GEO series

Anti-EGFR aptamer exhibits direct anti-cancer effects in NSCLC cells harboring EGFR L858R mutations

GSE259407 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2024/11/21 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 36 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: Lung cancerThis series is part of our curated briefing on it.
Samples: 36 samples: 12 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: Anti-EGFR aptamer exhibits direct anti-cancer effects in NSCLC cells harboring EGFR L858R mutationsNPJ precision oncology · 2024

Summary (written by the submitters)

Non-small cell lung cancer (NSCLC) lung adenocarcinoma (LUAD) is a leading cause of death worldwide. Activating mutations in the tyrosine kinase domain of the oncogene epidermal growth factor receptor (EGFR) are responsible for ~10-50% of all LUAD cases. Although EGFR tyrosine kinase inhibitors (TKIs) have been effective in prolonging NSCLC patient survival and quality of life, acquired resistance mechanisms and disease progression are inevitable.

Read the full summary ↓

Contemporary second- and third-line treatments, such as immunotherapy, remain ineffective for these patients, presenting a clear and unmet need for alternative or adjuvant therapeutics for the treatment of mutant EGFR positive NSCLC. Here we show that an anti-EGFR aptamer (EGFRapt) decreases viability of NSCLC cell lines harboring the L858R ± T790M mutation in EGFR but not cell lines harboring wild-type or exon 19 deletions. In a humanized xenograft mouse model, EGFRapt decreased tumor burden compared to controls when delivered intratumorally over multiple doses. To elucidate the mechanism by which EGFRapt exerts these effects, we examined kinase-dependent and kinase-independent mechanisms and found that it is cell line dependent, either inhibiting cellular proliferation or inducing cell death. Post hoc transcriptomics analysis comparing EGFRapt to control aptamer or vehicle validated these findings and provided additional mechanistic insights. Overall, these data establish that EGFRapt has direct anti-cancer activity in mutant EGFR positive NSCLC via targetable mechanisms that are independent of existing approaches and provide a foundation for further development of nucleic acid-based therapies that target EGFR.

Published in

Anti-EGFR aptamer exhibits direct anti-cancer effects in NSCLC cells harboring EGFR L858R mutations

Thomas BJ, Awan SZ, Joshi T et al. · NPJ precision oncology 2024 · PMID 39572699 · doi:10.1038/s41698-024-00758-9

This dataset

Open GSE259407 in finder → Find more human RNA-seq datasets → Lung 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 GSE259407_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 PRJNA1081432 and SRA study SRP492137. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39572699) ↗

Study design

12 conditions, mostly in triplicate

A549, C36, 24 h, ×3 A549, MinE07, 24 h, ×3 A549, Vehicle, 24 h, ×3 H1975, C36, 24 h, ×3 H1975, MinE07, 24 h, ×3 H1975, Vehicle, 24 h, ×3 H3255, C36, 24 h, ×3 H3255, MinE07, 24 h, ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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

GSM8115675 A549, C36, 24 h, rep1 A549, C36, 24 h,
GSM8115676 A549, C36, 24 h, rep2 A549, C36, 24 h,
GSM8115677 A549, C36, 24 h, rep3 A549, C36, 24 h,
GSM8115678 A549, MinE07, 24 h, rep1 A549, MinE07, 24 h,
GSM8115679 A549, MinE07, 24 h, rep2 A549, MinE07, 24 h,
GSM8115680 A549, MinE07, 24 h, rep3 A549, MinE07, 24 h,
GSM8115681 A549, Vehicle, 24 h, rep1 A549, Vehicle, 24 h,
GSM8115682 A549, Vehicle, 24 h, rep2 A549, Vehicle, 24 h,
GSM8115683 A549, Vehicle, 24 h, rep3 A549, Vehicle, 24 h,
GSM8115684 H1975, C36, 24 h, rep1 H1975, C36, 24 h,
GSM8115685 H1975, C36, 24 h, rep2 H1975, C36, 24 h,
GSM8115686 H1975, C36, 24 h, rep3 H1975, C36, 24 h,
GSM8115687 H1975, MinE07, 24 h, rep1 H1975, MinE07, 24 h,
GSM8115688 H1975, MinE07, 24 h, rep2 H1975, MinE07, 24 h,
GSM8115689 H1975, MinE07, 24 h, rep3 H1975, MinE07, 24 h,
GSM8115690 H1975, Vehicle, 24 h, rep1 H1975, Vehicle, 24 h,
GSM8115691 H1975, Vehicle, 24 h, rep2 H1975, Vehicle, 24 h,
GSM8115692 H1975, Vehicle, 24 h, rep3 H1975, Vehicle, 24 h,
GSM8115693 H3255, C36, 24 h, rep1 H3255, C36, 24 h,
GSM8115694 H3255, C36, 24 h, rep2 H3255, C36, 24 h,
GSM8115695 H3255, C36, 24 h, rep3 H3255, C36, 24 h,
GSM8115696 H3255, MinE07, 24 h, rep1 H3255, MinE07, 24 h,
GSM8115697 H3255, MinE07, 24 h, rep2 H3255, MinE07, 24 h,
GSM8115698 H3255, MinE07, 24 h, rep3 H3255, MinE07, 24 h,
GSM8115699 H3255, Vehicle, 24 h, rep1 H3255, Vehicle, 24 h,
GSM8115700 H3255, Vehicle, 24 h, rep2 H3255, Vehicle, 24 h,
GSM8115701 H3255, Vehicle, 24 h, rep3 H3255, Vehicle, 24 h,
GSM8115702 H820, C36, 24 h, rep1 H820, C36, 24 h,
GSM8115703 H820, C36, 24 h, rep2 H820, C36, 24 h,
GSM8115704 H820, C36, 24 h, rep3 H820, C36, 24 h,
GSM8115705 H820, MinE07, 24 h, rep1 H820, MinE07, 24 h,
GSM8115706 H820, MinE07, 24 h, rep2 H820, MinE07, 24 h,
GSM8115707 H820, MinE07, 24 h, rep3 H820, MinE07, 24 h,
GSM8115708 H820, Vehicle, 24 h, rep1 H820, Vehicle, 24 h,
GSM8115709 H820, Vehicle, 24 h, rep2 H820, Vehicle, 24 h,
GSM8115710 H820, Vehicle, 24 h, rep3 H820, Vehicle, 24 h,

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