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Diseases and Conditions

A Breakthrough Test for Lymphoma Patients: Predicting CAR T Cell Therapy Response with Machine Learning

A new article outlines a new tool that measures blood inflammation as a marker for poor CAR T therapy outcomes.

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The article reports on a significant breakthrough in cancer research, as City of Hope and Memorial Sloan Kettering (MSK) researchers have developed a tool using machine learning to predict the response of non-Hodgkin lymphoma patients to chimeric antigen receptor (CAR) T cell therapy. This test, called InflaMix, assesses inflammation in the blood, which is a potential cause of CAR T failure, and can identify patients at high risk for treatment failure.

The study involved 149 patients with NHL, and the machine learning model was able to find an inflammatory biomarker from a series of unique blood tests not usually employed in standard clinical practice. By analyzing this inflammatory signature, researchers found it was associated with a high risk of CAR T treatment failing, including increased risk of death or disease relapse.

The InflaMix model is an unsupervised machine learning approach, meaning it was trained without any knowledge of clinical outcomes. The team’s studies demonstrate that by using machine learning and blood tests, they could develop a highly reliable tool that can help predict who will respond well to CAR T cell therapy.

The researchers used three independent cohorts comprising 688 patients with NHL who had a wide range of clinical characteristics and disease subtypes and used different CAR T products to validate their initial findings. The study’s results were published in Nature Medicine.

City of Hope and MSK plan to investigate whether blood inflammation defined by InflaMix directly influences CAR T cell function and learn more about the source of this inflammation. This research has the potential to improve patient outcomes and inform new clinical trials that can boost the effectiveness of CAR T with additional treatment strategies.

The team’s studies were funded in part by the National Institutes of Health, the National Cancer Institute, and an MSK Support Grant. The work was primarily done at MSK where Dr. Van den Brink worked for more than two decades before coming to City of Hope in 2024.

City of Hope has treated over 1,700 patients since its CAR T program started in the late 1990s and continues to have one of the most comprehensive CAR T cell clinical research programs in the world, with about 70 ongoing clinical trials using immune cell products.

Diseases and Conditions

Ancient DNA Uncovers a Forgotten Chapter in Leprosy’s History in the Americas

Leprosy’s tale stretches from 5,000-year-old skeletons in Eurasia to a startling 4,000-year-old case in Chile, revealing that the rare strain Mycobacterium lepromatosis haunted the Americas millennia before Europeans arrived. Armed with cutting-edge ancient-DNA sleuthing, scientists have pieced together remarkably well-preserved genomes that challenge the idea of leprosy as purely a colonial import and hint that the disease may have homegrown American roots awaiting confirmation by future finds.

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The discovery of ancient DNA in human bones has revolutionized our understanding of diseases that have plagued humans for centuries. Recently, researchers have uncovered evidence that leprosy, also known as Hansen’s Disease, had a presence in the Americas long before European colonization. This finding challenges the common assumption that leprosy was introduced to the continent by European settlers.

Leprosy is a chronic disease caused by either Mycobacterium leprae or Mycobacterium lepromatosis. While M. leprae is the more commonly known pathogen, M. lepromatosis has been found in a rare form of the disease. The discovery of ancient DNA from 4000-year-old skeletons in Chile suggests that M. lepromatosis was present in the Americas thousands of years ago.

This finding is significant because it reveals a previously unknown chapter in leprosy’s history. Historically, leprosy has been documented in Europe and Asia for thousands of years, but its presence in the Americas before European colonization had gone undetected. The discovery of ancient DNA from M. lepromatosis in Chile provides evidence that this disease was present in the Americas at least 4000 years ago.

The study of ancient DNA has become a valuable tool for researchers to uncover the history of diseases that have affected humans over time. By analyzing ancient bone samples, researchers can identify the presence of pathogens and reconstruct their evolutionary history. In this case, the discovery of M. lepromatosis in Chile provides a fascinating example of how ancient DNA can shed new light on the history of a disease.

Further research is needed to understand the full extent of leprosy’s history in the Americas. The discovery of M. lepromatosis in Chile has opened up new avenues for research, and it is likely that more cases will be identified in the coming years. By studying ancient DNA from other time periods and contexts, researchers can gain a better understanding of how leprosy was transmitted and evolved over time.

