Germline variants in early and late-onset Brazilian prostate cancer patients.

BACKGROUND: The median age for Prostate Cancer (PCa) diagnosis is 66 years, but 10% are diagnosed before 55 years. Studies on early-onset PCa remain both limited and controversial. This investigation sought to identify and characterize germline variants within Brazilian PCa patients classified as either early or later onset disease. METHODS: Peripheral blood DNA from 71 PCa patients: 18 younger (≤ 55 years) and 53 older (≥ 60 years) was used for Targeted DNA sequencing of 20 genes linked to DNA damage response, transcriptional regulation, cell cycle, and epigenetic control. Subsequent genetic variant identification was performed and variant functional impacts were analyzed with in silico prediction. RESULTS: A higher frequency of variants in the BRCA2 and KMT2C genes across both age groups. KMT2C has been linked to the epigenetic dysregulation observed during disease progression in PCa. We present the first instance of KMT2C mutation within the blood of Brazilian PCa patients. Furthermore, out of the recognized variants within the KMT2C gene, 7 were designated as deleterious. Thirteen deleterious variants were exclusively detected in the younger group, while the older group exhibited 37 variants. Within these findings, 4 novel variants emerged, including 1 designated as pathogenic. CONCLUSIONS: Our findings contribute to a deeper understanding of the genetic factors associated with PCa susceptibility in different age groups, especially among the Brazilian population. This is the first investigation to explore germline variants specifically in younger Brazilian PCa patients, with high relevance given the genetic diversity of the population in Brazil. Additionally, our work presents evidence of functionally deleterious germline variants within the KMT2C gene among Brazilian PCa patients. The identification of novel and functionally significant variants in the KMT2C gene emphasizes its potential role in PCa development and warrants further investigation.

SARS-CoV-2 Infection Triggers Auto-Immune Response in ARDS.

Acute respiratory distress syndrome (ARDS) is a severe pulmonary disease, which is one of the major complications in COVID-19 patients. Dysregulation of the immune system and imbalances in cytokine release and immune cell activation are involved in SARS-CoV-2 infection. Here, the inflammatory, antigen, and auto-immune profile of patients presenting COVID-19-associated severe ARDS has been analyzed using functional proteomics approaches. Both, innate and humoral responses have been characterized through acute-phase protein network and auto-antibody signature. Severity and sepsis by SARS-CoV-2 emerged to be correlated with auto-immune profiles of patients and define their clinical progression, which could provide novel perspectives in therapeutics development and biomarkers of COVID-19 patients. Humoral response in COVID-19 patients' profile separates with significant differences patients with or without ARDS. Furthermore, we found that this profile can be correlated with COVID-19 severity and results more common in elderly patients.

Joining European Scientific Forces to Face Pandemics.

Despite the international guidelines on the containment of the coronavirus disease 2019 (COVID-19) pandemic, the European scientific community was not sufficiently prepared to coordinate scientific efforts. To improve preparedness for future pandemics, we have initiated a network of nine European-funded Cooperation in Science and Technology (COST) Actions that can help facilitate inter-, multi-, and trans-disciplinary communication and collaboration.

Exomes of Ductal Luminal Breast Cancer Patients from Southwest Colombia: Gene Mutational Profile and Related Expression Alterations.

Cancer is one of the leading causes of mortality worldwide. Breast cancer is the most frequent cancer in women, and in recent years it has become a serious public health problem in Colombia. The development of large-scale omic techniques allows simultaneous analysis of all active genes in tumor cells versus normal cells, providing new ways to discover the drivers of malignant transformations. Whole exome sequencing (WES) was obtained to provide a deep view of the mutational genomic profile in a set of cancer samples from Southwest Colombian women. WES was performed on 52 tumor samples from patients diagnosed with invasive breast cancer, which in most cases (33/52) were ductal luminal breast carcinomas (IDC-LM-BRCA). Global variant call was calculated, and six different algorithms were applied to filter out false positives and identify pathogenic variants. To compare and expand the somatic tumor variants found in the Colombian cohort, exome mutations and genome-wide expression alterations were detected in a larger set of tumor samples of the same breast cancer subtype from TCGA (that included DNA-seq and RNA-seq data). Genes with significant changes in both the mutational and expression profiles were identified, providing a set of genes and mutations associated with the etiology of ductal luminal breast cancer. This set included 19 single mutations identified as tumor driver mutations in 17 genes. Some of the genes (ATM, ERBB3, ESR1, TP53) are well-known cancer genes, while others (CBLB, PRPF8) presented driver mutations that had not been reported before. In the case of the CBLB gene, several mutations were identified in TCGA IDC-LM-BRCA samples associated with overexpression of this gene and repression of tumor suppressive activity of TGF-ß pathway.

