We apply computational approaches to study cancer evolution from a translational perspective.
Our mission is to understand cancer evolution at the molecular level, and to build tools and develop methods that use this information to improve patient treatment.
Nicolai Birkbak has a background in cancer biology, biomarker development, translational cancer research and cancer evolution and heterogeneity based on research undertaken at Technical University of Denmark (PhD and postdoc), Dana-Farber Cancer Institute (postdoc), and University College London & the Francis Crick Institute (senior postdoc).
An essential question in cancer research today and a focus of our research is understanding the key steps in carcinogenesis: how cells develop from a normal state to malignant cancer through benign, invasive and metastatic disease.
Over recent years, exponential drop in Next Generation Sequencing costs coupled with significant investment in cancer research has led to the creation of large cancer cohorts with extensively characterized tumor samples. This effort has improved our understanding of cancer as a molecular disease, but a focus on driver events has so far not led to a breakthrough in patient therapy, and patient survival has not significantly benefited.
Clonality and treatment
Our lab utilizes cancer NGS data and computational tools to mine the developmental history on individual cancers, and to determine clonality of events. In this manner, we aim to describe the order of carcinogenic events as probabilities that depend on past driver acquisitions. This will allow us to construct evolutionary trajectories for individual cancer types, potentially informing about likely changes malignant cells may be biased towards when subjected to anti-cancer therapy. This opens the door to therapeutic approaches where treatment may be directed towards likely cancer clones not yet observed in a given sample.
- Turajlic S, Xu H, Litchfield K, Rowan A, Horswell S, Chambers T, O'Brien T, Lopez JI, …, Birkbak NJ, Wilson GA, Pipek O, Ribli D, Krzystanek M, Csabai I, Szallasi Z, Gore M, McGranahan N, Van Loo P, Campbell P, Larkin J, Swanton C; TRACERx Renal Consortium (2018) Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal. Cell. 2018 Apr 19;173(3):595-610.e11. doi: 10.1016/j.cell.2018.03.043.
- Birkbak NJ, Li Y, Pathania S, Greene-Colozzi A, Dreze M, Bowman-Colin C, Sztupinszki Z, Krzystanek M, Diossy M, Tung N, Ryan PD, Garber JE, Silver DP, Iglehart JD, Wang ZC, Szuts D, Szallasi Z, Richardson AL (2018) Overexpression of BLM promotes DNA damage and increased sensitivity to platinum salts in triple negative breast and serous ovarian cancers. Ann Oncol. 2018 Feb 14. doi: 10.1093/annonc/mdy049.
- Jamal-Hanjani M*, Wilson GA*, McGranahan N*, Birkbak NJ*, Watkins TBK*, Veeriah S*, …, Swanton C; TRACERx Consortium (2017) Tracking the Evolution of Non-Small-Cell Lung Cancer. N Engl J Med. 2017 Jun 1;376(22):2109-2121. doi: 10.1056/NEJMoa1616288. Epub 2017 Apr 26. PMID: 28445112
- Marquard AM*, Eklund AC*, Joshi T, Krzystanek M, Favero F, Wang ZC, Richardson AL, Silver DP, Szallasi Z, Birkbak NJ (2015) Pan-cancer analysis of genomic scar signatures associated with homologous recombination deficiency suggests novel indications for existing cancer drugs. Biomark Res. 2015 May 1;3:9. doi: 10.1186/s40364-015-0033-4. eCollection 2015. PMID: 6015868
- Murugaesu N*, Wilson GA*, Birkbak NJ*, Watkins TBK*, McGranahan N*, Kumar S, Abbassi-Ghadi N, Salm M, Mitter R, Horswell S, Rowan A, Hochhauser D, Hanna GB, Swanton C (2015) Tracking the genomic evolution of esophageal adenocarcinoma through neoadjuvant chemotherapy. Cancer Discov. 2015 Aug;5(8):821-31. doi: 10.1158/2159-8290.CD-15-0412. Epub 2015 May 23. PMID: 26003801
- Favero F*, McGranahan N*, Salm M*, Birkbak NJ*, Sanborn JZ, Benz SC, Becq J, Peden JF, Kingsbury Z, Grocok RJ, Humphray S, Bentley D, Spencer-Dene B, Gutteridge A, Brada M, Roger S, Dietrich PY, Forshew T, Gerlinger M, Rowan A, Stamp G, Eklund AC, Szallasi Z, Swanton C (2015) Glioblastoma adaptation traced through decline of an IDH1 clonal driver and macro-evolution of a double-minute chromosome. Ann Oncol. 2015 Mar 2.
Tracking cancer in vivo
To utilize our improved understanding of cancer therapeutically, properly characterizing and tracking cancer evolution in real time is vital.
While a tissue biopsy remains the most informative, it cannot be performed at high frequency due to costs and discomfort. Non-invasive technologies such as liquid biopsies and radiomics analysis of medical imaging data are comparatively cheap and can be performed at high frequency.
By developing cancer-type specific assays it may be possible to characterize both cancer biology and treatment response in real-time, providing the treating clinician with crucial information about how to intervene, and when.
- Abbosh C, Birkbak NJ, Swanton C. (2018) Early stage NSCLC - challenges to implementing ctDNA-based screening and MRD detection. Nat Rev Clin Oncol. 2018 Sep;15(9):577-586. doi: 10.1038/s41571-018-0058-3. Review. PMID: 29968853
- Abbosh C, Swanton C, Birkbak NJ(2018) Circulating tumour DNA analyses reveal novel resistance mechanisms to CDK inhibition in metastatic breast cancer. Ann Oncol. 2018 Mar 1;29(3):535-537. doi: 10.1093/annonc/mdy017. No abstract available. PMID: 2935157
- Abbosh C*, Birkbak NJ*, Wilson GA*, Jamal-Hanjani M*, Constantin T*, Salari R*, Le Quesne J*, …, TRACERx consortium; PEACE consortium, Swanton C (2017) Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature. 2017 Apr 26;545(7655):446-451. doi: 10.1038/nature22364. PMID: 28445469