To wait for resistance to drugs to develop in patients and then identify why it happened, will lead to a deadly lag in the design of salvage therapies or indeed preventative treatment approaches.

In our latest manuscript we describe a systematic analysis of negative selection pressures acting on neoantigen forming mutations. Contrary to what is generally believed we did not find any clear evidence of this immunogenic form of selection and the resulting neoantigen depletion.

Turns out there are times when it’s important to improve on mother nature, especially when confronting a life-threatening disease.

In the November issue of Nature Medicine we describe the development of a first-in-class inhibitor of CLCF1 signaling and its effectiveness in several precllinical models of lung adenocarcinoma

The review introduces the idea of the PGC-1/ERR transcriptional network such as a novel category of metabolic target that could be useful for exploitation in future research in precision oncology. It addresses the concept of therapeutically explore biological capabilities acquired during the development of cancer to improve patient care against therapeutic resistance. What is the potential therapeutic target for cancer metabolism? If it exists, we do believe that targeting the PGC-1/ERR network as a mitochondrial vulnerability of metabolic-addictive cancers is a great opportunity to improve patient care. How to study it? The authors think that studying the PGC-1/ERR protein complex in its native state could shed new light on the mechanism of cancer resistance. As a potential tool, single-particle cryo-electron microscopy (cryo-EM) is urgently needed to develop a high-resolution biological structure to fully elucidate the function and molecular biology of the PGC-1/ERR network. In parallel, it would provide the identification of novel binding partners in signal transduction cascades that might have clinical relevance to improve patient care against therapeutic resistance. Here, the author tells the real story behind the paper, explaining what did motivate the authors to write this review? What is the biggest challenge to consider in the field of cryo-electron microscopy? And what next for further exacerbate our hope to improve patient care.

The paper introduces AI and its applications in precision oncology. It discusses major advances and challenges beyond pattern recognition and classification tasks. It argues in favor of wider innovative uses of AI for bringing benefits to patients. In this post, the author talks about the motivation behind the paper, important topics not covered in it and the excitement of doing research in this field.

In oncology research, the CRISPR technology provides a very powerful tool to support the investigation of the relationships between genes and phenotypes.

Precision oncology now encompasses precision immunotherapies, informatics, targeted therapies, and cellular engineering based on next generation sequencing and genomic profiling. Anti-cancer drugs are being rapidly developed, tested and approved by the FDA in an expedited effort to get the drugs to as many patients as possible in the shortest and safest timeframe. However, cancer is an insidious multifaceted group of diseases that are capable of adapting to harsh microenvironments and acquiring resistance to therapies. Immunotherapies have made a significant and positive impact on survival and quality of life in some patients. Even so, resistance is an issue with these therapies. Therefore, combinations of therapeutics to attack multiple cancer signaling pathways are often times more effective than a single drug treatment. This is all very promising, but what is really happening with the patient? First, even though, we, as scientists, think we are making great progress, being diagnosed with cancer is an extremely scary scenario. It’s important to think about the patient’s perspective.