Mining Drug-Target Associations in Cancer: Analysis of Gene Expression and Drug Activity Correlations.

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.

Deciphering Master Gene Regulators and Associated Networks of Human Mesenchymal Stromal Cells.

Mesenchymal Stromal Cells (MSC) are multipotent cells characterized by self-renewal, multilineage differentiation, and immunomodulatory properties. To obtain a gene regulatory profile of human MSCs, we generated a compendium of more than two hundred cell samples with genome-wide expression data, including a homogeneous set of 93 samples of five related primary cell types: bone marrow mesenchymal stem cells (BM-MSC), hematopoietic stem cells (HSC), lymphocytes (LYM), fibroblasts (FIB), and osteoblasts (OSTB). All these samples were integrated to generate a regulatory gene network using the algorithm ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks; based on mutual information), that finds regulons (groups of target genes regulated by transcription factors) and regulators (i.e., transcription factors, TFs). Furtherly, the algorithm VIPER (Algorithm for Virtual Inference of Protein-activity by Enriched Regulon analysis) was used to inference protein activity and to identify the most significant TF regulators, which control the expression profile of the studied cells. Applying these algorithms, a footprint of candidate master regulators of BM-MSCs was defined, including the genes EPAS1, NFE2L1, SNAI2, STAB2, TEAD1, and TULP3, that presented consistent upregulation and hypomethylation in BM-MSCs. These TFs regulate the activation of the genes in the bone marrow MSC lineage and are involved in development, morphogenesis, cell differentiation, regulation of cell adhesion, and cell structure.

Infectious stimuli promote malignant B-cell acute lymphoblastic leukemia in the absence of AID.

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.

Searching the overlap between network modules with specific betweeness (S2B) and its application to cross-disease analysis.

Discovering disease-associated genes (DG) is strategic for understanding pathological mechanisms. DGs form modules in protein interaction networks and diseases with common phenotypes share more DGs or have more closely interacting DGs. This prompted the development of Specific Betweenness (S2B) to find genes associated with two related diseases. S2B prioritizes genes frequently and specifically present in shortest paths linking two disease modules. Top S2B scores identified genes in the overlap of artificial network modules more than 80% of the times, even with incomplete or noisy knowledge. Applied to Amyotrophic Lateral Sclerosis and Spinal Muscular Atrophy, S2B candidates were enriched in biological processes previously associated with motor neuron degeneration. Some S2B candidates closely interacted in network cliques, suggesting common molecular mechanisms for the two diseases. S2B is a valuable tool for DG prediction, bringing new insights into pathological mechanisms. More generally, S2B can be applied to infer the overlap between other types of network modules, such as functional modules or context-specific subnetworks. An R package implementing S2B is publicly available at https://github.com/frpinto/S2B .

Loss of Pax5 Exploits Sca1-BCR-ABLp190 Susceptibility to Confer the Metabolic Shift Essential for pB-ALL.

