Gabriela Bindea

Dr. Gabriela Bindea

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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31 March 2015 in Genome Biology
Verified
Journal Article
Open access
PDF file
MAMihaela Angelova
Mihaela Angelova
PCPornpimol Charoentong
Pornpimol Charoentong
Hubert HacklHubert Hackl
Hubert Hackl
MFMaria L Fischer
Maria L Fischer
RSRene Snajder
Rene Snajder
ZTZlatko Trajanoski
Zlatko Trajanoski
Background: While large-scale cancer genomic projects are comprehensively characterizing the mutational spectrum of various cancers, so far little attention has been devoted to either define the antigenicity of these mutations or to characterize the immune responses they elicit. Here we present a strategy to characterize the immunophenotypes and the antigen-ome of human colorectal cancer. Results: We apply our strategy to a large colorectal cancer cohort (n = 598) and show that subpopulations of tumor-infiltrating lymphocytes are associated with distinct molecular phenotypes. The characterization of the antigenome shows that a large number of cancer-germline antigens are expressed in all patients. In contrast, neo-antigens are rarely shared between patients, indicating that cancer vaccination requires individualized strategy. Analysis of the genetic basis of the tumors reveals distinct tumor escape mechanisms for the patient subgroups. Hypermutated tumors are depleted of immunosuppressive cells and show upregulation of immunoinhibitory molecules. Non-hypermutated tumors are enriched with immunosuppressive cells, and the expression of immunoinhibitors and MHC molecules is downregulated. Reconstruction of the interaction network of tumor-infiltrating lymphocytes and immunomodulatory molecules followed by a validation with 11 independent cohorts (n = 1,945) identifies BCMA as a novel druggable target. Finally, linear regression modeling identifies major determinants of tumor immunogenicity, which include well-characterized modulators as well as a novel candidate, CCR8, which is then tested in an orthologous immunodeficient mouse model. Conclusions: The immunophenotypes of the tumors and the cancer antigenome remain widely unexplored, and our findings represent a step toward the development of personalized cancer immunotherapies.

1 January 2018 in Journal of Proteomics
Verified
Journal Article
Closed access
BMBernhard Mlecnik
Bernhard Mlecnik
JGJerome Galon
Jerome Galon
GBGabriela Bindea
Gabriela Bindea

29 October 2021 in Nucleic Acids Research
Verified
Journal Article
Open access
PDF file
BMBirgit Meldal
Birgit Meldal
LPLivia Perfetto
Livia Perfetto
CCColin Combe
Colin Combe
TLTiago Lubiana
Tiago Lubiana
JCJoão Vitor Ferreira Cavalcante
João Vitor Ferreira Cavalcante
SOSandra Orchard
Sandra Orchard
The Complex Portal (www.ebi.ac.uk/complexportal) is a manually curated, encyclopaedic database of macromolecular complexes with known function from a range of model organisms. It summarizes complex composition, topology and function along with links to a large range of domain-specific resources (i.e. wwPDB, EMDB and Reactome). Since the last update in 2019, we have produced a first draft complexome for Escherichia coli, maintained and updated that of Saccharomyces cerevisiae, added over 40 coronavirus complexes and increased the human complexome to over 1100 complexes that include approximately 200 complexes that act as targets for viral proteins or are part of the immune system. The display of protein features in ComplexViewer has been improved and the participant table is now colour-coordinated with the nodes in ComplexViewer. Community collaboration has expanded, for example by contributing to an analysis of putative transcription cofactors and providing data accessible to semantic web tools through Wikidata which is now populated with manually curated Complex Portal content through a new bot. Our data license is now CC0 to encourage data reuse. Users are encouraged to get in touch, provide us with feedback and send curation requests through the ‘Support’ link.

