Identificação de reguladores mestres em adenocarcinoma de pulmão e sua utilização para a prospecção de compostos antitumorais

O câncer de pulmão é uma das neoplasias malignas mais incidentes e letais da oncologia. Ademais, o adenocarcinoma pulmonar compreende o subtipo histológico mais comum e cuja frequência tem aumentado em detrimento de outros tipos nos últimos anos, especialmente em mulheres. Portanto, o entendimento da patofisiologia deste tipo de câncer e a busca por biomarcadores confiáveis, além de novas abordagens terapêuticas e regimes de tratamento, constituem áreas importantes de pesquisa e avanço biomédico. Nas últimas décadas, a Biologia de Sistemas coalesceu e fortaleceu-se com o advento de tecnologias ômicas e da bioinformática, viabilizando e impulsionando o estudo da biologia no contexto de sistemas complexos. Desta forma, este trabalho procura utilizar dados transcriptômicos e estratégias de bioinformática para obter fatores de transcrição candidatos a reguladores mestre do adenocarcinoma pulmonar, utilizado métodos, conceitos e visões oriundas da Biologia de Sistemas. Adicionalmente, desenvolvemos uma metodologia de reposicionamento computacional de drogas e aplicamos esta estratégia para obter drogas candidatas a elaboração de novos regimes terapêuticos. O primeiro passo do estudo foi a reconstrução de redes de co-expressão gênica centradas em fatores de transcrição e seus alvos utilizando informação de tecido não-tumoral, a fim de estabelecer redes de referência. Posteriormente, os grupos de genes constituídos pelos fatores de transcrição e seus alvos, conjuntamente chamados de unidades regulatórias, foram investigados quanto a seus perfis de expressão diferencial utilizando estudos caso-controle. As unidades regulatórias dos fatores de transcrição enriquecidos de genes diferencialmente expressos em mais de 80% dos estudos caso-controle, para ambas as redes de referência, foram consideradas reguladores mestre candidatos da patologia. Esta estratégia resultou em nove fatores de transcrição – ATOH8, DACH1, EPAS1, ETV5, FOXA2, FOXM1, HOXA4, SMAD6 e UHRF1. Em seguida, testamos se os estados de ativação inferidos para estes fatores de transcrição possuíam potencial prognóstico em diferentes coortes de adenocarcinoma, e observamos que três dos nove mostraram associações consistentes com o desfecho de pacientes. Finalmente, utilizamos as unidades regulatórias destes três fatores de transcrição – FOXA2, FOXM1 e UHRF1 – para prospectar drogas candidatas a reposicionamento, o que resultou em seis compostos potencialmente capazes de reverter os perfis transcricionais encontrados no contexto patológico. Estes compostos são: deptropina, promazina, ácido valproico, azaciclonol, metotrexato e composto ChemBridge ID 5109870. Avaliações dos potenciais terapêuticos destes fármacos e seus mecanismos de ação neste câncer podem auxiliar no desenvolvimento de novos tratamentos. Da mesma forma, elucidação dos papéis biológicos específicos dos nove reguladores mestres também tem grande potencial de contribuir para o entendimento da biologia do adenocarcinoma de pulmão.Lung cancer is one of the most common and lethal pathologies of medical oncology. Furthermore, adenocarcinoma comprises the most prevalent lung cancer histological subtype, which frequency increased over other types in recent years, especially among women. For these reasons, further understanding about the pathophysiology of this type of cancer and the search for reliable biomarkers, for new therapeutic drugs and for improved treatment strategies are all important areas of biomedical research and development. In recent decades, the Systems Biology paradigm emerged and strengthened due to novel omic technologies and bioinformatics, enabling and enhancing the study of biological phenomena in the context of complex systems. Thus, this study aims to search for the transcription factors acting as master regulators of lung adenocarcinoma using transcriptomics and employing Systems Biology concepts and views. Additionally, we developed a computational drug repositioning method and implemented it to retrieve candidate molecules for new treatment strategies. The first step in our study involved the reconstruction of co-expression gene networks centered in transcription factors and their targets using non-tumoral data in order to establish reference networks. Afterwards, the groups of genes comprising transcription factors and their targets, collectively called regulatory units, were queried for their differential expression profiles using case-control studies. Regulatory units of the transcription factors enriched with differentially expressed genes in over 80% of case-control studies, for both reference networks, were considered master regulator candidates of the disease. This strategy retrieved nine transcription factors - ATOH8, DACH1, EPAS1, ETV5, FOXA2, FOXM1, HOXA4, SMAD6 and UHRF1. Following that, we tested whether the inferred activities of these master regulators' regulatory units were associated with patient survival using several cohorts datasets, which highlighted three of them consistently associated with patient outcome. Finally, the regulatory units of these three transcription factors - FOXA2, FOXM1 e UHRF1 - were used to query drug candidates for repositioning in lung adenocarcinoma, resulting in six molecules capable to revert disease's the transcriptional profile. These drugs were deptropine, promazine, valproic acid, azacyclonol, methotrexate and ChemBridge ID compound 5109870. The evaluation of their therapeutic potentials and mechanisms of action in lung cancer may assist the development of new treatments. Additionally, further investigations of the retrieved master regulators' roles may lead to improvements in our understanding of adenocarcinoma pathophysiology

