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Elevated VAMP8 Expression Promotes Cervical Cancer Progression by Enhancing Autophagy via HIF-1 Pathway

GSE306495 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/08/30 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 12 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)
Topic
Cervical cancerThis series is part of our curated briefing on it.
Samples
12 samples
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
Elevated VAMP8 expression promotes cervical cancer progression by enhancing autophagy via HIF-1 pathwayBMC medicine · 2025
Summary (written by the submitters)
Background: Cervical cancer, prevalent in low- and middle-income countries, is primarily caused by high-risk HPV16. Vesicle-Associated Membrane Protein 8 (VAMP8), involved in vesicle trafficking and autophagy, may influence HPV16-related cervical cancer progression. Methods: VAMP8 expression was evaluated in cervical tissue specimens from patients with HPV16-positive lesions (including low- and high-grade squamous intraepithelial lesions and cancer) and HPV-negative normal controls using proteomics, qPCR, and immunohistochemistry.
Read the full summary ↓
A Cox proportional hazards model for prognosis was developed using immunohistochemical data from a cohort of cervical cancer patients. The clinical significance of VAMP8 was further assessed using RNA-seq and clinical data from The Cancer Genome Atlas-Cervical Cancer (TCGA-CESC) cohort. The effects of VAMP8 on autophagy and tumor progression were examined in HPV16 E6/E7-immortalized cervical epithelial cells (Ect1/E6E7) and cervical cancer cell lines (SiHa, HeLa, C-33A) in vitro, and in a SiHa xenograft model in vivo. Transcriptomic analysis of Ect1/E6E7 and SiHa cells identified VAMP8-regulated pathways. Chromatin immunoprecipitation (ChIP) and dual-luciferase reporter assays in SiHa cells were used to confirm the regulation of the HIF-1 pathway. Results: VAMP8 was upregulated in HPV16-positive samples, particularly in low-grade squamous intraepithelial lesions (LSIL). Elevated VAMP8 correlated with poor survival outcomes and advanced tumor stages. VAMP8 enhanced autophagy and reduced proliferation and invasiveness in HPV16-positive cervical cells but increased in established cancer cell lines. In vivo, VAMP8 overexpression promoted tumor growth and autophagy. The HIF-1 pathway emerged as a key regulatory axis of VAMP8, enhancing hypoxic responses and angiogenesis. Conclusion: Elevated VAMP8 in HPV16-associated cervical cancer promotes tumor progression by enhancing autophagy via the HIF-1 pathway, suggesting its potential as a diagnostic and prognostic biomarker.
Published in
Elevated VAMP8 expression promotes cervical cancer progression by enhancing autophagy via HIF-1 pathway
Wang Y, Wu D, Gai J et al. · BMC medicine 2025 · PMID 41063209 · doi:10.1186/s12916-025-04378-3
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 GSE306495_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.

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 PRJNA1310981 and SRA study SRP612648. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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