GEO series
Trajectories and Influencing Factors of Psychological Distress in Nasopharyngeal Carcinoma Patients Receiving Radiotherapy (Incorporating Genetic Factors): A Multicenter Longitudinal Study
GSE303758
Homo sapiens (human)
Non-coding RNA profiling
24 samples
Submitted 2025/09/17
Platform GPL24676
At a glance
Non-coding RNA profiling · human · 24 samples
- What it is
- Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
- Organism
- Homo sapiens (human)
- Topic
- Nasopharyngeal carcinomaThis series is part of our curated briefing on it.
- Samples
- 24 samples: 24 samples, each with a distinct title — no replicated groupsGroups 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.
- Paper
- Trajectories and influencing factors of psychological distress in nasopharyngeal carcinoma patients receiving radiotherapy (incorporating genetic factors): a multicenter longitudinal studyFrontiers in oncology · 2025
Summary (written by the submitters)
Background: This multicenter longitudinal study seeks to investigate the dynamic changes of psychological distress (PD) in nasopharyngeal carcinoma (NPC) patients during radiotherapy, and reveal the expression profiles and regulatory networks of circRNAs in these NPC patients. Methods: 282 newly diagnosed NPC patients from three hospitals in China were included.
Read the full summary ↓
Participants completed questionnaires and provided blood samples. PD trajectories were identified via a latent class growth model (LCGM). Moreover, the factors that influence the PD trajectories were explored. Whole transcriptome sequencing was performed to investigate genetic factors. The real-time quantitative PCR was applied to validate circRNAs. We predicted the target mirnas, target Mrnas and target RNA-binding proteins (RBPs) of the top 10 malregulated circrnas. Subsequently, circRNA-miRNA-mRNA (ceRNA) and circRNA-RBP networks were constructed. In addition, the role of circRNA and target mRNA parent genes was predicted by KEGG and GO analysis. Results: LCGM identified two of the most important PD trajectories during radiotherapy in NPC patients: Class 1 “decline distress group” (11.0%) and Class 4 “rise distress group” (20.3%). Household monthly per capita income, coping strategies, and perceived social support emerged as important predictors of PD trajectories. Regarding genetic factors, 600 circRNAs and 123 miRNAs were identified as being significantly differentially expressed. Notably, hsa_circ_0004277 demonstrated significant differences between patients in the rise and decline distress groups (P < 0.01). ceRNA and RBP networks may influence the pathophysiology of PD in NPC patients undergoing radiotherapy. Conclusion: This study unraveled that PD trajectories in NPC patients during radiotherapy were heterogeneous, indicating the need for screening and timely interventions within this population. Furthermore, the expression patterns of ceRNA and circRNA–RBP networks and pathways related to these networks suggested a potential role of circRNAs in developing PD among NPC patients receiving radiotherapy.
Published in
Ning J, Huang J, Liao Y et al.
· Frontiers in oncology 2025
· PMID 40936698
· doi:10.3389/fonc.2025.1640266
This dataset
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.
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 GSE303758_RAW.tar (it can run to tens of gigabytes).
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.
Also filed as BioProject PRJNA1297625 and SRA study SRP603938. Searching any of these in the dataset finder brings you back here.
Study design
24 samples, each with a distinct title — no replicated groups
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 24 sample titles: 24 distinct titles with little repetition. 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
- GSM9135410 D1, On admission
- GSM9135411 TD1, After treatment
- GSM9135412 D2, On admission
- GSM9135413 TD2, After treatment
- GSM9135414 D3, On admission
- GSM9135415 TD3, After treatment
- GSM9135416 R1, On admission
- GSM9135417 TR1, After treatment
- GSM9135418 R2, On admission
- GSM9135419 TR2, After treatment
- GSM9135420 R3, On admission
- GSM9135421 TR3, After treatment
- GSM9135422 D1, On admission [miRNA-seq]
- GSM9135423 TD1, After treatment [miRNA-seq]
- GSM9135424 D2, On admission [miRNA-seq]
- GSM9135425 TD2, After treatment [miRNA-seq]
- GSM9135426 D3, On admission [miRNA-seq]
- GSM9135427 TD3, After treatment [miRNA-seq]
- GSM9135428 R1, On admission [miRNA-seq]
- GSM9135429 TR1, After treatment [miRNA-seq]
- GSM9135430 R2, On admission [miRNA-seq]
- GSM9135431 TR2, After treatment [miRNA-seq]
- GSM9135432 R3, On admission [miRNA-seq]
- GSM9135433 TR3, After treatment [miRNA-seq]
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- GSE53819 Genome-wide expressing profiling of nasopharyngeal carcinoma primary tumors versus non-cancerous nasopharyngeal tissues. 36 samples same disease briefing · shares nasopharyngeal
- GSE150825 Comprehensive single-cell sequencing reveals the stromal dynamics and tumor-specific characteristics in the microenvironment of nasopharyngeal carcinoma 35 samples same disease briefing · shares nasopharyngeal
Share this dataset
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.