Biology subjects

Caruso, F. P.

Publications and source records attributed to Caruso, F. P..

5 recordsLinked to original sources

bioRxiv2025

Transposable Elements and Homotypic Niches Drive Immune Dynamics and Resistance in Melanoma Epigenetic-based immunotherapy

Melanoma plasticity drives immune evasion and therapy resistance through dynamic cell-state transitions beyond genetic alterations. Epigenetic remodeling critically influences such processes, yet its role in reshaping the tumor ecosystem under therapeutic pressure remains unresolved. Here, we profiled longitudinal biopsies from melanoma patients treated in the phase Ib NIBIT-M4 epi-immunotherapy clinical trial (NCT02608437), testing the combination of a DNMT1 inhibitor with anti-CTLA4 using single-cell multiome and high-resolution spatial transcriptomics. Integrated analyses resolved seven malignant meta-programs, including a rare Wnt/{beta}-catenin-driven melanocytic state and a de-differentiated neural crest-like state enriched in non-responders. Spatial modeling revealed that homotypic clustering stabilizes resistant programs, with neural crest-like cells forming compact, centrally localized niches, whereas Wnt/{beta}-catenin subpopulations displayed a bimodal architecture, either cohesive clusters sustained by adhesion or dispersed, transcriptionally plastic cells. Responders exhibited progressive enrichment of an antigen presentation/interferon program and coordinated remodeling of the tumor microenvironment with T and B cell expansion, whereas tumors from non-responder patients maintained stable composition of neural crest-like clusters. Epigenetic therapy reactivated transposable elements, providing both regulatory signals that prime innate immunity within microenvironment and generating antigens that drive immunoediting and immunogenicity of Antigen presentation/interferon cell states in responders. Finally, NFATC2 emerged as a master regulator of neural crests-like transcriptional phenotypes and promoter of resistance to therapeutic interventions in melanoma patients. NFATC2 perturbation was able to shift tumor cells towards more differentiated and immunogenic states. These findings reveal how epigenetic-based immunotherapy reshapes melanoma ecosystems, provide mechanistic insights into how multiple transcriptional programs promote tumor plasticity and resistance to both combinatorial therapies and immune checkpoint blockade, identify spatial clustering as a principle stabilizing resistant niches, and highlight {beta}-catenin and NFATC2 as actionable vulnerabilities to overcome resistance.

genomics↗

bioRxiv2025

Integrated multi-omics profiling reveals the role of the DNA methylation landscape in shaping biological heterogeneity and clinical behaviour of metastatic melanoma

The biological and clinical relevance of the DNA methylation landscape in metastatic melanoma (MM) remains underexplored. In a retrospective cohort of 191 MM lesions from 165 AJCC Stage III and IV patients (EPICA cohort) we identified four tumor subsets (i.e. DEMethylated, LOW, INTermediate and CIMP) with progressively increasing levels of DNA methylation. These findings were validated in the TCGA MM. In EPICA, patients with LOW methylation tumors exhibited a significantly longer survival and a lower progression rate to more advanced AJCC stages, compared to patients with CIMP tumors. Furthermore, in an independent adjuvant immune checkpoint blockade MM cohort, patients with DEM/LOW pre-therapy lesions showed significantly longer relapse-free survival compared to those with INT/CIMP lesions. RNA-seq data analysis revealed that LOW and CIMP EPICA tumors showed opposite activation of master molecules influencing prognostic target genes, and differential expression of immunotherapy response and melanoma differentiation signatures. Compared to CIMP tumors, LOW lesions showed enrichment for pre-exhausted and exhausted T cells and more frequent retention of HLA Class I antigens. The differentiation and immune-related transcriptional features associated with LOW vs CIMP lesions were tumor-intrinsic programs retained in-vitro by melanoma cell lines. Consistently, treatment of differentiated melanoma cell lines with a DNMT inhibitor induced global DNA de-methylation, promoted de-differentiation and upregulated viral mimicry and IFNG predictive signatures of immunotherapy response. These findings underscore the role of DNA methylation in driving MM biological and clinical heterogeneity and support exploration of methylome targeting strategies for precision immunotherapy in melanoma.

cancer biology↗

bioRxiv2024

DNA methylation status classifies pleural mesothelioma cells according to their immune profile: implication for precision epigenetic therapy

Backgroundco-targeting of immune checkpoint inhibitors (ICI) CTLA-4 and PD-1 has recently become the new first-line standard of care therapy of pleural mesothelioma (PM) patients, with a significant improvement of overall survival over conventional chemotherapy. The analysis by tumor histotype demonstrated a greater efficacy of ICI therapy in non-epithelioid (non-E) vs epithelioid (E) PM; although some E PM patients also benefit from treatment. This evidence suggests that molecular tumor features, beyond histotype, could be relevant to improve the efficacy of ICI therapy in PM. Among these, tumor DNA methylation emerges as a promising factor to explore, due to its potential role in driving the immune phenotype of cancer cells. Thus, we utilized a panel of cultured PM cells of different histotype, to provide preclinical evidence supporting the role of the tumor methylation landscape and of its pharmacologic modulation, to prospectively improve the efficacy of ICI therapy of PM patients. Methodsthe methylome profile (EPIC array) of distinct E (#5) and non-E (#9) PM cell lines was analyzed, followed by integrated analysis with their associated transcriptomic profile (Clariom S array), before and after in vitro treatment with the DNA hypomethylating agent (DHA) guadecitabine. The most variable methylated probes were selected to calculate the methylation score (CIMP index) for each cell line at baseline. Genes that were differentially expressed and methylated were then selected for gene ontology analysis. Resultsthe CIMP index stratified PM cell lines in two distinct classes, CIMP (hyper-methylated; #7) and LOW (hypo-methylated; #7), regardless of their E or non-E histotype. Integrated analyses of methylome and transcriptome data revealed that CIMP PM cells had a substantial number of hyper-methylated, silenced genes, which negatively impacted their immune phenotype compared to LOW PM cells. Treatment with DHA reverted the methylation-driven immune-compromised profile of CIMP PM cells and enhanced the constitutive immune-favorable profile of LOW PM cells. Conclusionthe study highlighted the relevance of DNA methylation in shaping the constitutive immune classification of PM cells, that is independent from their histological subtypes. The identified role of DHA in shifting the phenotype of PM cells towards an immune-favorable state supports its role in clinical trials of precision epigenetic therapy combined with ICI.

cancer biology↗

bioRxiv2022

Community assessment of methods to deconvolve cellular composition from bulk gene expression

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

bioinformatics↗

bioRxiv2021

A fast variational algorithm to detect the clonal copy number substructure of tumors from single-cell data

Here we report Single CEll Variational ANeuploidy analysis (SCEVAN), a fast variational algorithm for the deconvolution of the clonal substructure of tumors from single cell data. It uses a multichannel segmentation algorithm exploiting the assumption that all the cells in a given copy number clone share the same breakpoints. Thus, the smoothed expression profile of every individual cell constitutes part of the evidence of the copy number profile in each subclone. SCEVAN can automatically and accurately discriminate between malignant and non-malignant cells, resulting in a practical framework to analyze tumors and their microenvironment. We apply SCEVAN to several datasets encompassing 106 samples and 93,322 cells from different tumors types and technologies. We demonstrate its application to characterize the intratumor heterogeneity and geographic evolution of malignant brain tumors.

bioinformatics↗