Setting the basis of best practices and standards for curation and annotation of logical models in biology-highlights of the [BC]2 2019 CoLoMoTo/SysMod Workshop.

The fast accumulation of biological data calls for their integration, analysis and exploitation through more systematic approaches. The generation of novel, relevant hypotheses from this enormous quantity of data remains challenging. Logical models have long been used to answer a variety of questions regarding the dynamical behaviours of regulatory networks. As the number of published logical models increases, there is a pressing need for systematic model annotation, referencing and curation in community-supported and standardised formats. This article summarises the key topics and future directions of a meeting entitled 'Annotation and curation of computational models in biology', organised as part of the 2019 [BC]2 conference. The purpose of the meeting was to develop and drive forward a plan towards the standardised annotation of logical models, review and connect various ongoing projects of experts from different communities involved in the modelling and annotation of molecular biological entities, interactions, pathways and models. This article defines a roadmap towards the annotation and curation of logical models, including milestones for best practices and minimum standard requirements.

Immunogenic stress and death of cancer cells: Contribution of antigenicity vs adjuvanticity to immunosurveillance.

Cancer cells are subjected to constant selection by the immune system, meaning that tumors that become clinically manifest have managed to subvert or hide from immunosurveillance. Immune control can be facilitated by induction of autophagy, as well as by polyploidization of cancer cells. While autophagy causes the release of ATP, a chemotactic signal for myeloid cells, polyploidization can trigger endoplasmic reticulum stress with consequent exposure of the "eat-me" signal calreticulin on the cell surface, thereby facilitating the transfer of tumor antigens into dendritic cells. Hence, both autophagy and polyploidization cause the emission of adjuvant signals that ultimately elicit immune control by CD8+ T lymphocytes. We investigated the possibility that autophagy and polyploidization might also affect the antigenicity of cancer cells by altering the immunopeptidome. Mass spectrometry led to the identification of peptides that were presented on major histocompatibility complex (MHC) class I molecules in an autophagy-dependent fashion or that were specifically exposed on the surface of polyploid cells, yet lost upon passage of such cells through immunocompetent (but not immunodeficient) mice. However, the preferential recognition of autophagy-competent and polyploid cells by the innate and cellular immune systems did not correlate with the preferential recognition of such peptides in vivo. Moreover, vaccination with such peptides was unable to elicit tumor growth-inhibitory responses in vivo. We conclude that autophagy and polyploidy increase the immunogenicity of cancer cells mostly by affecting their adjuvanticity rather than their antigenicity.

Oxidative phosphorylation as a potential therapeutic target for cancer therapy.

In contrast to prior belief, cancer cells require oxidative phosphorylation (OXPHOS) to strive, and exacerbated OXPHOS dependency frequently characterizes cancer stem cells, as well as primary or acquired resistance against chemotherapy or tyrosine kinase inhibitors. A growing arsenal of therapeutic agents is being designed to suppress the transfer of mitochondria from stromal to malignant cells, to interfere with mitochondrial biogenesis, to directly inhibit respiratory chain complexes, or to disrupt mitochondrial function in other ways. For the experimental treatment of cancers, OXPHOS inhibitors can be advantageously combined with tyrosine kinase inhibitors, as well as with other strategies to inhibit glycolysis, thereby causing a lethal energy crisis. Unfortunately, most of the preclinical data arguing in favor of OXPHOS inhibition have been obtained in xenograft models, in which human cancer cells are implanted in immunodeficient mice. Future studies on OXPHOS inhibitors should elaborate optimal treatment schedules and combination regimens that stimulate-or at least are compatible with-anticancer immune responses for long-term tumor control.

PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling.

MOTIVATION: Due to the complexity and heterogeneity of multicellular biological systems, mathematical models that take into account cell signalling, cell population behaviour and the extracellular environment are particularly helpful. We present PhysiBoSS, an open source software which combines intracellular signalling using Boolean modelling (MaBoSS) and multicellular behaviour using agent-based modelling (PhysiCell). RESULTS: PhysiBoSS provides a flexible and computationally efficient framework to explore the effect of environmental and genetic alterations of individual cells at the population level, bridging the critical gap from single-cell genotype to single-cell phenotype and emergent multicellular behaviour. PhysiBoSS thus becomes very useful when studying heterogeneous population response to treatment, mutation effects, different modes of invasion or isomorphic morphogenesis events. To concretely illustrate a potential use of PhysiBoSS, we studied heterogeneous cell fate decisions in response to TNF treatment. We explored the effect of different treatments and the behaviour of several resistant mutants. We highlighted the importance of spatial information on the population dynamics by considering the effect of competition for resources like oxygen. AVAILABILITY AND IMPLEMENTATION: PhysiBoSS is freely available on GitHub (https://github.com/sysbio-curie/PhysiBoSS), with a Docker image (https://hub.docker.com/r/gletort/physiboss/). It is distributed as open source under the BSD 3-clause license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The abundance of the long intergenic non-coding RNA 01087 differentiates between luminal and triple-negative breast cancers and predicts patient outcome.

