Identification of Differentially Expressed Genes and Prognostic Biomarkers of Breast Cancer Based on RNA-Seq and KEGG Pathway Network
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
The incidence of breast cancer is a complex biological process and multiple genes involved in the regulation. The gene expression differences of tumor cells between different patients’ determine the different treatment and prognosis. Therefore investigate the characteristics changes of breast cancer from a genetic level include identification of differentially expressed genes and prognostic markers will facilitate the development of appropriate and effective treatment. This subject obtained RNA-Seq Level 3 gene expression data from TCGA database, SAM algorithm was used to find differentially expressed genes. Next, the DAVID bioinformatics tool was employed to analyze the function of these genes, and obtained the significantly enriched pathways of these genes. Then gene interaction information was extracted from the pathways, KEGG pathway network was built by integrating these information, and the network topology were analyzed. The hub nodes extracted from the network were as candidate genes. Then the genes which have a significant impact on the survival were identified by using Cox proportional hazards regression model. And these genes were introduced into a multivariate analysis, the sample risk scores were calculated, according to which samples were divided into a high risk group and a low risk group. The survival difference between these two groups was analyzed using Kaplan Meier method, and logrank test was used to assess the statistical significant. By analyzing the gene expression dataset of TCGA database, a total of 5880 differentially expressed genes were found. Eight significant pathways were obtained by enrichment analysis. Then we used the interaction information of genes extracted from the pathways to build a KEGG pathway network, and 32 candidate genes were obtained from the network. Three significant genes (AARS, ADK, and ADORA2A) which have significant impact on the prognosis of breast cancer were identified by Cox proportional hazards. These three genes can be used as new prognostic biomarkers in breast cancer, provide guidance for the treatment of breast cancer. Wherein AARS has been proven associated with breast cancer risk. By multivariate analysis, this subject divided breast cancer into a high risk group and a low risk group, and there exits significant difference between them.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle