Publications by authors named "Marco Mina"

26 Publications

  • Page 1 of 1

Cell-autonomous inflammation of BRCA1-deficient ovarian cancers drives both tumor-intrinsic immunoreactivity and immune resistance via STING.

Cell Rep 2021 Jul;36(3):109412

Ludwig Institute for Cancer Research, University Hospital of Lausanne (CHUV), Lausanne, Switzerland.

In this study, we investigate mechanisms leading to inflammation and immunoreactivity in ovarian tumors with homologous recombination deficiency (HRD). BRCA1 loss is found to lead to transcriptional reprogramming in tumor cells and cell-intrinsic inflammation involving type I interferon (IFN) and stimulator of IFN genes (STING). BRCA1-mutated (BRCA1) tumors are thus T cell inflamed at baseline. Genetic deletion or methylation of DNA-sensing/IFN genes or CCL5 chemokine is identified as a potential mechanism to attenuate T cell inflammation. Alternatively, in BRCA1 cancers retaining inflammation, STING upregulates VEGF-A, mediating immune resistance and tumor progression. Tumor-intrinsic STING elimination reduces neoangiogenesis, increases CD8 T cell infiltration, and reverts therapeutic resistance to dual immune checkpoint blockade (ICB). VEGF-A blockade phenocopies genetic STING loss and synergizes with ICB and/or poly(ADP-ribose) polymerase (PARP) inhibitors to control the outgrowth of Trp53Brca1 but not Brca1 ovarian tumors in vivo, offering rational combinatorial therapies for HRD cancers.
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http://dx.doi.org/10.1016/j.celrep.2021.109412DOI Listing
July 2021

Systematic inference and comparison of multi-scale chromatin sub-compartments connects spatial organization to cell phenotypes.

Nat Commun 2021 05 10;12(1):2439. Epub 2021 May 10.

Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.

Chromatin compartmentalization reflects biological activity. However, inference of chromatin sub-compartments and compartment domains from chromosome conformation capture (Hi-C) experiments is limited by data resolution. As a result, these have been characterized only in a few cell types and systematic comparisons across multiple tissues and conditions are missing. Here, we present Calder, an algorithmic approach that enables the identification of multi-scale sub-compartments at variable data resolution. Calder allows to infer and compare chromatin sub-compartments and compartment domains in >100 cell lines. Our results reveal sub-compartments enriched for poised chromatin states and undergoing spatial repositioning during lineage differentiation and oncogenic transformation.
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http://dx.doi.org/10.1038/s41467-021-22666-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8110550PMC
May 2021

Nongenetic Evolution Drives Lung Adenocarcinoma Spatial Heterogeneity and Progression.

Cancer Discov 2021 Jun 9;11(6):1490-1507. Epub 2021 Feb 9.

Swiss Cancer Center Leman, Lausanne, Switzerland.

Cancer evolution determines molecular and morphologic intratumor heterogeneity and challenges the design of effective treatments. In lung adenocarcinoma, disease progression and prognosis are associated with the appearance of morphologically diverse tumor regions, termed histologic patterns. However, the link between molecular and histologic features remains elusive. Here, we generated multiomics and spatially resolved molecular profiles of histologic patterns from primary lung adenocarcinoma, which we integrated with molecular data from >2,000 patients. The transition from indolent to aggressive patterns was not driven by genetic alterations but by epigenetic and transcriptional reprogramming reshaping cancer cell identity. A signature quantifying this transition was an independent predictor of patient prognosis in multiple human cohorts. Within individual tumors, highly multiplexed protein spatial profiling revealed coexistence of immune desert, inflamed, and excluded regions, which matched histologic pattern composition. Our results provide a detailed molecular map of lung adenocarcinoma intratumor spatial heterogeneity, tracing nongenetic routes of cancer evolution. SIGNIFICANCE: Lung adenocarcinomas are classified based on histologic pattern prevalence. However, individual tumors exhibit multiple patterns with unknown molecular features. We characterized nongenetic mechanisms underlying intratumor patterns and molecular markers predicting patient prognosis. Intratumor patterns determined diverse immune microenvironments, warranting their study in the context of current immunotherapies..
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http://dx.doi.org/10.1158/2159-8290.CD-20-1274DOI Listing
June 2021

Discovering functional evolutionary dependencies in human cancers.

Nat Genet 2020 11 28;52(11):1198-1207. Epub 2020 Sep 28.

Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.

