Biology subjects

Cerullo, V.

Publications and source records attributed to Cerullo, V..

6 recordsLinked to original sources

bioRxiv2026

Site-Dependent Decoupling of Drug-Biomarker Associations in Clear Cell Renal Cell Carcinoma Revealed by Functional Profiling of Patient-Derived Cell Models

Clear cell renal cell carcinoma (ccRCC) frequently exhibits primary and acquired resistance to standard-of-care therapies, underscoring the need for improved strategies to predict therapeutic response and prioritize patient-specific treatments. Although recent multi-omic and single-cell studies have provided insight into the molecular landscape of ccRCC, molecular alterations alone incompletely predict drug sensitivity. We prospectively profiled tumors from 28 patients with localized and metastatic ccRCC by integrating molecular characterization, functional drug sensitivity and resistance testing in patient-derived cell models, and longitudinal clinical data. Although genomic biomarkers suggested potentially actionable therapies in 27/28 patients, functional testing revealed discordance between genomic actionability and ex vivo drug sensitivity, whereas linear mixed-effects modelling uncovered 16 novel copy-number-based features associated with sensitivity to 11 drugs. Genotype-drug response associations were largely preserved between primary tumors and vena cava thrombi but frequently disrupted in distant metastases. Integrating functional drug testing with multi-omic profiling reveals vulnerabilities not apparent from genomic data alone, refines therapeutic actionability, captures interpatient and intersite heterogeneity in ccRCC, and provides a scalable framework for individualized treatment prioritization.

cancer biology↗

bioRxiv2024

Single-cell spatial atlas of high-grade serous ovarian cancer unveils MHC class II as a key driver of spatial tumor ecosystems and clinical outcomes

The tumor microenvironment (TME) is a complex network of interactions between malignant and host cells, yet its orchestration in advanced high-grade serous ovarian carcinoma (HGSC) remains poorly understood. We present a comprehensive single-cell spatial atlas of 280 metastatic HGSCs, integrating high-dimensional imaging, genomics, and transcriptomics. Using 929 single-cell maps, we identify distinct spatial domains associated with phenotypically heterogeneous cellular compositions, and demonstrate that immune cell co-infiltration at the tumor-stroma interface significantly influences clinical outcomes. To uncover the key drivers of the tumor ecosystem, we developed CEFIIRA (Cell Feature Importance Identification by RAndom forest), which identified tumor cell-intrinsic MHC-II expression as a critical predictor of prolonged survival, independent of clinicomolecular profiles. Validation with external datasets confirmed that MHC-II-expressing cancer cells drive immune infiltration and orchestrate spatial tumor-immune interactions. Our atlas offers novel insights into immune surveillance mechanisms across HGSC clinicomolecular groups, paving the way for improved therapeutic strategies and patient stratification.

cancer biology↗

bioRxiv2021

A novel immunopeptidomic-based pipeline for the generation of personalized oncolytic cancer vaccines

Beside the isolation and identification of MHC-I restricted peptides from the surface of cancer cells, one of the challenges is eliciting an effective anti-tumor CD8+ T cell mediated response as part of therapeutic cancer vaccine. Therefore, the establishment of a solid pipeline for the downstream selection of clinically relevant peptides and the subsequent creation of therapeutic cancer vaccines are of utmost importance. Indeed, the use of peptides for eliciting specific anti-tumor adaptive immunity is hindered by two main limitations: the efficient selection of the most optimal candidate peptides and the use of a highly immunogenic platform to combine with the peptides to induce effective tumor-specific adaptive immune responses. Here, we describe for the first time a streamlined pipeline for the generation of personalized cancer vaccines starting from the isolation and selection of the most immunogenic peptide candidates expressed on the tumor cells and ending in the generation of efficient therapeutic oncolytic cancer vaccines. This immunopeptidomics-based pipeline was carefully validated in a murine colon tumor model CT26. Specifically, we used state-of-the-art immunoprecipitation and mass spectrometric methodologies to isolate >8000 peptide targets from the CT26 tumor cell line. The selection of the target candidates was then based on two separate approaches: RNAseq analysis and the HEX software. The latter is a tool previously developed by Chiaro et al. (1), able to identify tumor antigens similar to pathogen antigens, in order to exploit molecular mimicry and tumor pathogen cross-reactive T-cells in cancer vaccine development. The generated list of candidates (twenty-six in total) was further tested in a functional characterization assay using interferon-{gamma} ELISpot (Enzyme-Linked Immunospot), reducing the number of candidates to six. These peptides were then tested in our previously described oncolytic cancer vaccine platform PeptiCRAd, a vaccine platform that combines an immunogenic oncolytic adenovirus (OAd) coated with tumor antigen peptides. In our work, PeptiCRAd was successfully used for the treatment of mice bearing CT26, controlling the primary malignant lesion and most importantly a secondary, non-treated, cancer lesion. These results confirmed the feasibility of applying the described pipeline for the selection of peptide candidates and generation of therapeutic oncolytic cancer vaccine, filling a gap in the field of cancer immunotherapy, and paving the way to translate our pipeline into human therapeutic approach.

