Statistical Cancer Genomics

The journey of tumour and cancer evolution, from a single non-cancerous cell to malignant (cancerous) tumour, is not yet fully discovered and quite complex to comprehend. There are several reasons for this such as:

1. Inter-patient heterogeneity: Tumours evolve differently among patients.

2. Inter-tumour heterogeneity: Tumours evolve differently among regions of the body taken from the same patients.

3. Intra-tumour heterogeneity: A single tumour sample taken from a patient contains bulk sequence of cells, that can be grouped into clusters according to mutations they carry. Those clusters of cells exist at various frequencies in the bulk cell sequence (meaning that it is a heterogeneous collection of cells).

Cancer
Figure taken from [1].

These different levels of heterogeneity can further be grouped into two as spatial (that is, heterogeneity levels vary over different regions of the body) and temporal (that is, heterogeneity proportions changes over time). All these source of heterogeneity make understanding tumour evolution complicated.

My job is to understand how a progenitor cell acquires mutations during cell proliferation, which changes the structure of DNA (i.e. Structural Variants - for example, deletion of a part of DNA) and leads to metastatic tumor growth over time. I am particularly studying the impact and role of structural variants in tumour evolution.

Structural variants are one of the major source of mutations in DNA. Examining their impact on mutational landspace over time has many applications such as understanding treatment response (why patients response to therapy differently), better disease prognosis (by identifying patterns of structural variants over time) as well as clinical applications (drug targets).

For more information, please check Ewing Research Group and/or contact me.

References:

[1] Bray, Laura J., Dietmar W. Hutmacher, and Nathalie Bock. “Addressing patient specificity in the engineering of tumor models.” Frontiers in bioengineering and biotechnology 7 (2019): 217.