DDR1

CAMBRIDGE, Mass.--(BUSINESS WIRE)-- Incendia Therapeutics, a precision oncology company discovering and developing a novel class of therapies that reprogram the tumor microenvironment (TME), today announced that it will have three poster presentations at the American Association for Cancer Research (AACR) Annual Meeting 2024, taking place April 5-10, 2024 in San Diego, California. “We look forward to presenting these posters at AACR, which highlight our work to characterize immune exclusion in the TME,” said Laura Dillon, PhD, Vice President of Translational Medicine & Bioinformatics at Incendia Therapeutics. “The data continue to validate that Discoidin Domain Receptor 1 (DDR1), the target of Incendia’s PRTH-101 program that is currently in the clinic, is highly correlated with immune exclusion in the tumor microenvironment across epithelial tumors. Additionally, they demonstrate the power of applying H&E-based biomarkers, driven by machine learning, to better interrogate the TME. We look forward to further exploring the potential of this technology, combined with our novel class of anti-cancer therapies, to better treat cancer patients by targeting the tumor microenvironment.” Presentation details for AACR 2024 are as follows: Title: Discoidin Domain Receptor 1 (DDR1) expression is associated with degree of immune exclusion across epithelial tumors Abstract Number: 2916 / 24 Presenting Author: Laura Dillon, Ph.D., Vice President of Translational Medicine & Bioinformatics at Incendia Therapeutics Session: The Tumor Microenvironment as a Drug Target Date and Time: Monday, April 8 from 1:30 - 5:00 PM PDT (4:30 – 8:00 PM EDT) Key Highlights: DDR1 mRNA and protein expression levels are correlated with immune exclusion of lymphocytes, CD8+ T cells, and CD45+ immune cells across epithelial tumor types (R: 0.31-0.56, adjusted p values: 0.04-0.07). While the degree of the correlation varied by indication and immune cell type considered, pancreatic cancer exhibited the strongest correlation between the lymphocyte-based Immune Exclusion Scores (IES) and DDR1 mRNA and protein expression (R: 0.48-0.54, adjusted p values: 0.04-0.07). This work provides additional insight into the role of DDR1 in human cancers and has utility for selecting indications and stratifying patients for DDR1-targeted therapies. Title: Machine learning-based identification of H&E-derived morphologic features associated with CD8+ T cell immune exclusion Abstract Number: 7392 / 20 Presenting Author: Yanchao Wang, Ph.D., Data Scientist at Incendia Therapeutics Session: Artificial Intelligence and Machine/Deep Learning 4 Date and Time: Wednesday, April 10 from 9:00 AM - 12:30 PM PDT (12:00 PM – 3:30 PM EDT) Key Highlights: Morphologic features derived from H&E images can be effective predictors of CD8-defined immune exclusion, providing an option for patient stratification by immune phenotype using widely available H&E images. We developed an Ens-L1-SVM model that identified 6 H&E features predictive of CD8-defined immune phenotypes. CD8-based immune phenotypes were classified by the Ens-L1-SVM model with an estimated accuracy of 97% using only the H&E-based features as input. Details on Incendia’s poster which is a collaboration with Alpenglow Biosciences: Title: 3D spatial quantification of lymphocyte infiltration and collagen features in the tumor microenvironment using a novel assay: 3D I/O Pro™ Abstract Number: 2309 / 20 Presenting Author: Bonnie Phillips, Ph.D., Director, Commercial Development at Alpenglow Biosciences Session: Liquid Biopsy and Precision Oncology Date and Time: Monday, April 8 from 9:00 AM - 12:30 PM PDT (12:00 PM – 3:30 PM EDT) Key Highlights: An end-to-end 3D spatial biology workflow, Alpenglow’s 3D I/O Pro™, was applied to colorectal cancer (CRC) tissues stained with nuclear and general protein fluorescent dyes to quantify lymphocyte density in tumor parenchyma and stroma and analyze collagen features, including orientation, within 3D regions of interest in the TME. The ratio of stromal to parenchymal lymphocytes (lymphocyte infiltration ratio) varied from 1.4 up to 9.1 in 3D volumes and 1 to 25 in 2D virtual sections taken throughout all 5 CRC samples. Qualitatively, areas with perpendicular collagen had more lymphocyte infiltration into the tumor parenchyma than areas with parallel collagen orientation. This work highlights how the 3D I/O Pro™ workflow can characterize tumors based on complex spatial relationships within the tumor microenvironment, and could have broad applicability in research and development of novel cancer therapies that target tumor fibrosis or other features of the TME. About Incendia Therapeutics Incendia Therapeutics is discovering and developing a novel class of experimental therapeutics that reprogram the tumor microenvironment (TME). Incendia’s platform is based on rigorous, groundbreaking research involving spatial characterization of the tumor microenvironment, multi-omics data integration, and extensive preclinical testing. The Company’s most advanced experimental molecule, PRTH-101, is in a Phase 1 clinical trial for the treatment of patients with advanced solid tumors. For more information visit incendia.com and LinkedIn.

