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Transcriptomic analysis reveals Streptococcus agalactiae activation of oncogenic pathways in cervical adenocarcinoma

GSE264492 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2024/09/18 Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 24 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
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
Transcriptomic analysis reveals Streptococcus agalactiae activation of oncogenic pathways in cervical adenocarcinomaOncology letters · 2024
Summary (written by the submitters)
Cervical adenocarcinoma (AC), a subtype of uterine cervical cancer (CC), poses a challenge due to its resistance to therapy and poor prognosis compared with squamous cervical carcinoma. Streptococcus agalactiae [group B Streptococcus (GBS)], a Gram-positive coccus, has been associated with cervical intraepithelial neoplasia in CC. However, the underlying mechanism interaction between GBS and CC, particularly AC, remains elusive.
Read the full summary ↓
Leveraging The Cancer Genome Atlas public data and time-series transcriptomic data, the present study investigated the interaction between GBS and AC, revealing activation of two pivotal pathways: ‘MAPK signaling pathway’ and ‘mTORC1 signaling’. Western blotting, reverse transcription-quantitative PCR and cell viability assays were performed to validate the activation of these pathways and their role in promoting cancer cell proliferation. Subsequently, the present study evaluated the efficacy of two anticancer drugs targeting these pathways (binimetinib and ridaforolimus) in AC cell treatment. Binimetinib demonstrated a cytostatic effect, while ridaforolimus had a modest impact on HeLa cells after 48 h of treatment, as observed in both cell viability and cytotoxicity assays. The combination of binimetinib and ridaforolimus resulted in a significantly greater cytotoxic effect compared to monotherapy, even though the synergy score indicated an additive effect. Furthermore, this drug combination may enhance the effect on HeLa cells exposed to GBS compared to those without exposure. In general, the MAPK and mTORC1 signaling pathways were identified as the main pathways associated with GBS and AC cells. The combination of binimetinib and ridaforolimus could be a potential AC treatment.
Published in
Transcriptomic analysis reveals Streptococcus agalactiae activation of oncogenic pathways in cervical adenocarcinoma
Nguyen HDT, Le TM, Jung DR et al. · Oncology letters 2024 · PMID 39411203 · doi:10.3892/ol.2024.14720
This dataset
Open GSE264492 in finder → Find more human RNA-seq datasets → Cervical cancer landscape →
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 GSE264492_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 PRJNA1102704 and SRA study SRP503023. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39411203) ↗
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
More Cervical cancer datasets

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