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NINJ2 inhibition increased chemo-sensitivity by decreasing CICs in chemotherapy-resistant gastric cancer 

GSE171054 Homo sapiens (human) RNA-seq (gene expression) 2 samples Submitted 2024/03/29 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 2 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
Gastric cancerThis series is part of our curated briefing on it.
Samples
2 samples
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)
One of the first-line chemotherapy regimes for gastric cancer is a combination treatment of epirubicin, cisplatin, and 5-fluorouracil (ECF). Chemoresistance remains the major obstacle to achieving successful results from gastric cancer treatment. Understanding acquired or pre-existing resistance to anticancer drugs is essential to the development of a therapeutic modality for gastric cancer.
Read the full summary ↓
In this study, we established ECF-resistant (ECF-R) gastric cancer cell lines. We found that nerve injury–induced protein 2 (Ninjurin2, NINJ2) functioned as a biomarker for ECF-R in both gastric cancer cells. We also investigated the NINJ2 binding molecule and downstream pathway using both LC-MS/MS and phospho-antibody arrays.
This dataset
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.

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 GSE171054_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA718254 and SRA study SRP312580. Searching any of these in the dataset finder brings you back here.

Samples in this study

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