The molecular complexity of human breast cancer (BC) renders the clinical management of the disease challenging. Long non-coding RNAs (lncRNAs) are promising biomarkers for BC patient stratification, early detection, and disease monitoring. Here, we identified the involvement of the long intergenic non-coding RNA 01087 (LINC01087) in breast oncogenesis. LINC01087 appeared significantly downregulated in triple-negative BCs (TNBCs) and upregulated in the luminal BC subtypes in comparison to mammary samples from cancer-free women and matched normal cancer pairs. Interestingly, deregulation of LINC01087 allowed to accurately distinguish between luminal and TNBC specimens, independently of the clinicopathological parameters, and of the histological and TP53 or BRCA1/2 mutational status. Moreover, increased expression of LINC01087 predicted a better prognosis in luminal BCs, while TNBC tumors that harbored lower levels of LINC01087 were associated with reduced relapse-free survival. Furthermore, bioinformatics analyses were performed on TNBC and luminal BC samples and suggested that the putative tumor suppressor activity of LINC01087 may rely on interferences with pathways involved in cell survival, proliferation, adhesion, invasion, inflammation and drug sensitivity. Altogether, these data suggest that the assessment of LINC01087 deregulation could represent a novel, specific and promising biomarker not only for the diagnosis and prognosis of luminal BC subtypes and TNBCs, but also as a predictive biomarker of pharmacological interventions.

MaBoSS 2.0: an environment for stochastic Boolean modeling.

MOTIVATION: Modeling of signaling pathways is an important step towards the understanding and the treatment of diseases such as cancers, HIV or auto-immune diseases. MaBoSS is a software that allows to simulate populations of cells and to model stochastically the intracellular mechanisms that are deregulated in diseases. MaBoSS provides an output of a Boolean model in the form of time-dependent probabilities, for all biological entities (genes, proteins, phenotypes, etc.) of the model. RESULTS: We present a new version of MaBoSS (2.0), including an updated version of the core software and an environment. With this environment, the needs for modeling signaling pathways are facilitated, including model construction, visualization, simulations of mutations, drug treatments and sensitivity analyses. It offers a framework for automated production of theoretical predictions. AVAILABILITY AND IMPLEMENTATION: MaBoSS software can be found at https://maboss.curie.fr , including tutorials on existing models and examples of models. CONTACT: gautier.stoll@upmc.fr or laurence.calzone@curie.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Systems biology of Ewing sarcoma: a network model of EWS-FLI1 effect on proliferation and apoptosis.

Ewing sarcoma is the second most frequent pediatric bone tumor. In most of the patients, a chromosomal translocation leads to the expression of the EWS-FLI1 chimeric transcription factor that is the major oncogene in this pathology. Relative genetic simplicity of Ewing sarcoma makes it particularly attractive for studying cancer in a systemic manner. Silencing EWS-FLI1 induces cell cycle alteration and ultimately leads to apoptosis, but the exact molecular mechanisms underlying this phenotype are unclear. In this study, a network linking EWS-FLI1 to cell cycle and apoptosis phenotypes was constructed through an original method of network reconstruction. Transcriptome time-series after EWS-FLI1 silencing were used to identify core modulated genes by an original scoring method based on fitting expression profile dynamics curves. Literature data mining was then used to connect these modulated genes into a network. The validity of a subpart of this network was assessed by siRNA/RT-QPCR experiments on four additional Ewing cell lines and confirmed most of the links. Based on the network and the transcriptome data, CUL1 was identified as a new potential target of EWS-FLI1. Altogether, using an original methodology of data integration, we provide the first version of EWS-FLI1 network model of cell cycle and apoptosis regulation.

Corrigendum to "Modeling signaling pathways in biology with MaBoSS: From one single cell to a dynamic population of heterogeneous interacting cells" [Comput. Struct. Biotechnol. 20 (2022) 5661-5671].

