{"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\/pt\/2023\/08\/ai-powered-blood-test-detects-cancers-in-single-dna-molecules\/","title":{"rendered":"Teste sangu\u00edneo alimentado por IA detecta cancros em mol\u00e9culas individuais de ADN"},"content":{"rendered":"

Os investigadores do Johns Hopkins Kimmel Cancer Center est\u00e3o a desenvolver uma nova tecnologia de an\u00e1lise ao sangue conhecida como GEMINI (Genome-wide Mutational Incidence for Non-Invasive detection of cancer).\u00a0<\/b><\/p>\n

Ao combinar a sequencia\u00e7\u00e3o de todo o genoma de mol\u00e9culas individuais de ADN eliminadas pelos tumores com a aprendizagem autom\u00e1tica (ML), o teste pode permitir a dete\u00e7\u00e3o precoce do cancro do pulm\u00e3o e de outros cancros.<\/span><\/p>\n

O teste GEMINI analisa fragmentos de ADN livre de c\u00e9lulas (cfDNA) libertados por tumores, utilizando o ML para detetar diferen\u00e7as nas frequ\u00eancias de muta\u00e7\u00f5es cancer\u00edgenas e n\u00e3o cancer\u00edgenas no genoma. As pontua\u00e7\u00f5es mais elevadas geradas pelo modelo sugerem uma maior probabilidade de ter cancro.<\/span><\/p>\n

Em testes de laborat\u00f3rio, o GEMINI foi aplicado a imagens de tomografia computorizada e detectou mais de 90% de cancros do pulm\u00e3o, mesmo em fases iniciais. O <\/span>estudo<\/span><\/a> Os resultados foram publicados na revista Nature Genetics.\u00a0<\/span><\/p>\n

Os investigadores concentraram-se principalmente na dete\u00e7\u00e3o do cancro do pulm\u00e3o em popula\u00e7\u00f5es de alto risco. <\/span><\/p>\n

No entanto, foram tamb\u00e9m observados perfis mutacionais alterados no cfDNA de doentes com cancro do f\u00edgado, melanoma e linfoma, pelo que esta abordagem pode ser utilizada em diferentes tipos de cancro.\u00a0<\/span><\/p>\n

Como os investigadores criaram o GEMINI<\/span><\/h2>\n

Para desenvolver o GEMINI, a equipa estudou as sequ\u00eancias gen\u00f3micas de 2511 indiv\u00edduos de 25 cancros diferentes.\u00a0<\/span><\/p>\n

Diferentes tipos de tumores apresentavam diferentes perfis de muta\u00e7\u00e3o. Os investigadores descobriram que as regi\u00f5es gen\u00f3micas com uma elevada frequ\u00eancia de muta\u00e7\u00e3o eram semelhantes entre o tecido tumoral e o cfDNA derivado do sangue em doentes com cancro do pulm\u00e3o, melanoma ou linfoma n\u00e3o-Hodgkin de c\u00e9lulas B.\u00a0<\/span><\/p>\n

O teste GEMINI foi ent\u00e3o aplicado ao cfDNA de 365 indiv\u00edduos com elevado risco de cancro do pulm\u00e3o, produzindo pontua\u00e7\u00f5es mais elevadas em pessoas com cancro do que naquelas sem cancro.\u00a0<\/span><\/p>\n

Os investigadores examinaram tamb\u00e9m a integra\u00e7\u00e3o do GEMINI com um teste anterior conhecido como DELFI (avalia\u00e7\u00e3o do ADN de fragmentos para interce\u00e7\u00e3o precoce),<\/span><\/p>\n

No total, GEMINI e DELFI identificaram corretamente os cancros em 91% das vezes em 89 amostras.<\/span><\/p>\n

\"ML
A aprendizagem autom\u00e1tica ajudou os investigadores a analisar os marcadores de cancro nas c\u00e9lulas. Fonte: Natureza<\/a>.<\/figcaption><\/figure>\n

De forma not\u00e1vel, o teste GEMINI detectou anomalias nos perfis de muta\u00e7\u00e3o do cfDNA anos antes dos diagn\u00f3sticos padr\u00e3o em sete doentes sem tumores detect\u00e1veis na altura da colheita de sangue.\u00a0<\/span><\/p>\n

Seis apresentaram resultados positivos com o teste GEMINI e foram posteriormente diagnosticados com cancro do pulm\u00e3o, entre 231 e 1868 dias ap\u00f3s a obten\u00e7\u00e3o das amostras.<\/span><\/p>\n

