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Coronary artery disease (CAD) is still a leading cause of death worldwide despite the extensive research and the considerable progresses made through the years. As other cardiovascular diseases, CAD is the result of the complex interaction between genetic variants and environmental factors. Currently identified genetic loci associated to CAD revealed the contribution of multiple molecular pathways to its pathogenesis, suggesting the need for a systemic approach to understand the role of genetic determinants. In this study we wanted to investigate how GWAS variants associated to CAD interact with each other and with nearby genes in the context of the coronary artery molecular interactome. GWAS variants associated to CAD were selected from GWAS Catalog, then, a tissue-specific interactome was constructed integrating protein-protein interactions (PPI) from multiple public repositories and computationally inferred co-expression relationships. To focus on the part of the network most relevant for CAD, we selected the interactions connecting the genes carrying a variant associated to the disease. A functional enrichment analysis conducted on the subnetwork revealed that genes carrying genetic variants associated to CAD closely interact with genes related to relevant biological processes, such as extracellular matrix organization, lipoprotein clearance, arterial morphology and inflammatory response. These results confirm that the identified subnetwork reflects the molecular pathways altered in CAD and intercepted by the selected variants. Interestingly, the most connected nodes of the network included amyloid beta precursor protein (APP) and huntingtin (HTT), both implicated in neurodegenerative disorders. In recent years the interest in investigating the common processes between cardiovascular diseases and neurodegenerative disorders is increasing, with growing evidence of a link between CAD and Alzheimer's disease. The results obtained in this work support the association between such apparently unrelated diseases and highlight the necessity of a systems biology approach to better elucidate shared pathological mechanisms.
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Aorta Torácica , Aneurisma da Aorta Torácica , Síndrome de Marfan , Músculo Liso Vascular , Miócitos de Músculo Liso , Proteômica , Síndrome de Marfan/metabolismo , Síndrome de Marfan/complicações , Síndrome de Marfan/diagnóstico , Síndrome de Marfan/genética , Aneurisma da Aorta Torácica/metabolismo , Aneurisma da Aorta Torácica/patologia , Miócitos de Músculo Liso/metabolismo , Miócitos de Músculo Liso/patologia , Humanos , Aorta Torácica/metabolismo , Aorta Torácica/patologia , Músculo Liso Vascular/metabolismo , Músculo Liso Vascular/patologia , Músculo Liso Vascular/efeitos dos fármacos , Células Cultivadas , AnimaisRESUMO
The transcription factors TTF1/NKX2-1 and ΔNp63/p40 are the counterposed molecular markers associated with the main Non-Small Cell Lung Cancer subtypes: TTF1 for adenocarcinoma, p40 for squamous cell carcinoma. Although they generally display a mutually exclusive expression, some exceptions exist simultaneously lacking or (very rarely) expressing both markers, either pattern being associated to poor prognosis. Hence, we quantitatively analyzed the relationship between their coordinated activity and prognosis. By analyzing the respective downstream transcriptional programs of the two genes, we defined a simple quantitative index summarizing the amount of mutual exclusivity between their activities, called Mean Absolute Activity (MAA). Systematic analysis of the MAA index in a dataset of 1018 NSCLC samples replicated on a validation dataset of 275 showed that the loss of imbalance between TTF-1 and p40 corresponds to a steady, progressive reduction in both overall and recurrence-free survival. Coherently, samples correspondent to more balanced activities were enriched for pathways related to increased malignancy and invasiveness. Importantly, multivariate analysis showed that the prognostic significance of the proposed index MAA is independent of other clinical variables including stage, sex, age and smoke exposure. These results hold irrespectively of tumor morphology across NSCLC subtypes, providing a unifying description of different expression patterns.