Cancer cells retain genomic alterations that provide a selective advantage. The prediction and validation of advantageous alterations are major challenges in cancer genomics. Moreover, it is crucial to understand how the coexistence of specific alterations alters response to genetic and therapeutic perturbations. In the present study, we inferred functional alterations and preferentially selected combinations of events in >9,000 human tumors. Using a Bayesian inference framework, we validated computational predictions with high-throughput readouts from genetic and pharmacological screenings on 2,000 cancer cell lines. Mutually exclusive and co-occurring cancer alterations reflected, respectively, functional redundancies able to rescue the phenotype of individual target inhibition, or synergistic interactions, increasing oncogene addiction. Among the top scoring dependencies, co-alteration of the phosphoinositide 3-kinase (PI3K) subunit PIK3CA and the nuclear factor NFE2L2 was a synergistic evolutionary trajectory in squamous cell carcinomas. By integrating computational, experimental and clinical evidence, we provide a framework to study the combinatorial functional effects of cancer genomic alterations.
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http://dx.doi.org/10.1038/s41588-020-0703-5DOI Listing
November 2020

Network analysis can guide resilience-based management in forest landscapes under global change.

Ecol Appl 2021 01 30;31(1):e2221. Epub 2020 Sep 30.

Centre for Forest Research (CEF), Université du Québec à Montréal (UQAM), succursale Centre-Ville, Montréal, H3C 3P8, Quebec, Canada.

Forests are projected to undergo dramatic compositional and structural shifts prompted by global changes, such as climatic changes and intensifying natural disturbance regimes. Future uncertainty makes planning for forest management exceptionally difficult, demanding novel approaches to maintain or improve the ability of forest ecosystems to respond and rapidly reorganize after disturbance events. Adopting a landscape perspective in forest management is particularly important in fragmented forest landscapes where both diversity and connectivity play key roles in determining resilience to global change. In this context, network analysis and functional traits combined with ecological dynamic modeling can help evaluate changes in functional response diversity and connectivity within and among forest stands in fragmented landscapes. Here, we coupled ecological dynamic modeling with functional traits analysis and network theory to analyze forested landscapes as an interconnected network of forest patches. We simulated future forest landscape dynamics in a large landscape in southern Quebec, Canada, under a combination of climate, disturbance, and management scenarios. We depicted the landscape as a functional network, assessed changes in future resilience using indicators at multiple spatial scales, and evaluated if current management practices are suitable for maintaining resilience to simulated changes in regimes. Our results show that climate change would promote forest productivity and favor heat-adapted deciduous species. Changes in natural disturbances will likely have negative impacts on native conifers and will drive changes in forest type composition. Climate change negatively impacted all resilience indicators and triggered losses of functional response diversity and connectivity across the landscape with undesirable consequences on the capacity of these forests to adapt to global change. Also, current management strategies failed to promote resilience at different spatial levels, highlighting the need for a more active and thoughtful approach to forest management under global change. Our study demonstrates the usefulness of combining dynamic landscape-scale simulation modeling with network analyses to evaluate the possible impacts of climate change as well as human and natural disturbances on forest resilience under global change.
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http://dx.doi.org/10.1002/eap.2221DOI Listing
January 2021

Cathepsin S Regulates Antigen Processing and T Cell Activity in Non-Hodgkin Lymphoma.

Cancer Cell 2020 05 23;37(5):674-689.e12. Epub 2020 Apr 23.

Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, EPFL, Lausanne, 1015 Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, 1015 Switzerland. Electronic address:

Genomic alterations in cancer cells can influence the immune system to favor tumor growth. In non-Hodgkin lymphoma, physiological interactions between B cells and the germinal center microenvironment are coopted to sustain cancer cell proliferation. We found that follicular lymphoma patients harbor a recurrent hotspot mutation targeting tyrosine 132 (Y132D) in cathepsin S (CTSS) that enhances protein activity. CTSS regulates antigen processing and CD4 and CD8 T cell-mediated immune responses. Loss of CTSS activity reduces lymphoma growth by limiting communication with CD4 T follicular helper cells while inducing antigen diversification and activation of CD8 T cells. Overall, our results suggest that CTSS inhibition has non-redundant therapeutic potential to enhance anti-tumor immune responses in indolent and aggressive lymphomas.
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http://dx.doi.org/10.1016/j.ccell.2020.03.016DOI Listing
May 2020

Dynamic Emergence of Observed and Hidden Intra-tumor Heterogeneity.

iScience 2019 Nov 10;21:157-167. Epub 2019 Oct 10.

