The initial steps of B-cell acute lymphoblastic leukemia (B-ALL) development usually pass unnoticed in children. Several preclinical studies have shown that exposure to immune stressors triggers the transformation of preleukemic B cells to full-blown B-ALL, but how this takes place is still a longstanding and unsolved challenge. Here we show that dysregulation of innate immunity plays a driving role in the clonal evolution of pre-malignant Pax5+/- B-cell precursors toward leukemia. Transcriptional profiling reveals that Myd88 is downregulated in immune-stressed pre-malignant B-cell precursors and in leukemic cells. Genetic reduction of Myd88 expression leads to a significant increase in leukemia incidence in Pax5+/-Myd88+/- mice through an inflammation-dependent mechanism. Early induction of Myd88-independent Toll-like receptor 3 signaling results in a significant delay of leukemia development in Pax5+/- mice. Altogether, these findings identify a role for innate immunity dysregulation in leukemia, with important implications for understanding and therapeutic targeting of the preleukemic state in children.

T cells form immunological synapses with professional antigen-presenting cells (APCs) resulting in T cell activation and the acquisition of peptide antigen-MHC (pMHC) complexes from the plasma membrane of the APC. They thus become APCs themselves. We investigate the functional outcome of T-T cell antigen presentation by CD4 T cells and find that the antigen-presenting T cells (Tpres) predominantly differentiate into regulatory T cells (Treg), whereas T cells that have been stimulated by Tpres cells predominantly differentiate into Th17 pro-inflammatory cells. Using mice deficient in pMHC uptake by T cells, we show that T-T antigen presentation is important for the development of experimental autoimmune encephalitis and Th17 cell differentiation in vivo. By varying the professional APC:T cell ratio, we can modulate Treg versus Th17 differentiation in vitro and in vivo, suggesting that T-T antigen presentation underlies proinflammatory responses in conditions of antigen scarcity.

Preventing development of childhood B-cell acute lymphoblastic leukemia (B-ALL), a disease with devastating effects, is a longstanding and unsolved challenge. Heterozygous germline alterations in the PAX5 gene can lead to B-ALL upon accumulation of secondary mutations affecting the JAK/STAT signaling pathway. Preclinical studies have shown that this malignant transformation occurs only under immune stress such as exposure to infectious pathogens. Here we show in Pax5+/- mice that transient, early-life administration of clinically relevant doses of ruxolitinib, a JAK1/2 inhibitor, significantly mitigates the risk of B-ALL following exposure to infection; 1 of 29 animals treated with ruxolitinib developed B-ALL versus 8 of 34 untreated mice. Ruxolitinib treatment preferentially targeted Pax5+/- versus wild-type B-cell progenitors and exerted unique effects on the Pax5+/- B-cell progenitor transcriptional program. These findings provide the first in vivo evidence for a potential strategy to prevent B-ALL development.

APID (Agile Protein Interactomes DataServer) is an interactive web server that provides unified generation and delivery of protein interactomes mapped to their respective proteomes. This resource is a new, fully redesigned server that includes a comprehensive collection of protein interactomes for more than 400 organisms (25 of which include more than 500 interactions) produced by the integration of only experimentally validated protein-protein physical interactions. For each protein-protein interaction (PPI) the server includes currently reported information about its experimental validation to allow selection and filtering at different quality levels. As a whole, it provides easy access to the interactomes from specific species and includes a global uniform compendium of 90,379 distinct proteins and 678,441 singular interactions. APID integrates and unifies PPIs from major primary databases of molecular interactions, from other specific repositories and also from experimentally resolved 3D structures of protein complexes where more than two proteins were identified. For this purpose, a collection of 8,388 structures were analyzed to identify specific PPIs. APID also includes a new graph tool (based on Cytoscape.js) for visualization and interactive analyses of PPI networks. The server does not require registration and it is freely available for use at http://apid.dep.usal.es.

The impact of LMO2 expression on cell lineage decisions during T-cell leukemogenesis remains largely elusive. Using genetic lineage tracing, we have explored the potential of LMO2 in dictating a T-cell malignant phenotype. We first initiated LMO2 expression in hematopoietic stem/progenitor cells and maintained its expression in all hematopoietic cells. These mice develop exclusively aggressive human-like T-ALL In order to uncover a potential exclusive reprogramming effect of LMO2 in murine hematopoietic stem/progenitor cells, we next showed that transient LMO2 expression is sufficient for oncogenic function and induction of T-ALL The resulting T-ALLs lacked LMO2 and its target-gene expression, and histologically, transcriptionally, and genetically similar to human LMO2-driven T-ALL We next found that during T-ALL development, secondary genomic alterations take place within the thymus. However, the permissiveness for development of T-ALL seems to be associated with wider windows of differentiation than previously appreciated. Restricted Cre-mediated activation of Lmo2 at different stages of B-cell development induces systematically and unexpectedly T-ALL that closely resembled those of their natural counterparts. Together, these results provide a novel paradigm for the generation of tumor T cells through reprogramming in vivo and could be relevant to improve the response of T-ALL to current therapies.

