Edinburgh Research Explorer

Dr Nizar Batada

(Former employee or visitor)

Profile photo

Willingness to take PhD students: Yes

Available PhD project: Single cell genomic characterization of tumor microenvironment The study will focus on characterizing the heterogeneity and cytokine signaling of tumour microenvironment of brain cancers (particularly glioblastoma). Of particular interests are tumor associated macrophages which have both tumor and metastasis promoting role as well as tumor suppressing role. Projects are available for students purely interested in computational biology/machine learning but also for students wiching to carry out a combined computational/wet-lab genomic project. Goal of the project will be generate and analyze single cell RNA sequencing data on tumours and tumour infiltrating immune cells to characterize transcriptomic programes that underlies various phenotypes such as therapy resistance, epithelial mesynchymal transitions, cancer stem cells and cytokine signaling to and from the tumour microenvironment. Moreover, the project will involve identifying somatic mutations and copy number alterations to define clonal heterogeneity. This post would suit a collaborative, self directed and an academic minded person who wishes to work at the interface of genomics and computational biology in an under-explored area of high importance for cancer biology and therapeutics. Ideally, the student is expected to be familiar with or be highly driven to quickly learn programming (in python and R), basic statistics and genomics. The student will have the opportunity to interact with outstanding scientists (over 40 labs and 100 graduate students) at the Institute of Genetics and Molecular Medicine at the University of Edinburgh. The successful student will receive substantial training tailored to individual requirements.

Education/Academic qualification

2000Doctor of Health Science, Stanford Univ, Stanford University

Area of Expertise

Research expertiseGenome sequencing, Bioinformatics, Chromatin, Epigenetics, Genome Instability, DNA double strand break repair, BRCA1, Histone methyltransferase, Single cell sequencing, Cancer Immunology, Single cell sequencing, Cancer , Whole Genome Sequencing, Copy Number Variations, Variant Calling, Exome Sequencing, DNA methylation, Python, R, Statistics, Probability

Biography

After completing his undergraduate degree in Biochemistry from University of Carleton (Canada), Nizar obtained a masters in Applied Mathematics from California Institute of Technology (CalTech) and a PhD in Biophysics from Stanford University (working with Michael Levitt, Nobel Laureate, 2013) during this period he published four first author papers, including two in PNAS in the area of computational biology. He was then awarded a Canadian Institute of Health Research postdoctoral fellowship to work jointly with Laurence Hurst (University of Bath) and Mike Tyers (University of Toronto) during this perio he published several first author papers in journals such as Nature Genetics and PLoS Biology in the area of protein-protein interaction networks, chromatin and genome evolution. He subsequently did a postdoc with George Church (Harvard Medical School) focusing on experimental genomics. In 2008, he moved back to Toronto to take up an Junior Investigator position at the Ontario Institute for Cancer Research, focusing on mechanisms causing genome instability. In late 2016, he moved to the IGMM at the University of Edinburgh as a Chancellor’s Fellow and was recently awarded a Wellcome Trust Seed Award.

My research in a nutshell

The general area of my lab’s research interest is in Cancer Immunology, in the context of brain (glioblastoma) and ovarian cancer. The remarkable success of cancer immunotherapies targetting T-cell checkpoint pathways suggest that cancers have evaded the immune system and blocking the evasion pathways can rearm the host's immune system to eradicate cancers. Unfortunately existing immunotherapies against T-cell checkpoint pathway do not work in the cancers of the brain and ovary. Existing studies suggest that tumour associated macrophages (TAMs) may be very high in these cancers and can be either excluding cytotoxic T cells from the tumour bed or turning them of either directly or through recruiting immunosuppresive cells such as regulatory T cells. In addition to contributing to immunosuppression in the tumour microenvironment, TAMs also appear to help tumour grow and metastasize through promoting blood vessel growth and matrix remodeling.  We combine both wet-lab genomic experiments and computational biology to generate and analyze single cell RNA-seq data on tumour infiltrating cells. We use computational analysis of single cell RNA-seq data to infer cell identity cells, their prevalence, to uncover the changes in their phenotypes relative to healthy tissues, the pro-tumour cytokine signaling within microenvironment in order to uncover mechanisms of immune evasion and mechanisms of therapy resistance mediated by the tumour microenvironment.  My lab is committed to making a significant clinical impact by discovering blood markers for early detection of cancer, by stratifying cancers based on immune phenotypes and uncovering biomarkers of response or resistance to immunotherapy.

Websites

Positions available

Available PhD project: Single cell genomic characterization of tumor microenvironment

The study will focus on characterizing the heterogeneity and cytokine signaling of tumour microenvironment of brain and ovarian cancers. Of particular interests are tumor associated macrophages which have both tumor and metastasis promoting role as well as tumor suppressing role. Projects are available for students purely interested in computational biology/machine learning but also for students wiching to carry out a combined computational/wet-lab genomic project. Goal of the project will be generate and analyze single cell RNA sequencing data on tumours and tumour infiltrating immune cells to characterize transcriptomic programes that underlies various phenotypes such as therapy resistance, epithelial mesynchymal transitions, cancer stem cells and cytokine signaling to and from the tumour microenvironment. Moreover, the project will involve identifying somatic mutations and copy number alterations to define clonal heterogeneity. This post would suit a collaborative, self directed and an academic minded person who wishes to work at the interface of genomics and computational biology in an under-explored area of high importance for cancer biology and therapeutics. Ideally, the student is expected to be familiar with or be highly driven to quickly learn programming (in python and R), basic statistics and genomics. 

The student will have the opportunity to interact with outstanding scientists (over 40 labs and 100 graduate students) at the Institute of Genetics and Molecular Medicine at the University of Edinburgh. The successful student will receive substantial training tailored to individual requirements.

ID: 29372291