{"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\/es\/2023\/08\/ai-powered-blood-test-detects-cancers-in-single-dna-molecules\/","title":{"rendered":"Un an\u00e1lisis de sangre basado en inteligencia artificial detecta c\u00e1nceres en mol\u00e9culas de ADN individuales"},"content":{"rendered":"

Investigadores del Johns Hopkins Kimmel Cancer Center est\u00e1n desarrollando una novedosa tecnolog\u00eda de an\u00e1lisis de sangre conocida como GEMINI (Genome-wide Mutational Incidence for Non-Invasive detection of cancer).\u00a0<\/b><\/p>\n

Al combinar la secuenciaci\u00f3n gen\u00f3mica de mol\u00e9culas individuales de ADN desechadas por los tumores con el aprendizaje autom\u00e1tico, la prueba podr\u00eda permitir la detecci\u00f3n precoz del c\u00e1ncer de pulm\u00f3n y otros tipos de c\u00e1ncer.<\/span><\/p>\n

La prueba GEMINI analiza los fragmentos de ADN libre de c\u00e9lulas (cfADN) que desprenden los tumores, utilizando ML para detectar diferencias en las frecuencias de mutaciones cancerosas y no cancerosas en todo el genoma. Las puntuaciones m\u00e1s altas generadas por el modelo sugieren una mayor probabilidad de padecer c\u00e1ncer.<\/span><\/p>\n

En pruebas de laboratorio, GEMINI se aplic\u00f3 a im\u00e1genes de tomograf\u00eda computerizada y detect\u00f3 m\u00e1s de 90% de c\u00e1nceres de pulm\u00f3n, incluso en estadios tempranos. El sitio <\/span>estudiar<\/span><\/a> se publicaron en Nature Genetics.\u00a0<\/span><\/p>\n

Los investigadores se centraron principalmente en la detecci\u00f3n del c\u00e1ncer de pulm\u00f3n en poblaciones de alto riesgo. <\/span><\/p>\n

Sin embargo, tambi\u00e9n se observaron perfiles mutacionales alterados en el cfDNA de pacientes con c\u00e1ncer de h\u00edgado, melanoma y linfoma, por lo que este enfoque podr\u00eda utilizarse en distintos tipos de c\u00e1ncer.\u00a0<\/span><\/p>\n

C\u00f3mo crearon GEMINI los investigadores<\/span><\/h2>\n

Para desarrollar GEMINI, el equipo estudi\u00f3 las secuencias gen\u00f3micas de 2.511 individuos de 25 tipos de c\u00e1ncer diferentes.\u00a0<\/span><\/p>\n

Los distintos tipos de tumor presentaban perfiles de mutaci\u00f3n diferentes. Los investigadores descubrieron que las regiones gen\u00f3micas con una elevada frecuencia de mutaci\u00f3n eran similares entre el tejido tumoral y el cfADN derivado de la sangre en pacientes con c\u00e1ncer de pulm\u00f3n, melanoma o linfoma no Hodgkin de c\u00e9lulas B.\u00a0<\/span><\/p>\n

A continuaci\u00f3n, la prueba GEMINI se aplic\u00f3 al cfDNA de 365 individuos con alto riesgo de c\u00e1ncer de pulm\u00f3n, obteni\u00e9ndose puntuaciones m\u00e1s altas en las personas con c\u00e1ncer que en las que no lo padec\u00edan.\u00a0<\/span><\/p>\n

Los investigadores tambi\u00e9n examinaron la integraci\u00f3n de GEMINI con una prueba anterior conocida como DELFI (evaluaci\u00f3n del ADN de fragmentos para la interceptaci\u00f3n precoz),<\/span><\/p>\n

En total, GEMINI y DELFI identificaron correctamente los c\u00e1nceres el 91% de las veces en 89 muestras.<\/span><\/p>\n

\"C\u00e1ncer
El aprendizaje autom\u00e1tico ayud\u00f3 a los investigadores a analizar los marcadores del c\u00e1ncer en las c\u00e9lulas. Fuente: Naturaleza<\/a>.<\/figcaption><\/figure>\n

Sorprendentemente, la prueba GEMINI detect\u00f3 anomal\u00edas en los perfiles de mutaci\u00f3n del cfADN a\u00f1os antes del diagn\u00f3stico est\u00e1ndar en siete pacientes sin tumores detectables en el momento de la extracci\u00f3n de sangre.\u00a0<\/span><\/p>\n

Seis dieron positivo en la prueba GEMINI y posteriormente se les diagnostic\u00f3 c\u00e1ncer de pulm\u00f3n entre 231 y 1.868 d\u00edas despu\u00e9s de la obtenci\u00f3n de las muestras.<\/span><\/p>\n

