We’ve launched the ‘Researcher Spotlight’ series to shine a light on the work and varied career journeys of the researchers who publish with us. We want researchers to be able to share their own personal stories and help others draw inspiration and extract learnings that can serve as a guide for the next steps in their own careers. These interviews will provide
insights and advice from researchers in different career stages and fields, from those who are just getting started in research to more experienced researchers.
Dr. Chi-Ping Day, expert in cancer modeling and the translation of preclinical testing to clinics, provides advice to young researchers, shares how he keeps his team motivated, talks about the importance of societal impact in research and shares some of his career highlights.
I have two pieces of advice, so I guess you could say I’m giving my “two cents” (pun intended). First, no matter what the career goal she/he has, or even lacks, the most important thing is to build her/his “expert status” over time. What is “expert status”? Imagine that you are organizing a meeting and need to decide on a list of speakers. Which names appear in your mind immediately? You think of these people because you recognize them as the experts in that research field. This is the status she/he should strive for.
Expert status brings researchers opportunities in career development. For example, when a research institute recruits new faculty, it looks for an expert that can fit into a specific research program. When a grant proposal study session is planned, the organizer needs an expert in a particular subject. Even when submitting a manuscript to a journal, whether the author is an expert in the field may influence the reviewers’ attitudes.
The process of building an expert status benefits the researcher’s science, too. An expert needs to have deep insight into a specific field while also being able to connect her/his knowledge to a general audience. With these two goals in mind, a researcher can establish a knowledge structure surrounding a central hypothesis which prevents her/himself from seeking superficial “novelty” or short-sighted “ambulance chasing”, thus reaching expert status. I have seen many hard-working young researchers repeatedly miss opportunities, in both career and scientific development, because they were caught by the myth of being “productive” or getting that one “big paper”, but never understanding how to build their expert status.
My second piece of advice is to apply to job postings once every one or two years, either in industry or academia. The process of job seeking can make a researcher re-evaluate her/himself through self-reflection: what is my expert status?; how might my expertise be useful in other professions?; do I do academic research because of scientific enthusiasm or because I have no idea what else to do? It’s always important to find out what else is out there. You may find a new frontier for yourself, either in science or career development.
I always believe that if people learn the historical context of how we got to where we are, they will get the vision for where to go and take the next step. When I work with a young researcher to plan a new project, I will explain how the current idea was generated or derived from a previous study in our lab, and how the previous study is connected to the history of cancer research.
I always believe that if people learn the historical context of how we got to where we are, they will get the vision for where to go and take the next step.
For example, when making a mouse model of metastatic cancer, in vivo cycling (recovering the cancer cells from the metastatic site and re-implanting them into the primary site) is a common practice to derive a tissue-tropic cell line. This procedure was developed by Dr. Isaiah Fidler in the 1980s at NCI-Frederick. Dr. Fidler intended to test the “seed and soil” hypothesis of metastasis proposed by Dr. Stephen Paget in England in 1889. Dr. Paget devised his hypothesis by analyzing the distribution of metastases in breast cancer patients.
By following this history, you can see how a researcher in the 19th century generated an important hypothesis by careful observation and data analysis without involving complicated experimental design or advanced technologies. This led, after almost 100 years, to another researcher being inspired by the concept to develop a model system to test and prove the hypothesis, without requiring an immense investment of labor, and the result became a legacy that has impacted the whole field of cancer research. When a young researcher realizes how we can see farther by standing on the shoulders of a giant, she/he will see how she/he could grow to become a giant that lifts the next generation.
I am extremely lucky to have spent my whole scientific career in the Intramural Research Program of the U.S. National Institutes of Health which has a research budget allocated annually by the U.S. Government, so I have never had to consider issues about funding.
Having said that, I work together with many extramural collaborators who rely on research grants. In observing their research and publications, I found that successful researchers are very good at creating their scientific niche. This gets back to my thinking that building “expert status” in a specific research field will help in many ways, including securing funding.
In my mind, there are two studies that best represent my contribution to cancer modeling. The first addressed the antigenicity in animal models of luciferase and eGFP, two of the most frequently used cell-labeling markers. To resolve the issue of host rejection, I developed a transgenic mouse that was pre-tolerized to luciferase and eGFP (“glowing head mice”), preventing rejection of transplanted labeled cells. This study illustrated how experimental manipulation can interfere with the complex system of in vivo studies, skewing or even distorting study outcomes. It also gave an example of how to minimize the “observer effect” in biological studies.
