Through their lens: Alexander Seutin learns how computer technology can help unlock secrets of blood cancers

This summer we’re sponsoring high school interns in stem cell labs throughout California. We asked those students to contribute to our Instagram photos and YouTube videos about life in the lab, and write about their experiences.

Alexander Seutin did a stem cell research internship this summer in the laboratory of Ravi Majeti at Stanford University.

This summer I worked at the Stanford school of medicine, conducting research in a lab run by principal investigator, Ravi Majeti in the stem cell department. We focus on a group of hematopoietic clonal disorders called myeloproliferative neoplasms. These blood disorders are characterized by their unregulated trilineage proliferation in myeloid cells, resulting in irregular hematopoiesis, often leading to many other complications down the line.

This category of diseases was first discovered in 1951 by William Dameshek who called attention to the morphologic similarities between chronic myeloid leukemia, polycythemia vera, essential thrombocythemia and primary myelofibrosis. In the years to follow, stem cells would emerge at the forefront of science and people would realize that these diseases produce cells that share a similar hierarchy to the healthy hematopoietic stem cell. It was then that people began to think about a leukemia or cancer stem cell.

In my project I analyzed gene expression data from microarrays run on these types of stem cells taken from individuals who have obtained one of these disorders. I then had to figure out how to interpret this immense quantity of data that had been given to me and it was then that I began to gain a real appreciation for what we are doing. I learned how to use many bioinformatics tools such as DAVID, gene expression commons, gene set enrichment analysis, hierarchical clustering, and many others all while gaining a deeper insight as to what I was actually doing. This insight not only allowed me to utilize these skills within my own project but also permitted me to gain a more universal understanding of modern science.

I slowly began to become more comfortable with my field through reading scientific papers, attending lab meetings, and by doing research on my own. This then allowed me to absorb more and more information about what people are presently doing which would not only show me how amazing the things we are doing are but more importantly teaching me that there is a giant window of opportunity in research, opened by modern technology, computer programming and the whole of bioinformatics. It is one that my generation will have to learn to exploit, hopefully allowing us to discover something great.

Alexander Seutin


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