Armando Giuseppe Licata

@istitutotumori.mi.it

Integrated Biology of Rare Tumors
Fondazione IRCCS Istituto Nazionale dei Tumori

Armando Giuseppe Licata


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https://researchid.co/licataarmando

RESEARCH, TEACHING, or OTHER INTERESTS

Oncology
7

Scopus Publications

Scopus Publications

  • A QIIME2-based workflowfor multi-amplicon 16S rRNA profiling
    Armando G. Licata, Marica Zoppi, Chiara Dossena, Federico Rossignoli, Davide Rizzo, Luca Bergamaschi, Olga Nigro, Stefano Chiaravalli, Maura Massimino, Loris De Cecco
    Microbiology Resource Announcements, 2026
    We present an open-source QIIME2 pipeline for 16S multi-amplicon sequencing. Benchmarked against proprietary software with a mock community, our workflow demonstrates comparable sequencing depth and taxonomic accuracy (F1-Score=0.875). The multi-region approach outperforms single amplicons, validating our pipeline as a robust alternative for semiconductor-based sequencing data.
  • QIIME2 enhances multi-amplicon sequencing data analysis: a standardized and validated open-source pipeline for comprehensive 16S rRNA gene profiling
    Armando G. Licata, Marica Zoppi, Chiara Dossena, Federico Rossignoli, Davide Rizzo, Manuela Marra, Giorgio Gargari, Giacomo Mantegazza, Simone Guglielmetti, Luca Bergamaschi, Olga Nigro, Stefano Chiaravalli, Maura Massimino, Loris De Cecco
    Microbiology Spectrum, 2025
    Multi-amplicon sequencing is a cost-effective method for profiling multiple regions of the 16S rRNA gene, offering a more comprehensive view of microbial diversity. However, implementing such pipelines on open-source platforms (e.g., QIIME2) is often hindered by limited documentation and lack of validation against established tools. This lack of standardization poses challenges for researchers, particularly in clinical and experimental settings. This study aims to: (i) develop and benchmark a standardized, open-source QIIME2- and R-based pipeline for 16S rRNA gene profiling using semiconductor-based sequencing, comparing it with a commercial, closed-source software; and (ii) validate its effectiveness in a pediatric cancer cohort to examine parental influence on the microbiome and child-caregiver microbial relationships. We generated 16S rRNA profiles from 5 mock communities and 12 child-caregiver fecal sample pairs. Benchmarking against commercial software showed that the multi-region (V2–9) approach produced microbial profiles nearly identical to proprietary outputs, with higher sequencing depth and improved taxonomic resolution compared to single-region analyses. Both approaches demonstrated similar microbial richness, accurate mock community reconstruction, and high reproducibility ( R = 0.99, P < 0.0001). These findings were further validated using fecal samples. Application of the pipeline to pediatric samples revealed distinct, differentially abundant Bifidobacterium bifidum and Bifidobacterium adolescentis variants in children whose microbiota closely resembled that of their caregivers. Overall, this study presents a validated, open-source QIIME2 and R pipeline for multi-amplicon sequencing, providing a standardized and reproducible framework for 16S rRNA gene profiling in clinical and research contexts. IMPORTANCE Multi-amplicon sequencing comprehensively characterizes microbial communities by targeting multiple regions of the 16S rRNA gene. However, analytical workflows and reference databases provided by commercial library preparation kits frequently rely on proprietary primers and closed-source pipelines, which can limit transparency, reproducibility, and adaptability. To address these limitations, we developed and validated an open-source bioinformatics pipeline utilizing QIIME2 and R. Our pipeline integrates data from all targeted 16S regions, generating microbial profiles comparable to those produced by proprietary software. Validation was performed using mock samples and fecal samples collected from pediatric cancer patients and their caregivers, confirming the pipeline’s reliability and broad applicability. Furthermore, our pipeline enables detailed analysis of microbial variants, surpassing traditional genus-level restrictions and fully leveraging the enhanced coverage offered by multi-amplicon sequencing. Our findings highlight the necessity of adopting open-source solutions to ensure scientific reproducibility and adaptability to emerging methodologies.
  • The interplay of hypoxia, inflammation, and microbiota as indicators of malignant transformation in oral potentially malignant disorders
    Cristina Gurizzan, Armando G. Licata, Luigi Lorini, Cesare Piazza, Davide Mattavelli, Alberto Paderno, Simonetta Battocchio, Laura Ardighieri, Anna Bozzola, Carlo Resteghini, Chiara Magri, Chiara Romani, Deborah Lenoci, Marta Lucchetta, Mara S. Serafini, Loris De Cecco, Paolo Bossi
    Oral Oncology, 2025
