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Article ; Online: Correction: Predicting drug response from single-cell expression profiles of tumours.

Pellecchia, Simona / Viscido, Gaetano / Franchini, Melania / Gambardella, Gennaro

2024 Volume 22, Issue 1, Page(s) 70

Language	English
Publishing date	2024-02-16
Publishing country	England
Document type	Published Erratum
ZDB-ID	2131669-7
ISSN	1741-7015 ; 1741-7015
ISSN (online)	1741-7015
ISSN	1741-7015
DOI	10.1186/s12916-024-03289-z
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Article ; Online: Single cell lineage tracing reveals clonal dynamics of anti-EGFR therapy resistance in triple negative breast cancer.

Pellecchia, Simona / Franchini, Melania / Viscido, Gaetano / Arnese, Riccardo / Gambardella, Gennaro

Genome medicine

2024 Volume 16, Issue 1, Page(s) 55

Abstract: Background: Most primary Triple Negative Breast Cancers (TNBCs) show amplification of the Epidermal Growth Factor Receptor (EGFR) gene, leading to increased protein expression. However, unlike other EGFR-driven cancers, targeting this receptor in TNBC ... ...

Abstract	Background: Most primary Triple Negative Breast Cancers (TNBCs) show amplification of the Epidermal Growth Factor Receptor (EGFR) gene, leading to increased protein expression. However, unlike other EGFR-driven cancers, targeting this receptor in TNBC yields inconsistent therapeutic responses. Methods: To elucidate the underlying mechanisms of this variability, we employ cellular barcoding and single-cell transcriptomics to reconstruct the subclonal dynamics of EGFR-amplified TNBC cells in response to afatinib, a tyrosine kinase inhibitor (TKI) that irreversibly inhibits EGFR. Results: Integrated lineage tracing analysis revealed a rare pre-existing subpopulation of cells with distinct biological signature, including elevated expression levels of Insulin-Like Growth Factor Binding Protein 2 (IGFBP2). We show that IGFBP2 overexpression is sufficient to render TNBC cells tolerant to afatinib treatment by activating the compensatory insulin-like growth factor I receptor (IGF1-R) signalling pathway. Finally, based on reconstructed mechanisms of resistance, we employ deep learning techniques to predict the afatinib sensitivity of TNBC cells. Conclusions: Our strategy proved effective in reconstructing the complex signalling network driving EGFR-targeted therapy resistance, offering new insights for the development of individualized treatment strategies in TNBC.
MeSH term(s)	Humans ; Triple Negative Breast Neoplasms/drug therapy ; Triple Negative Breast Neoplasms/genetics ; Triple Negative Breast Neoplasms/metabolism ; Afatinib/pharmacology ; Afatinib/therapeutic use ; Cell Lineage ; ErbB Receptors ; Signal Transduction ; Protein Kinase Inhibitors/pharmacology ; Protein Kinase Inhibitors/therapeutic use ; Cell Line, Tumor
Chemical Substances	Afatinib (41UD74L59M) ; ErbB Receptors (EC 2.7.10.1) ; Protein Kinase Inhibitors ; EGFR protein, human (EC 2.7.10.1)
Language	English
Publishing date	2024-04-11
Publishing country	England
Document type	Journal Article
ZDB-ID	2484394-5
ISSN	1756-994X ; 1756-994X
ISSN (online)	1756-994X
ISSN	1756-994X
DOI	10.1186/s13073-024-01327-2
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Article ; Online: Single-cell gene set enrichment analysis and transfer learning for functional annotation of scRNA-seq data.

Franchini, Melania / Pellecchia, Simona / Viscido, Gaetano / Gambardella, Gennaro

NAR genomics and bioinformatics

2023 Volume 5, Issue 1, Page(s) lqad024

Abstract: Although an essential step, cell functional annotation often proves particularly challenging from single-cell transcriptional data. Several methods have been developed to accomplish this task. However, in most cases, these rely on techniques initially ... ...