7 March 2019 in Bioinformatics
Verified
Journal Article
Open access
PDF file
BMBernhard Mlecnik
Bernhard Mlecnik
JGJérôme Galon
Jérôme Galon
GBGabriela Bindea
Gabriela Bindea
Large scale technologies produce massive amounts of experimental data that need to be investigated. To improve their biological interpretation we have developed ClueGO, a Cytoscape App that selects representative Gene Onology terms and pathways for one or multiple lists of genes/proteins and visualizes them into functionally organized networks. Because of its reliability, userfriendliness and support of many species ClueGO gained a large community of users. To further allow scientists programmatic access to ClueGO with R, Python, JavaScript etc., we implemented the cyREST API into ClueGO. In this article we describe this novel, complementary way of accessing ClueGO via REST, and provide R and Phyton examples to demonstrate how ClueGO workflows can be integrated into bioinformatic analysis pipelines. ClueGO is available in the Cytoscape App Store (http://apps.cytoscape.org/apps/cluego). Supplementary data are available at Bioinformatics online.

8 January 2023 in Cancers
Verified
Journal Article
Open access
PDF file
BMBernhard Mlecnik
Bernhard Mlecnik
ALAlessandro Lugli
Alessandro Lugli
GBGabriela Bindea
Gabriela Bindea
FMFlorence Marliot
Florence Marliot
CBCarlo Bifulco
Carlo Bifulco
JGJerome Galon
Jerome Galon
Background: The prognostic value of Immunoscore was evaluated in Stage II/III colon cancer (CC) patients, but it remains unclear in Stage I/II, and in early-stage subgroups at risk. An international Society for Immunotherapy of Cancer (SITC) study evaluated the pre-defined consensus Immunoscore in tumors from 1885 AJCC/UICC-TNM Stage I/II CC patients from Canada/USA (Cohort 1) and Europe/Asia (Cohort 2). METHODS: Digital-pathology is used to quantify the densities of CD3+ and CD8+ T-lymphocyte in the center of tumor (CT) and the invasive margin (IM). The time to recurrence (TTR) was the primary endpoint. Secondary endpoints were disease-free survival (DFS), overall survival (OS), prognosis in Stage I, Stage II, Stage II-high-risk, and microsatellite-stable (MSS) patients. RESULTS: High-Immunoscore presented with the lowest risk of recurrence in both cohorts. In Stage I/II, recurrence-free rates at 5 years were 78.4% (95%-CI, 74.4–82.6), 88.1% (95%-CI, 85.7–90.4), 93.4% (95%-CI, 91.1–95.8) in low, intermediate and high Immunoscore, respectively (HR (Hi vs. Lo) = 0.27 (95%-CI, 0.18–0.41); p < 0.0001). In Cox multivariable analysis, the association of Immunoscore to outcome was independent (TTR: HR (Hi vs. Lo) = 0.29, (95%-CI, 0.17–0.50); p < 0.0001) of the patient’s gender, T-stage, sidedness, and microsatellite instability-status (MSI). A significant association of Immunoscore with survival was found for Stage II, high-risk Stage II, T4N0 and MSS patients. The Immunoscore also showed significant association with TTR in Stage-I (HR (Hi vs. Lo) = 0.07 (95%-CI, 0.01–0.61); P = 0.016). The Immunoscore had the strongest (69.5%) contribution χ2 for influencing survival. Patients with a high Immunoscore had prolonged TTR in T4N0 tumors even for patients not receiving chemotherapy, and the Immunoscore remained the only significant parameter in multivariable analysis. CONCLUSION: In early CC, low Immunoscore reliably identifies patients at risk of relapse for whom a more intensive surveillance program or adjuvant treatment should be considered.

1 April 2014 in médecine/sciences
Verified
Journal Article
Open access
PDF file
JGJerome Galon
Jerome Galon
GBGabriela Bindea
Gabriela Bindea
BMBernhard Mlecnik
Bernhard Mlecnik
HAHelen Angell
Helen Angell
CLChristine Lagorce
Christine Lagorce
FPFranck Pagès
Franck Pagès