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Interferon responsive high endothelial venules drive tumor tertiary lymphoid structure formation and predict response to anti-PD-1 immunotherapy in nasopharyngeal carcinoma

GSE289272 Homo sapiens (human) Other 55 samples Submitted 2025/05/02 Platform GPL24676
At a glance

human · 55 samples

Organism
Homo sapiens (human)
Topic
Nasopharyngeal carcinomaThis series is part of our curated briefing on it.
Samples
55 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI.
Summary (written by the submitters)
The outcome of immune checkpoint blockade (ICB) therapy largely hinges on the antitumor immune response of tertiary lymphoid structures (TLSs), but the driver factors behind tumor TLS formation remain poorly understood. Through integrated analysis of spatial and pan-cancer single-cell transcriptomics, we reveal the characteristics of TLSs in nasopharyngeal carcinoma (NPC) and identify a subset of interferon responsive high endothelial venules (IFN-HEVs) that is responsible for the emergence of tumor-specific chemokines, especially CXCL9.
Read the full summary ↓
Functionally, IFN-HEVs facilitate the recruitment of CD4+ T cells into TLSs via the CXCL9-CXCR3 axis. IFN-HEV-related phenotypes are strongly correlated with positive prognostic outcomes and better responses to ICB therapy. Leveraging these phenotypes, we develop a pretreatment CXCL9-TLS Response-predictive scoring system (CTRscore) to forecast the efficacy of ICB therapy and validate its predictive efficiency in three independent NPC cohorts. Our study provides biological and functional insights into the IFN-HEVs in tumor TLSs, highlighting their potential role in the development of biomarkers and predictors for the success of ICB therapy.
This dataset
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Direct links to NCBI, 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.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE289272_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Also filed as BioProject PRJNA1222316. Searching any of these in the dataset finder brings you back here.

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