The prerequisite to prevent childhood B-cell acute lymphoblastic leukemia (B-ALL) is to decipher its etiology. The current model suggests that infection triggers B-ALL development through induction of activation-induced cytidine deaminase (AID; also known as AICDA) in precursor B-cells. This evidence has been largely acquired through the use of ex vivo functional studies. However, whether this mechanism governs native non-transplant B-ALL development is unknown. Here we show that, surprisingly, AID genetic deletion does not affect B-ALL development in Pax5-haploinsufficient mice prone to B-ALL upon natural infection exposure. We next test the effect of premature AID expression from earliest pro-B-cell stages in B-cell transformation. The generation of AID off-target mutagenic activity in precursor B-cells does not promote B-ALL. Likewise, known drivers of human B-ALL are not preferentially targeted by AID. Overall these results suggest that infections promote B-ALL through AID-independent mechanisms, providing evidence for a new model of childhood B-ALL development.

Cancer is a complex disease affecting millions of people worldwide, with over a hundred clinically approved drugs available. In order to improve therapy, treatment, and response, it is essential to draw better maps of the targets of cancer drugs and possible side interactors. This study presents a large-scale screening method to find associations of cancer drugs with human genes. The analysis is focused on the current collection of Food and Drug Administration (FDA)-approved drugs (which includes about one hundred chemicals). The approach integrates global gene-expression transcriptomic profiles with drug-activity profiles of a set of 60 human cell lines obtained for a collection of chemical compounds (small bioactive molecules). Using a standardized expression for each gene versus standardized activity for each drug, Pearson and Spearman correlations were calculated for all possible pairwise gene-drug combinations. These correlations were used to build a global bipartite network that includes 1007 gene-drug significant associations. The data are integrated into an open web-tool called GEDA (Gene Expression and Drug Activity) which includes a relational view of cancer drugs and genes, disclosing the putative indirect interactions found for FDA-approved drugs as well as the known targets of these drugs. The results also provide insight into the complex action of pharmaceuticals, presenting an alternative view to address predicted pleiotropic effects of the drugs.

PAX5 is one of the most frequently mutated genes in B-cell acute lymphoblastic leukemia (B-ALL), and children with inherited preleukemic PAX5 mutations are at a higher risk of developing the disease. Abnormal profiles of inflammatory markers have been detected in neonatal blood spot samples of children who later developed B-ALL. However, how inflammatory signals contribute to B-ALL development is unclear. Here, we demonstrate that Pax5 heterozygosis, in the presence of infections, results in the enhanced production of the inflammatory cytokine interleukin-6 (IL-6), which appears to act in an autocrine fashion to promote leukemia growth. Furthermore, in vivo genetic downregulation of IL-6 in these Pax5 heterozygous mice retards B-cell leukemogenesis, and in vivo pharmacologic inhibition of IL-6 with a neutralizing antibody in Pax5 mutant mice with B-ALL clears leukemic cells. Additionally, this novel IL-6 signaling paradigm identified in mice was also substantiated in humans. Altogether, our studies establish aberrant IL6 expression caused by Pax5 loss as a hallmark of Pax5-dependent B-ALL and the IL6 as a therapeutic vulnerability for B-ALL characterized by PAX5 loss.

RNA-seq is currently considered the most powerful, robust and adaptable technique for measuring gene expression and transcription activation at genome-wide level. As the analysis of RNA-seq data is complex, it has prompted a large amount of research on algorithms and methods. This has resulted in a substantial increase in the number of options available at each step of the analysis. Consequently, there is no clear consensus about the most appropriate algorithms and pipelines that should be used to analyse RNA-seq data. In the present study, 192 pipelines using alternative methods were applied to 18 samples from two human cell lines and the performance of the results was evaluated. Raw gene expression signal was quantified by non-parametric statistics to measure precision and accuracy. Differential gene expression performance was estimated by testing 17 differential expression methods. The procedures were validated by qRT-PCR in the same samples. This study weighs up the advantages and disadvantages of the tested algorithms and pipelines providing a comprehensive guide to the different methods and procedures applied to the analysis of RNA-seq data, both for the quantification of the raw expression signal and for the differential gene expression.

An essential question in cancer is why individuals with the same disease have different clinical outcomes. Progress toward a more personalized medicine in cancer patients requires taking into account the underlying heterogeneity at different molecular levels.

Understanding the cellular origin of cancer can help to improve disease prevention and therapeutics. Human plasma cell neoplasias are thought to develop from either differentiated B cells or plasma cells. However, when the expression of Maf oncogenes (associated to human plasma cell neoplasias) is targeted to mouse B cells, the resulting animals fail to reproduce the human disease. Here, to explore early cellular changes that might take place in the development of plasma cell neoplasias, we engineered transgenic mice to express MafB in haematopoietic stem/progenitor cells (HS/PCs). Unexpectedly, we show that plasma cell neoplasias arise in the MafB-transgenic mice. Beyond their clinical resemblance to human disease, these neoplasias highly express genes that are known to be upregulated in human multiple myeloma. Moreover, gene expression profiling revealed that MafB-expressing HS/PCs were more similar to B cells and tumour plasma cells than to any other subset, including wild-type HS/PCs. Consistent with this, genome-scale DNA methylation profiling revealed that MafB imposes an epigenetic program in HS/PCs, and that this program is preserved in mature B cells of MafB-transgenic mice, demonstrating a novel molecular mechanism involved in tumour initiation. Our findings suggest that, mechanistically, the haematopoietic progenitor population can be the target for transformation in MafB-associated plasma cell neoplasias.

