P53. Dr. Moshe Oren directs the Moross Center at the Weizmann Institute.

Moshe Oren, director of the Moross Integrated Center for Cancer Research at the Weizmann Institute in Israel, is one of the pioneers in the study of the p53 gene, one of the most determining in the development of tumours.

Researcher Moshe Oren (73) was involved in isolating the p53 gene in the early 1980s, when scientists such as Mariano Barbacid from Spain began to identify the first cancer-linked mutant genes. From the outset, it was clear that this gene played a key role in the development of many tumors and, after years of work, p53 was identified as ” guardian of the genome ”, responsible for avoiding the cellular imbalance at the origin of cancer.

The work of Oren, who emigrated to Israel during the 1950s, contributed to the understanding of the role played by the p53 protein in maintaining normal cell growth. Tumors appear when certain cells do not assume their programmed obsolescence and instead of dying when necessary, they continue to reproduce without any control. Often, for good reason, the p53 has mutated and therefore ceases to exercise its function of killing cells according to the process known as apoptosis.

The description of cancer as a genetic disease and of the molecular processes at its origin has made it possible to develop new therapeutic methods. Around the world, the main research centers on these conditions combine this research in fundamental biology with the search for solutions to this type of disease. Currently, Oren directs the Moross Integrated Center for Cancer Research at the Weizmann Institute, Israel. This multidisciplinary institution seeks to shed light on cancer with a view to treating it. Last week, researchers from this entity and the National Cancer Research Center (CNIO) met at the headquarters of the Ramon Areces Foundation, in Madrid. The meeting organized by the three institutions aimed to share their advances in understanding the mechanisms that stimulate cancer.

EL PAIS-. For many years, it has been known that cancer corresponds to a plethora of diseases, including that the same patient may present with several tumours. From this fact, should we deduce the need to fight a significant number of diseases, to be treated separately? Or can we hope for a certain theory of unification allowing us to detect common elements in order to simplify cancer treatments?

Moshe OREN -. We are moving in this direction. On the one hand, we now have tools for analyzing complexity, which obviously increases as we use them. For the same type of cancer, many differences are observed between patients, as well as between tumor cells of the same subject. The challenge is to bring all this information together and find common denominators.

It is impossible to come up with a single treatment for cancer. However, we also don’t want to ultimately need a million cancer cures. Moreover, we can only specify these common denominators if we understand the complexity, by making groupings, and by identifying the commonalities of a specific group of tumor mutations, and then figuring out how to treat patients with a limited number of treatments. . I think ultimately we’re going to be able to intelligently use a limited number of combination treatments.

What are the obstacles to achieving these goals?

The main challenge to be met in order to establish the link between our knowledge and the actions that are within our reach is linked, for the time being, to the absence of adequate treatments in the face of many of the alterations present in the case of cancer.

For each patient, the tumor can now be analyzed. Companies and large medical centers offer this service. They examine 100, 200, even 300 genes, and are able to identify mutations known to play a decisive role in the development of cancer. However, for most of these alterations, treatments are non-existent. Also, on the one hand, we want to reduce our knowledge gaps and find treatments for several types of mutations. On the other hand, we want to uncover the common biological implications of a specific group of mutations in order to predict whether it will respond selectively to available drugs.

In my opinion, efforts should focus, on the one hand, on the development of new drugs, because it is clear that we lack targeted therapies. And on the other hand, we also want to take into account this multitude of data that we are producing, which indicate that cancer is in particular more complex than we imagined, that it is not a question of a disease, or even 300 diseases, and that it constitutes a spectrum, a continuum. Moreover, we want to exploit this complexity by using deep learning, artificial intelligence, to simplify it, and then provide this information to the hospital to administer a treatment. This, in my opinion, will be the way forward: identify and understand the complexity at the highest level, then try to simplify it in favor of practical treatments, which are not applied ad infinitum.

Is artificial intelligence already used for this purpose?

Yes, we are already using artificial intelligence to extract meaning from the data that emerges from our research, not just on cancer. But these are only the premises. The last 10 years have been marked by close collaboration between computer and data experts and cancer-focused researchers. This will be one of the tracks to overcome the obstacles. A slow process, which will however take a lot of momentum.

To fight cancer, is it necessary to understand all the mechanisms that underlie it? Or can we continue to seek solutions by trial and error?

It may not be necessary to try to understand everything. What does that mean ? I do not know. It is as if we were proposing to apprehend the whole universe. On the other hand, as our understanding improves, we will have more opportunities to avoid mistakes. The problem is that in the laboratory, we do have a few ideas: we take 20 mice, we apply a different treatment to them, then we make comparisons to then find the most effective remedy. However, in humans, this method is not possible.

Today, we administer a series of remedies to the patient when, unfortunately, he does not respond to the first-line treatment. But this situation is not ideal. It is therefore necessary to increase the probability that the initial treatment is the best that is available to the person concerned. And that’s one of the big problems with cancer therapy, which is mostly trial and error. Our understanding is insufficient, as are the number of biomarkers at our disposal.

From my point of view, it is precisely these biomarkers that will help manage this complexity. You don’t have to have it all figured out: it all starts with having a group of measurable biomarkers on the patient and using machine learning to process the information. The clear correlations, when we get them, without necessarily understanding everything, allow us to determine whether a patient will respond better to a specific treatment.

Is there a risk that new cancer treatments will be very effective while remaining inaccessible to some due to their prohibitive cost?

This question is very delicate. The high cost of some treatments results from the amount of investment associated with their development, while for others, such as CAR-Ts, it is directly linked to their manufacture. Some cancer therapies available on the market have a low production cost. However, given the high expenditure on research and development, companies want to recoup the investments by charging high prices. For me, this is an ethical issue, but also a legislative one, which is also linked to health policies, and not only to research. Governments must find solutions that guarantee more reasonable prices. This concern is essential.

Lately, research on aging focused on the comprehensive treatment of many diseases has gained momentum. Do you think that this work will also be of interest for the fight against cancer?

It’s very simple: aging is the main risk factor for cancer, to which, in the end, it opens the door. Basically, our body and its evolution did not prepare us to live until 80 or 90, but rather until 30 or 40, to produce the next generation, and then disappear. This period of time between 40 and 80 years gradually exposes us to diseases; cancer also reflects an accident associated with this longevity. A better understanding of aging will be particularly useful in reducing the incidence of cancer. Moreover, research on aging plays, per se, a determining role, because it produces a series of other effects. Also, if we manage to make aging less symptomatic, we will reap a multitude of benefits.

Do you think that one day cancer will completely disappear?

I don’t think we can make cancer go away. It is different from a viral disease or the Black Death, for which a vaccine or something is made that will immunize you. There is not one cancer, but a range of types of cancer, which leads me to believe that we will not be able to control it completely. On the other hand, we may reach a stage where most cancer patients will be able to lead normal lives, with follow-up similar to that of a chronic disease, as in the case of hypertension. In my opinion, this scenario is more realistic. My wish is for the cancer to be totally eliminated, but I feel that is wishful thinking.

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P53. Dr. Moshe Oren directs the Moross Center at the Weizmann Institute.


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