Abstract	Although an essential step, cell functional annotation often proves particularly challenging from single-cell transcriptional data. Several methods have been developed to accomplish this task. However, in most cases, these rely on techniques initially developed for bulk RNA sequencing or simply make use of marker genes identified from cell clustering followed by supervised annotation. To overcome these limitations and automatize the process, we have developed two novel methods, the single-cell gene set enrichment analysis (scGSEA) and the single-cell mapper (scMAP). scGSEA combines latent data representations and gene set enrichment scores to detect coordinated gene activity at single-cell resolution. scMAP uses transfer learning techniques to re-purpose and contextualize new cells into a reference cell atlas. Using both simulated and real datasets, we show that scGSEA effectively recapitulates recurrent patterns of pathways' activity shared by cells from different experimental conditions. At the same time, we show that scMAP can reliably map and contextualize new single-cell profiles on a breast cancer atlas we recently released. Both tools are provided in an effective and straightforward workflow providing a framework to determine cell function and significantly improve annotation and interpretation of scRNA-seq data.
Language	English
Publishing date	2023-03-03
Publishing country	England
Document type	Journal Article
ISSN	2631-9268
ISSN (online)	2631-9268
DOI	10.1093/nargab/lqad024
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Article ; Online: Predicting drug response from single-cell expression profiles of tumours.

Pellecchia, Simona / Viscido, Gaetano / Franchini, Melania / Gambardella, Gennaro

BMC medicine

2023 Volume 21, Issue 1, Page(s) 476

Abstract: Background: Intra-tumour heterogeneity (ITH) presents a significant obstacle in formulating effective treatment strategies in clinical practice. Single-cell RNA sequencing (scRNA-seq) has evolved as a powerful instrument for probing ITH at the ... ...

Abstract	Background: Intra-tumour heterogeneity (ITH) presents a significant obstacle in formulating effective treatment strategies in clinical practice. Single-cell RNA sequencing (scRNA-seq) has evolved as a powerful instrument for probing ITH at the transcriptional level, offering an unparalleled opportunity for therapeutic intervention. Results: Drug response prediction at the single-cell level is an emerging field of research that aims to improve the efficacy and precision of cancer treatments. Here, we introduce DREEP (Drug Response Estimation from single-cell Expression Profiles), a computational method that leverages publicly available pharmacogenomic screens from GDSC2, CTRP2, and PRISM and functional enrichment analysis to predict single-cell drug sensitivity from transcriptomic data. We validated DREEP extensively in vitro using several independent single-cell datasets with over 200 cancer cell lines and showed its accuracy and robustness. Additionally, we also applied DREEP to molecularly barcoded breast cancer cells and identified drugs that can selectively target specific cell populations. Conclusions: DREEP provides an in silico framework to prioritize drugs from single-cell transcriptional profiles of tumours and thus helps in designing personalized treatment strategies and accelerating drug repurposing studies. DREEP is available at https://github.com/gambalab/DREEP .
MeSH term(s)	Humans ; Neoplasms/drug therapy ; Neoplasms/genetics ; Gene Expression Profiling/methods ; Transcriptome ; Sequence Analysis, RNA/methods ; Software
Language	English
Publishing date	2023-12-01
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2131669-7
ISSN	1741-7015 ; 1741-7015
ISSN (online)	1741-7015
ISSN	1741-7015
DOI	10.1186/s12916-023-03182-1
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Article: A Tool for Visualization and Analysis of Single-Cell RNA-Seq Data Based on Text Mining.

Gambardella, Gennaro / di Bernardo, Diego

Frontiers in genetics

2019 Volume 10, Page(s) 734

Abstract: Gene expression in individual cells can now be measured for thousands of cells in a single experiment thanks to innovative sample-preparation and sequencing technologies. State-of-the-art computational pipelines for single-cell RNA-sequencing data, ... ...

