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Pharma News - Insulin in the Brain Influences Dopamine Levels...

In the human brain, the hormone insulin also acts on the most important neurotransmitter for the reward system, dopamine. This was shown by researchers from the German Center for Diabetes Research (DZD) in Tübingen. Insulin lowers the dopamine level in a specific region of the brain (striatum*) that regulates reward processes and cognitive functions, among other things. This interaction can be an important driver of the brain’s regulation of glucose metabolism and eating behavior. The study has now been published in ‘The Journal of Clinical Endocrinology & Metabolism’.

Worldwide, more and more people are developing obesity and type 2 diabetes. Studies show that the brain plays an important role in causing these diseases. Dopamine is the most important neurotransmitter for the reward system. The hormone insulin is released after eating and regulates the metabolism in the human body (homeostatic system). It is not yet known how these two systems interact. However, changes in these systems have been linked to obesity and diabetes. In the current study, researchers from the Institute of Diabetes Research and Metabolic Diseases (IDM) of Helmholtz Zentrum München at the University of Tübingen, a partner of the DZD, and Tübingen University Hospital (Innere IV, Director: Prof. Andreas Birkenfeld) examined how the two systems interact specifically in the reward center of the brain, the striatum.

“Our eating behavior is regulated by the interaction between the reward system and homeostatic systems. Studies indicate that insulin also acts in dopamine-driven reward centers in the brain. It has also been shown that obesity leads to changes in the signaling of the brain that have a negative effect on the glucose metabolism in the whole body,” said first author Stephanie Kullmann. "We now wanted to decipher the interaction between the two systems in humans and find out how insulin regulates the dopamine system." For this purpose, ten healthy, normal-weight men received insulin or a placebo via a nasal spray (randomized, placebo-controlled, blinded crossover study). When insulin is absorbed via the nose, it reaches the brain directly. To study the interaction between insulin and dopamine, the researchers used a unique measurement technique: they combined magnetic resonance imaging to assess functional brain activity and positron emission tomography to assess dopamine levels.

Analysis of the study showed that the intranasal administration of insulin lowered dopamine levels and led to changes in the brain's network structure. "The study provides direct evidence of how and where in the brain signals triggered after eating – such as insulin release and the reward system – interact," said Professor Martin Heni, last author of the study, summarizing the results. "We were able to show that insulin is able to decrease dopamine levels in the striatum in normal-weight individuals. The insulin-dependent change in dopamine levels was also associated with functional connectivity changes in whoe-brain networks. Changes in this system may be an important driver of obesity and related diseases."

In further studies, the researchers want to investigate changes in the interaction of dopamine and insulin in obese or diabetic participants. These people often suffer from insulin resistance in the brain. The researchers therefore assume that this resistance prevents the normal insulin-induced regulation of dopamine levels in the reward center. In further steps, they want to restore the normal action of insulin in the brain by behavioral and/or pharmaceutical interventions.

#pharmanews #insulin #brain #dopamine #levels

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Pharma Research - Aspirin is linked with increased risk of heart failure...

Aspirin use is associated with a 26% raised risk of heart failure in people with at least one predisposing factor for the condition. That’s the finding of a study published today in ESC Heart Failure, a journal of the European Society of Cardiology (ESC). Predisposing factors included smoking, obesity, high blood pressure, high cholesterol, diabetes, and cardiovascular disease.
"This is the first study to report that among individuals with a least one risk factor for heart failure, those taking aspirin were more likely to subsequently develop the condition than those not using the medication," said study author Dr. Blerim Mujaj of the University of Freiburg, Germany. "While the findings require confirmation, they do indicate that the potential link between aspirin and heart failure needs to be clarified."

The influence of aspirin on heart failure is controversial. This study aimed to evaluate its relationship with heart failure incidence in people with and without heart disease and assess whether using the drug is related to a new heart failure diagnosis in those at risk.

The analysis included 30,827 individuals at risk for developing heart failure who were enrolled from Western Europe and the US into the HOMAGE study. "At risk" was defined as one or more of the following: smoking, obesity, high blood pressure, high cholesterol, diabetes and cardiovascular disease. Participants were aged 40 years and above and free of heart failure at baseline. Aspirin use was recorded at enrolment and participants were classified as users or non-users. Participants were followed-up for the first incidence of fatal or non-fatal heart failure requiring hospitalization.

The average age of participants was 67 years and 34% were women. At baseline, a total of 7,698 participants (25%) were taking aspirin. During the 5.3-year follow-up, 1,330 participants developed heart failure.

The investigators assessed the association between aspirin use and incident heart failure after adjusting for sex, age, body mass index, smoking, alcohol use, blood pressure, heart rate, blood cholesterol, creatinine, hypertension, diabetes, cardiovascular disease, and treatment with renin-angiotensin-aldosterone-system inhibitors, calcium channel blockers, diuretics, beta-blockers and lipid-lowering drugs. Taking aspirin was independently associated with a 26% raised risk of a new heart failure diagnosis.

