Biology subjects

Ferrazzi, F.

Publications and source records attributed to Ferrazzi, F..

4 recordsLinked to original sources

bioRxiv2025

A novel CAR T cell blend targeting PDPN and GD2 to overcome glioblastoma heterogeneity

BackgroundWhile chimeric antigen receptor (CAR) T cells have achieved encouraging remission rates in hematological malignancies, they demonstrated limited success in treating Glioblastoma (GBM), particularly due to high intra- and intertumoral heterogeneity. In this study, we identified a relevant and preserved target antigen, Podoplanin (PDPN), and evaluated the potential of a PDPN- and GD2-CAR T cell blend to overcome GBM heterogeneity. MethodsTarget antigen screening included clinical samples, healthy tissues and cell lines, as well as publicly available RNA sequencing datasets. The anti-tumor function of CAR T cells were examined in co-culture experiments with GBM cell lines and patient-derived organoids (PDOs), and in vivo after locoregional delivery in orthotopic xenograft models. ResultsThe generated CAR T cells demonstrated strong anti-tumor activity against several cell lines and PDOs from multiple patients. PDPN and GD2 expression was detectable in all PDOs at varying densities and regardless of the antigenic profile, the CAR T cell blend induced significantly higher levels of apoptosis in organoids than single antigen targeting counterparts. In vivo, we observed efficient tumor regression after locoregional administration of monospecific CAR T cells. While heterogeneous orthotopic tumors eventually relapsed in these groups, blended therapy resulted in a significantly increased overall survival and even achieved cure in the majority of mice. ConclusionThis novel PDPN-/GD2-CAR T cell blend demonstrated strong efficacy in advanced preclinical models of glioblastoma. The results suggest that this approach can overcome GBM heterogeneity in clinical application and address previous limitations of single antigen CAR T cell therapies. KEYPOINTSO_LIPDPN is a relevant and consistent CAR T cell target antigen in primary and recurrent GBM C_LIO_LIPDPN- and GD2-CAR T cells display synergistic anti-tumor activity in patient-derived organoids C_LIO_LILocal delivery of our CAR T cell blend confers long-term survival and cure in GBM-bearing mice C_LI IMPORTANCE OF THE STUDYThe highly variable landscape of tumor antigens in GBM represents a serious obstacle to single antigen CAR T cell therapies. In this study, we identified Podoplanin (PDPN) and GD2 as the most preserved target antigens in a screening campaign, with an even increased density in recurrent GBM compared to primary GBM. We combined PDPN- and GD2-CAR T cells in a blended treatment approach to counter antigen heterogeneity, and achieved a substantial gain in efficacy against patient-derived organoids (PDOs). In an orthotopic xenograft model, locoregional administration of the PDPN- and GD2-CAR T cell blend conferred long-term complete remission and increased survival compared to single antigen targeting. This study provides a hierarchy of CAR target antigens for treating GBM and illustrates the therapeutic potential of combinatorial antigen targeting using a PDPN/GD2-CAR T cell blend. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/636223v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@109a9aaorg.highwire.dtl.DTLVardef@16215faorg.highwire.dtl.DTLVardef@910623org.highwire.dtl.DTLVardef@129f79c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGRAPHICAL ABSTRACT:C_FLOATNO C_FIG

immunology↗

bioRxiv2024

Closing the gap in the clinical adoption of computational pathology: a standardized, open-source framework to integrate deep-learning algorithms into the laboratory information system

Digital pathology (DP) has revolutionized cancer diagnostics, allowing the development of deep-learning (DL) models supporting pathologists in their daily work and contributing to the improvement of patient care. However, the clinical adoption of such models remains challenging. Here we describe a proof-of-concept framework that, leveraging open-source DP software and Health Level 7 (HL7) standards, allows the integration of DL models in the clinical workflow. Development and testing of the workflow were carried out in a fully digitized Italian pathology department. A Python-based server-client architecture was implemented to interconnect the anatomic pathology laboratory information system (AP-LIS) with an external artificial intelligence decision support system (AI-DSS) containing 16 pre-trained DL models through HL7 messaging. Open-source toolboxes for DL model deployment, including WSInfer and WSInfer-MIL, were used to run DL model inference. Visualization of model predictions as colored heatmaps was performed in QuPath. As soon as a new slide is scanned, DL model inference is automatically run on the basis of the slides tissue type and staining. In addition, pathologists can initiate the analysis on-demand by selecting a specific DL model from the virtual slides tray. In both cases the AP-LIS transmits an HL7 message to the AI-DSS, which processes the message, runs DL model inference, and creates the appropriate type of colored heatmap on the basis of the employed classification model. The AI-DSS transmits model inference results to the AP-LIS, where pathologists can visualize the output in QuPath and/or directly from the virtual slides tray. The developed framework supports multiple DL toolboxes and it is thus suitable for a broad range of applications. In addition, this integration workflow is a key step to enable the future widespread adoption of DL models in pathology diagnostics.

pathology↗

bioRxiv2024

Macrophages foster adaptive anti-tumor immunity by ZEB1-dependent cytotoxic T cell chemoattraction

Tumor-associated macrophages (TAMs) shape the tumor microenvironment (TME) and exert a decisive impact on anti-tumor immunity. Understanding TAM function is therefore critical to understand anti-tumor immune responses and to design immunotherapies. Here, we describe the transcription factor ZEB1, a well-known driver of epithelial-to-mesenchymal transition, as an intrinsic regulator of TAM function in adaptive anti-tumor immunity. By combining cell type-specific deletion of Zeb1 with syngeneic models of colorectal and pancreatic cancer, we discovered an unexpected function of ZEB1 in the TAM-mediated control of T cell trafficking. ZEB1 supports secretion of a subset of chemokines including CCL2 and CCL22 by promoting their transcription and translation as well as by safeguarding protein processing. ZEB1 thereby elevates cytotoxic T cell (CTL) recruitment in vitro and in vivo and fosters immunosurveillance during tumor as well as lung metastatic outgrowth. Our study spotlights ZEB1 as a crucial facilitator of adaptive anti-tumor immunity and uncovers a potential therapeutic window of opportunity for cytokine-guided enhancement of CTL infiltration into tumors and metastases.

cancer biology↗

bioRxiv2020

Myogenin controls via AKAP6 non-centrosomal microtubule organizing center formation at the nuclear envelope

Non-centrosomal microtubule organizing centers (MTOC) are pivotal for the function of multiple cell types, but the processes initiating their formation are unknown. Here, we find that the transcription factor myogenin is required in myoblasts for the localization of MTOC proteins to the nuclear envelope. Moreover, myogenin is sufficient in fibroblasts for nuclear envelope MTOC (NE-MTOC) formation and centrosome attenuation. Bioinformatics combined with loss- and gain-of-function experiments identified induction of AKAP6 expression as one central mechanism for myogenin-mediated NE-MTOC formation. Promoter studies indicate that myogenin preferentially induces the transcription of muscle- and NE-MTOC-specific isoforms of Akap6 and Syne1, which encodes nesprin-1, the NE-MTOC anchor protein in muscle cells. Overexpression of AKAP6{beta} and nesprin-1 was sufficient to recruit endogenous MTOC proteins to the nuclear envelope of myoblasts in the absence of myogenin. Taken together, our results illuminate how mammals transcriptionally control the switch from a centrosomal MTOC to an NE-MTOC and identify AKAP6 as a novel NE-MTOC component in muscle cells.

cell biology↗