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Adenocarcinoma , Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Humanos , Carcinoma Pulmonar de Células não Pequenas/patologia , Neoplasias Pulmonares/patologia , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismo , Adenocarcinoma/patologia , Prognóstico , Biomarcadores Tumorais/metabolismo , Proteínas de Ligação a DNA/genéticaRESUMO
OBJECTIVES: Ki-67, a marker of cellular proliferation, is associated with prognosis across a wide range of tumours, including gastroenteropancreatic neuroendocrine neoplasms (NENs), lymphoma, urothelial tumours and breast carcinomas. Its omission from the classification system of pulmonary NENs is controversial. This systematic review sought to assess whether Ki-67 is a prognostic biomarker in lung NENs and, if feasible, proceed to a meta-analysis. RESEARCH DESIGN AND METHODS: Medline (Ovid), Embase, Scopus and the Cochrane library were searched for studies published prior to 28 February 2019 and investigating the role of Ki-67 in lung NENs. Eligible studies were those that included more than 20 patients and provided details of survival outcomes, namely, HRs with CIs according to Ki-67 percentage. Studies not available as a full text or without an English manuscript were excluded. This study was prospectively registered with PROSPERO. RESULTS: Of 11 814 records identified, seven studies met the inclusion criteria. These retrospective studies provided data for 1268 patients (693 TC, 281 AC, 94 large cell neuroendocrine carcinomas and 190 small cell lung carcinomas) and a meta-analysis was carried out to estimate a pooled effect. Random effects analyses demonstrated an association between a high Ki-67 index and poorer overall survival (HR of 2.02, 95% CI 1.16 to 3.52) and recurrence-free survival (HR 1.42; 95% CI 1.01 to 2.00). CONCLUSION: This meta-analysis provides evidence that high Ki-67 labelling indices are associated with poor clinical outcomes for patients diagnosed with pulmonary NENs. This study is subject to inherent limitations, but it does provide valuable insights regarding the use of the biomarker Ki-67, in a rare tumour. PROSPERO REGISTRATION NUMBER: CRD42018093389.
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Carcinoma Neuroendócrino , Neoplasias Pulmonares , Tumores Neuroendócrinos , Feminino , Humanos , Antígeno Ki-67 , Neoplasias Pulmonares/diagnóstico , Masculino , Prognóstico , Estudos RetrospectivosRESUMO
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent of the coronavirus disease 2019 (COVID-19) pandemic. Besides virus intrinsic characteristics, the host genetic makeup is predicted to account for the extreme clinical heterogeneity of the disease, which is characterized, among other manifestations, by a derangement of hemostasis associated with thromboembolic events. To date, large-scale studies confirmed that genetic predisposition plays a role in COVID-19 severity, pinpointing several susceptibility genes, often characterized by immunologic functions. With these premises, we performed an association study of common variants in 32 hemostatic genes with COVID-19 severity. We investigated 49,845 single-nucleotide polymorphism in a cohort of 332 Italian severe COVID-19 patients and 1668 controls from the general population. The study was conducted engaging a class of students attending the second year of the MEDTEC school (a six-year program, held in collaboration between Humanitas University and the Politecnico of Milan, allowing students to gain an MD in Medicine and a Bachelor's Degree in Biomedical Engineering). Thanks to their willingness to participate in the fight against the pandemic, we evidenced several suggestive hits (p < 0.001), involving the PROC, MTHFR, MTR, ADAMTS13, and THBS2 genes (top signal in PROC: chr2:127192625:G:A, OR = 2.23, 95%CI = 1.50-3.34, p = 8.77 × 10-5). The top signals in PROC, MTHFR, MTR, ADAMTS13 were instrumental for the construction of a polygenic risk score, whose distribution was significantly different between cases and controls (p = 1.62 × 10-8 for difference in median levels). Finally, a meta-analysis performed using data from the Regeneron database confirmed the contribution of the MTHFR variant chr1:11753033:G:A to the predisposition to severe COVID-19 (pooled OR = 1.21, 95%CI = 1.09-1.33, p = 4.34 × 10-14 in the weighted analysis).