To check the consistency of the results, the researchers repeated the analysis after matching aspirin users and non-users for heart failure risk factors. In this matched analysis, aspirin was associated with a 26% raised risk of a new heart failure diagnosis. To check the results further, the analysis was repeated after excluding patients with a history of cardiovascular disease. In 22,690 participants (74%) free of cardiovascular disease, aspirin use was associated with a 27% increased risk of incident heart failure.

Dr. Mujaj said: "This was the first large study to investigate the relationship between aspirin use and incident heart failure in individuals with and without heart disease and at least one risk factor. Aspirin is commonly used - in our study one in four participants were taking the medication. In this population, aspirin use was associated with incident heart failure, independent of other risk factors."

He concluded: "Large multinational randomized trials in adults at risk for heart failure are needed to verify these results. Until then, our observations suggest that aspirin should be prescribed with caution in those with heart failure or with risk factors for the condition."

Mujaj B, Zhang ZY, Yang WY, Thijs L, Wei FF, Verhamme P, Delles C, Butler J, Sever P, Latini R, Gf Cleland J, Zannad F, Staessen JA; Heart Omics in Ageing Investigators.
Aspirin use is associated with increased risk for incident heart failure: a patient-level pooled analysis.
ESC Heart Fail. 2021 Nov 22. doi: 10.1002/ehf2.13688

#pharma_research

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#pharma_research - Targeted drug combination shows unprecedented activity in some highly aggressive brain tumors...

A combination of two targeted cancer drugs showed unprecedented, "clinically meaningful" activity in patients with highly malignant brain tumors that carried a rare genetic mutation, according to a clinical trial report by investigators from Dana-Farber Cancer Institute.
The drug combination, which blocked an overactive cell-growth signaling pathway, shrank tumors by 50% or more in one-third of 45 patients with hard-to-treat high-grade gliomas, including glioblastomas, the most aggressive brain tumor. The patients were selected for the trial because their tumors carried a genetic mutation known as v600E in the BRAF gene. This mutation is found in only two to three percent of patients with high-grade gliomas but is found in up to 60% of certain types of low-grade gliomas. The study included 13 patients with low-grade gliomas. Of those patients, nine had an objective response to treatment with the drug combination, for a response rate of 69%.

"This is the first time that any targeted drug has been shown to work in glioblastoma in a clinical trial," said Patrick Wen, MD, first author of the report in The Lancet Oncology and director of the Center for Neuro-Oncology at Dana-Farber. With all current chemotherapy treatments for glioblastomas, the response rate is no better than five per cent, he said, which contrasts with the 33 percent response rate achieved by the combination. The response rate was even higher - about 40 % - in patients younger than 40 years of age, according to Wen.

The two drugs paired in the study were dabrafenib and trametinib. Both drugs target proteins in the MAPK pathway, a signaling chain of proteins that acts as a switch for cell growth and can become stuck in the "on" position, causing uncontrolled growth leading to tumors.

Three patients had complete responses - their tumors no longer could be seen on imaging scan - and 12 had partial shrinkage of their tumors. The patients were not cured, but those who responded to the drugs experienced remarkably durable benefits - by one assessment, the median duration of response was 13.6 months, and by another assessment, it was 36.9 months.

The findings are from an ongoing phase 2 study called ROAR (Rare Oncology Agnostic Research) that has been enrolling patients since 2014 in 27 community and academic cancer centers in 13 countries. The study is a so-called “basket” trial, which seeks to enroll patients who share a common tumor characteristic - in this case the BRAF v600E mutation - although they may have an array of different cancers. The ROAR study includes patients with thyroid and biliary tract cancers, gastrointestinal stromal tumors, hairy cell leukemia, multiple myeloma, low- and high-grade glioma brain tumors, and others. The study is designed to determine the overall response rate of dabrafenib combined with trametinib in patients with BRAF V600E-mutated cancers. The BRAF protein is a growth signaling protein kinase that plays a role in regulating the MAPK signaling pathway. BRAF V600E mutations drive cancer by activating the MAPK pathway, which is made up of many proteins, resulting in uncontrolled cell growth and the development of a tumor.

The drugs used in this study, dabrafenib and trametinib, are oral drugs that block parts of the overactive MAPK signaling pathway. Dabrafenib inhibits an enzyme, B-Raf, and trametinib inhibits molecules called MEK1 and MEK2, which are part of the MAPK pathway. They have been used in combination to treat melanoma, non-small cell lung cancer, and thyroid cancer.

