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Coexpression and functions of the colinear genes CD47 and IFT57 in thyroid cancer

GSE254982 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2024/09/13 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 20 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
Thyroid cancerThis series is part of our curated briefing on it.
Samples
20 samples: 20 samples, each with a distinct title — no replicated groupsGroups 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
CD47 and IFT57 Are Colinear Genes That Are Highly Coexpressed in Most Cancers and Exhibit Parallel Cancer-Specific Correlations with SurvivalInternational journal of molecular sciences · 2024
Summary (written by the submitters)
Higher CD47 expression in some cancers correlates with poor survival. In contrast, higher CD47 mRNA expression in papillary thyroid carcinomas correlated with significantly improved overall survival. IFT57 was the top gene coexpressed with CD47 in these tumors, and higher IFT57 mRNA correlated with significantly improved overall and disease-free survival.
Read the full summary ↓
IFT57 is a component of the primary cilium, which also regulates cancer pathogenesis. IFT57 and CD47 are colinear genes in humans, and this synteny is highly conserved across amniote genomes. Transcriptional regulators have been identified that increase CD47 expression in cancers, but its proximity suggested that IFT57 could be coregulated. CD47 and IFT57 mRNAs were also coregulated in anaplastic thyroid carcinoma cell lines and carcinomas of multiple tissues. Anaplastic thyroid carcinoma cell line mutants with decreased IFT57 or CD47 expression were used to define IFT57-dependent phenotypes and gene expression. Loss of IFT57 expression regulated transcripts involved in cell motility and extracellular matrix pathways. Altered cell motility was confirmed in IFT57 mutants. Three IFT57-dependent genes identified in the cell lines exhibited stronger coexpression with IFT57 than with CD47 in papillary thyroid tumors. CRACD was identified as an IFT57-specific target that correlates with survival in lung as well as papillary thyroid carcinomas.
Published in
CD47 and IFT57 Are Colinear Genes That Are Highly Coexpressed in Most Cancers and Exhibit Parallel Cancer-Specific Correlations with Survival
Dong K, Nihal R, Meyer TJ et al. · International journal of molecular sciences 2024 · PMID 39201643 · doi:10.3390/ijms25168956
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 GSE254982_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 PRJNA1072737 and SRA study SRP487830. Searching any of these in the dataset finder brings you back here.

Study design
20 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 20 sample titles: 20 distinct titles with little repetition. 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
More Thyroid cancer datasets

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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.