cancer biology↗

bioRxiv2021

A personalized anti-cancer vaccine for melanoma based on an approved vaccine against measles, mumps, and rubella

Common vaccines for infectious diseases have been repurposed as cancer immunotherapies. Intratumoural administration of these repurposed vaccines can induce immune cell infiltration into the treated tumour. Here, we have used an approved trivalent live attenuated measles, mumps, and rubella (MMR) vaccine in our previously developed PeptiENV anti-cancer vaccine platform. Intratumoural administration of this novel MMR-containing PeptiENV anti-cancer vaccine significantly increased both intratumoural as well as systemic tumour-specific T cell responses. In addition, PeptiENV therapy, in combination with immune checkpoint inhibitor therapy, significantly improved tumour growth control and survival as well as increased the number of mice responsive to immune checkpoint inhibitor therapy.

immunology↗

bioRxiv2021

Computationally prioritized drugs inhibit SARS-CoV-2 infection and syncytia formation

New affordable therapeutic protocols for COVID-19 are urgently needed despite the increasing number of effective vaccines and monoclonal antibodies. To this end, there is increasing attention towards computational methods for drug repositioning and de novo drug design. Here, we systematically integrated multiple data-driven computational approaches to perform virtual screening and prioritize candidate drugs for the treatment of COVID-19. From the set of prioritized drugs, we selected a subset of representative candidates to test in human cells. Two compounds, 7-hydroxystaurosporine and bafetinib, showed synergistic antiviral effects in our in vitro experiments, and strongly inhibited viral-induced syncytia formation. Moreover, since existing drug repositioning methods provide limited usable information for de novo drug design, we extracted and prioritized the chemical substructures of the identified drugs, providing a chemical vocabulary that may help to design new effective drugs.

pharmacology and toxicology↗

bioRxiv2021

Novel personalized cancer vaccine platform based on Bacillus Calmette-Guerin

Intratumoural bacillus Calmette-Guerin (BCG) therapy, one of the earliest immunotherapies, can lead to infiltration of immune cells into a treated tumour. Here, we have developed a novel cancer vaccine platform based on BCG that can direct BCG-induced immune responses against tumour antigens. By physically attaching tumour-specific peptides onto the mycobacterial outer membrane, we were able to induce strong systemic and intratumoural T cell-specific immune responses towards the attached tumour antigens. These therapeutic peptides can be attached to the mycobacterial outer membrane using a cell-penetrating peptide sequence derived from human immunodeficiency virus Tat, N-terminally fused to the tumour-specific peptides. Alternatively, therapeutic peptides can be conjugated with a poly-lysine sequence N-terminally fused to the tumour-specific peptides. Using two mouse models of melanoma and a mouse model of colorectal cancer, we observed that the anti-tumour responses of BCG can be significantly improved by coating the BCG with tumour-specific peptides. In addition, by combining this novel cancer vaccine platform with anti-PD-1 immune checkpoint inhibitor therapy, the number of responders to anti-PD-1 immunotherapy can be significantly increased.

cancer biology↗