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ALDH1A1 Promotes Immune Escape of Tumor Cells through ZBTB7B-Glycolysis Pathway

GSE269935 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/08/27 Platform GPL30209
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × HT29 CM10 vs 3 × HT29 shZBTB7BGroups 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
ALDH1A1 promotes immune escape of tumor cells through ZBTB7B-glycolysis pathwayCell death & disease · 2024
Summary (written by the submitters)
Background The primary impediment to the success of immunotherapy lies in the immune evasion orchestrated by tumors, contributing to the suboptimal overall response rates observed. Despite this recognition, the intricacies of the underlying mechanisms remain incompletely understood. Methods and Results Through preliminary detection of clinical patient tissues, we have found that ALDH1A1 was a key gene for the prognosis of cancer patients and tumor glycolysis.
Read the full summary ↓
In vitro experiments and tumor formation in nude mice suggested that targeting ALDH1A1 could inhibit tumor growth. Through further analysis of xenograft tumor models in immune-normal mice and flow cytometry, we found that deficiency in ALDH1A1 could promote immune system suppression of tumors in vivo. Specifically, RNA-seq analysis, combined with qPCR and western blot, identified the transcription factor ZBTB7B as downstream of ALDH1A1. The binding sites of the transcription factor ZBTB7B on the LDHA promoter region, which is responsible for regulating the rate-limiting enzyme gene LDHA in glycolysis, were determined using luciferase reporter gene detection and Chip-qPCR, respectively. In addition, the increased SUMOylation of ZBTB7B stabilized its transcriptional activity. Further in vivo and in vitro experiments confirmed that the combination of targeting ALDH1A1 and ZBTB7B with immune checkpoint inhibitors could synergistically inhibit tumors in vivo. Finally, after conducting additional verification of patient tissue and clinical data, we have confirmed the potential translational value of targeting ALDH1A1 and ZBTB7B for tumor immunotherapy. Conclusions These results emphasize the potential translational significance of targeting ALDH1A1 and ZBTB7B in the realm of tumor immunotherapy. The convergence of ALDH1A1 inhibition and immune checkpoint blockade, particularly with PD-L1/PD-1 mAb, presents a compelling avenue for curtailing tumor immune escape.
Published in
ALDH1A1 promotes immune escape of tumor cells through ZBTB7B-glycolysis pathway
Wang M, Wang T, Wang J et al. · Cell death & disease 2024 · PMID 39107297 · doi:10.1038/s41419-024-06943-9
This dataset
Open GSE269935 in finder → Find more human RNA-seq datasets →
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 GSE269935_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 ↗

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 PRJNA1124139 and SRA study SRP514093. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39107297) ↗
Study design
3 × HT29 CM10 vs 3 × HT29 shZBTB7B

Supports a between-group comparison across 6 samples.

How we read this: 2 replicated groups read from 12 sample titles; they account for 6 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
Datasets on a similar topic

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