Lorenzo Ferrando: Welcome to TJ Talks – Conversation about Oncology by Tumori Journal, the peer-reviewed oncology journal dedicated to the dissemination of key oncological themes and advancements. I am Professor Lorenzo Ferrando, Section Editor at Tumori Journal, and in this episode I’m really happy to meet Professor Matteo Benelli, Associate Professor of Biochemistry at University of Florence. Matteo, thank you for being here with us today.
Matteo Benelli: Thank you, Lorenzo, for the invitation. It’s really a pleasure to be here and to talk with you about what I think is partly our shared passion.
Lorenzo Ferrando: Yes, indeed. So, Matteo, the first question for me would be what led you to specialize in bioinformatics?
Matteo Benelli: Well, thank you, Lorenzo, for the question. It was really an opportunity that happened by chance, I would say, because I was finishing my master’s degree in Nuclear Physics when I heard about a group at Careggi Universital Hospital that is the main hospital here in Florence that was offering a sort of predoctoral fellowship in what at the time was an emerging field, the bioinformatics. And I have to say that I didn’t know anything about bioinformatics at the time. But then, as you can imagine, studying nuclear physics, I had some programming experience because I knew how to analyze and interpret massive amounts of data. So, I took this opportunity and started working with R, a programming language that was new to me at the time and start analyzing data from high throughput technologies that it was back in 2008. So more than 15 years ago. And so, the dominant technology at the time were microarrays, then were followed by NGS. And after that, I joined an exciting PhD Program at University of Florence that was called Non-linear Dynamics and Complex Systems. That was really a multidisciplinary because we were physicists, biologists, psychologists, mathematicians that collaborate to study and solve complex systems. And you know that biological systems are maybe the most fascinating example of this complexity. So, to conclude, the course of the career that led them to specialize in bioinformatics, then after my PhD, I moved to the laboratory of Francesca De Michelis at University of Trento, because I wanted to really specialize in a specific field that is Cancer “Omics”. And that experience was incredible because it really shaped my approach to research. And the two years that I spent there were fantastic. I had the chance to contribute to really important studies primarily focus on advanced breast cancer. And I would say that consider that experience may be the most important one in defining my career, because after that I had clear ideas that I wanted to do exactly that work.
Lorenzo Ferrando: So, I think that it’s a very interesting and rich journey, like citing a very famous song. It’s a long way if you want to do bioinformatics basically. Right?
Matteo Benelli: Yes. Very long.
Lorenzo Ferrando: Yeah, but really exciting. So, you are the Co-Principal Investigator of AURORA, which is an international research program with a very important aim, which is improving the knowledge of the molecular mechanisms leading to response or resistance to therapy. Metastatic breast cancer patients are a very important effort from Europe and from several labs here in Italy, Belgium and Spain. So, what led you, what inspired you to join the AURORA program?
Matteo Benelli: Yes. You know, AURORA is an incredible effort and incredible project. And my involvement in AURORA is thanks to one person who changed the following course of my career, who was Angelo Di Leo. Because indeed, after completing my Postdoc at University of Trento, I moved to the oncology department at the hospital of Prato that was led at the time by Angelo, who was a really an internationally renowned breast cancer oncology. And he offered me an incredible, and I would say, unexpected opportunity that was to establish my first lab, the focus on bioinformatics and cancer omics. And this was especially, um, surprising because Prato, that is my hometown, is known for its textile industry, not cancer research. And so, I took this opportunity and started my first lab there. And while I was running the lab, Angelo invited me to join AURORA as an expert bioinformatician because Angelo at the time played a key role in the Breast International Group, that is the organization that coordinates this study and working on AURORA. You know, Lorenzo also, I think is and was at the time an exciting experience because it brings together a multidisciplinary team of clinicians, molecular biologists, bioinformaticians, pathologists. And the project is unique because, as you mentioned before, it provides access to primary tumor metastasis. And we generated the data multi-omics profiling of these samples to better understand how breast cancer develops resistance to human therapies, and which are the molecular alterations that characterize metastasis. At the beginning, we work very hard for two, maybe three years, and our work led to the first publication of this project that was published in Cancer Discovery. So, what was the path that led me to assume the role of Pi? This was quite incredible for me because at the time, AURORA was led by two clinical co-pis. And after the manuscript was published, I think that, you know, our work received recognition. And I think that it became clear to the Breast International Group that a more technical, non-clinical lead, was also essential to move the project forward. And so I was invited to join AURORA as also as Co-pi.