    Oral Potentially Malignant Disorders (OPMDs), such as leukoplakia, erythroplakia, proliferative verrucous leukoplakia, and oral submucous fibrosis, carry a risk of malignant transformation, with reported rates ranging from 2.6 % to 7.9 %. Higher risks are observed in specific subtypes, such as erythroplakia and proliferative verrucous leukoplakia. Although clinical factors like lesion size, dysplasia, and patient demographics have been studied, none have consistently proven reliable for predicting malignancy. This study conducted a retrospective review of OPMD patients treated at the University of Brescia from 1996 to 2019, including various dysplasia grades and extensive clinical data. Gene expression profiling was performed on these samples to explore molecular stratification based on a six-subtype classification developed for Head and Neck Squamous Cell Carcinoma (HNSCC). Additionally, intratumor microbiota content was analyzed to assess its association with OPMD transformation risk. The findings highlighted the aggressive nature of the Cl3-Hypoxia molecular subtype, with a median malignant transformation time of 30.1 months. Considering the role of hypoxia in modulating tumor-associated inflammatory cell functions, we also assessed two inflammatory gene signatures, demonstrating their significant association with OPMDs and correlating with tissue-resident microbiota. This study provides compelling evidence of microbial-host interactions in the malignant transformation of OPMDs, with specific molecular features, particularly hypoxia-related pathways, linked to increased malignancy risk. These results suggest potential biomarkers for prognosis and offer therapeutic strategies targeting the tumor microenvironment and microbiota to mitigate malignant progression in high-risk OPMD patients.
  • Distinct gut microbiota composition in pediatric patients with central nervous system (CNS) tumors: A comparative study
    Chiara Dossena, Luca Bergamaschi, Federico Rossignoli, Armando Giuseppe Licata, Patrizia Gasparini, Lara Veronica Venturini, Manuela Marra, Oriani Matilde, Veronica Biassoni, Elisabetta Schiavello, Olga Nigro, Stefano Chiaravalli, Maura Massimino, Loris De Cecco
    Neuro Oncology Advances, 2025
    Background Central nervous system (CNS) tumors are the leading cause of cancer-related deaths in children aged 0–14 years. Despite significant efforts, targeted therapies based on identified pathways have not improved survival rates. Research has shown that the gut microbiota (GM) can influence brain tumor cell proliferation, suggesting that the microbiota–gut–brain axis plays a role in CNS cancer. Our study aims to assess whether the GM composition in pediatric CNS tumors exhibits specific characteristics. Methods The study included 18 pediatric patients, 9 diagnosed with CNS tumors (CNS tumors group) and 9 with other tumor types (extra-CNS tumors group). Microbial DNA was extracted from stool samples, and 16S DNA libraries were generated and sequenced. GM composition was analyzed using amplicon sequence variant (ASV) tables. Results Alpha-diversity analysis, represented by the number of observed features, was lower in the CNS tumors group (P = .0054), while Pielou’s evenness index was similar between groups. LEfSe analysis revealed a significantly reduced abundance of the Firmicutes phylum in CNS tumors group, along with other taxa within this phylum, such as the Clostridia class, Clostridiales order, and Lachnospiraceae family, compared to extra-CNS tumors group. Further analysis using sPLS-DA showed a distinct pattern in GM composition in the CNS tumors group, with lower levels of several taxa, particularly the Firmicutes phylum, Lachnospiraceae family, Clostridiales order, Clostridia class, Ruminococcaceae and Coriobacteriaceae families, and Blautia genus. Conclusions Pediatric patients with CNS tumors have a distinct GM composition. The reduction of specific beneficial microbial taxa may contribute to tumor growth through the microbiota–gut–brain axis.
  • Peritoneal fluid COVID-19 testing in patients with a negative nasopharyngeal swab: prospective study
    Armando G Licata, Chiara M Ciniselli, Luca Sorrentino, Arianna Micali, Maria Grazia Daidone, Marcello Guaglio, Manuela Gariboldi, Paolo Verderio, Loris De Cecco, Maurizio Cosimelli
    British Journal of Surgery, 2023
    Molecular Mechanisms Unit, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy Bioinformatics and Biostatistics Unit, Department of Applied Research and Technological Development, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy Colorectal Surgery Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy Scientific Directorate, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy Genetic Epidemiology and Pharmacogenomics Unit Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
  • Use of kefir-derived lactic acid bacteria for the preparation of a fermented soy drink with increased estrogenic activity
    Giacomo Mantegazza, Alessandro Dalla Via, Armando Licata, Robin Duncan, Claudio Gardana, Giorgio Gargari, Cristina Alamprese, Stefania Arioli, Valentina Taverniti, Matti Karp, Simone Guglielmetti
    Food Research International, 2023
  • hacksig: A unified and tidy R framework to easily compute gene expression signature scores
    Andrea Carenzo, Federico Pistore, Mara S Serafini, Deborah Lenoci, Armando G Licata, Loris De Cecco
    Bioinformatics, 2022
    Summary Hundreds of gene expression signatures have been developed during the last two decades. However, due to the multitude of development procedures and sometimes a lack of explanation for their implementation, it can become challenging to apply the original method on custom data. Moreover, at present, there is no unified and tidy interface to compute signature scores with different single sample enrichment methods. For these reasons, we developed hacksig, an R package intended as a unified framework to obtain single sample scores with a tidy output as well as a collection of manually curated gene signatures and methods from cancer transcriptomics literature. Availability and implementation The hacksig R package is freely available on CRAN (https://CRAN.R-project.org/package=hacksig) under the MIT license. The source code can be found on GitHub at https://github.com/Acare/hacksig. Supplementary information Supplementary data are available at Bioinformatics online.