Jorge Moscat
· Ph.D.VerifiedCornell University · Pathobiology
Active 1984–2025
About
Jorge Moscat is the Homer T. Hirst III Professor of Oncology in Pathology at Weill Cornell Medical College and Vice-Chair for Experimental Pathology. He is a Cancer Biologist with expertise in the cellular and molecular mechanisms that control the initiation and progression of tumors. His laboratory focuses on liver and colorectal cancer, making impactful contributions to understanding the metabolic and immunological landscape of these tumors and their response to immunotherapy. His research aims to identify non-oncogenic vulnerabilities in cancer, with a particular interest in the interface between inflammation and metabolism. Dr. Moscat has identified and characterized the roles of several novel signaling molecules in cancer, such as autophagy and PB1-containing signaling adaptors p62/SQSTM1 and NBR1, as well as PB1 kinases PKCζ and PKCλ/ι. He has served in numerous scientific and leadership positions, including being an elected member of the European Molecular Biology Organization. Prior to his current role, he held leadership positions at the Sanford Burnham Prebys Medical Discovery Institute and was a Professor and Chairman at the University of Cincinnati Medical College, as well as a Professor and Director at the National Research Council of Spain.
Research topics
- Biochemistry
- Endocrinology
- Chemistry
- Medicine
- Cancer research
- Cell biology
- Internal medicine
- Biology
Selected publications
Molecular Cell · 2025-04-01 · 5 citations
articleOpen accessSenior authorNature Communications · 2025-11-23 · 2 citations
articleOpen accessFibrotic colorectal cancers (CRC) are largely microsatellite-stable and display desmoplastic stroma with poor immune infiltration. Here we identify thrombospondin-2 (THBS2) as a key regulator of the immune-exclusionary phenotype in fibrotic CRC. THBS2 is highly expressed by matrix cancer-associated fibroblasts at the tumor front. In an orthotopic model using desmoplastic tumor organoids, global or fibroblast-specific Thbs2 deletion disrupts the exclusionary barrier and increases intratumoral CD8 T cells. Mechanistically, THBS2 limits recruitment of CXCR3+ CD8 T cells by restraining dendritic- and macrophage-derived CXCL9/10. Depletion of these myeloid cells or blockade of CXCL9/10-CXCR3 signaling abolishes the enhanced CD8 T-cell influx and antitumor efficacy. Spatial profiling demonstrates that THBS2 loss induces proximity between CD8 T cells and myeloid cells and upregulates chemokines. Despite increased infiltration, CD8 T cells manifest exhaustion, rendering tumors highly susceptible to immune checkpoint blockade. THBS2 thus represents a tractable CAF-restricted target to overcome immune exclusion in fibrotic CRCs. Desmoplastic stroma is a hallmark of aggressive colorectal cancer. Matrix cancer-associated fibroblasts derived THBS2 establishes a fibrotic, immune-exclusionary barrier that limits CD8+ T cell infiltration, while its inhibition restores CXCR3-mediated T cell recruitment and enhances response to immune checkpoint blockade.