Department of Computational Biology, University of Lausanne, Lausanne, 1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, 1015 Lausanne, Switzerland. Electronic address:

Intra-tumor heterogeneity is frequently observed in cancer patients, and it is associated with therapeutic resistance and disease relapse. However, its systematic assessment is still limited and often unfeasible. Here, we use a mathematical model of tumor progression to decipher how multiple clones emerge and organize into complex architectures. We found a trade-off between cancer cell alteration and proliferation rates that defines a transition between low and high heterogeneity, the latter characterized by branching tumor phylogenies. We predict the existence of observed and hidden intra-tumor heterogeneity, which challenges the correct estimation of intrinsic tumor complexity. Although the numbers of observed and hidden clones do not always correlate, we demonstrate that population frequencies of observed clones can be used to estimate the extent of hidden heterogeneity in both simulated and human tumors. The characterization of complex clonal architectures is a critical first step toward understanding their organizing principles and predicting their emergence.
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http://dx.doi.org/10.1016/j.isci.2019.10.018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6820272PMC
November 2019

The Oncogenic Action of NRF2 Depends on De-glycation by Fructosamine-3-Kinase.

Cell 2019 08;178(4):807-819.e21

Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. Electronic address:

The NRF2 transcription factor controls a cell stress program that is implicated in cancer and there is great interest in targeting NRF2 for therapy. We show that NRF2 activity depends on Fructosamine-3-kinase (FN3K)-a kinase that triggers protein de-glycation. In its absence, NRF2 is extensively glycated, unstable, and defective at binding to small MAF proteins and transcriptional activation. Moreover, the development of hepatocellular carcinoma triggered by MYC and Keap1 inactivation depends on FN3K in vivo. N-acetyl cysteine treatment partially rescues the effects of FN3K loss on NRF2 driven tumor phenotypes indicating a key role for NRF2-mediated redox balance. Mass spectrometry reveals that other proteins undergo FN3K-sensitive glycation, including translation factors, heat shock proteins, and histones. How glycation affects their functions remains to be defined. In summary, our study reveals a surprising role for the glycation of cellular proteins and implicates FN3K as targetable modulator of NRF2 activity in cancer.
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http://dx.doi.org/10.1016/j.cell.2019.07.031DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6693658PMC
August 2019

Publisher Correction: Uncoupling protein 2 reprograms the tumor microenvironment to support the anti-tumor immune cycle.

Nat Immunol 2019 Apr;20(4):515-516

Department of Fundamental Oncology, University of Lausanne, Lausanne, Switzerland.

In the version of this article initially published, the bars were not aligned with the data points or horizontal axis labels in Fig. 5d, and the labels along each horizontal axis of Fig. 5j-l indicating the presence (+) or absence (-) of doxycycline (Dox) were incorrectly included with the labels below that axis. Also, the right vertical bar above Fig. 7b linking 'P = 0.0001' to the key was incorrect; the correct comparison is αPD-1 versus Dox + αPD-1. Similarly, the right vertical bar above Fig. 7e linking 'P = 0.0002' to the key was incorrect; the correct comparison is αPD-1 versus Rosig + αPD-1. The errors have been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41590-019-0359-4DOI Listing
April 2019

EZH2 oncogenic mutations drive epigenetic, transcriptional, and structural changes within chromatin domains.

Nat Genet 2019 03 28;51(3):517-528. Epub 2019 Jan 28.

Swiss Institute for Experimental Cancer Research (ISREC), School of Life Science, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Chromatin is organized into topologically associating domains (TADs) enriched in distinct histone marks. In cancer, gain-of-function mutations in the gene encoding the enhancer of zeste homolog 2 protein (EZH2) lead to a genome-wide increase in histone-3 Lys27 trimethylation (H3K27me3) associated with transcriptional repression. However, the effects of these epigenetic changes on the structure and function of chromatin domains have not been explored. Here, we found a functional interplay between TADs and epigenetic and transcriptional changes mediated by mutated EZH2. Altered EZH2 (p.Tyr646* (EZH2)) led to silencing of entire domains, synergistically inactivating multiple tumor suppressors. Intra-TAD gene silencing was coupled with changes of interactions between gene promoter regions. Notably, gene expression and chromatin interactions were restored by pharmacological inhibition of EZH2. Our results indicate that EZH2 alters the topology and function of chromatin domains to promote synergistic oncogenic programs.
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http://dx.doi.org/10.1038/s41588-018-0338-yDOI Listing
March 2019

Uncoupling protein 2 reprograms the tumor microenvironment to support the anti-tumor immune cycle.

Nat Immunol 2019 02 21;20(2):206-217. Epub 2019 Jan 21.

Department of Fundamental Oncology, University of Lausanne, Lausanne, Switzerland.

