GEO series

PRKDC Induces Chemoresistance in Osteosarcoma by Recruiting GDE2 to Stabilize GNAS and Activate AKT

GSE268415 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/06/14 Platform GPL24676

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: OsteosarcomaThis series is part of our curated briefing on it.
Samples: 12 samples: 3 × hos_siNC vs 3 × hos_si vs 3 × hos_zdk64NC vs 3 × hos_zdkGroups 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)

Chemoresistance is one of the major causes of poor prognosis in osteosarcoma. Thus far, the therapeutic alternative for osteosarcoma is quite limited, thereby increasing sensitivity of the currently used drugs is an effective way to improve outcome of patients. In this study, through a Kinome-wide CRISPR screen, we identified PRKDC as a critical determinant of Doxorubicin (DOX) sensitivity in osteosarcoma.

Read the full summary ↓

Clinical sample analysis and functional experiments demonstrated that PRKDC is hyperactivated in osteosarcoma and that knockdown of PRKDC significantly increased sensitivity of osteosarcoma to DOX. Mechanistically, PRKDC could recruit and bind with GDE2 to augment the stability of GNAS. The increased GNAS protein subsequently activate Akt S473 and T308 phosphorylation and mediated DOX sensitivity. We also showed that the PRKDC inhibitor AZD7648 and DOX could synergize with each other and intensely suppressed the growth of osteosarcoma in mice xenograft models and human organoids. In conclusion, these results revealed a novel PRKDC-GDE2-GNAS-Akt regulatory axis in DOX sensitivity and provided targetable candidates for improving therapeutic efficacy of DOX in osteosarcoma.

This dataset

Open GSE268415 in finder → Find more human RNA-seq datasets → Osteosarcoma 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 GSE268415_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 PRJNA1117062 and SRA study SRP510155. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × hos_siNC vs 3 × hos_si vs 3 × hos_zdk64NC vs 3 × hos_zdk

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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

GSM8290907 hos_siNC1 hos_siNC
GSM8290908 hos_siNC2 hos_siNC
GSM8290909 hos_siNC3 hos_siNC
GSM8290910 hos_si1 hos_si
GSM8290911 hos_si2 hos_si
GSM8290912 hos_si3 hos_si
GSM8290913 hos_zdk64NC1 hos_zdk64NC
GSM8290914 hos_zdk64NC2 hos_zdk64NC
GSM8290915 hos_zdk64NC3 hos_zdk64NC
GSM8290916 hos_zdk641501 hos_zdk
GSM8290917 hos_zdk641502 hos_zdk
GSM8290918 hos_zdk641503 hos_zdk

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Search all human RNA-seq datasets in GEO →

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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.