GEO series
Paracrine Signals from HIV-1 Infected Immune Cells Reprogram Cervical Cancer Pathways
GSE299125
Homo sapiens (human)
RNA-seq (gene expression)
35 samples
Submitted 2026/05/04
Platform GPL21697
At a glance
RNA-seq (gene expression) · human · 35 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
- Cervical cancerThis series is part of our curated briefing on it.
- Samples
- 35 samples: 35 samples, each with a distinct title — no replicated groupsGroups 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
- Paracrine signals from HIV-1-infected immune cells reprogram cervical cancer pathwaysiScience · 2026
Summary (written by the submitters)
Persistent infection with human papillomavirus (HPV) is the primary cause of cervical cancer worldwide. Notably, women co-infected with HPV and human immunodeficiency virus type 1 (HIV-1) have a six-fold higher lifetime risk of developing cervical cancer compared to those without HIV, even when adhering to antiretroviral therapy (ART) and achieving T-cell reconstitution.
Read the full summary ↓
While chronic HIV-1 infection is known to cause inflammation, how paracrine signals from immune cells alter signaling in cervical cells remain poorly understood. To address this, we conducted global transcriptomics analysis on cervical swabs from Kenyan women with HPV, stratified by HIV-1 and cancer status. Strikingly, women with HIV-1 showed cancer-like gene expression patterns in non-cancerous cervical epithelial cells. Complementary global mass spectrometry (MS) proteomics of cervical cells exposed to the secretome of HIV-1–infected primary CD4+ T-cells revealed altered expression of proteins in MAPK, PI3K-AKT, and β-catenin signaling pathways. Integrative network analyses of transcriptomic and proteomic datasets revealed that HIV-1 altered gene expression in key pathways known to drive cervical cancer, including genes commonly mutated in HIV-1-naïve disease. Notably, IRS-1, a key PI3K-AKT pathway activator, was found to be consistently upregulated in both participant samples and cell culture models, as were interferon-stimulated genes. Phosphoproteomics MS analysis confirmed PI3K-AKT pathway activation in cervical cells exposed to conditioned media from HIV-1-infected T-cells. Together, our findings uncover how HIV-1 reshapes cervical cell signaling via paracrine mechanisms and highlights the PI3K pathway as a potential therapeutic target in HIV-associated cervical cancer.
Published in
Olwal CO, Rathore U, Makanani SK et al.
· iScience 2026
· PMID 42305618
· doi:10.1016/j.isci.2026.116083
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 GSE299125_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 PRJNA1272618 and SRA study SRP590244. Searching any of these in the dataset finder brings you back here.
Study design
35 samples, each with a distinct title — no replicated groups
Supports a case/control comparison: 23 samples read as cases, 12 as controls.
How we read this: Read from 35 sample titles: 35 distinct titles with little repetition. 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
- GSM9033939 sample1, HIV positive, normal cervix
- GSM9033940 sample2, HIV positive, normal cervix
- GSM9033941 sample3, HIV negative, normal cervix
- GSM9033942 sample4, HIV positive, normal cervix
- GSM9033943 sample5, HIV negative, normal cervix
- GSM9033944 sample6, HIV negative, normal cervix
- GSM9033945 sample7, HIV negative, normal cervix
- GSM9033946 sample8, HIV negative, normal cervix
- GSM9033947 sample9, HIV negative, normal cervix
- GSM9033948 sample10, HIV positive, normal cervix
- GSM9033949 sample11, HIV positive, normal cervix
- GSM9033950 sample12, HIV positive, normal cervix
- GSM9033951 sample13, HIV positive, precancerous cervical lesion
- GSM9033952 sample14, HIV positive, invasive cervical carcinoma
- GSM9033953 sample15, HIV positive, precancerous cervical lesion
- GSM9033954 sample16, HIV positive, precancerous cervical lesion
- GSM9033955 sample17, HIV positive, precancerous cervical lesion
- GSM9033956 sample18, HIV positive, precancerous cervical lesion
- GSM9033957 sample19, HIV positive, precancerous cervical lesion
- GSM9033958 sample20, HIV positive, precancerous cervical lesion
- GSM9033959 sample21, HIV positive, invasive cervical carcinoma
- GSM9033960 sample22, HIV negative, invasive cervical carcinoma
- GSM9033961 sample, 23, HIV negative, invasive cervical carcinoma
- GSM9033962 sample24, HIV negative, invasive cervical carcinoma
- GSM9033963 sample25, HIV negative, invasive cervical carcinoma
- GSM9033964 sample26, HIV negative, precancerous cervical lesion
- GSM9033965 sample27, HIV negative, invasive cervical carcinoma
- GSM9033966 sample28, HIV positive, invasive cervical carcinoma
- GSM9033967 sample29, HIV negative, precancerous cervical lesion
- GSM9033968 sample30, HIV negative, invasive cervical carcinoma
- GSM9033969 sample31, HIV negative, invasive cervical carcinoma
- GSM9033970 sample32, HIV negative, precancerous cervical lesion
- GSM9033971 sample33, HIV negative, invasive cervical carcinoma
- GSM9033972 sample34, HIV negative, invasive cervical carcinoma
- GSM9033973 sample35, HIV negative, invasive cervical carcinoma
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- GSE291247 DLEU2 promotes cell motility and immune infiltration in cervical squamous cell carcinoma through reciprocal feed-forward activation of E2F1 16 samples same disease briefing · shares cervical
- GSE308792 Profiling of immune cell subsets and functional characteristics of cervical cancer based on single cell RNA sequencing 6 samples same disease briefing · shares cervical
- GSE316098 Spatial Transcriptomic Landscape of Invasion Patterns in Human Papillomavirus-Associated Endocervical Adenocarcinoma 186 samples same disease briefing · shares cervical
Share this dataset
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.