Immune checkpoint blockade therapy has shifted the paradigm for cancer treatment. However, the majority of patients lack effective responses due to insufficient T cell infiltration in tumors. Here we show that expression of mitochondrial uncoupling protein 2 (UCP2) in tumor cells determines the immunostimulatory feature of the tumor microenvironment (TME) and is positively associated with prolonged survival. UCP2 reprograms the immune state of the TME by altering its cytokine milieu in an interferon regulatory factor 5-dependent manner. Consequently, UCP2 boosts the conventional type 1 dendritic cell- and CD8 T cell-dependent anti-tumor immune cycle and normalizes the tumor vasculature. Finally we show, using either a genetic or pharmacological approach, that induction of UCP2 sensitizes melanomas to programmed cell death protein-1 blockade treatment and elicits effective anti-tumor responses. Together, this study demonstrates that targeting the UCP2 pathway is a potent strategy for alleviating the immunosuppressive TME and overcoming the primary resistance of programmed cell death protein-1 blockade.
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http://dx.doi.org/10.1038/s41590-018-0290-0DOI Listing
February 2019

Pan-Cancer Landscape of Aberrant DNA Methylation across Human Tumors.

Cell Rep 2018 10;25(4):1066-1080.e8

Department of Computational Biology, University of Lausanne (UNIL), Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), University of Lausanne (UNIL), Lausanne, Switzerland. Electronic address:

The discovery of cancer-associated alterations has primarily focused on genetic variants. Nonetheless, altered epigenomes contribute to deregulate transcription and promote oncogenic pathways. Here, we designed an algorithmic approach (RESET) to identify aberrant DNA methylation and associated cis-transcriptional changes across >6,000 human tumors. Tumors exhibiting mutations of chromatin remodeling factors and Wnt signaling displayed DNA methylation instability, characterized by numerous hyper- and hypo-methylated loci. Most silenced and enhanced genes coalesced in specific pathways including apoptosis, DNA repair, and cell metabolism. Cancer-germline antigens (CG) were frequently epigenomically enhanced and their expression correlated with response to anti-PD-1, but not anti-CTLA4, in skin melanoma. Finally, we demonstrated the potential of our approach to explore DNA methylation changes in pediatric tumors, which frequently lack genetic drivers and exhibit epigenomic modifications. Our results provide a pan-cancer map of aberrant DNA methylation to inform functional and therapeutic studies.
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http://dx.doi.org/10.1016/j.celrep.2018.09.082DOI Listing
October 2018

Pan-cancer inference of intra-tumor heterogeneity reveals associations with different forms of genomic instability.

PLoS Genet 2018 09 13;14(9):e1007669. Epub 2018 Sep 13.

Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.

Genomic instability is a major driver of intra-tumor heterogeneity. However, unstable genomes often exhibit different molecular and clinical phenotypes, which are associated with distinct mutational processes. Here, we algorithmically inferred the clonal phylogenies of ~6,000 human tumors from 32 tumor types to explore how intra-tumor heterogeneity depends on different implementations of genomic instability. We found that extremely unstable tumors associated with DNA repair deficiencies or high chromosomal instability are not the most intrinsically heterogeneous. Conversely, intra-tumor heterogeneity is greatest in tumors exhibiting relatively high numbers of both mutations and copy number alterations, a feature often observed in cancers associated with exogenous mutagens. Independently of the type of instability, tumors with high number of clones invariably evolved through branching phylogenies that could be stratified based on the extent of clonal (early) and subclonal (late) instability. Interestingly, tumors with high number of subclonal mutations frequently exhibited chromosomal instability, TP53 mutations, and APOBEC-related mutational signatures. Vice versa, mutations of chromatin remodeling genes often characterized tumors with few subclonal but multiple clonal mutations. Understanding how intra-tumor heterogeneity depends on genomic instability is critical to identify markers predictive of the tumor complexity and envision therapeutic strategies able to exploit this association.
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http://dx.doi.org/10.1371/journal.pgen.1007669DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6155543PMC
September 2018

Oncogenic Signaling Pathways in The Cancer Genome Atlas.

Cell 2018 04;173(2):321-337.e10

Van Andel Research Institute, 333 Bostwick Ave NE, Grand Rapids Michigan, 49503, USA.

Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions and DNA methylation in 9,125 tumors profiled by The Cancer Genome Atlas (TCGA), we analyzed the mechanisms and patterns of somatic alterations in ten canonical pathways: cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGFβ signaling, p53 and β-catenin/Wnt. We charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity. Eighty-nine percent of tumors had at least one driver alteration in these pathways, and 57% percent of tumors had at least one alteration potentially targetable by currently available drugs. Thirty percent of tumors had multiple targetable alterations, indicating opportunities for combination therapy.
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http://dx.doi.org/10.1016/j.cell.2018.03.035DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6070353PMC
April 2018

Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas.

Cell Rep 2018 04;23(1):172-180.e3

Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:

Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these "hidden responders" may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq, copy number, and mutations from 33 different cancer types across The Cancer Genome Atlas (TCGA) PanCanAtlas project to predict aberrant molecular states in tumors. Applied to the Ras pathway, the method detects Ras activation across cancer types and identifies phenocopying variants. The model, trained on human tumors, can predict response to MEK inhibitors in wild-type Ras cell lines. We also present data that suggest that multiple hits in the Ras pathway confer increased Ras activity. The transcriptome is underused in precision oncology and, combined with machine learning, can aid in the identification of hidden responders.
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http://dx.doi.org/10.1016/j.celrep.2018.03.046DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918694PMC
April 2018

A transcribed enhancer dictates mesendoderm specification in pluripotency.

Nat Commun 2017 11 27;8(1):1806. Epub 2017 Nov 27.

Experimental Cardiology Unit, Department of Cardiovascular Medicine, University of Lausanne Medical School, 1011, Lausanne, Switzerland.

Enhancers and long noncoding RNAs (lncRNAs) are key determinants of lineage specification during development. Here, we evaluate remodeling of the enhancer landscape and modulation of the lncRNA transcriptome during mesendoderm specification. We sort mesendodermal progenitors from differentiating embryonic stem cells (ESCs) according to Eomes expression, and find that enhancer usage is coordinated with mesendoderm-specific expression of key lineage-determining transcription factors. Many of these enhancers are associated with the expression of lncRNAs. Examination of ESC-specific enhancers interacting in three-dimensional space with mesendoderm-specifying transcription factor loci identifies MesEndoderm Transcriptional Enhancer Organizing Region (Meteor). Genetic and epigenetic manipulation of the Meteor enhancer reveal its indispensable role during mesendoderm specification and subsequent cardiogenic differentiation via transcription-independent and -dependent mechanisms. Interestingly, Meteor-deleted ESCs are epigenetically redirected towards neuroectodermal lineages. Loci, topologically associating a transcribed enhancer and its cognate protein coding gene, appear to represent therefore a class of genomic elements controlling developmental competence in pluripotency.
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http://dx.doi.org/10.1038/s41467-017-01804-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5703900PMC
November 2017

Conditional Selection of Genomic Alterations Dictates Cancer Evolution and Oncogenic Dependencies.

Cancer Cell 2017 08 27;32(2):155-168.e6. Epub 2017 Jul 27.

Department of Computational Biology, University of Lausanne (UNIL), 1011 Lausanne, Vaud, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland. Electronic address:

Cancer evolves through the emergence and selection of molecular alterations. Cancer genome profiling has revealed that specific events are more or less likely to be co-selected, suggesting that the selection of one event depends on the others. However, the nature of these evolutionary dependencies and their impact remain unclear. Here, we designed SELECT, an algorithmic approach to systematically identify evolutionary dependencies from alteration patterns. By analyzing 6,456 genomes from multiple tumor types, we constructed a map of oncogenic dependencies associated with cellular pathways, transcriptional readouts, and therapeutic response. Finally, modeling of cancer evolution shows that alteration dependencies emerge only under conditional selection. These results provide a framework for the design of strategies to predict cancer progression and therapeutic response.
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http://dx.doi.org/10.1016/j.ccell.2017.06.010DOI Listing
August 2017

PD-L1 Is a Therapeutic Target of the Bromodomain Inhibitor JQ1 and, Combined with HLA Class I, a Promising Prognostic Biomarker in Neuroblastoma.

Clin Cancer Res 2017 Aug 7;23(15):4462-4472. Epub 2017 Mar 7.

Immuno-Oncology Laboratory, Oncohaematology Department, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.

