Precision medicine for hepatocelluar carcinoma using molecular pattern diagnostics: results from a preclinical pilot study
| Autor: | Serena Mancarella, Francesco Dituri, Rahul Agarwal, Peter Winter, Y. Cao, Klaus Hoffmeier, Ruth Jüngling, Lukas Jost, Björn Rotter, Alejandro Rodriguez Meisel, Nicolas Krezdorn, Gianluigi Giannelli |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Male Cancer Research Carcinoma Hepatocellular Transcription Genetic Immunology Pilot Projects Bioinformatics 03 medical and health sciences Cellular and Molecular Neuroscience Carcinoma Medicine Coding region Galunisertib Humans Precision Medicine biology business.industry Gene Expression Profiling Liver Neoplasms Cell Biology Transforming growth factor beta HCCS medicine.disease Precision medicine 3. Good health Gene expression profiling Gene Expression Regulation Neoplastic 030104 developmental biology Molecular Diagnostic Techniques Hepatocellular carcinoma Cancer research biology.protein Female Original Article business |
| Zdroj: | Cell Death & Disease |
| ISSN: | 2041-4889 |
| Popis: | The aim of this study was to design a road map for personalizing cancer therapy in hepatocellular carcinoma (HCC) by using molecular pattern diagnostics. As an exploratory study, we investigated molecular patterns of tissues of two tumors from individual HCC patients, which in previous experiments had shown contrasting reactions to the phase 2 transforming growth factor beta receptor 1 inhibitor galunisertib. Cancer-driving molecular patterns encompass – inter alias – altered transcription profiles and somatic mutations in coding regions differentiating tumors from their respective peritumoral tissues and from each other. Massive analysis of cDNA ends and all-exome sequencing demonstrate a highly divergent transcriptional and mutational landscape, respectively, for the two tumors, that offers potential explanations for the tumors contrasting responses to galunisertib. Molecular pattern diagnostics (MPDs) suggest alternative, individual-tumor-specific therapies, which in both cases deviate from the standard sorafenib treatment and from each other. Suggested personalized therapies use kinase inhibitors and immune-focused drugs as well as low-toxicity natural compounds identified using an advanced bioinformatics routine included in the MPD protocol. The MPD pipeline we describe here for the prediction of suitable drugs for treatment of two contrasting HCCs may serve as a blueprint for the design of therapies for various types of cancer. |
| Databáze: | OpenAIRE |
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