Abstract	Gene expression in individual cells can now be measured for thousands of cells in a single experiment thanks to innovative sample-preparation and sequencing technologies. State-of-the-art computational pipelines for single-cell RNA-sequencing data, however, still employ computational methods that were developed for traditional bulk RNA-sequencing data, thus not accounting for the peculiarities of single-cell data, such as sparseness and zero-inflated counts. Here, we present a ready-to-use pipeline named
Language	English
Publishing date	2019-08-09
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2019.00734
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Article ; Online: Single-Cell RNA Sequencing Analysis: A Step-by-Step Overview.

Slovin, Shaked / Carissimo, Annamaria / Panariello, Francesco / Grimaldi, Antonio / Bouché, Valentina / Gambardella, Gennaro / Cacchiarelli, Davide

Methods in molecular biology (Clifton, N.J.)

2021 Volume 2284, Page(s) 343–365

Abstract: Thanks to innovative sample-preparation and sequencing technologies, gene expression in individual cells can now be measured for thousands of cells in a single experiment. Since its introduction, single-cell RNA sequencing (scRNA-seq) approaches have ... ...

Abstract	Thanks to innovative sample-preparation and sequencing technologies, gene expression in individual cells can now be measured for thousands of cells in a single experiment. Since its introduction, single-cell RNA sequencing (scRNA-seq) approaches have revolutionized the genomics field as they created unprecedented opportunities for resolving cell heterogeneity by exploring gene expression profiles at a single-cell resolution. However, the rapidly evolving field of scRNA-seq invoked the emergence of various analytics approaches aimed to maximize the full potential of this novel strategy. Unlike population-based RNA sequencing approaches, scRNA seq necessitates comprehensive computational tools to address high data complexity and keep up with the emerging single-cell associated challenges. Despite the vast number of analytical methods, a universal standardization is lacking. While this reflects the fields' immaturity, it may also encumber a newcomer to blend in.In this review, we aim to bridge over the abovementioned hurdle and propose four ready-to-use pipelines for scRNA-seq analysis easily accessible by a newcomer, that could fit various biological data types. Here we provide an overview of the currently available single-cell technologies for cell isolation and library preparation and a step by step guide that covers the entire canonical analytic workflow to analyse scRNA-seq data including read mapping, quality controls, gene expression quantification, normalization, feature selection, dimensionality reduction, and cell clustering useful for trajectory inference and differential expression. Such workflow guidelines will escort novices as well as expert users in the analysis of complex scRNA-seq datasets, thus further expanding the research potential of single-cell approaches in basic science, and envisaging its future implementation as best practice in the field.
MeSH term(s)	Algorithms ; Animals ; Cluster Analysis ; Gene Expression Profiling/methods ; Gene Expression Profiling/statistics & numerical data ; Genomics/methods ; High-Throughput Nucleotide Sequencing/methods ; High-Throughput Nucleotide Sequencing/statistics & numerical data ; Humans ; Quality Control ; Sequence Analysis, RNA/methods ; Sequence Analysis, RNA/statistics & numerical data ; Single-Cell Analysis/methods ; Single-Cell Analysis/statistics & numerical data ; Software ; Transcriptome
Language	English
Publishing date	2021-04-09
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-0716-1307-8_19
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Article ; Online: β-catenin perturbations control differentiation programs in mouse embryonic stem cells.

Pedone, Elisa / Failli, Mario / Gambardella, Gennaro / De Cegli, Rossella / La Regina, Antonella / di Bernardo, Diego / Marucci, Lucia

iScience

2022 Volume 25, Issue 2, Page(s) 103756

Abstract: The Wnt/β-catenin pathway is involved in development, cancer, and embryonic stem cell (ESC) maintenance; its dual role in stem cell self-renewal and differentiation is still controversial. Here, by applying ... ...

