Mimicking Retinoblastoma Treatment With Repeated Topotecan or Melphalan Develops Cross-Resistance to Classic Agents But Not to Repurposed Drugs.

Purpose: Refractory or recurrent retinoblastoma results from acquired chemoresistance and the management of these eyes often requires surgical removal. Our objective was to develop retinoblastoma models resistant to chemotherapy by exposing cancer cells to repeated chemotherapy mimicking the clinical scenario. These newly resistant cells were used to evaluate potential novel therapies.

CRISPR/Cas13a-assisted amplification-free miRNA biosensor dark-field imaging and magnetic gold nanoparticles.

MicroRNAs (miRNAs) are short (about 18-24 nucleotides) non-coding RNAs and have emerged as potential biomarkers for various diseases, including cancers. Due to their short lengths, the specificity often becomes an issue in conventional amplification-based methods. Next-generation sequencing techniques could be an alternative, but the long analysis time and expensive costs make them less suitable for routine clinical diagnosis.

Establishment and Comprehensive Characterization of a Novel Preclinical Platform of Metastatic Retinoblastoma for Therapeutic Developments.

Purpose: Although there have been improvements in the management of metastatic retinoblastoma, most patients do not survive, and all patients suffer from multiple short- and long-term treatment toxicities. Reliable and informative models to assist clinicians are needed. Thus we developed and comprehensively characterized a novel preclinical platform of primary cell cultures and xenograft models of metastatic retinoblastoma to provide insights into the molecular biology underlying metastases and to perform drug screening for the identification of hit candidates with the highest potential for clinical translation.

EpiGe: A machine-learning strategy for rapid classification of medulloblastoma using PCR-based methyl-genotyping.

Molecular classification of medulloblastoma is critical for the treatment of this brain tumor. Array-based DNA methylation profiling has emerged as a powerful approach for brain tumor classification. However, this technology is currently not widely available.

Electrokinetically enhanced label-free plasmonic sensing for rapid detection of tumor-derived extracellular vesicles.

of rare circulating extracellular vesicles (EV) from early cancers or different types of host cells requires extremely sensitive EV sensing technologies. Nanoplasmonic EV sensing technologies have demonstrated good analytical performances, but their sensitivity is often limited by EVs' diffusion to the active sensor surface for specific target EV capture. Here, we developed an advanced plasmonic EV platform with electrokinetically enhanced yields (KeyPLEX).