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Epigenetics advancing personalized nanomedicine in cancer therapy.

ABSTRACT: Personalized medicine aims to deliver the right drug to a right patient at the right time. It offers unique opportunities to integrate new technologies and concepts to disease prognosis, diagnosis and therapeutics. While selective personalized therapies are conceptually impressive, the majority of cancer therapies have dismal outcome. Such therapeutic failure could result from no response, drug resistance, disease relapse or severe side effect from improper drug delivery. Nanomedicine, the application of nanotechnology in medicine, has a potential to advance the identification of diagnostic and prognostic biomarkers and the delivery of right drug to disease sites. Epigenetic aberrations dynamically contribute to cancer pathogenesis. Given the individualized traits of epigenetic biomarkers, epigenetic considerations would significantly refine personalized nanomedicine. This review aims to dissect the interface of personalized medicine with nanomedicine and epigenetics. I will outline the progress and highlight challenges and areas that can be further explored perfecting the personalized health care.

SUBMITTER: Liu S

PROVIDER: S-EPMC3477272 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Epigenetics advancing personalized nanomedicine in cancer therapy.

Liu Shujun S

Advanced drug delivery reviews 20120819 13

Personalized medicine aims to deliver the right drug to a right patient at the right time. It offers unique opportunities to integrate new technologies and concepts to disease prognosis, diagnosis and therapeutics. While selective personalized therapies are conceptually impressive, the majority of cancer therapies have dismal outcome. Such therapeutic failure could result from no response, drug resistance, disease relapse or severe side effect from improper drug delivery. Nanomedicine, the appli ...[more]

PMID: 22921595

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Project description:BackgroundBladder cancer (BLCA) was recognized as a significant public health challenge due to its high incidence and mortality rates. The influence of molecular subtypes on treatment outcomes was well-acknowledged, necessitating further exploration of their characterization and application. This study was aimed at enhancing the understanding of BLCA by mapping its molecular heterogeneity and developing a robust prognostic model using single-cell and bulk RNA sequencing data. Additionally, immunological characteristics and personalized treatment strategies were investigated through the risk score.MethodsSingle-cell RNA sequencing (scRNA-seq) data from GSE135337 and bulk RNA-seq data from several sources, including GSE13507, GSE31684, GSE32894, GSE69795, and TCGA-BLCA, were utilized. Molecular subtypes, particularly the basal-squamous (Ba/Sq) subtype associated with poor prognosis, were identified. A prognostic model was constructed using LASSO and Cox regression analyses focused on genes linked with the Ba/Sq subtype. this model was validated across internal and external datasets to ensure predictive accuracy. High- and low-risk groups based on the risk score derived from TCGA-BLCA data were analyzed to examine their immune-related molecular profiles and treatment responses.ResultsSix molecular subtypes were identified, with the Ba/Sq subtype being consistently associated with poor prognosis. The prognostic model, based on basal-squamous subtype-related genes (BSSRGs), was shown to have strong predictive performance across diverse clinical settings with AUC values at 1, 3, and 5 years indicating robust predictability in training, testing, and entire datasets. Analysis of the different risk groups revealed distinct immune infiltration and microenvironments. Generally higher tumor mutation burden (TMB) scores and lower tumor immune dysfunction and exclusion (TIDE) scores were exhibited by the low-risk group, suggesting varied potentials for systemic drug response between the groups. Finally, significant differences in potential systemic drug response rates were also observed between risk groups.ConclusionsThe study introduced and validated a new prognostic model for BLCA based on BSSRGs, which was proven effective in prognosis prediction. The potential for personalized therapy, optimized by patient stratification and immune profiling, was highlighted by our risk score, aiming to improve treatment efficacy. This approach was promised to offer significant advancements in managing BLCA, tailoring treatments based on detailed molecular and immunological insights.

Dataset Information

Epigenetics advancing personalized nanomedicine in cancer therapy.

Publications

Epigenetics advancing personalized nanomedicine in cancer therapy.

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