A comparative study of COVID-19 transcriptional signatures between clinical samples and preclinical cell models in the search for disease master regulators and drug repositioning candidates

Coronavirus disease 2019 (COVID-19) is an acute viral disease with millions of cases worldwide. Although the number of daily new cases and deaths has been dropping, there is still a need for therapeutic alternatives to deal with severe cases. A promising strategy to prospect new therapeutic candidates is to investigate the regulatory mechanisms involved in COVID-19 progression using integrated transcriptomics approaches. In this work, we aimed to identify COVID-19 Master Regulators (MRs) using a series of publicly available gene expression datasets of lung tissue from patients which developed the severe form of the disease. We were able to identify a set of six potential COVID-19 MRs related to its severe form, namely TAL1, TEAD4, EPAS1, ATOH8, ERG, and ARNTL2. In addition, using the Connectivity Map drug repositioning approach, we identified 52 different drugs which could be used to revert the disease signature, thus being candidates for the design of novel clinical treatments. Furthermore, we compared the identified signature and drugs with the ones obtained from the analysis of nasopharyngeal swab samples from infected patients and preclinical cell models. This comparison showed sig- nificant similarities between them, although also revealing some limitations on the overlap between clinical and preclinical data in COVID-19, highlighting the need for careful selection of the best model for each disease stage

Mortality of septic shock patients is associated with impaired mitochondrial oxidative coupling efficiency in lymphocytes : a prospective cohort study

Background: Septic shock is a life-threatening condition that challenges immune cells to reprogram their mitochondrial metabolism towards to increase ATP synthesis for building an appropriate immunity. This could print metabolic signatures in mitochondria whose association with disease progression and clinical outcomes remain elusive. Method: This is a single-center prospective cohort study performed in the ICU of one tertiary referral hospital in Brazil. Between November 2017 and July 2018, 90 consecutive patients, aged 18 years or older, admitted to the ICU with septic shock were enrolled. Seventy-five patients had Simplified Acute Physiology Score (SAPS 3) assessed at admission, and Sequential Organ Failure Assessment (SOFA) assessed on the first (D1) and third (D3) days after admission. Mitochondrial respiration linked to complexes I, II, V, and biochemical coupling efficiency (BCE) were assessed at D1 and D3 and Δ (D3–D1) in isolated lymphocytes. Clinical and mitochondrial endpoints were used to dichotomize the survival and death outcomes. Our primary outcome was 6-month mortality, and secondary outcomes were ICU and hospital ward mortality. Results: The mean SAPS 3 and SOFA scores at septic shock diagnosis were 75.8 (± 12.9) and 8 (± 3) points, respectively. The cumulative ICU, hospital ward, and 6-month mortality were 32 (45%), 43 (57%), and 50 (66%), respectively. At the ICU, non-surviving patients presented elevated arterial lactate (2.8 mmol/L, IQR, 2–4), C-reactive protein (220 mg/L, IQR, 119–284), and capillary refill time (5.5 s, IQR, 3–8). Respiratory rates linked to CII at D1 and D3, and ΔCII were decreased in non-surviving patients. Also, the BCE at D1 and D3 and the ΔBCE discriminated patients who would evolve to death in the ICU, hospital ward, and 6 months after admission. After adjusting for possible confounders, the ΔBCE value but not SOFA scores was independently associated with 6-month mortality (RR 0.38, CI 95% 0.18–0.78; P = 0.009). At a cut-off of − 0.002, ΔBCE displayed 100% sensitivity and 73% specificity for predicting 6-month mortality. Conclusions: The ΔBCE signature in lymphocytes provided an earlier recognition of septic shock patients in the ICU at risk of long-term deterioration of health status

Association of the fibronectin type III domain–containing protein 5 rs1746661 single nucleotide polymorphism with reduced brain glucose metabolism in elderly humans