咨询合作     药物筛选中心（暨南大学），隶属于暨南大学药学院公共科研平台。中心拥有Echo550微量液体超声转移工作站等先进的自动化药物筛选仪器，前期支撑的多个激酶抑制剂已经产业转化及发表JMC等高水平论文。目前，筛选中心建有激酶、蛋白酶、HDAC、病毒、细菌等筛选模型，能够开展肿瘤、病毒和细菌感染性疾病等领域相关靶标、细胞、机制的筛选和研究，每天能够完成数万次的新药筛选反应。已建立的药物筛选模型1）激酶：Abl, ABL(M351T), ABL(H396P), ABL(Y253F), ABL1 (E255K), ABL1 (G250E), ABL(Q252H), AKT1, AKT2, AKT3, ALK, ALK5, AuroraA, AuroraB, AXL, BRAF, BRAF(V599E), BTK, DDR1, DDR2, EGFR, EGFR (T790M), EGFR(L858R), EGFR(L861Q), EGFR(T790ML858R), EGFR(D746-750), EGFR(D746-750/T790M), Flt3, FLT3(D835Y), FGFR1, FGFR2, FGFR3, FGFR4, Her2, Her4, KIT, MET, IGF-1R, FGFR1, JAK1, JAK2, JAK3, MAPK10, MAPK14, mTOR, TrkA, TrkB, TrkC,TYK2, KDR, SRC, PDGFRa, PDGFRA(D842V), PDGFRb, RET, ZAK……2）肿瘤细胞模型：近500种肿瘤细胞系和基于Ba/F3的耐药模型。细胞系模型（300种）包括肺癌、胰腺癌、胃癌、肝癌、白血病等肿瘤；Ba/F3模型（200种）包括ABL、EGFR、FGFR、RET、ALK、FLT3、KIT、KRAS等靶点的敏感和耐药模型（支持了5个分子进入临床研究）。3）肿瘤移植瘤模型对外服务1）蛋白和细胞活性；2）体内抗肿瘤药效；3）蛋白表达、小分子-蛋白共晶；4）药代动力学；5）基于化学蛋白质组学的靶标发现;6) 肿瘤靶标及其候选药物的成药性评估。     咨询合作

Researchers are exploiting a unique biological feature of glioblastoma to gain a better understanding of how this puzzling brain cancer develops and how to target new treatments against it. The team developed human and mouse models of glioblastoma oncostreams and examined multiple factors in the tumor microenvironment that could impact how oncostreams develop and how to reverse them. Researchers at the University of Michigan Health Rogel Cancer Center are exploiting a unique biological feature of glioblastoma to gain a better understanding of how this puzzling brain cancer develops and how to target new treatments against it. The team, led by senior author Pedro Lowenstein, M.D., Ph.D., Richard Schneider Collegiate Professor of Neurosurgery at Michigan Medicine, had previously identified oncostreams as a key feature in glioblastoma development and in more aggressive disease. These highly active, elongated, spindle-like cells move throughout tissue in complicated patterns. The accumulation of oncostreams found throughout a tumor serve as the basis for cancerous cells' behavior, determining how tumors grow and invade normal tissue. In this new study, published in Advanced Science, the team developed human and mouse models of glioblastoma oncostreams and examined multiple factors in the tumor microenvironment that could impact how oncostreams develop and how to reverse them. Utilizing this model, they also identified a potential inhibitor, DDR1-IN-1, which appears to dismantle oncostreams. Preliminary studies in a mouse model of glioma showed the DDR1 inhibitor led to better survival. This suggests a potential pathway for additional research. Glioblastoma is an aggressive cancer, with only a 5% survival rate beyond two years. In large part, it's because even when surgery is possible, it's often difficult to remove all the cancerous cells. Radiation and chemotherapy have limited effectiveness, and no other treatment options have been developed in decades. This work will hopefully lead to new clinical trials, like the phase I trial of dual vector gene therapy, supported in part by the Rogel Cancer Center, which was published recently in The Lancet Oncology. "This model has deepened our understanding of how glioblastoma cells grow and invade and has led to the identification of a potential new therapeutic target," said Syed M. Faisal, Ph.D., a postdoctoral fellow in Lowenstein's lab and the first author of the study. "Understanding the mechanism of how glioblastoma grows and migrates is essential to developing new and better treatments," Lowenstein said. "Our oncostream model will be a valuable tool for gaining new insights into how glioma invades. It will allow us to test potential new therapeutic strategies that undermine the cellular and molecular foundations of glioblastoma malignancy." Additional authors: Jarred E. Clewner, Brooklyn Stack, Maria L. Varela, Andrea Comba, Grace Abbud, Sebastien Motsch, Maria G. Castro Funding for this work is from National Institutes of Health grants: R37-NS094804, R01-NS105556, R01-NS122536, R01-NS124167, R01-NS122165, R21-NS123879-01, R01-NS076991, R01-NS096756, R01-NS082311, R01-NS122234, R01-NS127378, R01-EB022563, U01-CA224160, R01-CA243916; RNA Biomedicine; Rogel Cancer Center; Ian's Friends Foundation; Leah's Happy Hearts Foundation; Pediatric Brain Tumor Foundation; Smiles for Sophie Forever Foundation; ChadTough Foundation.