Abstract	The Wnt/β-catenin pathway is involved in development, cancer, and embryonic stem cell (ESC) maintenance; its dual role in stem cell self-renewal and differentiation is still controversial. Here, by applying an
Language	English
Publishing date	2022-01-10
Publishing country	United States
Document type	Journal Article
ISSN	2589-0042
ISSN (online)	2589-0042
DOI	10.1016/j.isci.2022.103756
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Article ; Online: MicroRNA 483-3p overexpression unleashes invasive growth of metastatic colorectal cancer via NDRG1 downregulation and ensuing activation of the ERBB3/AKT axis.

Candiello, Ermes / Reato, Gigliola / Verginelli, Federica / Gambardella, Gennaro / D Ambrosio, Antonio / Calandra, Noemi / Orzan, Francesca / Iuliano, Antonella / Albano, Raffaella / Sassi, Francesco / Luraghi, Paolo / Comoglio, Paolo M / Bertotti, Andrea / Trusolino, Livio / Boccaccio, Carla

Molecular oncology

2023 Volume 17, Issue 7, Page(s) 1280–1301

Abstract: In colorectal cancer, the mechanisms underlying tumor aggressiveness require further elucidation. Taking advantage of a large panel of human metastatic colorectal cancer xenografts and matched stem-like cell cultures (m-colospheres), here we show that ... ...

Abstract	In colorectal cancer, the mechanisms underlying tumor aggressiveness require further elucidation. Taking advantage of a large panel of human metastatic colorectal cancer xenografts and matched stem-like cell cultures (m-colospheres), here we show that the overexpression of microRNA 483-3p (miRNA-483-3p; also known as MIR-483-3p), encoded by a frequently amplified gene locus, confers an aggressive phenotype. In m-colospheres, endogenous or ectopic miRNA-483-3p overexpression increased proliferative response, invasiveness, stem cell frequency, and resistance to differentiation. Transcriptomic analyses and functional validation found that miRNA-483-3p directly targets NDRG1, known as a metastasis suppressor involved in EGFR family downregulation. Mechanistically, miRNA-483-3p overexpression induced the signaling pathway triggered by ERBB3, including AKT and GSK3β, and led to the activation of transcription factors regulating epithelial-mesenchymal transition (EMT). Consistently, treatment with selective anti-ERBB3 antibodies counteracted the invasive growth of miRNA-483-3p-overexpressing m-colospheres. In human colorectal tumors, miRNA-483-3p expression inversely correlated with NDRG1 and directly correlated with EMT transcription factor expression and poor prognosis. These results unveil a previously unrecognized link between miRNA-483-3p, NDRG1, and ERBB3-AKT signaling that can directly support colorectal cancer invasion and is amenable to therapeutic targeting.
MeSH term(s)	Humans ; Proto-Oncogene Proteins c-akt/metabolism ; Down-Regulation/genetics ; Cell Line, Tumor ; MicroRNAs/genetics ; MicroRNAs/metabolism ; Colorectal Neoplasms/pathology ; Colonic Neoplasms/genetics ; Transcription Factors/metabolism ; Rectal Neoplasms/genetics ; Epithelial-Mesenchymal Transition/genetics ; Gene Expression Regulation, Neoplastic ; Cell Movement/genetics ; Neoplasm Invasiveness/genetics
Chemical Substances	Proto-Oncogene Proteins c-akt (EC 2.7.11.1) ; MicroRNAs ; Transcription Factors ; MIRN483 microRNA, human
Language	English
Publishing date	2023-03-19
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2415106-3
ISSN	1878-0261 ; 1574-7891
ISSN (online)	1878-0261
ISSN	1574-7891
DOI	10.1002/1878-0261.13408
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Article ; Online: Mutated axon guidance gene PLXNB2 sustains growth and invasiveness of stem cells isolated from cancers of unknown primary.

