Category: Newsletter Articles

Researchers in the field of autism spectrum disorder (ASD) have made significant strides in understanding the condition, its causes, and how to support individuals with autism. Insights from researchers span a wide range of disciplines, including genetics, neuroscience, psychology, and education.

Women’s health has long been an area that required more attention and innovation. Historically, medical research and treatments were often focused on male health issues, with women’s health concerns sidelined. Over the last few decades, however, there has been a notable shift toward prioritizing women’s health, leading to exciting advancements in the treatment of conditions that specifically affect women. From reproductive health to chronic conditions, the landscape of women’s healthcare has been evolving, offering hope for better treatment outcomes and quality of life.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most challenging cancers to treat, characterized by its aggressive nature and poor prognosis. Despite these challenges, recent studies have provided valuable insights and advancements in the understanding and management of PDAC. This article explores the latest statistics and findings in PDAC research, highlighting the progress made and the hurdles that remain.

The Grim Reality of PDAC

PDAC is the most common type of pancreatic cancer, accounting for over 90% of cases¹. It is notorious for its late detection and rapid progression, making it the fourth leading cause of cancer-related deaths worldwide¹. In 2023, there were approximately 62,210 new cases of PDAC reported in the United States, with 49,380 deaths attributed to the disease². The five-year survival rate remains dismally low at less than 8%¹.

Advances in Early Detection

One of the critical challenges in PDAC is early detection. Most patients are diagnosed at an advanced stage when the disease has already metastasized. Recent advancements in artificial intelligence (AI) and machine learning (ML) have shown promise in improving early detection rates. AI algorithms can analyze medical imaging and patient data to identify early signs of PDAC that might be missed by human eyes². These technologies are being integrated into clinical practice to enhance screening and diagnostic accuracy.

Genetic and Molecular Insights

Understanding the genetic and molecular underpinnings of PDAC has been a focal point of recent research. Studies have identified several genetic mutations associated with PDAC, including KRAS, TP53, CDKN2A, and SMAD4¹. These mutations play a crucial role in the development and progression of the disease. Targeted therapies aimed at these genetic alterations are being developed, offering hope for more effective treatments.

A notable study presented at the American Society of Clinical Oncology (ASCO) Gastrointestinal Cancers Symposium highlighted the promising results of a Phase 1 trial on RMC-6236, a novel multi-selective RAS inhibitor³. This drug targets KRAS mutations, which are present in over 90% of PDAC cases, and has shown potential in reducing tumor growth and improving patient outcomes.

Treatment Advances

The standard treatment for PDAC involves surgical resection followed by adjuvant chemotherapy. However, only 10-20% of patients are eligible for surgery due to the advanced stage of the disease at diagnosis¹. For the majority of patients, chemotherapy remains the primary treatment option. Recent studies have explored the efficacy of combining chemotherapy with other modalities, such as immunotherapy and radiation therapy, to improve outcomes.

A review published in Radiation Oncology discussed the potential of combined modality treatment approaches¹. The study emphasized the importance of personalized treatment plans that consider the unique characteristics of each patient’s tumor. By tailoring treatments to individual patients, researchers hope to enhance the efficacy of existing therapies and reduce side effects.

The Role of Lifestyle Factors

Lifestyle factors, such as obesity and type 2 diabetes, have been identified as significant risk factors for PDAC¹. The rising incidence of these conditions is expected to contribute to an increase in PDAC cases in the coming years. Public health initiatives aimed at promoting healthy lifestyles and early screening for high-risk individuals are crucial in combating this trend.

Future Directions

Despite the progress made, PDAC remains a formidable challenge in oncology. Ongoing research is focused on developing more effective treatments, improving early detection methods, and understanding the disease’s complex biology. The integration of AI and ML into PDAC care holds great promise for the future, potentially revolutionizing how this deadly disease is managed.

In conclusion, recent studies have provided valuable insights into the genetic, molecular, and clinical aspects of PDAC. While the prognosis for PDAC patients remains poor, advancements in early detection, targeted therapies, and personalized treatment approaches offer hope for improved outcomes. Continued research and innovation are essential to overcoming the challenges posed by this aggressive cancer and ultimately improving the lives of those affected by PDAC.

Current Trends

Two prominent researchers from Criterium’s AGICC Consortia group talk about what’s currently happening in PDAC:

Video with Dr Paul Oberstein, MD  of NYU Langone Health

Podcast with Dr Heinz-Josef Lenz, MD of USC Norris Comprehensive Cancer Center

This article is courtesy of the National Institutes of Health.

Implanted device responds to changes in brain biomarkers of Parkinson’s symptoms by adjusting stimulation, allowing the treatment to be tailored to a patient’s needs in real time.