Lorenzo Ferrando: Yeah. I think that the fact that you join the AURORA program as Co-pi is like a great opportunity for the right person, the right moment for the right person. And I think that it is clear that bioinformatics is getting more and more central and relevant in this kind of cancer research. So how does bioinformatics, in your opinion, contribute to understanding the evolution of breast cancer, especially in identifying new therapeutic targets? And especially can you share if you can, of course, some of the most exciting findings that your team has made so far.
Matteo Benelli: Yes, I agree completely with you, Lorenzo. Bioinformatics has become an essential tool for studying cancer. AURORA is a prime example. And because I think because it enables to deal with the complexity of cancer. For instance, helping us to understand the emergence, the evolution, response to treatments, identifying new therapeutic targets, as you mentioned before. And this is because today cancer research relies on high throughput biotechnologies such as sequencing that we use every day, but also some new technologies that we are approaching in the in the last years that are imaging techniques that generate a data set, including thousands to millions of variables. And bioinformatics has the tools, the methodology that can deal with this complexity, but also enable to identify the most relevant features among these huge amounts of data. And the AURORA, which you mentioned before, is an example of how our expertise is essential in understanding how breast cancer develop resistance to therapy, for instance, because with our methodology, we are able to integrate multiple data to analyze simultaneously different layers of molecular information, such as genomics, transcriptomics. Because our goal in this project is to investigate molecular alterations acquired by tumors, to identify those that could be targeted by specific treatments. But in general, in addition to AURORA, the primary focus of the research of my group is in precision medicine, precision oncology. And among the most exciting findings you were referring to, I would like to mention that we work hard on circulating biomarkers. You know very well, particularly to the study of epigenetic alterations such as DNA methylation. We know, you know, that the liquid biopsy, especially the analysis of circulating tumor DNA. That is, these fragments of DNA released by tumors into the bloodstream is exciting and is an emerging tool for monitoring disease status in patients with cancer. So we are working on developing new methods that are both from the lab point of view, but also computational, obviously, that exploit these epigenetic features to improve the technical aspects of this test, so to improve sensitivity and specificity of this assay, but also to going beyond, because we would like in the future to have a phenotypic characterization from these non-invasive tests, a sort of capability that is only mainly done on tissue biopsy. We would like to have the possibility to do this also in a non-invasive way.
Lorenzo Ferrando: Yeah. I think that we could continue discussing this kind of topics for the entire day. I mean, it’s really exciting, but as you said, I think it’s a matter of complexity. I mean, informatics is just a very central part of cancer research, and it’s very complementary to the other domain of knowledge biology, medicine and bioinformatics as a tool to unlock the capability to answer very complex questions because technology is evolving like super-fast. The data generated is getting huge, really difficult to handle to manage. So, informatics has the tool to answer this kind of new wave of complexity. You know.
Matteo Benelli: I agree. And uh, maybe the most important term for us is, and for us, studying cancer is multidisciplinarity. So orthogonal and complementary skills. So, this is very important. Bioinformatics plays a key role in complementing the division.
Lorenzo Ferrando: Yeah. In fact, the next question I was thinking about would be how do you think bioinformatics will shape the future of personalized medicine? But now the question after listening to you is how is shaping the present right of personalized medicine?
Matteo Benelli: Yeah, I think that I agree with you that will and is playing a central role in cancer research and in personalized medicine. And let’s think about, for instance, the Molecular Tumor Board. Now are defined as multidisciplinary because they are, in terms of clinics, multidisciplinary. But imagine that in a near future these boards will involve clinicians as currently are involved in from different disciplines, but also molecular biologists, bioinformaticians that will help a clinician to interpret the results that they have, for instance, received from a comprehensive cancer gene panel test where hundreds of cancer genes are screened, but only few alterations are important to decide on the management of the patient. So, I think that this integration of our skills in these boards will happen soon. Hopefully soon, will happen for sure, but I hope also soon.
Lorenzo Ferrando: Yeah. You talked about the very hot topic here, the MTB right. Uh, let’s discuss a little bit about what does it mean to be a principal investigator, a Pi, in this country, in Italy. And how do you see the future of bioinformatics in this country? What are the challenges? You know, being performative and especially a principal investigator in bioinformatics?