Nature Cancer · 2025-06-30 · 7 citations
articleOpen accessCancer Research · 2025-09-28
articleAbstract Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths, with a five-year survival rate around 12%. In PDAC, cancer-associated fibroblasts (CAFs) play a vital role in promoting the desmoplastic and immunosuppressive tumor microenvironment (TME), and have emerged as relevant cancer targets. CAFs produce intratumoral hyaluronic acid (HA) whose accumulation induces high interstitial fluid-pressure (IFP) which can interfere with drug delivery. Moreover, HA has been linked with tumor escape from immune surveillance. Systemic administration of Hyaluronidase, via the PEGPH20 formulation, has reduced stromal HA, normalized IFP, and consequently improved the efficiency of the cytotoxic compound, gemcitabine, leading to increased survival in mice. In this study we have decided to eliminate HA by a different approach involving its synthesis rather than inducing its degradation. To this end, we have genetically targeted the three genes encoding HA synthases (Has1, 2, 3). Has1 and Has3 null alleles were generated by CRISPR technology in mouse embryos since they are nor essential for embryonic development. To eliminate Has2, we used existing conditional Has2lox alleles (Matsumoto et al. 2019, PMID XXXX) along an inducible allele, Rosa26-CreERT2, encoding an inducible Cre-ERT2 recombinase to allow the systemic ablation of the conditional Has2lox alleles in adult mice upon exposure to a Tamoxifen-containing (TAM) diet. These alleles were added to the standard KPF strain (KRas +/FSFG12V;P53F/F;Pdx1-FlpO) to determine the effect of HA elimination in tumor-bearing mice. Exposure of these adult animals to the TMA diet induced significant levels of HA depletion leading to reprogramming of tumoral, stromal and immune cells leading to significantly reduced tumor progression. Tumor cells were more differentiated as illustrated by higher expression of cytokeratin19 and additional epithelial cell adhesion molecules. Furthermore, these tumor cells displayed reduced proliferative capacity, mor limited EMT, migration and invasive capacity. Interestingly, they also exhibited upregulated Kras expression. At the stroma level, we observed less fibrotic tissue, decreased collagen deposition, reduced CAFs activation,and changes in the CAF populations, with high content of iCAFs (Inflammatory CAFs) and very low content in myCAFs (Myofibroblast CAFs). More importantly, we also observed infiltration of CD8+ T cells. Notably, HA depletion enhanced the efficacy of gemcitabine, the anti-CTLA-4 and the panras inhibitor darasonrasib, either alone or in combination of anti-CTLA-4. In summary, HA depletion in PDAC produced multiple changes at different levels that opens up new opportunities for therapeutic interventions. Citation Format: Pian Sun, Ángeles Durán, Federico Virga, María Diaz-Meco, Jorge Moscat, Carmen Guerra, Mariano Barbacid. Targeting hyaluronic acid in pancreatic ductal adenocarcinoma uncovers novel therapeutic opportunities [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr B031.
Cancer Research · 2024-03-22 · 1 citations
articleAbstract Background: Up to 40% of colon cancer patients are at high risk of cancer recurrence, yet accurate and timely prediction tools are lacking. Leveraging whole slide images (WSIs) and deep learning models, we aimed to develop precise algorithm for prediction of colon cancer recurrence. Thus, enables risk stratification for optimized therapeutic interventions and improved health outcomes. Design: We designed an attention-based deep learning model for predicting colon cancer recurrence on paraffin-embedded, hematoxylin and eosin-stained colon tissue biopsies of digital slides. The WSIs were downloaded from the TCGA dataset, and preprocessed for color normalization, tissue segmentation, tilling, and histopathological features extraction. The entire dataset was then labeled based on cancer recurrence status, and divided into training (70%), validation (15%), and testing sets (15%). The model's performance was then evaluated by standard evaluation metrics, including receiver operating characteristic Area Under the Curve (AUC) and accuracy, on the training, validation, and testing datasets, where interpretability attention heatmaps were applied to gain insights into specific histological features and patterns involved in the model's decision-making process. The study is supported by the NIH-NCI-T32 for Next Generation Pathologists Program at our institution. Results: A total of 350 WSIs were included and labeled into two classes: post-therapeutic colon cancer recurrence and no recurrence. The tissue segmentation process involved converting RGB images to HSV color space, applying a median blur filter (kernel size: 7), and performing thresholding using Otsu's method. The extracted features were utilized to train and construct a Clustering-constrained Attention Multiple Instance Learning (CLAM) model. The model demonstrated consistent performance across the validation and testing datasets, achieving an AUC of 0.85 with an accuracy of 0.83 on the validation set, and an identical AUC of 0.85 with an accuracy of 0.83 on the testing set, indicating the model's robust ability to identify patients at risk of cancer recurrence. Conclusion: The study demonstrates the strong performance of our deep learning model in accurately identifying patients at risk for colon cancer recurrence based on H&E WSIs. This capability paves the way for optimizing therapeutic interventions and implementing effective surveillance strategies. Consequently, highlighting the crucial role of pathologists in collaborating with the oncologist for optimizing the management of colon cancer care in the era of personalized medicine. Citation Format: Mohammad K. Alexanderani, Mohamed Omar, Matthew Greenblatt, Ethel Cesarman, Maria T. Diaz-Meco, Jorge Moscat, Luigi Marchionni. Decoding colon cancer recurrence: Unveiling accurate predictions with attention-guided deep neural networks on histopathological whole slide images [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2584.