Desglose del estudio<\/span><\/h2>\n
    \n
  1. Muestras de sangre<\/b>: Se toma una muestra de sangre de una persona que podr\u00eda estar en riesgo de desarrollar c\u00e1ncer. Esta muestra contiene cfADN, fragmentos diminutos de ADN que han sido desprendidos por c\u00e9lulas del organismo, incluidas posibles c\u00e9lulas tumorales.<\/span><\/li>\n
  2. Extracci\u00f3n y secuenciaci\u00f3n del ADN<\/b>: El cfADN se extrae de la muestra de sangre y a continuaci\u00f3n se secuencia. Esto significa que los cient\u00edficos trazan el orden de los \"componentes b\u00e1sicos\" que componen el ADN. Esto les ayuda a identificar cualquier cambio o mutaci\u00f3n en el ADN.<\/span><\/li>\n
  3. An\u00e1lisis de las alteraciones del ADN<\/b>: Se analiza cada mol\u00e9cula de ADN individual para detectar cualquier alteraci\u00f3n de la secuencia, lo que permite a los investigadores trazar perfiles de mutaci\u00f3n en todo el genoma. En esencia, buscan patrones en las mutaciones que puedan sugerir la presencia de c\u00e1ncer.<\/span><\/li>\n
  4. Aprendizaje autom\u00e1tico<\/b>: Para analizar los perfiles de mutaci\u00f3n se utiliza un modelo de aprendizaje autom\u00e1tico que ha sido entrenado para reconocer la diferencia entre las frecuencias de mutaciones cancerosas y no cancerosas en diferentes \u00e1reas del genoma. El modelo de aprendizaje autom\u00e1tico da entonces una puntuaci\u00f3n que va de 0 a 1, donde una puntuaci\u00f3n m\u00e1s alta indica una mayor probabilidad de c\u00e1ncer.<\/span><\/li>\n
  5. Validaci\u00f3n y pruebas adicionales<\/b>: Si la puntuaci\u00f3n GEMINI es alta, lo que sugiere la presencia de c\u00e1ncer, se utilizan pruebas adicionales como la tomograf\u00eda computarizada y la prueba DELFI (que detecta cambios en el tama\u00f1o y la distribuci\u00f3n de los fragmentos de cfADN en el genoma) para confirmar el diagn\u00f3stico y detectar el estadio del c\u00e1ncer. Esta combinaci\u00f3n de pruebas ha demostrado ser muy eficaz, detectando m\u00e1s de 90% de c\u00e1nceres de pulm\u00f3n en el estudio.<\/span><\/li>\n<\/ol>\n

    Se trata de otro interesante estudio que revela la novedosa aplicaci\u00f3n del aprendizaje autom\u00e1tico al diagn\u00f3stico m\u00e9dico, esta vez analizando los c\u00e1nceres a nivel celular. <\/span><\/p>\n

    Se necesitan ensayos cl\u00ednicos m\u00e1s amplios para validar la herramienta antes de que pueda estar disponible para uso cl\u00ednico.<\/span><\/p>\n

    Esta semana, un Cribado del c\u00e1ncer de mama con ayuda de la IA<\/a> El flujo de trabajo mejor\u00f3 enormemente la rapidez y eficacia de la evaluaci\u00f3n de las mamograf\u00edas para detectar el c\u00e1ncer.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Investigadores del Johns Hopkins Kimmel Cancer Center est\u00e1n desarrollando una novedosa tecnolog\u00eda de an\u00e1lisis de sangre conocida como GEMINI (Genome-wide Mutational Incidence for Non-Invasive detection of cancer). Al combinar la secuenciaci\u00f3n gen\u00f3mica de mol\u00e9culas individuales de ADN desechadas por los tumores con el aprendizaje autom\u00e1tico, la prueba puede permitir la detecci\u00f3n precoz del c\u00e1ncer de pulm\u00f3n y otros tipos de c\u00e1ncer. La prueba GEMINI analiza fragmentos de ADN libre de c\u00e9lulas (cfADN) desechados por los tumores, utilizando el ML para detectar diferencias en las frecuencias de mutaciones cancerosas y no cancerosas en todo el genoma. Las puntuaciones m\u00e1s altas generadas por el modelo sugieren una mayor probabilidad de padecer c\u00e1ncer. En pruebas de laboratorio, GEMINI se aplic\u00f3 a im\u00e1genes de tomograf\u00eda computerizada<\/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\/es\/2023\/08\/ai-powered-blood-test-detects-cancers-in-single-dna-molecules\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\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. The GEMINI test analyzes cell-free DNA (cfDNA) fragments shed by tumors, using ML to detect differences in cancer and non-cancer mutation frequencies across the genome. Higher scores generated by the model suggest a higher probability of having cancer. 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