GEO series

Overexpression of RNA polymerase I specific SL1 component TAF1C induces cancer-specific gene expression in BEAS-2B cells

GSE198601 Homo sapiens (human) Non-coding RNA profiling 10 samples Submitted 2025/03/11 Platform GPL20795Platform GPL16791

At a glance

Non-coding RNA profiling · human · 10 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)
Samples: 10 samples: 3 × TAF1C vs 3 × smallRNA_TAF1C vs 2 × eV vs 2 × smallRNA_eVGroups 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)

Purpose: Hyperactive RNA Polymerase I (Pol I) transcription and the upregulation of proteins essential for the initiation of Pol I transcription are the common features of a wide range of cancers . However, the role of Pol I transcription in the etiology of cancer remains unclear. Here, we activated Pol I transcription by overexpressing SL1 subunit TAF1C, and performed whole transcriptome analysis by RNA-Seq.

Read the full summary ↓

Methods: Non-cancerous lung epithelial BEAS-2B cellswere transfected with empty vector (eV) and TAF1C expression vector (TAF1C) to generate stable cell lines. Total RNA was isolated from biological triplicates of eV and TAF1C BEAS-2B stable cells and used for RNA sequencing on Illumina platform. Results: The whole transcriptomics data revealed the upregulation of cancer related genes in BEAS-2B cells stably expressing TAF1C gene. Integration of whole transcriptome data revealed interactive regulatory networks between protein-coding RNAs, lncRNAs and miRNAs associated with various hallmarks of cancer. Conclusions: For the first time, we provide evidence for the global gene expression changes in response to activated Pol I transcription in the context of cancer. The regulatory networks identified in the study can further be validated as potential drug targets for cancer therapeutics

This dataset

Open GSE198601 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 GSE198601_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 ↗

Also filed as BioProject PRJNA816102 and SRA study SRP364010. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × TAF1C vs 3 × smallRNA_TAF1C vs 2 × eV vs 2 × smallRNA_eV

Supports a between-group comparison across 10 samples.

How we read this: 4 replicated groups read from 10 sample titles; they account for 10 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

GSM5953358 eV_1 eV
GSM5953359 eV_2 eV
GSM5953360 TAF1C_1 TAF1C
GSM5953361 TAF1C_2 TAF1C
GSM5953362 TAF1C_3 TAF1C
GSM5953363 smallRNA_eV_1 smallRNA_eV
GSM5953364 smallRNA_eV_2 smallRNA_eV
GSM5953365 smallRNA_TAF1C_1 smallRNA_TAF1C
GSM5953366 smallRNA_TAF1C_2 smallRNA_TAF1C
GSM5953367 smallRNA_TAF1C_3 smallRNA_TAF1C

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