Preleukemic clones carrying BCR-ABLp190 oncogenic lesions are found in neonatal cord blood, where the majority of preleukemic carriers do not convert into precursor B-cell acute lymphoblastic leukemia (pB-ALL). However, the critical question of how these preleukemic cells transform into pB-ALL remains undefined. Here, we model a BCR-ABLp190 preleukemic state and show that limiting BCR-ABLp190 expression to hematopoietic stem/progenitor cells (HS/PC) in mice (Sca1-BCR-ABLp190) causes pB-ALL at low penetrance, which resembles the human disease. pB-ALL blast cells were BCR-ABL-negative and transcriptionally similar to pro-B/pre-B cells, suggesting disease onset upon reduced Pax5 functionality. Consistent with this, double Sca1-BCR-ABLp190+Pax5+/- mice developed pB-ALL with shorter latencies, 90% incidence, and accumulation of genomic alterations in the remaining wild-type Pax5 allele. Mechanistically, the Pax5-deficient leukemic pro-B cells exhibited a metabolic switch toward increased glucose utilization and energy metabolism. Transcriptome analysis revealed that metabolic genes (IDH1, G6PC3, GAPDH, PGK1, MYC, ENO1, ACO1) were upregulated in Pax5-deficient leukemic cells, and a similar metabolic signature could be observed in human leukemia. Our studies unveil the first in vivo evidence that the combination between Sca1-BCR-ABLp190 and metabolic reprogramming imposed by reduced Pax5 expression is sufficient for pB-ALL development. These findings might help to prevent conversion of BCR-ABLp190 preleukemic cells.Significance: Loss of Pax5 drives metabolic reprogramming, which together with Sca1-restricted BCR-ABL expression enables leukemic transformation. Cancer Res; 78(10); 2669-79. ©2018 AACR.

Crebbp loss cooperates with Bcl2 overexpression to promote lymphoma in mice.

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.

Matrix-Gla protein promotes osteosarcoma lung metastasis and associates with poor prognosis.

Osteosarcoma (OS) is the most prevalent osseous tumour in children and adolescents and, within this, lung metastases remain one of the factors associated with a dismal prognosis. At present, the genetic determinants driving pulmonary metastasis are poorly understood. We adopted a novel strategy using robust filtering analysis of transcriptomic profiling in tumour osteoblastic cell populations derived from human chemo-naive primary tumours displaying extreme phenotypes (indolent versus metastatic) to uncover predictors associated with metastasis and poor survival. We identified MGP, encoding matrix-Gla protein (MGP), a non-collagenous matrix protein previously associated with the inhibition of arterial calcification. Using different orthotopic models, we found that ectopic expression of Mgp in murine and human OS cells led to a marked increase in lung metastasis. This effect was independent of the carboxylation of glutamic acid residues required for its physiological role. Abrogation of Mgp prevented lung metastatic activity, an effect that was rescued by forced expression. Mgp levels dramatically altered endothelial adhesion, trans-endothelial migration in vitro and tumour cell extravasation ability in vivo. Furthermore, Mgp modulated metalloproteinase activities and TGFß-induced Smad2/3 phosphorylation. In the clinical setting, OS patients who developed lung metastases had high serum levels of MGP at diagnosis. Thus, MGP represents a novel adverse prognostic factor and a potential therapeutic target in OS. Microarray datasets may be found at: http://bioinfow.dep.usal.es/osteosarcoma/ Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Infection Exposure is a Causal Factor in B-cell Precursor Acute Lymphoblastic Leukemia as a Result of Pax5-Inherited Susceptibility.

UNLABELLED: Earlier in the past century, infections were regarded as the most likely cause of childhood B-cell precursor acute lymphoblastic leukemia (pB-ALL). However, there is a lack of relevant biologic evidence supporting this hypothesis. We present in vivo genetic evidence mechanistically connecting inherited susceptibility to pB-ALL and postnatal infections by showing that pB-ALL was initiated in Pax5 heterozygous mice only when they were exposed to common pathogens. Strikingly, these murine pB-ALLs closely resemble the human disease. Tumor exome sequencing revealed activating somatic, nonsynonymous mutations of Jak3 as a second hit. Transplantation experiments and deep sequencing suggest that inactivating mutations in Pax5 promote leukemogenesis by creating an aberrant progenitor compartment that is susceptible to malignant transformation through accumulation of secondary Jak3 mutations. Thus, treatment of Pax5(+/-) leukemic cells with specific JAK1/3 inhibitors resulted in increased apoptosis. These results uncover the causal role of infection in pB-ALL development. SIGNIFICANCE: These results demonstrate that delayed infection exposure is a causal factor in pB-ALL. Therefore, these findings have critical implications for the understanding of the pathogenesis of leukemia and for the development of novel therapies for this disease.