[This corrects the article DOI: 10.1016/j.csbj.2022.10.003.].

New hormone receptor-positive breast cancer mouse cell line mimicking the immune microenvironment of anti-PD-1 resistant mammary carcinoma.

BACKGROUND: Progress in breast cancer (BC) research relies on the availability of suitable cell lines that can be implanted in immunocompetent laboratory mice. The best studied mouse strain, C57BL/6, is also the only one for which multiple genetic variants are available to facilitate the exploration of the cancer-immunity dialog. Driven by the fact that no hormone receptor-positive (HR+) C57BL/6-derived mammary carcinoma cell lines are available, we decided to establish such cell lines. METHODS: BC was induced in female C57BL/6 mice using a synthetic progesterone analog (medroxyprogesterone acetate, MPA) combined with a DNA damaging agent (7,12-dimethylbenz[a]anthracene, DMBA). Cell lines were established from these tumors and selected for dual (estrogen+progesterone) receptor positivity, as well as transplantability into C57BL/6 immunocompetent females. RESULTS: One cell line, which we called B6BC, fulfilled these criteria and allowed for the establishment of invasive estrogen receptor-positive (ER+) tumors with features of epithelial to mesenchymal transition that were abundantly infiltrated by myeloid immune populations but scarcely by T lymphocytes, as determined by single-nucleus RNA sequencing and high-dimensional leukocyte profiling. Such tumors failed to respond to programmed cell death-1 (PD-1) blockade, but reduced their growth on treatment with ER antagonists, as well as with anthracycline-based chemotherapy, which was not influenced by T-cell depletion. Moreover, B6BC-derived tumors reduced their growth on CD11b blockade, indicating tumor sustainment by myeloid cells. The immune environment and treatment responses recapitulated by B6BC-derived tumors diverged from those of ER+ TS/A cell-derived tumors in BALB/C mice, and of ER- E0771 cell-derived and MPA/DMBA-induced tumors in C57BL/6 mice. CONCLUSIONS: B6BC is the first transplantable HR+ BC cell line derived from C57BL/6 mice and B6BC-derived tumors recapitulate the complex tumor microenvironment of locally advanced HR+ BC naturally resistant to PD-1 immunotherapy.

Modeling signaling pathways in biology with MaBoSS: From one single cell to a dynamic population of heterogeneous interacting cells.

As a result of the development of experimental technologies and the accumulation of data, biological and molecular processes can be described as complex networks of signaling pathways. These networks are often directed and signed, where nodes represent entities (genes/proteins) and arrows interactions. They are translated into mathematical models by adding a dynamic layer onto them. Such mathematical models help to understand and interpret non-intuitive experimental observations and to anticipate the response to external interventions such as drug effects on phenotypes. Several frameworks for modeling signaling pathways exist. The choice of the appropriate framework is often driven by the experimental context. In this review, we present MaBoSS, a tool based on Boolean modeling using a continuous time approach, which predicts time-dependent probabilities of entities in different biological contexts. MaBoSS was initially built to model the intracellular signaling in non-interacting homogeneous cell populations. MaBoSS was then adapted to model heterogeneous cell populations (EnsembleMaBoSS) by considering families of models rather than a unique model. To account for more complex questions, MaBoSS was extended to simulate dynamical interacting populations (UPMaBoSS), with a precise spatial distribution (PhysiBoSS). To illustrate all these levels of description, we show how each of these tools can be used with a running example of a simple model of cell fate decisions. Finally, we present practical applications to cancer biology and studies of the immune response.

UPMaBoSS: A Novel Framework for Dynamic Cell Population Modeling.

Mathematical modeling aims at understanding the effects of biological perturbations, suggesting ways to intervene and to reestablish proper cell functioning in diseases such as cancer or in autoimmune disorders. This is a difficult task for obvious reasons: the level of details needed to describe the intra-cellular processes involved, the numerous interactions between cells and cell types, and the complex dynamical properties of such populations where cells die, divide and interact constantly, to cite a few. Another important difficulty comes from the spatial distribution of these cells, their diffusion and motility. All of these aspects cannot be easily resolved in a unique mathematical model or with a unique formalism. To cope with some of these issues, we introduce here a novel framework, UPMaBoSS (for Update Population MaBoSS), dedicated to modeling dynamic populations of interacting cells. We rely on the preexisting tool MaBoSS, which enables probabilistic simulations of cellular networks. A novel software layer is added to account for cell interactions and population dynamics, but without considering the spatial dimension. This modeling approach can be seen as an intermediate step towards more complex spatial descriptions. We illustrate our methodology by means of a case study dealing with TNF-induced cell death. Interestingly, the simulation of cell population dynamics with UPMaBoSS reveals a mechanism of resistance triggered by TNF treatment. Relatively easy to encode, UPMaBoSS simulations require only moderate computational power and execution time. To ease the reproduction of simulations, we provide several Jupyter notebooks that can be accessed within the CoLoMoTo Docker image, which contains all software and models used for this study.