Gliomas are cancer that originate in the glia - the supporting cells of the brain - not the brain neurons themselves. Gliomas comprise about 80 percent of all malignant brain tumors. Some are slow-growing low-grade gliomas, while others are aggressive high-grade gliomas including glioblastomas that are difficult to remove and almost always recur. No important advances in treating gliomas in recent years, the authors of the report said, but there have been isolated reports of the combination of dabrafenib and trametinib showing activity in gliomas. Their report from the ROAR study "is the first time that a combination of BRAF inhibitor (dabrafenib) and a MEK inhibitor (trametinib) have shown notable activity in these difficult-to-treat gliomas, including glioblastomas which have historically shown resistance to therapies."

Although the drugs only helped patients whose tumors carried the rare V600E mutation, Wen said the results were encouraging "because people were starting to think you will never have any targeted therapies for glioblastoma." He added that there is emerging evidence that there may be other targets in gliomas that could be blocked by designer drugs.

The ROAR trial was originally designed and sponsored by GlaxoSmithKline and is currently sponsored by Novartis.

Wen reports research support from Agios, AstraZeneca/MedImmune, Bayer, Celgene, Eli Lilly, Genentech/Roche, Kazia Therapeutics, MediciNova, Merck, Novartis, Nuvation Bio, Oncoceutics, Vascular Biogenics, and VBI Vaccines; and has an advisory or board member role in Agios, AstraZeneca, Bayer, Black Diamond, Boston Pharmaceuticals, ElevateBio, Imvax, Karyopharm Therapeutics, Merck, Mundipharma, Novartis, Novocure, Nuvation Bio, Prelude Therapeutics, QED Therapeutics, Sapience, Vascular Biogenics, VBI Vaccines, and Voyager.

Subbiah V, Lassen U, Élez E, Italiano A, Curigliano G, Javle M, de Braud F, Prager GW, Greil R, Stein A, Fasolo A, Schellens JHM, Wen PY, Viele K, Boran AD, Gasal E, Burgess P, Ilankumaran P, Wainberg ZA.
Dabrafenib plus trametinib in patients with BRAFV600E-mutated biliary tract cancer (ROAR): a phase 2, open-label, single-arm, multicentre basket trial.
Lancet Oncol. 2020 Sep;21(9):1234-1243. doi: 10.1016/S1470-2045(230321-1

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#pharma_news - Sanofi invests $180 million equity in Owkin's artificial intelligence and federated learning to advance oncology pipeline...

Sanofi announced an equity investment of $180 million and a new strategic collaboration with Owkin comprised of discovery and development programmes in four exclusive types of cancer, with a total payment of $90 million for three years plus additional research milestone-based payments. Owkin, an artificial intelligence (AI) and precision medicine company, builds best-in-class predictive biomedical AI models and robust data sets. With the ambition to optimize clinical trial design and detect predictive biomarkers for diseases and treatment outcomes, this collaboration will support Sanofi’s growing oncology portfolio in core areas such as lung cancer, breast cancer and multiple myeloma.

To accelerate medical research with AI in a privacy-preserving way, Owkin has assembled a global research network powered by federated learning, which allows data scientists to securely connect to decentralized, multi-party data sets and train AI models without having to pool data. This approach will complement Sanofi's emerging strength in oncology, as the company's scientists apply cutting-edge technology platforms to design potentially life-transforming medicines for cancer patients worldwide.

"Owkin's unique methodology, which applies AI on patient data from partnerships with multiple academic medical centers, supports our ambition to leverage data in innovative ways in R&D," said Arnaud Robert, Executive Vice President, Chief Digital Officer, Sanofi. "We are striving to advance precision medicine to the next level and to discover innovative treatment methods with the greatest benefits for patients."

Sanofi will leverage the comprehensive Owkin Platform, in order to find new biomarkers and therapeutic targets, building prognostic models, and predicting response to treatment from multimodal patient data. Sanofi's investment will support Owkin's development and goal to grow the world's leading histology and genomic cancer database from top oncology centers.

"Owkin's mission is to improve patient's lives by using our platform to discover and develop the right treatment for every patient," said Thomas Clozel, M.D., Co-Founder and CEO at Owkin. "We believe that the future of precision medicine lies in technologies that can unlock insights from the vast amount of patient data in hospitals and research centers in a privacy-preserving and secure way. This landmark partnership with Sanofi will see federated learning used to create research collaborations at a truly unprecedented scale. The future of AI to transform how we develop treatments is incredibly bright, and we are proud to partner with Sanofi on this mission."

This collaboration agreement will allow Sanofi to work closely with Owkin in identifying new oncology treatments across four cancers.

"We look forward to working with our colleagues at Owkin to analyze data from hundreds of thousands of patients," said John Reed, M.D., Ph.D., Global Head of Research and Development, Sanofi. "Sanofi's investment in the company includes a three-year agreement that will help discover and develop new treatments for non-small cell lung cancer, triple negative breast cancer, mesothelioma and multiple myeloma. This partnership will help accelerate our ambitious oncology program as we advance a rich pipeline of medicines to address unmet patient needs."

