Transcriptomics of cumulus cells – a window into oocyte maturation in humans
Bibliographic record
Abstract
BACKGROUND: Cumulus cells (CC) encapsulate growing oocytes and support their growth and development. Transcriptomic signatures of CC have the potential to serve as valuable non-invasive biomarkers for oocyte competency and potential. The present sibling cumulus-oocyte-complex (COC) cohort study aimed at defining functional variations between oocytes of different maturity exposed to the same stimulation conditions, by assessing the transcriptomic signatures of their corresponding CC. CC were collected from 18 patients with both germinal vesicle and metaphase II oocytes from the same cycle to keep the biological variability between samples to a minimum. RNA sequencing, differential expression, pathway analysis, and leading-edge were performed to highlight functional differences between CC encapsulating oocytes of different maturity. RESULTS: Transcriptomic signatures representing CC encapsulating oocytes of different maturity clustered separately on principal component analysis with 1818 genes differentially expressed. CCs encapsulating mature oocytes were more transcriptionally synchronized when compared with CCs encapsulating immature oocytes. Moreover, the transcriptional activity was lower, albeit not absent, in CC encapsulating mature oocytes, with 2407 fewer transcripts detected than in CC encapsulating immature (germinal vesicle - GV) oocytes. Hallmark pathways and ovarian processes that were affected by oocyte maturity included cell cycle regulation, steroid metabolism, apoptosis, extracellular matrix remodeling, and inflammation. CONCLUSIONS: Herein we review our findings and discuss how they align with previous literature addressing transcriptomic signatures of oocyte maturation. Our findings support the available literature and enhance it with several genes and pathways, which have not been previously implicated in promoting human oocyte maturation. This study lays the ground for future functional studies that can enhance our understanding of human oocyte maturation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".