Matteo Benelli: Yeah. So compared to the other countries that we know very well, Europe and also US, one consideration that we can do is that we are few.
Lorenzo Ferrando: True! Unfortunately, it’s true.
Matteo Benelli: Especially in relationship to the needs at least talking about the academic research. So, I think that this is due to the absence of specific academic course for sure, but also maybe most importantly, to the absence of a biotech industry, a solid biotech industry that is able to employ people with our skills out of academia. You know that being few can be seen as you are in a privileged condition because it’s easier to collaborate with other colleagues. But I think this has also some negative aspect related, for instance, to a limited competition that is usually not beneficial for improving the quality of the field. In some cases, your collaborators tend to consider you as a sort of service for their project. And this is really a problem for us because this situation limits the definition of bioinformatics as a valid research field. However, you know that being a Pi also means carrying on research projects and managing the lab, searching for funds. And I have to say that in Italy we are lucky because the Italian Association for Cancer Research is really a pillar for supporting us in our everyday work life, because they provide hundreds to thousands of researchers with the funding to conduct cancer research, including also researchers in the field of bioinformatics. And I am a recipient of a grant from ERC. So, I’m incredibly grateful for their support that they provide us for our activities. But, you know, regarding how I see the future of variable informatics in Italy, or last part of the question, I see it, I would say as bright because I’m optimistic for my group for sure, because I have a fantastic group of young researchers, both wet and dry, who work really with dedication and commitment. So, I am sure we will do some exciting work in the future. For the bioinformatics in general, I think it will be bright because the need for these skills will increase in the future. And I think also that we will assist a more balanced representation of computational water researchers in the in the future. But however, we also have to talk about some obstacles that we have in Italy. And we, Lorenzo, we discussed this a little bit in the past out of this podcast, because, you know, that Italy has some rigidity in the, in the system because it requires you to be, um, I mean, sort of labeled into specific categories, no disciplinary categories. So molecular biology, oncology, genetics, biochemistry. But our work is interdisciplinary per se. So, the categories do not easily apply to us. And we should work in some way to try to dismantle this bureaucratic rigidity and just let the research flow.
Lorenzo Ferrando: Yeah. I think that you touched a very relevant issue here because informatics being so hybrid, you know, touches different fields of from biology to medicine. So my hope and I think it’s your hope as well, is that in the future institutes the governments will be a little bit more elastic, let’s say, and will be more inclusive and maybe will Recognize officially in public institutes, hospital, etc. the professional figure of the Bioinformatician, which is now a little bit, you know, it’s not that easy to include and offer a long term job as a Bioinformatician is in a public institute. So, let’s see how the future will shape this next generation figure of researcher.
Matteo Benelli: I agree, Lorenzo, I think it will happen with some delay, obviously, because we are in Italy, but this is a real need, so in some way will happen.
Lorenzo Ferrando: Yeah, the need is there. So, let’s see. In the meantime, technology advances and as you know better than me, everyone like everyone is talking about AI and its use. So related to bioinformatics, what is the role of AI in analyzing big data and in this case big genomic data? Are there any emerging technologies or approaches that you are particularly excited about?
Matteo Benelli: Yeah, I agree with you that today AI has pervaded our language because everything is AI, but maybe nothing is important. Or I would say cool without AI, you know, you can stay out of AI because we have seen incredible stories of success of using AI in medicine, pathology, genomics. But these results have created an enormous hype around AI and obviously in our field. So, I think that we were in some way experts of AI, and we have always worked with different forms of AI, including also the classical machine learning, for instance, in the past. We have unethical role in not promoting too much AI. For instance, in cases where AI is not needed because you know that in some way it can be, AI has some disadvantages compared to other more classical approaches. And I think that there are many also of these disadvantages. One maybe the most important is that it depends on training using a huge amount of data to train these that are called the models now that are the core of the AI. But these models now in particular, if you think about the diagnostic test that exploit AI are proprietary of private biotech companies that are the only that have the budget to create them. So, think about, for instance, our health system. This situation could create some issues related to the dependency that our health system can in some way have with this private company. So, to be clear, I am a fan and supportive of AI, but only when it is needed. In other cases, let’s try to stay with more simple and also explainable approaches, because also explainability is a huge problem. I think that we are going to lose with some AI approach in the future.
