GEO series

Inhibition of miR-10b treats metastatic breast cancer by targeting stem cell-like properties

GSE270229 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/09/03 Platform GPL24247Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 18 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: Breast cancerThis series is part of our curated briefing on it.
Samples: 18 samples: 6 conditions, mostly in triplicateGroups 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: Inhibition of miR-10b treats metastatic breast cancer by targeting stem cell-like propertiesOncotarget · 2024

Summary (written by the submitters)

Despite advances in breast cancer screening and treatment, prognosis for metastatic disease remains dismal at 30% five-year survival. This is due, in large, to the failure of current therapeutics to target properties unique to metastatic cells. One of the drivers of metastasis is miR-10b, a small noncoding RNA implicated in cancer cell invasion, migration, viability, and proliferation.

Read the full summary ↓

We have developed a nanodrug termed MN-anti-miR10b that delivers anti-miR10b antisense oligomers to cancer cells. In mouse models of metastatic triple-negative breast cancer, MN-anti-miR10b has been shown to prevent onset of metastasis and eliminate existing metastasis in combination with chemotherapy even after treatment has been stopped. Recent studies have implicated miR-10b in conferring stem cell-like properties onto cancer cells, such as chemoresistance. In this study, we show transcriptional evidence that inhibition of miR-10b with MN-anti-miR10b activates developmental processes in cancer cells and that stem-like cancer cells have increased miR-10b expression. We then demonstrate that treatment of breast cancer cells with MN-anti-miR10b reduces their stemness confirming that these properties make metastatic cells susceptible to the nanodrug actions. Collectively, these findings indicate that inhibition of miR-10b functions to impair breast cancer cell stemness, positioning MN-anti-miR10b as an effective treatment option for stem-like breast cancer subtypes.

Published in

Inhibition of miR-10b treats metastatic breast cancer by targeting stem cell-like properties

Halim A, Al-Qadi N, Kenyon E et al. · Oncotarget 2024 · PMID 39189967 · doi:10.18632/oncotarget.28641

This dataset

Open GSE270229 in finder → Find more RNA-seq datasets → Breast 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 GSE270229_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 PRJNA1125448 and SRA study SRP514734. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39189967) ↗

Study design

6 conditions, mostly in triplicate

231_MN ×3 231_MN_Anti10b ×3 231_NTC ×3 4T1_MN ×3 4T1_MN_Anti10b ×3 4T1_NTC ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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

GSM8337526 231_MN_1 231_MN
GSM8337527 231_MN_2 231_MN
GSM8337528 231_MN_3 231_MN
GSM8337529 231_MN_Anti10b_1 231_MN_Anti10b
GSM8337530 231_MN_Anti10b_2 231_MN_Anti10b
GSM8337531 231_MN_Anti10b_3 231_MN_Anti10b
GSM8337532 231_NTC_1 231_NTC
GSM8337533 231_NTC_2 231_NTC
GSM8337534 231_NTC_3 231_NTC
GSM8337535 4T1_MN_1 4T1_MN
GSM8337536 4T1_MN_2 4T1_MN
GSM8337537 4T1_MN_3 4T1_MN
GSM8337538 4T1_MN_Anti10b_1 4T1_MN_Anti10b
GSM8337539 4T1_MN_Anti10b_2 4T1_MN_Anti10b
GSM8337540 4T1_MN_Anti10b_3 4T1_MN_Anti10b
GSM8337541 4T1_NTC_1 4T1_NTC
GSM8337542 4T1_NTC_2 4T1_NTC
GSM8337543 4T1_NTC_3 4T1_NTC

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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.