CNTN4

New research has shed light in the complex interplay between cell proteins, and how they impact on neurons in neurodevelopmental disorders and Alzheimer's disease. New research has shed light in the complex interplay between cell proteins, and how they impact on neurons in neurodevelopmental disorders and Alzheimer's disease. A new study led by the University of Exeter and published in Royal Society Open Biology has discovered the key role that the protein Contactin-4 (encoded by the gene CNTN4) plays in shaping neurons. The researchers began studying CNTN4 because it was known to have a role in autism, but its functional roles were not well understood. The team explored how CNTN4 functions within the brain, particularly its interactions with proteins involved in neurodegenerative diseases like Alzheimer's disease. For the first time, the researchers studied mice who have had the CNTN4 gene knocked out in the cortex, the region of the brain responsible for key functions including memory, thinking and reasoning. They found that neurons developed in a different way in the cortex region. Researchers have demonstrated for the first time in human cells the interaction between genes CNTN4 and APP, a gene strongly linked to Alzheimer's disease, revealing a co-dependent relationship that is essential for brain development, and specifically for the healthy growth of neurons. They found that CNTN4 not only contributes to neural elongation in the frontal cortex region of the brain, but also CNTN4 expression is regulated via a relationship with APP. Using studies in genetically modified human cells, the team also discovered that a complex interaction exists between CNTN4 and APP. If CNTN4 is knocked out, then levels of APP decrease, but not to zero. The scientists believe that APP may compensate for the loss of CNTN4, and vice versa. The study's lead author, Dr Rosemary Bamford, of the University of Exeter Medical School, said: "It was quite remarkable to discover that CNTN4, a gene linked to developmental processes, also plays a role in modulating factors involved in Alzheimer's disease. This intersection of developmental and neurodegenerative pathways offers exciting new insights into the broader implications of these proteins." Senior author Dr Asami Oguro-Ando, of the University of Exeter Medical School, said: "Looking ahead, my group is keen to further dissect the molecular mechanisms underpinning the interaction between CNTN4 and APP and explore their wider implications for disorders like Alzheimer's and Autism Spectrum Disorder. Our next steps involve clarifying how the CNTN4-APP interaction impacts neural activity. Understanding this interaction is crucial as it represents a fundamental step towards a comprehensive grasp of neurodevelopmental and neurodegenerative disorders."

- Lunit's AACR 2024 presentations to spotlight HER2 mutation insights and CNTN4's role in immunotherapy success, pioneering next-gen personalized treatment approaches, supported by the AI-powered Lunit SCOPE suite SEOUL, South Korea, April 1, 2024 /PRNewswire/ -- Lunit (KRX:328130.KQ), a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, today announced the presentation of seven studies at the American Association for Cancer Research (AACR) 2024 Annual Meeting in San Diego, California, from April 5 to 10. Continue Reading Lunit to Showcase 7 Studies at AACR 2024 In a poster presentation, Lunit's AI-powered HER2 analyzer, Lunit SCOPE HER2's precision shines through its analysis of 194,259 pan-cancer samples, correlating different ERBB2 mutations with changes in HER2 protein expression. This AI-powered assessment successfully identified key mutation-expression correlations, particularly focusing on exon 20 insertions (ex20ins) and S310x mutations across a variety of cancers, including NSCLC, urothelial, and breast cancers. Through detailed HER2 intensity examination, the AI analysis highlighted that, among ERBB2-mutated cases with HER2 IHC images, a higher proportion of HER2 3+ tumor cells was observed in S310x and ex20ins cases compared to others. Similarly, high HER2 expression was observed in both S301x and ex20ins cases compared to other mutation cases. The findings suggest that understanding these mutation-expression relationships could improve the prediction of treatment responses, enabling a step forward in the development of more personalized and precise therapeutic strategies for cancer patients with ERBB2 mutations. The study also indicates the potential of AI in enhancing the precision of cancer treatment through the identification of genetic alterations that influence protein levels. In a collaborative study with Genome & Company, a clinical-stage biotechnology specializes in anti-cancer therapeutic development, Lunit leveraged its AI-powered immunohistochemistry (IHC) analyzer to investigate the expression of Contactin-4 (CNTN4) and its relationship with PD-L1 across 18 types of cancers. CNTN4, which is mainly expressed in tumor cells, is known to reduce T-cell activation and responsiveness to tumors. The analysis of 795 pan-cancer tissue samples revealed an important inverse correlation between CNTN4 expression and PD-L1 levels. When PD-L1 intensity was ≥ 30%, 50%, 75%, and 90%, CNTN4 was observed in 42.4% (337/795), 25.5% (203/795), 