A5054504245- Cancer Genomics and Diagnostics
- Single-cell and spatial transcriptomics
- Renal cell carcinoma treatment
- Genomics and Phylogenetic Studies
- Gene expression and cancer classification
- Epigenetics and DNA Methylation
- Pancreatic and Hepatic Oncology Research
- Immune Response and Inflammation
- Computational Drug Discovery Methods
- Bioinformatics and Genomic Networks
- Genetic factors in colorectal cancer
- Hematopoietic Stem Cell Transplantation
- Ubiquitin and proteasome pathways
- Cancer Mechanisms and Therapy
- Breast Cancer Treatment Studies
- Tryptophan and brain disorders
- Lung Cancer Treatments and Mutations
- Cancer Cells and Metastasis
- Inflammasome and immune disorders
- RNA modifications and cancer
- Colorectal Cancer Treatments and Studies
- Evolution and Genetic Dynamics
- Protein Degradation and Inhibitors
- Myeloproliferative Neoplasms: Diagnosis and Treatment
- Acute Myeloid Leukemia Research
SIB Swiss Institute of Bioinformatics
2015-2022
ETH Zurich
2015-2022
Freie Universität Berlin
2014
Reconstructing the evolution of tumors is a key aspect towards identification appropriate cancer therapies. The task challenging because evolve as heterogeneous cell populations. Single-cell sequencing holds promise resolving heterogeneity tumors; however, it has its own challenges including elevated error rates, allelic drop-out, and uneven coverage. Here, we develop new approach to mutation detection in individual tumor cells by leveraging evolutionary relationship among cells. Our method,...
Next-generation sequencing technologies produce unprecedented amounts of data, leading to completely new research fields. One these is metagenomics, the study large-size DNA samples containing a multitude diverse organisms. A key problem in metagenomics functionally and taxonomically classify sequenced DNA, which end well-known BLAST program usually used. But has dramatic resource requirements at metagenomic scales imposing high financial or technical burden on researcher. Multiple attempts...
Next-generation sequencing of matched tumor and normal biopsy pairs has become a technology paramount importance for precision cancer treatment. Sequencing costs have dropped tremendously, allowing the whole exome tumors just fraction total treatment costs. However, clinicians scientists cannot take full advantage generated data because accuracy analysis pipelines is limited. This particularly concerns reliable identification subclonal mutations in tissue sample with very low frequencies,...
Abstract Motivation Next-generation sequencing is now an established method in genomics, and massive amounts of data are being generated on a regular basis. Analysis the typically performed by lab-specific in-house solutions, but agreement results from different facilities often small. General standards for quality control, reproducibility documentation missing. Results We developed NGS-pipe, flexible, transparent easy-to-use framework design pipelines to analyze whole-exome, whole-genome...
Determining the composition of viral populations is becoming increasingly important in field medical virology. While recently developed computational tools for haplotype analysis allow correcting sequencing errors, they do not always removal errors occurring upstream experimental protocol, such as PCR errors. Primer IDs (pIDs) are one method to address this problem by harnessing redundant template resampling error correction. By using a reference mixture five HIV-1 strains, we show how pIDs...
Tumours evolve as heterogeneous populations of cells, which may be distinguished by different genomic aberrations. The resulting intra-tumour heterogeneity plays an important role in cancer patient relapse and treatment failure, so that obtaining a clear understanding each patient's tumour composition evolutionary history is key for personalized therapies. Single-cell sequencing (SCS) now provides the possibility to resolve at highest resolution individual but brings with it challenges...
Molecular precision oncology is an emerging practice to improve cancer therapy by decreasing the risk of choosing treatments that lack efficacy or cause adverse events. However, challenges integrating molecular profiling into routine clinical care are manifold. From a computational perspective these include importance short analysis turnaround time, interpretation complex drug-gene and gene-gene interactions, necessity standardized high-quality workflows. In addition, difficulties faced when...
Abstract Background Genetic aberrations in hepatocellular carcinoma (HCC) are well known, but the functional consequences of such remain poorly understood. Results Here, we explored effect defined genetic changes on transcriptome, proteome and phosphoproteome twelve tumors from an mTOR-driven mouse model. Using Network-based Integration multi-omiCS data (NetICS), detected 74 ‘mediators’ that relay via molecular interactions effects miRNA expression changes. The mediators account for...
Intra-tumour heterogeneity is the molecular hallmark of renal cancer, and tumour composition determines treatment outcome cancer patients. In tumourigenesis, in general, different clones evolve over time. We analysed intra-tumour subclonal mutation patterns 178 samples obtained from 89 clear cell carcinoma an initial discovery phase, whole-exome transcriptome sequencing data paired biopsies 16 ccRCC patients were used to design a gene panel for follow-up analysis. this second 826 selected...
Abstract Understanding the evolution of cancer is important for development appropriate therapies. The task challenging because tumors evolve as heterogeneous cell populations with an unknown number genetically distinct subclones varying frequencies. Conventional approaches based on bulk sequencing are limited in addressing this challenge clones cannot be observed directly. Single-cell holds promise resolving heterogeneity tumors; however, it has its own challenges including elevated error...
Tumours evolve as heterogeneous populations of cells, which may be distinguished by different genomic aberrations. The resulting intra-tumour heterogeneity plays an important role in cancer patient relapse and treatment failure, so that obtaining a clear understanding each patient’s tumour composition evolutionary history is key for personalised therapies. Single-cell sequencing now provides the possibility to resolve at highest resolution individual but brings with it challenges related...
Abstract Intra-tumour heterogeneity is the molecular hallmark of renal cancer, and tumour composition determines treatment outcome cancer patients. In tumourigenesis, in general, different clones evolve over time. We analysed intra-tumour subclonal mutation patterns 178 samples obtained from 89 clear cell carcinoma an initial discovery phase, whole-exome transcriptome sequencing data paired biopsies 16 ccRCC patients were used to design a gene panel for follow-up analysis. this second 826...