GEO series

Omics Analysis of Pancreatic Cancer Platelets Reveals Active “Education”, including Dysregulation of Splicing Signature and Inhibition of SPARC by Modified Forms of miRNAs

GSE160252 Homo sapiens (human) Non-coding RNA profiling 44 samples Submitted 2021/01/19 Platform GPL20301Platform GPL16791

At a glance

Non-coding RNA profiling · human · 44 samples

What it is: Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism: Homo sapiens (human)
Topic: Pancreatic cancerThis series is part of our curated briefing on it.
Samples: 44 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)

PDAC cells can activate platelets and change their RNA and protein content, thus, we performed an integrative study investigating the biological processes of differentially spliced mRNAs and expressed miRNAs, as well as proteins. To focus on these “dangerous liaisons”, we used benign disease as a background noise correction for putative inflammatory signals.

Read the full summary ↓

Gene set enrichment analysis on differential miRNAs, RNA transcripts and proteins revealed an enrichment of RNA splicing, mRNA processing and translation initiation on miRNAs and proteins and depletion on RNA transcripts, as previously described. Furthermore, we provide a new repertoire of PDAC and benign platelet-ome, visualized by the R shiny application, to be exploited for future studies. In conclusion, our data show that platelets change their biological repertoire in the presence of PDAC, through dysregulation of miRNAs and splicing factors, supporting the presence of de novo protein machinery that can “educate” the platelet. This has major clinical implications since the emerging molecules could provide important innovative PDAC biomarkers in the context of liquid biopsies.

This dataset

Open GSE160252 in finder → Find more human RNA-seq datasets → Pancreatic 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 GSE160252_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 ↗

Also filed as BioProject PRJNA672701 and SRA study SRP288935. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 33383671) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 44 more — browse all 44 samples with per-sample file links →

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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.