Background: Glioblastoma (GBM) is categorized as a grade IV astrocytoma by the World Health Organization (WHO), representing the most aggressive and prevalent form of glioma. It presents a significant clinical challenge, with limited treatment options and poor prognosis. This systematic review evaluates the efficacy and safety of various nanotherapy approaches for GBM and explores future directions in tumor management. Nanomedicine, which involves nanoparticles in the 1–100 nm range, shows promise in improving drug delivery and targeting tumor cells. Methods: Following PRISMA guidelines, a systematic search of databases including Google Scholar, NCBI PubMed, Cochrane Library, and ClinicalTrials.gov was conducted to identify clinical trials on GBM and nanomedicine. The primary outcome measures were median overall survival, progression-free survival, and quality of life assessed through Karnofsky performance scores. The safety profile was assessed by adverse events. Results: The analysis included 225 GBM patients, divided into primary and recurrent sub-populations. Primary GBM patients had a median overall survival of 6.75 months, while recurrent GBM patients had a median overall survival of 9.7 months. The mean PFS period was 2.3 months and 3.92 months in primary GBM and recurrent GBM patients, respectively. Nanotherapy showed an improvement in quality of life, with KPS scores increasing after treatment in recurrent GBM patients. Adverse events were observed in 14.2% of patients. Notably, Bevacizumab therapy exhibited better survival outcomes but with a higher incidence of adverse events. Conclusions: Nanotherapy offers a modest increase in survival with fewer severe side effects. It shows promise in improving the quality of life, especially in recurrent GBM patients. However, it falls short in terms of overall survival compared to Bevacizumab. The heterogeneous nature of treatment protocols and reporting methods highlights the need for standardized multicenter trials to further evaluate the potential of nanomedicine in GBM management.

Bladder cancer is one of the most frequent cancers and shows high recurrence rates. Despite recent advances, key knowledge gaps remain in understanding the molecular mechanisms of disease progression, which would support the development of early detection methods and effective personalized treatments. We apply integrated multi-omics and spatial analyses in a cohort of 49 bladder cancer patients to comprehensively profile genetic, epigenetic, transcriptomic, and spatial features of bladder cancer, alongside cell-free DNA blood analysis. Combining low-pass whole-genome cell-free DNA sequencing, Oxford Nanopore long-read tumor DNA sequencing, RNA-sequencing, and spatial transcriptomics, we provide insights into molecular alterations driving bladder cancer. We show frequent somatic LINE-1 (L1) insertions, with up to more than 500 insertions per tumor. We find that L1 insertions are active and occur early in bladder cancer development. We link aberrant somatic L1 insertion in bladder cancer with downstream genomic rearrangements and chromosomal instability, with an excess of structural variants and extrachromosomal DNA (ecDNA) in patients with particularly high L1 counts. By detecting ecDNA within tissue architecture using spatial transcriptomics, we identify the localization of ecDNA to distinct spatial clusters with differential expression of APOBEC3B and immune response pathways. These results, combined with replication timing analysis and gene set enrichment analysis (GSEA), offer evidence for the previously hypothesized viral mimicry response to L1 retrotransposition, mediated via APOBEC3B-editing, the cGAS-STING pathway, and RIG-I and MDA5 responses.

Glioblastoma multiforme (GBM) is a heterogeneous, invasive primary brain tumor that develops chemoresistance post therapy. Theories regarding the aetiology of GBM focus on transformation of normal neural stem cells (NSCs) to a cancerous phenotype or tumorigenesis driven via glioma stem cells (GSCs). Comparative RNA-Seq analysis of GSCs and NSCs can provide a better understanding of the origin of GBM. Thus, in the current study, we performed various bioinformatics analyses on transcriptional profiles of a total 40 RNA-seq samples including 20 NSC and 20 GSC, that were obtained from the NCBI-SRA (SRP200400). First, differential gene expression (DGE) analysis using DESeq2 revealed 348 significantly differentially expressed genes between GSCs and NSCs (padj. value <0.05, log2fold change ≥ 3.0 (for GSCs) and ≤ −3.0 (for NSCs)) with 192 upregulated and 156 downregulated genes in GSCs in comparison to NSCs. Subsequently, exploratory data analysis using principal component analysis (PCA) based on key significant genes depicted the clear separation between both the groups. Further, Hierarchical clustering confirmed the distinct clusters of GSC and NSC samples. Eventually, the biological enrichment analysis of the significant genes showed their enrichment in tumorigenesis pathways such as Wnt-signalling, VEGF-signalling and TGF-β-signalling pathways. Conclusively, our study depicted significant differences in the gene expression patterns between NSCs and GSCs. Besides, we also identified novel genes and genes previously unassociated with gliomagenesis that may prove to be valuable in establishing diagnostic, prognostic biomarkers and therapeutic targets for GBM.