New smart robot accelerates cancer research 

molecular scissors, disease, genetic, immune cells, drug development, Diabetes, Antibiotic, hydrogen generation, chronic obstructive pulmonary disease, malaria, photosynthesis, kidney failure, Brain tumours, mental health, blood cancer, cancer, dementia, cancer treatment, antibiotic resistance, blood vessel leakage, quantum simulations, atrial fibrillation, batteries, goiter treatment, terahertz radiation, organic materials , Guild of European Research Intensive Universities, gene copies, social anxiety, blue light screens, ‘Our hope is that these findings will make it possible to discover a way to selectively inhibit the TGF-beta signals that stimulate tumour development without knocking out the signals that inhibit tumour development, and that this can eventually be used in the fight against cancer,’ says Eleftheria Vasilaki, postdoctoral researcher at Ludwig Institute for Cancer Research at Uppsala University and lead author of the study. TGF-beta regulates cell growth and specialisation, in particular during foetal development. In the context of tumour development, TGF-beta has a complicated role. Initially, it inhibits tumour formation because it inhibits cell division and stimulates cell death. At a late stage of tumour development, however, TGF-beta stimulates proliferation and metastasis of tumour cells and thereby accelerates tumour formation. TGF-beta’s signalling mechanisms and role in tumour development have been studied at the Ludwig Institute for Cancer Research at Uppsala University for the past 30 years. Recent discoveries at the Institute, now published in the current study in Science Signaling, explain part of the mechanism by which TGF-beta switches from suppressing to enhancing tumour development. Uppsala researchers, in collaboration with a Japanese research team, discovered that TGF-beta along with the oncoprotein Ras, which is often activated in tumours, affects members of the p53 family. The p53 protein plays a key role in regulating tumour development and is often altered – mutated – in tumours. TGF-beta and Ras suppress the effect of mutated p53, thereby enhancing the effect of another member of the p53 family, namely delta-Np63, which in turn stimulates tumour development and metastasis.

A new smart research robot accelerates research on cancer treatments. The new robot system finds optimal treatment combinations. Today Scientific Reports (Nature Publishing Group) is publishing an article about the robot, authored by Dr Mats Gustafsson, Professor of Medical Bioinformatics at Uppsala University.

Today complex diseases like cancer is medically almost exclusively treated by combining several different drugs. These combinations are typically composed from drugs that show effect on their own, but do not necessarily constitute the best possible combinations. The new robot system finds optimal treatment combinations and was developed by a research group led by Dr Mats Gustafsson, Professor of Medical Bioinformatics at Uppsala University.

‘We have built a robot system that plans and conducts experiments with many substances, and draws its own conclusions from the results. The idea is to gradually refine combinations of substances so that they kill cancer cells without harming healthy cells’, says Dr Claes Andersson, also a leading scientist in the project.

Instead of just combining a couple of substances at a time, the new lab robot has the ability to handle on the order of a dozen drugs simultaneously. The aim for the future is to be able to handle many more, preferably hundreds.

‘We are now one among the few laboratories in the world with this type of lab robot. However, so far researchers have only used the systems to look for combinations that kills the cancer cells, not taking the side effects into account’, says Mats Gustafsson.

The next step in the development is to make the robot system more automated and smarter. The current version still involves a few manual steps that could be automated. The scientists also want to build more prior knowledge into the guiding algorithm of the robot, for example, prior knowledge about drug targets and disease pathways.

For patients with the same cancer type returning multiple times, sometimes the cancer cells develop resistance against the pharmacotherapy used. The new robot systems may also become important in the efforts to find new drug compounds that make these resistant cells sensitive again.

An article about the robot system was presented today in Scientific Reports, and is part of a doctoral thesis on drug combinations, recently defended by Dr Muhammad Kashif.