WebMaBoSS: A Web Interface for Simulating Boolean Models Stochastically.

WebMaBoSS is an easy-to-use web interface for conversion, storage, simulation and analysis of Boolean models that allows to get insight from these models without any specific knowledge of modeling or coding. It relies on an existing software, MaBoSS, which simulates Boolean models using a stochastic approach: it applies continuous time Markov processes over the Boolean network. It was initially built to fill the gap between Boolean and continuous formalisms, i.e., providing semi-quantitative results using a simple representation with a minimum number of parameters to fit. The goal of WebMaBoSS is to simplify the use and the analysis of Boolean models coping with two main issues: 1) the simulation of Boolean models of intracellular processes with MaBoSS, or any modeling tool, may appear as non-intuitive for non-experts; 2) the simulation of already-published models available in current model databases (e.g., Cell Collective, BioModels) may require some extra steps to ensure compatibility with modeling tools such as MaBoSS. With WebMaBoSS, new models can be created or imported directly from existing databases. They can then be simulated, modified and stored in personal folders. Model simulations are performed easily, results visualized interactively, and figures can be exported in a preferred format. Extensive model analyses such as mutant screening or parameter sensitivity can also be performed. For all these tasks, results are stored and can be subsequently filtered to look for specific outputs. This web interface can be accessed at the address: https://maboss.curie.fr/webmaboss/ and deployed locally using docker. This application is open-source under LGPL license, and available at https://github.com/sysbio-curie/WebMaBoSS.

Paradoxical implication of BAX/BAK in the persistence of tetraploid cells.

Pro-apoptotic multi-domain proteins of the BCL2 family such as BAX and BAK are well known for their important role in the induction of mitochondrial outer membrane permeabilization (MOMP), which is the rate-limiting step of the intrinsic pathway of apoptosis. Human or mouse cells lacking both BAX and BAK (due to a double knockout, DKO) are notoriously resistant to MOMP and cell death induction. Here we report the surprising finding that BAX/BAK DKO cells proliferate less than control cells expressing both BAX and BAK (or either BAX or BAK) when they are driven into tetraploidy by transient exposure to the microtubule inhibitor nocodazole. Mechanistically, in contrast to their BAX/BAK-sufficient controls, tetraploid DKO cells activate a senescent program, as indicated by the overexpression of several cyclin-dependent kinase inhibitors and the activation of ß-galactosidase. Moreover, DKO cells manifest alterations in ionomycin-mobilizable endoplasmic reticulum (ER) Ca2+ stores and store-operated Ca2+ entry that are affected by tetraploidization. DKO cells manifested reduced expression of endogenous sarcoplasmic/endoplasmic reticulum Ca2+ ATPase 2a (Serca2a) and transfection-enforced reintroduction of Serca2a, or reintroduction of an ER-targeted variant of BAK into DKO cells reestablished the same pattern of Ca2+ fluxes as observed in BAX/BAK-sufficient control cells. Serca2a reexpression and ER-targeted BAK also abolished the tetraploidy-induced senescence of DKO cells, placing ER Ca2+ fluxes downstream of the regulation of senescence by BAX/BAK. In conclusion, it appears that BAX/BAK prevent the induction of a tetraploidization-associated senescence program. Speculatively, this may contribute to the low incidence of cancers in BAX/BAK DKO mice and explain why human cancers rarely lose the expression of both BAX and BAK.

Metabolic features of cancer cells impact immunosurveillance.