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Introduction: Double occurrence of TTF1 and ΔNp63/p40 (henceforth, p40) within the same individual cells is exceedingly rare in lung cancer. Little is known on their biological and clinical implications. Methods: Two index cases immunoreactive for both p40 and TTF1 and nine tumors selected from The Cancer Genome Atlas (TCGA) according to the mRNA levels of the two relevant genes entered the study. Results: The two index cases were peripherally located, poorly differentiated, and behaviorally unfavorable carcinomas, which shared widespread p40 and TTF1 decoration within the same individual tumor cells. They also retained SMARCA2 and SMARCA4 expression, while variably stained for p53, cytokeratin 5, and programmed death-ligand 1. A subset of basal cells p40+/TTF1+ could be found in normal distal airways. Biphenotypic glandular and squamous differentiation was unveiled by electron microscopy, along with EGFR, RAD51B, CCND3, or NF1 mutations and IGF1R, MYC, CCND1, or CDK2 copy number variations on next-generation sequencing analysis. The nine tumors from TCGA (0.88% of 1018 tumors) shared the same poor prognosis, clinical presentation, and challenging histology and had activated pathways of enhanced angiogenesis and epithelial-mesenchymal transition. Mutation and copy number variation profiles did not differ from the other TCGA tumors. Conclusions: Double p40+/TTF1+ lung carcinomas are aggressive and likely underrecognized non-small cell carcinomas, whose origin could reside in double-positive distal airway stem-like basal cells through either de novo-basal-like or differentiating cell mechanisms according to a model of epithelial renewal.
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Lung neuroendocrine neoplasms (lung NENs) are categorised by morphology, defining a classification sometimes unable to reflect ultimate clinical outcome. Subjectivity and poor reproducibility characterise diagnosis and prognosis assessment of all NENs. Here, we propose a machine learning framework for tumour prognosis assessment based on a quantitative, automated and repeatable evaluation of the spatial distribution of cells immunohistochemically positive for the proliferation marker Ki-67, performed on the entire extent of high-resolution whole slide images. Combining features from the fields of graph theory, fractality analysis, stochastic geometry and information theory, we describe the topology of replicating cells and predict prognosis in a histology-independent way. We demonstrate how our approach outperforms the well-recognised prognostic role of Ki-67 Labelling Index on a multi-centre dataset comprising the most controversial lung NENs. Moreover, we show that our system identifies arrangement patterns in the cells positive for Ki-67 that appear independently of tumour subtyping. Strikingly, the subset of these features whose presence is also independent of the value of the Labelling Index and the density of Ki-67-positive cells prove to be especially relevant in discerning prognostic classes. These findings disclose a possible path for the future of grading and classification of NENs.
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Neuroendocrine neoplasms (NENs) of the lung encompass neuroendocrine tumors (NETs) composed of typical (TC) and atypical (AC) carcinoids and full-fledged carcinomas (NECs) inclusive of large cell neuroendocrine carcinoma (LCNEC) and small cell carcinoma (SCLC). NETs and NECs are thought to represent distinct and separate lesions with neither molecular overlap nor common developmental continuum. Two perspectives were addressed regarding the morphologic and molecular classification of lung NENs: (i) a supervised approach by browsing the traditional classification, the relevant gene alterations, and their clinical implications; and (ii) an unsupervised approach, by reappraising neoplasms according to risk factors and natural history of disease to construct an interpretation model relied on biological data. We herein emphasize lights and shadows of the current classification of lung NENs and provide an alternative outlook on these tumors focused on what we currently know about the biological determinants and the natural history of disease.
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Carcinoma Neuroendócrino/patologia , Neoplasias Pulmonares/patologia , Pulmão/patologia , Tumores Neuroendócrinos/patologia , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismo , Carcinoma Neuroendócrino/genética , Carcinoma Neuroendócrino/metabolismo , Humanos , Pulmão/metabolismo , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/metabolismo , Tumores Neuroendócrinos/genética , Tumores Neuroendócrinos/metabolismoRESUMO
INTRODUCTION: Neuroendocrine neoplasms of the lung (Lung NENs) encompass NE tumors (NETs), which are in turn split into typical and atypical carcinoids, and NE carcinomas (NECs), which group together small-cell carcinoma and large-cell NE carcinoma. This classification is the current basis for orienting the daily practice of these patients, with diagnostic, prognostic, and predictive inferences. AREAS COVERED: The clinical implications of lung NEN classification are addressed according to three converging perspectives, which were dissected through an extensive literature overview: (1) how to put intratumor heterogeneity into the context of the current classification; (2) how to contextualize immunohistochemistry markers to improve diagnosis, prognosis, and therapy prediction; and (3) how to use immuno-oncology strategies for life-threatening NECs, which still account for 90% or more of lung NENs. EXPERT OPINION: We provide practical insights to account for intratumor heterogeneity, practice the choice of immunohistochemistry markers, and emphasize once again the added value of immuno-oncology in the setting of personalized medicine of lung NENs.