Lorenzo Ferrando: Again, super interesting topic here because AI is really pervasive. Like everyone can use it, but whenever you talk about AI in diagnostics and etc., there is no competition. There is this gigantic investment in private companies developing tools. And they are really, really, really hungry for new data. And it can happen sometimes that public hospital can sell data sometimes, not sell is not the right word, but you know there must be some regulation between these private companies hungry for new data, hungry to develop new models and the data, and the data are of the people. Right? It’s a very interesting but complicated.
Matteo Benelli: Also, I have no mention. I did not mention another maybe limitation with the AI. That is the I have some doubts about some the issue of reproducibility because AI works very well when the context is clearly defined. No? The models are built on some training data that depends on some specific, for instance, assays, some specific technologies. But is it possible to translate this assay from the central lab in these private companies to a hospital? So how the model translates and how the model performs when we translate from the private company to the hospital? This I think it’s an open question. It’s problematic for the future.
Lorenzo Ferrando: True. So, you are a professor at University of Florence. Your lab is plenty of brilliant young researchers and students, but your lab is not the most common bioinformatics lab in this country, right? So, there are not so many labs like yours. And what advice would you give to young researchers who want to enter this field?
Matteo Benelli: I would have many advices, but maybe the most important one is to be prepared to work at the boundaries of many disciplines and languages, because our main role, if I have to define a single one, is to first understand or ask ourself a diagnostic, clinical or molecular question, then exploit our skills, our knowledge to solve this problem using computational statistics and mathematical strategies. And then we have to translate back the results that we obtained to molecular biologists, clinicians and so. So, we have to learn multiple languages because a clear communication between the declinations, the molecular biologist, for instance, and us is essential because we have to reach together the goal of solving some clinical question. And knowing multiple languages means also knowing multiple disciplines, or at least the discipline bioinformatics is applied to. So, I would suggest to interested students, researchers coming from computer science, engineering, physics, mathematics, statistics, study biology or medicine. The other way around, for those coming from biology, biotechnology and medicine, study statistics and computer science.
Lorenzo Ferrando: Yeah, I think that you said it perfectly. I mean, don’t be afraid. One student studied biology, right? Okay. Now, after finishing the university, if you want to do bioinformatics, he must study statistics and sometimes can be, you know, let’s say not trivial, right? And the other way around. And in my opinion, sometimes it’s more difficult the other way around. So, a Stem guy wants to study a little bit of cancer biology. So, it’s difficult at the beginning, but it’s really rewarding.
Matteo Benelli: Yeah. You have to be very committed, dedicated. But I think that at the end the results are clear.
Lorenzo Ferrando: Yeah, absolutely. Matteo, we are going to the end of this very nice and super interesting conversation. But where can people follow your work and learn about these really exciting AURORA program?
Matteo Benelli: Oh yes. Lorenzo, thanks for the question. So, you can have a look at my research group on the website of my university department in Florence. The site is sbsc.unifi.it. You can follow me and all news about the research we are doing on LinkedIn, my personal page. While regarding AURORA, there are much information on the website of the Breast International group that coordinate the study. The website is big against cancer.org. If you are interested, you can read the first manuscript that was published on Cancer Discovery a few years ago. It’s very easy to retrieve from PubMed, Google scholar, first name is Philippe Aftimos. He’s a friend of mine and co-pi of the study. But also, for other many, many new exciting findings from AURORA, I am sure you will hear very soon.
Lorenzo Ferrando: So, to all the listeners, I really encourage to follow Matteo because there are some very interesting surprises, let’s say, or publication in the really next future. So, it has been my pleasure to have you here. Thank you so much for being with us on TJ Talks.
Matteo Benelli: Thank you again, Lorenzo. And it was really a pleasure also for me chatting with you.
Lorenzo Ferrando: In this episode we found out how bioinformatics is transforming oncology from understanding breast cancer at the molecular level to uncovering new therapeutic targets. Professor Matteo Benelli shared insights from the AURORA program and highlighted the impact of AI on personalized medicine. We also explored the future of bioinformatics in Italy and heard valuable advice for the next generation of researchers. TJ Talks is available on our website tumorijournal.org and on the best podcast platforms. Follow us on X and LinkedIn to always be updated on cancer research and clinical practice in oncology. I am Professor Lorenzo Ferrando, Section Editor at Tumori Journal. Thanks for listening!