BACKGROUND: Tumors rewire their metabolism to achieve robust anabolism and resistance against therapeutic interventions like cisplatin treatment. For example, a prolonged exposure to cisplatin causes downregulation of pyridoxal kinase (PDXK), the enzyme that generates the active vitamin B6, and upregulation of poly ADP-ribose (PAR) polymerase-1 (PARP1) activity that requires a supply of nicotinamide (vitamin B3) adenine dinucleotide. We investigated the impact of the levels of PDXK and PAR on the local immunosurveillance (ie, density of the antigen presenting cells and adaptive immune response by CD8 T lymphocytes) in two different tumor types. METHODS: Tumors from patients with locally advanced cervical carcinoma (LACC) and non-small cell lung cancer (NSCLC) were stained for PAR, PDXK, dendritic cell lysosomal associated membrane glycoprotein (DC-LAMP) and CD8 T cell infiltration. Their correlations and prognostic impact were assessed. Cisplatin-resistant NSCLC cell clones isolated from Lewis-lung cancer (LLC) cells were evaluated for PAR levels by immunoblot. Parental (PARlow) and cisplatin-resistant (PARhigh) clones were subcutaneously injected into the flank of C57BL/6 mice. Tumors were harvested to evaluate their immune infiltration by flow cytometry. RESULTS: The infiltration of tumors by CD8 T and DC-LAMP+ cells was associated with a favorable overall survival in patients with LACC (p=0.006 and p=0.008, respectively) and NSCLC (p<0.001 for both CD8 T and DC-LAMP cells). We observed a positive correlation between PDXK expression and the infiltration by DC-LAMP (R=0.44, p=0.02 in LACC, R=0.14, p=0.057 in NSCLC), and a negative correlation between PAR levels and CD8 T lymphocytes (R=-0.39, p=0.034 in LACC, R=-0.18, p=0.017 in NSCLC). PARP1 is constitutively hyperactivated in cisplatin-resistant LLC cells manifesting elevated intracellular levels of poly(ADP-ribosyl)ated proteins (PARhigh). Tumors formed by such cancer cells injected into immunocompetent mice were scarcely infiltrated by CD8 T (p=0.028) and antigen presenting cells (p=0.086). CONCLUSIONS: Oncometabolic features can impact local immunosurveillance, providing new functional links between cisplatin resistance and therapeutic failure.

Autoimmunity affecting the biliary tract fuels the immunosurveillance of cholangiocarcinoma.

Cholangiocarcinoma (CCA) results from the malignant transformation of cholangiocytes. Primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC) are chronic diseases in which cholangiocytes are primarily damaged. Although PSC is an inflammatory condition predisposing to CCA, CCA is almost never found in the autoimmune context of PBC. Here, we hypothesized that PBC might favor CCA immunosurveillance. In preclinical murine models of cholangitis challenged with syngeneic CCA, PBC (but not PSC) reduced the frequency of CCA development and delayed tumor growth kinetics. This PBC-related effect appeared specific to CCA as it was not observed against other cancers, including hepatocellular carcinoma. The protective effect of PBC was relying on type 1 and type 2 T cell responses and, to a lesser extent, on B cells. Single-cell TCR/RNA sequencing revealed the existence of TCR clonotypes shared between the liver and CCA tumor of a PBC host. Altogether, these results evidence a mechanistic overlapping between autoimmunity and cancer immunosurveillance in the biliary tract.

A TLR3 Ligand Reestablishes Chemotherapeutic Responses in the Context of FPR1 Deficiency.

For anthracycline-based chemotherapy to be immunogenic, dying cancer cells must release annexin A1 (ANXA1) that subsequently interacts with the pattern recognition receptor, formyl peptide receptor 1 (FPR1), on the surface of dendritic cells (DC). Approximately 30% of individuals bear loss-of-function alleles of FPR1, calling for strategies to ameliorate their anticancer immune response. Here, we show that immunotherapy with a ligand of Toll-like receptor-3, polyinosinic:polycytidylic acid (pIC), restores the deficient response to chemotherapy of tumors lacking ANXA1 developing in immunocompetent mice or those of normal cancers growing in FPR1-deficient mice. This effect was accompanied by improved DC- and T-lymphocyte-mediated anticancer immunity. Of note, carcinogen-induced breast cancers precociously developed in FPR1-deficient mice as compared with wild-type controls. A similar tendency for earlier cancer development was found in patients carrying the loss-of-function allele of FPR1. These findings have potential implications for the clinical management of FPR1-deficient patients. SIGNIFICANCE: The loss-of-function variant rs867228 in FPR1, harbored by approximately 30% of the world population, is associated with the precocious manifestation of breast, colorectal, esophageal, and head and neck carcinomas. pIC restores deficient chemotherapeutic responses in mice lacking Fpr1, suggesting a personalized strategy for compensating for the FPR1 defect.This article is highlighted in the In This Issue feature, p. 211.

