsh\u00e4ufigkeiten in verschiedenen Bereichen des Genoms zu erkennen, wird dann zur Analyse der Mutationsprofile verwendet. Das maschinelle Lernmodell vergibt dann eine Punktzahl zwischen 0 und 1, wobei eine h\u00f6here Punktzahl auf eine h\u00f6here Krebswahrscheinlichkeit hinweist.<\/span><\/li>\n
  5. Weitere Validierung und Pr\u00fcfung<\/b>: Ist der GEMINI-Score hoch, was auf das Vorhandensein von Krebs hindeutet, werden zus\u00e4tzliche Tests wie die Computertomographie und der DELFI-Test (der Ver\u00e4nderungen in der Gr\u00f6\u00dfe und Verteilung von cfDNA-Fragmenten im Genom nachweist) eingesetzt, um die Diagnose zu best\u00e4tigen und das Krebsstadium zu ermitteln. Diese Kombination von Tests hat sich als sehr wirksam erwiesen, da mehr als 90% der Lungenkrebse in der Studie entdeckt wurden.<\/span><\/li>\n<\/ol>\n

    Dies ist eine weitere faszinierende Studie, die die neuartige Anwendung des maschinellen Lernens in der medizinischen Diagnostik zeigt, diesmal bei der Analyse von Krebserkrankungen auf zellul\u00e4rer Ebene. <\/span><\/p>\n

    Gr\u00f6\u00dfere klinische Studien sind erforderlich, um das Instrument zu validieren, bevor es f\u00fcr den klinischen Einsatz zur Verf\u00fcgung stehen kann.<\/span><\/p>\n

    Diese Woche wird ein AI-gest\u00fctztes Brustkrebs-Screening<\/a> Der Workflow hat die Geschwindigkeit und Effizienz der Auswertung von Mammogrammen auf Krebs erheblich verbessert.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Forscher am Johns Hopkins Kimmel Cancer Center entwickeln eine neuartige Bluttesttechnologie namens GEMINI (Genomweite Mutationsinzidenz zur nicht-invasiven Erkennung von Krebs). Durch die Kombination von genomweiter Sequenzierung einzelner DNA-Molek\u00fcle, die von Tumoren abgesto\u00dfen werden, mit maschinellem Lernen (ML) k\u00f6nnte der Test eine fr\u00fchere Erkennung von Lungen- und anderen Krebsarten erm\u00f6glichen. Der GEMINI-Test analysiert Fragmente zellfreier DNA (cfDNA), die von Tumoren ausgeschieden werden, und nutzt ML, um Unterschiede in der H\u00e4ufigkeit von Krebs- und Nicht-Krebs-Mutationen im gesamten Genom zu erkennen. H\u00f6here Werte, die das Modell ermittelt, deuten auf eine h\u00f6here Wahrscheinlichkeit hin, an Krebs zu erkranken. In Labortests wurde GEMINI auf Computertomographie-Bilder angewendet<\/p>","protected":false},"author":2,"featured_media":3801,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[203,274,105,101],"class_list":["post-3799","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-biotech","tag-cancer","tag-machine-learning","tag-medtech"],"yoast_head":"\nAI-powered blood test detects cancers in single DNA molecules | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/de\/2023\/08\/ai-powered-blood-test-detects-cancers-in-single-dna-molecules\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI-powered blood test detects cancers in single DNA molecules | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Researchers at the Johns Hopkins Kimmel Cancer Center are advancing a novel blood testing technology known as GEMINI (Genome-wide Mutational Incidence for Non-Invasive detection of cancer).\u00a0 By merging genome-wide sequencing of single DNA molecules discarded by tumors with machine learning (ML), the test may enable earlier detection of lung and other cancers. 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