Prostate cancer clinical trials working group

Prostate cancer clinical trials working group

Starting to integrate AI for treatment decisions in oncology.

Read the paper Precision oncology is a beautiful concept of individually treating cancer patients based on the molecular cause of their disease. However, we must overcome several theoretical and technological hurdles to make precision oncology a reality for all cancer patients.

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The first hurdle was when we realized that most cancers are heterogeneous at the molecular level. In other words, a specific tumor type, for example, lung cancer, is driven by several different cancer genes. Therefore, it is not enough to know the tumor's localization and histology to use most targeted therapies successfully.

Instead, we have to do a molecular diagnostic test on the tumor tissue to determine which driver gene is responsible for our patient's cancer.

However, we identified a lung cancer patient whose tumor harbored an activating mutation in the EGFR gene in the same year 2. Our medical team treated her with gefitinib based on this molecular information.

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  • Менее чем через секунду после того, как мужчины остановились на голубом круге, огни в комнате погасли.
  • Октопаук, находившийся в центре, - Элли назвала его "Верховным Оптимизатором" (после нескольких неудачных попыток обнаружить точное соответствие обязанностям главы октопауков на человеческом языке), - шагнул вперед и начал речь.
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As a result, she achieved a complete dramatic response and remained in remission for over five years 2. Experiences like this case deepened our dedication to advance precision oncology It became apparent that we have to integrate the development of predictive biomarkers into drug discovery to co-develop and register molecularly targeted therapies and companion diagnostic tests, as we also advocated in our review in 6.

Meanwhile, cancer genome studies revealed more and more cancer-related "driver" genes and genetic alterations in these genes.

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Today, we know over cancer genes and 6 million somatic mutations in cancer 7. The Pan-Cancer Analysis of Whole Genomes, published inrevealed additional functional relevant genetic alterations in the non-coding region of the genome in one-third of patients. At least, now we know the whole picture.

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Prostate cancer clinical trials working group study also showed that each patient harbors a combination of an average of prostate cancer clinical trials working group 8. It is reassuring to know that even though the human genome is vast, it is a closed box.

Prostate cancer clinical trials working group

The number of potential cancer genes and genetic alterations is limited. We see that the number of new cancer genes discovered reaching a plateau. The number of cancer genes does not seem formidable, but the problem is that is more than EGFR is an overrepresented cancer gene in the longtail distribution of cancer genes.

Full size table Experimental design A To investigate the effect of DDW on metabolic changes occur in diabetes, diabetic and control rats were divided into two main groups: half of the animals were given DDW 25 ppm Dand the other half received normal tap water ppm Dboth provided ad libitum. To determine whether DDW exerts its effects, at least partially, by modifying the action of insulin, diabetic rats were further divided into subgroups according to insulin treatment. The control rats did not receive insulin treatment. We did not want to achieve euglycaemia by insulin treatment, but to prevent severe acute complications only.

It was an exceptionally easy target to validate even in randomized clinical trials. Most cancer genes are far less frequent. Let's also consider the number of different specific alterations within these genes and the potential combination of genetic alterations.


It is impossible to generate a high level of clinical evidence for most alterations' functional and clinical relevance and register all these biomarkers as companion diagnostics. Even if the patient has a genetic alteration in a gene that constitutes a companion diagnostics of a particular targeted therapy, the functional relevance of the specific genetic alteration can be unknown or contradictory.

In addition, the presence of other alterations in other genes in the same tumor can influence the therapeutic response to the targeted therapy, as we have recently shown in the case of a patient with ALK fusion In these situations, we would need randomized studies for all combinations of alterations to decide which treatment we should prefer.

Clinical trials are not feasible for such small groups. The paradox is that we want to give personalized therapy, but we want to use the principles of evidence-based medicine. The solution that we propose in our study published NPJ Precision Oncology is to develop a standardized AI-based method to consider all that we know about the interactions between driver cancer genes, drugable targets, and targeted therapies. Next, implement this method into software as a medical device.

Abiraterone Acetate in Treating Patients With Metastatic Hormone-Resistant Prostate Cancer

The advantage of explainable computational systems is that modern antibiotikum a prosztatitis kezelésére "make" standardized and reproducible decisions. Therefore, the medical device we use to make the decision for personalized, individual treatment decisions can be tested in randomized clinical trials according to the rules of evidence-based medicine.

This also means that we can move away from the single biomarker paradigm to multiple parameters, aggregated data-based approach. We envision that AI-oncology algorithms will become the new companion diagnostics. SHIVA01 was the first randomized clinical trial to test the performance of precision oncology in comparison to chemotherapy We had the privilege to work prostate cancer clinical trials working group with Professor Prof.

Christophe Le Tourneau, the principal investigator of SHIVA01, and his team to analyze the performance of precision oncology again, this time powered by artificial intelligence AI and starting to integrate AI into precision oncology. Johnson DH. Gefitinib Iressa trials in non-small cell lung cancer.

World Lung Cancer Day 2020 Fact Sheet

Lung Cancer. PMID: Modern treatment of lung cancer: case 1. Amplification and mutation of the epidermal growth factor receptor in metastatic lung cancer with remission from gefitinib.

J Clin Oncol. PMID: 3.

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Epub Oct Combined dabrafenib and trametinib treatment in a case of chemotherapy-refractory extrahepatic BRAF VE mutant cholangiocarcinoma: dramatic clinical and radiological response with a confusing synchronic new liver lesion.

J Gastrointest Oncol.

Molecular subtype specific efficacy of MEK inhibitors in pancreatic cancers. PLoS One. Integrating molecular diagnostics into anticancer drug discovery.

Click here to learn more Oncology Informatics Philips IntelliSpace Precision Medicine enables the implementation and scaling of a precision medicine program. Our suite of products integrates phenotypes, genomics, proteomics, and bioinformatics together to expand the results into clinical practice.

Nat Rev Drug Discov. Epub Jun 7.

Top 10 Things to Know About Prostate Cancer Clinical Trials - Summit 2021

Nucleic Acids Res. Pan-cancer analysis of whole genomes. Epub Feb 5. Clin Lung Cancer. Epub Sep J Pers Med. Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer SHIVA : a multicentre, open-label, proof-of-concept, randomised, controlled phase 2 trial.

Clinical trials Prostate cancer clinical trials working group Principal inclusion criteria 1.

Lancet Oncol.