This study sought to evaluate the expression of programmed cell death-ligand-1 (PD-L1) and HLA class I on neuroblastoma cells and programmed cell death-1 (PD-1) and lymphocyte activation gene 3 (LAG3) on tumor-infiltrating lymphocytes to better define patient risk stratification and understand whether this tumor may benefit from therapies targeting immune checkpoint molecules. IHC staining for PD-L1, HLA class I, PD-1, and LAG3 was assessed in 77 neuroblastoma specimens, previously characterized for tumor-infiltrating T-cell density and correlated with clinical outcome. Surface expression of PD-L1 was evaluated by flow cytometry and IHC in neuroblastoma cell lines and tumors genetically and/or pharmacologically inhibited for MYC and MYCN. A dataset of 477 human primary neuroblastomas from GEO and ArrayExpress databases was explored for PD-L1, MYC, and MYCN correlation. Multivariate Cox regression analysis demonstrated that the combination of PD-L1 and HLA class I tumor cell density is a prognostic biomarker for predicting overall survival in neuroblastoma patients ( = 0.0448). MYC and MYCN control the expression of PD-L1 in neuroblastoma cells both and Consistently, abundance of PD-L1 transcript correlates with MYC expression in primary neuroblastoma. The combination of PD-L1 and HLA class I represents a novel prognostic biomarker for neuroblastoma. Pharmacologic inhibition of MYCN and MYC may be exploited to target PD-L1 and restore an efficient antitumor immunity in high-risk neuroblastoma. .
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http://dx.doi.org/10.1158/1078-0432.CCR-16-2601DOI Listing
August 2017

LPS-induced TNF-α factor mediates pro-inflammatory and pro-fibrogenic pattern in non-alcoholic fatty liver disease.

Oncotarget 2015 Dec;6(39):41434-52

Liver Research Unit, "Bambino Gesù" Children's Hospital-IRCCS, Rome, Italy.

Lipopolysaccharide (LPS) is currently considered one of the major players in non-alcoholic fatty liver disease (NAFLD) pathogenesis and progression. Here, we aim to investigate the possible role of LPS-induced TNF-α factor (LITAF) in inducing a pro-inflammatory and pro-fibrogenic phenotype of non-alcoholic steatohepatitis (NASH).We found that children with NAFLD displayed, in different liver-resident cells, an increased expression of LITAF which correlated with histological traits of hepatic inflammation and fibrosis. Total and nuclear LITAF expression increased in mouse and human hepatic stellate cells (HSCs). Moreover, LPS induced LITAF-dependent transcription of IL-1β, IL-6 and TNF-α in the clonal myofibroblastic HSC LX-2 cell line, and this effect was hampered by LITAF silencing. We showed, for the first time in HSCs, that LITAF recruitment to these cytokine promoters is LPS dependent. However, preventing LITAF nuclear translocation by p38MAPK inhibitor, the expression of IL-6 and TNF-α was significantly reduced with the aid of p65NF-ĸB, while IL-1β transcription exclusively required LITAF expression/activity. Finally, IL-1β levels in plasma mirrored those in the liver and correlated with LPS levels and LITAF-positive HSCs in children with NASH.In conclusion, a more severe histological profile in paediatric NAFLD is associated with LITAF over-expression in HSCs, which in turn correlates with hepatic and circulating IL-1β levels outlining a panel of potential biomarkers of NASH-related liver damage. The in vitro study highlights the role of LITAF as a key regulator of the LPS-induced pro-inflammatory pattern in HSCs and suggests p38MAPK inhibitors as a possible therapeutic approach against hepatic inflammation in NASH.
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http://dx.doi.org/10.18632/oncotarget.5163DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4747165PMC
December 2015

Tumor-infiltrating T lymphocytes improve clinical outcome of therapy-resistant neuroblastoma.

Oncoimmunology 2015 Sep 2;4(9):e1019981. Epub 2015 Apr 2.

Paediatric Haematology/Oncology Department; IRCCS; Ospedale Pediatrico Bambino Gesù , Rome, Italy.

Neuroblastoma grows within an intricate network of different cell types including epithelial, stromal and immune cells. The presence of tumor-infiltrating T cells is considered an important prognostic indicator in many cancers, but the role of these cells in neuroblastoma remains to be elucidated. Herein, we examined the relationship between the type, density and organization of infiltrating T cells and clinical outcome within a large collection of neuroblastoma samples by quantitative analysis of immunohistochemical staining. We found that infiltrating T cells have a prognostic value greater than, and independent of, the criteria currently used to stage neuroblastoma. A variable structural organization and different concurrent infiltration of T-cell subsets were detected in tumors with various outcomes. Low-risk neuroblastomas were characterized by a higher number of proliferating T cells and a more structured T-cell organization, which was gradually lost in tumors with poor prognosis. We defined an immunoscore based on the presence of CD3, CD4 and CD8 infiltrating T cells that associates with favorable clinical outcome in MYCN-amplified tumors, improving patient survival when combined with the v-myc avian myelocytomatosis viral oncogene neuroblastoma derived homolog (MYCN) status. These findings support the hypothesis that infiltrating T cells influence the behavior of neuroblastoma and might be of clinical importance for the treatment of patients.
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http://dx.doi.org/10.1080/2162402X.2015.1019981DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4570119PMC
September 2015

Novel therapeutic strategy in the management of COPD: a systems medicine approach.