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Carcinoma Neuroendócrino/classificação , Neoplasias Pulmonares/classificação , Tumores Neuroendócrinos/classificação , Animais , Tumor Carcinoide/classificação , Tumor Carcinoide/patologia , Tumor Carcinoide/terapia , Carcinoma Neuroendócrino/patologia , Carcinoma Neuroendócrino/terapia , Carcinoma de Células Pequenas/classificação , Carcinoma de Células Pequenas/patologia , Carcinoma de Células Pequenas/terapia , Humanos , Imuno-Histoquímica , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/terapia , Tumores Neuroendócrinos/patologia , Tumores Neuroendócrinos/terapia , Medicina de Precisão , PrognósticoRESUMO
All-trans retinoic acid (ATRA), a recognized differentiating agent, has significant potential in the personalized/stratified treatment of breast cancer. The present study reports on the molecular mechanisms underlying the anti-tumor activity of ATRA in breast cancer. The work is based on transcriptomic experiments performed on ATRA-treated breast cancer cell-lines, short-term tissue cultures of patient-derived mammary-tumors and a xenograft model. ATRA upregulates gene networks involved in interferon-responses, immune-modulation and antigen-presentation in retinoid-sensitive cells and tumors characterized by poor immunogenicity. ATRA-dependent upregulation of these gene networks is caused by a viral mimicry process, involving the activation of endogenous retroviruses. ATRA induces a non-canonical type of viral mimicry, which results in increased expression of the IRF1 (Interferon Responsive Factor 1) transcription factor and the DTX3L (Deltex-E3-Ubiquitin-Ligase-3L) downstream effector. Functional knockdown studies indicate that IRF1 and DTX3L are part of a negative feedback loop controlling ATRA-dependent growth inhibition of breast cancer cells. The study is of relevance from a clinical/therapeutic perspective. In fact, ATRA stimulates processes controlling the sensitivity to immuno-modulatory drugs, such as immune-checkpoint-inhibitors. This suggests that ATRA and immunotherapeutic agents represent rational combinations for the personalized treatment of breast cancer. Remarkably, ATRA-sensitivity seems to be relatively high in immune-cold mammary tumors, which are generally resistant to immunotherapy.
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BACKGROUND: The genetic bases of many complex phenotypes are still largely unknown, mostly due to the polygenic nature of the traits and the small effect of each associated mutation. An alternative approach to classic association studies to determining such genetic bases is an evolutionary framework. As sites targeted by natural selection are likely to harbor important functionalities for the carrier, the identification of selection signatures in the genome has the potential to unveil the genetic mechanisms underpinning human phenotypes. Popular methods of detecting such signals rely on compressing genomic information into summary statistics, resulting in the loss of information. Furthermore, few methods are able to quantify the strength of selection. Here we explored the use of deep learning in evolutionary biology and implemented a program, called ImaGene, to apply convolutional neural networks on population genomic data for the detection and quantification of natural selection. RESULTS: ImaGene enables genomic information from multiple individuals to be represented as abstract images. Each image is created by stacking aligned genomic data and encoding distinct alleles into separate colors. To detect and quantify signatures of positive selection, ImaGene implements a convolutional neural network which is trained using simulations. We show how the method implemented in ImaGene can be affected by data manipulation and learning strategies. In particular, we show how sorting images by row and column leads to accurate predictions. We also demonstrate how the misspecification of the correct demographic model for producing training data can influence the quantification of positive selection. We finally illustrate an approach to estimate the selection coefficient, a continuous variable, using multiclass classification techniques. CONCLUSIONS: While the use of deep learning in evolutionary genomics is in its infancy, here we demonstrated its potential to detect informative patterns from large-scale genomic data. We implemented methods to process genomic data for deep learning in a user-friendly program called ImaGene. The joint inference of the evolutionary history of mutations and their functional impact will facilitate mapping studies and provide novel insights into the molecular mechanisms associated with human phenotypes.
