Article

Transcriptomics-Driven Machine Learning Models Accurately Predict Chemotherapy Response in Muscle-invasive Bladder Cancer

2024-06-28

Abstract excerpt

<h4>ABSTRACT</h4> Muscle-invasive bladder cancer (MIBC) is associated with poor predictability of response to cisplatin-based neoadjuvant chemotherapy (NAC). Consequently, the benefit of NAC remains unclear for many patients due to the lack of reliable biomarkers. In order to identify biomarkers and build an integrated and accurate model to predict NAC response, we conducted a comprehensive transcriptomic and geno...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: dcf01020-99a8-5dd7-8ac8-ffcdff8bf0a2
DOI: 10.1101/2024.06.28.24309634

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Transcriptomics-Driven Machine Learning Models Accurately Predict Chemotherapy Response in Muscle-invasive Bladder CancerDOI 10.1101/2024.06.28.24309634Read

Molecular correlates of cisplatin-based chemotherapy response in muscle invasive bladder cancer by integrated multi-omics analysis.Semantic proximity Read

Machine Learning and Experimental Validation Reveal MYH11 as a Novel Prognostic Biomarker and Therapeutic Target in Bladder CancerSemantic proximity Read

Personalized <i>in-silico</i> drug response prediction based on the genetic landscape of muscle-invasive bladder cancerSemantic proximity Read

A Five-Gene Stromal-EMT Signature Predicts Prognosis, Immunotherapy Resistance, and Therapeutic Vulnerability in Bladder CancerSemantic proximity Read

Multi-omics consensus ensemble refines the classification of muscle-invasive bladder cancer with stratified prognosis, tumour microenvironment and distinct sensitivity to frontline therapiesSemantic proximity Read

Machine learning prediction models based on hub genes related to immune phenotypes in muscle-invasive bladder cancer treated with immune checkpoint blockadeSemantic proximity Read

Tumor Immune Infiltration as a Predictor of Response to Neoadjuvant Chemo-Immunotherapy in Muscle-Invasive Bladder Cancer: An Integrative TCGA AnalysisSemantic proximity Read

A showcase study on personalized in silico drug response prediction based on the genetic landscape of muscle invasive bladder cancer.Semantic proximity Read

EGFR as a potential therapeutic target for a subset of muscle-invasive bladder cancers presenting a basal-like phenotype.Semantic proximity Read

A Novel Patient-specific Protein Expression-based Algorithmic Model for Immune Checkpoint Inhibition Therapy Response Prediction in a Pan-cancer CohortSemantic proximity Read

Identification of an immunotherapy-responsive molecular subtype of bladder cancer.Semantic proximity Read