A small feasibility study funded by the National Institutes of Health (NIH) found that an implanted device regulated by the body’s brain activity could provide continual and improved treatment for the symptoms of Parkinson’s disease (PD) in certain people with the disorder. This type of treatment, called adaptive deep brain stimulation (aDBS), is an improvement on a technique that has been used for PD and other brain disorders for many years. The study found aDBS was markedly more effective at controlling PD symptoms compared to conventional DBS treatments. Small NIH-funded trial shows the promise of personalized medicine. 

“This study marks a big step forward towards developing a DBS system that adapts to what the individual patient needs at a given time,” said Megan Frankowski, Ph.D., program director for NIH’s Brain Research Through Advancing Innovative Neurotechnologies® Initiative, or The BRAIN Initiative®, which helped fund this project. “By helping to control residual symptoms while not exacerbating others, adaptive DBS has the potential to improve the quality of life for some people living with Parkinson’s disease.”

DBS involves implanting fine wires called electrodes into the brain at specific locations. These wires then deliver electrical signals that can help mitigate the symptoms of brain disorders such as PD. Conventional DBS provides a constant level of stimulation and can also lead to unwanted side effects, because the brain does not always need the same strength of treatment. Therefore, aDBS uses data taken directly from a person’s brain and uses machine learning to adjust the level of stimulation in real time as the person’s needs change over time.

Four people already receiving conventional DBS were first asked what they felt was their most bothersome symptom that had persisted despite treatment. In many instances this was either involuntary movements or difficulty in initiating movement. The participants were then set up to receive aDBS treatment alongside their existing DBS therapy. After training the aDBS algorithm for several months, the participants were sent home, where the comparison test was performed by alternating between conventional and aDBS treatments. Changes occurred every two to seven days.

aDBS improved each participant’s most bothersome symptom roughly 50% compared to conventional DBS. Notably, even though they were not told which type of treatment they were receiving at any one time, three of the four participants were often able to correctly guess when they were on aDBS due to noticeable symptom improvement.

This project is a continuation of several years of work led by Philip Starr, M.D., Ph.D., and colleagues at the University of California, San Francisco. Previously, in 2018, they reported the development of an adaptive DBS system, referred to as a “closed loop” system, that adjusted based on feedback from the brain itself. Later, in 2021, they described their ability to record brain activity in people as they went about their daily lives.

Here, those two findings were combined to use brain activity recorded during normal life activities to drive the aDBS system. However, DBS treatment changed brain activity so much that the signal that had been expected to control the aDBS system was no longer detectable. This required researchers to take a computational and data-driven approach to identify a different signal within the brains of people with PD who were receiving conventional DBS therapy.

Conventional treatment for Parkinson’s disease often involves the drug levodopa, which is used to replace dopamine in the brain that has been lost because of the disorder. Because the amount of the drug in the brain fluctuates, peaking shortly after administration of the drug and gradually decreasing as it is metabolized by the body, aDBS could help smooth out the fluctuations by providing increased stimulation when drug levels are high and vice versa, making it an attractive option for patients requiring high doses of levodopa.

This study was supported by NINDS and NIH’s The BRAIN Initiative (NS10054, NS129627, NS080680, NS120037, NS131405, NS113637), Thiemann Foundation, and the TUYF Charitable Trust Fund.

About the National Institute of Neurological Disorders and Stroke (NINDS): NINDS is the nation’s leading funder of research on the brain and nervous system. The mission of NINDS is to seek fundamental knowledge about the brain and nervous system and to use that knowledge to reduce the burden of neurological disease.

NIH’s The BRAIN Initiative, a multidisciplinary collaboration across 10 NIH Institutes and Centers, is uniquely positioned for cross-cutting discoveries in neuroscience to revolutionize our understanding of the human brain. By accelerating the development and application of innovative neurotechnologies, The BRAIN Initiative® is enabling researchers to understand the brain at unprecedented levels of detail in both health and disease, improving how we treat, prevent, and cure brain disorders. The BRAIN Initiative involves a multidisciplinary network of federal and non-federal partners whose missions and current research portfolios complement the goals of The BRAIN Initiative. For more about the National Institutes of Health (NIH): visit www.nih.gov. 

Reference Article: Oehrn CR, Cernera S, Hammer LH, et al. “Chronic adaptive deep brain stimulation is superior to conventional stimulation in Parkinson’s disease: a blinded randomized feasibility trial.” Nature Medicine August 19, 2024. DOI: 10.1038/s41591-024-03196-z

Article courtesy of NIH at https://www.nih.gov/news-events 

Rheumatoid arthritis (RA) is an autoimmune disease characterized by inflammation and joint destruction. Recent studies have pointed to an imbalance of commensal bacteria in mucosal sites as a possible cause of inflammation leading to the initiation of the autoimmune process.

In an effort to reduce treatment-related side effects, more researchers are studying whether some cancer drugs can be given at lower doses while still maintaining their effectiveness.