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Bases de Dados Genéticas , Genômica/métodos , Redes Neurais de Computação , Seleção Genética , Software , Algoritmos , Alelos , Genética Populacional , Humanos , FenótipoAssuntos
Proteínas Estimuladoras de Ligação a CCAAT/genética , Inversão Cromossômica , Leucemia Mieloide Aguda/tratamento farmacológico , Leucemia Mieloide Aguda/genética , Mutação , Translocação Genética , Tretinoína/farmacologia , Antineoplásicos/uso terapêutico , Biomarcadores Tumorais/genética , Árvores de Decisões , Perfilação da Expressão Gênica , Regulação Leucêmica da Expressão Gênica , Humanos , Medicina de Precisão , Valor Preditivo dos Testes , Prognóstico , Resultado do TratamentoRESUMO
High-grade serous epithelial ovarian cancer (HGS-EOC) is a systemic disease, with marked intra and interpatient tumor heterogeneity. The issue of spatial and temporal heterogeneity has long been overlooked, hampering the possibility to identify those genomic alterations that persist, before and after therapy, in the genome of all tumor cells across the different anatomical districts. This knowledge is the first step to clarify those molecular determinants that characterize the tumor biology of HGS-EOC and their route toward malignancy. In our study, -omics data were generated from 79 snap frozen matched tumor biopsies, withdrawn before and after chemotherapy from 24 HGS-EOC patients, gathered together from independent cohorts. The landscape of somatic copy number alterations depicts a more homogenous and stable genomic portrait than the single nucleotide variant profile. Genomic identification of significant targets in cancer analysis identified two focal and minimal common regions (FMCRs) of amplification in the cytoband 3q26.2 (region α, 193 kb long) and 8q24.3 (region ß, 495 kb long). Analysis in two external databases confirmed regions α and ß are features of HGS-EOC. The MECOM gene is located in region α, and 15 genes are in region ß. No functional data are yet available for the genes in the ß region. In conclusion, we have identified for the first time two FMCRs of amplification in HGS-EOC, opening up a potential biological role in its etiopathogenesis.
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Carcinoma Epitelial do Ovário/genética , Cromossomos Humanos Par 3/genética , Cromossomos Humanos Par 8/genética , Variações do Número de Cópias de DNA , Neoplasias Ovarianas/genética , Biópsia , Carcinoma Epitelial do Ovário/patologia , Estudos de Coortes , Biologia Computacional , Bases de Dados Genéticas , Conjuntos de Dados como Assunto , Feminino , Genômica , Humanos , Gradação de Tumores , Neoplasias Ovarianas/patologia , Ovário/patologia , Sequenciamento do ExomaRESUMO
INTRODUCTION: Neuroendocrine tumors of the lung (Lung-NETs) make up a heterogenous family of neoplasms showing neuroendocrine differentiation and encompass carcinoids and neuroendocrine carcinomas. On molecular grounds, they considered two completely distinct and separate tumor groups with no overlap of molecular alterations nor common developmental mechanisms. Areas covered: Two perspectives were evaluated based on an extensive review and rethinking of literature: (1) the current classification as an instrument to obtaining clinical and molecular insights into the context of Lung-NETs; and (2) an alternative and innovative interpretation of these tumors, proposing a tripartite separation into early aggressive primary high-grade neuroendocrine tumors (HGNET), differentiating or secondary HGNET, and indolent NET. Expert opinion: We herein provide an alternative outlook on Lung-NETs, which is a paradigm shift to current pathogenesis models and expands the understanding of these tumors.
