ArticleAdvances and applications in bioinformatics and chemistry : AABC2024
LAMP5, One of Four Genes Related to Oxidative Stress That Predict Biochemical Recurrence-Free Survival, Promotes Proliferation and Invasion in Prostate Cancer.
Article in Advances and applications in bioinformatics and chemistry : AABC, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.
What it found
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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
2 citing papers in PubMed.
- Oncogenic and immunological roles of LAMP5 across cancers and its potential utility in bladder cancer.Apoptosis : an international journal on programmed cell death · 2026Article
- Pathway-based molecular subtyping identifies LAMP5 as an EMT-associated prognostic target in colorectal cancer.Frontiers in pharmacology · 2026Article
Corrections and comments
- Retracted
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Prostate cancer (PCa) development largely depends on increased levels of oxidative stress (OS) and a deficient anti-oxidative system. Identifying genes associated with oxidative stress is critical in order to direct PCa therapy and future research. Methods: The TCGA and GTEx databases provided the bulk RNA-seq data, and the GEO database provided the single-cell data GSE141445. Utilizing reactive oxygen species (ROS) markers, single-cell analysis and cluster identification related to oxidative stress were conducted using the R packages "Seurat" and "AUCell". The differentially expressed genes (DEGs) in normal and PCa samples were identified with the "limma" R package. LASSO regression analysis was used to build a recurrence score (RS) model. The R packages "maftools" and the CIBERSORT method were employed to explore genetic mutation and the infiltrating immune cell, respectively. LAMP5 was chosen for further investigation after random forest analysis was performed. Results: The Conclusion: We successfully created a robust
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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 Socratic graph.