STAR Protocols · 2024-09-01
articleOpen accessSenior authorCorrespondingApplying Opal multiplex immunofluorescence (OMI) to characterize intestinal tissues of genetically engineered mouse models provides an excellent tool for studying complex processes. However, detecting appropriate signals from multiple target molecules is challenging. Here, we present a protocol to characterize mouse intestinal epithelial cell lineage using OMI. We describe steps for processing small intestine and colonic mouse tissues and designing and optimizing panels for OMI in mouse intestinal tissues. We then detail procedures for performing a quantitative evaluation of acquired images. For complete details on the use and execution of this protocol, please refer to Kinoshita et al. 1 • Steps for small intestine and colon processing and fixation • Multiplex imaging to delineate intestinal regeneration and tumor development • Steps for cell detection and image quantification Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Applying Opal multiplex immunofluorescence (OMI) to characterize intestinal tissues of genetically engineered mouse models provides an excellent tool for studying complex processes. However, detecting appropriate signals from multiple target molecules is challenging. Here, we present a protocol to characterize mouse intestinal epithelial cell lineage using OMI. We describe steps for processing small intestine and colonic mouse tissues and designing and optimizing panels for OMI in mouse intestinal tissues. We then detail procedures for performing a quantitative evaluation of acquired images.
Developmental Cell · 2024-05-29 · 7 citations
articleOpen accessSenior authorNature Communications · 2024-11-20 · 12 citations
articleOpen accessOvercoming resistance to therapy is a major challenge in castration-resistant prostate cancer (CRPC). Lineage plasticity towards a neuroendocrine phenotype enables CRPC to adapt and survive targeted therapies. However, the molecular mechanisms of epigenetic reprogramming during this process are still poorly understood. Here we show that the protein kinase PKCλ/ι-mediated phosphorylation of enhancer of zeste homolog 2 (EZH2) regulates its proteasomal degradation and maintains EZH2 as part of the canonical polycomb repressive complex (PRC2). Loss of PKCλ/ι promotes a switch during enzalutamide treatment to a non-canonical EZH2 cistrome that triggers the transcriptional activation of the translational machinery to induce a transforming growth factor β (TGFβ) resistance program. The increased reliance on protein synthesis creates a synthetic vulnerability in PKCλ/ι-deficient CRPC. The transition of androgen receptor-dependent prostate cancer to a therapy resistant cancer with neuroendocrine phenotype is an important process that remains poorly understood. Here, the authors show that PKCλ/ι-loss promotes epigenetic reprogramming resulting in a TGFβ resistance programme via transcriptional upregulation of translational machinery.
Molecular Cell · 2024-10-17 · 11 citations
articleOpen accessSenior authorCorresponding2023-03-31
supplementary-materialsOpen access<p>Oxidative stress genes regulated by p62</p>
Recent grants
Control of stellate cells-driven liver cancer by the p62/NBR1 adapters
NIH · $2.2M · 2016–2022
Protein Kinase Cz targets in Intestinal Cancer Stem Cells
NIH · $2.2M · 2013–2018
Cholesterol metabolism in mesenchymal colorectal cancer
NIH · $2.1M · 2022–2027
Interferon regulation by NBR1-driven chaperone-mediated autophagy in stellate cells in liver cancer
NIH · $2.4M · 2021–2026
NIH · $2.1M · 2013
Frequent coauthors
- 693 shared
Marı́a T. Diaz-Meco
Cornell University
- 169 shared
Angeles Durán
Cornell University
- 93 shared
Juan F. Linares
Weill Cornell Medicine
- 77 shared
Miguel Reina‐Campos
La Jolla Institute for Immunology
- 75 shared
Laura Sanz
Hospital Universitario Puerta de Hierro Majadahonda
- 70 shared
Hiroaki Kasashima
Osaka Metropolitan University
- 64 shared
Hong Cai
Zhejiang Chinese Medical University
- 64 shared
M.M. Municio
Consejo Superior de Investigaciones Científicas
Education
Ph.D., Molecular Biology
National Research Council of Spain
M.D.
University of Cincinnati Medical College
Awards & honors
- Elected member of the European Molecular Biology Organizatio…
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