Curr Med Chem 2015 ;22(32):3655-75

Unit of Thoracic Surgery, IRCCS-Arcispedale Santa Maria Nuova, Reggio Emilia, Italy.

Respiratory diseases including chronic-obstructive-pulmonary-disease (COPD) are globally increasing, with COPD predicted to become the third leading cause of global mortality by 2020. COPD is a heterogeneous disease with COPD-patients displaying different phenotypes as a result of a complex interaction between various genetic, environmental and life-style factors. In recent years, several investigations have been performed to better define such interactions, but the identification of the resulting phenotypes is still somewhat difficult, and may lead to inadequate assessment and management of COPD (usually based solely on the severity of airflow limitation parameter FEV1). In this new scenario, the management of COPD has been driven towards an integrative and holistic approach. The degree of complexity requires analyses based on large datasets (also including advanced functional genomic assays) and novel computational biology approaches (essential to extract information relevant for the clinical decision process and for the development of new drugs). Therefore, according to the emerging "systems/network medicine", COPD should be re.-evaluated considering multiple network(s) perturbations such as genetic and environmental changes. Systems Medicine (SM) platforms, in which patients are extensively characterized, offer a basis for a more targeted clinical approach, which is predictive, preventive, personalized and participatory ("P4-medicine"). It clearly emerges that in the next future, new opportunities will become available for clinical research on rare COPD patterns and for the identification of new biomarkers of comorbidity, severity, and progression. Herein, we overview the literature discussing the opportunity coming from the adoption of SMapproaches in COPD management, focusing on proteomics and metabolomics, and emphasizing the identification of disease sub-clusters, to improve the development of more effective therapies.
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http://dx.doi.org/10.2174/0929867322666150904113032DOI Listing
August 2016

Promoter-level expression clustering identifies time development of transcriptional regulatory cascades initiated by ErbB receptors in breast cancer cells.

Sci Rep 2015 Jul 16;5:11999. Epub 2015 Jul 16.

Fondazione Bruno Kessler, Via Sommarive 18, I-38123 Povo, Trento, Italy.

The analysis of CAGE (Cap Analysis of Gene Expression) time-course has been proposed by the FANTOM5 Consortium to extend the understanding of the sequence of events facilitating cell state transition at the level of promoter regulation. To identify the most prominent transcriptional regulations induced by growth factors in human breast cancer, we apply here the Complexity Invariant Dynamic Time Warping motif EnRichment (CIDER) analysis approach to the CAGE time-course datasets of MCF-7 cells stimulated by epidermal growth factor (EGF) or heregulin (HRG). We identify a multi-level cascade of regulations rooted by the Serum Response Factor (SRF) transcription factor, connecting the MAPK-mediated transduction of the HRG stimulus to the negative regulation of the MAPK pathway by the members of the DUSP family phosphatases. The finding confirms the known primary role of FOS and FOSL1, members of AP-1 family, in shaping gene expression in response to HRG induction. Moreover, we identify a new potential regulation of DUSP5 and RARA (known to antagonize the transcriptional regulation induced by the estrogen receptors) by the activity of the AP-1 complex, specific to HRG response. The results indicate that a divergence in AP-1 regulation determines cellular changes of breast cancer cells stimulated by ErbB receptors.
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http://dx.doi.org/10.1038/srep11999DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4503981PMC
July 2015

Improving the Robustness of Local Network Alignment: Design and Extensive Assessment of a Markov Clustering-Based Approach.

IEEE/ACM Trans Comput Biol Bioinform 2014 May-Jun;11(3):561-72

The analysis of protein behavior at the network level had been applied to elucidate the mechanisms of protein interaction that are similar in different species. Published network alignment algorithms proved to be able to recapitulate known conserved modules and protein complexes, and infer new conserved interactions confirmed by wet lab experiments. In the meantime, however, a plethora of continuously evolving protein-protein interaction (PPI) data sets have been developed, each featuring different levels of completeness and reliability. For instance, algorithms performance may vary significantly when changing the data set used in their assessment. Moreover, existing papers did not deeply investigate the robustness of alignment algorithms. For instance, some algorithms performances vary significantly when changing the data set used in their assessment. In this work, we design an extensive assessment of current algorithms discussing the robustness of the results on the basis of input networks. We also present AlignMCL, a local network alignment algorithm based on an improved model of alignment graph and Markov Clustering. AlignMCL performs better than other state-of-the-art local alignment algorithms over different updated data sets. In addition, AlignMCL features high levels of robustness, producing similar results regardless the selected data set.
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http://dx.doi.org/10.1109/TCBB.2014.2318707DOI Listing
March 2016

M-Finder: Uncovering functionally associated proteins from interactome data integrated with GO annotations.

