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Precise hourly personalized embryo transfer significantly improves clinical outcomes in patients with repeated implantation failure

GSE245473 Homo sapiens (human) RNA-seq (gene expression) 115 samples Submitted 2025/10/01 Platform GPL30209Platform GPL21697
At a glance

RNA-seq (gene expression) · human · 115 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
115 samples: 115 × P+5 endometrium tissue in RIF patientGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
This was a retrospective study enrolling patients with a history of RIF who received at least one autologous high-quality blastocyst during the subsequent FET cycle. Patients were divided into two groups: Group rsERT, comprising patients who underwent rsERT-guided pET (n=115), and Group FET, comprising patients who underwent standard FET without rsERT (n=272).
Read the full summary ↓
Of the patients who underwent rsERT, 39.1% (45/115) were receptive, and 60.9% (70/115) were non-receptive. Group rsERT patients showed a significantly higher probability of achieving both a positive human chorionic gonadotropin rate (63.5% vs. 51.5%, P=0.03) and clinical pregnancy rate (54.8% vs. 38.6%, P=0.003). In the subgroup analysis, Group rsERT patients with non-receptive results showed a significantly higher clinical pregnancy rate than patients in Group FET (58.6% vs. 38.6%, P=0.003). Furthermore, Group rsERT patients with receptive results guided by rsERT with a precise window-of-implantation time showed a higher clinical pregnancy rate (48.9% vs. 38.6%, P=0.192) compared with patients who underwent standard-time FET, although the difference was not significant. Hourly precise rsERT can significantly improve the probability of achieving clinical pregnancy in patients with RIF, especially in those with non-receptive rsERT results.
This dataset
Open GSE245473 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE245473_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1028561 and SRA study SRP466578. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
115 × P+5 endometrium tissue in RIF patient

Supports a between-group comparison across 115 samples.

How we read this: 1 replicated groups read from 115 sample titles; they account for 115 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 75 more — browse all 115 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.