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Carcinoma/genética , Variações do Número de Cópias de DNA/genética , Neoplasias Pulmonares/genética , Tumores Neuroendócrinos/genética , Carcinoma/patologia , Humanos , Antígeno Ki-67/genética , Pulmão/patologia , Neoplasias Pulmonares/patologia , Mutação/genética , Gradação de Tumores , Tumores Neuroendócrinos/patologiaRESUMO
In chronic lymphocytic leukemia (CLL), the non-hematopoietic stromal microenvironment plays a critical role in promoting tumor cell recruitment, activation, survival, and expansion. However, the nature of the stromal cells and molecular pathways involved remain largely unknown. Here, we demonstrate that leukemic B lymphocytes induce the activation of retinoid acid synthesis and signaling in the microenvironment. Inhibition of RA-signaling in stromal cells causes deregulation of genes associated with adhesion, tissue organization and chemokine secretion including the B-cell chemokine CXCL13. Notably, reducing retinoic acid precursors from the diet or inhibiting RA-signaling through retinoid-antagonist therapy prolong survival by preventing dissemination of leukemia cells into lymphoid tissues. Furthermore, mouse and human leukemia cells could be distinguished from normal B-cells by their increased expression of Rarγ2 and RXRα, respectively. These findings establish a role for retinoids in murine CLL pathogenesis, and provide new therapeutic strategies to target the microenvironment and to control disease progression.
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Leucemia Linfocítica Crônica de Células B/patologia , Células Estromais/patologia , Tretinoína/fisiologia , Animais , Linhagem Celular , Quimiocina CXCL13/metabolismo , Técnicas de Cocultura , Progressão da Doença , Feminino , Regulação Neoplásica da Expressão Gênica , Leucemia Linfocítica Crônica de Células B/metabolismo , Masculino , Camundongos Endogâmicos C57BL , Transdução de Sinais , Análise de Sobrevida , Tretinoína/metabolismo , Microambiente TumoralRESUMO
Elucidating the molecular basis of tumor metastasis is pivotal for eradicating cancer-related mortality. Triple-negative breast cancer (TNBC) encompasses a class of aggressive tumors characterized by high rates of recurrence and metastasis, as well as poor overall survival. Here, we find that the promyelocytic leukemia protein PML exerts a prometastatic function in TNBC that can be targeted by arsenic trioxide. We found that, in TNBC patients, constitutive HIF1A activity induces high expression of PML, along with a number of HIF1A target genes that promote metastasis at multiple levels. Intriguingly, PML controls the expression of these genes by binding to their regulatory regions along with HIF1A. This mechanism is specific to TNBC cells and does not occur in other subtypes of breast cancer where PML and prometastatic HIF1A target genes are underexpressed. As a consequence, PML promotes cell migration, invasion, and metastasis in TNBC cell and mouse models. Notably, pharmacological inhibition of PML with arsenic trioxide, a PML-degrading agent used to treat promyelocytic leukemia patients, delays tumor growth, impairs TNBC metastasis, and cooperates with chemotherapy by preventing metastatic dissemination. In conclusion, we report identification of a prometastatic pathway in TNBC and suggest clinical development toward the use of arsenic trioxide for TNBC patients.
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Regulação Neoplásica da Expressão Gênica , Subunidade alfa do Fator 1 Induzível por Hipóxia/genética , Proteína da Leucemia Promielocítica/genética , Neoplasias de Mama Triplo Negativas/genética , Animais , Linhagem Celular Tumoral , Movimento Celular , Células HEK293 , Humanos , Subunidade alfa do Fator 1 Induzível por Hipóxia/metabolismo , Células MCF-7 , Camundongos , Camundongos Endogâmicos NOD , Camundongos SCID , Células NIH 3T3 , Invasividade Neoplásica , Metástase Neoplásica , Transplante de Neoplasias , Proteína da Leucemia Promielocítica/metabolismo , Neoplasias de Mama Triplo Negativas/metabolismo , Neoplasias de Mama Triplo Negativas/patologiaRESUMO
BACKGROUND: Pathological grading of tumors is a way to measure biological aggressiveness. In lung neuroendocrine tumors (NET), grading is tautologically included into the current 2015 WHO histologic classification. Little is known, however, about alternative grading systems in lung NET. METHODS: Through an extensive search of the English literature on lung NET (updated to April 2016), the following key questions were addressed: a) current concepts of grading; b) clinicians' requests for grading; c) functional parameters for grading; d) Ki-67 labeling index (LI) for grading; e) towards an effective pathology grading system. RESULTS: There is some room for inconsistency in the histologic classification of lung NET, likely due to the varying attribution of defining criteria. Innovative diffusion-weighted imaging upon magnetic resonance or molecular analysis could help separate indolent from aggressive lung NET, thus integrating a grading approach other than histology. Troubles in the clinical handling of metastatic or individual tumors when relying on morphology alone support the development of a lung-specific grading system for the more accurate prediction of prognosis and planning therapy in individual patients. To integrate the 2015 WHO classification using innovative grading based on Ki-67 LI, mitotic count and necrosis, a new proposal is emerging where three categories of lung NET are identified, namely Lu-NET G1, Lu-NET G2 and Lu-NET G3, which would allow tumors with similar behavior and therapy to be better handled according to their own biological potential. CONCLUSION: This new formulation of lung NET grading could have clinical relevance for the individual handling of patients.