Fibronectin type III domain–containing protein 5 (FNDC5) and its derived hormone, irisin, have been associated with metabolic control in humans, with described FNDC5 single nucleotide polymorphisms being linked to obesity and metabolic syndrome. Decreased brain FNDC5/irisin has been reported in subjects with dementia due to Alzheimer’s disease. Since impaired brain glucose metabolism develops in ageing and is prominent in Alzheimer’s disease, here, we examined associations of a single nucleotide polymorphism in the FNDC5 gene (rs1746661) with brain glucose metabolism and amyloid-β deposition in a cohort of 240 cognitively unimpaired and 485 cognitively impaired elderly individuals from the Alzheimer’s Disease Neuroimaging Initiative. In cognitively unimpaired elderly individuals harbouring the FNDC5 rs1746661(T) allele, we observed a regional reduction in low glucose metabolism in memory-linked brain regions and increased brain amyloid-β PET load. No differences in cognition or levels of cerebrospinal fluid amyloid-β42, phosphorylated tau and total tau were observed between FNDC5 rs1746661(T) allele carriers and non-carriers. Our results indicate that a genetic variant of FNDC5 is associated with low brain glucose metabolism in elderly individuals and suggest that FNDC5 may participate in the regulation of brain metabolism in brain regions vulnerable to Alzheimer’s disease pathophysiology. Understanding the associations between genetic variants in metabolism-linked genes and metabolic brain signatures may contribute to elucidating genetic modulators of brain metabolism in humans

Soluble amyloid-beta isoforms predict downstream Alzheimer’s disease pathology

Background: Changes in soluble amyloid-beta (Aβ) levels in cerebrospinal fluid (CSF) are detectable at early preclinical stages of Alzheimer’s disease (AD). However, whether Aβ levels can predict downstream AD pathological features in cognitively unimpaired (CU) individuals remains unclear. With this in mind, we aimed at investigating whether a combination of soluble Aβ isoforms can predict tau pathology (T+) and neurodegeneration (N+) positivity. Methods: We used CSF measurements of three soluble Aβ peptides (Aβ1–38, Aβ1–40 and Aβ1–42) in CU individuals (n = 318) as input features in machine learning (ML) models aiming at predicting T+ and N+. Input data was used for building 2046 tuned predictive ML models with a nested cross-validation technique. Additionally, proteomics data was employed to investigate the functional enrichment of biological processes altered in T+ and N+ individuals. Results: Our findings indicate that Aβ isoforms can predict T+ and N+ with an area under the curve (AUC) of 0.929 and 0.936, respectively. Additionally, proteomics analysis identified 17 differentially expressed proteins (DEPs) in individuals wrongly classified by our ML model. More specifically, enrichment analysis of gene ontology biological processes revealed an upregulation in myelinization and glucose metabolism-related processes in CU individuals wrongly predicted as T+. A significant enrichment of DEPs in pathways including biosynthesis of amino acids, glycolysis/gluconeogenesis, carbon metabolism, cell adhesion molecules and prion disease was also observed. Conclusions: Our results demonstrate that, by applying a refined ML analysis, a combination of Aβ isoforms can predict T+ and N+ with a high AUC. CSF proteomics analysis highlighted a promising group of proteins that can be further explored for improving T+ and N+ prediction

Lifelong exposure to a low-dose of the glyphosate-based herbicide RoundUp® causes intestinal damage, gut dysbiosis, and behavioral changes in mice

RoundUp® (RUp) is a comercial formulation containing glyphosate (N-(phosphono-methyl) glycine), and is the world’s leading wide-spectrum herbicide used in agriculture. Supporters of the broad use of glyphosate-based herbicides (GBH) claim they are innocuous to humans, since the active compound acts on the inhibition of enzymes which are absent in human cells. However, the neurotoxic effects of GBH have already been shown in many animal models. Further, these formulations were shown to disrupt the microbiome of different species. Here, we investigated the effects of a lifelong exposure to low doses of the GBH-RUp on the gut environment, including morphological and microbiome changes. We also aimed to determine whether exposure to GBH-RUp could harm the developing brain and lead to behavioral changes in adult mice. To this end, animals were exposed to GBH-RUp in drinking water from pregnancy to adulthood. GBH-RUp-exposed mice had no changes in cognitive function, but developed impaired social behavior and increased repetitive behavior. GBH-Rup-exposed mice also showed an activation of phagocytic cells (Iba-1–positive) in the cortical brain tissue. GBH-RUp exposure caused increased mucus production and the infiltration of plama cells (CD138-positive), with a reduction in phagocytic cells. Long-term exposure to GBH-RUp also induced changes in intestinal integrity, as demonstrated by the altered expression of tight junction effector proteins (ZO-1 and ZO-2) and a change in the distribution of syndecan-1 proteoglycan. The herbicide also led to changes in the gut microbiome composition, which is also crucial for the establishment of the intestinal barrier. Altogether, our findings suggest that long-term GBH-RUp exposure leads to morphological and functional changes in the gut, which correlate with behavioral changes that are similar to those observed in patients with neurodevelopmental disorders