The Cancermuts software package for the prioritization of missense cancer variants: a case study of AMBRA1 in melanoma

Tiberti, Matteo; Leo, Luca Di; Vistesen, Mette Vixø; Kuhre, Rikke Sofie; Cecconi, Francesco; Zio, Daniela De; Papaleo, Elena

doi:10.1038/s41419-022-05318-2

Cited by 10 publications

(13 citation statements)

References 56 publications

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“…On the contrary, if after the structure-based calculations the substitution is expected to retain the properties of the phospho-site the annotation is changed to ‘neutral’. The PTM module takes advantage of the annotations provided by our recently developed Cancer-muts package 52 for searching SLiM motifs and identifying the phospho-sites.…”

Section: Resultsmentioning

confidence: 99%

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MAVISp: A Modular Structure-Based Framework for Protein Variant Effects

Arnaudi

Beltrame

Degn

et al. 2022

Preprint

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Cancer is a complex group of diseases due to the accumulation of mutations in tumor suppressors or oncogenes in the genome. Cancer alterations can be very heterogeneous, even in tumors from the same tissue, affecting the response to treatment and risks of relapse in different patients. The role of genomics variants on cancer predisposition, progression, and response to treatment continues to be realized. Thanks to advances in sequencing techniques and their introduction in a clinical setting, the number of genomic variants discovered is growing exponentially. Many of these variants are classified as Variants of Uncertain Significance (VUS), while other variants have been reported with conflicting evidence. Applications of bioinformatic-based approaches to characterize the effects of these variants demonstrated their full potential thanks to advances in machine learning, comparisons between predicted effects and cellular readouts, and advances in the field of structural biology and biomolecular simulations. We here introduce a modular structure-based framework for the annotations and classification of the impact of variants affecting the coding region of genes and impacting on the corresponding protein product (MAVISp, Multi-layered Assessment of VarIants by Structure for proteins) together with a Streamlit-based web application (https://github.com/ELELAB/MAVISp) where the variants and the data generated by the assessment are made available to the community for consultation or further studies. Currently, MAVISp includes information for ten different proteins and more than 4000 variants. New protein targets are routinely analyzed in batches through standardized Python-based workflows and high-throughput free energy and biomolecular simulations. We also illustrate the potential of the approach for each protein included in the database. New variants will be deposited on a regular base or in connection with future publications where the approach will be applied. Finally, we provide guidelines for new contributors who are interested in contributing to the collection in relation to their research.

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Section: Resultsmentioning

confidence: 99%

“…We will plan regular updates of the entries in the MAVISp database to add new variants or correct previously misreported ones. The variants are retrieved using ClinVarMiner 53 and Cancermuts 52 .…”

Section: Resultsmentioning

confidence: 99%

MAVISp: A Modular Structure-Based Framework for Protein Variant Effects

Arnaudi

Beltrame

Degn

et al. 2022

Preprint

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“…Generation and transfection of AMBRA1 mutants were carried out as described in a study by Tiberti et al . 19 After 24 hours from transfection of cells with siAMBRA1 #2, re-expression of the mutants was performed for a total of 24 hours; a myc-ß-Gal plasmid cloned in the pcDNA3.1 Mammalian Expression Vector (Thermo Fisher Scientific, Massachusetts, USA; cat# V79020) was used as negative control.…”

Section: Methodsmentioning

confidence: 99%

Ambra1 modulates the tumor immune microenvironment and response to PD-1 blockade in melanoma

