Unveiling the molecular mechanisms of human platelet lysate in enhancing endometrial receptivity
Notice bibliographique
Résumé
STUDY QUESTION: Which biological pathways are modulated by primary human endometrial cells in response to in vitro treatment with non-autologous human platelet lysate (HPL)? SUMMARY ANSWER: HPL treatment stimulates endometrial growth and trophoblast attachment by activating cell proliferation, and modulating cell-cell signaling and extracellular matrix organization. WHAT IS KNOWN ALREADY: There is currently no standard therapy for recurrent implantation failure (RIF), and existing treatments have variable effectiveness and do not consistently improve clinical pregnancy rates. Intrauterine infusion of autologous platelet-rich plasma (aPRP), before embryo transfer, promotes endometrial growth and may be the most effective immunomodulatory intervention to significantly improving pregnancy outcomes in RIF patients. HPL is a commercially available, pooled, and cell debris-cleared derivative of PRP suitable for cell culture. STUDY DESIGN, SIZE, DURATION: Cross-sectional (control versus treatment) study including five non-RIF (control) patients and 18 RIF patients. The 18 RIF patients were categorized into two sub-groups: RIF and RIF including thin endometrium (TE). PARTICIPANTS/MATERIALS, SETTING, METHODS: Endometrial tissue was collected from pre-menopausal women (32-47 years of age) during routine biopsy procedures at the CReATe Fertility Centre, Toronto. Primary endometrial epithelial (EECs) and stromal cells (ESCs) were enzymatically isolated, cultured separately, and treated for 48 h with either serum-free media (SFM) as the untreated control, or SFM supplemented with 1% HPL (EECs), or 10% HPL (ESCs). Cell proliferation was assessed by metabolic assay and immunocytochemistry for Ki-67 expression. Following 48-h treatment, total RNA was isolated from untreated and treated cells to prepare pooled RNA libraries, which were then subjected to RNA sequencing (150 cycles paired-end). Differential gene expression was performed using the DESeq2 package and RStudio/R. Significant differentially expressed genes were determined with the following cut-off values: log2FoldChange >|2| and Padj <0.05. Pathway enrichment analysis was then performed with Enrichr (Reactome 2022 database) to identify enriched pathways. After 48-h treatment with SFM or HPL, a trophoblast attachment assay was also performed with fluorescently labeled HTR-8/SVneo trophoblast spheroids, where spheroids were seeded on top of pre-treated EEC monolayers for a 1-h incubation to allow for attachment. Fluorescent microscopy and ImageJ software were used to image and quantify the total number of seeded and attached spheroids. MAIN RESULTS AND THE ROLE OF CHANCE: Treatment with non-autologous HPL for 48 h significantly increased EEC proliferation by 1.24- to 1.49-fold (P < 0.05) in all groups. ESCs showed a significant proliferation increase of 1.29-fold in the proliferative phase RIF group and 1.92-fold in the secretory phase RIF+TE group (P < 0.05). HPL treatment upregulated 45 genes in EECs, including MMP1, MMP9, and ADAMTS18, while 378 genes were upregulated in ESCs, such as BUB1, CDK1, MKI67, and PLK1. Twenty-two common genes were significantly upregulated in both cell types. EECs had 30 downregulated genes, including KL and ADRA2A, while ESCs had 429 downregulated genes, such as PTGIS, PTGDS, and PTGES, with seven common genes downregulated in both cell types. Pathway enrichment analysis revealed that upregulated pathways in EECs included extracellular matrix organization and degradation, while ESCs showed enrichment in cell cycle (mitotic), cell cycle checkpoints, and extracellular matrix degradation. Downregulated pathways included receptor signaling of the fibroblast growth factor receptor 1 in EECs, prostaglandin synthesis in ESCs, and G-protein coupled receptor signaling in both cell types. HPL treatment also increased primary EEC attachment to trophoblast spheroids compared to the untreated control. This increased attachment was consistent in EECs from RIF patients, regardless of endometrial thickness, with a 26% increase (from 42.58% to 68.90%, P < 0.01) in RIF cultures and a significant 29% increase (from 57.52% to 86.5%, P < 0.01) in RIF+TE cultures. LARGE SCALE DATA: Raw sequencing and count data have been deposited under GEO accession number GSE279514. LIMITATIONS, REASONS FOR CAUTION: One limitation is the small sample size of primary human endometrial samples (N = 23), divided into four patient groups (N = 5-6 per group). Additionally, all participants were pre-menopausal women aged 32-47 years, most of whom fall into the advanced reproductive age category (>35 years), a group often recommended for infertility assessment after 6 months of unsuccessful conception attempts. Although our study utilized primary endometrial cells and indicates that HPL may be an effective treatment for RIF and TE, these in vitro findings need to be validated in vivo. While research from our group and others suggests that PRP and HPL contain a similar growth factor milieu, randomized controlled trials are necessary to evaluate and compare the efficacy of commercial HPL as a treatment alternative to aPRP. WIDER IMPLICATIONS OF THE FINDINGS: Our data provide the first detailed map of the signaling and extracellular-matrix programs that platelet derivatives activate in primary endometrial cells, offering a mechanistic bridge between the growing clinical use of platelet-rich plasma and its observed improvements in implantation. By clarifying which pathways (chiefly cell-cycle drivers, matrix remodeling enzymes, and intercellular signaling factors) are engaged, the study equips clinicians to refine treatment variables such as dose and timing, and highlights actionable biomarkers that could be monitored to verify a receptive endometrial response. At the scientific level, these insights shift the focus from empirical application to rational modulation of endometrial paracrine signaling, guiding the design of next-generation platelet formulations or synthetic analogs that replicate the same molecular signature with greater consistency and safety. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by the CReATe Fertility Centre.
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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 ».