ArticlePloS one2024
Comprehensive transcriptomic analysis of prostate cancer lung metastases.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- MIAAIM: Multi-omics image integration with dimensional reduction for tissue state mapping.PLoS computational biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metastatic prostate cancer (mPCa) is a widespread disease with high mortality. Unraveling molecular mechanisms of disease progression is of utmost importance. The microenvironment in visceral organs and the skeletal system is of particular interest as a harbinger of metastatic spread. Therefore, we performed a comprehensive transcriptomic analysis of prostate cancer lung metastases with a special focus on differentially expressed genes attributable to the microenvironment. Digital gene expression analysis using the NanoString nCounter analysis system was performed on formalin-fixed, paraffin-embedded (FFPE) tissue from prostate cancer (PCa) lung metastases (n = 24). Data were compared to gene expression data from primary PCa and PCa bone metastases. Bioinformatic analysis was performed using several publicly available tools. In comparison to prostate cancer bone metastases, 209 genes were significantly upregulated, and 100 genes were significantly downregulated in prostate cancer lung metastases. Among the up-regulated genes, the top 10 genes with the most significant P-value were HLA-DPB1, PTPRC, ITGB7, C3, CCL21, CCL5, ITGAM, SERPINA1, MFAP4, ARAP2 and among the down-regulated genes, the top 10 genes with the most significant P-value were FOXC2, TWIST1, CDK14, CHAD, IBSP, EPN3, VIT, HAPLN1, SLC44A4, TBX1. In PCa lung metastases genes associated with immunogenic responses were upregulated while genes associated with epithelial-mesenchymal transition were down-regulated. We also showed that CXCR3/CXCL10 axis plays a significant role in prostate cancer lung metastases in comparison to bone metastases. In this study, we comprehensively explored transcriptomic alterations in PCa lung metastases in comparison to primary PCa and PCa bone metastases. In PCa lung metastases genes associated with immunogenic responses are upregulated while genes associated with epithelial-mesenchymal transition are down-regulated. This points to a more immunogenic phenotype of PCa lung metastases thus potentially making patients more susceptible to immunotherapeutic approaches.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.