Frías

Leo

Antoranz

et al. 2023

J Immunother Cancer

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BackgroundLoss of Ambra1 (autophagy and beclin 1 regulator 1), a multifunctional scaffold protein, promotes the formation of nevi and contributes to several phases of melanoma development. The suppressive functions of Ambra1 in melanoma are mediated by negative regulation of cell proliferation and invasion; however, evidence suggests that loss of Ambra1 may also affect the melanoma microenvironment. Here, we investigate the possible impact of Ambra1 on antitumor immunity and response to immunotherapy.MethodsThis study was performed using an Ambra1-depletedBrafV600E/Pten−/−genetically engineered mouse (GEM) model of melanoma, as well as GEM-derived allografts ofBrafV600E/Pten−/−andBrafV600E/Pten−/−/Cdkn2a−/−tumors with Ambra1 knockdown. The effects of Ambra1 loss on the tumor immune microenvironment (TIME) were analyzed using NanoString technology, multiplex immunohistochemistry, and flow cytometry. Transcriptome and CIBERSORT digital cytometry analyses of murine melanoma samples and human melanoma patients (The Cancer Genome Atlas) were applied to determine the immune cell populations in null or low-expressing AMBRA1 melanoma. The contribution of Ambra1 on T-cell migration was evaluated using a cytokine array and flow cytometry. Tumor growth kinetics and overall survival analysis inBrafV600E/Pten−/−/Cdkn2a−/−mice with Ambra1 knockdown were evaluated prior to and after administration of a programmed cell death protein-1 (PD-1) inhibitor.ResultsLoss of Ambra1 was associated with altered expression of a wide range of cytokines and chemokines as well as decreased infiltration of tumors by regulatory T cells, a subpopulation of T cells with potent immune-suppressive properties. These changes in TIME composition were associated with the autophagic function of Ambra1. In theBrafV600E/Pten−/−/Cdkn2a−/−model inherently resistant to immune checkpoint blockade, knockdown of Ambra1 led to accelerated tumor growth and reduced overall survival, but at the same time conferred sensitivity to anti-PD-1 treatment.ConclusionsThis study shows that loss of Ambra1 affects the TIME and the antitumor immune response in melanoma, highlighting new functions of Ambra1 in the regulation of melanoma biology.

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“…We used ClinVar Miner 94 to identify variants from ClinVar, whereas the aggregation step and the search for variants in COSMIC and cBioPortal have been carried out with Cancermuts 95 . For TP53, we used Cancermuts to include also mutations from other sources 56 .…”

Section: Methodsmentioning

confidence: 99%

“…This step has been performed since the protocols for free energy calculations upon mutations applied in the MAVISp framework are currently not supporting transmembrane regions. We used ClinVar Miner 94 to identify variants from ClinVar, whereas the aggregation step and the search for variants in COSMIC and cBioPortal have been carried out with Cancermuts 95 . For TP53, we used Cancermuts to include also mutations from other sources 56 .…”

Section: Mavisp Frameworkmentioning

confidence: 99%

TRAP1S-nitrosylation as a model of population-shift mechanism to study the effects of nitric oxide on redox-sensitive oncoproteins

Papaleo

Tiberti

Arnaudi

et al. 2022

Preprint

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S-nitrosylation is a post-translational modification in which nitric oxide (NO) binds to the thiol group of cysteine, generating an S-nitrosothiol (SNO) adduct. S-nitrosylation has different physiological roles, and its alteration has also been linked to a growing list of pathologies, including cancer. SNO can affect the function and stability of different proteins, such as the mitochondrial chaperone TRAP1. Interestingly, the SNO site (C501) of TRAP1 is in the proximity of another cysteine (C527). This feature suggests that the S-nitrosylated C501 could engage in a disulfide bridge with C527 in TRAP1, resembling the well-known ability of S-nitrosylated cysteines to resolve in disulfide bridge with vicinal cysteines. We used enhanced sampling simulations and in-vitro biochemical assays to address the structural mechanisms induced by TRAP1 S-nitrosylation. We showed that the SNO site induces conformational changes in the proximal cysteine and favors conformations suitable for disulfide-bridge formation. We explored 4172 known S-nitrosylated proteins using high-throughput structural analyses. Furthermore, we carried out coarse-grain simulations of 44 proteins to account for protein dynamics in the analyses. This resulted in the identification of up to 1248 examples of proximal cysteines which could sense the redox state of the SNO site, opening new perspectives on the biological effects of redox switches. In addition, we devised two bioinformatic workflows (https://github.com/ELELAB/SNO_investigation_pipelines) to identify proximal or vicinal cysteines for a SNO site with accompanying structural annotations. Finally, we analyzed mutations in tumor suppressor or oncogenes in connection with the conformational switch induced by S-nitrosylation. We classified the variants as neutral, stabilizing, or destabilizing with respect to the propensity to be S-nitrosylated and to undergo the population-shift mechanism. The methods applied here provide a comprehensive toolkit for future high-throughput studies of new protein candidates, variant classification, and a rich data source for the research community in the NO field.

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The Cancermuts software package for the prioritization of missense cancer variants: a case study of AMBRA1 in melanoma

Cited by 10 publications

References 56 publications

MAVISp: A Modular Structure-Based Framework for Protein Variant Effects

MAVISp: A Modular Structure-Based Framework for Protein Variant Effects

Ambra1 modulates the tumor immune microenvironment and response to PD-1 blockade in melanoma

TRAP1S-nitrosylation as a model of population-shift mechanism to study the effects of nitric oxide on redox-sensitive oncoproteins

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