CREBBP is targeted by inactivating mutations in follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL). Here, we provide evidence from transgenic mouse models that Crebbp deletion results in deficits in B-cell development and can cooperate with Bcl2 overexpression to promote B-cell lymphoma. Through transcriptional and epigenetic profiling of these B cells, we found that Crebbp inactivation was associated with broad transcriptional alterations, but no changes in the patterns of histone acetylation at the proximal regulatory regions of these genes. However, B cells with Crebbp inactivation showed high expression of Myc and patterns of altered histone acetylation that were localized to intragenic regions, enriched for Myc DNA binding motifs, and showed Myc binding. Through the analysis of CREBBP mutations from a large cohort of primary human FL and DLBCL, we show a significant difference in the spectrum of CREBBP mutations in these 2 diseases, with higher frequencies of nonsense/frameshift mutations in DLBCL compared with FL. Together, our data therefore provide important links between Crebbp inactivation and Bcl2 dependence and show a role for Crebbp inactivation in the induction of Myc expression. We suggest this may parallel the role of CREBBP frameshift/nonsense mutations in DLBCL that result in loss of the protein, but may contrast the role of missense mutations in the lysine acetyltransferase domain that are more frequently observed in FL and yield an inactive protein.

The collection and integration of all the known protein-protein physical interactions within a proteome framework are critical to allow proper exploration of the protein interaction networks that drive biological processes in cells at molecular level. APID Interactomes is a public resource of biological data (http://apid.dep.usal.es) that provides a comprehensive and curated collection of `protein interactomes' for more than 1100 organisms, including 30 species with more than 500 interactions, derived from the integration of experimentally detected protein-to-protein physical interactions (PPIs). We have performed an update of APID database including a redefinition of several key properties of the PPIs to provide a more precise data integration and to avoid false duplicated records. This includes the unification of all the PPIs from five primary databases of molecular interactions (BioGRID, DIP, HPRD, IntAct and MINT), plus the information from two original systematic sources of human data and from experimentally resolved 3D structures (i.e. PDBs, Protein Data Bank files, where more than two distinct proteins have been identified). Thus, APID provides PPIs reported in published research articles (with traceable PMIDs) and detected by valid experimental interaction methods that give evidences about such protein interactions (following the `ontology and controlled vocabulary': www.ebi.ac.uk/ols/ontologies/mi; developed by `HUPO PSI-MI'). Within this data mining framework, all interaction detection methods have been grouped into two main types: (i) `binary' physical direct detection methods and (ii) `indirect' methods. As a result of these redefinitions, APID provides unified protein interactomes including the specific `experimental evidences' that support each PPI, indicating whether the interactions can be considered `binary' (i.e. supported by at least one binary detection method) or not.

Post-pregnancy breast cancer often carries a poor prognosis, posing a major clinical challenge. The increasing trend of later-life pregnancies exacerbates this risk, highlighting the need for effective chemoprevention strategies. Current options, limited to selective estrogen receptor modulators, aromatase inhibitors, or surgical procedures, offer limited efficacy and considerable side effects. Here, we report that cabergoline, a dopaminergic agonist, reduces the risk of breast cancer post-pregnancy in a Brca1/P53-deficient mouse model, with implications for human breast cancer prevention. We show that a single dose of cabergoline administered post-pregnancy significantly delayed the onset and reduced the incidence of breast cancer in Brca1/P53-deficient mice. Histological analysis revealed a notable acceleration in post-lactational involution over the short term, characterized by increased apoptosis and altered gene expression related to ion transport. Over the long term, histological changes in the mammary gland included a reduction in the ductal component, decreased epithelial proliferation, and a lower presence of recombinant Brca1/P53 target cells, which are precursors of tumors. These changes serve as indicators of reduced breast cancer susceptibility. Additionally, RNA sequencing identified gene expression alterations associated with decreased proliferation and mammary gland branching. Our findings highlight a mechanism wherein cabergoline enhances the protective effect of pregnancy against breast cancer by potentiating postlactational involution. Notably, a retrospective cohort study in women demonstrated a markedly lower incidence of post-pregnancy breast cancer in those treated with cabergoline compared to a control group. Our work underscores the importance of enhancing postlactational involution as a strategy for breast cancer prevention, and identifies cabergoline as a promising, low-risk option in breast cancer chemoprevention. This strategy has the potential to revolutionize breast cancer prevention approaches, particularly for women at increased risk due to genetic factors or delayed childbirth, and has wider implications beyond hereditary breast cancer cases.