In the second study , we developed multiple mouse models of melanoma. Using comparative analysis, we found that the responses of these models to immunotherapies were associated with their developmental status. We further demonstrated through genomic data analysis that this association was also relevant in human melanoma. This study showed that cancer modeling should be based on evolutionarily conserved pathways, especially developmental biology, so the results can be extrapolated to the clinic.
I am also very happy that these two studies generated reagents useful for the fields of melanoma and metastatic research, including three strains of glowing head mice, four mouse models of melanoma, and four cell lines derived from the models. They have become extremely popular and we have received many requests from research groups to use these models. By sending out these reagents, we have built many new collaborations nationwide and even worldwide, which have inspired new ideas and projects. These reagents have been deposited to the Jackson Laboratory and ATCC.
These two studies developed beyond our expectations because we wanted to address technical deficiencies in the field - consistent tracing of labeled tumors in vivo and mouse models that responded to immunotherapy more like human melanoma - rather than jumping into “big” questions. In other words, we wanted to use the right models before studying any mechanism. It turns out that we generated useful reagents for the field, and we used them appropriately to answer our experimental questions.
Retrospectively, I wish that I had understood the importance of immunological analysis and data analytics to cancer modeling from the beginning of these projects and collaborated with immunologists and computational biologists early on. We would surely have produced more translational insights from such collaborations.
In my mind, biology is unique among the branches of science because it connects the physical sciences with our lives. Biologists have the best opportunities to show society what life is and how the world works. I believe biologists need to take advantage of such opportunities to improve people’s lives. It’s our responsibility.
One of my favorite examples is the evolution of altruism and cooperation. Cooperation did not develop from the “noble” quality of complicated minds. It is the best evolutionary strategy, in a well-defined condition, to keep genes propagating. In contrast, vicious competition will only result in the collapse of the whole system. We learn this is true by observing nature and doing experiments. If people understand this, they may be more willing to improve the sustainability of our society, rather than accepting intentionally misguiding ideas, such as “the market can solve all problems”. This kind of understanding might result in better evidence-based policy.
Cooperation did not develop from the “noble” quality of complicated minds. It is the best evolutionary strategy, in a well-defined condition, to keep genes propagating.
I believe our societal impact comes from us caring about human issues. We must consider the implication of our research on people’s lives. The contemporary world is very noisy; I don’t anticipate that my studies can be found easily, even by biomedical scientists. However, we have to be prepared: make the message clear and comprehensible so that when people search for answers, the answers are there to help.
I believe our societal impact comes from us caring about human issues. We must consider the implication of our research on people’s lives.
It’s not important for me at all. However, I do hope that the concepts that I believe are important can be well received and disseminated. I think evolution is the genome’s way of modeling the world, and the organism is a kind of simulator. I hope I can write review articles on this topic someday and that people would find this idea useful.
The author would like to thank Dr. Sarah Spaeh for her editorial assistance.
Other Blogs you might find interesting:
Dr. Chi-Ping Day received his B.Sc. in chemistry from National Cheng-Kung University, Tainan, Taiwan in 1992 and his M.Sc. in biochemistry from National Yang-Ming University, Taipei, Taiwan in 1996. He then joined the Graduate School of Biomedical Sciences at the University of Texas Health Science Center at Houston and M.D. Anderson Cancer Center, where he received his Ph.D. in 2005 for his work on the development of a breast cancer-specific gene therapy system. In October 2005, he joined the laboratory of Dr. Merlino, National Cancer Institute, NIH, for his post-doctoral training. He was promoted to Staff Scientist in 2012 and then Associate Scientist in 2021.
Dr. Day is an expert in cancer modeling and the translation of preclinical testing to clinics, focusing on immunotherapy and its combination with other treatments. His research emphasizes modeling as an approach of data integration to map a complex system through a process of continuous improvement. He has generated a series of mouse models of melanoma, cell lines, and cell-labeling vectors that have been used in many research groups worldwide.
Dr. Day founded the NIH Interspecific Modeling Interest Group. He received the 2007 NCI Director's Innovation Award, the 2018 Staff Scientist and Staff Cilinician Outstanding Mentor Award, and the 2020 Staff Scientist and Staff Clinician Scientific Merit Award. He is also Co-PI on an NCI FLEX Award project, "Preclinical Development of Immunotherapy for Brain Metastasis".