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Contact information


naser.ansari-pour@imm.ox.ac.uk


ORCID ID https://orcid.org/0000-0003-0908-0484


Weatherall Institute of Molecular Medicine

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Naser Ansari-Pour

BSc PhD

Senior Bioinformatician in Cancer Genomics

  • MEMBER OF CONGREGATION
  • DPHIL STUDENT SUPERVISOR

RESEARCH THEME: Deciphering tumour heterogeneity and evolution using bulk and single cell DNA data in haematological cancers

My work is funded by the NIHR Oxford Biomedical Research Centre (BRC). I investigate heterogeneity and evolution of tumours in the context of metastasis and therapeutic resistance. The key part to this investigation is the accurate reconstruction of the clonal architecture of tumours. 

Tumours are not easy to treat because they evolve over time by accumulating mutations that enable them to metastasise to distant organs or that result in resistance to treatment (relapse/refractory status). To better understand the underlying biology, I mainly analyse deep whole-genome sequencing (WGS) data to detect intra-tumoural heterogeneity, infer tumour phylogenies and identify alternative evolutionary trajectories. See Rabbie & Ansari-Pour et al. 2020 for a multi-sampling approach in understanding metastasis in melanoma and Gooding et al. 2021 in characterising therapeutic resistance in multiple myeloma.

Melanoma tumour phylogeny (Rabbie & Ansari-Pour et al. 2020)

I am also interested in genomic events driving tumourigenesis. For this, I identify significantly enriched copy number aberrations (CNA), mutational drivers and whole-genome duplication and infer the chronological order of events using a state-of-the-art timing model pipeline that I have recently developed (see Ansari-Pour et al. 2021).

Chronological ordering of genomic events in Nigerian breast cancer (Ansari-Pour et al. 2021)

Another key interest of mine is in high-resolution tracking of genomic heterogeneity and drivers using single cell data based on RNA & DNA. For single-cell DNA (scDNA) data, I have developed code to analyse scDNA for both short variants, calling CNA from raw scDNA data and trace evolution of single cells pre- to post-malignancy (Ansari-Pour et al. 2021 IMW)

scDNA copy number loss-of-heterozygosity (LOH) [Ansari-Pour et al. 2021]
Tumour phylogeny of multiple myeloma single cells [Ansari-Pour et al. 2021]

Talks