Brundu, Serena / Napolitano, Virginia / Franzolin, Giulia / Lo Cascio, Ettore / Mastrantonio, Roberta / Sardo, Gabriele / Cascardi, Eliano / Verginelli, Federica / Sarnataro, Sergio / Gambardella, Gennaro / Pisacane, Alberto / Arcovito, Alessandro / Boccaccio, Carla / Comoglio, Paolo M / Giraudo, Enrico / Tamagnone, Luca

EMBO molecular medicine

2023 Volume 15, Issue 3, Page(s) e16104

Abstract: The genetic changes sustaining the development of cancers of unknown primary (CUP) remain elusive. The whole-exome genomic profiling of 14 rigorously selected CUP samples did not reveal specific recurring mutation in known driver genes. However, by ... ...

Abstract	The genetic changes sustaining the development of cancers of unknown primary (CUP) remain elusive. The whole-exome genomic profiling of 14 rigorously selected CUP samples did not reveal specific recurring mutation in known driver genes. However, by comparing the mutational landscape of CUPs with that of most other human tumor types, it emerged a consistent enrichment of changes in genes belonging to the axon guidance KEGG pathway. In particular, G842C mutation of PlexinB2 (PlxnB2) was predicted to be activating. Indeed, knocking down the mutated, but not the wild-type, PlxnB2 in CUP stem cells resulted in the impairment of self-renewal and proliferation in culture, as well as tumorigenic capacity in mice. Conversely, the genetic transfer of G842C-PlxnB2 was sufficient to promote CUP stem cell proliferation and tumorigenesis in mice. Notably, G842C-PlxnB2 expression in CUP cells was associated with basal EGFR phosphorylation, and EGFR blockade impaired the viability of CUP cells reliant on the mutated receptor. Moreover, the mutated PlxnB2 elicited CUP cell invasiveness, blocked by EGFR inhibitor treatment. In sum, we found that a novel activating mutation of the axon guidance gene PLXNB2 sustains proliferative autonomy and confers invasive properties to stem cells isolated from cancers of unknown primary, in EGFR-dependent manner.
MeSH term(s)	Animals ; Humans ; Mice ; Axon Guidance ; ErbB Receptors/genetics ; Mutation ; Neoplasm Recurrence, Local ; Neoplasms, Unknown Primary/genetics ; Nerve Tissue Proteins/genetics ; Neoplastic Stem Cells/pathology
Chemical Substances	ErbB Receptors (EC 2.7.10.1) ; PLXNB2 protein, human ; Plxnb2 protein, mouse ; Nerve Tissue Proteins
Language	English
Publishing date	2023-02-01
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2467145-9
ISSN	1757-4684 ; 1757-4676
ISSN (online)	1757-4684
ISSN	1757-4676
DOI	10.15252/emmm.202216104
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Article ; Online: MEGA-V: detection of variant gene sets in patient cohorts.

Gambardella, Gennaro / Cereda, Matteo / Benedetti, Lorena / Ciccarelli, Francesca D

Bioinformatics (Oxford, England)

2017 Volume 33, Issue 8, Page(s) 1248–1249

Abstract: Summary: : Detecting significant associations between genetic variants and disease may prove particularly challenging when the variants are rare in the population and/or act together with other variants to cause the disease. We have developed a ... ...

Abstract	Summary: : Detecting significant associations between genetic variants and disease may prove particularly challenging when the variants are rare in the population and/or act together with other variants to cause the disease. We have developed a statistical framework named Mutation Enrichment Gene set Analysis of Variants (MEGA-V) that specifically detects the enrichments of genetic alterations within a process in a cohort of interest. By focusing on the mutations of several genes contributing to the same function rather than on those affecting a single gene, MEGA-V increases the power to detect statistically significant associations. Availability and implementation: MEGA-V is available at https://github.com/ciccalab/MEGA. Contact: francesca.ciccarelli@kcl.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.
MeSH term(s)	Cohort Studies ; Data Interpretation, Statistical ; Humans ; Mutation ; Software
Language	English
Publishing date	2017-04-15
Publishing country	England
Document type	Journal Article
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btw809
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