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Liquid Biopsy: Examination of platelet RNA obtained from head and neck squamous cell carcinoma patients for molecular tumor markers

GSE156554 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2023/07/19 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 15 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
Head and neck cancerThis series is part of our curated briefing on it.
Samples
15 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)
The present study aims to clarify whether patients suffering from head and neck squamous cell carcinoma (HNSCC) could be recognized based on platelet mRNA sequencing (RNAseq). Sequencing analysis of RNA derived from platelets of tumor patients and healthy donors revealed significantly differentially expressed RNA encoding 618 genes. Among them, we identified RNA coding for 49 genes characteristically expressed in epithelial cells.
Read the full summary ↓
Additionally, in tumor patient’s platelets we observed RNA coding for genes involved in tumor progression by contributing to proliferation, metastasis or angiogenesis. Furthermore, 41 non-coding RNAs involved in transcription and translation have been identified. Results were verified by quantitative RT-PCR on platelet RNA derived from a second tumor patient / healthy donor cohort. However, in order to identify a combination of a certain set of genes allowing the identification of HNSCC based on platelet RNAseq further research is necessary.
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 GSE156554_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 PRJNA658334 and SRA study SRP278211. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 15 more — browse all 15 samples with per-sample file links →

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