The MHC I Immunopeptidome Is Moulded by the Transcriptome and Conceals a Tissue-Specific Signature.
Notice bibliographique
Résumé
Abstract Background: Cell surface MHC I molecules are associated with self peptides that are collectively referred to as the self MHC I immunopeptidome (sMII). The sMII plays vital roles: it shapes the repertoire of developing thymocytes, transmits survival signals to mature CD8 T cells, amplifies responses against intracellular pathogens, allows immunosurveillance of neoplastic cells, and influences mating preferences in mice. Despite the tremendous importance of the sMII, very little is known on its genesis and molecular composition. Methodology/Principal Findings: We developed a novel high-throughput mass spectrometry approach that yields an accurate definition of the nature and relative abundance of unlabeled peptides presented by MHC I molecules. Two major points emerged from a comprehensive analysis of the sMII of primary mouse thymocytes: the sMII is enriched in peptides derived from highly abundant transcripts; and the sMII conceals a tissue-specific signature that emanates from about 17% of genes represented in the sMII. We found that about 25% of MHC I-associated peptides were differentially expressed on normal versus neoplastic thymocytes. Remarkably, about half of those peptides derived from molecules implicated in neoplastic transformation. Integration of peptidomic and transcriptomic data unveiled that, in most cases, overexpression of MHC I peptides on cancer cells entailed posttranscriptional mechanisms. Finally, mice immunized against peptides overexpressed by 10 to ≥ 85 fold on cancer cells generated specific cytotoxic T-cell responses against malignant cells endogenously expressing the target epitope. Conclusion: High-throughput analysis and sequencing of MHC I-associated peptides yields unique insights into the genesis of the sMII in normal and neoplastic cells, and can be used to discover peptide targets for cancer immunotherapy. Furthermore, global portrayal of the sMII offers a novel perspective into how neoplastic transformation affects protein metabolism. Figure 1. Relative Quantification of Differentially Expressed MHC I peptides and Source mRNAs from Thymocytes and EL4 Cells (A) Volcano Plot representation illustrate MHC I peptides reproducibly detected across biological replicates (n = 3). Peptides over- and underexpressed on EL4 cells relative to thymocytes (p-values≤0.05; fold change ≥ 2.5) were highlighted in blue and red, respectively. MS-MS spectra of circled peptides are shown in B and C. B) Scatter plot shows the correlation between relative expression of mRNA and that of MHC I peptide. Expression ratios for source mRNA (x axis) and MHC I peptide (y axis) between EL4 cells and thymocytes were plotted on a log 2 scale for 47 pairs. A Spearman correlation coefficient was calculated from the linear regression. MHC I peptides overexpressed in EL4 cells or normal thymocytes are highlighted in blue and red, respectively; peptides that were not differentially expressed are in grey. Dashed box includes peptides whose overexpression on EL4 cells did not correlated with increased mRNA levels of their source protein. Figure 1. Relative Quantification of Differentially Expressed MHC I peptides and Source mRNAs from Thymocytes and EL4 Cells (A) Volcano Plot representation illustrate MHC I peptides reproducibly detected across biological replicates (n = 3). Peptides over- and underexpressed on EL4 cells relative to thymocytes (p-values≤0.05; fold change ≥ 2.5) were highlighted in blue and red, respectively. MS-MS spectra of circled peptides are shown in B and C. B) Scatter plot shows the correlation between relative expression of mRNA and that of MHC I peptide. Expression ratios for source mRNA (x axis) and MHC I peptide (y axis) between EL4 cells and thymocytes were plotted on a log 2 scale for 47 pairs. A Spearman correlation coefficient was calculated from the linear regression. MHC I peptides overexpressed in EL4 cells or normal thymocytes are highlighted in blue and red, respectively; peptides that were not differentially expressed are in grey. Dashed box includes peptides whose overexpression on EL4 cells did not correlated with increased mRNA levels of their source protein.
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 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».