{"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\/it\/2023\/08\/ai-powered-blood-test-detects-cancers-in-single-dna-molecules\/","title":{"rendered":"Un test del sangue alimentato dall'intelligenza artificiale rileva i tumori in singole molecole di DNA"},"content":{"rendered":"

I ricercatori del Johns Hopkins Kimmel Cancer Center stanno portando avanti una nuova tecnologia di analisi del sangue nota come GEMINI (Genome-wide Mutational Incidence for Non-Invasive detection of cancer).\u00a0<\/b><\/p>\n

Unendo il sequenziamento dell'intero genoma di singole molecole di DNA scartate dai tumori con l'apprendimento automatico (ML), il test potrebbe consentire di individuare pi\u00f9 precocemente i tumori del polmone e altri tipi di cancro.<\/span><\/p>\n

Il test GEMINI analizza i frammenti di DNA libero da cellule (cfDNA) rilasciati dai tumori, utilizzando il metodo ML per rilevare le differenze nelle frequenze di mutazioni tumorali e non tumorali nel genoma. I punteggi pi\u00f9 alti generati dal modello suggeriscono una maggiore probabilit\u00e0 di avere un cancro.<\/span><\/p>\n

Nei test di laboratorio, GEMINI \u00e8 stato applicato alle immagini della tomografia computerizzata e ha individuato oltre 90% di tumori polmonari, anche in fase iniziale. Il <\/span>studio<\/span><\/a> I risultati sono stati pubblicati su Nature Genetics.\u00a0<\/span><\/p>\n

I ricercatori si sono concentrati soprattutto sull'individuazione del cancro al polmone nelle popolazioni ad alto rischio. <\/span><\/p>\n

Tuttavia, sono stati osservati profili mutazionali alterati anche nel cfDNA di pazienti con cancro al fegato, melanoma e linfoma, per cui questo approccio potrebbe essere utilizzato in diversi tipi di cancro.\u00a0<\/span><\/p>\n

Come i ricercatori hanno creato GEMINI<\/span><\/h2>\n

Per sviluppare GEMINI, il team ha studiato le sequenze genomiche di 2.511 individui in 25 diversi tipi di cancro.\u00a0<\/span><\/p>\n

I diversi tipi di tumore presentavano profili di mutazione diversi. I ricercatori hanno scoperto che le regioni genomiche con un'alta frequenza di mutazioni erano simili tra il tessuto tumorale e il cfDNA derivato dal sangue in pazienti con cancro al polmone, melanoma o linfoma non-Hodgkin a cellule B.\u00a0<\/span><\/p>\n

Il test GEMINI \u00e8 stato poi applicato al cfDNA di 365 individui ad alto rischio di cancro ai polmoni, ottenendo punteggi pi\u00f9 alti nelle persone con cancro rispetto a quelle senza.\u00a0<\/span><\/p>\n

I ricercatori hanno anche esaminato l'integrazione di GEMINI con un test precedente noto come DELFI (valutazione del DNA dei frammenti per l'intercettazione precoce),<\/span><\/p>\n

In totale, GEMINI e DELFI hanno identificato correttamente i tumori nel 91% dei casi in 89 campioni.<\/span><\/p>\n

\"Cancro
L'apprendimento automatico ha aiutato i ricercatori ad analizzare i marcatori tumorali nelle cellule. Fonte: Natura<\/a>.<\/figcaption><\/figure>\n

In particolare, il test GEMINI ha rilevato anomalie nei profili di mutazione del cfDNA anni prima delle diagnosi standard in sette pazienti senza tumori rilevabili al momento del prelievo di sangue.\u00a0<\/span><\/p>\n

Sei sono risultati positivi al test GEMINI e in seguito hanno ricevuto una diagnosi di cancro ai polmoni da 231 a 1.868 giorni dopo il prelievo dei campioni.<\/span><\/p>\n

Ripartizione dello studio<\/span><\/h2>\n
    \n
  1. Campione di sangue<\/b>: Un campione di sangue viene prelevato da una persona che potrebbe essere a rischio di sviluppare un cancro. Questo campione contiene cfDNA, piccoli frammenti di DNA rilasciati dalle cellule del corpo, comprese quelle potenzialmente tumorali.<\/span><\/li>\n
  2. Estrazione e sequenziamento del DNA<\/b>: Il cfDNA viene estratto dal campione di sangue e poi sequenziato. Ci\u00f2 significa che gli scienziati tracciano l'ordine dei \"mattoni\" che compongono il DNA. Questo aiuta a identificare eventuali cambiamenti o mutazioni del DNA.<\/span><\/li>\n
  3. Analisi delle alterazioni del DNA<\/b>: Ogni singola molecola di DNA viene analizzata per individuare eventuali alterazioni della sequenza, consentendo ai ricercatori di tracciare i profili di mutazione dell'intero genoma. In sostanza, cercano schemi nelle mutazioni che possano suggerire la presenza di un cancro.<\/span><\/li>\n
  4. Apprendimento automatico<\/b>: Un modello di apprendimento automatico, addestrato a riconoscere la differenza tra le frequenze di mutazioni cancerose e non cancerose in diverse aree del genoma, viene quindi utilizzato per analizzare i profili di mutazione. Il modello di apprendimento automatico assegna quindi un punteggio che va da 0 a 1, dove un punteggio pi\u00f9 alto indica una maggiore probabilit\u00e0 di cancro.<\/span><\/li>\n
  5. Ulteriori convalide e test<\/b>Se il punteggio GEMINI \u00e8 elevato e suggerisce la presenza di un tumore, per confermare la diagnosi e individuare lo stadio del tumore si ricorre a test aggiuntivi come la tomografia computerizzata per immagini e il test DELFI (che rileva i cambiamenti nelle dimensioni e nella distribuzione dei frammenti di cfDNA nel genoma). Questa combinazione di test si \u00e8 dimostrata molto efficace, rilevando oltre 90% di tumori polmonari nello studio.<\/span><\/li>\n<\/ol>\n

    Si tratta di un altro studio intrigante che rivela la nuova applicazione dell'apprendimento automatico alla diagnostica medica, questa volta analizzando i tumori a livello cellulare. <\/span><\/p>\n

    Sono necessari studi clinici pi\u00f9 ampi per convalidare lo strumento prima che possa essere disponibile per l'uso clinico.<\/span><\/p>\n

    Questa settimana, un Screening del cancro al seno supportato dall'AI<\/a> Il flusso di lavoro ha migliorato notevolmente la velocit\u00e0 e l'efficienza della valutazione delle mammografie per individuare eventuali tumori.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    I ricercatori del Johns Hopkins Kimmel Cancer Center stanno portando avanti una nuova tecnologia di analisi del sangue nota come GEMINI (Genome-wide Mutational Incidence for Non-Invasive detection of cancer). Unendo il sequenziamento del genoma di singole molecole di DNA scartate dai tumori con l'apprendimento automatico (ML), il test pu\u00f2 consentire di individuare pi\u00f9 precocemente i tumori del polmone e altri tipi di cancro. Il test GEMINI analizza i frammenti di DNA libero da cellule (cfDNA) scartati dai tumori, utilizzando il metodo di apprendimento automatico per rilevare le differenze nelle frequenze di mutazioni tumorali e non tumorali nel genoma. I punteggi pi\u00f9 alti generati dal modello suggeriscono una maggiore probabilit\u00e0 di avere il cancro. Nei test di laboratorio, GEMINI \u00e8 stato applicato alle immagini di tomografia computerizzata.<\/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\/it\/2023\/08\/ai-powered-blood-test-detects-cancers-in-single-dna-molecules\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\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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