Reparti\u00e7\u00e3o do estudo<\/span><\/h2>\n
    \n
  1. Colheita de sangue<\/b>: \u00c9 recolhida uma amostra de sangue de uma pessoa que pode estar em risco de desenvolver cancro. Esta amostra cont\u00e9m cfDNA, pequenos fragmentos de ADN que foram libertados pelas c\u00e9lulas do organismo, incluindo eventuais c\u00e9lulas tumorais.<\/span><\/li>\n
  2. Extra\u00e7\u00e3o e sequencia\u00e7\u00e3o de ADN<\/b>: O cfDNA \u00e9 extra\u00eddo da amostra de sangue e depois sequenciado. Isto significa que os cientistas mapeiam a ordem dos \"blocos de constru\u00e7\u00e3o\" que constituem o ADN. Isto ajuda-os a identificar quaisquer altera\u00e7\u00f5es ou muta\u00e7\u00f5es no ADN.<\/span><\/li>\n
  3. An\u00e1lise das altera\u00e7\u00f5es do ADN<\/b>: Cada mol\u00e9cula de ADN \u00e9 analisada individualmente para detetar altera\u00e7\u00f5es na sequ\u00eancia, o que permite aos investigadores tra\u00e7ar perfis de muta\u00e7\u00e3o em todo o genoma. Essencialmente, est\u00e3o \u00e0 procura de padr\u00f5es nas muta\u00e7\u00f5es que possam sugerir a presen\u00e7a de cancro.<\/span><\/li>\n
  4. Aprendizagem autom\u00e1tica<\/b>: Um modelo de aprendizagem autom\u00e1tica, que foi treinado para reconhecer a diferen\u00e7a entre as frequ\u00eancias de muta\u00e7\u00f5es cancer\u00edgenas e n\u00e3o cancer\u00edgenas em diferentes \u00e1reas do genoma, \u00e9 ent\u00e3o utilizado para analisar os perfis de muta\u00e7\u00e3o. O modelo de aprendizagem autom\u00e1tica atribui ent\u00e3o uma pontua\u00e7\u00e3o que varia entre 0 e 1, em que uma pontua\u00e7\u00e3o mais elevada indica uma maior probabilidade de cancro.<\/span><\/li>\n
  5. Valida\u00e7\u00e3o e ensaios adicionais<\/b>: Se a pontua\u00e7\u00e3o GEMINI for elevada, sugerindo a presen\u00e7a de cancro, s\u00e3o utilizados testes adicionais como a tomografia computorizada e o teste DELFI (que detecta altera\u00e7\u00f5es no tamanho e na distribui\u00e7\u00e3o dos fragmentos de cfDNA no genoma) para confirmar o diagn\u00f3stico e detetar o est\u00e1dio do cancro. Esta combina\u00e7\u00e3o de testes revelou-se muito eficaz, detectando mais de 90% de cancros do pulm\u00e3o no estudo.<\/span><\/li>\n<\/ol>\n

    Este \u00e9 mais um estudo intrigante que revela a nova aplica\u00e7\u00e3o da aprendizagem autom\u00e1tica ao diagn\u00f3stico m\u00e9dico, desta vez analisando os cancros a n\u00edvel celular. <\/span><\/p>\n

    S\u00e3o necess\u00e1rios ensaios cl\u00ednicos de maior dimens\u00e3o para validar a ferramenta antes de esta poder ser disponibilizada para utiliza\u00e7\u00e3o cl\u00ednica.<\/span><\/p>\n

    Esta semana, um Rastreio do cancro da mama apoiado por IA<\/a> O fluxo de trabalho melhorou consideravelmente a velocidade e a efici\u00eancia da avalia\u00e7\u00e3o das mamografias para dete\u00e7\u00e3o de cancro.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Investigadores do Johns Hopkins Kimmel Cancer Center est\u00e3o a desenvolver uma nova tecnologia de an\u00e1lise ao sangue conhecida como GEMINI (Genome-wide Mutational Incidence for Non-Invasive detection of cancer). Ao combinar a sequencia\u00e7\u00e3o de todo o genoma de mol\u00e9culas de ADN descartadas pelos tumores com a aprendizagem autom\u00e1tica (ML), o teste pode permitir a dete\u00e7\u00e3o precoce do cancro do pulm\u00e3o e de outros cancros. O teste GEMINI analisa fragmentos de ADN sem c\u00e9lulas (cfDNA) eliminados pelos tumores, utilizando a aprendizagem autom\u00e1tica para detetar diferen\u00e7as nas frequ\u00eancias de muta\u00e7\u00f5es cancer\u00edgenas e n\u00e3o cancer\u00edgenas em todo o genoma. As pontua\u00e7\u00f5es mais elevadas geradas pelo modelo sugerem uma maior probabilidade de ter cancro. Em testes de laborat\u00f3rio, o GEMINI foi aplicado a imagens de tomografia computorizada<\/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\/pt\/2023\/08\/ai-powered-blood-test-detects-cancers-in-single-dna-molecules\/\" \/>\n<meta property=\"og:locale\" content=\"pt_PT\" \/>\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. In lab tests, GEMINI was applied to computerized tomography images\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/pt\/2023\/08\/ai-powered-blood-test-detects-cancers-in-single-dna-molecules\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2023-08-04T17:59:22+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-08-04T18:05:23+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2023\/08\/shutterstock_1176407548.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1000\" \/>\n\t<meta property=\"og:image:height\" content=\"563\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Sam Jeans\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DailyAIOfficial\" \/>\n<meta name=\"twitter:site\" content=\"@DailyAIOfficial\" \/>\n<meta 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