The future of science lies in the hands of the next generation of researchers. Cancer Grand Challenges aims to develop a cohort of brave, daring future leaders who are willing to unite and challenge the status quo – whatever their discipline and wherever they are in the world. Chelsea Nikula (chemist and higher research scientist) and Rory Steven (analytical chemist and senior research scientist), two early-career researchers helped identify SLC7A5 as a target for KRAS-driven colorectal cancer, answered questions about the project.
What is your role within the Rosetta team and this project?
Chelsea: I’m a chemist working in mass spectrometry imaging (MSI). For this particular work, I used matrix assisted laser desorption ionisation (MALDI) and desorption electrospray ionisation (DESI) MSI to analyse samples before assisting in the data processing. I’m very interested in how we can apply MSI techniques to the investigation of complex biological systems.
Rory: I’m an analytical chemist, working primarily in the fundamentals of MSI and its application in biological research. My contribution to this work has been acquiring MALDI and DESI MSI data, associated data analysis and helping to coordinate communications between team members and institutions.
How has the multidisciplinary, collaborative nature of the Rosetta team contributed to these findings and the team’s work?
Rory: A huge part of working on a large interdisciplinary project is effective communication – both in the context of technical discussions and on a more administrative level. Learning to speak one another’s language is key. It’s here that many of the challenges of interdisciplinary working occur, but the benefit of these interactions is massive. As an analytical scientist, I depend on the knowledge and insight our biologically focussed partners bring.
Chelsea: Having close working collaborations with cancer biologists, data scientists, chemists and physicists within our Cancer Grand Challenges team is incredibly beneficial, bringing unique perspectives to the complex datasets we produce. The mix of expertise enhances the interpretation of our results and means we gain a better understanding of our MSI data in relation to biological impact – which is absolutely crucial when forming hypotheses and conclusions. This paper illustrates the high impact science that can be achieved through highly multidisciplinary collaborations.