GEO series

Alterations to the bronchial gene-expression effects of tobacco smoking in people living with HIV

GSE318533 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2026/02/05 Platform GPL30173

At a glance

RNA-seq (gene expression) · human · 36 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: Lung cancerThis series is part of our curated briefing on it.
Samples: 36 samples
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: Alterations to the Bronchial Gene-Expression Effects of Tobacco Smoking in People Living With HIVJournal of acquired immune deficiency syndromes (1999) · 2026

Summary (written by the submitters)

Background: Although acquired immunodeficiency syndrome-related mortality has decreased since the introduction of antiretroviral therapy, the incidence of lung cancer in patients living with HIV (PLWH) remains high. Understanding the effects of tobacco smoke on airway gene expression in PLWH may provide insight into the elevated lung cancer risk associated with HIV.

Read the full summary ↓

Methods: Airway epithelial brushings were collected from 12 PLWH who smoke and 19 PLWH who have never smoked and profiled using RNA-seq. Linear models were used to identify genes differentially expressed between people who smoke and have never smoked and between people who previously smoked and have never smoked. Gene set enrichment analysis was used to validate smoking-related gene signatures across datasets. Data was integrated with gene expression data from a cohort of patients without HIV to identify genes differentially modulated by both smoking and HIV status. Results: We found that previous smoking-related gene signatures are similarly associated with smoking in PLWH, including the persistent differential expression of a subset of "irreversibly altered" genes in people who previously smoked compared to people who have never smoked. We also identified and validated two gene signatures specifically modulated in people who smoke without HIV. Conclusions: Many of the effects of smoking on bronchial gene expression are shared between PLWH and non-HIV individuals. Of the subset of genes that differ between PLWH and non-HIV individuals, it appears that the effect of smoking on gene expression is more attenuated in PLWH. This includes genes related to oxidative stress and epithelial integrity, and suggests potential mechanisms that may contribute to smoking-related outcomes that are more prevalent in PLWH, such as lung cancer.

Published in

Alterations to the Bronchial Gene-Expression Effects of Tobacco Smoking in People Living With HIV

Lee M, Olson A, Pickering RT et al. · Journal of acquired immune deficiency syndromes (1999) 2026 · PMID 41734085 · doi:10.1097/QAI.0000000000003853

This dataset

Open GSE318533 in finder → Find more human RNA-seq datasets → Lung cancer landscape →

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 GSE318533_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 PRJNA1419182. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41734085) ↗

Samples in this study

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+ 36 more — browse all 36 samples with per-sample file links →

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