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A Spatially Resolved Transcriptome Landscape during Thyroid Cancer Progression

GSE250521 Homo sapiens Expression profiling by high throughput sequencing; Other 25 samples Submitted 2025/02/16 Platform GPL24676
Summary
Thyroid cancer ranks as the ninth most common cancer type in terms of incidence worldwide. Furthermore, the global incidence of thyroid cancer has been on the rise over the past decades.Spatial transcriptomics technology systematically profiles gene expression across tissue space by combing high-throughput RNA sequencing and imaging techniques. The applications of ST have revealed high-resolution spatial architecture and cellular crosstalk in many tumor types, advancing the discovery of new targets for diagnosis and therapy. However, the spatial architecture in thyroid cancer and the structural differences in the TME among papillary thyroid cancer (PTC), locally advanced thyroid cancer (LPTC), and Anaplastic thyroid carcinoma (ATC) have been little investigated. Herein , we applied ST and scRNA-seq data to reveal the spatial difference of TME in PTC, LPTC, and ATC samples.
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Direct links to NCBI, no account and no request form: the whole study as GSE250521_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 25 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1054236 and SRA study SRP478784. Searching any of these in the dataset finder brings you back here.

Study design
25 conditions, each sampled once — no replicated groups

Read from 25 sample titles: 25 distinct titles with little repetition. Check it against the sample list below before relying on it.

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