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Neoplasias Pulmonares/patologia , Gradação de Tumores/métodos , Tumores Neuroendócrinos/patologia , Humanos , Neoplasias Pulmonares/diagnóstico , Tumores Neuroendócrinos/diagnósticoRESUMO
Hypoxia inducible transcription factors (HIFs) are the main regulators of adaptive responses to hypoxia and are often activated in solid tumors, but their role in leukemia is less clear. In acute myeloid leukemia (AML), in particular, controversial new findings indicate that HIF-1α can act either as an oncogene or a tumor suppressor gene, and this may depend on the stage of leukemia development and/or the AML sub-type.In this study, we find that HIF-1α promotes leukemia progression in the acute monocytic leukemia sub-type of AML through activation of an invasive phenotype. By applying a list of validated HIF-1α-target genes to different AML sub-types, we identified a HIF-1α signature that typifies acute monocytic leukemia when compared with all other AML sub-types. We validated expression of this signature in cell lines and primary cells from AML patients. Interestingly, this signature is enriched for genes that control cell motility at different levels. As a consequence, inhibiting HIF-1α impaired leukemia cell migration, chemotaxis, invasion and transendothelial migration in vitro, and this resulted in impaired bone marrow homing and leukemia progression in vivo. Our data suggest that in acute monocytic leukemia an active HIF-1α-dependent pro-invasive pathway mediates the ability of leukemic cells to migrate and invade extramedullary sites and may be targeted to reduce leukemia dissemination.
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Subunidade alfa do Fator 1 Induzível por Hipóxia/metabolismo , Leucemia Monocítica Aguda/patologia , Animais , Linhagem Celular Tumoral , Movimento Celular/fisiologia , Progressão da Doença , Xenoenxertos , Humanos , Leucemia Monocítica Aguda/metabolismo , Camundongos , FenótipoRESUMO
Common variants in the UMOD gene encoding uromodulin, associated with risk of hypertension and CKD in the general population, increase UMOD expression and urinary excretion of uromodulin, causing salt-sensitive hypertension and renal lesions. To determine the effect of selective pressure on variant frequency, we investigated the allelic frequency of the lead UMOD variant rs4293393 in 156 human populations, in eight ancient human genomes, and in primate genomes. The T allele of rs4293393, associated with CKD risk, has high frequency in most modern populations and was the one detected in primate genomes. In contrast, we identified only the derived, C allele in Denisovan and Neanderthal genomes. The distribution of the UMOD ancestral allele did not follow the ancestral susceptibility model observed for variants associated with salt-sensitive hypertension. Instead, the global frequencies of the UMOD alleles significantly correlated with pathogen diversity (bacteria, helminths) and prevalence of antibiotic-resistant urinary tract infections (UTIs). The inverse correlation found between urinary levels of uromodulin and markers of UTIs in the general population substantiates the link between UMOD variants and protection against UTIs. These data strongly suggest that the UMOD ancestral allele, driving higher urinary excretion of uromodulin, has been kept at a high frequency because of its protective effect against UTIs.