Jason PITT

Cancer is a disease with multifactorial etiology. Environment, lifestyle, and genetics are well-known mediators of oncogenic cellular transformation. However – with respect to individual malignancies – the relative contributions of these factors are difficult to discern and require knowledge derived from massive, multivariate datasets. Accordingly, the Pitt laboratory’s research program has two major aims: 1) the development of state-of-the-art software to facilitate data-intensive genomic analyses; and 2) the integration of inherited genetic variation, acquired mutations, and epidemiology to better understand cancer susceptibility and tumorigenesis. Using data science to unravel cancer’s origins can ultimately sharpen screening, early detection, and prophylactic treatment programs that are crucial to precision oncology.

The world is an ecosystem flooded with data. Tech giants such as Google, Amazon, and Facebook have capitalized on this resource by transforming torrential data streams into actionable intelligence. Advances in biotechnology have fostered a similar data niche in cancer genomics, which offers considerable scientific returns to those able to exploit it. As such, our laboratory develops software that enables cancer genome analyses to be performed at scale. These tools include SwiftSeq (https://github.com/PittGenomics/SwiftSeq), a highly-parallel computational workflow for processing DNA sequencing data on clusters, supercomputers, and clouds. In an effort to further increase throughput and minimize expenditures, some of our continued work emphasizes cost profiling and optimization of genomic workflows on commercial cloud platforms. Processing, however, is only one aspect of data-driven science. We are also constructing novel analytical tools that facilitate quick and efficient interrogation of structured genomic data.

Importantly, the aforementioned software initiatives are driven by the desire to discover impactful biology. Our laboratory also leverages large cancer datasets to unravel the intricacies of germline and somatic cancer genetics, often through an epidemiological lens. Using over 8,000 germline exomes from The Cancer Genome Atlas, we have shown that age at cancer diagnosis is negatively associated with the number of harmful alleles within known cancer risk genes. Along with extramural collaborators, we have explored the breast cancer mutational landscape (exomes and genomes) across more than 1,100 racially and ethnically diverse women. Individuals with African ancestry – particularly Nigerians – were more likely to harbor aggressive molecular features, which is consistent with known clinical differences. Our work continues to utilize germline and somatic DNA sequencing data to enhance understanding of cancer susceptibility, early clonal expansion, and disparities amongst populations.

Selected Publications:

  1. Baughman, M., Chard, R., Ward, L., Pitt, J. J., Chard, K., & Foster, I. T. (2018). Profiling and Predicting Application Performance on the Cloud. IEEE Utility and Cloud Computing. In Press.
  2. Pitt, J. J., Riester, M., Zheng, Y., Yoshimatsu, T. F., Sanni, A., Oluwasola, O., … Barretina, J. (2018). Characterization of Nigerian breast cancer reveals prevalent homologous recombination deficiency and aggressive molecular features. Nature Communications, 9(1), 4181.
  3. Pitt, J. J., Zheng, Y., & Olopade, O. I. (2018). Genetic Ancestry May Influence the Evolutionary Trajectory of Cancers. Cancer Cell, 34(4), 529–530.
  4. Pitroda, S. P., Khodarev, N. N., Huang, L., Uppal, A., Wightman, S. C., Ganai, S., Joseph, N., Pitt, J. … Weichselbaum, R. R. (2018). Integrated molecular subtyping defines a curable oligometastatic state in colorectal liver metastasis. Nature Communications, 9(1), 1793.
  5. Cheng, J., Demeulemeester, J., Wedge, D. C., Vollan, H. K. M., Pitt, J. J., Russnes, H. G., … Van Loo, P. (2017). Pan-cancer analysis of homozygous deletions in primary tumours uncovers rare tumour suppressors. Nature Communications, 8(1), 1221.
  6. Huo, D., Hu, H., Rhie, S. K., Gamazon, E. R., Cherniack, A. D., Liu, J., Yoshimatsu, T., Pitt, J.J. … Olopade, O. I. (2017). Comparison of Breast Cancer Molecular Features and Survival by African and European Ancestry in The Cancer Genome Atlas. JAMA Oncol. https://doi.org/10.1001/jamaoncol.2017.0595
  7. Camps, J., Pitt, J. J., Emons, G., Hummon, A. B., Case, C. M., Grade, M., … Ried, T. (2013). Genetic amplification of the NOTCH modulator LNX2 upregulates the WNT/β-catenin pathway in colorectal cancer. Cancer Research, 73(6), 2003–2013.
  8. Huppi, K., Pitt, J. J., Wahlberg, B. M., & Caplen, N. J. (2012). The 8q24 gene desert: an oasis of non-coding transcriptional activity. Frontiers in Genetics, 3, 69.
  9. Hummon, A. B., Pitt, J. J., Camps, J., Emons, G., Skube, S. B., Huppi, K., … Caplen, N. J. (2012). Systems-wide RNAi analysis of CASP8AP2/FLASH shows transcriptional deregulation of the replication-dependent histone genes and extensive effects on the transcriptome of colorectal cancer cells. Molecular Cancer, 11, 1.
  10. Mackiewicz, M., Huppi, K., Pitt, J. J., Dorsey, T. H., Ambs, S., & Caplen, N. J. (2011). Identification of the receptor tyrosine kinase AXL in breast cancer as a target for the human miR-34a microRNA. Breast Cancer Research and Treatment, 130(2), 663–679.
Name Jason PITT
Affiliations Special Fellow, Cancer Science Institute of Singapore, NUS
Email jason.j.pitt[at]nus.edu.sg


Institute Degree (if applicable) Year(s)
University of Chicago, Chicago, IL, USA Ph.D. 2017
Gustavus Adolphus College, St. Peter, MN, USA B.A. 2009

Professional Experience

Special Fellow, Cancer Science Institute of Singapore, NUS 2018 – Present
Post-baccalaureate Fellow, Genetics Branch, National Cancer Institute, USA 2009 – 2011

Yi (Leo) HSIAO

HLA-TW Intern

After earning double degrees of Electrical Engineering and Chemistry, Yi completed a Master’s degree in Bioinformatics at National Taiwan University. There he assessed quantitative models depicting the relationship between drug molecular structure. In our group, he is applying his software development and bioinformatics skills to build a voice-based, virtual assistant for cancer genome analyses.

Wenning ZHENG

Research Associate

Wenning earned her Bachelor of Bioinformatics with Honours from Multimedia University and later completed her PhD in Bioinformatics at the University of Malaya. She currently is characterizing the genetic etiology of the rare cancer types extranodal NK/T-cell lymphoma (NKTL), nasal type NKTL, and peripheral T-cell lymphoma.

Charles J. Epstein Trainee Award for Excellence in Human Genetics Research – Finalist (American Society of Human Genetics) 2016
Partners in International Research (PIRE) Fellow (National Science Foundation) 2012
Genetics and Regulation Training Grant recipient (University of Chicago) 2011-2014
Rupert Anderson Award for Research (Gustavus Adolphus College) 2009
Presidential Research Grant (Gustavus Adolphus College) 2008
Mayo Clinic Scholars Program 2007-2008