Objective 1

Understanding how and where DNA mutations occur. Lifestyle habits and the microbiome can be genotoxic and leave an imprint on tumor DNA. The immune system can shape the mutational landscape as well by weeding out cells with certain mutations (a theory called the “neoantigen theory”). Additionally, DNA-intrinsic features such as the 3D conformation and the 2D base sequence favor mutations at certain loci.

Selected Publications:

1. Gurjao, C. et al. Discovery and Features of an Alkylating Signature in Colorectal Cancer. Cancer Discov. (2021) doi:10.1158/2159-8290.CD-20-1656
2. Gurjao, C. et al. Features and susceptibility to dietary-induced alkylating damage in colorectal cancer. Cancer Prevention Research. (2023) doi:10.1158/2159-8290.CD-20-1656

Objective 2

Leveraging mutational landscapes to inform clinical decisions. The FDA has been approving more and more cancer therapies and combinations of them. Despite being effective for several cancer types, their clinical use is encumbered by a high variability in patient response. Studying the mutational landscape of tumors can inform the best course of treatment and predict the aggressiveness of certain cancers.

Selected Publications:

1. C Gurjao et al. is tumor mutational burden predictive of response to immunotherapy?. Cancer Immunology Research 7, 1230–1236 (2019).
2. K Yang, Y Cao, C Gurjao*, Y Liu, CG Guo*, et al. Clinical and Genomic Characterization of Interval Colorectal Cancer in Three Prospective Cohorts. Gastroenterology 7, 1230–1236 (2019).

Objective 3

Adjusting methods to analyze and integrate genomic datasets. Large scale genomic data presents specific challenges, notably multiple hypothesis testing and variable selection. Formulating adjusted statistical models can provide meaningful insights into cancer biology.

Selected Publications:

1. Gurjao, C., Tsukrov, D., Imakaev, M., Luquette, L. J. & Mirny, L. A. Limited evidence of tumour mutational burden as a biomarker of response to immunotherapy. eLife (2020).