About Owkin
Owkin is a French American startup that specializes in AI and federated learning for medical research. It was co-founded in 2016 by Dr Thomas Clozel M.D., a clinical research doctor and former assistant professor in clinical hematology, and Dr Gilles Wainrib, Ph.D., a pioneer in the field of artificial intelligence in biology. Owkin has recently published groundbreaking research at the frontier of AI and medicine in Nature Medicine, Nature Communications and Hepatology. The Owkin Platform connects life science companies with world-class academic researchers and hospitals to share deep medical insights for drug discovery and development. Using federated learning and breakthrough collaborative AI technology, Owkin enables its partners to unlock siloed datasets while protecting patient privacy and securing proprietary data. Through sharing high-value insights, the company powers unprecedented collaboration to improve patient outcomes. Owkin works with the most prominent cancer centers and pharmaceutical companies in Europe and the US. Key achievements to date include HealthChain and MELLODDY; two Owkin led federated learning consortia fuelling unprecedented collaboration in academic research and drug discovery, respectively.

About Sanofi
Sanofi is dedicated to supporting people through their health challenges. We are a global biopharmaceutical company focused on human health. We prevent illness with vaccines, provide innovative treatments to fight pain and ease suffering. We stand by the few who suffer from rare diseases and the millions with long-term chronic conditions. With more than 100,000 people in 100 countries, Sanofi is transforming scientific innovation into healthcare solutions around the globe.

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#pharma_research - Scientists identify new types of a blood cancer and potential targeted treatments...

Mount Sinai researchers have developed a new model that uses DNA and RNA sequencing data from hundreds of patients to identify specific genes and genetic alterations responsible for never-before-defined subtypes of a blood cancer called multiple myeloma. They also identified potential targeted treatments based on the findings, as reported in Science Advances in November.
This is the first study using multi-omics, the integration and analysis of multiple data types, to create a computational model of multiple myeloma, which the scientists named the Multiple Myeloma Patient Similarity Network (MM-PSN). The genes identified in the analysis included some associated with a high risk of relapse.

"Our findings have immediate implications for the development of novel precision medicine tools and clinical trials, as different subgroups of patients may respond to different targeted and immuno- oncology therapies based on their genomic and transcriptomic profiles," said lead author Alessandro Lagana, PhD, Assistant Professor of Oncological Sciences at The Tisch Cancer Institute at Mount Sinai. "These studies are fundamental to advancing our understanding of myeloma pathology and pave the way for future research into drug repurposing approaches aimed at novel therapies tailored to specific patient subgroups."

Researchers believe that MM-PSN captures the complexity of multiple myeloma by associating patients with highly similar DNA and RNA profiles to form more granular and homogeneous classes than achieved by previous classifications. Within the MM-PSN model, researchers represented patients as nodes, much as in a social network, that are connected with one another based on how similar their DNA and RNA profiles are.

To create MM-PSN, researchers analyzed five different types of data obtained from DNA and RNA sequencing of 655 newly diagnosed multiple myeloma patients. The analysis of MM-PSN identified three main groups and 12 subgroups enriched for distinct genetic and molecular features, revealing remarkable diversity within previously defined disease subtypes - such as hyperdiploid and MMSET-translocated, which are chromosome abnormalities - and novel insights into the occurrence of primary and secondary genomic alterations within each patient's cancer.

One of the biggest findings of the MM-PSN is the an abnormality within an area of chromosome 1 being the most important single genetic variant associated with a high risk of relapse; the study suggests that it should now be incorporated into international myeloma staging systems. Researchers also identified new classes of high-risk patients beyond current classifications in multiple myeloma, including one of patients at highest risk of relapse and shortest overall survival, and another that is often associated with more favorable outcomes.

This work was supported by grants from the National Cancer Institute (NCI) (R21-CA209875-01A1; R01-1R01CA244899-01A1), The Tisch Cancer Institute NCI Support Grant (P30 CA196521) and the Multiple Myeloma philanthropic fund. This work was also supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai.

Sherry Bhalla, David T Melnekoff, Adolfo Aleman, Violetta Leshchenko, Paula Restrepo, Jonathan Keats, Kenan Onel, Jeffrey R Sawyer, Deepu Madduri, Joshua Richter, Shambavi Richard, Ajai Chari, Hearn Jay Cho, Joel T Dudley, Sundar Jagannath, Alessandro Laganà, Samir Parekh.
Patient similarity network of newly diagnosed multiple myeloma identifies patient subgroups with distinct genetic features and clinical implications,
Science Advances, 2021. doi: 10.1126/sciadv.abg9551

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