Dynamical Boolean Modeling of Immunogenic Cell Death.

As opposed to the standard tolerogenic apoptosis, immunogenic cell death (ICD) constitutes a type of cellular demise that elicits an adaptive immune response. ICD has been characterized in malignant cells following cytotoxic interventions, such as chemotherapy or radiotherapy. Briefly, ICD of cancer cells releases some stress/danger signals that attract and activate dendritic cells (DCs). The latter can then engulf and cross-present tumor antigens to T lymphocytes, thus priming a cancer-specific immunity. This series of reactions works as a positive feedback loop where the antitumor immunity further improves the therapeutic efficacy by targeting cancer cells spared by the cytotoxic agent. However, not all chemotherapeutic drugs currently approved for cancer treatment are able to stimulate bona fide ICD: some commonly used agents, such as cisplatin or 5-fluorouracil, are unable to activate all features of ICD. Therefore, a better characterization of the process could help identify some gene or protein candidates to target pharmacologically and suggest combinations of drugs that would favor/increase antitumor immune response. To this end, we have built a mathematical model of the major cell types that intervene in ICD, namely cancer cells, DCs, CD8+ and CD4+ T cells. Our model not only integrates intracellular mechanisms within each individual cell entity, but also incorporates intercellular communications between them. The resulting cell population model recapitulates key features of the dynamics of ICD after an initial treatment, in particular the time-dependent size of the different cell types. The model is based on a discrete Boolean formalism and is simulated by means of a software tool, UPMaBoSS, which performs stochastic simulations with continuous time, considering the dynamics of the system at the cell population level with appropriate timing of events, and accounting for death and division of each cell type. With this model, the time scales of some of the processes involved in ICD, which are challenging to measure experimentally, have been predicted. In addition, our model analysis led to the identification of actionable targets for boosting ICD-induced antitumor response. All computational analyses and results are compiled in interactive notebooks which cover the presentation of the network structure, model simulations, and parameter sensitivity analyses.

Publisher Correction: Immunoprophylactic and immunotherapeutic control of hormone receptor-positive breast cancer.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Immunoprophylactic and immunotherapeutic control of hormone receptor-positive breast cancer.

Hormone receptor (HR)+ breast cancer (BC) causes most BC-related deaths, calling for improved therapeutic approaches. Despite expectations, immune checkpoint blockers (ICBs) are poorly active in patients with HR+ BC, in part reflecting the lack of preclinical models that recapitulate disease progression in immunocompetent hosts. We demonstrate that mammary tumors driven by medroxyprogesterone acetate (M) and 7,12-dimethylbenz[a]anthracene (D) recapitulate several key features of human luminal B HR+HER2- BC, including limited immune infiltration and poor sensitivity to ICBs. M/D-driven oncogenesis is accelerated by immune defects, demonstrating that M/D-driven tumors are under immunosurveillance. Safe nutritional measures including nicotinamide (NAM) supplementation efficiently delay M/D-driven oncogenesis by reactivating immunosurveillance. NAM also mediates immunotherapeutic effects against established M/D-driven and transplantable BC, largely reflecting increased type I interferon secretion by malignant cells and direct stimulation of immune effector cells. Our findings identify NAM as a potential strategy for the prevention and treatment of HR+ BC.

Contribution of annexin A1 to anticancer immunosurveillance.

Mouse cancers lacking the expression of annexin A1 (ANXA1) fail to respond to immunogenic chemotherapies. This has been initially explained by the requirement of extracellular ANXA1 (which is released from dying cancer cells) to engage formyl peptide receptor-1 (FPR1) on dendritic cells (DC) for the establishment of corpse/DC synapses. Here, we show that ANXA1-deficent cancer cells exhibit a defect in the exposure of calreticulin (CALR), which is an important "eat-me" signal, facilitating the phagocytic uptake of dead-cell antigens by DC. Of note, intratumoral injection of recombinant CALR protein was able to restore the therapeutic response of ANXA1-deficient cancers to anthracycline-based chemotherapy. Carcinomas developing in patients tend to downregulate ANXA1 expression as compared to their normal tissues of origin. ANXA1-low breast, colorectal, lung and kidney cancers are scarcely infiltrated by DC and cytotoxic T lymphocytes, supporting the idea that ANXA1 deficiency facilitates immune escape. We propose that such ANXA1-low cancers might be particularly suitable to local immunotherapy with CALR protein.