Ultimately, the discovery of M. lepromatosis in Chile highlights the importance of studying ancient DNA to uncover the history of diseases that have affected humans for centuries. By doing so, we can gain a deeper understanding of how these diseases were transmitted and evolved over time, and perhaps even find new ways to prevent or treat them.

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Brain Tumor

AI Tool Tracks Lung Tumors as You Breathe, Potentially Saving Lives

An AI system called iSeg is reshaping radiation oncology by automatically outlining lung tumors in 3D as they shift with each breath. Trained on scans from nine hospitals, the tool matched expert clinicians, flagged cancer zones some missed, and could speed up treatment planning while reducing deadly oversights.

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The article describes how a team of Northwestern Medicine scientists has developed an innovative AI tool called iSeg that can accurately outline lung tumors on CT scans, even as they move with each breath. This is a critical factor in planning radiation treatment, which half of all cancer patients in the US receive during their illness. The study found that iSeg consistently matches expert outlines across hospitals and scan types, and also flags additional areas that some doctors may miss – areas linked to worse outcomes if left untreated.

The AI tool was trained using CT scans and doctor-drawn tumor outlines from hundreds of lung cancer patients treated at nine clinics within the Northwestern Medicine and Cleveland Clinic health systems. The study’s authors believe that iSeg can help reduce delays, ensure fairness across hospitals, and potentially identify areas that doctors might miss – ultimately improving patient care and clinical outcomes.

The research team is now testing iSeg in clinical settings, comparing its performance to physicians in real time. They are also integrating features like user feedback and working to expand the technology to other tumor types, such as liver, brain, and prostate cancers. The team envisions this as a foundational tool that could standardize and enhance how tumors are targeted in radiation oncology.

The study was published today (June 30) in the journal npj Precision Oncology.

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Autism

Unpacking the Gene That Hijacks Fear: How PTEN Rewires the Brain’s Anxiety Circuit

Deleting a gene called PTEN in certain brain cells disrupts the brain’s fear circuitry and triggers anxiety-like behavior in mice — key traits seen in autism. Researchers mapped how this genetic tweak throws off the brain’s delicate balance of excitation and inhibition in the amygdala, offering deep insights into how one gene can drive specific ASD symptoms.

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The gene PTEN has emerged as one of the most significant autism risk genes. Variations in this gene are found in a significant proportion of people with autism who also exhibit brain overgrowth. Researchers at the Max Planck Florida Institute for Neuroscience have discovered how loss of this gene rewires circuits and alters behavior, leading to increased fear learning and anxiety in mice – core traits seen in ASD.

PTEN has been linked to alterations in the function of inhibitory neurons in the development of ASD. The researchers focused on the changes in the central lateral amygdala driven by loss of PTEN in a critical neuronal population – somatostatin-expressing inhibitory neurons. They found that deleting PTEN specifically in these interneurons disrupted local inhibitory connectivity in the amygdala by roughly 50% and reduced the strength of the remaining inhibitory connections.

This diminished connectivity between inhibitory connections within the amygdala was contrasted by an increase in the strength of excitatory inputs received from the basolateral amygdala, a nearby brain region that relays emotionally-relevant sensory information to the amygdala. Behavioral analysis demonstrated that this imbalance in neural signaling was linked to heightened anxiety and increased fear learning, but not alterations in social behavior or repetitive behavior traits commonly observed in ASD.

The results confirm that PTEN loss in this specific cell type is sufficient to induce specific ASD-like behaviors and provide one of the most detailed maps to date of how local inhibitory networks in the amygdala are affected by genetic variations associated with neurological disorders. Importantly, the altered circuitry did not affect all ASD-relevant behaviors – social interactions remained largely intact – suggesting that PTEN-related anxiety and fear behaviors may stem from specific microcircuit changes.

By teasing out the local circuitry underlying specific traits, researchers hope to differentiate the roles of specific microcircuits within the umbrella of neurological disorders, which may one day help in developing targeted therapeutics for specific cognitive and behavioral characteristics. In future studies, they plan to evaluate these circuits in different genetic models to determine if these microcircuit alterations are convergent changes that underlie heightened fear and anxiety expression across diverse genetic profiles.

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