Proteome Sci 2013 Nov 7;11(Suppl 1):S3. Epub 2013 Nov 7.

Background: Protein-protein interactions (PPIs) play a key role in understanding the mechanisms of cellular processes. The availability of interactome data has catalyzed the development of computational approaches to elucidate functional behaviors of proteins on a system level. Gene Ontology (GO) and its annotations are a significant resource for functional characterization of proteins. Because of wide coverage, GO data have often been adopted as a benchmark for protein function prediction on the genomic scale.

Results: We propose a computational approach, called M-Finder, for functional association pattern mining. This method employs semantic analytics to integrate the genome-wide PPIs with GO data. We also introduce an interactive web application tool that visualizes a functional association network linked to a protein specified by a user. The proposed approach comprises two major components. First, the PPIs that have been generated by high-throughput methods are weighted in terms of their functional consistency using GO and its annotations. We assess two advanced semantic similarity metrics which quantify the functional association level of each interacting protein pair. We demonstrate that these measures outperform the other existing methods by evaluating their agreement to other biological features, such as sequence similarity, the presence of common Pfam domains, and core PPIs. Second, the information flow-based algorithm is employed to discover a set of proteins functionally associated with the protein in a query and their links efficiently. This algorithm reconstructs a functional association network of the query protein. The output network size can be flexibly determined by parameters.

Conclusions: M-Finder provides a useful framework to investigate functional association patterns with any protein. This software will also allow users to perform further systematic analysis of a set of proteins for any specific function. It is available online at http://bionet.ecs.baylor.edu/mfinder.
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http://dx.doi.org/10.1186/1477-5956-11-S1-S3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3909039PMC
November 2013

AlignNemo: a local network alignment method to integrate homology and topology.

PLoS One 2012 12;7(6):e38107. Epub 2012 Jun 12.

Department of Information Engineering, University of Padova, Padova, Italy.

Local network alignment is an important component of the analysis of protein-protein interaction networks that may lead to the identification of evolutionary related complexes. We present AlignNemo, a new algorithm that, given the networks of two organisms, uncovers subnetworks of proteins that relate in biological function and topology of interactions. The discovered conserved subnetworks have a general topology and need not to correspond to specific interaction patterns, so that they more closely fit the models of functional complexes proposed in the literature. The algorithm is able to handle sparse interaction data with an expansion process that at each step explores the local topology of the networks beyond the proteins directly interacting with the current solution. To assess the performance of AlignNemo, we ran a series of benchmarks using statistical measures as well as biological knowledge. Based on reference datasets of protein complexes, AlignNemo shows better performance than other methods in terms of both precision and recall. We show our solutions to be biologically sound using the concept of semantic similarity applied to Gene Ontology vocabularies. The binaries of AlignNemo and supplementary details about the algorithms and the experiments are available at: sourceforge.net/p/alignnemo.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0038107PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3373574PMC
December 2012

Semantic similarity analysis of protein data: assessment with biological features and issues.

Brief Bioinform 2012 Sep 2;13(5):569-85. Epub 2011 Dec 2.

University ‘Magna Gracia’ of Catanzaro, Italy.

The integration of proteomics data with biological knowledge is a recent trend in bioinformatics. A lot of biological information is available and is spread on different sources and encoded in different ontologies (e.g. Gene Ontology). Annotating existing protein data with biological information may enable the use (and the development) of algorithms that use biological ontologies as framework to mine annotated data. Recently many methodologies and algorithms that use ontologies to extract knowledge from data, as well as to analyse ontologies themselves have been proposed and applied to other fields. Conversely, the use of such annotations for the analysis of protein data is a relatively novel research area that is currently becoming more and more central in research. Existing approaches span from the definition of the similarity among genes and proteins on the basis of the annotating terms, to the definition of novel algorithms that use such similarities for mining protein data on a proteome-wide scale. This work, after the definition of main concept of such analysis, presents a systematic discussion and comparison of main approaches. Finally, remaining challenges, as well as possible future directions of research are presented.
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http://dx.doi.org/10.1093/bib/bbr066DOI Listing
September 2012
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