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Humanized antibody-drug conjugates for SSTR2-positive tumor treatment

GSE304978 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2025/08/12 Platform GPL20795
At a glance

RNA-seq (gene expression) · human · 10 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)
Samples
10 samples: 5 × CH157-MN Control vs 5 × CH157-MN TreatmentGroups 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.
Summary (written by the submitters)
Somatostatin receptor 2 (SSTR2) is overexpressed in neuroendocrine tumors (NETs) and meningiomas. The objective of this study was to develop an SSTR2-targeted therapy to treat both tumor types. We engineered and humanized an anti-SSTR2 monoclonal antibody (mAb) demonstrating strong cancer cell binding, internalization in cancer cells, and tumor specificity, as evidenced by flow cytometry, confocal microscopy, and live-animal imaging.
Read the full summary ↓
Antibody-drug conjugates (ADCs) were generated by conjugating the SSTR2 mAb with potent payloads, including monomethyl auristatin F (MMAF) or mertansine (DM1). In vitro assessments revealed high cytotoxicity across diverse NET subtypes and meningioma cell lines. In vivo efficacy was confirmed in two mouse models, i.e. subcutaneous NET xenografts and intracranial meningioma xenografts, where treatment inhibited proliferation, induced apoptosis and cell death, exhibited minimal toxicity, and extended survival. The mechanism of action was further elucidated through bulk RNA sequencing post-treatment. These findings highlight the therapeutic potential of our humanized SSTR2 mAb for targeted payload delivery in NETs and meningiomas.
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 GSE304978_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 PRJNA1303643 and SRA study SRP607752. Searching any of these in the dataset finder brings you back here.

Study design
5 × CH157-MN Control vs 5 × CH157-MN Treatment

Supports a between-group comparison across 10 samples.

How we read this: 2 replicated groups read from 10 sample titles; they account for 10 of them. 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
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