11.4% (91/795), and 5.2% (41/795) of cases, respectively. This insight positions CNTN4 as a promising target for immunotherapy, particularly in cancers that exhibit low PD-L1 expression. Another study conducted with Genome & Company focused on the correlation between the efficacy of pembrolizumab treatment and CNTN4 expression in gastric cancer patients. This study categorized patients based on CNTN4 and PD-L1 expression levels. The results indicated that patients with low CNTN4 expression and high PD-L1 levels were more likely to respond favorably to pembrolizumab, showing a 64.3% objective response rate (ORR). Conversely, patients exhibiting both high CNTN4 and PD-L1 expression demonstrated a 0% ORR, with non-responders presenting lower PD-L1 expression and higher CNTN4 levels compared to responders. These findings not only highlight CNTN4's potential as a predictive biomarker for immunotherapy response but also underscore the pivotal role of AI-powered analytics in identifying novel biomarkers. "We are excited to present our groundbreaking studies at AACR 2024, illustrating the profound impact of the Lunit SCOPE suite on cancer research and treatment," said Brandon Suh, CEO of Lunit. "Our findings, particularly the discovery of key mutation-expression correlations by Lunit SCOPE HER2 and the potential of CNTN4 as a novel biomarker for immunotherapy responsiveness, underscore our commitment to transforming cancer care. These studies not only highlight our pioneering role in leveraging AI to enhance precision medicine but also pave the way into the future of oncology - where treatment is not just personalized but predictive, ensuring the best possible outcomes for patients worldwide. We're proud to contribute to this transformative journey, marking a significant milestone in our mission to fight cancer with AI." In addition to the studies above, Lunit will present four more studies at this year's AACR, showcasing the diverse capabilities of Lunit SCOPE IO, Lunit SCOPE HER2, and an AI-based CT image analyzer combining analysis of CT scans with digital pathology analysis to predict response to checkpoint therapy. Visit Lunit at booth 808 to explore how the Lunit SCOPE suite is revolutionizing oncology research and clinical practice. Presentations at AACR 2024 featuring Lunit SCOPE include: "Pan-Cancer analysis of the influence of ERBB2 alteration on HER2 expression" (4640/16, Section 26, April 9, 9:00 AM - 12:30 PM) "Association of artificial intelligence (AI)-based HER2 scoring with clinical outcomes to first-line trastuzumab plus chemotherapy in HER2-positive metastatic gastric cancer (mGC)" (2484/1, Section 43, April 8, 9:00 AM - 12:30 PM) "Assessment of CNTN4 expression and its association with PD-L1 across 18 various cancers using an artificial intelligence-powered immunohistochemistry analyzer" (553/6, Section 23, April 7, 1:30 PM - 5:00 PM) "Association between the CNTN4 expression and responsiveness to pembrolizumab in gastric cancer" (7522/10, Section 42, April 10, 9:00 AM - 12:30 PM) "Artificial intelligence (AI)-based multi-modal approach using H&E and CT image for predicting treatment response of immune checkpoint inhibitor (ICI) in non-small cell lung cancer (NSCLC)" (4170/25, Section 8, April 9, 9:00 AM - 12:30 PM) "Artificial intelligence-powered analysis of tumor-stroma ratio and fibroblast density as prognostic indicators in colorectal cancer" (276/7, Section 11, April 7, 1:30 PM - 5:00 PM) "Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes as a prognostic biomarker for pembrolizumab plus chemotherapy in recurrent or metastatic head and neck squamous cell carcinoma" (7658/19, Section 46, April 10, 9:00 AM - 12:30 PM) About Lunit Founded in 2013, Lunit is a deep learning-based medical AI company on a mission to conquer cancer. We are committed to harnessing AI to ensure accurate diagnosis and optimal treatment for each cancer patient using AI-powered medical image analytics and AI biomarkers. As a medical AI company grounded on clinical evidence, our findings are presented in major peer-reviewed journals, such as the Journal of Clinical Oncology and the Lancet Digital Health, and global conferences, including ASCO and RSNA. After receiving FDA clearance and the CE Mark, our flagship Lunit INSIGHT suite is clinically used in approximately 3,000+ hospitals and medical institutions across 40+ countries. Lunit is headquartered in Seoul, South Korea, with offices and representatives worldwide. For more information, please visit lunit.io. About Lunit SCOPE Lunit SCOPE is a suite of AI-powered software that analyzes tissue slide images for digital pathology and AI biomarker development, aiming to optimize workflow and facilitate more accurate and predictive clinical data for clinicians and researchers. Lunit SCOPE platform offers multiple AI-powered tissue analysis products and assays that can streamline digital pathology workflow and diagnostics and enhance the drug development process. Lunit SCOPE IO analyzes the tumor microenvironment (TME) based on H&E analysis and provides AI-based predictive clinical outcome information. In addition, AI-driven Immunohistochemistry (IHC) slide analysis services are offered through products such as Lunit SCOPE PD-L1, Lunit SCOPE HER2, Lunit SCOPE ER/PR, and others. SOURCE Lunit