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Enregistrement W4394483675 · doi:10.6084/m9.figshare.24001741

Reveal the potential molecular mechanism of circRNA regulating immune-related mRNA through sponge miRNA in the occurrence and immune regulation of papillary thyroid cancer

2023· dataset· en· W4394483675 sur OpenAlexaff
Bo Wang, Wei Shen, Yan Li, Xiaoyu Li, Linlei Zhang, Suyuan Zhao, Xiao Jin

Notice bibliographique

RevueFigshare · 2023
Typedataset
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueCircular RNAs in diseases
Établissements canadiensVector InstituteUniversity of TorontoUniversity Health NetworkCanadian Institute for Advanced Research
Organismes subventionnairesnon disponible
Mots-clésmicroRNAImmune systemMechanism (biology)Thyroid cancerImmune escapeMessenger RNABiologyPapillary thyroid cancerCancer researchCancerComputational biologyImmunologyGeneGeneticsPhilosophy

Résumé

récupéré en direct d'OpenAlex

Papillary thyroid cancer (PTC) is the most common endocrine malignant tumour. The purpose of this study was to explore the potential molecular mechanism of circRNA regulating immune-related mRNA through sponge miRNA in the occurrence and immune regulation of PTC. All data were downloaded from public databases, such as GEO, Immport and TCGA. Differentially expressed (DE) mRNAs (DEmRNAs), DEmiRNAs and DEcircRNAs were identified using metaMA and limma packages. Subsequently, immune-related DEmRNAs were screened, and circRNA-miRNA-mRNA (ceRNA) regulatory network was constructed. In addition, functional annotation, protein-protein interaction (PPI) network construction, immune cell infiltration analysis and Pearson correlation analysis were performed. Finally, qRT-PCR validation and cell experiments were also performed. In total, 2962 DEmRNAs, 78 DEmiRNAs and 51 DEcircRNAs were obtained. Subsequently, 195 immune-related DEmRNAs were obtained based on Immport database. Cytokine-cytokine receptor interaction was the only signalling pathway obtained in KEGG analysis. Then, 8 hub immune-related DEmRNAs were identified based on PPI network and CytoHubba plug-in. Subsequently, ceRNA sub-network containing hub immune-related DEmRNAs was extracted from ceRNA regulatory network. In ceRNA sub-network, hsa_circ_0082182-hsa-miR-18b-5p-FGF1/PDGFC, hsa_circ_0016404-hsa-miR-1275-FGF1/CTSB/IL13RA1, hsa_circ_0070100-hsa-miR-27a-3p/hsa-miR-27b-3p-TGFBR3, hsa_circ_0060055/hsa_circ_0038718-hsa-miR-150-3p-CXCL14, hsa_circ_0030427/hsa_circ_0002917-hsa-miR-22-3p-BMP7 and hsa_circ_0030427/hsa_circ_0002917-hsa-miR-125a-5p-LIFR axes were identified. Moreover, FGF1, PDGFC, CTSB, IL13RA1, TGFBR3, CXCL14, BMP7, LIFR, hsa-miR-125a-5p, hsa-miR-1275, hsa-miR-150-3p, hsa-miR-18b-5p and hsa-miR-27b-3p were also found to have good diagnostic accuracy and may be potential novel diagnostic markers for PTC. XCell analysis showed that the levels of immune cell infiltration (including Tregs, HSC, DC and Monocytes) were significantly different between the PTC and the control groups. Knockdown of the expression of hsa_circ_0082182 significantly inhibits the activity, proliferation, migration and invasion of TPC-1 cells. Several circRNA-miRNA-mRNA axes identified in this study may be related to the occurrence, progression and survival of PTC. This lays a theoretical foundation for further understanding the molecular mechanism of PTC, and also contributes to clinical management and research. In ceRNA sub-network, hsa_circ_0082182-hsa-miR-18b-5p-FGF1/PDGFC, hsa_circ_0016404-hsa-miR-1275-FGF1/CTSB/IL13RA1, hsa_circ_0070100-hsa-miR-27a-3p/hsa-miR-27b-3p-TGFBR3, hsa_circ_0060055/hsa_circ_0038718-hsa-miR-150-3p-CXCL14, hsa_circ_0030427/hsa_circ_0002917-hsa-miR-22-3p-BMP7 and hsa_circ_0030427/hsa_circ_0002917-hsa-miR-125a-5p-LIFR axes were identified.FGF1, PDGFC, CTSB, IL13RA1, TGFBR3, CXCL14, BMP7, LIFR, hsa-miR-125a-5p, hsa-miR-1275, hsa-miR-150-3p, hsa-miR-18b-5p and hsa-miR-27b-3p were also found to have good diagnostic accuracy and may be potential novel diagnostic markers for PTC.Knockdown the expression of hsa_circ_0082182 significantly inhibits the activity, proliferation, migration and invasion of TPC-1 cell. In ceRNA sub-network, hsa_circ_0082182-hsa-miR-18b-5p-FGF1/PDGFC, hsa_circ_0016404-hsa-miR-1275-FGF1/CTSB/IL13RA1, hsa_circ_0070100-hsa-miR-27a-3p/hsa-miR-27b-3p-TGFBR3, hsa_circ_0060055/hsa_circ_0038718-hsa-miR-150-3p-CXCL14, hsa_circ_0030427/hsa_circ_0002917-hsa-miR-22-3p-BMP7 and hsa_circ_0030427/hsa_circ_0002917-hsa-miR-125a-5p-LIFR axes were identified. FGF1, PDGFC, CTSB, IL13RA1, TGFBR3, CXCL14, BMP7, LIFR, hsa-miR-125a-5p, hsa-miR-1275, hsa-miR-150-3p, hsa-miR-18b-5p and hsa-miR-27b-3p were also found to have good diagnostic accuracy and may be potential novel diagnostic markers for PTC. Knockdown the expression of hsa_circ_0082182 significantly inhibits the activity, proliferation, migration and invasion of TPC-1 cell.

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.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,527
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,015
Tête enseignante GPT0,267
Écart entre enseignants0,252 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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